Quantitative Deep Value Investing

(Image:  Zen Buddha Silence by Marilyn Barbone.)

October 14, 2018

Virtually all of the historical evidence shows that quantitative deep value investing—systematically buying stocks at low multiples (low P/B, P/E, P/S, P/CF, and EV/EBITDA)—does better than the market over time.

Deep value investing means investing in ugly stocks that are doing terribly—with low- or no-growth—and that are trading at low multiples.  Quantitative deep value investing means that the portfolio of deep value stocks is systematically constructed based solely on quantitative factors including cheapness.  (It’s a process that can easily be automated.)

One of the best papers on quantitative deep value investing is by Josef Lakonishok, Andrei Shleifer, and Robert Vishny (1994), “Contrarian Investment, Extrapolation, and Risk.”  Link: http://scholar.harvard.edu/files/shleifer/files/contrarianinvestment.pdf

Buffett has called deep value investing the cigar butt approach:

…You walk down the street and you look around for a cigar butt someplace.  Finally you see one and it is soggy and kind of repulsive, but there is one puff left in it.  So you pick it up and the puff is free—it is a cigar butt stock.  You get one free puff on it and then you throw it away and try another one.  It is not elegant.  But it works.  Those are low return businesses.

(Photo by Sensay)

Outline for this blog post:

  • Rare Temperament
  • Early Buffett: Deep Value Investor
  • Investors Much Prefer Income Over Assets
  • Companies at Cyclical Lows

 

RARE TEMPERAMENT

Many value investors prefer to invest in higher-quality companies rather than deep value stocks.  A high-quality company has a sustainable competitive advantage that allows it to earn a high ROIC (return on invested capital) for a long time.  When you invest in such a company, you can simply hold the position for years as it compounds intrinsic value.  Assuming you’ve done your homework and gotten the initial buy decision right, you typically don’t have to worry much.

Investing in cigar butts (deep value stocks), however, means that you’re investing in many mediocre or bad businesses.  These are companies that have terrible recent performance.  Some of these businesses won’t survive over the longer term, although even the non-survivors often survive many years longer than is commonly supposed.

Deep value investing can work quite well, but it takes a certain temperament not to care about various forms of suffering—such as being isolated and looking foolish.  As Bryan Jacoboski puts it:

The very reason price and value diverge in predictable and exploitable ways is because people are emotional beings.  That’s why the distinguishing attribute among successful investors is temperament rather than brainpower, experience, or classroom training.  They have the ability to be rational when others are not.

(Photo by Nikki Zalewski)

In The Manual of Ideas (Wiley, 2013), John Mihaljevic explains the difficulty of deep value investing:

It turns out that Graham-style investing may be appropriate for a relatively small subset of the investment community, as it requires an unusual willingness to stand alone, persevere, and look foolish.

On more than one occasion, we have heard investors respond as follows to a deep value investment thesis: ‘The stock does look deeply undervalued, but I just can’t get comfortable with it.’  When pressed on the reasons for passing, many investors point to the uncertainty of the situation, the likelihood of negative news flow, or simply a bad gut feeling.  Most investors also find it less rewarding to communicate to their clients that they own a company that has been in the news for the wrong reasons.

Comfort can be expensive in investing.  Put differently, acceptance of discomfort can be rewarding, as equities that cause their owners discomfort frequently trade at exceptionally low valuations.

Many investors will look at a list of statistically cheap stocks and conclude that most of them would be awful investments.  But in practice, a basket of deep value stocks tends to outperform, given enough time.  And typically some of the big winners include stocks that looked the worst prior to being included in the portfolio.

 

EARLY BUFFETT: DEEP VALUE INVESTOR

Warren Buffett started out as a cigar-butt investor.  That was the method he learned from his teacher and mentor, Ben Graham, the father of value investing.  When Buffett ran his partnership, he generated exceptional performance using a deep value strategy focused on microcap stocks: http://boolefund.com/buffetts-best-microcap-cigar-butts/

(Early Buffett teaching at the University of Nebraska, via Wikimedia Commons)

One reason Buffett transitioned from deep value to buying high-quality companies (and holding them forever) was simply that the assets he was managing at Berkshire Hathaway became much too large for deep value.  But in his personal account, Buffett recently bought a basket of South Korean cigar butts and ended up doing very well.

Buffett has made it clear that if your assets under management are relatively small, then deep value investing—especially when focused on microcap stocks—can do better than investing in high-quality companies.  Buffett has said he could make 50% a year by investing in deep value microcap stocks: http://boolefund.com/buffetts-best-microcap-cigar-butts/

In the microcap world, since most professional investors don’t look there, if you turn over enough rocks you can find some exceptionally cheap companies.  If you don’t have sufficient time and interest to find the most attractive individual microcap stocks, using a quantitative approach is an excellent alternative.  A good quantitative value fund focused on microcaps is likely to do much better than the S&P 500 over time.  That’s the mission of the Boole Fund.

 

INVESTORS MUCH PREFER INCOME OVER ASSETS

Outside of markets, people naturally assess the value of possessions or private businesses in terms of net asset value—which typically corresponds with what a buyer would pay.  But in markets, when the current income of an asset-rich company is abnormally low, most investors fixate on the low income even when the best estimate of the company’s value is net asset value.  (Mihaljevic makes this point.)

If an investor is considering a franchise (high-quality) business like Coca-Cola or Johnson & Johnson, then it makes sense to focus on income, since most of the asset value involves intangible assets (brand value, etc).

But for many potential investments, net asset value is more important than current income.  Most investors ignore this fact and stay fixated on current income.  This is a major reason why stock prices occasionally fall far below net asset value, which creates opportunities for deep value investors.

(Illustration by Teguh Jati Prasetyo)

Over a long period of time, the income of most businesses does relate to net asset value.  Bruce Greenwald, in his book Value Investing (Wiley, 2004), explains the connection.  For most businesses, the best way to estimate intrinsic value is to estimate the reproduction cost of the assets.  And for most businesses—because of competition—earnings power over time will not be more than what is justified by the reproduction cost of the assets.

Only franchise businesses like Coca-Cola—with a sustainable competitive advantage that allows it to earn more than its cost of capital—are going to have normalized earnings that are higher than is justified by the reproduction cost of the assets.

Because most investors view cigar butts as unattractive investments—despite the overwhelming statistical evidence—there are always opportunities for deep value investors.  For instance, when cyclical businesses are at the bottom of the cycle, and current earnings are far below earnings power, investors’ fixation on current earnings can create very cheap stocks.

A key issue is whether the current low income reflects a permanently damaged business or a temporary—or cyclical—decline in profitability.

 

COMPANIES AT CYCLICAL LOWS

Although you can make money by buying cheap businesses that are permanently declining, you can usually make more money by buying stocks at cyclical lows.

(Illustration by Prairat Fhunta)

Mihaljevic:

Assuming a low enough entry price, money can be made in both cheap businesses condemned to permanent fundamental decline and businesses that may benefit from mean reversion as their industry moves through the cycle.  We much prefer companies that find themselves at a cyclical low, as they may restore much, if not all, of their earning power, providing multi-bagger upside potential.  Meanwhile, businesses likely to keep declining for a long time have to be extremely cheap and keep returning cash to shareholders to generate a positive investment outcome.

The question of whether a company has entered permanent decline is anything but easy to answer, as virtually all companies appear to be in permanent decline when they hit a rock-bottom market quotation.  Even if a business has been cyclical in the past, analysts generally adopt a ‘this time is different’ attitude.  As a pessimistic stock price inevitably influences the appraisal objectivity of most investors, it becomes exceedingly difficult to form a view strongly opposed to the prevailing consensus.

If you can stay calm and rational while being isolated and looking foolish, then you can buy deeply out of favor cyclical stocks, which often have multi-bagger upside potential.

Example: Ensco plc (ESV)

A good example of a cyclical stock with multi-bagger potential is Ensco plc, an offshore oil driller.  The Boole Microcap Fund had an investment in Atwood Oceanics, which was acquired by Ensco in 2017.  The Boole Fund continues to hold Ensco because it’s quite cheap.

Oil companies prefer offshore drillers that are well-capitalized and reliable.  Ensco has one of the best safety records in the industry.  Also, it was rated #1 in customer satisfaction for the eighth consecutive year in the leading independent industry survey.  Moreover, Ensco is one of the best capitalized drillers in the industry, with $2.9 billion in liquidity and only $236 million in debt due before 2024.

Here are intrinsic value scenarios:

  • Low case: If oil prices languish below $60 (WTI) for the next 3 to 5 years, then Ensco will be a survivor, due to its large fleet, globally diverse customer base, industry leading performance, and well-capitalized position.  In this scenario, Ensco is likely worth at least $13, about 50% higher than today’s $8.70.
  • Mid case: If oil prices are in a range of $65 to $85 over the next 3 to 5 years—which is likely based on long-term supply and demand—then Ensco is probably worth at least $26 a share, roughly 200% higher than today’s $8.70.
  • High case: If oil prices average $85 or more over the next 3 to 5 years, then Ensco could easily be worth $39 a share, close to 350% higher than today’s $8.70.

Last week, on October 8, Ensco plc and Rowan Companies plc announced that they were merging.  The merger is still subject to shareholder and regulatory approval.

The merger of Ensco and Rowan will likely be accretive to the current shareholders of Ensco.  Ensco and Rowan believe they will achieve cost savings of $150 million per year, which adds at least 5-10% of intrinsic value to Ensco shares.

You might wonder if Ensco is giving up something in the merger, given its ability to offer the highest specification drilling rigs—especially for ultra-deepwater.  However, Rowan’s groundbreaking partnership (ARO Drilling) with Saudi Aramco will likely create billions of dollars in value for shareholders.  Moreover, Rowan is a leading provider of ultra-harsh and modern harsh environment jackups.

In brief, the combination looks to be accretive for the shareholders of both companies.  Therefore, the potential upside for current Ensco shareholders is probably greater if the merger is completed.  So for the low, mid, and high cases, the potential upside for current Ensco shareholders is at least 50%, 200%, and 350%, respectively, and probably more.

 

BOOLE MICROCAP FUND

An equal weighted group of micro caps generally far outperforms an equal weighted (or cap-weighted) group of larger stocks over time.  See the historical chart here:  http://boolefund.com/best-performers-microcap-stocks/

This outperformance increases significantly by focusing on cheap micro caps.  Performance can be further boosted by isolating cheap microcap companies that show improving fundamentals.  We rank microcap stocks based on these and similar criteria.

There are roughly 10-20 positions in the portfolio.  The size of each position is determined by its rank.  Typically the largest position is 15-20% (at cost), while the average position is 8-10% (at cost).  Positions are held for 3 to 5 years unless a stock approaches intrinsic value sooner or an error has been discovered.

The goal of the Boole Microcap Fund is to outperform the Russell Microcap Index over time, net of fees.  The Boole Fund has low fees. 

 

If you are interested in finding out more, please e-mail me or leave a comment.

My e-mail: jb@boolefund.com

 

 

 

Disclosures: Past performance is not a guarantee or a reliable indicator of future results. All investments contain risk and may lose value. This material is distributed for informational purposes only. Forecasts, estimates, and certain information contained herein should not be considered as investment advice or a recommendation of any particular security, strategy or investment product. Information contained herein has been obtained from sources believed to be reliable, but not guaranteed. No part of this article may be reproduced in any form, or referred to in any other publication, without express written permission of Boole Capital, LLC.

Quantitative Microcap Value

(Image:  Zen Buddha Silence by Marilyn Barbone.)

October 7, 2018

Jack Bogle and Warren Buffett correctly maintain that most investors should invest in an S&P 500 index fund.  An index fund will allow you to outpace 90-95% of all active investors—net of costs—over the course of 4-5 decades.  This is purely a function of cost.  Active investors as a group will do the same as the S&P 500, but that is before costs.  After costs, active investors will do about 2.5% worse per year than the index.

An index fund is a wise choice.  But you can do much better if you invest in a quantitative microcap value strategy—focused on undervalued microcap stocks with improving fundamentals.  If you adopt such an approach, you can outperform the S&P 500 by roughly 7% per year.  For details, see: http://boolefund.com/cheap-solid-microcaps-far-outperform-sp-500/

But this can only work if you have the ability to ignore volatility and stay focused on the very long term.

“Investing is simple but not easy.” — Warren Buffett

(Photo by USA International Trade Administration)

Assume the S&P 500 index will return 8% per year over the coming decades.  The average active approach will produce roughly 5.5% per year.  A quantitative microcap approach—cheap micro caps with improving fundamentals—will generate about 15% per year.

What would happen if you invested $50,000 for the next 30 years in one of these approaches?

Investment Strategy Beginning Value Ending Value
Active $50,000 $249,198
S&P 500 Index $50,000 $503,133
Quantitative Microcap $50,000 $3,310,589

As you can see, investing $50,000 in an index fund will produce $503,133, which is more than ten times what you started with.  Furthermore, $503,133 is more than twice $249,198, which would be the result from the average active fund.

However, if you invested $50,000 in a quantitative microcap strategy, you would end up with $3,310,589.  This is more than 66 times what you started with, and it’s more than 6.5 times greater than the result from the index fund.

You could either invest in a quantitative microcap approach or you could invest in an index fund.  You’ll do fine either way.  You could also invest part of your portfolio in the microcap strategy and part in an index fund.

What’s the catch?

For most of us as investors, our biggest enemy is ourselves.  Let me explain.  Since 1945, there have been 27 corrections where stocks dropped 10% to 20%, and there have been 11 bear markets where stocks dropped more than 20%.  However, the stock market has always recovered and gone on to new highs.

Edgar Wachenheim, in the great book Common Stocks and Common Sense, gives the following example:

The financial crisis during the fall of 2008 and the winter of 2009 is an extreme (and outlier) example of volatility.  During the six months between the end of August 2008 and end of February 2009, the [S&P] 500 Index fell by 42 percent from 1,282.83 to 735.09.  Yet by early 2011 the S&P 500 had recovered to the 1,280 level, and by August 2014 it had appreciated to the 2000 level.  An investor who purchased the S&P 500 Index on August 31, 2008, and then sold the Index six years later, lived through the worst financial crisis and recession since the Great Depression, but still earned a 56 percent profit on his investment before including dividends—and 69 percent including the dividends… During the six-year period August 2008 through August 2014, the stock market provided an average annual return of 11.1 percent—above the range of normalcy in spite of the abnormal horrors and consequences of the financial crisis and resulting deep recession.

If you can stay the course through a 25% drop and even through a 40%+ drop, and remain focused on the very long term, then you should invest primarily in stocks, whether via an index fund, a quantitative microcap value fund, or some other investment vehicle.

The best way to stay focused on the very long term is simply to ignore the stock market entirely.  All you need to know or believe is:

  • The U. S. and global economies will continue to grow, mainly due to improvements in technology.
  • After every correction or bear market—no matter how severe—the stock market has always recovered and gone on to new highs.

If you’re unable to ignore the stock market, and if you might get scared and sell during a correction or bear market—don’t worry if you’re in this category since many investors are—then you should try to invest a manageable portion of your liquid assets in stocks.  Perhaps investing 50% or 25% of your liquid assets in stocks will allow you to stay the course through the inevitable corrections and bear markets.

The best-performing investors will be those who can invest for the very long term—several decades or more—and who don’t worry about (or even pay any attention to) the inevitable corrections and bear markets along the way.  In fact, Fidelity did a study of its many retail accounts.  It found that the best-performing accounts were owned by investors who literally forgot that they had an account!

  • Note: If you were to buy and hold twenty large-cap stocks chosen at random, your long-term performance would be very close to the S&P 500 Index.  (The Dow Jones Industrial Average is a basket of thirty large-cap stocks.)

Bottom Line

If you’re going to be investing for a few decades or more, and if you can basically ignore the stock market in the meantime, then you should invest fully in stocks.  Your best long-term investment is an index fund, a quantitative microcap value fund, or a combination of the two.

If you can largely ignore volatility, then you should consider investing primarily in a quantitative microcap value fund.  This is very likely to produce far better long-term performance than an S&P 500 index fund.

Many top investors—including Warren Buffett, perhaps the greatest investors of all time—earned the highest returns of their career when they could invest in microcap stocks.  Buffett has said that he’d still be investing in micro caps if he were managing small sums.

To learn more about Buffett getting his highest returns mainly from undervalued microcaps, here’s a link to my favorite blog post: http://boolefund.com/buffetts-best-microcap-cigar-butts/

The Boole Microcap Fund that I manage is a quantitative microcap value fund.  For details on the quantitative investment process, see: http://boolefund.com/why-invest-in-boole-microcap/

Although the S&P 500 index appears rather high—a bear market in the next year or two wouldn’t be a surprise—the positions in the Boole Fund are quite undervalued.  When looking at the next 3 to 5 years, I’ve never been more excited about the prospects of the Boole Fund relative to the S&P 500—regardless of whether the index is up, down, or flat.

(The S&P 500 may be flat for 5 years or even 10 years, but after that, as you move further into the future, eventually there’s more than a 99% chance that the index will be in positive territory.  The longer your time horizon, the less risky stocks are.)

 

BOOLE MICROCAP FUND

An equal weighted group of micro caps generally far outperforms an equal weighted (or cap-weighted) group of larger stocks over time.  See the historical chart here:  http://boolefund.com/best-performers-microcap-stocks/

This outperformance increases significantly by focusing on cheap micro caps.  Performance can be further boosted by isolating cheap microcap companies that show improving fundamentals.  We rank microcap stocks based on these and similar criteria.

There are roughly 10-20 positions in the portfolio.  The size of each position is determined by its rank.  Typically the largest position is 15-20% (at cost), while the average position is 8-10% (at cost).  Positions are held for 3 to 5 years unless a stock approaches intrinsic value sooner or an error has been discovered.

The goal of the Boole Microcap Fund is to outperform the Russell Microcap Index over time, net of fees.  The Boole Fund has low fees. 

 

If you are interested in finding out more, please e-mail me or leave a comment.

My e-mail: jb@boolefund.com

 

 

 

Disclosures: Past performance is not a guarantee or a reliable indicator of future results. All investments contain risk and may lose value. This material is distributed for informational purposes only. Forecasts, estimates, and certain information contained herein should not be considered as investment advice or a recommendation of any particular security, strategy or investment product. Information contained herein has been obtained from sources believed to be reliable, but not guaranteed. No part of this article may be reproduced in any form, or referred to in any other publication, without express written permission of Boole Capital, LLC.

Cheap, Solid Microcaps Far Outperform the S&P 500

(Image: Zen Buddha Silence, by Marilyn Barbone)

September 30, 2018

The wisest long-term investment for most investors is an S&P 500 index fund.  It’s just simple arithmetic, as Warren Buffett and Jack Bogle frequently observe: http://boolefund.com/warren-buffett-jack-bogle/

But you can do significantly better — roughly 7% per year (on average) — by systematically investing in cheap, solid microcap stocks.  The mission of the Boole Microcap Fund is to help you do just that.

Most professional investors never consider microcaps because their assets under management are too large.  Microcaps aren’t as profitable for them.  That’s why there continues to be a compelling opportunity for savvy investors.  Because microcaps are largely ignored, many get quite cheap on occasion.

Warren Buffett earned the highest returns of his career when he could invest in microcap stocks.  Buffett says he’d do the same today if he were managing small sums: http://boolefund.com/buffetts-best-microcap-cigar-butts/

Look at this summary of the CRSP Decile-Based Size and Return Data from 1927 to 2015:

Decile Market Cap-Weighted Returns Equal Weighted Returns Number of Firms (year-end 2015) Mean Firm Size (in millions)
1 9.29% 9.20% 173 84,864
2 10.46% 10.42% 178 16,806
3 11.08% 10.87% 180 8,661
4 11.32% 11.10% 221 4,969
5 12.00% 11.92% 205 3,151
6 11.58% 11.40% 224 2,176
7 11.92% 11.87% 300 1,427
8 12.00% 12.27% 367 868
9 11.40% 12.39% 464 429
10 12.50% 17.48% 1,298 107
9+10 11.85% 16.14% 1,762 192

(CRSP is the Center for Research in Security Prices at the University of Chicago.  You can find the data for various deciles here:  http://mba.tuck.dartmouth.edu/pages/faculty/ken.french/data_library.html)

The smallest two deciles — 9+10 — comprise microcap stocks, which typically are stocks with market caps below $500 million.  What stands out is the equal weighted returns of the 9th and 10th size deciles from 1927 to 2015:

Microcap equal weighted returns = 16.14% per year

Large-cap equal weighted returns = ~11% per year

In practice, the annual returns from microcap stocks will be 1-2% lower because of the difficulty (due to illiquidity) of entering and exiting positions.  So we should say that an equal weighted microcap approach has returned 14% per year from 1927 to 2015, versus 11% per year for an equal weighted large-cap approach.

Still, if you can do 3% better per year than the S&P 500 index (on average) — even with only a part of your total portfolio — that really adds up after a couple of decades.

 

VALUE SCREEN: +2-3%

By systematically implementing a value screen — e.g., low EV/EBIT or low P/E — to a microcap strategy, you can add 2-3% per year.

 

IMPROVING FUNDAMENTALS: +2-3%

You can further boost performance by screening for improving fundamentals.  One excellent way to do this is using the Piotroski F_Score, which works best for cheap micro caps.  See:  http://boolefund.com/joseph-piotroski-value-investing/

 

BOTTOM LINE

In sum, over time, a quantitative value strategy — applied to cheap microcap stocks with improving fundamentals — has high odds of returning at least 7% (+/- 3%) more per year than an S&P 500 index fund.

If you’d like to learn more about how the Boole Fund can help you do roughly 7% better per year than the S&P 500, please call or e-mail me any time.

E-mail: jb@boolefund.com  (Jason Bond)

 

BOOLE MICROCAP FUND

An equal weighted group of micro caps generally far outperforms an equal weighted (or cap-weighted) group of larger stocks over time.  See the historical chart here:  http://boolefund.com/best-performers-microcap-stocks/

This outperformance increases significantly by focusing on cheap micro caps.  Performance can be further boosted by isolating cheap microcap companies that show improving fundamentals.  We rank microcap stocks based on these and similar criteria.

There are roughly 10-20 positions in the portfolio.  The size of each position is determined by its rank.  Typically the largest position is 15-20% (at cost), while the average position is 8-10% (at cost).  Positions are held for 3 to 5 years unless a stock approaches intrinsic value sooner or an error has been discovered.

The goal of the Boole Microcap Fund is to outperform the Russell Microcap Index over time, net of fees.  The Boole Fund has low fees. 

 

If you are interested in finding out more, please e-mail me or leave a comment.

My e-mail: jb@boolefund.com

 

 

 

Disclosures: Past performance is not a guarantee or a reliable indicator of future results. All investments contain risk and may lose value. This material is distributed for informational purposes only. Forecasts, estimates, and certain information contained herein should not be considered as investment advice or a recommendation of any particular security, strategy or investment product. Information contained herein has been obtained from sources believed to be reliable, but not guaranteed. No part of this article may be reproduced in any form, or referred to in any other publication, without express written permission of Boole Capital, LLC.

Think Twice

(Image:  Zen Buddha Silence by Marilyn Barbone.)

September 23, 2018

In today’s blog post, I review some lessons from Michael Mauboussin’s excellent book Think Twice: Harnessing the Power of Counterintuition.   Each chapter is based on a common mistake in decision-making:

  • RQ vs. IQ
  • The Outside View
  • Open to Options
  • The Expert Squeeze
  • Situational Awareness
  • More Is Different
  • Evidence of Circumstance
  • Phase Transitions—”Grand Ah-Whooms”
  • Sorting Luck From Skill
  • Time to Think Twice
Illustration by Kheng Guan Toh

 

RQ vs IQ

Given a proper investment framework or system, obviously IQ can help a great deal over time.  Warren Buffett and Charlie Munger are seriously smart.  But they wouldn’t have become great investors without a lifelong process of learning and improvement, including learning how to be rational.  The ability to be rational may be partly innate, but it can be improved—sometimes significantly—with work.

Illustration by hafakot

An investor dedicated to lifelong improvements in knowledge and rationality can do well in value investing even without being brilliant.  A part of rationality is focusing on the knowable and remembering the obvious.

“We try more to profit from always remembering the obvious than from grasping the esoteric. It is remarkable how much long-term advantage people like us have gotten by trying to be consistently not stupid, instead of trying to be very intelligent.” — Charlie Munger

Quite often, the best approach for a value investor is to invest in an index fund or in a quantitative value fund.  Lifelong improvements are still helpful in these cases.  Many value investors, including the father of value investing Ben Graham, have advocated and used a quantitative approach.

 

THE OUTSIDE VIEW

Mauboussin discusses why Big Brown was a bad bet to win the Triple Crown in 2008.  Big Brown had won the Kentucky Derby by four-and-three-quarters lengths, and he won the Preakness by five-and-one-quarter lengths.  The horse’s trainer, Rick Dutrow, said, “He looks as good as he can possibly look.  I can’t find any flaws whatsoever in Big Brown.  I see the prettiest picture.  I’m so confident, it’s unbelievable.”  UPS (after whom Big Brown was named) signed a marketing deal.  And enthusiasm for Big Brown’s chances in the Belmont Stakes grew.

(Photo of Big Brown by Naoki Nakashima, via Wikimedia Commons)

What happened?  Big Brown trailed the field during the race, so his jockey eased him out of the race.  This was a shocking result.  But the result of not winning could have been much more widely anticipated if people had used the outside view.

The outside view means identifying similar situations and finding the statistics on how things worked out.  Renowned handicapper Steven Crist developed an outside view, as Mauboussin summarizes:

Of the twenty-nine horses with a chance to capture the Triple Crown after winning the Kentucky Derby and the Preakness Stakes, only eleven triumphed, a success rate less than 40 percent.  But a closer examination of those statistics yielded a stark difference before and after 1950.  Before 1950, eight of the nine horses attempting to win the Triple Crown succeeded.  After 1950, only three of twenty horses won.  It’s hard to know why the achievement rate dropped from nearly 90 percent to just 15 percent, but logical factors include better breeding (leading to more quality foals) and bigger starting fields.

Most people naturally use the inside view.  This essentially means looking at more subjective factors that are close at hand, like how tall and strong the horse looks and the fact that Big Brown had handily won the Kentucky Derby and the Preakness.

Why do people naturally adopt the inside view?  Mauboussin gives three reasons:

  • the illusion of superiority
  • the illusion of optimism
  • the illusion of control

First is the illusion of superiority.  Most people say they are above average in many areas, such as looks, driving, judging humor, investing.  Most people have an unrealistically positive view of themselves.  In many areas of life, this does not cause problems.  In fact, unrealistic positivity may often be an advantage that helps people to persevere.  But in zero-sum games—like investing—where winning requires clearly being above average, the illusion of superiority is harmful.

Illustration by OptureDesign

Munger calls it the Excessive Self-Regard Tendency.  Munger also notes that humans tend to way overvalue the things they possess—the endowment effect.  This often causes someone already overconfident about a bet he is considering to become even more overconfident after making the bet.

The illusion of optimism, which is similar to the illusion of superiority, causes most people to see their future as brighter than that of others.

The illusion of control causes people to behave as if chance events are somehow subject to their control.  People throwing dice throw softly when they want low numbers and hard for high numbers.  A similar phenomenon is seen when people choose which lottery card to take, as opposed to getting one by chance.

Mauboussin observes that a vast range of professionals tends to use the inside view to make important decisions, with predictably poor results.

Encouraged by the three illusions, most believe they are making the right decision and have faith that the outcomes will be satisfactory.

In the world of investing, many investors believe that they will outperform the market over time.  However, after several decades, there are very few investors who have done better than the market.

Another area where people fall prey to the three illusions is mergers and acquisitions.  Two-thirds of acquisitions fail to create value, but most executives, relying on the inside view, believe that they can beat the odds.

The planning fallacy is yet another example of how most people rely on the inside view instead of the outside view.  Mauboussin gives one common example of students estimating when they’d finish an assignment:

…when the deadline arrived for which the students had given themselves a 50 percent chance of finishing, only 13 percent actually turned in their work.  At the point when the students thought there was 75 percent chance they’d be done, just 19 percent had completed the project.  All the students were virtually sure they’d be done by the final date.  But only 45 percent turned out to be right.

Illustration by OpturaDesign

Daniel Kahneman gives his own example of the planning fallacy.  He was part of a group assembled to write a curriculum to teach judgment and decision-making to high school students.  Kahneman asked everyone in the group to write down their opinion of when they thought the group would complete the task.  Kahneman found that the average was around two years, and everyone, including the dean, estimated between eighteen and thirty months.

Kahneman then realized that the dean had participated in similar projects in the past.  Kahneman asked the dean how long it took them to finish.

The dean blushed and then answered that 40 percent of the groups that had started similar programs had never finished, and that none of the groups completed it in less than seven years.  Kahneman then asked how good this group was compared to past groups.  The dean thought and then replied: ‘Below average, but not by much.’

 

OPEN TO OPTIONS

In making decisions, people often fail to consider a wide enough range of alternatives.  People tend to have “tunnel vision.”

Anchoring is an important example of this mistake.  Mauboussin:

Kahneman and Amos Tversky asked people what percentage of the UN countries is made up of African nations.  A wheel of fortune with the numbers 1 to 100 was spun in front of the participants before they answered.  The wheel was rigged so it gave either 10 or 65 as the result of a spin.  The subjects were then asked—before giving their specific prediction—if the answer was higher or lower than the number on the wheel.  The median response from the group that saw the wheel stop at 10 was 25%, and the median response from the group that saw 65 was 45%.

(Illustration by Olga Vainshtein)

Behavioral finance expert James Montier has run his own experiment on anchoring.  People are asked to write down the last four digits of their phone number.  Then they are asked whether the number of doctors in their capital city is higher or lower than the last four digits of their phone number.  Results: Those whose last four digits were greater than 7000 on average report 6762 doctors, while those with telephone numbers below 2000 arrived at an average 2270 doctors.

Stock prices often have a large component of randomness, but investors tend to anchor on various past stock prices.  The rational way to avoid such anchoring is to carefully develop different possible scenarios for the intrinsic value of a stock.  For instance, you could ask:

  • What is the business worth if things go better than expected?
  • What is the business worth if things go as expected?  Or: What is the business worth under normal conditions?
  • What is the business worth if things go worse than expected?

Ideally, you would not want to know about past stock prices—or even the current stock price—before developing the intrinsic value scenarios.

The Representativeness Heuristic

The representativeness heuristic is another bias that leads many people not to consider a wide range of possibilities.  Daniel Kahneman and Amos Tversky defined representativeness as “the degree to which [an event] (i) is similar in essential characteristics to its parent population, and (ii) reflects the salient features of the process by which it is generated.”

People naturally tend to believe that something that is more representative is more likely.  But frequently that’s not the case.  Here is an example Kahneman and Tversky have used:

“Steve is very shy and withdrawn, invariably helpful but with very little interest in people or in the world of reality.  A meek and tidy soul, he has a need for order and structure, and a passion for detail.  Question: Is Steve more likely to be a librarian or a farmer?”

Most people say “a librarian.”  But the fact that the description seems more representative of librarians than of farmers does not mean that it is more likely that Steve is a librarian.  Instead, one must look at the base rate: there are twenty times as many farmers as librarians, so it is far more likely that Steve is a farmer.

Another example Kahneman gives:

“Linda is 31 years old, single, outspoken, and very bright.  She majored in philosophy.  As a student, she was deeply concerned with issues of discrimination and social justice, and also participated in anti-nuclear demonstrations.  Question: Which is more probable?

  1.  Linda is a bank teller.
  2.  Linda is a bank teller and is active in the feminist movement.”

Most people say the second option is more likely.  But just using simple logic, we know that the second option is a subset of the first option, so the first option is more likely.  Most people get this wrong because they use the representativeness heuristic.

Availability Bias, Vividness Bias, Recency Bias

If a fact is easily available—which often happens if a fact is vivid or recent—people generally far overestimate its probability.

A good example is a recent and vivid plane crash.  The odds of dying in a plane crash are one in 11 million—astronomically low.  The odds of dying in a car crash are one in five thousand.  But many people, after seeing recent and vivid photos of a plane crash, decide that taking a car is much safer than taking a plane.

Extrapolating the Recent Past

Most people automatically extrapolate the recent past into the future without considering various alternative scenarios.  To understand why, consider Kahneman’s definitions of two systems in the mind, System 1 and System 2:

System 1:   Operates automatically and quickly;  makes instinctual decisions based on heuristics.

System 2:   Allocates attention (which has a limited budget) to the effortful mental activities that demand it, including logic, statistics, and complex computations.

In Thinking, Fast and Slow, Kahneman writes that System 1 and System 2 work quite well on the whole:

The division of labor between System 1 and System 2 is highly efficient:  it minimizes effort and optimizes performance.  The arrangement works well most of the time because System 1 is generally very good at what it does: its models of familiar situations are accurate, its short-term predictions are usually accurate as well, and its initial reactions to challenges are swift and generally appropriate.  System 1 has biases, however, systematic errors that it is prone to make in specified circumstances.  As we shall see, it sometimes answers easier questions than the one it was asked, and it has little understanding of logic and statistics.

System 1 is automatic and quick, and it works remarkably well much of the time.  Throughout most of our evolutionary history, System 1 has been instrumental in keeping us alive.  However, when we were hunter-gatherers, the recent past was usually the best guide to the future.

  • If there was a rustling in the grass or any other sign of a predator, the brain automatically went on high alert, which was useful because otherwise you weren’t likely to survive long.  A statistical calculation wasn’t needed.
  • There were certain signs indicating the potential presence of animals to hunt or wild plants to collect.  You learned to recognize those signs.  You foraged or you died.  You didn’t need to know any statistics.
  • Absent any potential threats, and assuming enough to eat, then things were fine and you could relax for a spell.

In today’s world—unlike when we were hunter-gatherers—the recent past is often a terrible guide to the future.  For instance, when it comes to investing, extrapolating the recent past is one of the biggest mistakes that investors make.  In a highly random environment, you should expect reversion to the mean, rather than a continuation of the recent past.  Investors must learn to think counterintuitively.  That includes thinking probabilistically—in terms of possible scenarios and reversion to the mean.

Illustration by intheskies

Doubt Avoidance

Charlie Munger—see Poor Charlie’s Almanack, Expanded Third Edition—explains what he calls Doubt Avoidance Tendency as follows:

“The brain of man is programmed with a tendency to quickly remove doubt by reaching some decision.”

System 1 is designed (by evolution) to jump to conclusions.  In the past, when things were simpler and less probabilistic, the ability to make a quick decision was beneficial.  In today’s complex world, you must train yourself to slow down when facing an important decision under uncertainty—a decision that depends on possible scenarios and their associated probabilities.

The trouble is that our mind—due to System 1—wants to jump immediately to a conclusion, even more so if we feel pressured, puzzled, or stressed.  Munger explains:

What triggers Doubt-Avoidance Tendency?  Well, an unthreatened man, thinking of nothing in particular, is not being prompted to remove doubt through rushing to some decision.  As we shall see later when we get to Social-Proof Tendency and Stress-Influence Tendency, what usually triggers Doubt-Avoidance Tendency is some combination of (1) puzzlement and (2) stress…

The fact that social pressure and stress trigger the Doubt-Avoidance Tendency supports the notion that System 1 excelled at keeping us alive when we lived in a much more primitive world.  In that type of environment where things usually were what they seemed to be, the speed of System 1 in making decisions was vital.  If the group was running in one direction, the immediate, automatic decision to follow was what kept you alive over time.

Inconsistency Avoidance and Confirmation Bias

Munger on the Inconsistency-Avoidance Tendency:

The brain of man conserves programming space by being reluctant to change, which is a form of inconsistency avoidance.  We see this in all human habits, constructive and destructive.  Few people can list a lot of bad habits that they have eliminated, and some people cannot identify even one of these.  Instead, practically everyone has a great many bad habits he has long maintained despite their being known as bad…. chains of habit that were too light to be felt before they became too heavy to be broken.

The rare life that is wisely lived has in it many good habits maintained and many bad habits avoided or cured.

Photo by Marek

Munger continues:

It is easy to see that a quickly reached conclusion, triggered by Doubt-Avoidance Tendency, when combined with a tendency to resist any change in that conclusion, will naturally cause a lot of errors in cognition for modern man.  And so it observably works out…

And so, people tend to accumulate large mental holdings of fixed conclusions and attitudes that are not often reexamined or changed, even though there is plenty of good evidence that they are wrong.

Our brain will jump quickly to a conclusion and then resist any change in that conclusion.  How do we combat this tendency?  One great way to overcome first conclusion bias is to train our brains to emulate Charles Darwin:

One of the most successful users of an antidote to first conclusion bias was Charles Darwin.  He trained himself, early, to intensively consider any evidence tending to disconfirm any hypothesis of his, more so if he thought his hypothesis was a particularly good one.  The opposite of what Darwin did is now called confirmation bias, a term of opprobrium.  Darwin’s practice came from his acute recognition of man’s natural cognitive faults arising from Inconsistency-Avoidance Tendency.  He provides a great example of psychological insight correctly used to advance some of the finest mental work ever done.  (my emphasis)

Selective Attention and Inattentional Blindness

We tend to be very selective about what we hear and see, and this is partly a function of what we already believe.  We often see and hear only what we want, and tune out everything else.

On a purely visual level, there is something called inattentional blindness.  When we focus on certain aspects of our environment, this causes many of us to miss other aspects that are plainly visible.  There is a well-known experiment related to inattentional blindness.  People watch a thirty-second video that shows two teams, one wearing white and the wearing black.  Each team is passing a basketball back and forth.  In the middle of the video, a woman wearing a gorilla suit walks into the middle of the scene, thumps her chest, and walks off.  Roughly half of the people watching the video have no recollection of the gorilla.

Struggles and Stresses

Stress or fatigue causes many of us to make poorer decisions than we otherwise would.  Thus, we must take care.  With the right attitude, however, stress can slowly be turned into an advantage over a long period of time.

As Ray Dalio and Charlie Munger have pointed out, mental strength is one of life’s greatest gifts.  With a high degree of focus and discipline, a human being can become surprisingly strong and resilient.  But this typically only happens gradually, over the course of years or decades, as the result of an endless series of struggles, stresses, and problems.

A part of strength that can be learned over time is inner peace or total calm in the face of seemingly overwhelming difficulties.  The practice of transcendental meditation is an excellent way to achieve inner peace and total calm in the face of any adversity.  But there are other ways, too.

Wise men such as Munger or Lincoln are of the view that total calm in the face of any challenge is simply an aspect of mental strength that can be developed over time.  Consider Rudyard Kipling’s poem “If”:

If you can keep your head when all about you
    Are losing theirs and blaming it on you,
If you can trust yourself when all men doubt you,
    But make allowance for their doubting too;
If you can wait and not be tired by waiting,
    Or being lied about, don’t deal in lies,
Or being hated, don’t give way to hating,
    And yet don’t look too good, nor talk too wise…
(Image by nickolae)
In the 2016 Daily Journal Annual Meeting, Charlie Munger made the following remarks:

…So, maybe in that sense I think a tougher hand has been good for us.  My answer to that question reminds me of my old Harvard law professor who used to say, ‘Charlie, let me know what your problem is and I’ll try to make it harder for you.’  I’m afraid that’s what I’ve done to you.

As for how do I understand a new industry: the answer is barely.  I just barely have enough cognitive ability to do what I do.  And that’s because the world promoted me to the place where I’m stressed.  And you’re lucky if it happens to you, because that’s what you want to end up: stressed.  You want to have your full powers called for.  Believe you me, I’ve had that happen all my life.  I’ve just barely been able to think through to the right answer, time after time.  And sometimes I’ve failed…

Link to 2016 Daily Journal Meeting Notes (recorded courtesy of Whitney Tilson): https://www.scribd.com/doc/308879985/MungerDJ-2-16

Incentives

Mauboussin writes about the credit crisis of 2007-2008.  People without credit could buy nice homes.  Lenders earned fees and usually did not hold on to the mortgages.  Investment banks bought mortgages and bundled them for resale, earning a fee.  Rating agencies were paid to rate the mortgage-backed securities, and they rated many of them AAA (based partly on the fact that home prices had never declined nationwide).  Investors worldwide in AAA-rated mortgage-backed securities earned higher returns than they did on other AAA issues.  Some of these investors were paid based on portfolio performance and thus earned higher fees this way.

Incentives are extremely important:

Never, ever think about something else when you should be thinking about incentives.” – Charlie Munger

Under a certain set of incentives, many people who normally are good people will behave badly.  Often this bad behavior is not only due to the incentives at play, but also involves other psychological pressures like social proof, stress, and doubt-avoidance.  A bad actor could manipulate basically good people to do bad things using social proof and propaganda.  If that fails, he could use bribery or blackmail.

Finally, Mauboussin offers advice about how to deal with “tunnel vision,” or the insufficient consideration of alternatives:

  • Explicitly consider alternatives.
  • Seek dissent. (This is very difficult, but highly effective.  Think of Lincoln’s team of rivals.)
  • Keep track of previous decisions. (A decision journal does not cost much, but it can help one over time to make better decisions.)
  • Avoid making decisions while at emotional extremes. (One benefit to meditation—in addition to total calm and rationality—is that it can give you much greater self-awareness.  You can learn to accurately assess your emotional state, and you can learn to postpone important decisions if you’re too emotional or tired.)
  • Understand incentives.

 

THE EXPERT SQUEEZE

In business today, there are many areas where you can get better insights or predictions than what traditional experts can offer.

Mauboussin gives the example of Best Buy forecasting holiday sales.  In the past, Best Buy depended on specialists to make these forecasts.  James Surowiecki, author of The Wisdom of Crowds, went to Best Buy’s headquarters and told them that a crowd could predict better than their specialists could.

Jeff Severts, a Best Buy executive, decided to test Surowiecki’s suggestion.  Late in 2005, Severts set up a location for employees to submit and update their estimates of sales from Thanksgiving to year-end.  In early 2006, Severts revealed that the internal experts had been 93 percent accurate, while the “amateur crowd” was off only one-tenth of one percent.  Best Buy then allocated more resources to its prediction market, and benefited.

Another example of traditional experts being supplanted:  Orley Ashenfelter, wine lover and economist, figured out a simple regression equation that predicts the quality of red wines from France’s Bordeaux region better than most wine experts.  Mauboussin:

With the equation in hand, the computer can deliver appraisals that are quicker, cheaper, more reliable, and without a whiff of snobbishness.

Mauboussin mentions four categories over which we can judge experts versus computers:

Rule based; limited range of outcomes—experts are generally worse than computers. Examples include credit scoring and simple medical diagnosis.

Rule based; wide range of outcomes—experts are generally better than computers.  But this may be changing.  For example, humans used to be better at chess and Go, but now computers are far better than humans.

Probabilistic; limited range of outcomes—experts are equal or worse than collectives.  Examples include admissions officers and poker.

Probabilistic; wide range of outcomes—experts are worse than collectives.  Examples include forecasting any of the following: stock prices, the stock market, interest rates, or the economy.

Regarding areas that are probabilistic, with a wide range of outcomes (the fourth category), Mauboussin comments on economic and political forecasts:

The evidence shows that collectives outperform experts in solving these problems.  For instance, economists are extremely poor forecasters of interest rates, often failing to accurately guess the direction of rate moves, much less their correct level.  Note, too, that not only are experts poor at predicting actual outcomes, they rarely agree with one another.  Two equally credentialed experts may make opposite predictions and, hence, decisions from one another.

Mauboussin notes that experts do relatively well with rule-based problems with a wide range of outcomes because they can be better than computers at eliminating bad choices and making creative connections between bits of information.  A fascinating example: Eric Bonabeau, a physicist, has developed programs that generate alternative designs for packaging using the principles of evolution (recombination and mutation).  But the experts select the best designs at the end of the process, since the computers have no taste.

Yet computers will continue to make big improvements in this category (rule-based problems with a wide range of outcomes).  For instance, many chess programs today can beat any human, whereas there was only one program (IBM’s Deep Blue) that could do this in the late 1990’s.  Also, in October 2015, Google DeepMind’s program AlphaGo beat Fan Hui, the European Go champion.

Note:  We still need experts to make the systems that replace them.  Severts had to set up the prediction market.  Ashenfelter had to find the regression equation.  And experts need to stay on top of the systems, making improvements when needed.

Also, experts are still needed for many areas in strategy, including innovation and creativity.  And people are needed to deal with people.  (Although many jobs will soon be done by robots.)

I’ve written before about how simple quant models outperform experts in a wide variety of areas: http://boolefund.com/simple-quant-models-beat-experts-in-a-wide-variety-of-areas/

 

SITUATIONAL AWARENESS

Mauboussin writes about the famous experiment by Solomon Asch.  The subject is shown lines of obviously different lengths.  But in the same room with the subject are shills, who unbeknownst to the subject have already been instructed to say that two lines of obviously different lengths actually have the same length.  So the subject of the experiment has to decide between the obvious evidence of his eyes—the two lines are clearly different lengths—and the opinion of the crowd.  A significant number (36.8 percent) ignored their own eyes and went with the crowd, saying that the two lines had equal length, despite the obvious fact that they didn’t.

(Photo by D-janous, via Wikimedia Commons)

Mauboussin notes that the interesting question about the Solomon Asch experiment is: what’s going on in the heads of people who conform?  Asch himself suggested three possibilities:

Distortion of judgment.  The subjects conclude that their perceptions are wrong and that the group is right.

Distortion of action.  These individuals suppress their own knowledge in order to go with the majority.

Distortion of perception.  This group is not aware that the majority opinion distorts their estimates.

Unfortunately, Asch didn’t have the tools to try to test these possibilities.  Gregory Berns, a neuroscientist, five decades after Asch, used functional magnetic resonance imaging (fMRI) in the lab at Emory University.

For the conforming subjects, the scientists found activity in the areas of the brain that were related to perception of the object.  Also, the scientists did not find a meaningful change in activity in the frontal lobe—an area associated with activities like judgment.  Thus, for conforming subjects, it is a distortion of perception: what the majority claims to see, the subject actually does see.  Remarkable.

What about the people who remained independent when faced with the group’s wrong responses?  Those subjects showed increased activity in the amygdala, a region that signals to prepare for immediate action (fight or flight).  Mauboussin comments: “…while standing alone is commendable, it is unpleasant.”

Priming

Mauboussin:

How do you feel when you read the word ‘treasure’? … If you are like most people, just ruminating on ‘treasure’ gives you a little lift.  Our minds naturally make connections and associate ideas.  So if someone introduces a cue to you—a word, a smell, a symbol—your mind often starts down an associative path.  And you can be sure the initial cue will color a decision that waits at the path’s end.  All this happens outside your perception.

(Subconscious as brain under water, Illustration by Agawa288)

Scientists did the following experiment:

In this test, the researchers placed the French and German wines next to each other, along with small national flags.  Over two weeks, the scientists alternated playing French accordion music and German Bierkeller pieces and watched the results.  When French music played, French wines represented 77 percent of the sales.  When German music played, consumers selected German wines 73 percent of the time… The music made a huge difference in shaping purchases.  But that’s not what the shoppers thought…

While the customers acknowledged that the music made them think of either France or Germany, 86 percent denied that the tunes had any influence on their choice.  This experiment is an example of priming, which psychologists formally define as ‘the incidental activation of knowledge structures by the current situational context.’  In other words, what comes in through our senses influences how we make decisions, even when it seems completely irrelevant in a logical sense.  Priming is by no means limited to music.  Researchers have manipulated behavior through exposure to words, smells, and visual backgrounds.

Mauboussin gives some examples of priming:

  • Immediately after being exposed to words associated with the elderly, primed subjects walked 13 percent slower than subjects seeing neutral words.
  • Exposure to the scent of an all-purpose cleaner prompted study participants to keep their environment tidier while eating a crumbly biscuit.
  • Subjects reviewing Web pages describing two sofa models preferred the more comfortable model when they saw a background with puffy clouds, and favored the cheaper sofa when they saw a background with coins.

The Fault of the Default

While virtually 100 percent of Austrians have consented to be an organ donor, only 12 percent of Germans have.  The difference is due entirely to how the choice is presented.  In Austria, you must opt-out of being an organ donor—being an organ donor is the default choice.  In Germany, you must opt-in to being an organ donor—not being a donor is the default choice.  But this directly translates into many more saved lives in Austria than in Germany.

Illustration by hafakot

Mauboussin makes an important larger point.  We tend to assume that people decide what is best for them independent of how the choice is framed, but in reality, “many people simply go with the default options.”  This includes consequential areas (in addition to organ donation) like savings, educational choice, medical alternatives, etc.

The Power of Inertia

To overcome inertia, Peter Drucker suggested asking: “If we did not do this already, would we, knowing what we now know, go into it?”

Dr. Atul Gawande, author of The Checklist Manifesto, tells the story of Dr. Peter Pronovost, an anesthesiologist and critical-care specialist at the Johns Hopkins Hospital.  Pronovost’s father died due to a medical error, which led Pronovost to dedicate his career to ensuring the safety of patients.  Mauboussin explains:

In the United States, medical professionals put roughly 5 million lines into patients each year, and about 4 percent of those patients become infected within a week and a half.  The added cost of treating those patients is roughly $3 billion per year, and the complications result in twenty to thirty thousand annual preventable deaths.

Pronovost came up with a simple checklist because he observed that physicians in a hurry would often overlook some simple routine that is normally done as a part of safety.  It saved numerous lives and millions of dollars in the first few years at Johns Hopkins Hospital, so Pronovost got the Michigan Health & Hospital Association to try the checklist.  After just three months, the rate of infection dropped by two-thirds.  After eighteen months, the checklist saved 1,500 lives and nearly $200 million.

 

MORE IS DIFFERENT

Mauboussin covers complex adaptive systems such as the stock market or the economy.  His advice, when dealing with a complex adaptive system, is:

  • Consider the system at the correct level.  An individual agent in the system can be very different from one outside the system.
  • Watch for tightly coupled systems.  A system is tightly coupled when there is no slack between items, allowing a process to go from one stage to the next without any opportunity to intervene.  (Examples include space missions and nuclear power plants.)  Most complex adaptive systems are loosely coupled, where removing or incapacitating one or a few agents has little impact on the system’s performance.
  • Use simulations to create virtual worlds.  Simulation is a tool that can help our learning process.  Simulations are low cost, provide feedback, and have proved their value in other domains like military planning and pilot training.

Mauboussin notes that complex adaptive systems often perform well at the system level, despite dumb agents (consider ants or bees).  Moreover, there are often unintended consequences that can lead to failure when well-meaning humans try to manage a complex system towards a particular goal.

 

EVIDENCE OF CIRCUMSTANCE

Decisions that work well in one context can often fail miserably in a different context.  The right answer to many questions that professionals face is: “It depends.”

Mauboussin writes about how most people make decisions based on a theory, even though often they are not aware of it.  Two business professors, Paul Carlile and Clayton Christensen, describe three stages of theory building:

  • The first stage is observation, which includes carefully measuring a phenomenon and documenting the results.  The goal is to set common standards so that subsequent researchers can agree on the subject and the terms to describe it.
  • The second stage is classification, where researchers simplify and organize the world into categories to clarify the differences among phenomena.  Early in theory development, these categories are based predominantly on attributes.
  • The final stage is definition, or describing the relationship between the categories and the outcomes.  Often, these relationships start as simple correlations.

What’s especially important, writes Mauboussin:

Theories improve when researchers test predictions against real-world data, identify anomalies, and subsequently reshape the theory.  Two crucial improvements occur during this refining process.  In the classification stage, researchers evolve the categories to reflect circumstances, not just attributes.  In other words, the categories go beyond what works to when it works.  In the definition stage, the theory advances beyond simple correlations and sharpens to define causes—why it works.  This pair of improvements allows people to go beyond crude estimates and to tailor their choices to the situation they face.

Here is what is often done:  Some successes are observed, some common attributes are identified, and it is proclaimed that these attributes can lead others to success.  This doesn’t work.

By the same logic, a company should not adopt a strategy without understanding the conditions under which it succeeds or fails.  Mauboussin gives the example of Boeing outsourcing both the design and the building of sections of the Dreamliner to its suppliers.  This was a disaster.  Boeing had to pull the design work back in-house.

The Colonel Blotto Game

Each player gets a hundred soldiers (resources) to distribute across three battlefields (dimensions).  The players make their allocations in secret.  Then the players’ choices are simultaneously revealed, and the winner of each battle is whichever army has more soldiers in that battlefield.  The overall winner is whichever player wins the most battles.  What’s interesting is how the game changes as you adjust one of the two parameters (resources, dimensions).

Mauboussin observes that it’s not intuitive how much advantage additional points give to one side in a three-battlefield game:

In a three-battlefield game, a player with 25 percent more resources has a 60 percent expected payoff (the proportion of battles the player wins), and a player with twice the resources has a 78 percent expected payoff.  So some randomness exists, even in contests with fairly asymmetric resources, but the resource-rich side has a decisive advantage.  Further, with low dimensions, the game is largely transitive: if A can beat B and B can beat C, then A can beat C.  Colonel Blotto helps us to understand games with few dimensions, such as tennis.

Things can change even more unexpectedly when the number of dimensions is increased:

But to get the whole picture of the payoffs, we must introduce the second parameter, the number of dimensions or battlefields.  The more dimensions the game has, the less certain the outcome (unless the players have identical resources).  For example, a weak player’s expected payoff is nearly three times higher in a game with fifteen dimensions than in a nine-dimension game.  For this reason, the outcome is harder to predict in a high-dimension game than in a low-dimension game, and as a result there are more upsets.  Baseball is a good example of a high-dimension game…

What may be most surprising is that the Colonel Blotto game is highly nontransitive (except for largely asymmetric, low-dimension situations).  This means that tournaments often fail to reveal the best team.  Mauboussin gives an example where A beats B, B beats C, C beats A, and all of them beat D.  Because there is no best player, the winner of a tournament is simply “the player who got to play D first.”  Mauboussin:

Because of nontransitivity and randomness, the attribute of resources does not always prevail over the circumstance of dimensionality.

Bottom Line on Attributes vs. Circumstances

Mauboussin sums up the  main lesson on attributes versus circumstances:

Most of us look forward to leveraging our favorable experiences by applying the same approach to the next situation.  We also have a thirst for success formulas—key steps to enrich ourselves.  Sometimes our experience and nostrums work, but more often they fail us.  The reason usually boils down to the simple reality that the theories guiding our decisions are based on attributes, not circumstances.  Attribute-based theories come very naturally to us and often appear compelling… However, once you realize the answer to most questions is, ‘It depends,’ you are ready to embark on the quest to figure out what it depends on.

 

PHASE TRANSITIONS—“GRAND AH-WHOOMS”

Just a small incremental change in temperature leads to a change from solid to liquid or from liquid to gas.  Philip Ball, a physicist and author of Critical Mass: How One Thing Leads to Another, calls it a grand ah-whoom.

(Illustration by Designua)

Critical Points, Extremes, and Surprise

In part due to the writings of Nassim Taleb, people are more aware of black swans, or extreme outcomes within a power law distribution.  According to Mauboussin, however, what most people do not yet appreciate is how black swans are caused:

Here’s where critical points and phase transitions come in.  Positive feedback leads to outcomes that are outliers.  And critical points help explain our perpetual surprise at black swan events because we have a hard time understanding how such small incremental perturbations can lead to such large outcomes.

Mauboussin explains critical points in social systems.  Consider the wisdom of crowds: Crowds tend to make accurate predictions when three conditions prevail—diversity, aggregation, and incentives.

Diversity is about people having different ideas and different views of things.  Aggregation means you can bring the group’s information together.  Incentives are rewards for being right and penalties for being wrong that are often, but not necessarily, monetary.

Mauboussin continues:

For a host of psychological and sociological reasons, diversity is the most likely condition to fail when humans are involved.  But what’s essential is that the crowd doesn’t go from smart to dumb gradually.  As you slowly remove diversity, nothing happens initially.  Additional reductions may also have no effect.  But at a certain critical point, a small incremental reduction causes the system to change qualitatively.

Blake LeBaron, an economist at Brandeis University, has done an experiment.  LaBaron created a thousand investors within the computer and gave them money, guidelines on allocating their portfolios, and diverse trading rules.  Then he let the system play out.  As Mauboussin describes:

His model was able to replicate many of the empirical features we see in the real world, including cycles of booms and crashes.  But perhaps his most important finding is that a stock price can continue to rise even while the diversity of decision rules falls.  Invisible vulnerability grows.  But then, ah-whoom, the stock price tumbles as diversity rises again.  Writes LaBaron, ‘During the run-up to a crash, population diversity falls.  Agents begin using very similar trading strategies as their common good performance is reinforced.  This makes the population very brittle, in that a small reduction in the demand for shares could have a strong destabilizing impact on the market.’

The Problem of Induction, Reductive Bias, and Bad Predictions

Extrapolating from what we see or have seen, to what will happen next, is a common decision-making mistake.  Nassim Taleb retells Bertrand Russell’s story of a turkey (Taleb said turkey instead of chicken to suit his American audience).  The turkey is fed a thousand days in a row.  The turkey feels increasingly good until the day before Thanksgiving, when an unexpected event occurs.  None of the previous one thousand days has given the turkey any clue about what’s next.  Mauboussin explains:

The equivalent of the turkey’s plight—sharp losses following a period of prosperity—has occurred repeatedly in business.  For example, Merrill Lynch (which was acquired by Bank of America) suffered losses over a two-year period from 2007 to 2008 that were in excess of one-third of the profits it had earned cumulatively in its thirty-six years as a public company….

The term black swan reflects the criticism of induction by the philosopher Karl Popper.  Popper argued that seeing lots of white swans doesn’t prove the theory that all swans are white, but seeing one black swan does disprove it.  So Popper’s point is that to understand a phenomenon, we’re better off focusing on falsification than on verification.  But we’re not naturally inclined to falsify something.

Black swan, Photo by Dr. Jürgen Tenckhoff

Not only does System 1 naturally look for confirming evidence.  But even System 2 uses a positive test strategy, looking for confirming evidence for any hypothesis, rather than looking for disconfirming evidence.

People have a propensity to stick to whatever they currently believe.  Most people rarely examine or test their beliefs (hypotheses).  As Bertrand Russell pointed out:

Most people would rather die than think;  many do.

People are generally overconfident.  Reductive bias means that people tend to believe that reality is much simpler and more predictable than it actually is.  This causes people to oversimplify complex phenomena.  Instead of properly addressing the real questions—however complex and difficult—System 1 naturally substitutes an easier question.  The shortcuts used by System 1 work quite well in simple environments.  But these same shortcuts lead to predictable errors in complex and random environments.

System 2—which can be trained to do logic, statistics, and complex computations—is naturally lazy.  It requires conscious effort to activate System 2 .  If System 1 recognizes a serious threat, then System 2 can be activated if needed.

The problem is that System 1 does not recognize the dangers associated with complex and random environments.  Absent an obvious threat, System 1 will nearly always oversimplify complex phenomena.  This creates overconfidence along with comforting illusions—”everything makes sense” and “everything is fine.”  But complex systems frequently undergo phase transitions, and some of these new phases have sharply negative consequences, especially when people are completely unprepared.

Even very smart people routinely oversimplify and are inclined to trust overly simple mathematical models—for instance, models that assume a normal distribution even when the distribution is far from normal.  Mauboussin argues that Long-Term Capital Management, which blew up in the late 1990’s, had oversimplified reality by relying too heavily on its financial models.  According to their models, the odds of LTCM blowing up—as it did—were astronomically low (1 out of billions).  Clearly their models were very wrong.

Mauboussin spoke with Benoit Mandelbrot, the French mathematician and father of fractal geometry.  Mauboussin asked about the reductive bias.  Mandelbrot replied that the wild randomness of stock markets was clearly visible for all to see, but economists continued to assume mild randomness, largely because it simplified reality and made the math more tractable.  If you assume a normal distribution, the math is much easier than if you tried to capture the wildness and complexity of  reality:

Mandelbrot emphasized that while he didn’t know what extreme event was going to happen in the future, he was sure that the simple models of the economists would not anticipate it.

Mauboussin gives the example of David Li’s formula, which measures the correlation of default between assets.  (The formula is known as a Gaussian copula function.)  Li’s equation could measure the likelihood that two or more assets within a portfolio would default at the same time.  This “opened the floodgates” for financial engineers to create new products, including collateralized debt obligations (bundles of corporate bonds), and summarize the default correlation using Li’s equation “rather than worry about the details of how each corporate bond within the pool would behave.”

Unfortunately, Li’s equation oversimplified a complex world: Li’s equation did not make any adjustments for the fact that many correlations can change significantly.

The failure of Long-Term Capital Management illustrates how changing correlations can wreak havoc.  LTCM observed that the correlation between its diverse investments was less than 10 percent over the prior five years.  To stress test its portfolio, LTCM assumed that correlations could rise to 30 percent, well in excess of anything the historical data showed.  But when the financial crisis hit in 1998, the correlations soared to 70 percent.  Diversification went out the window, and the fund suffered mortal losses.  ‘Anything that relies on correlation is charlatanism,’ scoffed Taleb.  Or, as I’ve heard traders say, ‘The only thing that goes up in a bear market is correlation.’

Music Lab

Duncan Watts, a sociologist, led a trio of researchers at Columbia University in doing a social experiment.  Subjects went to a web site—Music Lab—and were invited to participate in a survey.  Upon entering the site, 20 percent of the subjects were assigned to an independent world and 10 percent each to eight worlds where people could see what other people were doing.

In the independent world, subjects were free to listen to songs, rated them, and download them, but they had no information about what other subjects were doing.  In each of the other eight worlds, the subjects could see how many times other people had downloaded each song.

The subjects in the independent world collectively gave a reasonable indication of the quality of each of the songs.  Thus, you could see for the other eight worlds whether social influence made a difference or not.

Song quality did play a role in the ranking, writes Mauboussin.  A top-five song in the independent world had about a 50 percent chance of finishing in the top five in a social influence world.  And the worst songs rarely topped the charts.  But how would you guess the average song did in the social worlds?

The scientists found that social influence played a huge part in success and failure.  One song, ‘Lockdown’ by the band 52metro, ranked twenty-sixth in the independent world, effectively average.  Yet it was the number one song in one of the social influence worlds, and number forty in another.  Social influence catapulted an average song to hit status in one world—ah-whoom—and relegated it to the cellar in another.  Call it Lockdown’s lesson.

In the eight social worlds, the songs the subjects downloaded early in the experiment had a huge influence on the songs subjects downloaded later.  Since the patterns of download were different in each social world, so were the outcomes.

(Illustration by Mindscanner)

Mauboussin summarizes the lessons:

  • Study the distribution of outcomes for the system you are dealing with.  Taleb defines gray swans as “modelable extreme events,” which are events you can at least prepare for, as opposed to black swans, which are by definition exceedingly difficult to prepare for.
  • Look for ah-whoom moments.  In social systems, you must be mindful of the level of diversity.
  • Beware of forecasters.  Especially for phase transitions, forecasts are generally dismal.
  • Mitigate the downside, capture the upside.  One of the Kelly criterion’s central lessons is that betting too much in a system with extreme outcomes leads to ruin.

 

SORTING LUCK FROM SKILL

In areas such as business, investing, and sports, people make predictable and natural mistakes when it comes to distinguishing skill from luck.  Consider reversion to the mean:

The idea is that for many types of systems, an outcome that is not average will be followed by an outcome that has an expected value closer to the average.  While most people recognize the idea of reversion to the mean, they often ignore or misunderstand the concept, leading to a slew of mistakes in their analysis.

Reversion to the mean was discovered by the Victorian polymath Francis Galton, a cousin of Charles Darwin.  For instance, Dalton found that tall parents tend to have children that are tall, but not as talltheir heights are closer to the mean.  Similarly, short parents tend to have children that are short, but not as shorttheir heights are closer to the mean.

Yet it’s equally true that tall people have parents that are tall, but not as tallthe parents’ heights are closer to the mean.  Similarly, short people have parents that are short, but not as shorttheir heights are closer to the mean.  Thus, Dalton’s crucial insight was that the overall distribution of heights remains stable over time: the proportions of the population in every height category was stable as one looks forward or backward in time.

Skill, Luck, and Outcomes

Mauboussin writes that Daniel Kahneman was asked to offer a formula for the twenty-first century.  Kahneman gave two formulas:

Success = Some talent + luck

Great success = Some talent + a lot of luck

Consider an excellent golfer who scores well below her handicap during the first round.  What do you predict will happen in the second round?  We expect the golfer to have a score closer to her handicap for the second round because we expect there to be less luck compared to the first round.

Illustration by iQoncept

When you think about great streaks in sports like baseball, the record streak always belongs to a very talented player.  So a record streak is a lot of talent plus a lot of luck.

 

TIME TO THINK TWICE

You don’t need to think twice before every decision.  The stakes for most decisions are low.  And even when the stakes are high, the best decision is often obvious enough.

The value of Think Twice is in situations with high stakes where your natural decision-making process will typically lead to a suboptimal choice.  Some final thoughts:

Raise Your Awareness

As Kahneman has written, it is much easier to notice decision-making mistakes in others than in ourselves.  So pay careful attention not only to others, but also to yourself.

It is difficult to think clearly about many problems.  Furthermore, after outcomes have occurred, hindsight bias causes many of us to erroneously recall that we assigned the outcome a much higher probability than we actually did ex ante.

Put Yourself in the Shoes of Others

Embracing the outside view is typically essential when making an important probabilistic decision.  Although the situation may be new for us, there are many others who have gone through similar things.

When it comes to understanding the behavior of individuals, often the situationor specific, powerful incentivescan overwhelm otherwise good people.

Also, be careful when trying to understand or to manage a complex adaptive system, whether an ecosystem or the economy.

Finally, leaders must develop empathy for people.

Recognize the Role of Skill and Luck

When luck plays a significant role, anticipate reversion to the mean: extreme outcomes are followed by more average outcomes.

Short-term investment results reflect a great deal of randomness.

Get Feedback

Timely, accurate, and clear feedback is central to deliberate practice, which is the path to gaining expertise.  The challenge is that in some fields, like long-term investing, most of the feedback comes with a fairly large time lag.

For investors, it is quite helpful to keep a journal detailing the reasons for every investment decision.  (If you have the time, you can also write down how you feel physically and mentally at the time of each decision.)

 

(Photo by Vinay_Mathew)

A well-kept journal allows you to clearly audit your investment decisions.  Otherwise, most of us will lose any ability to recall accurately why we made the decisions we did.  This predictable memory lossin the absence of careful written recordsis often associated with hindsight bias.

It’s essential to identifyregardless of the outcomewhen you have made a good decision and when you have made a bad decision.  A good decision means that you faithfully followed a solid, proven process.

Another benefit of a well-kept investment journal is that you will start to notice other factors or patterns associated with bad investment decisions.  For instance, too much stress or too much fatigue is often associated with poorer decisions.  On the other hand, a good mood is often associated with overconfident decisions.

Mauboussin mentions a story told by Josh Waitzkin about Tigran Petrosian, a former World Chess Champion:

“When playing matches lasting days or weeks, Petrosian would wake up and sit quietly in his room, carefully assessing his own mood.  He then built his game plan for the day based on that mood, with great success.  A journal can provide a structured tool for similar introspection.”

Create a Checklist

Mauboussin:

When you face a tough decision, you want to be able to think clearly about what you might inadvertently overlook.  That’s where a decision checklist can be beneficial.

Photo by Andrey Popov

Mauboussin again:

A good checklist balances two opposing objectives.  It should be general enough to allow for varying conditions, yet specific enough to guide action.  Finding this balance means a checklist should not be too long; ideally, you should be able to fit it on one or two pages.

If you have yet to create a checklist, try it and see which issues surface.  Concentrate on steps or procedures, and ask where decisions have gone off track before.  And recognize that errors are often the result of neglecting a step, not from executing the other steps poorly.

Perform a Premortem

Mauboussin explains:

You assume you are in the future and the decision you made has failed.  You then provide plausible reasons for that failure.  In effect, you try to identify why your decision might lead to a poor outcome before you make the decision.  Klein’s research shows that premortems help people identify a greater number of potential problems than other techniques and encourage more open exchange, because no one individual or group has invested in a decision yet.

…You can track your individual or group premortems in your decision journal.  Watching for the possible sources of failure may also reveal early signs of trouble.

Know What You Can’t Know

  • In decisions that involve a system with many interacting parts, causal links are frequently unclear…. Remember what Warren Buffet said: ‘Virtually all surprises are unpleasant.’  So considering the worst-case scenarios is vital and generally overlooked in prosperous times.
  • Also, resist the temptation to treat a complex system as if it’s simpler than it is…. We can trace most of the large financial disasters to a model that failed to capture the richness of outcomes inherent in a complex system like the stock market.

Mauboussin notes a paradox with decision making: Nearly everyone realizes its importance, but hardly anyone practices (or keeps a journal).  Mauboussin concludes:

There are common and identifiable mistakes that you can understand, see in your daily affairs, and manage effectively.  In those cases, the correct approach to deciding well often conflicts with what your mind naturally does.  But now that you know when to think twice, better decisions will follow.  So prepare your mind, recognize the context, apply the right techniqueand practice.

 

BOOLE MICROCAP FUND

An equal weighted group of micro caps generally far outperforms an equal weighted (or cap-weighted) group of larger stocks over time.  See the historical chart here:  http://boolefund.com/best-performers-microcap-stocks/

This outperformance increases significantly by focusing on cheap micro caps.  Performance can be further boosted by isolating cheap microcap companies that show improving fundamentals.  We rank microcap stocks based on these and similar criteria.

There are roughly 10-20 positions in the portfolio.  The size of each position is determined by its rank.  Typically the largest position is 15-20% (at cost), while the average position is 8-10% (at cost).  Positions are held for 3 to 5 years unless a stock approaches intrinsic value sooner or an error has been discovered.

The goal of the Boole Microcap Fund is to outperform the Russell Microcap Index over time, net of fees.  The Boole Fund has low fees. 

 

If you are interested in finding out more, please e-mail me or leave a comment.

My e-mail: jb@boolefund.com

 

 

 

Disclosures: Past performance is not a guarantee or a reliable indicator of future results. All investments contain risk and may lose value. This material is distributed for informational purposes only. Forecasts, estimates, and certain information contained herein should not be considered as investment advice or a recommendation of any particular security, strategy or investment product. Information contained herein has been obtained from sources believed to be reliable, but not guaranteed. No part of this article may be reproduced in any form, or referred to in any other publication, without express written permission of Boole Capital, LLC.

Invest Like Sherlock Holmes

(Image:  Zen Buddha Silence by Marilyn Barbone.)

September 16, 2018

Robert G. Hagstrom has written a number of excellent books on investing.  One of his best is The Detective and the Investor  (Texere, 2002).

Many investors are too focused on the short term, are overwhelmed with information, take shortcuts, or fall prey to cognitive biases.  Hagstrom argues that investors can learn from the Great Detectives as well as from top investigative journalists.

Great detectives very patiently gather information from a wide variety of sources.  They discard facts that turn out to be irrelevant and keep looking for new facts that are relevant.  They painstakingly use logic to analyze the given information and reach the correct conclusion.  They’re quite willing to discard a hypothesis, no matter how well-supported, if new facts lead in a different direction.

(Illustration of Sherlock Holmes by Sidney Paget (1891), via Wikimedia Commons)

Top investigative journalists follow a similar method.

Outline for this blog post:

  • The Detective and the Investor
  • Auguste Dupin
  • Jonathan Laing and Sunbeam
  • Top Investigative Journalists
  • Edna Buchanan—Pulitzer Prize Winner
  • Sherlock Holmes
  • Arthur Conan Doyle
  • Holmes on Wall Street
  • Father Brown
  • How to Become a Great Detective

The first Great Detective is Auguste Dupin, an invention of Edgar Allan Poe.  The financial journalist Jonathan Laing’s patient and logical analysis of the Sunbeam Corporation bears similarity to Dupin’s methods.

Top investigative journalists are great detectives.  The Pulitzer Prize-winning journalist Edna Buchanan is an excellent example.

Sherlock Holmes is the most famous Great Detective.  Holmes was invented by Dr. Arthur Conan Doyle.

Last but not least, Father Brown is the third Great Detective discussed by Hagstrom.  Father Brown was invented by G. K. Chesterton.

The last section—How To Become a Great Detective—sums up what you as an investor can learn from the three Great Detectives.

 

THE DETECTIVE AND THE INVESTOR

Hagstrom writes that many investors, both professional and amateur, have fallen into bad habits, including the following:

  • Short-term thinking: Many professional investors advertise their short-term track records, and many clients sign up on this basis.  But short-term performance is largely random, and usually cannot be maintained.  What matters (at a minimum) is performance over rolling five-year periods.
  • Infatuation with speculation: Speculation is guessing what other investors will do in the short term.  Investing, on the other hand, is figuring out the value of a given business and only buying when the price is well below that value.
  • Overload of information: The internet has led to an overabundance of information.  This makes it crucial that you, as an investor, know how to interpret and analyze the information.
  • Mental shortcuts: We know from Daniel Kahneman (see Thinking, Fast and Slow) that most people rely on System 1 (intuition) rather than System 2 (logic and math) when making decisions under uncertainty.  Most investors jump to conclusions based on easy explanations, and then—due to confirmation bias—only see evidence that supports their conclusions.
  • Emotional potholes: In addition to confirmation bias, investors suffer from overconfidence, hindsight bias, loss aversion, and several other cognitive biases.  These cognitive biases regularly cause investors to make mistakes in their investment decisions.  I wrote about cognitive biases here: http://boolefund.com/cognitive-biases/

How can investors develop better habits?  Hagstrom:

The core premise of this book is that the same mental skills that characterize a good detective also characterize a good investor… To say this another way, the analytical methods displayed by the best fictional detectives are in fact high-level decision-making tools that can be learned and applied to the investment world.

(Illustration of Sherlock Holmes by Sidney Paget, via Wikimedia Commons)

Hagstrom asks if it is possible to combine the methods of the three Great Detectives.  If so, what would the ideal detective’s approach to investing be?

First, our investor-detective would have to keep an open mind, be prepared to analyze each new opportunity without any preset opinions.  He or she would be well versed in the basic methods of inquiry, and so would avoid making any premature and possibly inaccurate assumptions.  Of course, our investor-detective would presume that the truth might be hidden below the surface and so would distrust the obvious.  The investor-detective would operate with cool calculation and not allow emotions to distract clear thinking.  The investor-detective would also be able to deconstruct the complex situation into its analyzable parts.  And perhaps most important, our investor-detective would have a passion for truth, and, driven by a nagging premonition that things are not what they seem to be, would keep digging away until all the evidence had been uncovered.

 

AUGUSTE DUPIN

(Illustration—by Frédéric Théodore Lix—to The Purloined Letter, via Wikimedia Commons)

The Murders in the Rue Morgue exemplifies Dupin’s skill as a detective.  The case involves Madame L’Espanaye and her daughter.  Madame L’Espanaye was found behind the house in the yard with multiple broken bones and her head almost severed.  The daughter was found strangled to death and stuffed upside down into a chimney.  The murders occurred in a fourth-floor room that was locked from the inside.  On the floor were a bloody straight razor, several bloody tufts of grey hair, and two bags of gold coins.

Several witnesses heard voices, but no one could say for sure which language it was.  After deliberation, Dupin concludes that they must not have been hearing a human voice at all.  He also dismisses the possibility of robbery, since the gold coins weren’t taken.  Moreover, the murderer would have to possess superhuman strength to stuff the daughter’s body up the chimney.  As for getting into a locked room, the murderer could have gotten in through a window.  Finally, Dupin demonstrates that the daughter could not have been strangled by a human hand.  Dupin concludes that Madame L’Espanaye and her daughter were killed by an orangutan.

Dupin places an advertisement in the local newspaper asking if anyone had lost an orangutan.  A sailor arrives looking for it.  The sailor explains that he had seen the orangutan with a razor, imitating the sailor shaving.  The orangutan had then fled.  Once it got into the room with Madame L’Espanaye and her daughter, the orangutan probably grabbed Madame’s hair and was waving the razor, imitating a barber.  When the woman screamed in fear, the orangutan grew furious and killed her and her daughter.

Thus Dupin solves what at first seemed like an impossible case.  The solution is completely unexpected but is the only logical possibility, given all the facts.

Hagstrom writes that investors can learn important lessons from the Great Detective Auguste Dupin:

First, look in all directions, observe carefully and thoughtfully everything you see, and do not make assumptions from inadequate information.  On the other hand, do not blindly accept what you find.  Whatever you read, hear, or overhear about a certain stock or company may not necessarily be true.  Keep on with your research;  give yourself time to dig beneath the surface.

If you’re a small investor, it’s often best to invest in microcap stocks.  (This presumes that you have access to a proven investment process.)  There are hundreds of tiny companies much too small for most professional investors even to consider.  Thus, there is much more mispricing among micro caps.  Moreover, many microcap companies are relatively easy to analyze and understand.  (The Boole Microcap Fund invests in microcap companies.)

 

JONATHAN LAING AND SUNBEAM

(Sunbeam logo, via Wikimedia Commons)

Hagstrom writes that, in the spring of 1997, Wall Street was in love with the self-proclaimed ‘turnaround genius’ Al Dunlap.  Dunlap was asked to take over the troubled Sunbeam Corporation, a maker of electric home appliances.  Dunlap would repeat the strategy he used on previous turnarounds:

[Drive] up the stock price by any means necessary, sell the company, and cash in his stock options at the inflated price.

Although Dunlap made massive cost cuts, some journalists were skeptical, viewing Sunbeam as being in a weak competitive position in a harsh industry.  Jonathan Laing of Barron’s, in particular, took a close look at Sunbeam.  Laing focused on accounting practices:

First, Laing pointed out that Sunbeam took a huge restructuring charge ($337 million) in the last quarter of 1996, resulting in a net loss for the year of $228.3 million.  The charges included moving reserves from 1996 to 1997 (where they could later be recharacterized as income);  prepaying advertising expenses to make the new year’s numbers look better;  a suspiciously high charge for bad-debt allowance;  a $90 million write-off for inventory that, if sold at a later date, could turn up in future profits;  and write-offs for plants, equipment, and trademarks used by business lines that were still operating.

To Laing, it looked very much like Sunbeam was trying to find every possible way to transfer 1997 projected losses to 1996 (and write 1996 off as a lost year, claiming it was ruined by previous management) while at the same time switching 1996 income into 1997…

(Photo by Evgeny Ivanov)

Hagstrom continues:

Even though Sunbeam’s first-quarter 1997 numbers did indeed show a strong increase in sales volume, Laing had collected evidence that the company was engaging in the practice known as ‘inventory stuffing’—getting retailers to place abnormally large orders either through high-pressure sales tactics or by offering them deep discounts (using the written-off inventory from 1996).  Looking closely at Sunbeam’s financial reports, Laing also found a hodgepodge of other maneuvers designed to boost sales numbers, such as delaying delivery of sales made in 1996 so they could go on the books as 1997 sales, shipping more units than the customer had actually ordered, and counting as sales orders that had already been canceled.

The bottom line was simply that much of 1997’s results would be artificial.  Hagstrom summarizes the lesson from Dupin and Laing:

The core lesson for investors here can be expressed simply:  Take nothing for granted, whether it comes from the prefect of police or the CEO of a major corporation.  This is, in fact, a key theme of this chapter.  If something doesn’t make sense to you—no matter who says it—that’s your cue to start digging.

By July 1998, Sunbeam stock had lost 80 percent of its value and was lower than when Dunlap took over.  The board of directors fired Dunlap and admitted that its 1997 financial statements were unreliable and were being audited by a new accounting firm.  In February 2001, Sunbeam filed for Chapter 11 bankruptcy protection.  On May 15, 2001, the Securities and Exchange Commission filed suit against Dunlap and four senior Sunbeam executives, along with their accounting firm, Arthur Andersen.  The SEC charged them with a fraudulent scheme to create the illusion of a successful restructuring.

Hagstrom points out what made Laing successful as an investigative journalist:

He read more background material, dissected more financial statements, talked to more people, and painstakingly pieced together what many others failed to see.

 

TOP INVESTIGATIVE JOURNALISTS

Hagstrom mentions Professor Linn B. Washington, Jr., a talented teacher and experienced investigative reporter.  (Washington was awarded the Robert F. Kennedy Prize for his series of articles on drug wars in the Richard Allen housing project.)  Hagstrom quotes Washington:

Investigative journalism is not a nine-to-five job.  All good investigative journalists are first and foremost hard workers.  They are diggers.  They don’t stop at the first thing they come to but rather they feel a need to persist.  They are often passionate about the story they are working on and this passion helps fuel the relentless pursuit of information.  You can’t teach that.  They either have it or they don’t.

…I think most reporters have a sense of morality.  They are outraged by corruption and they believe their investigations have a real purpose, an almost sacred duty to fulfill.  Good investigative reporters want to right the wrong, to fight for the underdog.  And they believe there is a real responsibility attached to the First Amendment.

(Photo by Robyn Mackenzie)

Hagstrom then refers to The Reporter’s Handbook, written by Steve Weinberg for investigative journalists.  Weinberg maintains that gathering information involves two categories: documents and people.  Hagstrom:

Weinberg asks readers to imagine three concentric circles.  The outmost one is ‘secondary sources,’ the middle one ‘primary sources.’  Both are composed primarily of documents.  The inner circle, ‘human sources,’ is made up of people—a wide range of individuals who hold some tidbit of information to add to the picture the reporter is building.

Ideally, the reporter starts with secondary sources and then primary sources:

At these two levels of the investigation, the best reporters rely on what has been called a ‘documents state of mind.’  This way of looking at the world has been articulated by James Steele and Donald Bartlett, an investigative team from the Philadephia Inquirer.  It means that the reporter starts from day one with the belief that a good record exists somewhere, just waiting to be found.

Once good background knowledge is accumulated from all the primary and secondary documents, the reporter is ready to turn to the human sources…

Photo by intheskies

Time equals truth:

As they start down this research track, reporters also need to remember another vital concept from the handbook:  ‘Time equals truth.’  Doing a complete job of research takes time, whether the researcher is a reporter following a story or an investor following a company—or for that matter, a detective following the evidence at a crime scene.  Journalists, investors, and detectives must always keep in mind that the degree of truth one finds is directly proportional to the amount of time one spends in the search.  The road to truth permits no shortcuts.

The Reporter’s Handbook also urges reporters to question conventional wisdom, to remember that whatever they learn in their investigation may be biased, superficial, self-serving for the source, or just plain wrong.  It’s another way of saying ‘Take nothing for granted.’  It is the journalist’s responsibility—and the investor’s—to penetrate the conventional wisdom and find what is on the other side.

The three concepts discussed above—‘adopt a documents state of mind,’ ‘time equals truth,’ and ‘question conventional wisdom;  take nothing for granted’—may be key operating principles for journalists, but I see them also as new watchwords for investors.

 

EDNA BUCHANAN—PULITZER PRIZE WINNER

Edna Buchanan, working for the Miami Herald and covering the police beat, won a Pulitzer Prize in 1986.  Hagstrom lists some of Buchanan’s principles:

  • Do a complete background check on all the key players.  Find out how a person treats employees, women, the environment, animals, and strangers who can do nothing for them.  Discover if they have a history of unethical and/or illegal behavior.
  • Cast a wide net.  Talk to as many people as you possibly can.  There is always more information.  You just have to find it.  Often that requires being creative.
  • Take the time.  Learning the truth is proportional to the time and effort you invest.  There is always more that you can do.  And you may uncover something crucial.  Never take shortcuts.
  • Use common sense.  Often official promises and pronouncements simply don’t fit the evidence.  Often people lie, whether due to conformity to the crowd, peer pressure, loyalty (like those trying to protect Nixon et al. during Watergate), trying to protect themselves, fear, or any number of reasons.  As for investing, some stories take a long time to figure out, while other stories (especially for tiny companies) are relatively simple.
  • Take no one’s word.  Find out for yourself.  Always be skeptical and read between the lines.  Very often official press releases have been vetted by lawyers and leave out critical information.  Take nothing for granted.
  • Double-check your facts, and then check them again.  For a good reporter, double-checking facts is like breathing.  Find multiples sources of information.  Again, there are no shortcuts.  If you’re an investor, you usually need the full range of good information in order to make a good decision.

In most situations, to get it right requires a great deal of work.  You must look for information from a broad range of sources.  Typically you will find differing opinions.  Not all information has the same value.  Always be skeptical of conventional wisdom, or what ‘everybody knows.’

 

SHERLOCK HOLMES

Image by snaptitude

Sherlock Holmes approaches every problem by following three steps:

  • First, he makes a calm, meticulous examination of the situation, taking care to remain objective and avoid the undue influence of emotion.  Nothing, not even the tiniest detail, escapes his keen eye.
  • Next, he takes what he observes and puts it in context by incorporating elements from his existing store of knowledge.  From his encyclopedic mind, he extracts information about the thing observed that enables him to understand its significance.
  • Finally, he evaluates what he observed in the light of this context and, using sound deductive reasoning, analyzes what it means to come up with the answer.

These steps occur and re-occur in an iterative search for all the facts and for the best hypothesis.

There was a case involving a young doctor, Percy Trevelyan.  Some time ago, an older gentleman named Blessington offered to set up a medical practice for Trevelyan in return for a share of the profits.  Trevelyan agreed.

A patient suffering from catalepsy—a specialty of the doctor—came to the doctor’s office one day.  The patient also had his son with him.  During the examination, the patient suffered a cataleptic attack.  The doctor ran from the room to grab the treatment medicine.  But when he got back, the patient and his son were gone.  The two men returned the following day, giving a reasonable explanation for the mix-up, and the exam continued.  (On both visits, the son had stayed in the waiting room.)

Shortly after the second visit, Blessington burst into the exam room, demanding to know who had been in his private rooms.  The doctor tried to assure him that no one had.  But upon going to Blessington’s room, he saw a strange set of footprints.  Only after Trevelyan promises to bring Sherlock Holmes to the case does Blessington calm down.

Holmes talks with Blessington.  Blessington claims not to know who is after him, but Holmes can tell that he is lying.  Holmes later tells his assistant Watson that the patient and his son were fakes and had some sinister reason for wanting to get Blessington.

Holmes is right.  The next morning, Holmes and Watson are called to the house again.  This time, Blessington is dead, apparently having hung himself.

But Holmes deduces that it wasn’t a suicide but a murder.  For one thing, there were four cigar butts found in the fireplace, which led the policeman to conclude that Blessington had stayed up late agonizing over his decision.  But Holmes recognizes that Blessington’s cigar is a Havana, but the other three cigars had been imported by the Dutch from East India.  Furthermore, two had been smoked from a holder and two without.  So there were at least two other people in the room with Blessington.

Holmes does his usual very methodical examination of the room and the house.  He finds three sets of footprints on the stairs, clearly showing that three men had crept up the stairs.  The men had forced the lock, as Holmes deduced from scratches on it.

Holmes also realized the three men had come to commit murder.  There was a screwdriver left behind.  And he could further deduce (by the ashes dropped) where each man sat as the three men deliberated over how to kill Blessington.  Eventually, they hung Blessington.  Two killers left the house and the third barred the door, implying that the third murderer must be a part of the doctor’s household.

All these signs were visible:  the three sets of footprints, the scratches on the lock, the cigars that were not Blessington’s type, the screwdriver, the fact that the front door was barred when the police arrived.  But it took Holmes to put them all together and deduce their meaning:  murder, not suicide.  As Holmes himself remarked in another context, ‘The world is full of obvious things which nobody by any chance ever observes.’

…He knows Blessington was killed by people well known to him.  He also knows, from Trevelyan’s description, what the fake patient and his son look like.  And he has found a photograph of Blessington in the apartment.  A quick stop at policy headquarters is all Holmes needs to pinpoint their identity.  The killers, no strangers to the police, were a gang of bank robbers who had gone to prison after being betrayed by their partner, who then took off with all the money—the very money he used to set Dr. Trevelyan up in practice.  Recently released from prison, the gang tracked Blessington down and finally executed him.

Spelled out thus, one logical point after another, it seems a simple solution.  Indeed, that is Holmes’s genius:  Everything IS simple, once he explains it.

Hagstrom then adds:

Holmes operates from the presumption that all things are explainable;  that the clues are always present, awaiting discovery. 

The first step—gathering all the facts—usually requires a great deal of careful effort and attention.  One single fact can be the key to deducing the true hypothesis.  The current hypothesis is revisable if there may be relevant facts not yet known.  Therefore, a heightened degree of awareness is always essential.  With practice, a heightened state of alertness becomes natural for the detective (or the investor).

“Details contain the vital essence of the whole matter.” — Sherlock Holmes

Moreover, it’s essential to keep emotion out of the process of discovery:

One reason Holmes is able to see fully what others miss is that he maintains a level of detached objectivity toward the people involved.  He is careful not to be unduly influenced by emotion, but to look at the facts with calm, dispassionate regard.  He sees everything that is there—and nothing that is not.  For Holmes knows that when emotion seeps in, one’s vision of what is true can become compromised.  As he once remarked to Dr. Watson, ‘Emotional qualities are antagonistic to clear reasoning… Detection is, or ought to be, an exact science and should be treated in the same cold and unemotional manner.  You have attempted to tinge it with romanticism, which produces much the same effect as if you worked a love story or an elopement into the fifth proposition of Euclid.’

Image by snaptitude

Holmes himself is rather aloof and even antisocial, which helps him to maintain objectivity when collecting and analyzing data.

‘I make a point of never having any prejudices and of following docilely wherever fact may lead me.’  He starts, that is, with no preformed idea, and merely collects data.  But it is part of Holmes’s brilliance that he does not settle for the easy answer.  Even when he has gathered together enough facts to suggest one logical possibility, he always knows that this answer may not be the correct one.  He keeps searching until he has found everything, even if subsequent facts point in another direction.  He does not reject the new facts simply because they’re antithetical to what he’s already found, as so many others might.

Hagstrom observes that many investors are susceptible to confirmation bias:

…Ironically, it is the investors eager to do their homework who may be the most susceptible.  At a certain point in their research, they have collected enough information that a pattern becomes clear, and they assume they have found the answer.  If subsequent information then contradicts that pattern, they cannot bring themselves to abandon the theory they worked so hard to develop, so they reject the new facts.

Gathering information about an investment you are considering means gather all the information, no matter where it ultimately leads you.  If you find something that does not fit your original thesis, don’t discard the new information—change the thesis.

 

ARTHUR CONAN DOYLE

Arthur Conan Doyle was a Scottish doctor.  One of his professors, Dr. Bell, challenged his students to hone their skills of observation.  Bell believed that a correct diagnosis required alert attention to all aspects of the patient, not just the stated problem.  Doyle later worked for Dr. Bell.  Doyle’s job was to note the patients’ problem along with all possibly relevant details.

Doyle had a very slow start as a doctor.  He had virtually no patients.  He spent his spare time writing, which he had loved doing since boarding school.  Doyle’s main interest was historical fiction.  But he didn’t get much money from what he wrote.

One day he wrote a short novel, A Study in Scarlet, which introduced a private detective, Sherlock Holmes.  Hagstrom quotes Doyle:

I thought I would try my hand at writing a story where the hero would treat crime as Dr. Bell treated disease, and where science would take the place of chance.

Doyle soon realized that he might be able to sell short stories about Sherlock Holmes as a way to get some extra income.  Doyle preferred historical novels, but his short stories about Sherlock Holmes started selling surprisingly well.  Because Doyle continued to emphasize historical novels and the practice of medicine, he demanded higher and higher fees for his short stories about Sherlock Holmes.  But the stories were so popular that magazine editors kept agreeing to the fee increases.

Photo by davehanlon

Soon thereafter, Doyle, having hardly a single patient, decided to abandon medicine and focus on writing.  Doyle still wanted to do other types of writing besides the short stories.  He asked for a very large sum for the Sherlock Holmes stories so that the editors would stop bothering him.  Instead, the editors immediately agreed to the huge fee.

Many years later, Doyle was quite tired of Holmes and Watson after having written fifty-six short stories and four novels about them.  But readers never could get enough.  And the stories are still highly popular to this day, which attests to Doyle’s genius.  Doyle has always been credited with launching the tradition of the scientific sleuth.

 

HOLMES ON WALL STREET

Sherlock Holmes is the most famous Great Detective for good reason.  He is exceptionally thorough, unemotional, and logical.

Holmes knows a great deal about many different things, which is essential in order for him to arrange and analyze all the facts:

The list of things Holmes knows about is staggering:  the typefaces used by different newspapers, what the shape of a skull reveals about race, the geography of London, the configuration of railway lines in cities versus suburbs, and the types of knots used by sailors, for a few examples.  He has authored numerous scientific monographs on such topics as tattoos, ciphers, tobacco ash, variations in human ears, what can be learned from typewriter keys, preserving footprints with plaster of Paris, how a man’s trade affects the shape of his hands, and what a dog’s manner can reveal about the character of its owner.

(Illustration of Sherlock Holmes with various tools, by Elena Kreys)

Consider what Holmes says about his monograph on the subject of tobacco:

“In it I enumerate 140 forms of cigar, cigarette, and pipe tobacco… It is sometimes of supreme importance as a clue.  If you can say definitely, for example, that some murder has been done by a man who was smoking an Indian lunkah, it obviously narrows your field of search.”

It’s very important to keep gathering and re-gathering facts to ensure that you haven’t missed anything.  Holmes:

“It is a capital mistake to theorize before you have all the evidence.  It biases the judgment.”

“The temptation to form premature theories upon insufficient data is the bane of our profession.”

Although gathering all facts is essential, at the same time, you must be organizing those facts since not all facts are relevant to the case at hand.  Of course, this is an iterative process. You may discard a fact as irrelevant and realize later that it is relevant.

Part of the sorting process involves a logical analysis of various combinations of facts.  You reject combinations that are logically impossible.  As Holmes famously said:

“When you have eliminated the impossible, whatever remains, however improbable, must be the truth.”

Often there is more than one logical possibility that is consistent with the known facts.  Be careful not to be deceived by obvious hypotheses.  Often what is ‘obvious’ is completely wrong.

Sometimes finding the solution requires additional research.  Entertaining several possible hypotheses may also be required.  Holmes:

“When you follow two separate chains of thought you will find some point of intersection which should approximate to the truth.”

But be careful to keep facts and hypotheses separate, as Holmes asserts:

“The difficulty is to detach the frame of absolute undeniable facts from the embellishments of theorists.  Then, having established ourselves upon this sound basis, it is our duty to see what inferences may be drawn and what are the special points upon which the whole mystery turns.”

For example, there was a case involving the disappearance of a valuable racehorse.  The chief undeniable fact was that the dog did not bark, which meant that the intruder had to be familiar to the dog.

Sherlock Holmes As Investor

How would Holmes approach investing?  Hagstrom:

Here’s what we know of his methods:  He begins an examination with an objective mind, untainted by prejudice.  He observes acutely and catalogues all the information, down to the tiniest detail, and draws on his broad knowledge to put those details into context.  Then, armed with the facts, he walks logically, rationally, thoughtfully toward a conclusion, always on the lookout for new, sometimes contrary information that might alter the outcome.

It’s worth repeating that much of the process of gathering facts can be tedious and boring.  This is the price you must pay to ensure you get all the facts.  Similarly, analyzing all the facts often requires patience and can take a long time.  No shortcuts.

 

FATHER BROWN

Hagstrom opens the chapter with a scene in which Aristide Valentin—head of Paris police and the most famous investigator in Europe—is chasing Hercule Flambeau, a wealthy and famous French jewel thief.  Both Valentin and Flambeau are on the same train.  But Valentin gets distracted by the behavior of a very short Catholic priest with a round face.  The priest is carrying several brown paper parcels, and he keeps dropping one or the other, or dropping his umbrella.

When the train reaches London, Valentin isn’t exactly sure where Flambeau went.  So Valentin decides to go systematically to the ‘wrong places.’  Valentin ends up at a certain restaurant that caught his attention.  A sugar bowl has salt in it, while the saltcellar contains sugar.  He learns from a waiter that two clergymen had been there earlier, and that one had thrown a half-empty cup of soup against the wall.  Valentin inquires which way the priests went.

Valentin goes to Carstairs Street.  He passes a greengrocer’s stand where the signs for oranges and nuts have been switched.  The owner is still upset about a recent incident in which a parson knocked over his bin of apples.

Valentin keeps looking and notices a restaurant that has a broken window.  He questions the waiter, who explains to him that two foreign parsons had been there.  Apparently, they overpaid.  The waiter told the two parsons of their mistake, at which point one parson said, ‘Sorry for the confusion.  But the extra amount will pay for the window I’m about to break.’  Then the parson broke the window.

Valentin finally ends up in a public park, where he sees two men, one short and one tall, both wearing clerical garb.  Valentin approaches and recognizes that the short man is the same clumsy priest from the train.  The short priest suspected all along that the tall man was not a priest but a criminal.  The short priest, Father Brown, had left the trail of hints for the police.  At that moment, even without turning around, Father Brown knew the police were nearby ready to arrest Flambeau.

Father Brown was invented by G. K. Chesterton.  Father Brown is very compassionate and has deep insight into human psychology, which often helps him to solve crimes.

He knows, from hearing confessions and ministering in times of trouble, how people act when they have done something wrong.  From observing a person’s behavior—facial expressions, ways of walking and talking, general demeanor—he can tell much about that person.  In a word, he can see inside someone’s heart and mind, and form a clear impression about character…

His feats of detection have their roots in this knowledge of human nature, which comes from two sources:  his years in the confessional, and his own self-awareness.  What makes Father Brown truly exceptional is that he acknowledges the capacity for evildoing in himself.  In ‘The Hammer of God’ he says, ‘I am a man and therefore have all devils in my heart.’

Because of this compassionate understanding of human weakness, from both within and without, he can see into the darkest corners of the human heart.  The ability to identify with the criminal, to feel what he is feeling, is what leads him to find the identity of the criminal—even, sometimes, to predict the crime, for he knows the point at which human emotions such as fear or jealousy tip over from acceptable expression into crime.  Even then, he believes in the inherent goodness of mankind, and sets the redemption of the wrongdoer as his main goal.

While Father Brown excels in understanding human psychology, he also excels at logical analysis of the facts.  He is always open to alternative explanations.

(Frontispiece to G. K. Chesterton’s The Wisdom of Father Brown, Illustration by Sydney Semour Lucas, via Wikimedia Commons)

Later the great thief Flambeau is persuaded by Father Brown to give up a life of crime and become a private investigator.  Meanwhile, Valentin, the famous detective, turns to crime and nearly gets away with murder.  Chesterton loves such ironic twists.

Chesterton was a brilliant writer who wrote in an amazing number of different fields.  Chesterton was very compassionate, with a highly developed sense of social justice, notes Hagstrom.  The Father Brown stories are undoubtedly entertaining, but they also deal with questions of justice and morality.  Hagstrom quotes an admirer of Chesterton, who said:  ‘Sherlock Holmes fights criminals;  Father Brown fights the devil.’  Whenever possible, Father Brown wants the criminal to find redemption.

Hagstrom lists what could be Father Brown’s investment guidelines:

  • Look carefully at the circumstances;  do whatever it takes to gather all the clues.
  • Cultivate the understanding of intangibles.
  • Using both tangible and intangible evidence, develop such a full knowledge of potential investments that you can honestly say you know them inside out.
  • Trust your instincts.  Intuition is invaluable.
  • Remain open to the possibility that something else may be happening, something different from that which first appears; remember that the full truth may be hidden beneath the surface.

Hagstrom mentions that psychology can be useful for investing:

Just as Father Brown’s skill as an analytical detective was greatly improved by incorporating the study of psychology with the method of observations, so too can individuals improve their investment performance by combining the study of psychology with the physical evidence of financial statement analysis.

 

HOW TO BECOME A GREAT DETECTIVE

Hagstrom lists the habits of mind of the Great Detectives:

Auguste Dupin

  • Develop a skeptic’s mindset;  don’t automatically accept conventional wisdom.
  • Conduct a thorough investigation.

Sherlock Holmes

  • Begin an investigation with an objective and unemotional viewpoint.
  • Pay attention to the tiniest details.
  • Remain open-minded to new, even contrary, information.
  • Apply a process of logical reasoning to all you learn.

Father Brown

  • Become a student of psychology.
  • Have faith in your intuition.
  • Seek alternative explanations and re-descriptions.

Hagstrom argues that these habits of mind, if diligently and consistently applied, can help you to do better as an investor over time.

Furthermore, the true hero is reason, a lesson directly applicable to investing:

As I think back over all the mystery stories I have read, I realize there were many detectives but only one hero.  That hero is reason.  No matter who the detective was—Dupin, Holmes, Father Brown, Nero Wolfe, or any number of modern counterparts—it was reason that solved the crime and captured the criminal.  For the Great Detectives, reason is everything.  It controls their thinking, illuminates their investigation, and helps them solve the mystery.

Illustration by yadali

Hagstrom continues:

Now think of yourself as an investor.  Do you want greater insight about a perplexing market?  Reason will clarify your investment approach.

Do you want to escape the trap of irrational, emotion-based action and instead make decisions with calm deliberation?  Reason will steady your thinking.

Do you want to be in possession of all the relevant investment facts before making a purchase?  Reason will help you uncover the truth.

Do you want to improve your investment results by purchasing profitable stocks?  Reason will help you capture the market’s mispricing.

In sum, conduct a thorough investigation.  Painstakingly gather all the facts and keep your emotions entirely out of it.  Skeptically question conventional wisdom and ‘what is obvious.’  Carefully use logic to reason through possible hypotheses.  Eliminate hypotheses that cannot explain all the facts.  Stay open to new information and be willing to discard the best current hypothesis if new facts lead in a different direction.  Finally, be a student of psychology.

 

BOOLE MICROCAP FUND

An equal weighted group of micro caps generally far outperforms an equal weighted (or cap-weighted) group of larger stocks over time.  See the historical chart here:  http://boolefund.com/best-performers-microcap-stocks/

This outperformance increases significantly by focusing on cheap micro caps.  Performance can be further boosted by isolating cheap microcap companies that show improving fundamentals.  We rank microcap stocks based on these and similar criteria.

There are roughly 10-20 positions in the portfolio.  The size of each position is determined by its rank.  Typically the largest position is 15-20% (at cost), while the average position is 8-10% (at cost).  Positions are held for 3 to 5 years unless a stock approaches intrinsic value sooner or an error has been discovered.

The goal of the Boole Microcap Fund is to outperform the Russell Microcap Index over time, net of fees.  The Boole Fund has low fees. 

 

If you are interested in finding out more, please e-mail me or leave a comment.

My e-mail: jb@boolefund.com

 

 

 

Disclosures: Past performance is not a guarantee or a reliable indicator of future results. All investments contain risk and may lose value. This material is distributed for informational purposes only. Forecasts, estimates, and certain information contained herein should not be considered as investment advice or a recommendation of any particular security, strategy or investment product. Information contained herein has been obtained from sources believed to be reliable, but not guaranteed. No part of this article may be reproduced in any form, or referred to in any other publication, without express written permission of Boole Capital, LLC.

Kahneman and Tversky

(Image:  Zen Buddha Silence by Marilyn Barbone.)

September 2, 2018

If we’re more aware of cognitive biases today than a decade or two ago, that’s thanks in large part to the research of the Israeli psychologists Daniel Kahneman and Amos Tversky.  I’ve written about cognitive biases before, including:

I’ve seen few books that do a good job covering the work of Kahneman and Tversky.  The Undoing Project: A Friendship That Changed Our Minds, by Michael Lewis, is one such book.  (Lewis also writes well about the personal stories of Kahneman and Tversky.)

Why are cognitive biases important?  Economists, decision theorists, and others used to assume that people are rational.  Sure, people make mistakes.  But many scientists believed that mistakes are random: if some people happen to make mistakes in one direction—estimates that are too high—other people will (on average) make mistakes in the other direction—estimates that are too low.  Since the mistakes are random, they cancel out, and so the aggregate results in a given market will nevertheless be rational.  Markets are efficient.

For some markets, this is still true.  Francis Galton, the English Victorian-era polymath, wrote about a contest in which 787 people guessed at the weight of a large ox.  Most participants in the contest were not experts by any means, but ordinary people.  The ox actually weighed 1,198 pounds.  The average guess of the 787 guessers was 1,197 pounds, which was more accurate than the guesses made by the smartest and the most expert guessers.   The errors are completely random, and so they cancel out.

This type of experiment can easily be repeated.  For example, take a jar filled with pennies, where only you know how many pennies are in the jar.  Pass the jar around in a group of people and ask each person—independently (with no discussion)—to write down their guess of how many pennies are in the jar.  In a group that is large enough, you will nearly always discover that the average guess is better than any individual guess.  (That’s been the result when I’ve performed this experiment in classes I’ve taught.)

However, in other areas, people do not make random errors, but systematic errors.  This is what Kahneman and Tversky proved using carefully constructed experiments that have been repeated countless times.  In certain situations, many people will tend to make mistakes in the same direction—these mistakes do not cancel out.  This means that the aggregate results in a given market can sometimes be much less than fully rational.  Markets can be inefficient.

Outline (based on chapters from Lewis’s book):

  • Introduction
  • Man Boobs
  • The Outsider
  • The Insider
  • Errors
  • The Collision
  • The Mind’s Rules
  • The Rules of Prediction
  • Going Viral
  • Birth of the Warrior Psychologist
  • The Isolation Effect
  • This Cloud of Possibility

(Illustration by Alain Lacroix)

 

INTRODUCTION

In his 2003 book, Moneyball, Lewis writes about the Oakland Athletic’s efforts to find betters methods for valuing players and evaluating strategies.  By using statistical techniques, the team was able to perform better than many others teams even though the A’s had less money.  Lewis says:

A lot of people saw in Oakland’s approach to building a baseball team a more general lesson: If the highly paid, publicly scrutinized employees of a business that had existed since the 1860s could be misunderstood by their market, would couldn’t be?  If the market for baseball players was inefficient, what market couldn’t be?  If a fresh analytical approach had led to the discovery of new knowledge in baseball, was there any sphere of human activity in which it might not do the same?

After the publication of Moneyball, people started applying statistical techniques to other areas, such as education, movies, golf, farming, book publishing, presidential campaigns, and government.  However, Lewis hadn’t asked the question of what it was about the human mind that led experts to be wrong so often.  Why were simple statistical techniques so often better than experts?

The answer had to do with the structure of the human mind.  Lewis:

Where do the biases come from?  Why do people have them?  I’d set out to tell a story about the way markets worked, or failed to work, especially when they were valuing people.  But buried somewhere inside it was another story, one that I’d left unexplored and untold, about the way the human mind worked, or failed to work, when it was forming judgments and making decisions.  When faced with uncertainty—about investments or people or anything else—how did it arrive at its conclusions?  How did it process evidence—from a baseball game, an earnings report, a trial, a medical examination, or a speed date?  What were people’s minds doing—even the minds of supposed experts—that led them to the misjudgments that could be exploited for profit by others, who ignored the experts and relied on data?

 

MAN BOOBS

Daryl Morey, the general manager of the Houston Rockets, used statistical methods to make decisions, especially when it came to picking players for the team.  Lewis:

His job was to replace one form of decision making, which relied upon the intuition of basketball experts,  with another, which relied mainly on the analysis of data.  He had no serious basketball-playing experience and no interest in passing himself off as a jock or basketball insider.  He’d always been just the way he was, a person who was happier counting than feeling his way through life.  As a kid he’d cultivated an interest in using data to make predictions until it became a ruling obsession.

Lewis continues:

If he could predict the future performance of professional athletes, he could build winning sports teams… well, that’s where Daryl Morey’s mind came to rest.  All he wanted to do in life was build winning sports teams.

Morey found it difficult to get a job for a professional sports franchise.  He concluded that he’d have to get rich so that he could buy a team and run it.  Morey got an MBA, and then got a job consulting.  One important lesson Morey picked up was that part of a consultant’s job was to pretend to be totally certain about uncertain things.

There were a great many interesting questions in the world to which the only honest answer was, ‘It’s impossible to know for sure.’… That didn’t mean you gave up trying to find an answer; you just couched that answer in probabilistic terms.

Leslie Alexander, the owner of the Houston Rockets, had gotten disillusioned with the gut instincts of the team’s basketball experts.  That’s what led him to hire Morey.

Morey built a statistical model for predicting the future performance of basketball players.

A model allowed you to explore the attributes in an amateur basketball player that led to professional success, and determine how much weight should be given to each.

The central idea was that the model would usually give you a “better” answer than relying only on expert intuition.  That said, the model had to be monitored closely because sometimes it wouldn’t have important information.  For instance, a player might have had a serious injury right before the NBA draft.

(Illustration by fotomek)

Statistical and algorithmic approaches to decision making are more widespread now.  But back in 2006 when Morey got started, such an approach was not at all obvious.

In 2008, when the Rocket’s had the 33rd pick, Morey’s model led him to select Joey Dorsey.  Dorsey ended up not doing well at all.  Meanwhile, Morey’s model had passed over DeAndre Jordan, who ended up being chosen 35th by the Los Angeles Clippers.  DeAndre Jordan ended up being the second best player in the entire draft, after Russell Westbrook.  What had gone wrong?  Lewis comments:

This sort of thing happened every year to some NBA team, and usually to all of them.  Every year there were great players the scouts missed, and every year highly regarded players went bust.  Morey didn’t think his model was perfect, but he also couldn’t believe that it could be so drastically wrong.

Morey went back to the data and ended up improving his model.  For example, the improved model assigned greater weight to games played against strong opponents than against weak ones.  Lewis adds:

In the end, he decided that the Rockets needed to reduce to data, and subject to analysis, a lot of stuff that had never before been seriously analyzed: physical traits.  They needed to know not just how high a player jumped but how quickly he left the earth—how fast his muscles took him into the air.  They needed to measure not just the speed of the player but the quickness of his first two steps.

At the same time, Morey realized he had to listen to his basketball experts.  Morey focused on developing a process that relied both on the model and on human experts.  It was a matter of learning the strengths and weaknesses of the model, as well as the strengths and weaknesses of human experts.

But it wasn’t easy.  By letting human intuition play a role, that opened the door to more human mistakes.  In 2007, Morey’s model highly valued the player Marc Gasol.  But the scouts had seen a photo of Gasol without a shirt.  Gasol was pudgy with jiggly pecs.  The Rockets staff nicknamed Gasol “Man Boobs.”  Morey allowed this ridicule of Gasol’s body to cause him to ignore his statistical model.  The Rockets didn’t select Gasol.  The Los Angeles Lakers picked him 48th.  Gasol went on to be a two-time NBA All-Star.  From that point forward, Morey banned nicknames because they could interfere with good decision making.

Over time, Morey developed a list of biases that could distort human judgment: confirmation bias, the endowment effect, present bias, hindsight bias, et cetera.

 

THE OUTSIDER

Although Danny Kahneman had frequently delivered a semester of lectures from his head, without any notes, he nonetheless always doubted his own memory.  This tendency to doubt his own mind may have been central to his scientific discoveries in psychology.

But there was one experience he had while a kid that he clearly remembered.  In Paris, about a year after the Germans occupied the city, new laws required Jews to wear the Star of David.  Danny didn’t like this, so he wore his sweater inside out.  One evening while going home, he saw a German soldier with a black SS uniform.  The soldier had noticed Danny and picked him up and hugged him.  The soldier spoke in German, with great emotion.  Then he put Danny down, showed him a picture of a boy, and gave him some money.  Danny remarks:

I went home more certain than ever that my mother was right: people were endlessly complicated and interesting.

Another thing Danny remembers is when his father came home after being in  a concentration camp.  Danny and his mother had gone shopping, and his father was there when they returned.  Despite the fact that he was extremely thin—only ninety-nine pounds—Danny’s father had waited for them to arrive home before eating anything.  This impressed Danny.  A few years later, his father got sick and died.  Danny was angry.

Over time, Danny grew even more fascinated by people—why they thought and behaved as they did.

When Danny was thirteen years old, he moved with his mother and sister to Jerusalem.  Although it was dangerous—a bullet went through Danny’s bedroom—it seemed better because they felt they were fighting rather than being hunted.

On May 14, 1948, Israel declared itself a sovereign state.  The British soldiers immediately left.  The armies from Jordan, Syria, and Egypt—along with soldiers from Iraq and Lebanon—attacked.  The war of independence took ten months.

Because he was identified as intellectually gifted, Danny was permitted to go to university at age seventeen to study psychology.  Most of his professors were European refugees, people with interesting stories.

Danny wasn’t interested in Freud or in behaviorism.  He wanted objectivity.

The school of psychological thought that most charmed him was Gestalt psychology.  Led by German Jews—its origins were in the early twentieth century Berlin—it sought to explore, scientifically, the mysteries of the human mind.  The Gestalt psychologists had made careers uncovering interesting phenomena and demonstrating them with great flair: a light appeared brighter when it appeared from total darkness; the color gray looked green when it was surrounded by violet and yellow if surrounded by blue; if you said to a person, “Don’t step on the banana eel!,” he’d be sure that you had said not “eel” but “peel.”  The Gestalists showed that there was no obvious relationship between any external stimulus and the sensation it created in people, as the mind intervened in many curious ways.

(Two faces or a vase?  Illustration by Peter Hermes Furian)

Lewis continues:

The central question posed by Gestalt psychologists was the question behaviorists had elected to ignore: How does the brain create meaning?  How does it turn the fragments collected by the senses into a coherent picture of reality?  Why does the picture so often seem to be imposed by the mind upon the world around it, rather than by the world upon the mind?  How does a person turn the shards of memory into a coherent life story?  Why does a person’s understanding of what he sees change with the context in which he sees it?

In his second year at Hebrew Univeristy, Danny heard a fascinating talk by a German neurosurgeon.  This led Danny to abandon psychology in order to pursue a medical degree.   He wanted to study the brain.  But one of his professors convinced him it was only worth getting a medical degree if he wanted to be a doctor.

After getting a degree in psychology, Danny had to serve in the Israeli military.  The army assigned him to the psychology unit, since he wasn’t really cut out for combat.  The head of the unit at that time was a chemist.  Danny was the first psychologist to join.

Danny was put in charge of evaluating conscripts and assigning them to various roles in the army.  Those applying to become officers had to perform a task: to move themselves over a wall without touching it using only a log that could not touch the wall or the ground.  Danny and his coworkers thought that they could see “each man’s true nature.”  However, when Danny checked how the various soldiers later performed, he learned that his unit’s evaluations—with associated predictions—were worthless.

Danny compared his unit’s delusions to the Müller-Lyer optical illusion.  Are these two lines the same length?

(Müller-Lyer optical illusion by Gwestheimer, Wikimedia Commons)

The eye automatically sees one line as longer than the other even though the lines have equal length.  Even after you use a ruler to show the lines are equal, the illusion persists.  If we’re automatically fooled in such a simple case, what about in more complex cases?

Danny thought up a list of traits that seemed correlated with fitness for combat.  However, Danny was concerned about how to get an accurate measure of these traits from an interview.  One problem was the halo effect: If people see that a person is strong, they tend to see him as impressive in other ways.  Or if people see a person as good in certain areas, then they tend to assume that he must be good in other areas.  More on the halo effect: http://boolefund.com/youre-deluding-yourself/

Danny developed special instructions for the interviewers.  They had to ask specific questions not about how subjects thought of themselves, but rather about how they actually had behaved in the past.  Using this information, before moving to the next question, the interviewers would rate the subject from 1 to 5.  Danny’s essential process is still used in Israeli today.

 

THE INSIDER

To his fellow Israelis, Amos Tversky somehow was, at once, the most extraordinary person they had ever met and the quintessential Israeli.  His parents were among the pioneers who had fled Russian anti-Semitism in the early 1920s to build a Zionist nation.  His mother, Genia Tversky, was a social force and political operator who became a member of the first Israeli Parliament, and the next four after that.  She sacrificed her private life for public service and didn’t agonize greatly about the choice…

Amos was raised by his father, a veterinarian who hated religion and loved Russian literature, and who was amused by things people say:

…His father had turned away from an early career in medicine, Amos explained to friends, because “he thought animals had more real pain than people and complained a lot less.”  Yosef Tversky was a serious man.  At the same time, when he talked about his life and work, he brought his son to his knees with laughter about his experiences, and about the mysteries of existence.

Although Amos had a gift for math and science—he may have been more gifted than any other boy—he chose to study the humanities because he was fascinated by a teacher, Baruch Kurzweil.  Amos loved Kurzweil’s classes in Hebrew literature and philosophy.  Amos told others he was going to be a poet or literary critic.

Amos was small but athletic.  During his final year in high school, he volunteered to become an elite soldier, a paratrooper.  Amos made over fifty jumps.  Soon he was made a platoon commander.

By late 1956, Amos was not merely a platoon commander but a recipient of one of the Israeli army’s highest awards for bravery.  During a training exercise in front of the General Staff of the Israeli Defense Forces, one of his soldiers was assigned to clear a barbed wire fence with a bangalore torpedo.  From the moment he pulled the string to activate the fuse, the soldier had twenty seconds to run for cover.  The soldier pushed the torpedo under the fence, yanked the string, fainted, and collapsed on top of the explosive.  Amos’s commanding officer shouted for everyone to stay put—to leave the unconscious soldier to die.  Amos ignored him and sprinted from behind the wall that served as cover for his unit, grabbed the soldier, picked him up, hauled him ten yards, tossed him on the ground, and threw himself on top of him.  The shrapnel from the explosion remained in Amos for the rest of his life.  The Israeli army did not bestow honors for bravery lightly.  As he handed Amos his award, Moshe Dayan, who had watched the entire episode, said, “You did a very stupid and brave thing and you won’t get away with it again.”

Amos was a great storyteller and also a true genius.  Lewis writes about one time when Tel Aviv University threw a party for a physicist who had just won the Wolf Prize.  Most of the leading physicists came to the party.  But the prizewinner, by chance, ended up in a corner talking with Amos.  (Amos had recently gotten interested in black holes.)  The following day, the prizewinner called his hosts to find out the name of the “physicist” with whom he had been talking.  They realized he had been talking with Amos, and told him that Amos was a psychologist rather than a physicist.  The physicist replied:

“It’s not possible, he was the smartest of all the physicists.”

Most people who knew Amos thought that Amos was the smartest person they’d ever met.  Moreover, he kept strange hours and had other unusual habits.  When he wanted to go for a run, he’d just sprint out his front door and run until he could run no more.  He didn’t pretend to be interested in whatever others expected him to be interested in.  Rather, he excelled at doing exactly what he wanted to do and nothing else.  He loved people, but didn’t like social norms and he would skip family vacation if he didn’t like the place.  Most of his mail he left unopened.

People competed for Amos’s attention.  As Lewis explains, many of Amos’s friends would ask themselves: “I know why I like him, but why does he like me?”

While at Hebrew University, Amos was studying both philosophy and psychology.  But he decided a couple of years later that he would focus on psychology.  He thought that philosophy had too many smart people studying too few problems, and some of the problems couldn’t be solved.

Many wondered how someone as bright, optimistic, logical, and clear-minded as Amos could end up in psychology.  In an interview when he was in his mid-forties, Amos commented:

“It’s hard to know how people select a course in life.  The big choices we make are practically random.  The small choices probably tell us more about who we are.  Which field we go into may depend upon which high school teacher we happen to meet.  Who we marry may depend on who happens to be around at the right time of life.  On the other hand, the small decisions are very systematic.  That I became a psychologist is probably not very revealing.  What kind of psychologist I am may depend upon deep traits.”

Amos became interested in decision making.  While pursuing a PhD at the University of Michigan, Amos ran experiments on people making decisions involving small gambles.  Economists had always assumed that people are rational.  There were axioms of rationality that people were thought to follow, such as transitivity:  if a person prefers A to B and B to C, then he must prefer A to C.  However, Amos found that many people preferred A to B when considering A and B, B to C when considering B and C, and C to A when considering A and C.  Many people violated transitivity.  Amos didn’t generalize his findings at that point, however.

(Transitivity illustration by Thuluviel, Wikimedia Commons)

Next Amos studied how people compare things.  He had read papers by the Berkeley psychologist Eleanor Rosch, who explored how people classified objects.

People said some strange things.  For instance, they said that magenta was similar to red, but that red wasn’t similar to magenta.  Amos spotted the contradiction and set out to generalize it.  He asked people if they thought North Korea was like Red China.  They said yes.  He asked them if Red China was like North Korea—and they said no.  People thought Tel Aviv was like New York but that New York was not like Tel Aviv.  People thought that the number 103 was sort of like the number 100, but that 100 wasn’t like 103.  People thought a toy train was a lot like a real train but that a real train was not like a toy train.

Amos came up with a theory, “features of similarity.”  When people compare two things, they make a list of noticeable features.  The more features two things have in common, the more similar they are.  However, not all objects have the same number of noticeable features.  New York has more than Tel Aviv.

This line of thinking led to some interesting insights:

When people picked coffee over tea, and tea over hot chocolate, and then turned around and picked hot chocolate over coffee—they weren’t comparing two drinks in some holistic manner.  Hot drinks didn’t exist as points on some mental map at fixed distances from some ideal.  They were collections of features.  Those features might become more or less noticeable; their prominence in the mind depended on the context in which they were perceived.  And the choice created its own context: Different features might assume greater prominence in the mind when the coffee was being compared to tea (caffeine) than when it was being compared to hot chocolate (sugar).  And what was true of drinks might also be true of people, and ideas, and emotions.

 

ERRORS

Amos returned to Israel after marrying Barbara Gans, who was a fellow graduate student in psychology at the University of Michigan.  Amos was now an assistant professor at Hebrew University.

Israel felt like a dangerous place because there was a sense that if the Arabs ever united instead of fighting each other, they could overrun Israel.  Israel was unusual in how it treated its professors: as relevant.  Amos gave talks about the latest theories in decision-making to Israeli generals.

Furthermore, everyone who was in Israel was in the army, including professors.  On May 22, 1967, the Egyptian president Gamal Abdel Nasser announced that he was closing the Straits of Tiran to Israeli ships.  Since most Israeli ships passed through the straits, Israel viewed the announcement as an act of war.  Amos was given an infantry unit to command.

By June 7, Israel was in a war on three fronts against Egypt, Jordan, and Syria.  In the span of a week, Israel had won the war and the country was now twice as big.  679 had died.  But because Israel was a small country, virtually everyone knew someone who had died.

Meanwhile, Danny was helping the Israeli Air Force to train fighter pilots.  He noticed that the instructors viewed criticism as more useful than praise.  After a good performance, the instructors would praise the pilot and then the pilot would usually perform worse on the next run.  After a poor performance, the instructors would criticize the pilot and the pilot would usually perform better on the next run.

Danny explained that pilot performance regressed to the mean.  An above average performance would usually be followed by worse performance—closer to the average.  A below average performance would usually be followed by better performance—again closer to the average.  Praise and criticism had little to do with it.

Illustration by intheskies

Danny was brilliant, though insecure and moody.  He became interested in several different areas in psychology.  Lewis adds:

That was another thing colleagues and students noticed about Danny: how quickly he moved on from his enthusiasms, how easily he accepted failure.  It was as if he expected it.  But he wasn’t afraid of it.  He’d try anything.  He thought of himself as someone who enjoyed, more than most, changing his mind.

Danny read about research by Eckhart Hess focused on measuring the dilation and contraction of the pupil in response to various stimuli.  People’s pupils expanded when they saw pictures of good-looking people of the opposite sex.  Their pupils contracted if shown a picture of a shark.  If given a sweet drink, their pupils expanded.  An unpleasant drink caused their pupils to contract.  If you gave people five slightly differently flavored drinks, their pupils would faithfully record the relative degree of pleasure.

People reacted incredibly quickly, before they were entirely conscious of which one they liked best.  “The essential sensitivity of the pupil response,” wrote Hess, “suggests that it can reveal preferences in some cases in which the actual taste differences are so slight that the subject cannot even articulate them.”

Danny tested how the pupil responded to a series of tasks requiring mental effort.  Does intense mental activity hinder perception?  Danny found that mental effort also caused the pupil to dilate.

 

THE COLLISION

Danny invited Amos to come to his seminar, Applications in Psychology, and talk about whatever he wanted.

Amos was now what people referred to, a bit confusingly, as a “mathematical psychologist.”  Nonmathematical psychologists, like Danny, quietly viewed much of mathematical psychology as a series of pointless exercises conducted by people who were using their ability to do math as camouflage for how little of psychological interest they had to say.  Mathematical psychologists, for their part, tended to view nonmathematical psychologists as simply too stupid to understand the importance of what they were saying.  Amos was then at work with a team of mathematically gifted American academics on what would become a three-volume, molasses-dense, axiom-filled textbook called Foundations of Measurement—more than a thousand pages of arguments and proofs of how to measure stuff.

Instead of talking about his own research, Amos talked about a specific study of decision making and how people respond to new information.  In the experiment, the psychologists presented people with two bags full of poker chips.  Each bag contained both red poker chips and white poker chips.  In one bag, 75 percent of the poker chips were white and 25 percent red.  In the other bag, 75 percent red and 25 percent white.  The subject would pick a bag randomly and, without looking in the bag, begin pulling poker chips out one at a time.  After each draw, the subject had to give her best guess about whether the chosen bag contained mostly red or mostly white chips.

There was a correct answer to the question, and it was provided by Bayes’s theorem:

Bayes’s rule allowed you to calculate the true odds, after each new chip was pulled from it, that the book bag in question was the one with majority white, or majority red, chips.  Before any chips had been withdrawn, those odds were 50:50—the bag in your hands was equally likely to be either majority red or majority white.  But how did the odds shift after each new chip was revealed?

That depended, in a big way, on the so-called base rate: the percentage of red versus white chips in the bag… If you know that one bag contains 99 percent red chips and the other, 99 percent white chips, the color of the first chip drawn from the bag tells you a lot more than if you know that each bag contains only 51 percent red or white… In the case of the two bags known to be 75 percent-25 percent majority red or white, the odds that you are holding the bag containing mostly red chips rise by three times every time you draw a red chip, and are divided by three every time you draw a white chip.  If the first chip you draw is red, there is a 3:1 (or 75 percent) chance that the bag you are holding is majority red.  If the second chip you draw is also red, the odds rise to 9:1, or 90 percent.  If the third chip you draw is white, they fall back to 3:1.  And so on.

Were human beings good intuitive statisticians?

(Image by Honina, Wikimedia Commons)

Lewis notes that these experiments were radical and exciting at the time.  Psychologists thought that they could gain insight into a number of real-world problems: investors reacting to an earnings report, political strategists responding to polls, doctors making a diagnosis, patients reacting to a diagnosis, coaches responding to a score, et cetera.  A common example is when a woman is diagnosed with breast cancer from a single test.  If the woman is in her twenties, it’s far more likely to be a misdiagnosis than if the woman is in her forties.  That’s because the base rates are different:  there’s a higher percentage of women in their forties than women in their twenties who have breast cancer.

Amos concluded that people do move in the right direction, however they usually don’t move nearly far enough.  Danny didn’t think people were good intuitive statisticians at all.  Although Danny was the best teacher of statistics at Hebrew University, he knew that he himself was not a good intuitive statistician because he frequently made simple mistakes like not accounting for the base rate.

Danny let Amos know that people are not good intuitive statisticians.  Uncharacteristically, Amos didn’t argue much, except he wasn’t inclined to jettison the assumption of rationality:

Until you could replace a theory with a better theory—a theory that better predicted what actually happened—you didn’t chuck a theory out.  Theories ordered knowledge, and allowed for better prediction.  The best working theory in social science just then was that people were rational—or, at the very least, decent intuitive statisticians.  They were good at interpreting new information, and at judging probabilities.  They of course made mistakes, but their mistakes were a product of emotions, and the emotions were random, and so could be safely ignored.

Note: To say that the mistakes are random means that mistakes in one direction will be cancelled out by mistakes in the other direction.  This implies that the aggregate market can still be rational and efficient.

Amos left Danny’s class feeling doubtful about the assumption of rationality.  By the fall of 1969, Amos and Danny were together nearly all the time.  Many others wondered at how two extremely different personalities could wind up so close.  Lewis:

Danny was a Holocaust kid; Amos was a swaggering Sabra—the slang term for a native Israeli.  Danny was always sure he was wrong.  Amos was always sure he was right.  Amos was the life of every party; Danny didn’t go to parties.  Amos was loose and informal; even when he made a stab at informality, Danny felt as if he had descended from some formal place.  With Amos you always just picked up where you left off, no matter how long it had been since you last saw him.  With Danny there was always a sense you were starting over, even if you had been with him just yesterday.  Amos was tone-deaf but would nevertheless sing Hebrew folk songs with great gusto.  Danny was the sort of person who might be in possession of a lovely singing voice that he would never discover.  Amos was a one-man wrecking ball for illogical arguments; when Danny heard an illogical argument, he asked, What might that be true of?  Danny was a pessimist.  Amos was not merely an optimist; Amos willed himself to be optimistic, because he had decided pessimism was stupid.

Lewis later writes:

But there was another story to be told, about how much Danny and Amos had in common.  Both were grandsons of Eastern European rabbis, for a start.  Both were explicitly interested in how people functioned when there were in a normal “unemotional” state.  Both wanted to do science.  Both wanted to search for simple, powerful truths.  As complicated as Danny might have been, he still longed to do “the psychology of single questions,” and as complicated as Amos’s work might have seemed, his instinct was to cut through endless bullshit to the simple nub of any matter.  Both  men were blessed with shockingly fertile minds.

After testing scientists with statistical questions, Amos and Danny found that even most scientists are not good intuitive statisticians.  Amos and Danny wrote a paper about their findings, “A Belief in the Law of Small Numbers.”  Essentially, scientists—including statisticians—tended to assume that any given sample of a large population was more representative of that population than it actually was.

Amos and Danny had suspected that many scientists would make the mistake of relying too much on a small sample.  Why did they suspect this?  Because Danny himself had made the mistake many times.  Soon Amos and Danny realized that everyone was prone to the same mistakes that Danny would make.  In this way, Amos and Danny developed a series of hypotheses to test.

 

THE MIND’S RULES

The Oregon Research Institute is dedicated to studying human behavior.  It was started in 1960 by psychologist Paul Hoffman.  Lewis observes that many of the psychologists who joined the institute shared an interest in Paul Meehl’s book, Clinical vs. Statistical Prediction.  The book showed how algorithms usually perform better than psychologists when trying to diagnose patients or predict their behavior.

In 1986, thirty two years after publishing his book, Meehl argued that algorithms outperform human experts in a wide variety of areas.  That’s what the vast majority of studies had demonstrated by then.  Here’s a more recent meta-analysis: http://boolefund.com/simple-quant-models-beat-experts-in-a-wide-variety-of-areas/

In the 1960s, researchers at the institute wanted to build a model of how experts make decisions.  One study they did was to ask radiologists how they determined if a stomach ulcer was benign or malignant.  Lewis explains:

The Oregon researchers began by creating, as a starting point, a very simple algorithm, in which the likelihood that an ulcer was malignant depended on the seven factors the doctors had mentioned, equally weighted.  The researchers then asked the doctors to judge the probability of cancer in ninety-six different individual stomach ulcers, on a seven-point scale from “definitely malignant” to “definitely benign.”  Without telling the doctors what they were up to, they showed them each ulcer twice, mixing up the duplicates randomly in the pile so the doctors wouldn’t notice they were being asked to diagnose the exact same ulcer they had already diagnosed.

Initially the researchers planned to start with a simple model and then gradually build a more complex model.  But then they got the results of the first round of questions.  It turned out that the simple statistical model often seemed as good or better than experts at diagnosing cancer.  Moreover, the experts didn’t agree with each other and frequently even contradicted themselves when viewing the same image a second time.

Next, the Oregon experimenters explicitly tested a simple algorithm against human experts:  Was a simple algorithm better than human experts?  Yes.

If you wanted to know whether you had cancer or not, you were better off using the algorithm that the researchers had created than you were asking the radiologist to study the X-ray.  The simple algorithm had outperformed not merely the group of doctors; it had outperformed even the single best doctor.

(Algorithm illustration by Blankstock)

The strange thing was that the simple model was built on the factors that the doctors themselves had suggested as important.  While the algorithm was absolutely consistent, it appeared that human experts were rather inconsistent, most likely due to things like boredom, fatigue, illness, or other distractions.

Amos and Danny continued asking people questions where the odds were hard or impossible to know.  Lewis:

…Danny made the mistakes, noticed that he had made the mistakes, and theorized about why he had made the mistakes, and Amos became so engrossed by both Danny’s mistakes and his perceptions of those mistakes that he at least pretended to have been tempted to make the same ones.

Once again, Amos and Danny spent hour after hour after hour together talking, laughing, and developing hypotheses to test.  Occasionally Danny would say that he was out of ideas.  Amos would always laugh at this—he remarked later, “Danny has more ideas in one minute than a hundred people have in a hundred years.”  When they wrote, Amos and Danny would sit right next to each other at the typewriter.  Danny explained:

“We were sharing a mind.”

The second paper Amos and Danny did—as a follow-up on their first paper, “Belief in the Law of Small Numbers”—focused  on how people actually make decisions.  The mind typically doesn’t calculate probabilities.  What does it do?  It uses rules of thumb, or heuristics, said Amos and Danny.  In other words, people develop mental models, and then compare whatever they are judging to their mental models.  Amos and Danny wrote:

“Our thesis is that, in many situations, an event A is judged to be more probable than an event B whenever A appears more representative than B.”

What’s a bit tricky is that often the mind’s rules of thumb lead to correct decisions and judgments.  If that weren’t the case, the mind would not have evolved this ability.  For the same reason, however, when the mind makes mistakes because it relies on rules of thumb, those mistakes are not random, but systematic.

(Image by Argus)

When does the mind’s heuristics lead to serious mistakes?  When the mind is trying to judge something that has a random component.  That was one answer.  What’s interesting is that the mind can be taught the correct rule about how sample size impacts sampling variance; however, the mind rarely follows the correct statistical rule, even when it knows it.

For their third paper, Amos and Danny focused on the availability heuristic.  (The second paper had been about the representativeness heuristic.)  In one question, Amos and Danny asked their subjects to judge whether the letter “k” is more frequently the first letter of a word or the third letter of a word.  Most people thought “k” was more frequently the first letter because they could more easily recall examples where “k” was the first letter.

The more easily people can call some scenario to mind—the more available it is to them—the more probable they find it to be.  An fact or incident that was especially vivid, or recent, or common—or anything that happened to preoccupy a person—was likely to be recalled with special ease and so be disproportionately weighted in any judgment.  Danny and Amos had noticed how oddly, and often unreliably, their own minds recalculated the odds, in light of some recent or memorable experience.  For instance, after they drove past a gruesome car crash on the highway, they slowed down: Their sense of the odds of being in a crash had changed.  After seeing a movie that dramatizes nuclear war, they worried more about nuclear war; indeed, they felt that it was more likely to happen.

Amos and Danny ran similar experiments and found similar results.  The mind’s rules of thumb, although often useful, consistently made the same mistakes in certain situations.  It was similar to how the eye consistently falls for certain optical illusions.

Another rule of thumb Amos and Danny identified was the anchoring and adjustment heuristic.  One famous experiment they did was to ask people to spin a wheel of fortune, which would stop on a number between 0 and 100, and then guess the percentage of African nations in the United Nations.  The people who spun higher numbers tended to guess a higher percentage than those who spun lower numbers, even though the number spun was purely random and was irrelevant to the question.

 

THE RULES OF PREDICTION

For Amos and Danny, a prediction is a judgment under uncertainty.  They observed:

“In making predictions and judgments under uncertainty, people do not appear to follow the calculus of chance or the statistical theory of prediction.  Instead, they rely on a limited number of heuristics which sometimes yield reasonable judgments and sometimes lead to severe and systematic error.”

In 1972, Amos gave talks on the heuristics he and Danny had uncovered.  In the fifth and final talk, Amos spoke about historical judgment, saying:

“In the course of our personal and professional lives, we often run into situations that appear puzzling at first blush.  We cannot see for the life of us why Mr. X acted in a particular way, we cannot understand how the experimental results came out the way they did, etc.  Typically, however, within a very short time we come up with an explanation, a hypothesis, or an interpretation of the facts that renders them understandable, coherent, or natural.  The same phenomenon is observed in perception.  People are very good at detecting patterns and trends even in random data.  In contrast to our skill in inventing scenarios, explanations, and interpretations, our ability to assess their likelihood, or to evaluate them critically, is grossly inadequate.  Once we have adopted a particular hypothesis or interpretation, we grossly exaggerate the likelihood of that hypothesis, and find it very difficult to see things in any other way.”

In one experiment, Amos and Danny asked students to predict various future events that would result from Nixon’s upcoming visit to China and Russia.  What was intriguing was what happened later: If a predicted event had occurred, people overestimated the likelihood they had previously assigned to that event.  Similarly, if a predicted event had not occurred, people tended to claim that they always thought it was unlikely.  This came to be called hindsight bias.

  • A possible event that had occurred was seen in hindsight to be more predictable than it actually was.
  • A possible event that had not occurred was seen in hindsight to be less likely that it actually was.

As Amos said:

All too often, we find ourselves unable to predict what will happen; yet after the fact we explain what did happen with a great deal of confidence.  This “ability” to explain that which we cannot predict, even in the absence of any additional information, represents an important, though subtle, flaw in our reasoning.  It leads us to believe that there is a less uncertain world than there actually is…

Experts from many walks of life—from political pundits to historians—tend to impose an imagined order on random events from the past.  They change their stories to “explain”—and by implication, “predict” (in hindsight)—whatever random set of events occurred.  This is hindsight bias, or “creeping determinism.”

Hindsight bias can create serious problems: If you believe that random events in the past are more predictable than they actually were, you will tend to see the future as more predictable than it actually is.  You will be surprised much more often than you should be.

Image by Zerophoto

 

GOING VIRAL

Part of Don Redelmeier’s job at Sunnybrook Hospital (located in a Toronto suburb) was to check the thinking of specialists for mental mistakes.  In North America, more people died every year as a result of preventable accidents in hospitals than died in car accidents.  Redelmeier focused especially on clinical misjudgment.  Lewis:

Doctors tended to pay attention mainly to what they were asked to pay attention to, and to miss some bigger picture.  They sometimes failed to notice what they were not directly assigned to notice.

[…]

Doctors tended to see only what they were trained to see… A patient received treatment for something that was obviously wrong with him, from a specialist oblivious to the possibility that some less obvious thing might also be wrong with him.  The less obvious thing, on occasion, could kill a person.

When he was only seventeen years old, Redelmeier had read an article by Kahneman and Tversky, “Judgment Under Uncertainty: Heuristics and Biases.”  Lewis writes:

What struck Redelmeier wasn’t the idea that people make mistakes.  Of course people made mistakes!  What was so compelling is that the mistakes were predictable and systematic.  They seemed ingrained in human nature.

One major problem in medicine is that the culture does not like uncertainty.

To acknowledge uncertainty was to admit the possibility of error.  The entire profession had arranged itself as if to confirm the wisdom of its decisions.  Whenever a patient recovered, for instance, the doctor typically attributed the recovery to the treatment he had prescribed, without any solid evidence the treatment was responsible… [As Redelmeier said:]  “So many diseases are self-limiting.  They will cure themselves.  People who are in distress seek care.  When they seek care, physicians feel the need to do something.  You put leeches on; the condition improves.  And that can propel a lifetime of leeches.  A lifetime of overprescribing antibiotics.  A lifetime of giving tonsillectomies to people with ear infections.  You try it and they get better the next day and it is so compelling…”

Photo by airdone

One day, Redelmeier was going to have lunch with Amos Tversky.  Hal Sox, Redelmeier’s superior, told him just to sit quietly and listen, because Tversky was like Einstein, “one for the ages.”  Sox had coauthored a paper Amos had done about medicine.  They explored how doctors and patients thought about gains and losses based upon how the choices were framed.

An example was lung cancer.  You could treat it with surgery or radiation.  Surgery was more likely to extend your life, but there was a 10 percent chance of dying.  If you told people that surgery had a 90 percent chance of success, 82 percent of patients elected to have surgery.  But if you told people that surgery had a 10 percent chance of killing them, only 54 percent chose surgery.  In a life-and-death decision, people made different choices based not on the odds, but on how the odds were framed.

Amos and Redelmeier ended up doing a paper:

[Their paper] showed that, in treating individual patients, the doctors behaved differently than they did when they designed ideal treatments for groups of patients with the same symptoms.  They were likely to order additional tests to avoid raising troubling issues, and less likely to ask if patients wished to donate their organs if they died.  In treating individual patients, doctors often did things they would disapprove of if they were creating a public policy to treat groups of patients with the exact same illness…

The point was not that the doctor was incorrectly or inadequately treating individual patients.  The point was that he could not treat his patient one way, and groups of patients suffering from precisely the same problem in another way, and be doing his best in both cases.  Both could not be right.

Redelmeier pointed out that the facade of rationality and science and logic is “a partial lie.”

In late 1988 or early 1989, Amos introduced Redelmeier to Danny.  One of the recent things Danny had been studying was people’s experience of happiness versus their memories of happiness.  Danny also looked at how people experienced pain versus how they remembered it.

One experiment involved sticking the subject’s arms into a bucket of ice water.

[People’s] memory of pain was different from their experience of it.  They remembered moments of maximum pain, and they remembered, especially, how they felt the moment the pain ended.  But they didn’t particularly remember the length of the painful experience.  If you stuck people’s arms in ice buckets for three minutes but warmed the water just a bit for another minute or so before allowing them to flee the lab, they remembered the experience more fondly than if you stuck their arms in the bucket for three minutes and removed them at a moment of maximum misery.  If you asked them to choose one experience to repeat, they’d take the first session.  That is, people preferred to endure more total pain so long as the experience ended on a more pleasant note.

Redelmeier tested this hypothesis on seven hundred people who underwent a colonoscopy.  The results supported Danny’s finding.

 

BIRTH OF THE WARRIOR PSYCHOLOGIST

In 1973, the armies of Egypt and Syria surprised Israel on Yom Kippur.  Amos and Danny left California for Israeli.  Egyptian President Anwar Sadat had promised to shoot down any commercial airliners entering Israel.  That was because, as usual, Israelis in other parts of the world would return to Israel during a war.  Amos and Danny managed to land in Tel Aviv on an El Al flight.  The plane had descended in total darkness.  Amos and Danny were to join the psychology field unit.

Amos and Danny set out in a jeep and went to the battlefield in order to study how to improve the morale of the troops.  Their fellow psychologists thought they were crazy.  It wasn’t just enemy tanks and planes.  Land mines were everywhere.  And it was easy to get lost.  People were more concerned about Danny than Amos because Amos was more of a fighter.  But Danny proved to be more useful because he had a gift for finding solutions to problems where others hadn’t even noticed the problem.

Soon after the war, Amos and Danny studied public decision making.

Both Amos and Danny thought that voters and shareholders and all the other people who lived with the consequences of high-level decisions might come to develop a better understanding of the nature of decision making.  They would learn to evaluate a decision not by its outcomes—whether it turned out to be right or wrong—but by the process that led to it.  The job of the decision maker wasn’t to be right but to figure out the odds in any decision and play them well.

It turned out that Israeli leaders often agreed about probabilities, but didn’t pay much attention to them when making decisions on whether to negotiate for peace or fight instead.  The director-general of the Israeli Foreign Ministry wasn’t even interested in the best estimates of probabilities.  Instead, he made it clear that he preferred to trust his gut.  Lewis quotes Danny:

“That was the moment I gave up on decision analysis.  No one ever made a decision because of a number.  They need a story.”

Some time later, Amos introduced Danny to the field of decision making under uncertainty.  Many students of the field studied subjects in labs making hypothetical gambles.

The central theory in decision making under uncertainty had been published in the 1730s by the Swiss mathematician Daniel Bernoulli.  Bernoulli argued that people make probabilistic decisions so as to maximize their expected utility.  Bernoulli also argued that people are “risk averse”: each new dollar has less utility than the one before.  This theory seemed to describe some human behavior.

(Utility as a function of outcomes, Global Water Forum, Wikimedia Commons)

The utility function above illustrates risk aversion: Each additional dollar—between $10 and $50—has less utility than the one before.

In 1944, John von Neumann and Oskar Morgenstern published the axioms of rational decision making.  One axiom was “transitivity”: if you preferred A to B, and B to C, then you preferred A to C.  Another axiom was “independence”:  if you preferred A to B, your preference between A and B wouldn’t change if some other alternative (say D) was introduced.

Many people, including nearly all economists, accepted von Neumann and Morgenstern’s axioms of rationality as a fair description for how people actually made choices.  Danny recalls that Amos regarded the axioms as a “sacred thing.”

By the summer of 1973, Amos was searching for ways to undo the reigning theory of decision making, just as he and Danny had undone the idea that human judgment followed the precepts of statistical theory.

Lewis records that by the end of 1973, Amos and Danny were spending six hours a day together.  One insight Danny had about utility was that it wasn’t levels of wealth that represented utility (or happiness); it was changes in wealth—gains and losses—that mattered.

 

THE ISOLATION EFFECT

Many of the ideas Amos and Danny had could not be attributed to either one of them individually, but seemed to come from their interaction.  That’s why they always shared credit equally—they switched the order of their names for each new paper, and the order for their very first paper had been determined by a coin toss.

In this case, though, it was clear that Danny had the insight that gains and losses are more important than levels of utility.  However, Amos then asked a question with profound implications: “What if we flipped the signs?”  Instead of asking whether someone preferred a 50-50 gamble for $1,000 or $500 for sure, they asked this instead:

Which of the following do you prefer?

  • Gift A: A lottery ticket that offers a 50 percent chance of losing $1,000
  • Gift B: A certain loss of $500

When the question was put in terms of possible gains, people preferred the sure thing.  But when the question was put in terms of possible losses, people preferred to gamble.  Lewis elaborates:

The desire to avoid loss ran deep, and expressed itself most clearly when the gamble came with the possibility of both loss and gain.  That is, when it was like most gambles in life.  To get most people to flip a coin for a hundred bucks, you had to offer them far better than even odds.  If they were going to loss $100 if the coin landed on heads, they would need to win $200 if it landed on tails.  To get them to flip a coin for ten thousand bucks, you had to offer them even better odds than you offered them for flipping it for a hundred.

It was easy to see that loss aversion had evolutionary advantages.  People who weren’t sensitive to pain or loss probably wouldn’t survive very long.

A loss is when you end up worse than your status quo.  Yet determining the status quo can be tricky because often it’s a state of mind.  Amos and Danny gave this example:

Problem A.  In addition to whatever you own, you have been given $1,000.  You are now required to choose between the following options:

  • Option 1.  A 50 percent chance to win $1,000
  • Option 2.  A gift of $500

Problem B.  In addition to whatever you own, you have been given $2,000.  You are now required to choose between the following options:

  • Option 3.  A 50 percent chance to lose $1,000
  • Option 4.  A sure loss of $500

In Problem A, most people picked Option 2, the sure thing.  In Problem B, most people chose Option 3, the gamble.  However, the two problems are logically identical:  Overall, you’re choosing between $1,500 for sure versus a 50-50 chance of either $2,000 or $1,000.

What Amos and Danny had discovered was framing.  The way a choice is framed can impact the way people choose, even if two different frames both refer to exactly the same choice, logically speaking.  Consider the Asian Disease Problem, invented by Amos and Danny.  People were randomly divided into two groups.  The first group was given this question:

Problem 1.  Imagine that the U.S. is preparing for the outbreak of an unusual Asian disease, which is expected to kill 600 people.  Two alternative problems to combat the disease have been proposed.  Assume that the exact scientific estimate of the consequence of the programs is as follows:

  • If Program A is adopted, 200 people will be saved.
  • If Program B is adopted, there is a 1/3 probability that 600 people will be saved, and a 2/3 probability that no one will be saved.

Which of the two programs would you favor?

People overwhelming chose Program A, saving 200 people for sure.

The second group was given the same problem, but was offered these two choices:

  • If Program C is adopted, 400 people will die.
  • If Program D is adopted, there is a 1/3 probability that nobody will die and a 2/3 probability that 600 people will die.

People overwhelmingly chose Program D.  Once again, the underlying choice in each problem is logically identical.  If you save 200 for sure, then 400 will die for sure.  Because of framing, however, people make inconsistent choices.

 

THIS CLOUD OF POSSIBILITY

In 1984, Amos learned he had been given a MacArthur “genius” grant.  He was upset, as Lewis explains:

Amos disliked prizes.  He thought that they exaggerated the differences between people, did more harm than good, and created more misery than joy, as for every winner there were many others who deserved to win, or felt they did.

Amos was angry because he thought that being given the award, and Danny not being given the award, was “a death blow” for the collaboration between him and Danny.  Nonetheless, Amos kept on receiving prizes and honors, and Danny kept on not receiving them.  Furthermore, ever more books and articles came forth praising Amos for the work he had done with Danny, as if he had done it alone.

Amos continued to be invited to lectures, seminars, and conferences.  Also, many groups asked him for his advice:

United States congressmen called him for advice on bills their were drafting.  The National Basketball Association called to hear his argument about statistical fallacies in basketball.  The United States Secret Service flew him to Washington so that he could advise them on how to predict and deter threats to the political leaders under their protection.  The North Atlantic Treaty Organization flew him to the French Alps to teach them about how people made decisions in conditions of uncertainty.  Amos seemed able to walk into any problem, and make the people dealing with it feel as if he grasped its essence better than they did.

Despite the work of Amos and Danny, many economists and decision theorists continued to believe in rationality.  These scientists argued that Amos and Danny had overstated human fallibility.  So Amos looked for new ways to convince others.  For instance, Amos asked people: Which is more likely to happen in the next year, that a thousand Americans will die in a flood, or that an earthquake in California will trigger a massive flood that will drown a thousand Americans?  Most people thought the second scenario was more likely; however, the second scenario is a special case of the first scenario, and therefore the first scenario is automatically more likely.

Amos and Danny came up with an even more stark example.  They presented people with the following:

Linda is 31 years old, single, outspoken, and very bright.  She majored in philosophy.  As a student, she was deeply concerned with issues of discrimination and social justice, and also participated in anti-nuclear demonstrations.

Which of the two alternatives is more probable?

  • Linda is a bank teller.
  • Linda is a bank teller and is active in the feminist movement.

Eighty-five percent of the subjects thought that the second scenario is more likely than the first scenario.  However, just like the previous problem, the second scenario is a special case of the first scenario, and so the first scenario is automatically more likely than the second scenario.

Say there are 50 people who fit the description, are named Linda, and are bank tellers.  Of those 50, how many are also active in the feminist movement?  Perhaps quite a few, but certainly not all 50.

Amos and Danny constructed a similar problem for doctors.  But the majority of doctors made the same error.

Lewis:

The paper Amos and Danny set out to write about what they were now calling “the conjunction fallacy” must have felt to Amos like an argument ender—that is, if the argument was about whether the human mind reasoned probabilistically, instead of the ways Danny and Amos had suggested.  They walked the reader through how and why people violated “perhaps the simplest and the most basic qualitative law of probability.”  They explained that people chose the more detailed description, even though it was less probable, because it was more “representative.”  They pointed out some places in the real world where this kink in the mind might have serious consequences.  Any prediction, for instance, could be made to seem more believable, even as it became less likely, if it was filled with internally consistent details.  And any lawyer could at once make a case seem more persuasive, even as he made the truth of less likely, by adding “representative” details to his description of people and events.

Around the time Amos and Danny published work with these examples, their collaboration had come to be nothing like it was before.  Lewis writes:

It had taken Danny the longest time to understand his own value.  Now he could see that the work Amos had done alone was not as good as the work they had done together.  The joint work always attracted more interest and higher praise than anything Amos had done alone.

Danny pointed out to Amos that Amos that been a member of the National Academy of Sciences for a decade, but Danny still wasn’t a member.  Danny asked Amos why he hadn’t put Danny’s name forward.

A bit later, Danny told Amos they were no longer friends.  Three days after that, Amos called Danny.  Amos learned that his body was riddled with cancer and that he had at most six months to live.

 

BOOLE MICROCAP FUND

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If you are interested in finding out more, please e-mail me or leave a comment.

My e-mail: jb@boolefund.com

 

 

 

Disclosures: Past performance is not a guarantee or a reliable indicator of future results. All investments contain risk and may lose value. This material is distributed for informational purposes only. Forecasts, estimates, and certain information contained herein should not be considered as investment advice or a recommendation of any particular security, strategy or investment product. Information contained herein has been obtained from sources believed to be reliable, but not guaranteed. No part of this article may be reproduced in any form, or referred to in any other publication, without express written permission of Boole Capital, LLC.

Shoe Dog

(Image:  Zen Buddha Silence by Marilyn Barbone.)

August 19, 2018

Shoe Dog is the autobiography of Phil Knight, the creator of Nike.  Bill Gates mentioned this book as one of his favorites in 2016, saying it was “a refreshingly honest reminder of what the path to business success really looks like:  messy, precarious, and riddled with mistakes.”

After the introduction, Knight has a chapter for each year, starting in 1962 and going through 1980.

 

DAWN

Knight introduces his story:

On paper, I thought, I’m an adult.  Graduated from a good college – University of Oregon.  Earned a master’s from a top business school – Stanford.  Survived a yearlong hitch in the U.S. Army – Fort Lewis and Fort Eustis.  My resume said I was a learned, accomplished soldier, a twenty-four-year-old man in full… So why, I wondered, why do I still feel like a kid?

Worse, like the same shy, pale, rail-thin kid I’d always been.

Maybe because I still hadn’t experienced anything of life.  Least of all its many temptations and excitements.  I hadn’t smoked a cigarette, hadn’t tried a drug.  I hadn’t broken a rule, let alone a law.  The 1960s were just underway, the age of rebellion, and I was the only person in America who hadn’t yet rebelled.  I couldn’t think of one time I’d cut loose, done the unexpected.

I’d never even been with a girl.

If I tended to dwell on all the things I wasn’t, the reason was simple.  Those were the things I knew best.  I’d have found it difficult to see who or what exactly I was, or might become.  Like all my friends I wanted to be successful.  Unlike my friends I didn’t know what that meant.  Money?  Maybe.  Wife?  Kids?  House?  Sure, if I was lucky.  These were the goals I was taught to aspire to, and part of me did aspire to them, instinctively.  But deep down I was searching for something else, something more.  I had an aching sense that our time is short, shorter than we ever know, short as a morning run, and I wanted mine to be meaningful.  And purposeful.  And creative.  And important.  Above all… different.

I wanted to leave a mark on the world…

And then it happened.  As my young heart began to thump, as my pink lungs expanded like the wings of a bird, as the trees turned to greenish blurs, I saw it all before me, exactly what I wanted my life to be.  Play.

Yes, I thought.  That’s it.  That’s the word.  The secret of happiness, I’d always suspected, the essence of beauty or truth, or all we ever need to know of either, lay somewhere in that moment when the ball is in midair, when both boxers sense that approach of the bell, when the runners near the finish line and the crowd rises as one.  There’s a kind of exuberant clarity in that pulsing half second before winning and losing are decided.  I wanted that, whatever that was, to be my life, my daily life.

(Sweet Sixteen Syracuse vs. Gonzaga, March 25, 2016, Photo by Ryan Dickey, Wikimedia Commons)

Knight continues:

At different times, I’d fantasized about becoming a great novelist, a great journalist, a great statesman.  But the ultimate dream was always to be a great athlete.  Sadly, fate had made me good, not great.  At twenty-four, I was finally resigned to that fact.  I’d run track at Oregon, and I’d distinguished myself, lettering three of four years.  But that was that, the end.  Now, as I began to clip off one brisk six-minute mile after another, as the rising sun set fire to the lowest needles of the pines, I asked myself:  What if there were a way, without being an athlete, to feel what athletes feel?  To play all the time, instead of working?  Or else to enjoy work so much that it becomes essentially the same thing.

I was suddenly smiling.  Almost laughing.  Drenched in sweat, moving as gracefully and effortlessly as I ever did, I saw my Crazy Idea shining up ahead, and it didn’t look all that crazy.  It didn’t even look like an idea.  It looked like a place.  It looked like a person, or some life force that existed long before I did, separate from me, but also part of me.  Waiting for me, but also hiding from me.  That might sound a little high-flown, a little crazy.  But that’s how I felt back then.

…At twenty-four, I did have a crazy idea, and somehow, despite being dizzy with existential angst, and fears about the future, and doubts about myself, as all young men and women in their midtwenties are, I did decide that the world is made up of crazy ideas.  History is one long processional of crazy ideas.  The things I loved most – books, sports, democracy, free enterprise – started as crazy ideas.

For that matter, few ideas are as crazy as my favorite thing, running.  It’s hard.  It’s painful.  It’s risky.  The rewards are few and far from guaranteed… Whatever pleasures or gains you drive from the act of running, you must find them within.  It’s all in how you frame it, how you sell it to yourself.

(Runner silhouette, Illustration by Msanca)

Knight:

So that morning in 1962 I told myself:  Let everyone else call your idea crazy… just keep going.  Don’t stop.  Don’t even think about stopping until you get there, and don’t give much thought to where ‘there’ is.  Whatever comes, just don’t stop.

That’s the precocious, prescient, urgent advice I managed to give myself, out of the blue, and somehow managed to take.  Half a century later, I believe it’s the best advice – maybe the only advice – any of us should ever give.

 

1962

Knight explains that his crazy idea started as a research paper for a seminar on entrepreneurship at Stanford.  He became obsessed with the project.  As a runner, he knew about shoes.  He also knew that some Japanese products, such as cameras, had recently gained much market share.  Perhaps Japanese running shoes might do the same thing.

When Knight presented his idea to his classmates, everyone was bored.  No one asked any questions.  But Knight held on to his idea.  He imagined pitching it to a Japanese shoe company.  Knight also conceived of the idea of seeing the world on his way to Japan.  He wanted to see “the world’s most beautiful and wondrous places.”

And its most sacred.  Of course I wanted to taste other foods, hear other languages, dive into other cultures, but what I really craved was connection with a capital C.  I wanted to experience what the Chinese call Tao, the Greeks call Logos, the Hindus call Jnana, the Buddhists call Dharma.  What the Christians call Spirit.  Before setting out on my own personal life voyage, I thought, let me first understand the greater voyage of humankind.  Let me explore the grandest temples and churches and shrines, the holiest rivers and mountaintops.  Let me feel the presence of… God?

Yes, I told myself, yes.  For lack of a better word, God.

But Knight needed his father’s blessing and cash in order to make the trip around the world.

At the time, most people had never been on an airplane.  Also, Knight’s father’s father had died in an air crash.  As for the shoe company idea, Knight was keenly aware that twenty-six out of twenty-seven new companies failed.  Knight then notes that his father, besides being a conventional Episcopalian, also liked respectability.  Traveling around the world just wasn’t done except by beatniks and hipsters.

Knight then adds:

Possibly, the main reason for my father’s respectability fixation was a fear of his inner chaos.  I felt this, viscerally, because every now and then that chaos would burst forth.

Knight tells about having to pick his father up from his club.  On these evenings, Knight’s father had had too much to drink.  But father and son would pretend nothing was wrong.  They would talk sports.

Knight’s mom’s mom, “Mom Hatfield” – from Roseburg, Oregon – warned “Buck” (Knight’s nickname) that the Japanese would take him prisoner and gouge out his eyeballs.  Knight’s sisters, four years younger (twins), Jeanne and Joanne, had no reaction.  His mom didn’t say anything, as usual, but seemed proud of his decision.

Knight asked a Stanford classmate, Carter, a college hoops star, to come with him.  Carter loved to read good books.  And he liked Buck’s idea.

The first stop was Honolulu.  After seeing Hawaiian girls, then diving into the warm ocean, Buck told Carter they should stay.  What about the plan?  Plans change.  Carter liked the new idea and grinned.

They got jobs selling Encyclopedias door-to-door.  But their main mission was learning how to surf.  “Life was heaven.”  Except that Buck couldn’t sell encyclopedias.  He thought he was getting shier as he got older.

So he tried a job selling securities.  Specifically, Dreyfus funds for Investors Overseas Services, Bernard Cornfeld’s firm.  Knight had better luck with this.

Eventually, the time came for Buck and Carter to continue on their trip around the world.  However, Carter wasn’t sure.

He’d met a girl.  A beautiful Hawaiian teenager with long brown legs and jet-black eyes, the kind of girl who’d greeted our airplane, the kind I dreamed of having and never would.  He wanted to stick around, and how could I argue?

Buck hesitated, not sure he wanted to continue on alone.  But he decided not to stop his journey.  He bought a plane ticket that was good for one year on any airline going anywhere.

When Knight got to Tokyo, much of the city was black because it still hadn’t been rebuilt after the bombing.

American B-29s.  Superfortresses.  Over a span of several nights in the summer of 1944, waves of them dropped 750,000 pounds of bombs, most filled with gasoline and flammable jelly.  One of the world’s oldest cities, Tokyo was made largely of wood, so the bombs set off a hurricane of fire.  Some three hundred thousand people were burned alive, instantly, four times the number who died in Hiroshima.  More than a million were gruesomely injured.  And nearly 80 percent of the buildings were vaporized.  For long, solemn stretches the cab driver and I said nothing.  There was nothing to say.

Fortunately, Buck’s father knew some people in Tokyo at United Press International.  They advised Buck to talk to two ex-GI’s who ran a monthly magazine, the Importer.

First, Knight spent long periods of time in walled gardens reading about Buddhism and Shinto.  He liked the concept of kensho, or sartori – a flash of enlightenment.

But according to Zen, reality is nonlinear.  No past, no present.  All is now.  That required Knight to change his thinking.  There is no self.  Even in competition, all is one.

Knight decided to mix it up and visited the Tokyo Stock Exchange – Tosho.  All was madness and yelling.  Is this what it’s all about?

Knight sought peace and enlightenment again.  He visited the garden of the nineteenth century emperor Meiji and his empress.  This particular place was thought to possess great spiritual power.  Buck sat beneath the ginkgo trees, beside the gorgeous torii gate, which was thought of as a portal to the sacred.

Next it was Tsukiji, the world’s largest fish market.  Tosho all over again.

Then to the lakes region in the Northern Hakone mountains.  An area that inspired many of the great Zen poets.

Knight went to see the two ex-GI’s.  They told him how they’d fallen in love with Japan during the Occupation.  So they stayed.  They had managed to keep the import magazine going for seventeen years thus far.

Knight told them he liked the Tiger shoes produced by Onitsuka Co. in Kobe, Japan.  The ex-GI’s gave him tips on negotiating with the Japanese:

‘No one ever turns you down, flat.  No one ever says, straight out, no.  But they don’t say yes, either.  They speak in circles, sentences with no clear subject or object.  Don’t be discouraged, but don’t be cocky.  You might leave a man’s office thinking you’ve blown it, when in fact he’s ready to do a deal.  You might leave thinking you’ve closed a deal, when in fact you’ve just been rejected.  You never know.’

Knight decided to visit Onitsuka right away, with the advice fresh in his mind.  He managed to get an appointment, but got lost and arrived late.

When he did arrive, several executives met him.  Ken Miyazaki showed him the factory.  Then they went to a conference room.

Knight had rehearsed this scene his head, just like he used to visualize his races.  But one thing he hadn’t prepared for was the recent history of World War II hanging over everything.  The Japanese had heroically rebuilt, putting the war behind them.  And these Japanese executives were young.  Still, Knight thought, their fathers and uncles had tried to kill his.  In brief, Knight hesitated and coughed, then finally said, “Gentlemen.”

Mr. Miyazaki interrupted, “Mr. Knight.  What company are you with?”

Knight replied, “Ah, yes.  Good question.”  Knight experienced fight or flight for a moment.  A random jumble of thoughts flickered in his mind until he visualized his wall of blue ribbons from track.  “Blue Ribbon… Gentleman, I represent Blue Ribbon Sports of Portland, Oregon.”

Knight presented his basic argument, which was that the American shoe market was huge and largely untapped.  If Onitsuka could produce good shoes and price them below Adidas, it could be highly profitable.  Knight had spent so much time on his research paper at Stanford that he could simply quote it and come across as eloquent.

The Japanese executives started talking excitedly together, then suddenly stood up and left the room.  Knight didn’t know if he had been rejected.  Perhaps he should leave.  He waited.

Then they came back into the room with sketches of different Tiger shoes.  They told him they had been thinking about the American market for some time.  They asked Knight how big he thought the market could be.  Knight tossed out, “$1 billion.”  He doesn’t know where the number came from.

They asked him if Blue Ribbon would be interested in selling Tigers in the United States.  Yes, please send samples to this address, Knight said, and I’ll send a money order for fifty dollars.

Knight considered returning home to get a jump on the new business.  But then he decided to finish his trek around the world.

Hong Kong, then the Phillipines.

I was fascinated by all the great generals, from Alexander the Great to George Patton.  I hated war, but I loved the warrior spirit.  I hated the sword, but loved the samurai.  And of all the great fighting men in history I found MacArthur the most compelling.  Those Ray-Bans, that corncob pipe – the man didn’t lack for confidence.  Brilliant tactician, master motivator, he also went on to head the U.S. Olympic Committee.  How could I not love him?

Of course, he was deeply flawed.  But he knew that…

Bangkok.  He made his way to Wat Phra Kaew, a huge 600-year-old Buddha carved from one hunk of jade.  One of the most sacred statues in Asia.

(Emerald Buddha at Wat Phra Kaew, Image by J. P. Swimmer, Wikimedia Commons)

Vietnam, where U.S. soldiers filled the streets.  Everyone knew a very ugly and different war was coming.

Calcutta.  Knight got sick immediately.  He thinks food poisoning.  He was sure, for one whole day, that he was going to die.  He rallied.  He ended up at the Ganges.  There was a funeral.  Others were bathing.  Others were drinking the same water.

“The Upanishads say, Lead me from the unreal to the real.”  So Knight went to Kathmandu and hiked up the Himalayas.

Back to India.  Bombay.

Kenya.  Giant ostriches tried to outrun the bus, records Knight.  When Masai warriors boarded the bus, a baboon or two would also try to board.

Cairo.  The Giza plateau.  Standing besides desert nomads with their silk-draped camels.  At the foot of the Great Sphinx.

…The sun hammered down on my head, the same sun that hammered down on the thousands of men who built these pyramids, and the millions of visitors who came after.  Not one of them was remembered, I thought.  All is vanity, says the Bible.  All is now, says Zen.  All is dust, says the desert.

(Great Sphinx of Giza, Photo by Johnny 201, Wikimedia Commons)

Then Jerusalem.

…the first century rabbi Eleazar ben Azariah said our work is the holiest part of us.  All are proud of their craft.  God speaks of his work;  how much more should man.

Istanbul.  Turkish coffee.  Lost on the confusing streets of the Bosphorus.  Glowing minarets.  Then the golden labyrinths of Topkapi Palace.

Rome.  Tons of pasta.  And the most beautiful women and shoes he’d ever seen, says Knight.  The Coliseum.  The Vatican.  The Sistine Chapel.

Florence.  Reading Dante.  Milan.  Da Vinci:  One of his obsessions was the human foot, which he called a masterpiece of engineering.

Venice.  Marco Polo.  The palazzo of Robert Browning:  “If you get simply beauty and naught else, you get about the best thing God invents.”

Paris.  The Pantheon.  Rousseau.  Voltaire:  “Love truth, but pardon error.”  Praying at Notre Dame.  Lost in the Louvre.

(The Louvre, Photo by Pipiten, Wikimedia Commons)

Then to where Joyce slept, and F. Scott Fitzgerald.  Walking down the Seine, and stopping where Hemingway and Dos Passos read the New Testament aloud to each other.

Next, up the Champs-Elysees, along the liberators’ path, thinking of Patton:  “Don’t tell people how to do things, tell them what to do and let them surprise you with their results.”

Munich.  Berlin.  East Berlin:

…I looked around, all directions.  Nothing.  No trees, no stores, no life.  I thought of all the poverty I’d seen in every corner of Asia.  This was a different kind of poverty, more willful, somehow, more preventable.  I saw three children playing in the street.  I walked over, took their picture.  Two boys and a girl, eight years old.  The girl – red wool hat, pink coat – smiled directly at me.  Will I ever forget her?  Or her shoes?  They were made of cardboard.

Vienna.  Stalin, Trotsky, Tito, Hitler, Jung, Freud.  All at the same location in the same time period.  A “coffee-scented crossroads.”  Where Mozart walked.  Crossing the Danube.  The spires of St. Stephen’s Church, where Beethoven realized he was deaf.

London.  Buckingham Palace, Speakers’ Corner, Harrods.

Knight asked himself what the highlight of his trip was.

Greece, I thought.  No question.  Greece.

…I meditated on that moment, looking up at those astonishing columns, experiencing that bracing shock, the kind you receive from all great beauty, but mixed with a powerful sense of – recognition?

Was it only my imagination?  After all, I was standing at the birthplace of Western civilization.  Maybe I merely wanted it to be familiar.  But I don’t think so.  I had the clearest thought:  I’ve been here before.

Then, walking up those bleached steps, another thought:  This is where it all begins.

On my left was the Parthenon, which Plato had watched the teams of architects and workmen build.  On my right was the Temple of Athena Nike.  Twenty-five centuries ago, per my guidebook, it had housed a beautiful frieze of the goddess Athena, thought to be the bringer of “nike,” or victory.

It was one of many blessings Athena bestowed.  She also rewarded the dealmakers.  In the Oresteia she says:  ‘I admire… the eyes of persuasion.’  She was, in a sense, the patron saint of negotiators.

(Temple of Athena Nike, Photo by Steve Swayne, Wikimedia Commons)

 

1963

When Buck got home, his hair was to his shoulders and his beard three inches long.  It had been four months since meeting with Onitsuka.  But they hadn’t sent the sample shoes.  Knight wrote to them to ask why.  They wrote back, “Shoes coming… In a little more days.”

Knight got a haircut and shaved.  He was back.  His father suggested he speak with his old friend, Don Frisbee, CEO of Pacific Power & Light.  Frisbee had an MBA from Harvard.  Frisbee told Buck to get his CPA while he was young, a relatively conservative way to put a floor under his earnings.  Knight liked that idea.  He had to take three more courses in accounting, first, which he promptly did at Portland State.

Then Knight worked at Lybrand, Ross Bros. & Montgomery.  It was a Big Eight national firm, but its Portland office was small.  $500 a month and some solid experience.  But pretty boring.

 

1964

Finally, twelve pairs of shoes arrived from Onitsuka.  They were beautiful, writes Knight.  He sent two pairs immediately to his old track coach at Oregon, Bill Bowerman.

Bowerman was a genius coach, a master motivator, a natural leader of young men, and there was one piece of gear he deemed crucial to their development.  Shoes.

Bowerman was obsessed with shoes.  He constantly took his runners’ shoes and experimented on them.  He especially wanted to make the shoes lighter.  One ounce over a mile is fifty pounds.

Bowerman would try anything.  Kangaroo.  Cod.  Knight says four or five runners on the team were Bowerman’s guinea pigs.  But Knight was his “pet project.”

It’s possible that everything I did in those days was motivated by some deep yearning to impress, to please, Bowerman.  Besides my father there was no man whose approval I craved more, and besides my father there was no man who gave it less often.  Frugality carried over to every part of the coach’s makeup.  He weighed and hoarded words of praise, like uncut diamonds.

After you’d won a race, if you were lucky, Bowerman might say:  ‘Nice race.’  (In fact, that’s precisely what he said to one of his milers after the young man became one of the very first to crack the mythical four-minute mark in the United States.)  More likely Bowerman would say nothing.  He’d stand before you in his tweed blazer and ratty sweater vest, his string tie blowing in the wind, his battered ball cap pulled low, and nod once.  Maybe stare.  Those ice-blue eyes, which missed nothing, gave nothing.  Everyone talked about Bowerman’s dashing good looks, his retro crew cut, his ramrod posture and planed jawline, but what always got me was that gaze of pure violet blue.

(Statue of Bill Bowerman, Photo by Diane Lee Jackson, Wikimedia Commons)

For his service in World War II, Bowerman received the Silver Star and four Bronze Stars.  Bowerman eventually became the most famous track coach in America.  But he hated being called “coach,” writes Knight.  He called himself, “Professor of Competitive Responses” because he viewed himself as preparing his athletes for the many struggles and competitions that lay ahead in life.

Knight did his best to please Bowerman.  Even so, Bowerman would often lose patience with Knight.  On one occasion, Knight told Bowerman he was coming down with the flu and wouldn’t be able to practice.  Bowerman told him to get his ass out there.  The team had a time trial that day.  Knight was close to tears.  But he kept his composure and ran one of his best times of the year.  Bowerman gave him a nod afterward.

Bowerman suggested meeting for lunch shortly after seeing the Tiger shoes from Onitsuka.  At lunch, Bowerman told Knight the shoes were pretty good and suggested they become business partners.  Knight was shocked.

Had God himself spoken from the whirlwind and asked to be my partner, I wouldn’t have been more surprised.

Knight and Bowerman signed an agreement soon thereafter.  Knight found himself thinking again about his coach’s eccentricities.

…He always went against the grain.  Always.  For example, he was the first college coach in America to emphasize rest, to place as much value on recovery as on work.  But when he worked you, brother, he worked you.  Bowerman’s strategy for running the mile was simple.  Set a fast pace for the first two laps, run the third as hard as you can, then triple your speed on the fourth.  There was a Zen-like quality to this strategy because it was impossible.  And yet it worked.  Bowerman coached more sub-four-minute milers than anybody, ever.

Knight wrote Onitsuka and ordered three hundred pairs of shoes, which would cost $1,ooo.  Buck had to ask his dad for another loan, who asked him, “Buck, how long do you think you’re going to keep jackassing around with these shoes?”  His father told him he didn’t send him to Oregon and Stanford to be a door-to-door shoe salesman.

At this point, Knight’s mother told him she wanted to purchase a pair of Tigers.  This helped convince Knight’s father to give him another loan.

In April 1964, Knight got the shipment of Tigers.  Also, Mr. Miyazaki told him he could be the distributor for Onitsuka in the West.  Knight quit his accounting job to focus on selling shoes that spring.  His dad was horrified, his mom happy, remarks Knight.

After being rejected by a couple of sporting goods stores, Knight decided to travel around to various track meets in the Pacific Northwest.  Between races, he’d talk with the coaches, the runners, the fans.  He couldn’t write the orders fast enough.  Knight wondered how this was possible, given his inability to sell encyclopedias.

…So why was selling shoes so different?  Because, I realized, it wasn’t selling.  I believed in running.  I believed that if people got out and ran a few miles every day, the world would be a better place, and I believed these shoes were better to run in.  People, sensing my belief, wanted some of that belief for themselves.

Belief, I decided.  Belief is irresistable.

(Illustration by Lkeskinen0)

Knight started the mail order business because he started getting letters from folks wanting Tigers.  To help the process along, he mailed some handouts with big type:

‘Best news in flats!  Japan challenges European track shoe domination!  Low Japanese labor costs make it possible for an exciting new firm to offer these shoes at the low, low price of $6.95.’  [Note:  This is close to $54 in 2018 dollars, due to inflation.]

Knight had sold out his first shipment by July 4, 1964.  So he ordered 900 more.  This would cost $3,000.  His dad grudgingly gave him a letter of guarantee, which Buck took to the First National Bank of Oregon.  They approved the loan.

Knight wondered how to sell in California.  He couldn’t afford airfare.  So every other weekend, he’d stuff a duffel bag with Tigers.  He’d don his army uniform and head to the local air base.  The MPs would wave him on to the next military transport to San Francisco or Los Angeles.

When in Los Angeles, he’d save more money by staying with a friend from Stanford, Chuck Cale.  At a meet at Occidental College, a handsome guy approached Knight, introducing himself as Jeff Johnson.  He was a fellow runner whom Knight had run with and against while at Stanford.  At this point, Johnson was studying anthropology and planning on becoming a social worker.  But he was selling shoes – Adidas then – on weekends.  Knight tried to recruit him to sell Tigers instead.  No, because he was getting married and needed stability, responded Johnson.

Then Knight got a letter from a high school wrestling coach in Manhasset, New York, claiming that Onitsuka had named him the exclusive distributor for Tigers in the United States.  He ordered Knight to stop selling Tigers.

Knight contacted his cousin, Doug Houser, who’d recently graduated from Stanford Law School.  Houser found out Mr. Manhasset was a bit of a celebrity, a model who was one of the original Marlboro Men.  Knight:  “Just what I need.  A pissing match with some mythic American cowboy.”

Knight went into a funk for awhile.  Then he decided to go visit Onitsuka in Japan.  Knight bought a new suit and also a book, How to Do Business with the Japanese.

Knight realized he had to remain cool.  Emotion could be fatal.

The art of competition, I’d learned from track, was the art of forgetting, and now I reminded myself of that fact.  You must forget your limits.  You must forget your doubts, your pain, your past.  You must forget that internal voice screaming, begging, ‘Not one more step!’  And when it’s not possible to forget it, you must negotiate with it.  I thought over all the races in which my mind wanted one thing, and my body wanted another, those laps in which I’d had to tell my body, ‘Yes, you raise some excellent points, but let’s keep going anyway…’

After finding a place to stay in Kobe, Knight called Onitsuka and requested a meeting.  He got a call back saying Mr. Miyazaki no longer worked there.  Mr. Morimoto had replaced him, and didn’t want Knight to visit headquarters.  Mr. Morimoto would meet him for tea.  None of this was good.

At the meeting, Knight layed out the arguments.  They had had an agreement.  He also pointed out the very robust sales Blue Ribbon had had thus far.  He dropped the name of his business partner.  Mr. Morimoto, who was about Knight’s age, said he’d get back to him.

Knight thought it was over.  But then he got a call from Morimoto saying, “Mr. Onitsuka… himself… wishes to see you.”

At this meeting, Knight first presented his arguments again to those who were initially present.  Then Mr. Onitsuka arrived.

Dressed in a dark blue Italian suit, with a head of black hair as thick as shag carpet, he filled every man in the conference room with fear.  He seemed oblivious, however.  For all his power, for all his wealth, his movements were deferential… Morimoto tried to summarize my reasons for being there.  Mr. Onitsuka raised a hand, cut him off.

Without preamble, he launched into a long, passionate monologue.  Some time ago, he’d said, he’d had a vision.  A wondrous glimpse of the future.  ‘Everyone in the world wear athletic shoes all the time,’ he said.  ‘I know this day will come.’  He paused, looking around the table at each person, to see if they also knew.  His gaze rested on me.  He smiled.  I smiled.  He blinked twice.  ‘You remind me of myself when I am young,’ he said softly.  His stared into my eyes.  One second.  Two.  Now he turned his gaze to Morimoto.  ‘This about those thirteen western states?’ he said.  ‘Yes,’ Morimoto said.  ‘Hm,’ Onitsuka said.  ‘Hmmmm.’  He narrowed his eyes, looked down.  He seemed to be meditating.  Again he looked up at me.  ‘Yes,’ he said.  ‘Alright.  You have western states.’

Knight ordered $3,400 worth of shoes [about $26,000 in 2018 dollars].

(Mount Fuji, Photo by Wipark Kulnirandorn)

To celebrate, Knight decided to climb to the top of Mount Fuji.  Buck met a girl on the wap up, Sarah, who was studying philosophy at Connecticut College for Women.  It went well for a time.  Many letters back and forth.  A couple of visits.  But she decided Knight wasn’t “sophisticated” enough.  Jeanne, one of Buck’s younger sisters, found the letters, read them, and told Buck, “You’re better off without her.”  Buck then asked his sister – given her interest in mail – if she’d like to help with the mail order business for $1.50 an hour.  Sure.  Blue Ribbon Employee Number One.

 

1965

Buck got a letter from Johnson.  He’d bought some Tigers and loved them.  Could he become a commissioned salesman for Blue Ribbon?  Sure.  $1.75 for each pair of running shoes, $2 for spikes, were the commissions.

Then the letters from Johnson kept coming:

I liked his energy, of course.  And it was hard to fault his enthusiasm.  But I began to worry he might have too much of each.  With the twentieth letter, or the twenty-fifth, I began to worry that the man might be unhinged.  I wondered why everything was so breathless.  I wondered if he was ever going to run out of things he urgently needed to tell me, or ask me…

…He wrote to say that he wanted to expand his sales territory beyond California, to include Arizona, and possibly New Mexico.  He wrote to suggest that we open a retail store in Los Angeles.  He wrote to tell me that he was considering placing ads in running magazines and what did I think?  He wrote to inform me that he’d placed those ads in running magazines and the response was good.  He wrote to ask why I hadn’t answered any of his previous letters.  He wrote to plead for encouragement.  He wrote to complain that I hadn’t responded to his previous plea for encouragement.

I’d always considered myself a conscientious correspondent… And I always meant to answer Johnson’s letters.  But before I got around to it, there was always another one, waiting.  Something about the sheer volume of his correspondence stopped me…

Eventually Johnson realized he loved shoes and running more than anthropology or social work.

(Monk meditating, Photo by Ittipon)

In his heart of hearts Johnson believed that runners are God’s chosen, that running, done right, in the correct spirit and with the proper form, is a mystical exercise, no less than meditation or prayer, and thus he felt called to help runners reach their nirvana.  I’d been around runners much of my life, but this kind of dewy romanticism was something I’d never encountered.  Not even the Yahweh of running, Bowerman, was as pious about the sport as Blue Ribbon’s Part-Time Employee Number Two.

In fact, in 1965, running wasn’t even a sport.  It wasn’t popular, it wan’t unpopular, it just was.  To go out for a three-mile run was something weirdos did, presumably to burn off manic energy.  Running for exercise, running for pleasure, running for endorphins, running to live better and longer – these things were unheard of.

People often went out of their way to mock runners.  Drivers would slow down and honk their horns.  ‘Get a horse!,’ they’d yell, throwing a beer or soda at the runner’s head.  Johnson had been drenched by many a Pepsi.  He wanted to change all this…

Above all, he wanted to make a living doing it, which was next to impossible in 1965.  In me, in Blue Ribbon, he thought he saw a way.

I did everything I could to discourage Johnson from thinking like this.  At every turn, I tried to dampen his enthusiasm for me and my company.  Besides not writing back, I never phoned, never visited, never invited him to Oregon.  I also never missed an opportunity to tell him the unvarnished truth.  I put it flatly:  ‘Though our growth has been good, I owe First National Bank of Oregon $11,000… Cash flow is negative.’

He wrote back immediately, asking if he could work for me full-time…

Knight just shook his head.  Finally in last summer of 1965, Knight accepted Johnson’s offer.  Johnson had been making $460 as a social worker, so he proposed $400 a month [over $3,000 a month in 2018 dollars].  Knight very reluctantly agreed.  It seemed like a huge sum.  Knight writes:

As ever, the accountant in me saw the risk, the entrepreneur the possibility.  So I split the difference and kept moving forward.

Knight then forgot about Johnson because he had bigger issues.  Blue Ribbon had doubled its sales in one year.  But Knight’s banker said they were growing too fast for their equity.  Knight asked how doubling sales – profitably – can be a bad thing.

In those days, however, commercial banks were quite different from investment banks.  Commercial banks never wanted you to outgrow your cash balance.  Knight tried to explain that growing sales as much as possible – profitably – was essential to convince Onitsuka to stick with Blue Ribbon.  And then there’s the monster, Adidas.  But his banker kept repeating:

‘Mr. Knight, you need to slow down.  You don’t have enough equity for this kind of growth.’

Knight kept hearing the word “equity” in his head over and over.  “Cash,” that’s what it meant.  But he was deliberately reinvesting every dollar – on a profitable basis.  What was the problem?

Every meeting with his banker, Knight managed to hold his tongue and say nothing, basically agreeing.  Then he’d keep doubling his orders from Onitsuka.

Knight’s banker, Harry White, had essentially inherited the account.  Previously, Ken Curry was Knight’s banker, but Curry bailed when Knight’s father wouldn’t guarantee the account in the case of business failure.

Furthermore, the fixation on equity didn’t come from White, but from White’s boss, Bob Wallace.  Wallace wanted to be the next president of the bank.  Credit risks were the main roadblock to that goal.

Oregon was smaller back then.  First National and U.S. Bank were the only banks, and the second one had already turned Blue Ribbon down.  So Knight didn’t have a choice.  Also, there as no such thing as venture capital in 1965.

(First National Bank of Oregon, Photo by Steve Morgan, Wikimedia Commons)

To make matters worse, Onitsuka was always late in its shipments, no matter how much Knight pleaded with them.

By this point, Knight had passed the four parts of the CPA exam.  So he decided to get a job as an accountant.  He invested a good chunk of his paycheck into Blue Ribbon.

In analyzing companies as an accountant, Knight learned how they sold things or didn’t, how they survived or didn’t.  He learned how companies got into trouble and how they got out.

It was while working for the Portland branch of Price Waterhouse that he met Delbert J. Hayes, who was the best accountant in the office.  Knight describes Hayes as a man with “great talent, great wit, great passions – and great appetites.”  Hayes was six-foot-two and three hundred pounds.  He loved food and alcohol.  And he smoked two packs a day.

Hayes looked at numbers the way a poet looks at clouds or a geologist looks at rocks, says Knight.  He could see the beauty of numbers.  Numbers were a secret code.

Every evening, Hayes would insist on taking junior accountants out for a drink.  Hayes would talk nonstop, like he drank.  But while other accountants dismissed Hayes’ stories, Knight always paid careful attention.  In every tale told by Hayes was some piece of wisdom about business.  So Knight would match Hayes, shot for shot, in order to learn as much as he could.

The following morning, Knight was always sick.  But he willed himself to do the work.  Being in the Army Reserves at the same time wasn’t easy.  Meanwhile, the conflict in Vietnam was heating up.  Knight:

I had grown to hate that war.  Not simply because I felt it was wrong.  I also felt it was stupid, wasteful.  I hated stupidity.  I hated waste.  Above all, that war, more than other wars, seemed to be run along the same principles of my bank.  Fight not to win, but to avoid losing.  A surefire losing strategy.

Hayes came to appreciate Knight.  Hayes thought it was a tough time to launch a new company with zero cash balance.  But he did acknowledge that having Bowerman as a partner was a valuable, intangible asset.

Recently, Bowerman and Mrs. Bowerman had visited Onitsuka and charmed everyone.  Mr. Onitsuka told Bowerman about founding his shoe company in the rubble after World War II.

He’d built his first lasts, for a line of basketball shoes, by pouring hot wax from Buddhist candles over his own feet.  Though the basketball shoes didn’t sell, Mr. Onitsuka didn’t give up.  He simply switched to running shoes, and the rest is shoe history.  Every Japanese runner in the 1964 Games, Bowerman told me, was wearing Tigers.

Mr. Onitsuka also told Bowerman that the inspiration for the unique soles on Tigers had come to him while eating sushi.  Looking down at his wooden platter, at the underside of an octopus’s leg, he thought a similar suction cup might work on the sole of a runner’s flat.  Bowerman filed that away.  Inspiration, he learned, can come from quotidian things.  Things you might eat.  Or find lying around the house.

Bowerman started corresponding not only with Mr. Onitsuka, but with the entire production team at the Onitsuka factory.  Bowerman realized that Americans tend to be longer and heavier than the Japanese.  He thought the Tigers could be modified to fit Americans better.  Most of Bowerman’s letters went unanswered, but like Johnson Bowerman just kept writing more.

Eventually he broke through.  Onitsuka made prototypes that conformed to Bowerman’s vision of a more American shoe.  Soft inner sole, more arch support, heel wedge to reduce stress on the Achilles tendon – they sent the prototype to Bowerman and he went wild for it.  He asked for more.

Bowerman also experimented with drinks to help his runners recover.  He invented an early version of Gatorade.  As well, he conducted experiments to make the track softer.  He invented an early version of polyurethane.

 

1966

Johnson kept inundating Knight with long letters, including a boatload of parenthetical comments and a list of PS’s.  Knight felt he didn’t have time to send the requested words of encouragement.  Also, it wasn’t his style.

I look back now and wonder if I was truly being myself, or if I was emulating Bowerman, or my father, or both.  Was I adopting their man-of-few-words demeanor?  Was I maybe modeling all the men I admired?  At the time I was reading everything I could get my hands on about generals, samurai, shoguns, along with biographies of my three main heroes – Churchill, Kennedy, and Tolstoi.  I had no love of violence, but I was fascinated by leadership, or lack thereof, under extreme conditions…

I wasn’t that unique.  Throughout history men have looked to the warrior for a model of Hemingway’s cardinal virtue, pressurized grace… One lesson I took from all my home-schooling about heroes was that they didn’t say much.  None was a blabbermouth.  None micromanaged.  “Don’t tell people how to do things, tell them what to do and let them surprise you with their results.” 

(Winston Churchill in 1944, Wikimedia Commons)

Johnson never let Knight’s lack of communication discourage him.  Johnson was full of energy, passion, and creativity.  He was going all-out, seven days a week, to sell Blue Ribbon shoes.  Johnson had an index card for each customer including their shoe sizes and preferences.  He sent all of them birthday cards and Christmas cards.  Johnson developed extensive correspondence with hundreds of customers.

Johnson began aggregating customer feedback on the shoes.

…One man, for instance, complained that Tiger flats didn’t have enough cushion.  He wanted to run the Boston Marathon but didn’t think the Tigers would last the twenty-six miles.  So Johnson hired a local cobbler to graft rubber soles from a pair of shower shoes into a pair of Tiger flats.  Voila.  Johnsn’s Frankenstein flat had space-age, full-length, midsole cushioning.  (Today it’s standard in all training shoes for runners.)  The jerry-rigged Johnson sole was so dynamic, so soft, so new, Johnson’s customer posted a personal best in the Boston.  Johnson forwarded me the results and urged me to pass them along to Tiger.  Bowerman had just asked me to do the same with his batch of notes a few weeks earlier.  Good grief, I thought, one mad genius at a time.

Johnson had customers in thirty-seven states.  Knight meant to warn him about encroaching on Malboro Man’s territory.  But he never got around to it.

Knight did write to tell Johnson that if he could sell 3,250 shoes by the end of June 1966, then he could open the retail outlet he’d been asking about.  Knight calculated that 3,250 was impossible, so he wasn’t too worried.

Somehow Johnson hit 3,250.  So Blue Ribbon opened its first retail store in Santa Monica.

He then set about turning the store into a mecca, a holy of holies for runners.  He bought the most comfortable chairs he could find, and afford (yard sales), and he created a beautiful space for runners to hang out and talk.  He built shelves and filled them with books that every runner should read, many of them first editions from his own library.  He covered the walls with photos of Tiger-shod runners, and laid in a supply of silk-screened T-shirts with Tiger across the front, which he handed out to his best customers.  He also stuck Tigers to a black lacquered wall and illuminated them with a strip of can lights – very hip.  Very mod.  In all the world, there had never been a sanctuary for runners, a place that didn’t just sell them shoes but celebrated them and their shoes.  Johnson, the aspiring cult leader of runners, finally had his church.  Services were Monday through Saturday, nine to six.

When he first wrote me about the store, I thought of the temples and shrines I’d seen in Asia, and I was anxious to see how Johnson’s compared.  But there just wasn’t time…

Knight got a heads up that the Marlboro man had just launched an advertising campaign which involved poaching customers of Blue Ribbon.  So Knight flew down to see Johnson.

(Jeff Johnson, Employee Number One)

Johnson’s apartment was one giant running shoe.  There were running shoes seemingly everywhere.  And there were many books – mostly thick volumes on philosophy, religion, sociology, anthropology, and classics in Western literature.  Knight had thought he liked to read.  This was a new level, says Knight.

Johnson told Knight he had to go visit Onitsuka again.  Johnson started typing notes, ideas, lists, which would become a manifesto for Knight to take to Onitsuka.  Knight wired Onitsuka.  They got back to him, but it wasn’t Morimoto.  It was a new guy, Kitami.

Knight told Kitami and other executives about the performance of Blue Ribbon thus far, virtually doubling sales each year and projecting more of the same.  Kitami said they wanted someone more established, with offices on the East Coast.  Knight replied that Blue Ribbon had offices on the East Coast and could handle national distribution.  “Well,” said Kitami, “this changes things.”

The next morning, Kitami awarded Blue Ribbon exclusive distribution rights for the United States.  A three-year contract.  Knight promptly placed an order for 5,000 more shoes, which would cost $20,000 – more than $150,000 in 2018 dollars – that he didn’t have.  Kitami said he would ship them to Blue Ribbon’s East Coast office.

There was only one person crazy enough to move to the East Coast on a moment’s notice….

 

1967

Knight delayed telling Johnson.  Then he hired John Bork, a high school track coach and a friend of a friend, to run the Santa Monica store.  Bork showed up at the store and told Johnson that he, Bork, was the new boss so that Johnson could go back east.

Johnson called Knight.  Knight told him he’d had to tell Onitsuka that Blue Ribbon had an east coast office.  A huge shipment was due to arrive at this office.  Johnson was the only one who could manage the east coast store.  The fate of the company was on his shoulders.  Johnson was shocked, then mad, then freaked out.  Knight flew down to visit him.

Johnson talked himself into going to the east coast.

The forgiveness Johnson showed me, the overall good nature he demonstrated, filled me with gratitude, and a new fondness for the man.  And perhaps a deeper loyalty.  I regretted my treatment of him.  All those unanswered letters.  There are team players, I thought, and then there are team players, and then there’s Johnson.

Soon thereafter, Bowerman called asking Knight to add a new employee – Geoff Hollister.  A former track guy.  Full-time Employee Number Three.

Then Bowerman called again with yet another employee – Bob Woodell.

I knew the name, of course.  Everyone in Oregon knew the name.  Woodell had been a standout on Bowerman’s 1965 team.  Not quite a star, but a gritty and inspiring competitor.  With Oregon defending its second national championship in three years, Woodell had come out of nowhere and won the long jump against vaunted UCLA.  I’d been there, I’d watched him do it, and I’d come away mighty impressed.

The very next day, during a celebration, there had been an accident.  The float twenty guys were carrying collapsed after someone lost their footing.  It landed on Woodell and crushed one of his vertebra, paralyzing his legs.

Knight called Woodell.  Knight realized it was best to keep it strictly business.  So he told Woodell that Bowerman had recommended him.  Would he like to grab lunch to discuss the possibility of working for Blue Ribbon?  Sure thing, he said.

Woodell had already mastered a special car, a Mercury Cougar with hand controls.  At lunch, they hit it off and Woodell impressed Knight.

I wasn’t certain what Blue Ribbon was, or if it would ever become a thing at all, but whatever it was or might become, I hoped it would have something of this man’s spirit.

Knight offered Woodell a job opening a second retail store, in Eugene, for a monthly salary of $400.  Woodell immediately agreed.  They shook hands.  “He still hand the strong grip of an athlete.”

(Bob Woodell 1967)

Bowerman’s latest experiment was with the Spring Up.  He noticed the outer sole melted, whereas the midsole remained solid.  He convinced Onitsuka to fuse the outer sole to the midsole.  The result looked like the ultimate distance training shoe.  Onitsuka also accepted Bowerman’s suggestion of a name for the shoe, the “Aztec,” in homage to the upcoming 1968 Olympics in Mexico City.  Unfortunately, Adidas had a similar name for one of its shoes and threatened to sue.  So Bowerman changed the name to “Cortez.”

The situation with Adidas reminded Knight of when he had been a runner in high school.  The fastest runner in the state was Jim Grelle (pronounced “Grella”) and Knight had been second-fastest.  So Knight spent many races staring at Grelle’s back.  Then they both went to Oregon, so Knight spent more years staring at Grelle’s back.

Adidas made Knight think of Grelle.  Knight felt super motivated.

Once again, in my quixotic effort to overtake a superior opponent, I had Bowerman as my coach.  Once again he was doing everything he could to put me in position to win.  I often drew on the memory of his old prerace pep talks, especially when we were up against our blood rivals, Oregon State.  I would replay Bowerman’s epic speeches… Nearly sixty years later it gives me chills to recall his words, his tone.  No one could get your blood going like Bowerman, though he never raised his voice.

Thanks to the Cortez, Blue Ribbon finished the year strong.  They had nearly doubled their sales again, to $84,000.  Knight rented an office for $50 a month.  And he transferring Woodell to the “home office.”  Woodell had shown himself to be highly skilled and energetic, and in particular, he was excellent at organizing.

The office was cold and the floor was warped.  But it was cheap.  Knight built a corkboard wall, pinning up different Tiger models and borrowing some of Johnson’s ideas from the Santa Monica store.

Knight thought perhaps he could save even more money by living at his office.  Then he reflected that living at your office was what a crazy person does.  Then he got a letter from Johnson saying he was living at his office.  Johnson had set up shop in Wellesley, a suburb of Boston.

Johnson told Knight how he had chosen the location.  He’d seen people running along country roads, many of them women.  Ali MacGraw look-alikes.  Sold.

 

1968

Knight:

I wanted to dedicate every minute of every day to Blue Ribbon… I wanted to be present, always.  I wanted to focus constantly on the one task that really mattered.  If my life was to be all work and no play, I wanted my work to be play.  I wanted to quit Price Waterhouse.  Not that I hated it;  it just wasn’t me.

I wanted what everyone wants.  To be me, full-time.

Even though Blue Ribbon was on track to double sales again, there was never enough cash, certainly not to pay Knight.  Knight found another job he thought might fit better with his desire to focus as much as possible on Blue Ribbon.  Assistant Professor of Accounting at Portland State University.

Knight, a CPA who had worked for two accounting firms, knew accounting pretty well at this point.  But he was restless and twitchy, with several nervous tics – including wrapping rubber banks around his wrist and snapping them.  One of his students was named Penelope Parks.  Knight was captivated by her.

Knight decided to use the Socratic method to teach accounting.  Miss Parks turned out to be the best student in the class.  Soon thereafter, Miss Parks asked if Knight would be her advisor.  Knight then asked her if she’d like a job for Blue Ribbon to help with bookkeeping.  “Okay.”

On Miss Parks’ first day at Blue Ribbon, Woodell gave her a list of things – typing, bookkeeping, scheduling, stocking, filing invoices – and told her to pick two.  Hours later, she’d done every thing on the list.  Within a week, Woodell and Knight couldn’t remember how they’d gotten by without her, recalls Knight.

Furthermore, Miss Parks was “all-in” with respect to the mission of Blue Ribbon.  She was good with people, too.  She had a healing effect on Woodell, who was still struggling to adjust to his legs being paralyzed.

Knight often volunteered to go get lunch for the three of them.  But his head was usually so full of business matters that he would invariably get the orders mixed up.  “Can’t wait to see what I’m eating for lunch today,” Woodell might say quietly.  Miss Parks would hide a smile.

Later on, Knight found out that Miss Parks and Woodell weren’t cashing any of their paychecks.  They truly believed in Blue Ribbon.  It was more than just a job for them.

Knight and Penny started dating.  They were good at communicating nonverbally since they were both shy people.  They were a good match and eventually decided to get married.  Knight felt like she was a partner in life.

Knight made another trip to Onitsuka.  Kitami was very friendly this time, inviting him to the company’s annual picnic.  Knight met a man named Fujimoto at the picnic.  It turned out to be another life-altering partnership.

…I was doing business with a country I’d come to love.  Gone was the initial fear.  I connected with the shyness of the Japanese people, with the simplicity of their culture and products and arts.  I liked that they tried to add beauty to every part of life, from the tea ceremony to the commode.  I liked that the radio announced each day which cherry trees, on which corner, were blossoming, and how much.

(Cherry trees in Japan, Photo by Nathapon Triratanachat)

 

1969

Knight was able to hire more ex-runners on commission.  Sales in 1968 had been $150,000 and now they were on track for $300,000 for 1969.

Knight was finally able to pay himself a salary.  But before leaving Portland State, he happened to see a starving artist in the hallway and asked if she’d do advertising art part-time.  Her name was Carolyn Davidson, and she said OK.

Bowerman and Knight were losing trust in Kitami.  Bowerman thought he didn’t know much about shoes and was full of himself.  Knight hired Fujimoto to be a spy.  Knight pondered again that when it came to business in Japan, you never knew what a competitor or a partner would do.

Knight was absentminded.  He couldn’t go to the store and return with the one thing Penny asked for.  He misplaced wallets and keys frequently.  And he was constantly bumping into trees, poles, and fenders while driving.

Knight got in the habit of calling his father in the evening.  His father would be in his recliner, while Buck would be in his.  They’d hash things over.

Woodell and Knight began looking for a new office.  They started enjoying hanging out together.  Before parting, Knight would time Woodell on how fast he could fold up his wheelchair and get it and himself into his car.

Woodell was super positive and super energetic, a constant reminder of the importance of good spirits and a great attitude.

Buck and Penny would have Woodell over for dinner.  Those were fun times.  They would take turns describing what the company was and might be, and what it must never be.  Woodell was always dressed carefully and always had on a pair of Tigers.

Knight asked Woodell to become operations manager.  He’d demonstrated already that he was exceptionally good at managing day-to-day tasks.  Woodell was delighted.

 

1970

Knight visited Onitsuka again.  He discovered that Kitami was being promoted to operations manager.  Onitsuka and Blue Ribbon signed another 3-year agreement.  Knight looked into Kitami’s eyes and noticed something very cold.  Knight never forgot that cold look.

Knight pondered the fact that the shipments from Onitsuka were always late, and sometimes had the wrong sizes or even the wrong models.  Woodell and Knight discovered that Onitsuka always filled its orders from Japanese companies first, and then sent its foreign exports.

Meanwhile, Wallace at the bank kept making things difficult.  Knight concluded that a small public offerings could create the extra cash Blue Ribbon needed.  At the time, in 1970, a few venture capital firms had been launched.  But they were in California and mostly invested in high-tech.  So Knight formed Sports-Tek, Inc., as a holding company for Blue Ribbon.  They tried a small public offering.  It didn’t work.

Friends and family chipped in.  Woodell’s parents were particularly generous.

On June 15, 1970, Knight was shocked to see a Man of Oregon on the cover of Sports Illustrated.  His name was Steve Prefontaine.  He’d already set a national record in high school at the two-mile (8:41).  In 1970, he’d run three miles in 13:12.8, the fastest time on the planet.

Knight learned from a Fortune magazine about Japan’s hyper-aggressive sosa shoga, “trading companies.”  It was hard to see what these trading companies were exactly.  Sometimes they were importers.  Sometimes they were exporters.  Sometimes they were banks.  Sometimes they were an arm of the government.

After being harangued by Wallace at First National about cash balances again, Knight walked out and saw a sign for the Bank of Tokyo.  He was escorted to a back room, where a man appeared after a couple of minutes.  Knight showed the man his financials and said he needed credit.  The man said that Japan’s sixth-largest trading company had an office at the top floor of this same building.  Nissho Iwai was a $100-billion dollar company.

Knight met a man named Cam Murakami, who offered Knight a deal on the spot.  Knight said he had to check with Onitsuka first.  Knight wired Kitami, but heard nothing back at all for weeks.

Then Knight got a call from a guy on the east coast who told him that Onitsuka had approached him about becoming its new U.S. distributor.  Knight checked with Fujimoto, his spy.  Yes, it was true.  Onitsuka was considering a clean break with Blue Ribbon.

Knight invited Kitami to visit Blue Ribbon.

 

1971

March 1971.  Kitami was on his way.  Blue Ribbon vowed to give him the time of his life.

Kitami arrived with a personal assistant, Hiraku Iwano, who was just a kid.  At one point, Kitami told Knight that Blue Ribbon’s sales were disappointing.  Knight said sales were doubling every year.  “Should be triple some people say,” Kitami replied.  “What people?”, asked Knight.  “Never mind,” answered Kitami.

Kitami took a folder from his briefcase and repeated the charge.  Knight tried to defend Blue Ribbon.  Back and forth.  Kitami had to use the restroom.  When he left the meeting room, Knight looked into Kitami’s briefcase and tried to snag the folder that he thought Kitami had been referring to.

Kitami went back to his hotel.  Knight still had the folder.  He and Woodell opened it up.  They found a list of eighteen U.S. athletic shoe distributors.  These were the “some people” who told Kitami that Blue Ribbon wasn’t performing well enough.

I was outraged, of course.  But mostly hurt.  For seven years we’d devoted ourselves to Tiger shoes.  We’d introduced them to America, we’d reinvented the line.  Bowerman and Johnson had shown Onitsuka how to make a better shoe, and their designs were now foundational, setting sales records, changing the face of the industry – and this was how we were repaid?

At the end of Kitami’s visit, as planned, there was dinner with Bowerman, Mrs. Bowerman, and his friend (and lawyer), Jaqua.  Mrs. Bowerman usually didn’t allow alcohol, but she was making an exception.  Knight and Kitami both liked mai tais, which were being served.

Unfortunately, Bowerman had a few too many mai tais.  It appeared things might get out of hand.  Knight looked at Jaqua, remembering that he’d been a fighter pilot in World World II, and that his wingman, one of his closest friends, had been shot out of the sky by a Japanese Zero.  Knight thought he sensed something starting to erupt in Jaqua.

Kitami, however, was having a great time.  Then he found a guiter.  He started playing it and singing a country Western.  Suddenly, he sang “O Sole Mio.”

A Japanese businessman, strumming a Western guitar, singing an Italian ballad, in the voice of an Irish tenor.  It was surreal, then a few miles past surreal, and it didn’t stop.  I’d never know there were so many verses to “O Sole Mio.”  I’d never known a roomful of active, restless Oregonians could sit still and quite for so long.  When he set down the guitar, we all tried not to make eye contact with each other as we gave him a big hand.  I clapped and clapped and it all made sense.  For Kitami, this trip to the United States – the visit to the bank, the meetings with me, the dinner with the Bowermans – wasn’t about Blue Ribbon.  Nor was it about Onitsuka.  Like everything else, it was all about Kitami.

At a meeting soon thereafter, however, Kitami told Knight that Onitsuka wanted to buy Blue Ribbon.  If Blue Ribbon did not accept, Onitsuka would have to work with other distributors.  Knight knew he still needed Onitsuka, at least for awhile.  So he thought of a stall.  He told Kitami he’d have to talk with Bowerman.  Kitami said OK and left.

Knight sent the budget and forecast to First National.  White informed Knight at a meeting that First National would no longer be Blue Ribbon’s bank.  White was sick about it, the bank officers were divided, but it had been Wallace’s call.  Knight strove straight to U.S. Bank.  Sorry.  No.

Blue Ribbon was finishing 1971 with $1.3 million in sales, but it was in danger of failing.  Fortunately, Bank of Cal gave Blue Ribbon a small line of credit.

Knight went back to Nissho and met Tom Sumeragi.  Sumeragi told Knight that Nissho was willing to take a second position to their banks.  Also, Nissho had sent a delegation to Onitsuka to try to work out a deal on financing.  Onitsuka had tossed them out.  Nissho was embarrased that a $25 million company had thrown out a $100 billion company.  Sumeragi told Knight that Nissho could introduce him to other shoe manufacturers in Japan.

Knight knew he had to find a new shoe factory somewhere.  He found one in Gaudalajara, Mexico.  Knight placed an order for three thousand soccer shoes.  It’s at this point that Knight asked his part-time artist, Carolyn Davidson, to try to design a logo.  “Something that evokes a sense of motion.”  She came back two weeks later and her sketches had a theme.  But Knight was wondering what the theme was, “…fat lightning bolts?  Chubby check marks?  Morbidly obese squiggles?…”

Davidson returned later.  Same theme, but better.  Woodell, Johnson, and a few others liked it, saying it looked like a wing or a whoosh of air.  Knight wasn’t thrilled about it, but went along because they were out of time and had to send it to the factory in Mexico.

(Nike logo, Timidonfire, Wikimedia Commons)

They also needed a name.  Falcon.  Dimension Six.  These were possibilities they’d come up with.  Knight liked Dimension Six mostly because he’d come up with it.  Everyone told him it was awful.  It didn’t mean anything.  Bengal.  Condor.  They debated possibilities.

It was time to decide.  Knight still didn’t know.  Then Woodell told him that Johnson had had a dream and then woke up with the name clearly in mind:  “Nike.”

Knight reminisced…  “The Greek goddess of victory.  The Acropolis.  The Parthenon.  The Temple…”

Knight had to decide.  He hated having to decide under time pressure.  He’s not sure if it was luck or spirit or something else, but he chose “Nike.”  Woodell said, “Hm.”  Knight replied, “Yeah, I know.  Maybe it’ll grow on us.”

(Nike logo, Wikimedia Commons)

Meanwhile, Nissho was infusing Blue Ribbon with cash.  But Knight wanted a more permanent solution.  He conceived of a public offering of convertible debentures.  People bought them, including Knight’s friend Cale.

The factory in Mexico didn’t produce good shoes.  Knight talked with Sumeragi, who knew a great deal about shoe factories around the world.  Sumeragi also offered to introduce Knight to Jonas Senter, “a shoe dog.”

Shoe dogs were people who devoted themselves wholly to the making, selling, buying, or designing of shoes.  Lifers used the phrase cheerfully to describe other lifers, men and women who had toiled so long and hard in the shoe trade, they thought and talked about nothing else.  It was an all-consuming mania… But I understood.  The average person takes seventy-five hundred steps a day, 274 million steps over the course of a long life, the equivalent of six times around the globe – shoe dogs, it seemed to me, simply wanted to be part of that journey.  Shoes were their way of connecting with humanity…

Senter was the “knockoff king.”  He’d been behind a recent flood of knockoff Adidas.  Senter’s protege was a guy named Sole.

Knight wasn’t sure partnering with Nissho was the best move.  Jaqua suggested Knight meet with his brother-in-law, Chuck Robinson, CEO of Marcona Mining, which had many joint ventures.  Each of the big eight Japanese trading firms was a partner in at least one of Marcona’s mines, records Knight.  Chuck to Buck:  “If the Japanese trading company understands the rules from the first day, they will be the best partners you’ll ever have.”

Knight went to Sumeragi and said:  “No equity in my company.  Ever.”  Sumeragi consulted a few folks, came back and said:  “No problem.  But here’s our deal.  We take four percent off the top, as a markup on product.  And market interest rates on top of that.”  Done.

Knight met Sole, who mentioned five factories in Japan.

A bit later, Bowerman was eating breakfast when he noticed the waffle iron’s gridded pattern.  This gave him an idea and he started experimenting.

…he took a sheet of stainless steel and punched it with holes, creating a waffle-like surface, and brought this back to the rubber company.  The mold they made from that steel sheet was pliable, workable, and Bowerman now had two foot-sized squares of hard rubber nubs, which he brought home and sewed to the sole of a pair of running shoes.  He gave these to one of his runners.  The runner laced them on and ran like a rabbit.

Bowerman phoned me, excited, and told me about his experiment.  He wanted me to send a sample of his waffle-soled shoes to one of my new factories.  Of course, I said.  I’d send it right away – to Nippon Rubber.

I look back over decades and see him toiling in his workshop, Mrs. Bowerman carefully helping, and I get goosebumps.  He was Edison in Menlo Park, Da Vinci in Florence, Tesla in Wardenclyffe.  Divinely inspired.  I wonder if he knew, if he had any clue, that he was the Daedalus of sneakers, that he was making history, remaking an industry, transforming the way athletes would run and stop and jump for generations.  I wonder if he could conceive in that moment all he’d done.  All that would follow.

 

1972

The National Sporting Goods Association Show in Chicago in 1972 was extremely important for Blue Ribbon because they were going to introduce the world to Nike shoes.  If sales reps liked Nike shoes, Blue Ribbon had a chance to flourish.  If not, Blue Ribbon wouldn’t be back in 1973.

Right before the show, Onitsuka announced its “acquisition” of Blue Ribbon.  Knight had to reassure Sumeragi that there was no acquisition.  At the same time, Knight couldn’t break from Onitsuka just yet.

As Woodell and Johnson prepared the booth – with stacks of Tigers and also with stacks of Nikes – they realized the Nikes from Nippon Rubber weren’t as high-quality as the Tigers.  The swooshes were crooked, too.

Darn it, this was no time to be introducing flawed shoes.  Worse, we had to push these flawed shoes on to people who weren’t our kind of people.  They were salesmen.  They talked like salesmen, walked like salesmen, and they dressed like salesmen – tight polyester shirts, Sansabelt slacks.  They were extroverts, we were introverts.  They didn’t get us, we didn’t get them, and yet our future depended on them.  And now we’d have to persuade them, somehow, that this Nike thing was worth their time and trust – and money.

I was on the verge of losing it, right on the verge.  Then I saw Johnson and Woodell were already losing it, and I realized that I couldn’t afford to… ‘Look fellas, this is the worst the shoes will ever be.  They’ll get better.  So if we can just sell these… we’ll be on our way.’

The salesmen were skeptical and full of questions about the Nikes.  But by the end of the day, Blue Ribbon had exceeded its highest expectations.  Nikes had been the smash hit of the show.

Johnson was so perplexed that he demanded an answer from the representative of one his biggest accounts.  The rep explained:

‘We’ve been doing business with you Blue Ribbon guys for years and we know that you guys tell the truth.  Everyone else bullshits, you guys always shoot straight.  So if you say this new shoe, this Nike, is worth a shot, we believe.’

Johnson came back to the booth and said, “Telling the truth.  Who knew?”  Woodell laughed.  Johnson laughed.  Knight laughed.

Two weeks later, Kitami showed up without warning in Knight’s office, asking about “this… NEE-kay.”  Knight had been rehearsing for this situation.  He replied simply that it was a side project just in case Onitsuka drops Blue Ribbon.  Kitami seemed placated.

Kitami asked if the Nikes were in stores.  No, said Knight.  Kitami asked when Blue Ribbon was going to sell to Onitsuka.  Knight answered that he still needed to talk with Bowerman.  Kitami then said he had business in California, but would be back.

Knight called Bork in Los Angeles and told him to hide the Nikes.  Bork hid them in the back of the store.  But Kitami, when visiting the store, told Bork he had to use the bathroom.  While in the back, Kitami found stacks of Nikes.

Bork called Knight and told him, “Jig’s up… It’s over.”  Bork ended up quitting.  Knight discovered later that Bork had a new job… working for Kitami.

Kitami demanded a meeting.  Bowerman, Jaqua, and Knight were in attendance.  Jaqua told Knight to say nothing no matter what.  Jaqua told Kitami that he hoped something could still be worked out, since a lawsuit would be damaging to both companies.

Knight called a company-wide meeting to explain that Onitsuka had cut them off.  Many people felt resigned, says Knight, in part because there was a recession in the United States.  Gas lines, political gridlock, rising unemployment, Vietnam.  Knight saw the discouragement in the faces of Blue Ribbon employees, so he told them:

‘…This is the moment we’ve been waiting for.  One moment.  No more selling someone else’s brand.  No more working for someone else.  Onitsuka has been holding us down for years.  Their late deliveries, their mixed-up orders, their refusal to hear and implement our design ideas – who among us isn’t sick of dealing with all that?  It’s time we faced facts:  If we’re going to succeed, or fail, we should do so on our own terms, with our own ideas – our own brand.  We posted two million in sales last year… none of which had anything to do with Onitsuka.  That number was a testament to our ingenuity and hard work.  Let’s not look at this as a crisis.  Let’s look at this as our liberation.  Our Independence Day.’

Johnson told Knight, “Your finest hour.”  Knight replied he was just telling the truth.

The Olympic track-and-field trials in 1972 were going to be in Eugene.  Blue Ribbon gave Nikes to anyone who would take them.  And they handed out Nike T-shirts left and right.

The main event was on the final day, a race between Steve Prefontaine – known as “Pre” – and the great Olympian George Young.  Pre was the biggest thing to hit American track and field since Jesse Owens.  Knight tried to figure out why.  It was hard to say, exactly.  Knight:

Sometimes I thought the secret to Pre’s appeal was his passion.  He didn’t care if he died crossing the finish line, so long as he crossed first.  No matter what Bowerman told him, no matter what his body told him, Pre refused to slow down, ease off.  He pushed himself to the brink and beyond.  This was often a counterproductive strategy, and sometimes it was plainly stupid, and occasionally it was suicidal.  But it was always uplifting for the crowd.  No matter the sport – no matter the human endeavor, really – total effort will win people’s hearts.

(Steve Prefontaine)

Gerry Lindgren was also in this race with Pre and Young.  Lindgren may have been the best distance runner in the world at that time.  Lindgren had beaten Pre when Lindgren was a senior and Pre a freshman.

Pre took the lead right away.  Young tucked in behind him.  In no time they pulled way ahead of the field and it became a two-man affair… Each man’s strategy was clear.  Young meant to stay with Pre until the final lap, then use his superior sprint to go by and win.  Pre, meanwhile, intended to set such a fast pace at the outset that by the time they got to that final lap, Young’s legs would be gone.

For eleven laps they ran a half stride apart.  With the crowd now roaring, frothing, shrieking, the two men entered the final lap.  It felt like a boxing match.  It felt like a joust… Pre reached down, found another level – we saw him do it.  He opened up a yard lead, then two, then five.  We saw Young grimacing and we knew that he would not, could not, catch Pre.  I told myself, Don’t forget this.  Do not forget.  I told myself there was much to be learned from such a display of passion, whether you were running a mile or a company.

Both men had broken the American record.  Pre had broken it by a little bit more.

…What followed was one of the greatest ovations I’ve ever heard, and I’ve spent my life in stadiums.

I’d never witnessed anything quite like that race.  And yet I didn’t just witness it.  I took part in it.  Days later I felt sore in the hams and quads.  This, I decided, this is what sports are, what they can do.  Like books, sports give people a sense of having lived other lives, of taking part in other people’s victories.  And defeats.  When sports are at their best, the spirit of the fan merges with the spirit of the athlete, and in that convergence, in that transference, is the oneness that mystics talk about.

 

1973

Bowerman had retired from coaching, partly because of the sadness of the terrorist attacks at the 1972 Olympics in Munich.  Bowerman had been able to help hide one Israeli athlete.  Bowerman had immediately called the U.S. consul and shouted, “Send the marines!”  Eleven Israeli athletes had been captured and later killed.  An unspeakable tragedy.  Knight thought of the deaths of the two Kennedys, and Dr. King, and the students at Kent State.

Ours was a difficult, death-drenched age, and at least once every day you were forced to ask yourself:  What’s the point?

Although Bowerman had retired from coaching, he was still coaching Pre.  Pre had finished a disappointing fourth at the Olympics.  He could have gotten silver if he’d allowed another runner to be the front runner and if he’d coasted in his wake.  But, of course, Pre couldn’t do that.

It took Pre six months to re-emerge.  He won the NCAA three-mile for a fourth straight year, with a time of 13:05.3.  He also won in the 5,000 by a good margin with a time of 13:22.4, a new American record.  And Bowerman had finally convinced Pre to wear Nikes.

At that time, Olympic athletes couldn’t receive endorsement money.  So Pre sometimes tended bar and occasionally ran in Europe in exchange for illicit cash from promoters.

Knight decided to hire Pre, partly to keep him from injuring himself by racing too much.  Pre’s title was National Director of Public Affairs.  People often asked Knight what that meant.  Knight would say, “It means he can run fast.”  Pre wore Nikes everywhere and he preached Nike as gospel, says Knight.

Around this time, Knight realized that Johnson was becoming an excellent designer.  The East Coast was running smoothly, but needed reorganization.  So Knight asked Johnson to switch places with Woodell.  Woodell excelled at operations and thus would be a great fit for the East Coast situation.

Although Johnson and Woodell irritated one another, they both denied it.  When Knight asked them to switch places, the two exchanged house keys without the slightest complaint.

In the spring of 1973, Knight held his second meeting with the debenture holders.  He had to tell them that despite $3.2 million in sales, the company had lost $57,000.  The reaction was negative.  Knight tried to explain that sales continue to explode higher.  But the investors were not happy.

Knight left the meeting thinking he would never, ever take the company public.  He didn’t want to deal with that much negativity and rejection ever again.

Onitsuka filed suit against Blue Ribbon in Japan.  So Blue Ribbon had to file against them in the United States.

Knight asked his Cousin Houser to be in charge of the case.  Houser was a fine lawyer who carried himself with confidence.

Better yet, he was a tenacious competitor.  When we were kids Cousin Houser and I used to play vicious, marathon games of badminton in his backyard.  One summer we played exactly 116 games.  Why 116?  Because Cousin Houser beat me 115 straight times.  I refused to quit until I’d won.  And he had no trouble understanding my position.

More importantly, Cousin Houser was able to talk his firm into taking the Blue Ribbon case on contingency.

Knight continued his evening conversations with this father, who believed strongly in Blue Ribbon’s cause.  Knight’s father, who had been trained as a lawyer, spent time studying law books.  He reassured Buck, “we” are going to win.  This support from his father boosted Buck’s spirits at a challenging time.

(Law library, Photo by Spiroview Inc.)

Cousin Houser told Knight one day that he was bringing on a new member of the team, a young lawyer from UC Berkeley School of Law, Rob Strasser.  Not only was Strasser brilliant.  He also believed in the rightness of Blue Ribbon’s case, viewing it as a “holy crusade.”

Strasser was a fellow Oregonian who felt looked down on by folks north and south.  Moreover, he felt like an outcast.  Knight could relate.  Strasser often downplayed his intelligence for fear of alienating people.  Knight could relate to that, too.

Intelligence like Strasser’s, however, couldn’t be hidden for long.  He was one of the greatest thinkers I ever met.  Debator, negotiator, talker, seeker – his mind was always whirring, trying to understand.

When he wasn’t preparing for the trial, Knight was exclusively focused on sales.  It was essential that they sell out every pair of shoes in each order.  The company was still growing fast and cash was always short.

Whenever there was a delay, Woodell always knew what the problem was and could quickly let Knight know.  Knight on Woodell:

He had a superb talent for underplaying the bad, and underplaying the good, for simply being in the moment… throughout the day a steady rain of pigeon poop would fall on Woodell’s hair, shoulders, desktop.  But Woodell would simply dust himself off, casually clear his desk with the side of his hand, and continue with his work.

…I tried often to emulate Woodell’s Zen monk demeanor.  Most days, however, it was beyond me…

Blue Ribbon couldn’t meet demand.  This frustrated Knight.  Supplies were arriving on time.  But in 1973, it seemed that the whole world, all at once, wanted running shoes.  And there were never enough.  This made things precarious, to say the least, for Blue Ribbon:

…We were leveraged to the hilt, and like most people who live from paycheck to paycheck, we were walking the edge of a precipice.  When a shipment of shoes was late, our pair count plummeted.  When our pair count plummeted, we weren’t able to generate enough revenue to repay Nissho and the Bank of California on time.  When we couldn’t repay Nissho and the Bank of California on time, we couldn’t borrow more.  When we couldn’t borrow more we were late placing our next order.

Sales for 1973 hit $4.8 million, up 50 percent from the previous year.  But Blue Ribbon was still on fragile ground, it seemed.  Knight then thought of asking their retailers to sign up for large and unrefundable orders, six months in advance, in exchange for hefty discounts, up to 7 percent.  Such long-term commitments from well-established retailers like Nordstrom, Kinney, Athlete’s Foot, United Sporting Goods, and others, could then be used to get more credit from Nissho and the Bank of California.

Much later, after much protesting, the retailers signed on to the long-term commitments.

 

1974

The trial.  Federal courthouse in downtown Portland.  Wayne Hilliard was the lead lawyer for the opposition.  He was fiery and eloquent.  Cousin Houser was the lead for Blue Ribbon.  He’d convinced his firm to take the Blue Ribbon case on contingency.  But instead of a few months, it was now two years later.  Houser hadn’t seen a dime and costs were huge.  Moreover, Houser told Knight that his fellow law partners sometimes put a great deal of pressure on Houser to drop the Blue Ribbon case.

(Federal courthouse in Portland, Oregon, Wikimedia Commons)

Houser stuck with the case.  He wasn’t fiery.  But he was prepared and dedicated.  Knight was initially disappointed, but later came to admire him.  “Fire or no, Cousin Houser was a true hero.”

After being questioned by both sides, Knight felt he hadn’t done well at all, a D minus.  Houser and Strasser didn’t disagree.

The judge in the case was the Honorable James Burns.  He called himself James the Just.  Johnson made the mistake of discussing the trial with a store manager after James the Just had expressly forbidden all discussion of the case outside the courtroom.  James the Just was upset.  Knight:

Johnson redeemed himself with his testimony.  Articulate, dazzlingly anal about the tiniest details, he described the Boston and the Cortez better than anyone else in the world could, including me.  Hilliard tried and tried to break him, and couldn’t.

Later on, the testimony of Iwano, the young assistant who’d been with Kitami, was heard.  Iwano testified that Kitami had a fixed plan already in place to break the contract with Blue Ribbon.  Kitami had openly discussed this plan on many occasions, said Iwano.

Bowerman’s testimony was so-so because, out of disdain, he hadn’t prepared.  Woodell, for his part, was nervous.

Mr. Onitsuka said he hadn’t known anything about the conflict between Kitami and Knight.  Kitami, in his testimony, lied again and again.  He said that he had no plan to break the contract with Blue Ribbon.  He also claimed that meeting with other distributors had just been market research.  As well, the idea of acquiring Blue Ribbon “was initiated by Phil Knight.”

James the Just was convinced that Blue Ribbon had been more truthful.  In particular, Iwano seemed truthful, while Kitami didn’t.  On the issue of trademarks, Blue Ribbon would retain all rights to the Boston and the Cortez.

A bit later, Hilliard offered $400,000.  Finally, Blue Ribbon accepted.  Knight was happy for Cousin Houser, who would get half.  It was the largest payment in the history of his firm.

Knight, with help from Hayes, convinced Strasser to come work for Blue Ribbon.  Strasser later accepted.

Japanese labor costs were rising.  The yen was fluctuating.  Knight decided Blue Ribbon needed to find factories outside of Japan.  He looked at Taiwan, but shoe factories there weren’t quite ready.  He looked next at Puerto Rico.

Then Knight went to the east coast to look for possible factories.  The first factory owner laughed in Knight’s face.

The next empty factory Knight visited – with Johnson – the owner was willing to lease the third floor to Blue Ribbon.  He suggested a local guy to manage the factory, Bill Giampietro.  Giampietro turned out to be “a true shoe dog,” said Knight.  All he’d ever done is make shoes, like his father.  Perfect.  Could he get the old Exeter factory up and running?  How much would it cost?  No problem.  About $250,000.  Deal.

Knight asked Johnson to run the new factory.  Johnson said, “…what do I know about running a factory?  I’d be in completely over my head.”

Knight couldn’t stop laughing:  “Over your head?  Over your head!  We’re all in over our heads!  Way over!”

Knight writes that, at Blue Ribbon, it wasn’t that they thought they couldn’t fail.  On the contrary, they thought they would fail.  But they believed they would fail fast, learn from it, and be better for it.

Finishing up 1974, the company was on track for $8 million in sales.  Their contact at Bank of California, Perry Holland, kept telling them to slow down.  So they sped up, as usual.

 

1975

Knight kept telling Hayes, “Pay Nissho first.”  Blue Ribbon had a line of credit at the bank for $1 million.  They had a second million from Nissho.  That was absolutely essential.

…Grow or die, that’s what I believed, no matter the situation.  Why cut your order from $3 million down to $2 million if you believed in your bones that demand out there was for $5 million?  So I was forever pushing my conservative bankers to the brink, forcing them into a game of chicken.  I’d order a number of shoes that seemed to them absurd, a number we’d need to stretch to pay for, and I’d always just barely pay for them, in the nick of time, and then just barely pay our other monthly bills, at the last minute, always doing just enough, and no more, to prevent the bankers from booting us.  And then, at the end of the month, I’d empty our accounts to pay Nissho and start from zero again.

Demand was always greater than sales, so Knight concluded his approach was reasonable.  There was a new manager at Nissho’s Portland office, Tadayuki Ito, in place of Sumeragi.  (Sumeragi still helped with the Blue Ribbon account, though.)

One day in the spring of 1975, Blue Ribbon was $75,000 short of the $1 million they owed Nissho.  Blue Ribbon would have to completely drain every other account to make up for the shortfall.  Retail stores.  Johnson’s Exeter factory.  All of them.

(Illustration by Lkeskinen0)

In Exeter, a mob of angry workers was at Johnson’s door.  Giampetro drove with Johnson to see an old friend who owned a box company that depended on Blue Ribbon.  Giampetro asked for a loan of $5,000 (more than $25,000 in 2018), which was outrageous.  The man counted out fifty crisp hundred-dollar bills, says Knight.

Then Holland called Knight and Hayes to a meeting at the Bank of California.  The bank would no longer do business with Blue Ribbon.

Knight was worried how Ito and Sumeragi, representing Nissho, would react.  Ito and Sumeragi, after hearing what happened, said they would need to look at Blue Ribbon’s books.

On the weekend, Knight called a company-wide meeting to discuss the situation.  The Exeter factory had been a secret kept from Nissho.  But everyone agreed to give Nissho all information.

During this meeting, two creditors – owed $500,000 and $100,000 – called and were livid.  They were on their way to Oregon to collect and cash out.

On Monday, Ito and Sumeragi arrived at Blue Ribbon’s office.  Without a word, they went through the lobby to the conference room, sat down with the books and got to work.  Then Ito came to information related to the Exeter factory.  He did a slow double-take and then looked up at Knight.  Knight nodded.  Ito smiled.  Knight:

I gave him a weak half smile in return, and in that brief wordless exchange countless fates and futures were decided.

It turned out that Sumeragi had been trying to help Blue Ribbon by hiding Nissho’s invoices in a drawer.  Blue Ribbon had been stressing out trying to pay Nissho on time, but they’d never paid them on time because Sumeragi thought he was helping, writes Knight.

Ito accused Sumeragi of working for Blue Ribbon.  Sumeragi swore on his life that he’d acted independently.  Ito asked why.  Sumeragi answered that he thought Blue Ribbon would be a great success, perhaps a $20 million account.  Ito eventually forgave Blue Ribbon.  “There are worse things than ambition,” he said.

Ito accompanied Knight and Hayes to a meeting with the Bank of California.  Only this time, Ito – whom Knight saw as a “mythic samurai, wielding a jeweled sword” – was on their side.

(Samurai, Photo by Esolex)

According to Knight, Ito opened the meeting and “went all in.”  After confirming that Bank of California no longer wanted to handle Blue Ribbon’s account, Ito said Nissho wanted to pay off Blue Ribbon’s outstanding debt.  He asked for the number and it was the same number he’d learned earlier.  Ito already had a check made out for the amount and slid an envelope with the check across the table.  Ito insisted the check be deposited immediately.

After the meeting, Knight and Hayes bowed to Ito.  Ito remarked:

‘Such stupidity… I do not like such stupidity.  People pay too much attention to numbers.’

***

Blue Ribbon still needed a bank.  They started calling.  “The first six hung up on us,” recalls Knight.  First State Bank of Oregon didn’t hang up.  They offered one million in credit.

Pre died in a tragic car accident at the age of twenty-four.  At the time of his death, he held every American record from 2,000 to 10,000 meters, from two miles to six miles.  People created a shrine where Pre had died.  They left flowers, letters, notes, gifts.  Knight, Johnson, and Woodell decided that Blue Ribbon would curate Pre’s rock, making it a holy site forever.

 

1976

Knight had several meetings early in 1976 with Woodell, Hayes, and Strasser about the company’s cash situation.  Nissho was lending Blue Ribbon millions, but to keep up with demand, they needed millions more.  The most logical solution was to go public.  But Knight and the others felt that it just wasn’t who they were.  No way.

They found other ways to raise money, including a million-dollar loan guaranteed by the U.S. Small Business Administration.

Meanwhile, Bowerman’s waffle trainer was getting even more popular.

(Nike 1976 waffle trainer)

With its unique outer sole, and its pillowy midsole cushion, and its below-market price ($24.95), the waffle trainer was continuing to capture the popular imagination like no previous shoe.  It didn’t just feel different, or fit different – it looked different.  Radically so.  Bright red upper, fat white swoosh – it was a revolution in aesthetics.  Its look was drawing hundreds of thousands of new customers into the Nike fold, and its performance was sealing their loyalty.  It had better traction and cushioning than anything on the market.

Watching that shoe evolve in 1976 from popular accessory to cultural artifact, I had a thought.  People might start wearing this thing to class.

And the office.

And the grocery store.

And throughout their everyday lives.

It was a rather grandiose idea… So I ordered the factories to start making the waffle trainer in blue, which would go better with jeans, and that’s when it really took off.

We couldn’t make enough.  Retailers and sales reps were on their knees, pleading for all the waffle trainers we could ship.  The soaring pair counts were transforming our company, not to mention the industry.  We were seeing numbers that redefined our long-term goals, because they gave us something we’d always lacked – an identify.  More than a brand, Nike was now becoming a household word, to such an extent that we would have to change the company name.  Blue Ribbon, we decided, had run its course.  We would have to incorporate as Nike, Inc.

They needed to ramp up production.  Knight realized the time had come to visit Taiwan.  To help with the Taiwan effort, Knight turned to Jim Gorman.  Gorman had been raised in a series of foster homes.  Nike was the family he’d never had.

…In every instance, Gorman had done a fine job and never uttered a sour word.  He seemed the perfect candidate to take on the latest mission impossible – Taiwan.  But first I needed to give him a crash course on Asia.  So I scheduled a trip, just the two of us.

Gorman was full of questions for Knight and took notes on everything.  Knight enjoyed teaching Gorman, partly because Knight himself could learn what he knew even better through the process of teaching.

Taiwan had a hundred smaller factories, whereas South Korea had a few larger ones.  That’s why Nike needed to go to Taiwan at this juncture.  Demand for Nikes was exploding, but their volume was still too low for a giant shoe factory.  However, Knight knew it would be a challenge to get a shoe factory in Taiwan to improve its quality enough to be able to produce Nikes.

During the visit to various Taiwan shoe factories, Jerry Hsieh introduced himself to Knight and Gorman.  Hsieh was a genuine shoe dog, but quite young, twenty-something.  When Knight and Gorman found their way to Hsieh’s office – a room stuffed with shoes everywhere – Hsieh started sharing his deep knowledge of shoes.  Also, Hsieh told them he knew the very best shoe factories in Taiwan and for a small fee, would be happy to introduce them.  They agreed on a commission per pair.

The 1976 Olympic trials, again in Eugene.  In the 10,000 meter race, all top three finishers wore Nikes.  Some top finishers in other qualifying races also wore Nikes.  Meanwhile, Penny created a great number of Nike T-shirts.  People would see other people wearing the Nike T-shirts and want to buy one.  The Nike employees heard people whispering.  “Nike.”  “Nike.”  “Nike.”

At the close of 1976, Nike had doubled its sales to $14 million.  The company still had no cash, though.  Its bank accounts were often at zero.

The company’s biannual retreat was taking place.  People called it Buttface.

Johnson coined the phrase, we think.  At one of our earliest retreats he muttered:  “How many multi-million dollar companies can you yell out, ‘Hey, Buttface,’ and the entire management team turns around?”  It got a laugh.  And then it stuck.  And then it became a key part of our vernacular.  Buttface referred to both the retreat and the retreaters, and it not only captured the informal mood of those retreats, where no idea was too sacred to be mocked, and no person was too important to be ridiculed, it also summed up the company spirit, mission and ethos.

Knight continues:

…The problems confronting us were grave, complex, insurmountable… And yet we were always laughing.  Sometimes, after a really cathartic guffaw, I’d look around the table and feel overcome by emotion.  Camaraderie, loyalty, gratitude.  Even love.  Surely love.  But I also remember feeling shocked that these were the men I’d assembled.  These were the founding fathers of a multi-million dollar company that sold athletic shoes?  A paralyzed guy, two morbidly obese guys, a chain-smoking guy?  It was bracing to realize that, in this group, the one with whom I had the most in common was… Johnson.  And yet, it was undeniable.  While everyone else was laughing, rioting, he’d be the sane one, sitting quietly in the middle of the table reading a book.

A bit later, Knight writes:

Undoubtedly we looked, to any casual observer, like a sorry, motley crew, hopelessly mismatched.  But in fact we were more alike than different, and that gave a coherence to our goals and our efforts.  We were mostly Oregon guys, which was important.  We had an inborn need to prove ourselves, to show the world that we weren’t hicks and hayseeds.  And we were nearly all merciless self-loathers, which kept the egos in check.  There was none of that smartest-guy-in-the-room foolishness.  Hayes, Strasser, Woodell, Johnson, each would have been the smartest guy in any room, but none believed of himself, or the next guy.  Our meetings were defined by contempt, disdain, and heaps of abuse.

(Photo by Chris Dorney)

Knight records:

…Each of us had been misunderstood, misjudged, dismissed.  Shunned by bosses, spurned by luck, rejected by society, short-changed by fate when looks and other natural graces were handed out.  We’d each been forged by early failure.  We’d each given ourselves to some quest, some attempt at validation or meaning, and fallen short.

I identified with the born loser in each Buttface, and vice versa, and I knew that together we could become winners…

Knight’s management style continued to be very hands-off, following Patton’s leadership belief:

Don’t tell people how to do things, tell them what to do and let them surprise you with their results.

Nike’s culture seemed to be working thus far.  Since Bork, no one had gotten really upset, not even what they were paid, which is unusual, notes Knight.  Knight created a culture he himself would have wanted:  let people be, let people do, let people make their own mistakes.

 

1977

M. Frank Rudy, a former aerospace engineer, and his business partner, Bob Bogert, presented to Nike the idea of putting air in the soles of shoes.  Great cushioning, great support, a wonderful ride.  Knight tried wearing a pair Rudy showed him on a six-mile run.  Unstable, but one great ride.

Strasser, who by this point had become Nike’s negotiator, offered Rudy 10 cents for every pair we sold.  Rudy asked for twenty.  They settled somewhere in the middle.  Knight sent Rudy and his partner back to Exeter, which “was becoming our de facto Research and Development Department.”

Knight calls this time “an odd moment,” saying furthermore that “a second strange shoe dog showed up on our door step.  His name was Sonny Vaccaro…”.  Vaccaro had founded the Dapper Dan Classic, a high school all-star game that had become very popular.  Though it, Vaccaro had gotten to know many coaches.  Knight hired Vaccaro and sent him, with Strasser, to sign up college basketball coaches.  Knight expected them to fail.  But they succeeded.

Knight knew he had to meet again with Chuck Robinson, who’d served with distinction as a lieutenant commander on a battle ship in World War II.  Chuck knew business better than anyone Knight had ever met.  Recently, he’d been the number two guy under Henry Kissinger, so he wasn’t available for meetings.  Now Chuck was free.

Chuck took a look at Nike’s financials and couldn’t stop laughing, saying, “Compositionally, you are a Japanese trading company – 90 percent debt!”

Chuck told Buck, “You can’t live like this.”  The solution was to go public in order to raise a large amount of cash.  Knight invited Chuck to join the board.  Chuck agreed, to Knight’s surprise.

When Knight put the question of going public to a company vote, however, the consensus was still to remain private.

Then they received a letter from the U.S. Customs Service containing a bill for $25 million.  Nike’s competitors, Converse and Keds – plus a few small factories – were behind it.  They had been lobbying in Washington, DC, trying to slow Nike by enforcing the American Selling Price, an old law dating back to protectionist days.

(Photo by Ian Wilson)

ASP – American Selling Price – said that import duties on nylon shoes should be 20 percent of the shoe’s manufacturing cost.  Unless there was a “similar shoe” made by a U.S. competitor.  Then it should be 20 percent of that shoe’s selling price.  Nike’s competitors just needed to make some shoes deemed “similar,” price them very high, and voila – high import duties for Nike.

They’d managed to pull the trick off, raising Nike’s import duties retroactively by 40 percent.

Near the end of 1977, Nike’s sales were approaching $70 million.

 

1978

Knight calls Strasser the “five-star general” in the battle with the U.S. government.  But they knew they needed “a few good men.”  Strasser suggested a friend of his, a young Portland lawyer, Richard Werschkul.  Stanford undergrad, University of Oregon law.  A sharp guy with a presence.  And an eccentric streak.  Some worried he was too serious and obsessive.  But that seemed good to Knight.  And Knight trusted Strasser.  Werschkul was dispatched to Washington, DC.

Meanwhile, sales were on track for $140 million.  Furthermore, Nike shoes were finally recognized as higher quality than Adidas shoes.  Knight thought Nike had led in quality and innovation for years.

Nike had to start selling clothes, announced Knight at Buttface in 1978.  First, Adidas sold more apparel than shoes.  Second, it would be easier to get athletes into endorsement deals.

Knight decided to hire a young accountant, Bob Nelson, and put him in charge of the new line of Nike apparel.  But Nelson had no sense of style, unfortunately.  When he presented his ideas, they didn’t look good.  Knight decided to transfer him to an accounting position, where he would excel.  Knight writes:

…Then I quietly shifted Woodell to apparel.  He did his typically flawless job, assembling a line that gained immediate attention and respect in the industry.  I asked myself why I didn’t just let Woodell do everything.

Tailwind – a new Nike shoe with air – came out in late 1978.  Then Nike had to recall it due to a design flaw.  Knight concluded they’d learned a valuable lesson.  “Don’t put twelve innovations into one shoe.”

Around this time, many seemed to be suffering from burnout, including Knight.  And back in DC, Werschkul was becoming hyper obsessive.  He’d tried to talk with everyone possible.  They all told him to put something in writing so they could study it.

Werschkul spent months writing.  It became hundreds of pages.  “Without a shred of irony Werschkul called it:  Werschkul on American Selling Price, Volume I.”  Knight:

When you thought about it, when you really thought about it, what really scared you was that Volume I.

Knight sent Strasser to calm Werschkul down.  Knight realized that he himself would have to go to DC.  “Maybe the cure for any burnout… is just to work harder.”

 

1979

Senators Mark O. Hatfield and Bob Packwood helped Nike deal with the $25 million bill from U.S. Customs.  Knight started the process of looking for a factory in China.

 

1980

Chuck Robinson suggested to Knight that Nike could go public but have two classes of stock, class A and class B.  Nike insiders would own class A shares, which would allow them to name three-quarters of the board of directors.  The Washington Post Company and a few other companies had done this.

Knight explained the idea – going public with two classes of stock – to colleagues at Nike.  All agreed that it was time to go public to raise badly needed cash.

In China, Knight – with Strasser, Hayes, and others – signed a deal with China’s Ministry of Sports.  Four years later, at the Olympics in Los Angeles, the Chinese track-and-field team entered the stadium wearing Nike shoes and warm-ups.  Before leaving China, Nike signed a deal with two Chinese factories.

Knight then muses about “business”:

It seems wrong to call it “business.”  It seems wrong to throw all those hectic days and sleepless nights, all those magnificent triumphs and desperate struggles, under that bland, generic banner:  business.  What we were doing felt like so much more.  Each new day brought fifty new problems, fifty tough decisions that needed to be made, right now, and we were always acutely aware that one rash move, one wrong decision could be the end.  The margin for error was forever getting narrower, while the stakes were forever creeping higher – and none of us wavered in the belief that “stakes” didn’t mean “money.”  For some, I realize, business is the all-out pursuit of profits, period, full stop, but for us business was no more about making money than being human is about making blood.  Yes, the human body needs blood.  It needs to manufacture red and white cells and platelets and redistribute them evenly, smoothly, to all the right places, on time, or else.  But that day-to-day mission of the human body isn’t our mission as human beings.  It’s a basic process that enables our higher aims, and life always strives to transcend the basic processes of living – and at some point in the late 1970s, I did, too.  I redefined winning, expanded it beyond my original definition of not losing, of merely staying alive.  That was no longer enough to sustain me, or my company.  We wanted, as all great businesses do, to create, to contribute, and we dared to say so aloud.  When you make something, when you improve something, when you add to some new thing or service to the lives of strangers, making them happier, or healthier, or safer, or better, and when you do it all crisply and efficiently, smartly, the way everything should be done but so seldom is – you’re participating more fully in the whole grand human drama.  More than simply alive, you’re helping others to live more fully, and if that’s business, all right, call me a businessman.

 

BOOLE MICROCAP FUND

An equal weighted group of micro caps generally far outperforms an equal weighted (or cap-weighted) group of larger stocks over time.  See the historical chart here:  http://boolefund.com/best-performers-microcap-stocks/

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There are roughly 10-20 positions in the portfolio.  The size of each position is determined by its rank.  Typically the largest position is 15-20% (at cost), while the average position is 8-10% (at cost).  Positions are held for 3 to 5 years unless a stock approaches intrinsic value sooner or an error has been discovered.

The goal of the Boole Microcap Fund is to outperform the Russell Microcap Index over time, net of fees.  The Boole Fund has low fees. 

 

If you are interested in finding out more, please e-mail me or leave a comment.

My e-mail: jb@boolefund.com

 

Disclosures: Past performance is not a guarantee or a reliable indicator of future results. All investments contain risk and may lose value. This material is distributed for informational purposes only. Forecasts, estimates, and certain information contained herein should not be considered as investment advice or a recommendation of any particular security, strategy or investment product. Information contained herein has been obtained from sources believed to be reliable, but not guaranteed. No part of this article may be reproduced in any form, or referred to in any other publication, without express written permission of Boole Capital, LLC.

 

 

Warren Buffett’s Ground Rules

(Image:  Zen Buddha Silence by Marilyn Barbone.)

July 29, 2018

Warren Buffett’s Ground Rules: Words of Wisdom from the Partnership Letters of the World’s Greatest Investor, is an excellent book by Jeremy C. Miller.  Miller did the book with no input at all from Buffett.  But Buffett has commented quite favorably on the result:

Mr. Miller has done a superb job of researching and dissecting the operation of Buffett Partnership Ltd., and of explaining how Berkshire’s culture has evolved from its BPL origin.  If you are fascinated by investment theory and practice, you will enjoy this book.

Miller has arranged each chapter around a single theme.  Here is a brief summary of these chapters:

  • Orientation—The Principles of Ben Graham
  • Compounding
  • Measuring Up
  • The Partnership—An Elegant Structure
  • The Generals
  • Workouts
  • Controls
  • Dempster Diving—The Asset Conversion Play
  • Conservative versus Conventional
  • Size versus Performance
  • Go-Go or No-Go
  • Toward a Higher Form

(Buffett teaching at the University of Nebraska, via Wikimedia Commons)

 

ORIENTATION—The Principles of Ben Graham

At the beginning of the Buffett Partnership Ltd. (BPL), the small amount of capital Buffett was investing—$100,100—meant that, in a sense, his opportunities were similar to that of any small individual investor.  No companies were too small or obscure to be potential investment opportunities.

Ben Graham, the father of value investing, was Buffett’s teacher and mentor.  Buffett learned several key principles from Graham that are still true today and that still inform Buffett’s investing:

  • Margin of Safety
  • Market Prices
  • Owning Stock is Owning Part of a Business
  • Forecasting

Margin of Safety

Margin of safety means that if you think a stock is worth $20 a share, then you try to buy it at $10 (or lower).  You try to buy well below your estimate of the intrinsic value of the business.

No investor is always right.  Good value investors tend to be right about 60% of the time and wrong 40% of the time.  Sometimes an investor makes a mistake.  Other times an investor gets unlucky.  Luck does play a role, and the future is always unpredictable to an extent.

A margin of safety is meant to help limit losses in those cases where you make a mistake or are unlucky.

Market Prices

Market prices in the shorter term often deviate from intrinsic value.  The intrinsic value of any business is the total cash that can be taken out of the business over time, discounted back to the present.  (For some businesses, liquidation value is the best estimate of intrinsic value.)   Figuring out the intrinsic value of a given business requires careful analysis, which should be done without any input from stock price fluctuations.  Graham notes that many investors make the mistake of thinking that random stock price movements actually represent something fundamental, but they rarely do.

(Illustration by Prairat Fhunta)

It is only over a long period of time that a stock price will approximate the intrinsic value of a business based on the actual business results.  Over shorter periods of time, stock prices can be completely irrational, deviating significantly from the intrinsic value of a given business.

According to Graham, the wise, long-term value investor will buy if the price get irrationally low and will sell if the price gets irrationally high.  Most of the time, however, he will simply ignore the random daily gyrations of stock prices.  Summarizing Graham’s lesson, Buffett wrote:

[A] market quote’s availability should never be turned into a liability whereby its periodic aberrations in turn formulate your judgments.

It is only over a period of roughly 3 to 5 years—at a minimum—that the stock price of an individual business can be expected to track intrinsic value.

Owning Stock is Owning Part of a Business

A share of stock is a fractional ownership claim on the entire business.  Thus, if you can value the business—whether based on liquidation value, net asset value, or discounted cash flows—then you can value the stock.

(Illustration by Teguh Jati Prasetyo)

As Miller explains, a company’s shares over the lifetime of a business will necessarily produce a return equal to the returns produced by that business.  Any investor can enjoy the returns of a given business as long as they do not pay too high a price for the stock.

Value investors focus on valuing businesses, and they do not worry about unpredictable shorter term stock prices.  Buffett again:

We don’t buy and sell stocks based upon what other people think the stock market is going to do (I never have an opinion) but rather upon what we think the company is going to do.  The course of the stock market will determine, to a great degree, when we will be right, but the accuracy of our analysis of the company will largely determine whether we will be right.  In other words, we tend to concentrate on what should happen, not when it should happen.

Buffett stresses these lessons repeatedly.  As Miller writes, stocks are not pieces of paper to trade back and forth.  Stocks are claims on a business, and some of those businesses can be valued.  We cannot predict when a stock price will approximate intrinsic value, but we know that it will in the long run.  The market eventually gets it right.  The proper focus for an investor is finding the right businesses at the right prices, without worrying about when an investment will work.

Forecasting

Buffett learned from Graham that macro variables simply cannot be predicted.  It’s just too hard to forecast the stock market, interest rates, commodity prices, GDP, etc.  Regarding the annual values of macro variables, Buffett was (and still is) extremely consistent in his opinion:

I don’t have the first clue.

All of Buffett’s experience over the past 65+ years has convinced him even more that such variables simply can’t be predicted from year to year with any sort of reliability.  As Buffett wrote in 2014:

Anything can happen anytime in markets.  And no advisor, economist, or TV commentator—and definitely not Charlie nor I—can tell you when chaos will occur.  Market forecasters will fill your ear but will never fill your wallet.

Link: http://berkshirehathaway.com/letters/2014ltr.pdf

(Illustration by Maxim Popov)

Ben Graham:

If I have noticed anything over these sixty years on Wall Street, it is that people do not succeed in forecasting what’s going to happen to the stock market.

Seth Klarman:

In reality, no one knows what the market will do; trying to predict it is a waste of time and investing based upon that prediction is a speculative undertaking.

Finally, Buffett again:

Charlie and I never have an opinion on the market because it wouldn’t be any good and it might interfere with the opinions we have that are good.

The unpredictability of the stock market from year to year (along with other macro variables) is an extremely important lesson for investors.  History is full of examples of highly intelligent people making these types of predictions, and being wrong.  Miller notes:

Through Buffett’s insights, we learn not to fall victim to the siren songs of these ‘expert’ opinions and churn our portfolios, jumping from guesstimate to guesstimate and allowing what could otherwise be a decent result to be consumed by taxes, commissions, and random chance.

Buffett himself is a good example of how unpredictable the stock market is.  For most of the years when Buffett ran BPL—from the mid-1950’s until 1969—he often commented that he thought stocks were overvalued.  But as a value investor, Buffett focused nearly all his time on finding individual stocks that were undervalued.  He kept writing that the stock market would decline, even though he didn’t know when.  It turned out to take almost a decade from Buffett’s initial warning before the stock market actually did decline.  Because he stayed focused on individual stocks, his track record was stellar.  Had Buffett ever stopped focusing on individual stocks because he was worried about a stock market decline, he would have missed many years of excellent results.

Miller remarks:

A good deal of Buffett’s astonishing success during the Partnership years and beyond has come from never pretending to know things that were either unknowable or unknown.

Miller concludes:

The good news is that the occasional market drop is of little consequence to long-term investors.  Preparing yourself to shrug off the next downturn is an important element of the method Buffett lays out.  While no one knows what the market is going to do from year to year, odds are we will have at least a few 20-30% drops over the next decade or two.  Exactly when these occur is of no great significance.  What matters is where you start and where you end up—shuffle around the order of the plus and minus years and you still come to the same ultimate result in the end.  Since the general trend is up, as long as a severe 25-40% drop isn’t going to somehow cause you to sell out at the low prices, you’re apt to do pretty well in stocks over the long run.  You can allow the market pops and drops to come and go, as they inevitably will.

For the vast majority of investors, it is literally true that they would get the best long-term results if, after buying some decent investments (value investments or index funds), they completely forgot about these holdings.  One study by Fidelity showed that the best performing of all their account holders literally forgot they had portfolios at all.

Graham explained this long ago (as quoted by Miller):

The true investor scarcely ever is forced to sell his shares, and at all other times he is free to disregard the current price quotation.  He need pay attention to it and act upon it only to the extent that it suits his book, and no more.  Thus the investor who permits himself to be stampeded or unduly worried by unjustified market declines in his holdings is perversely transforming his basic advantage into a basic disadvantage.  That man would be better off if his stocks had no market quotation at all, for he would then be spared the mental anguish caused him by other persons’ mistakes of judgment.

 

COMPOUNDING

If Buffett skipped a haircut for $10 in 1956 and invested it instead, that $10 would be worth more than $1 million today ($10 compounded at 22% for 60 years).  Being keenly aware of the power of compounding, Buffett has always been exceptionally frugal.

(Photo by Bjørn Hovdal)

Another example of the power of compounding is Ronald Read, a gas station attendant.  As Miller observes, Read ended up with $8 million by consistently investing a small portion of his salary into high-quality dividend-paying stocks.

In Buffett’s case, after becoming the world’s richest man during a few different years, he was able to make the largest private charitable donation in history—to the Gates Foundation, run by his friends Bill and Melinda Gates.  It’s also noteworthy, says Miller, that Buffett is (and has long been) one of the happiest people on earth because he gets to spend the majority of his time doing things he loves doing.

Stocks versus Bonds Today

Miller writes (in 2016):

Today, with bond yields not too far from zero, a 5-6% per annum result over the next 20 to 30 years seems like a reasonable assumption [for stocks].  If we get those kinds of results, the power of compound interest will be just as important, but it will take longer for the effects to gain momentum.

Small costs add up to a very large difference over time.  Probably no one explains this better than Jack Bogle.  See: http://boolefund.com/bogle-index-funds/

 

MEASURING UP

One of Buffett’s “Ground Rules” for BPL was Ground Rule #5:

While I much prefer a five-year test, I feel three years is an absolute minimum for judging performance.  It is a certainty that we will have years when the partnership performance is poorer, perhaps substantially so, than the Dow.  If any three-year or longer period produces poor results, we should start looking around for other places to have our money.  An exception to the latter statement would be three years covering a speculative explosion in a bull market.

Buffett also set very ambitious goals at the outset of BPL, including beating the Dow by an average margin of 10 percentage points per year.  Buffett explains how his value investing approach could achieve this target:

I would consider a year in which we declined 15% and the Average 30% to be much superior to a year when both we and the Average advanced 20%.  Over a period of time there are going to be good and bad years; there is nothing to be gained by getting enthused or depressed about the sequence in which they occur.  The important thing is to be beating par; a four on a par three hole is not as good as a five on a par five hole and it is unrealistic to assume we are not going to have our share of both par three’s and par five’s.

 

THE PARTNERSHIP: AN ELEGANT STRUCTURE

Incentives drive human conduct.  The vast majority of people underestimate just how important incentives are when trying to predict or explain human behavior.  As Charlie Munger has said:

I think I’ve been in the top 5% of my age cohort almost my entire adult life in understanding the power of incentives, and yet I’ve always underestimated that power.  Never a year passes but I get some surprise that pushes a little further my appreciation of the incentive superpower.

(Image by Ctitze)

Buffett figured that stocks would increase 5-7% per year on average.  He designed the fee structure of BPL with this in mind.  The chief fee structure was as follows:  there would be no flat fee based on assets under management, and there would be no fee on the first 6% increase in any given year.  There would be a fee of 25% of profits above the first 6% increase in any given year.

The 6% would compound from year to year.  Because Buffett’s explicitly stated goal was to beat the Dow by an average of 10% per year, his fee structure was designed accordingly.  Unlike most professional investors, Buffett didn’t charge any flat fee just for having assets under management.  Rather, his entire fee essentially came from beating the market—or beating a 6% increase compounded each year.  If Buffett did much better than the market, then he would be rewarded accordingly.  Yet if Buffett fell behind the market, then it could take some time before he earned any fees, since the 6% level compounded each and every year.

In a nutshell, the incentives were well-designed for Buffett to minimize the downside and maximize the upside.  Because Buffett understood Graham’s value investing approach to be set up in just this way—where minimizing the downside was a part of maximizing the upside—Buffett was incentivized to do value investing as well as he possibly could.

Compare Buffett’s fee structure in BPL to the fee structure of many of today’s hedge funds.  These days, many hedge funds charge “2 and 20,” or a 2% flat fee for assets under management and 20% of all profits.  There are, of course, some hedge funds that have outstanding track records.  Yet there are quite a few hedge funds where the performance, net of all fees, is not very different (and frequently worse) than the S&P 500 Index.  Whereas Buffett’s entire fee was based upon performance above a 6% compounded annual return, there are many hedge funds bringing in huge fees even though their net results are not much different from 6% per year.

In pursuing his investment goals, Buffett used three categories of investments:

  • The Generals
  • Workouts
  • Controls

Miller discusses each category in turn.

 

THE GENERALS

Miller begins by highlighting that there are many different approaches to value investing.  You can focus on very cheap stocks, regardless of business quality or fundamentals.  You can instead look for great, well-protected franchise businesses that can compound value over time.  You can focus on tiny, obscure microcap companies that are much too small for most professional investors even to consider.  Or you could find value in mid- or large-cap companies.  And within these categories, you could take a passive approach—like an index fund or a quantitative fund—or you could adopt an active approach of carefully picking each individual stock.

Miller says Buffett essentially used all of these different approaches at one time or another.  Miller:

For Buffett, the Generals were a highly secretive, highly concentrated portfolio of undervalued common stocks that produced the majority of the Partnership’s overall gains.

With one exception, Buffett never revealed the names of the companies in which he was investing.  These were trade secrets.

Using the Moody’s Manuals and other primary sources of statistical data, Buffett scoured the field to find stocks trading at rock-bottom valuations.  Often these were tiny, obscure, and off-the-radar companies trading below their liquidation value.  In the early years especially, the Partnership was small enough to be largely unconstrained, allowing for a go-anywhere, do-anything approach, similar to that of most individual investors today.

Even today, it’s remarkable how many tiny microcap companies are virtually unknown.  They’re simply too small for most professional investors even to consider.  Quite a few have no analyst coverage.

(Photo by Sean824)

Buffett was never concerned about when specific cheap stocks would finally rise toward their intrinsic values.  Buffett:

Sometimes these work out very fast; many times they take years.  It is difficult at the time of purchase to know any specific reason why they should appreciate in price.  However, because of this lack of glamour or anything pending which might create immediate favorable market action, they are available at very cheap prices.  A lot of value can be obtained for the price paid.

Among the Generals, Buffett had two subdivisions, as Miller explains.

“Generals – Private Owner” were undervalued based on what a private owner would pay—which itself is still based on discounted future cash flows or liquidation value.  But in some cases, these Generals became controlled investments in BPL, meaning Buffett bought enough stock to be able to influence management.

“Generals – Relatively Undervalued” were undervalued stocks that lacked any prospect for BPL or any other private owner to acquire control.  Without the possibility of an activist, these cheap stocks were riskier than “Generals – Private Owner.”

Earlier I mentioned discounted cash flows and liquidation value as two primary ways to value companies.  These two valuation methods can also be referred to as earnings power value and net asset value.  They are linked in that net asset value for a going concern is based on the earnings power of the assets.

Often, however, net asset value is better approximated by liquidation value rather than earnings power.  Buffett referred to these deep value opportunities as cigar butts.  Like a soggy cigar butt found on a street corner, a deep value investment would often give “one free puff.”  Such a cigar butt is disgusting, but that one puff is “all profit.”

One potential problem with Graham’s cigar-butt approach—buying well below liquidation value—is that if a company continues to lose money, then the liquidation value gradually gets eroded.

(Illustration by Preecha Israphiwat)

In these cases, if possible, Buffett would try to buy enough stock in order to influence management.  Thus, a General would become a Control.  Buffett also looked for situations where another investor would take control.  Buffett called this “coattail riding.”

Buffett wrote that deep value cigar butts were central to the great performance of the Buffett Partnership:

… over the years this has been our best category, measured by average return, and has also maintained by far the best percentage of profitable transactions.  This approach was the way I was taught the business, and it formerly accounted for a large proportion of all our investment ideas.  Our total individual profits in this category during the twelve-year BPL history are probably fifty times or more our total losses.

Yet over time, Buffett evolved from primarily a deep value, cigar-butt strategy to an approach focused on higher quality businesses.  Buffett explained the difference in his 1967 letter to partners:

The evaluation of securities and businesses for investment purposes has always involved a mixture of qualitative and quantitative factors.  At the one extreme, the analyst exclusively oriented to qualitative factors would say, ‘Buy the right company (with the right prospects, inherent industry conditions, management, etc.) and the price will take care of itself.’  On the other hand, the quantitative spokesman would say, ‘Buy at the right price and the company (and stock) will take care of itself.’  As is so often the pleasant result in the securities world, money can be made with either approach.  And, of course, any analyst combines the two to some extent—his classification in either school would depend on the relative weight he assigns to the various factors and not to his consideration of one group of factors to the exclusion of the other group.

Interestingly enough, although I consider myself to be primarily in the quantitative school… the really sensational ideas I have had over the years have been heavily weighted toward the qualitative side where I have had a ‘high-probability insight.’  This is what causes the cash register to really sing.  However, it is an infrequent occurrence, as insights usually are, and, of course, no insight is required on the quantitative side—the figures should hit you over the head with a baseball bat.  So the really big money tends to be made by investors who are right on the qualitative decisions, but, at least in my opinion, the more sure money tends to be made on the obvious quantitative decisions.

Much later, in his 2014 Berkshire Hathaway Letter to Shareholders, Buffett would explain his evolution from deep value investing to investing in higher quality companies that could be held for a long time.  See page 25: http://berkshirehathaway.com/letters/2014ltr.pdf

My cigar-butt strategy worked very well while I was managing small sums.  Indeed, the many dozens of free puffs I obtained in the 1950’s made the decade by far the best of my life for both relative and absolute performance…

But a major weakness in this approach gradually became apparent:  Cigar-butt investing was scalable only to a point.  With large sums, it would never work well.

In addition, though marginal businesses purchased at cheap prices may be attractive as short-term investments, they are the wrong foundation on which to build a large and enduring enterprise.

Miller quotes Charlie Munger:

… having started out as Grahamites—which, by the way, worked fine—we gradually got what I would call better insights.  And we realized that some company that was selling at two or three times book value could still be a hell of a bargain because of the momentum implicit in its position, sometimes combined with an unusual managerial skill plainly present in some individual or other, or some system or other.

And once we’d gotten over the hurdle of recognizing that a thing could be based on quantitative measures that would have horrified Graham, we started thinking about better businesses… Buffett Partnership, for example, owned American Express and Disney when they got pounded down.

(Illustration by Patrick Marcel Pelz)

Buffett actually amended the Ground Rules so that he could put 40% of BPL into American Express, which had gotten cheap after a huge, but solvable problem—exposure to the Salad Oil Scandal.  This was the largest position the partnership ever held, both on a percentage and absolute dollar basis.  BPL’s $13 million investment into American Express produced $20 million in profits over the course of a few years, thus creating a large portion of the partnership’s performance during this time.  (In today’s dollars, BPL’s Amex investment was about $90 million, while the profit was about $140 million.)

A high quality company has a high and sustainable return on invested capital (ROIC).  That’s only possible if the business has a sustainable competitive advantage.  Buffett:

The key to investing is not assessing how much an industry is going to affect society, or how much it will grow, but rather determining the competitive advantage of any given company and, above all, the durability of that advantage.  The products or services that have wide, sustainable moats around them are the ones that deliver rewards to investors.

Any investor who could find a company like See’s Candies—the quintessential high quality business—and buy it at a reasonable price, would do extremely well over time.  But it is exceedingly difficult, even for the smartest investors, to find companies like See’s Candies.

(Photo by Cihcvlss, via Wikimedia Commons)

Buffett and his business partner, Charlie Munger, acquired See’s Candies in 1972.  The company has typically experienced a return on invested capital (ROIC) of over 100 percent, which is extraordinary.  Buffett and Munger purchased See’s Candies for $25 million.  Since then, the business has generated over $2 billion in pre-tax earnings.

Tom Gayner of the Markel Corporation is another investor who has done quite well by buying high quality businesses.  Miller notes:

Tom emphasizes that you have to get only a very small number of these right for this type of strategy to really pay off.  The companies you get right will harness the power of compounding and grow to dwarf the mistakes.  He argues that investors who make twenty or so sound purchases over a lifetime will come to see one or two grow to become a significant percentage of their net worth.

Tom has a great example of this phenomenon that also reminds us not to pigeonhole Ben Graham as purely a deep value investor.  Graham paid up for quality when he bought the insurance company GEICO—he ended up making more profits from that single investment than he did from all his other activities combined.

What Should You Do?

Assume that you are an investor operating with modest sums.  Is it best to follow the deep value, cigar butt approach, or is it best to look for high-quality companies that can compound business value over time?  Miller writes:

One can make a strong case for either method, just as many well-respected investors have done.  Both can work, but what’s right for you will depend on the size of funds you are working with, your personality, your own ability to do good valuation work, and your ability to define objectively the outer edges of your own competence.

Tobias Carlisle, with his 2014 book, Deep Value, comes out as a good example of a Graham purist.  His research shows that the worse a cheap company’s fundamentals, the better the stock is likely to do.  With his deeply quantitative orientation, Tobias has developed something he calls the ‘Acquirer’s Multiple’ to identify and systematically make good investment decisions.  He seems to have found something that he understands and that works well for him.  Note that he literally shuns quality in his approach to finding value.

… While he’s smart to have found something that works for him, he’s even smarter to avoid what doesn’t.  Of course he’d prefer to buy a great business over a poor business if he could be sure that it could maintain its high returns well into the future.  However, he hasn’t yet found a way to identify the companies with the factors needed to protect those high returns from competition, at least systematically, so he avoids them.

As Buffett himself has often written, a quantitative, deep value approach is a much surer source of investment profits than an approach based on finding high quality companies.  Many investors are better off following a cigar-butt approach.  (This is what the Boole Microcap Fund does.)

(Photo by Sensay)

Buffett himself got the highest returns of his career from microcap cigar butts.  See: http://boolefund.com/buffetts-best-microcap-cigar-butts/

Concentration

Buffett has often observed that only a small handful of investments have been responsible for the vast majority of wealth he’s created over time.  Buffett:

I will only swing at pitches that I really like.  If you do it 10 times in your life, you’ll be rich.  You should approach investing like you have a punch card with 20 punch-outs, one for each trade in your life.

I think people would be better off if they only had 10 opportunities to buy stocks throughout their lifetime.  You know what would happen?  They would make sure that each buy was a good one.  They would do lots and lots of research before they made the buy.  You don’t have to have many 4X growth opportunities to get rich.  You don’t need to do too much, but the environment makes you feel like you need to do something all the time.

Whether you use a deep value approach or a strategy based on higher quality, it is possible to concentrate.

That said, if you use a quantitative approach—which works well for deep value—then having at least 15-20 positions generally works better over time.  Part of the reason is that, when buying a basket of deep value stocks—stocks which are typically very ugly—it is rarely possible to say which ones will be the best performers.  The legendary value investor Joel Greenblatt, who has excelled at both deep value and high-quality value, has readily admitted that the deep value stocks he picks as best often are not the best.  Greenblatt also has said:

In our experience, eliminating the stocks you would obviously not want to own eliminates many big winners.

As Tobias Carlisle so clearly illustrates in Deep Value, the ugliest of the ugly often end up being among the best performers.  Without a fully quantitative strategy—which forces you to buy the cheapest, ugliest stocks—it is easy to miss many big winners.

Tom Gayner’s strategy is almost the opposite of Tobias Carlisle’s but he understands it and it works for him.  Neither one is ‘right’ or ‘wrong’; each has developed a value system that works for him.  What’s right in investing is what works for the individual.

 

WORKOUTS

What Buffett called Workouts is now known as merger arbitrage (or risk arbitrage).  When one company announces that it will buy another, the acquisition target stock will move up towards the announced price, but not all the way.

With a sufficient spread and with a high probability of the deal closing, Buffett would take a position in the target company’s stock.  Buffett learned the technique from Graham.  If one were to combine the record of Graham-Newman, BPL, and Berkshire Hathaway through 1988—a total period of 65 years—Buffett calculated that merger arbitrage produced unlevered returns of about 20% per year.  So this was a very profitable category for the Buffett Partnership.

Because Buffett would often use up to 10% margin—and never more than 25%—the actual net returns for BPL were likely higher than 20% per year.  Thus, not only could Workouts do just as well as the Generals—because of the modest leverage used in merger arbitrage—but even more importantly, Workouts were largely uncorrelated (and often negatively correlated) with the overall stock market.  So even when the overall market was flat or down—which often meant that the Generals were flat or down—Workouts could and sometimes did produce a positive return.  As Buffett wrote:

Obviously the workouts (along with controls) saved the day in 1962, and if we had been light in this category that year, our final result would have been much poorer, although still quite respectable considering market conditions during the year.  We could just as well have had a much smaller percentage of our portfolio in workouts that year; availability decided it, not any notion on my part as to what the market was going to do.  Therefore, it is important to realize that in 1962 we were just plain lucky regarding mix of categories.

In 1963 we had one sensational workout which greatly influenced results, and generals gave a good account of themselves, resulting in a banner year.  If workouts had been normal, (say, more like 1962) we would have looked much poorer compared to the Dow….

Buffett goes on to note that in 1964, Workouts were a big drag on performance.  So Workouts didn’t work in every year, but they did tend to produce excellent returns over time.  And these returns were uncorrelated or negatively correlated with the returns of the Generals.  Buffett wrote: “In years of market decline, it piles up a big edge for us;  during bull markets, it is a drag on performance.”

Note:  Merger arbitrage has gotten much more difficult and competitive these days based on a much larger number of investors and based on huge computing power.  Thus, merger arbitrage is best not to do for most investors today.  Yet there are other types of investments with low correlation with the overall market that nonetheless can provide good long-term returns.  For instance, privately owned businesses might serve in this role.  Energy-related stocks—if held for at least 5 years—have low correlation with the overall market and also tend to outperform it.  Similarly, many microcap stocks have relatively low correlation with the broad market and outperform it over time.

 

CONTROLS

Controls are situations when Buffett bought enough stock so as to influence management to unlock value.  Miller gives the example of the Sanborn Map Company.  Buffett had more than one-third of the Partnership invested in this stock.  The company published and constantly revised highly detailed maps of all cities in the United States.  Fire insurance companies were the primary users of these maps.  Buffett wrote:

In the early 1950’s a competitive method of underwriting known as ‘carding’ made inroads on Sanborn’s business and after-tax profits of the map business fell from an average level of over $500,000 in the late 1930’s to under $100,000 in 1958 and 1959.  Considering the upward bias in the economy during this period, this amounted to an almost complete elimination of what had been sizable, stable earning power.

However, during the early 1930’s Sanborn had begun to accumulate an investment portfolio.  There were no capital requirements to the business so that any retained earnings could be devoted to this project.  Over a period of time, about $2.5 million was invested, roughly half in bonds and half in stocks.  Thus, in the last decade particularly, the investment portfolio blossomed while the operating map business wilted.

Let me give you some idea of the extreme divergence of these two factors.  In 1938 when the Dow-Jones Industrial Average was in the 100-120 range, Sanborn sold at $110 per share.  In 1958 with the Average in the 550 area, Sanborn sold at $45 per share.  Yet during that same period the value of the Sanborn investment portfolio increased from about $20 per share to $65 per share.  This means, in effect, that the buyer of Sanborn stock in 1938 was placing a positive valuation of $90 per share on the map business ($110 less the $20 value of the investments unrelated to the map business) in a year of depressed business and stock market conditions.  In the tremendously more vigorous climate of 1958 the same map business was evaluated at a minus $20 with the buyer of the stock unwilling to pay more than 70 cents on the dollar for the investment portfolio with the map business thrown in for nothing.

Buffett:

… The very fact that the investment portfolio had done so well served to minimize in the eyes of most directors the need for rejuvenation of the map business.  Sanborn had a sales volume of about $2 million per year and owned about $7 million worth of marketable securities.  The income from the investment portfolio was substantial, the business had no possible financial worries, the insurance companies were satisfied with the price paid for maps, and the stockholders still received dividends.  However, these dividends were cut five times in eight years although I could never find any record of suggestions pertaining to cutting salaries or director’s and committee fees.

[Most board members owned virtually no stock…]  The officers were capable, aware of the problems of the business, but kept in a subservient role by the Board of Directors.  The final member of our cast was a son of a deceased president of Sanborn.  The widow owned about 15,000 shares of stock.

In late 1958, the son, unhappy with the trend of the business, demanded the top position in the company, was turned down, and submitted his resignation, which was accepted.  Shortly thereafter we made a bid to his mother for her block of stock, which was accepted.  At the time there were two other large holdings, one of about 10,000 shares (dispersed among customers of a brokerage firm) and one of about 8,000.  These people were quite unhappy with the situation and desired a separation of the investment portfolio from the map business as did we.

Buffett continues:

There was considerable opposition on the Board to change of any type, particularly when initiated by an outsider, although management was in complete accord with our plan… To avoid a proxy fight… and to avoid time delay with a large portion of Sanborn’s money tied up in blue-chip stocks which I didn’t care for at current prices, a plan was evolved taking out all stockholders at fair value who wanted out.  The SEC ruled favorably on the fairness of the plan.  About 72% of the Sanborn stock, involving 50% of the 1,600 stockholders, was exchanged for portfolio securities at fair value.  The map business was left with over $1.25 million in government and municipal bonds as a reserve fund, and a potential corporate capital gains tax of over $1 million was eliminated.  The remaining stockholders were left with a slightly improved asset value, substantially higher earnings per share, and an increased dividend rate.

Lessons from Controls

Miller reminds us that investing in a stock is becoming a part owner of the business:

In 1960, one-third of the Partnership was in Sanborn’s stock, meaning one-third of the Partnership was in the business of selling insurance maps and managing a securities portfolio.  In his discussion of Controls, Buffett is teaching us to not think about ‘investing in a stock’ but instead to think about ‘being in a business.’

Miller again:

Whether you are running a business or evaluating one, a singular question remains paramount: what is its value, both in terms of the assets involved and the earnings produced, then, how can it be maximized?  The skill in answering these questions determines the success of investors and business managers like.

Buffett often quotes Ben Graham on this point:

Investment is most intelligent when it is most businesslike and business is most intelligent when it’s most investment-like.

In some cases, a General would languish in price for years, allowing BPL to continue acquiring the stock at cheap prices.  In this way, a General would sometimes become a Control.  A General is attractive as a cheap stock.  When a General becomes a Control, it becomes more attractive to the extent that BPL can actively work to unlock value.

In the case of Controls, Buffett was willing to work actively to unlock value, but it did often require taking actions that would be criticized, as Miller writes:

… he had to threaten Sanborn Map’s board with a proxy fight (legal battle) to get them to act… At Dempster Mill, we’ll see that he had to fire the CEO and bring in his own man, Harry Bottle.  Together they liquidated large parts of the business to restore the economics of the company.  Buffett was vilified in the local newspaper for doing so.  While he saw himself as saving the business by excising the rotten parts, critics only saw the lost jobs.  Early at Berkshire, he had to fire the CEO and hit the brakes on capital expenditures in textiles before redirecting the company’s focus to insurance and banking.  It was never easy and often stressful, but when action was needed, action was taken.  As he said, ‘Everything else being equal, I would much rather let others do the work.  However, when an active role is necessary to optimize the employment of capital, you can be sure we will not be standing in the wings.’

The ability to actively unlock value led Buffett naturally to concentrate heavily.  A situation like Sanborn had high upside and a tiny risk of loss, so it made sense to bet big.

With Dempster Mill, Berkshire, and Diversified Retailing Company (DRC), the values had to be estimated by Buffett and confirmed by auditors.  In the case of Dempster and Berkshire, BPL owned so much stock that trying to trade it could dramatically impact the market price.  That is why the year-end values had to be estimated, which Buffett did conservatively based on current value rather than future value.  DRC also had to be valued this way because it was a privately owned business that never had a publicly traded stock.

Correctly valuing the Controls was important.  Not only would it impact the year-end overall performance of BPL—too high of an estimate would inflate the performance, while too low of an estimate would depress the performance.  But also, correctly valuing Controls would impact limited partners who were entering or leaving the Partnership.  Exiting limited partners would benefit at the expense of remaining limited partners if the estimated value of the Controls was too high.  Conversely, new limited partners would benefit at the expense of existing limited partners if the estimated value of the Controls was too low.  Buffett was very careful, and his estimates were audited by the firm that would later become KPMG.

Buffett’s November 1966 letter to partners gives some detail on the appraisal process:

The dominant factors affecting control valuations are earnings power (past and prospective) and asset values.  The nature of our controlled businesses, the quality of the assets involved, and the fact that the Federal Income Tax basis applicable to the net assets substantially exceeds our valuations, cause us to place considerably more weight on the asset factor than is typical in most business valuations…. The Partnership Agreement charges me with the responsibility for establishing fair value for controlling interests, and this means fair to both adding and withdrawing partners at a specific point in time.  Wide changes in the market valuations accorded stocks at some point obviously find reflection in the valuation of businesses, although this factor is of much less importance when asset factors (particularly when current assets are significant) overshadow earnings power considerations in the valuation process…

It’s worth noting that Sanborn, Dempster, and Berkshire were all cigar butts where net asset value was much higher than the current market price.  They were very cheap businesses, but they were not good businesses, which is part of why valuing them was mostly based on asset value rather than earnings power.

Because Ben Graham relied mostly on the cigar-butt approach, basing his investments on discounts to liquidation value, Buffett had already learned how to value companies based on their assets.  Miller quotes Chapter 43 of Graham and Dodd’s Security Analysis:

The rule in calculating liquidating value is that the liabilities are real but the value of the assets must be questioned. This means that all true liabilities shown on the books must be deducted at their face amount.  The value to be ascribed to the assets, however, will vary according to their character.

Graham advised the following rule of thumb for liquidation analysis: 100 cents on the dollar for cash, 80 cents on the dollar for receivables, 67 cents on the dollar for inventory (with a wide range depending on the business), and 15 cents on the dollar for fixed assets.

In the case of Sanborn, the company had a hidden asset in the form of a large investment portfolio that was not reflected on its balance sheet.  Dempster Mill’s net assets were much higher on the balance sheet than was indicated by the market price.  Buffett had to determine what the assets were really worth.  With Berkshire, part of the value would be determined by redeploying capital into higher return opportunities.  (Buffett’s successful redeployment of Berkshire’s cash formed the foundation for Berkshire Hathaway, now one of the largest and most successful U.S. companies.)

Circle of Competence

A central concept for Buffett and Munger is circle of competence.  For any given company, are you capable of reasonably estimating what the assets are worth?  If not, you can either spend the time required to understand the company and the industry, or you can put it into the TOO HARD pile.

Buffett and Munger have three piles:  IN, OUT, and TOO HARD.  A great many public companies simply go into the TOO HARD pile.  This limitation—sticking with companies you can understand well—has been a key to the excellent long-term performance of Buffett and Munger.

For a value investor managing a smaller sum, who can focus on tiny, obscure microcap companies, there are thousands and thousands of businesses.  When there are so many that you probably can understand well, it makes no sense to spend long periods of time on businesses that are decidedly difficult to understand.

For example, you could spend months gaining an understanding of General Electric, or you could spend that same amount of time gaining a complete understanding of at least a dozen tiny microcap companies.  Many microcap businesses are quite simple.

Here’s the thing:  As Buffett has pointed out, frequently you don’t get paid for degree of difficulty in investing.  If you’re willing to turn over enough rocks, eventually you can find a microcap business that you can easily understand and that is extraordinarily cheap.  You’ll almost certainly do far better with that type of investment than with a mid-cap or large-cap company that’s much harder to understand and probably not nearly as cheap.

 

DEMPSTER DIVING:  THE ASSET CONVERSION PLAY

Dempster was a tiny micro cap, a family-owned company in Beatrice, Nebraska, that manufactured windmills and farm equipment.

(Photo by Digikhmer)

Miller:

Much of the fun in investing comes from the hunting process itself… Picture the pulse-quickening moment in 1956 when Buffett, thumbing through the Moody’s Manual, came across a tiny, obscure manufacturing company whose stock had fallen 75% in the previous year.  Realizing that it was now available for a fraction of its net working capital and an even smaller fraction of its book value, he started buying the stock as low as $17 a share.  He got out at $80.

Miller writes that Dempster can serve as a template for valuing businesses using the net asset value approach.  Dempster’s profits were very low, but the stock traded far below its asset value.

Buffett joined the board of directors soon after his first purchase.  He kept buying the stock for the next five years.  A large block of stock from the Dempster family became available for sale in 1961.  By August of that year, BPL owned 70% of Dempster and a few “associates” owned another 10%.  BPL’s average price was $1.2 million ($28/share), roughly a 50% discount to working capital and 66% discount to book value.  Dempster accounted for roughly 20% of BPL’s total assets by year-end.

The situation was challenging at first because the inventories were high and rising.  Buffett tried to work with existing management, but had to throw them out because inventories kept rising.  The company’s bank was threatening to seize the collateral backing the loan.  With 20% of BPL in Dempster, if the company went under it would have a large negative impact on the Partnership.  At Munger’s recommendation, Buffett met and hired an “operating man” name Harry Bottle.

Bottle was a turnaround specialist.  Buffett was so happy with Bottle’s work that in the next year’s letter, Buffett named him “man of the year.”  He cut inventories from $4 million to $1 million, quickly repaid the bank loan, cut administrative and selling expenses in half, and closed five unprofitable branches.  With help from Buffett and Munger, Bottle also raised prices up to 500% on their used equipment.  There was little impact on sales volume.  All of these steps worked together to put Dempster on a healthy economic footing.

Buffett then took an unusual step.  Whereas most managers feel automatically that they must reinvest profits into the business, even if the business is creating low returns, Buffett was more rational.  Miller explains:

With Dempster he wasn’t at all bogged down with all the emotional baggage of being a veteran of the windmill business.  He was in it to produce the highest rate of return on the capital he had tied up in the assets of the business.  This absolute scale allowed him to see that the fix for Dempster would come by not reinvesting back in windmills.  He immediately stopped the company from putting more capital in and started taking the capital out.

Instead, Buffett invested the capital into the cheapest stocks he could find, those offering the highest potential returns.  In effect, he was converting capital from a low-return business to a high-return business—buying cheap stocks until they rose towards intrinsic value.  Over time, Dempster looked less like a manufacturing company and more like the investment partnership.  Miller observes:

The willingness and ability to see investment capital as completely fungible, whether it is capital tied up in the assets of a business or capital that’s invested in securities, is an exceedingly rare trait.

Dempster initially was worth $35/share in 1961.  By year-end 1962, Dempster was worth $51/share, with market securities worth $35/share and the manufacturing operations worth $16/share.

Buffett also learned from this experience the importance of a high-quality and trustworthy CEO.  Buffett heaped praise on Harry Bottle.  Miller points out that Buffett developed a style like that of Dale Carnegie: Praise by name, criticize by category.

It should also be noted that Dempster’s market value in 1961 was $1.6 million, a tiny microcap company.  This kind of opportunity—including being able to buy control—is open to those investing relatively small sums.  Very often the cheapest stocks can be found among microcap companies.  This high degree of inefficiency results from the fact that most professionals investors never look at micro caps.

Miller sums it up:

Buffett teaches investors to think of stocks as a conduit through which they can own their share of the assets that make up a business.  The value of that business will be determined by one of two methods: (1) what the assets are worth if sold, or (2) the level of profits in relation to the value of assets required in producing them.  This is true for each and every business and they are interrelated.  Buffett commented, ‘Harry has continued this year to turn under-utilized assets into cash, but in addition, he has made the remaining needed assets productive.’

Operationally, a business can be improved in only three ways: (1) increase the level of sales; (2) reduce costs as a percent of sales; (3) reduce assets as a percentage of sales.  The other factors, (4) increase leverage or (5) lower the tax rate, are the financial drivers of business value.  These are the only ways a business can make itself more valuable.

Buffett ‘pulled all the levers’ at Dempster.  Raising prices on replacement parts and reducing operating costs pulled levers #1 and #2.  Lever #3 was pulled as inventories (assets) were reduced.  Lever #4 was pulled when Buffett borrowed money to buy more stocks.  Lever #5 was pulled when he avoided a big tax bill by selling all the operating assets of the company.

When profitability goes up and the capital required to produce it goes down, the returns and the value of the business go straight up.  Buffett understood this intrinsically and Dempster is now a powerful example for today’s investors who obsess over (1) and (2) at the expense of (3).  Pulling underutilized assets out of a company not only produces cash to be used elsewhere, it makes the business better and more valuable.  It is a wonderful reminder to individual and professional investors alike to focus their attention first on the balance sheet (there is a reason it comes first in the set of financial statements).  Never lose sight of the fact that without tangible assets, there would be no earnings in the first place.

 

CONSERVATIVE VERSUS CONVENTIONAL

Although following the crowd made sense in our evolutionary history, and still makes sense in many circumstances, following the crowd kills your ability to outperform the stock market.  Miller explains:

Successful investing requires you to do your own thinking and train yourself to be comfortable going against the crowd.  You could say that good results come primarily from a properly calibrated balance of hubris and humility—hubris enough to think you can have insights that are superior to the collective wisdom of the market, humility enough to know the limits of your abilities and to be willing to change course when errors are recognized.

You’ll have to evaluate facts and circumstances, apply logic and reason to form a hypothesis, and then act when the facts line up, irrespective of whether the crowd agrees or disagrees with your conclusions.  Investing well goes against the grain of social proof; it goes against the instincts that have been genetically programmed into our human nature.  That’s part of what makes it so hard.

Howard Marks, a Buffett contemporary who also has a literary bent, challenges his readers to “dare to be great” in order to dare to be better investors.  As he tells his readers, “the real question is whether you dare to do the things that are necessary in order to be great.  Are you willing to be different, and are you willing to be wrong?  In order to have a chance at great results, you have to be open to being both.”

There are two key ideas in Buffett’s highly independent approach:

  • The best purchases are made when your thinking puts you in opposition to conventional wisdom or popular trends.
  • A concentrated portfolio can actually be more conservative than a diversified one when the right conditions are met.

Conventional, academic thinking equates the riskiness of a stock with its beta, which is a measure of its volatility.  Buffett, later in his career, gave the following example to illustrate the silliness of beta:

The Washington Post Company in 1973 was selling for $80 million in the market.  At the time, that day, you could have sold the assets to any one of ten buyers for not less than $400 million, probably appreciably more…

Now, if the stock had declined even further to a price that made the valuation $40 million instead of $80 million, it’s beta would have been greater.  And to people who think beta [or, more importantly, downside volatility] measures risk, the cheaper price would have made it look riskier.  This is truly Alice in Wonderland.  I have never been able to figure out why it’s riskier to buy $400 million worth of properties for $40 million than $80 million….

In the 1970’s, the Washington Post Company was an outstanding, high-return business and remained so for decades.  Of course, like most businesses, its high profitability did not last, in this case because of the internet.

But the point is that if you, as a value investor, buy something at 20% of probable intrinsic value, and the stock then drops 50% and you buy a bunch more, your investment now has 10x upside instead of 5x, and simultaneously, your investment is now probably safer.

Having the expected return from your investment double, while at the same time having the downside risk get cut in half, is completely contrary to what is taught in modern finance theory.  Finance theory says that a higher potential return always requires higher risk.  Yet the experience of many value investors is that quite often an increase in potential return also means a decrease in risk.  Thus, a value investor cheers (and backs up the truck) when his or her best idea keeps going down in price, and this happens routinely.

Thinking for Yourself

The best time to buy is when the crowd is most fearful.  But this requires thinking for yourself.  A good example is when Buffett put 40% of BPL into American Express after the Salad Oil Scandal.  Miller:

The Partnership lessons teach investors that there is only one set of circumstances where you or anyone else should make an investment—when the important facts in a situation are fully understood and when the course of action is as plain as day.  Otherwise, pass.  For instance, in Sanborn, when Buffett realized he was virtually assured to make money in the stock given he was buying the securities portfolio at 70 cents on the dollar with the map company coming for free, he invested heavily.  When he saw Dempster was selling below the value of its excess inventory alone, he loaded up.

Miller quotes Buffett:

When we really sit back with a smile on our face is when we run into a situation we can understand, where the facts are ascertainable and clear, and the course of action is obvious.  In that case—whether conventional or unconventional—whether others agree or disagree—we feel—we are progressing in a conservative manner.

Ben Graham:

You’re neither right nor wrong because the crowd disagrees with you.  You’re right because your data and reasoning are right.

Buffett again:

You will not be right simply because a large number of people momentarily agree with you.  You will not be right simply because important people agree with you… You will be right, over the course of many transactions, if your hypotheses are correct, your facts are correct, and your reasoning is correct.

Buffett, once more:

A public opinion poll is no substitute for thought.

Loading Up

Buffett thought it was conservative and rational to put 40% of the Partnership assets into American Express.  Buffett had amended the Ground Rules of the Partnership to include a provision that allowed up to 40% of BPL’s assets to be in a single security under conditions “coupling an extremely high probability that our facts and reasoning are correct with a very low probability that anything could drastically change the underlying value of the investment.”

Miller notes that Buffett gave the following advice to a group of students in the late 1990s:

If you can identify six wonderful businesses, that is all the diversification you need.  And you will make a lot of money.  And I can guarantee that going into a seventh one instead of putting more money into your first one is going to be a terrible mistake.  Very few people have gotten rich on their seventh best idea.  But a lot of people have gotten rich with their best idea.  So I would say for anyone working with normal capital who really knows the businesses they have gone into, six is plenty, and I [would] probably have half of [it in] what I like best.

Your Best Ideas Define Your Next Choice

If you’re using concentrated value investing, then the simple test for whether to add a new idea to your portfolio is to compare any new idea to your best current ideas.

Successful concentrated value investing requires a great deal of passion, curiosity, patience, and prior experience (i.e., lots of mistakes).  It also often requires a focus on tiny, obscure micro caps, since this is the most inefficient part of the market and it contains many simple businesses.

Buffett explains:

Simply stated, this means I am willing to concentrate quite heavily in what I believe to be the best investment opportunities recognizing very well that this may cause an occasional very sour year—one somewhat more sour, probably, than if I had diversified more.  While this means our results will bounce around more, I think it also means that our long-term margin of superiority should be greater.

Buffett in the January 25, 1967, BPL Letter:

Our relative performance in this category [Generals–Relatively Undervalued] was the best we have ever had—due to one holding which was our largest investment at yearend 1965 and also yearend 1966.  This investment has substantially outperformed the general market for us during each year (1964, 1965, 1966) that we have held it.  While any single year’s performance can be quite erratic, we think the probabilities are highly favorable for superior future performance over a three or four year period.  The attractiveness and relative certainty of this particular security are what caused me to introduce Ground Rule 7 in November, 1965 to allow individual holdings of up to 40% of our net assets.  We spend considerable effort continuously evaluating every facet of the company and constantly testing our hypothesis that this security is superior to alternative investment choices.  Such constant evaluation and comparison at shifting prices is absolutely essential to our investment operation.

It would be much more pleasant (and indicate a more favorable future) to report that our results in the Generals—Relatively Undervalued category represented fifteen securities in ten industries, practically all of which outperformed the market.  We simply don’t have that many good ideas…

 

SIZE VERSUS PERFORMANCE

Miller comments that Buffett, if he were managing a relatively small amount of money, probably would have stayed fully invested even during the speculative peak of the late 1990’s.  This is largely because there are almost always cheap microcap companies that are too small and obscure to be noticed by most investors.  As Buffett said during the late 1990’s:

If I was running $1 million, or $10 million for that matter, I’d be fully invested.

There were times when he was managing BPL when Buffett recognized that more assets under management would increase the Partnership’s ability to do Control investments.  But according to Buffett, it was also sometimes true that less assets under management made it easier to invest in tiny, cheap microcap companies.  So Buffett wrote:

What is more important—the decreasing prospects of profitability in passive investments or the increasing prospects in control investments?  I can’t give a definite answer to this since to a great extent it depends on the type of market in which we are operating.  My present opinion is that there is no reason to think these should not be offsetting factors;  if my opinion should change, you will be told.  I can say, most assuredly, that our results in 1960 and 1961 would not have been better if we had been operating with the much smaller sums of 1956 and 1957.

By 1966, however, when assets under management reached $43 million, Buffett changed his mind.  He wrote his partners:

As circumstances presently appear, I feel substantially greater size is more likely to harm future results than to help them.  This might not be true for my own personal results, but it is likely to be true for your results.

Buffett saw a drag on performance that would probably develop as a result of two factors:  larger assets under management, and a stock market that was high overall, with far fewer opportunities.  It’s important to note again that Buffett did not think a high market would be a factor if he were managing smaller sums.  As Buffett said in 2005, when asked if he could still make 50% per year with smaller sums:

Yes, I would still say the same thing today.  In fact, we are still earning those types of returns on some of our smaller investments.  The best decade was the 1950s;  I was earning 50% plus returns with small amounts of capital.  I could do the same thing today with smaller amounts.  It would perhaps even be easier to make that much money in today’s environment because information is easier to access.  You have to turn over a lot of rocks to find those little anomalies.  You have to find the companies that are off the map—way off the map.  You may find local companies that have nothing wrong with them at all.  A company that I found, Western Insurance Securities, was trading for $3/share when it was earning $20/share!!  I tried to buy up as much of it as possible.  No one will tell you about these businesses.  You have to find them.

Ideas versus Capital

The bottom line is simple:  If you have more capital than ideas, then assets are too large and will be a drag on performance.  If you have more ideas than capital, then assets are not a drag and may even be too small.

 

GO-GO OR NO-GO

In 1956, Buffett had told his partners that he thought the stock market was high relative to intrinsic value.  Since he never tried to predict the market, he remained focused on finding tiny microcap companies that were cheap.  Staying focused on finding what was cheapest was central to the 29.8% per year the BPL achieved over the ensuing decade.  Had Buffett ever invested less because he was worried about a stock market decline, his record would have been nowhere near as good.

An expensive stock market says nothing about when a correction will happen.  And an expensive stock market rarely means that there are no obscure, cheap microcap companies.

By 1966, however, because BPL had more assets under management and because Buffett thought the stock market was even more overvalued, Buffett finally decided not to accept any new capital.

Somewhat ironically, BPL had its best year ever in 1968, with a return of 58.8%.  But this also led Buffett to consider closing the Partnership altogether.  Buffett had simply run out of ideas, due to the combination of his assets under management and a stock market that was quite overvalued in his view.

In May 1969, Buffett announced his decision to liquidate the Partnership.  Performance in 1969 was mediocre, and Buffett wrote:

… I would continue to operate the Partnership in 1970, or even 1971, if I had some really first class ideas.  Not because I want to, but simply because I would so much rather end with a good year than a poor one.  However, I just don’t see anything available that gives any reasonable hope of delivering such a good year and I have no desire to grope around, hoping to ‘get lucky’ with other people’s money.  I am not attuned to this market environment and I don’t want to spoil a decent result by trying to play a game I don’t understand just so I can go out a hero.

Go-Go Years – Jerry Tsai

The big bull market run of the 1960s became known as the Go-Go years.  Jerry Tsai’s highly speculative investment style, which produced high returns for some time, was representative of the Go-Go years.  In 1968, Tsai shrewdly sold his Manhattan Fund, which had $500 million under management.  The fund went on to lose 90% of its value over the next several years.

 

TOWARD A HIGHER FORM

Buffett constantly evolved as an investor.  As Miller writes:

A good deal of this evolution occurred throughout the Partnership years, where we have seen a willingness to concentrate his investments to greater and greater degrees, a steady migration toward quality compounders from statistically cheap cigar butts, and the forging of his highly unique ability to break down the distinction between assets and capital in a way that allows for their fungibility in the pursuit of higher returns.

 

BOOLE MICROCAP FUND

An equal weighted group of micro caps generally far outperforms an equal weighted (or cap-weighted) group of larger stocks over time.  See the historical chart here:  http://boolefund.com/best-performers-microcap-stocks/

This outperformance increases significantly by focusing on cheap micro caps.  Performance can be further boosted by isolating cheap microcap companies that show improving fundamentals.  We rank microcap stocks based on these and similar criteria.

There are roughly 10-20 positions in the portfolio.  The size of each position is determined by its rank.  Typically the largest position is 15-20% (at cost), while the average position is 8-10% (at cost).  Positions are held for 3 to 5 years unless a stock approaches intrinsic value sooner or an error has been discovered.

The goal of the Boole Microcap Fund is to outperform the Russell Microcap Index over time, net of fees.  The Boole Fund has low fees. 

 

If you are interested in finding out more, please e-mail me or leave a comment.

My e-mail: jb@boolefund.com

 

 

 

Disclosures: Past performance is not a guarantee or a reliable indicator of future results. All investments contain risk and may lose value. This material is distributed for informational purposes only. Forecasts, estimates, and certain information contained herein should not be considered as investment advice or a recommendation of any particular security, strategy or investment product. Information contained herein has been obtained from sources believed to be reliable, but not guaranteed. No part of this article may be reproduced in any form, or referred to in any other publication, without express written permission of Boole Capital, LLC.

You’re deluding yourself

(Image: Zen Buddha Silence, by Marilyn Barbone)

July 15, 2018

You’re deluding yourself.  I’m deluding myself.  Our brains just do this automatically, all the time.  We invent simple stories based on cause and effect.  Often this is harmless.  But sometimes it’s important to recognize that reality is far more unpredictable than we’d like.

We’re not wired to understand probabilities.  As Daniel Kahneman and Amos Tversky have demonstrated, even many professional statisticians are not good “intuitive statisticians.”  They’re usually only good if they slow down and work through the problem at hand step-by-step.  Otherwise, they too tend to create overly simplistic, overly deterministic stories.

(Photo by Wittayayut Seethong)

To develop better mental habits, a good place to start is by recognizing delusions and biases, which are widespread in business, politics, and economics.  To that end, here are four of the best books:

  • Thinking, Fast and Slow (Farrar, Straus and Giroux, 2011), by Daniel Kahneman
  • Poor Charlie’s Almanack (Walsworth, 3rd edition, 2005), by Charles T. Munger
  • The Halo Effect…and Eight Other Business Delusions That Deceive Managers (Free Press, 2007), by Phil Rosenzweig
  • Expert Political Judgment: How Good Is It? How Can We Know? (Princeton University Press, 2006), by Philip Tetlock

Tetlock’s work is particularly important.  He tracked over 27,000 predictions made in real time by 284 experts from 1984 to 2003.  Tetlock found that the expert predictions—on the whole—were no better than chance.  Many of these experts have deep historical knowledge of politics or economics, which can give us important insights and is often a precursor to scientific knowledge.  But it’s not yet science—the ability to make predictions.

Kahneman and Munger both show how our intuition uses mental shortcuts (heuristics) to jump to conclusions.  Often these conclusions are fine.  But not if probabilistic reasoning is needed to reach a good decision.

This blog post focuses on Rosenzweig’s book, which examines delusions in business, with particular emphasis on the Halo Effect.

Outline for this blog post:

  • The Halo Effect
  • Illusions and Delusions
  • How Little We Know
  • The Story of Cisco
  • Up and Down with ABB
  • Halos All Around Us
  • Research to the Rescue?
  • Searching for Stars, Finding Halos
  • The Mother of All Business Questions, Take Two
  • Managing Without Coconut Headsets

 

THE HALO EFFECT

Rosenzweig quotes John Kay of the Financial Times:

The power of the halo effect means that when things are going well praise spills over to every aspect of performance, but also that when the wheel of fortune spins, the reappraisal is equally extensive.  Our search for excessively simple explanations, our desire to find great men and excellent companies, gets in the way of the complex truth.

(Image by Ileezhun)

Rosenzweig explains the essence of the Halo Effect:

If you select companies on the basis of outcomes—whether success or failure—and then gather data that are biased by those outcomes, you’ll never know what drives performance.  You’ll only know how high performers or low performers are described.

Rosenzweig describes his book as “a guide for the reflective manager,” a way to avoid delusions and to think critically.  It’s quite natural for us to construct simple stories about why things happen.  But many events—including business success and failure—don’t happen in a straightforward way.  There’s a large measure of uncertainty (chance) involved.

Rosenzweig adds:

Of course, for those who want a book that promises to reveal the secret of success, or the formula to dominate their market, or the six steps to greatness, there are plenty to choose from.  Every year, dozens of new books claim to reveal the secrets of leading companies… Others tell you how to become an innovation powerhouse, or craft a failsafe strategy, or devise a boundaryless organization, or make the competition irrelevant.

But if anything, the world is getting more unpredictable:

In fact, for all the secrets and formulas, for all the self-proclaimed thought leadership, success in business is as elusive as ever.  It’s probably more elusive than ever, with increasingly global competition and technological change moving at faster and faster rates—which might explain why we’re tempted by promises of breakthroughs and secrets and quick fixes in the first place.  Desperate circumstances push us to look for miracle cures.

Rosenzweig explains that business managers are under great pressure to increase profits.  So they naturally look for clear solutions that they can implement right away.  Business writers and experts are happy to supply what is demanded.  However, reality is usually far more unpredictable than is commonly assumed.

 

ILLUSIONS AND DELUSIONS

Science is the ability to predict things:  if x, then y (with probability z).  (If we’re talking about physics—other than quantum mechanics—then z = 100% in the vast majority of cases.)  But the sciences that deal with human behavior still haven’t discovered enough to make many predictions.  There are specific experiments or circumstances where good predictions can be made—such as where to place specific items in a retailer to maximize sales.  And good research has uncovered numerous statistical correlations.

But on the whole, there’s still much unpredictability in business and in human behavior generally.  There’s still not much scientific knowledge.

Rosenzweig says some of the biggest recent business blockbusters contain several delusions:

For all their claims of scientific rigor, for all their lengthy descriptions of apparently solid and careful research, they operate mainly at the level of storytelling.  They offer tales of inspiration that we find comforting and satisfying, but they’re based on shaky thinking.  They’re deluded.

Rosenzweig explains that most management books seek to understand what leads to high performance.  By contrast, Rosenzweig asks why it is so difficult to understand high performance.  We suffer from many delusions.  Our intuition leads us to construct simple stories to explain things, even when those stories are false.

(Image by Edward H. Adelson, via Wikimedia commons)

Look at squares A and B just above:  Are they the same color?  Or is one square lighter than the other?

A and B are exactly the same color.  However, our visual system automatically uses contrast.  If it didn’t, then as Steven Pinker has pointed out, we would think a lump of coal in bright sunlight was white.  We would think a lump of snow inside a dark house was black.  We don’t make these mistakes because our visual system works in part by contrast.  Kathryn Schulz mentions this in her excellent book, Being Wrong (HarperCollins, 2010).

This use of contrast is a heuristic—a shortcut—used by our visual system.  This happens automatically.  And usually this heuristic helps us, as in Pinker’s examples.

The important point is that our intuition (part of our mental system) is like our visual system Our intuition also uses heuristics.

  • If we are asked a difficult question, our intuition substitutes an easier question and then answers that question.  This happens automatically and without our conscious awareness. 
  • Similarly, our intuition constructs simple stories in terms of cause and effect, even if reality is far more complex and random.  This happens automatically and without our conscious awareness.

(Image by Edward H. Adelson, via Wikimedia Commons)

This second image is the same as the previous one—except this one has two vertical grey bars.  This helps (to some extent) our eyes to see that squares A and B are exactly the same color.

Rosenzweig mentions that some rigorous research of business has been conducted.  But this research often reaches far more modest conclusions than what we seek.  As a result, it’s not popular or well-known.  For instance, there may be a 0.2 correlation between certain approaches of a CEO and business performance.  That’s a huge finding—20% of business performance is based on specific CEO behavior.

But that means 80% of business performance is due to other factors, including chance.  That’s not the type of information people in business want to hear when they’re busy and under pressure.

 

HOW LITTLE WE KNOW

In January 2004, after a disastrous holiday season, Lego—the Danish toymaker—fired its chief operating officer, Poul Ploughman.  Rosenzweig points out that when a company does well, we tend to automatically think its leaders did the right things and should be praised or promoted.  When a company does poorly, we tend to jump to the conclusion that its leaders did the wrong things and should be replaced.

But reality is far more complex.  Good leadership may represent 20-30% of the reason a company is doing well now, but luck may be an even bigger factor.  Similarly, bad leadership may be responsible for 20-30% of a company’s poor performance, whereas bad luck—unforeseeable events—may be a bigger factor.

(Photo by Marco Clarizia)

As humans, we’re driven to construct stories in which success and failure are completely explainable—without reference to luck—based on the actions of people and systems.  This satisfies our psychological need to see the world as a predictable place.

However, reality is unpredictable to an extent.  We understand far less than we think.  Luck usually plays a large role in business success and failure.

When Lego hired Ploughman, it was seen as a coup.  Ploughman helped Lego expand into electronic toys.  When the initial results of this expansion were not positive, Lego’s CEO Kjeld Kirk Kristiansen lost patience and fired Ploughman.

The business press reported that Lego had “strayed from its core.”  However, the company tried to expand because its traditional operations were not as profitable as before.  If the company’s attempted expansion had been more profitable, the business press would have reported that Lego “wisely expanded.”

(Photo of lego bricks by Benjamin D. Esham)

When it comes to business performance, there are many factors—including luck.  A company may move forward on an absolute basis, but fall behind relative to competitors.  Also, consumer tastes are unpredictable.

  • A company may attempt expansion and fail, but the decision may have been wise based on available information.  Regardless, observers are likely to say the company “unwisely strayed from its core.”
  • Or a company may try to expand and succeed, but it may have been a stupid decision based on available information.  Regardless, observers are likely to claim that the company “brilliantly expanded.”

To understand better how businesses succeed, we should try to understand what factors are involved in good decisions, even though good decisions often don’t work and bad decisions sometimes do.  We want to avoid outcome bias, where our evaluation of the quality of a decision is colored by whether the result was favorable or not.

Science is:  if x, then y (with probability z).  This is a slightly modified definition (I added “with probability z”) Rosenzweig borrowed from physicist Richard Feynman.

In some areas of business, scientists have discovered reliable statistical correlations.  For instance, this set of behaviors—a, b, and c—has a 0.10 correlation with revenues.  If you do a, b, and c—holding all else constant—then revenues will increase approximately 10%.

The difficult thing about studying business is that often you cannot run controlled experiments.  Of course, sometimes you can.  For instance, you can experiment with where to place various items in a store (or chain of stores).  You can compare results and gain good statistical information.  Also, there are promotions and advertising campaigns that you can test.  And you can track consumer behavior online.

But frequently you cannot run controlled experiments.  As Rosenzweig observes, you can’t do 100 acquisitions, and manage half of them one way, the other half another way, and then compare the results.

There’s nothing wrong with stories, which are satisfying explanations we construct about various events.  But stories are not science, and it’s important to keep the distinction straight, especially when we’re trying to understand why things happen.

An even better term than pseudo-science is Feynman’s term, Cargo Cult Science.  Rosenzweig quotes Feynman:

In the South Seas, there is a cult of people.  During the war, they saw airplanes land with lots of materials, and they want the same thing to happen now.  So they’ve arranged to make things like runways, to put fires along the sides of the runways, to make a wooden hut for a man to sit in, with two wooden pieces on his head like headphones and bars of bamboo sticking out like antennas—he’s the controller—and they wait for the airplanes to land.  They’re doing everything right.  The form is perfect.  But it doesn’t work.  No airplanes land.  So I call these things Cargo Cult Science, because they follow all the apparent precepts and forms of scientific investigation, but they’re missing something essential, because the planes don’t land.

(Photo of Richard Feynman in 1984, by Tamiko Thiel)

Rosenzweig concludes:

The business world is full of Cargo Cult Science, books and articles that claim to be rigorous scientific research but operate mainly at the level of storytelling.  In later chapters, we’ll look at some of this research—some that meet the standard of science but aren’t satisfying as stories, and some that offer wonderful stories but are doubtful as science.  As we’ll see, some of the most successful business books of recent years, perched atop the bestseller list for months on end, cloak themselves in the mantle of science, but have little more predictive power than a pair of coconut headsets on a tropical island.

It’s not that stories have nothing to teach us.  For instance, experts may develop deep historical knowledge that offers us useful insights into human behavior.  And such knowledge is often an antecedent to scientific knowledge.

But we have to be careful not to confuse stories with science.  Otherwise, it’s very easy and natural to delude ourselves that we understand something scientifically, when in fact we don’t.  Our intuition creates simple stories of cause and effect just as automatically as our visual system is unable to avoid optical illusions.

(Holy grail or two girls, by Micka)

 

THE STORY OF CISCO

Rosenzweig tells the story of Cisco.  Sandra K. Lerner and Leonard Bosack met in graduate school, fell in love, and got married.  After graduating, they each took jobs managing computer networks at different corners of the Stanford campus.  They wanted to communicate, and they invented a multiprotocol router.  Rosenzweig:

Like many start-ups, Cisco began by operating out of a basement and at first sold its wares to friends and professional acquaintances.  Once revenues approached $1 million, Lerner and Bosack went in search of venture capital.  The man who finally said yes was Donald Valentine at Sequoia Capital, the seventy-seventh moneyman they approached, who invested $2.5 million for a third of the stock and management control.  Valentine began to professionalize Cisco’s management, bringing in as CEO an industry veteran, John Morgridge.  Sales grew rapidly, from $1.5 million in 1987 to $28 million in 1989, and in February 1990, Cisco went public.

Valentine and Morgridge brought on John Chambers as a sales executive in 1991.  Chambers had worked at IBM and Wang Labs, and was ready to work at a smaller company where he might have more of an impact.  Chambers came up with a plan for Cisco to dominate the market for computer infrastructure.  Over the next three years, Cisco acquired two dozen companies.

(Cisco Logo, via Wikimedia Commons)

Chambers became CEO in 1995 and Cisco continued acquiring companies.  Cisco’s revenues reached $4 billion in 1997.  Rosenzweig:

Cisco rode the crest of the internet wave in 1998… Cisco had a 40 percent share of the $20 billion data-networking equipment industry—routers, hubs, and devices that made up the so-called plumbing of the Internet—and a massive 80 percent share of the high-end router market.  But Cisco wasn’t just growing revenues.  It was profitable, too.  At a time when even the most admired Internet start-ups, like Amazon.com, were losing money, Cisco posted operating margins of 60 percent.  This wasn’t some dot-com with a business plan, way out there in the blue, riding on a smile and a shoeshine.  It wasn’t panning for Internet gold, it was selling picks and shovels to miners who were lining up around the corner to buy them…

Cisco reached $100 billion market capitalization in just twelve years.  It had taken Microsoft twenty years (the previous record).

Accounts explaining Cisco’s success nearly always gave credit to John Chambers.  He’d overcome dyslexia to go to law school.  And Chambers said he learned from working at IBM and Wang that if you don’t react to shifts in technology, your work will be lost and the lives of employees disrupted.  Cisco wouldn’t make that mistake, Chambers declared.

Cisco had a disciplined, detailed process for making acquisitions, and an even more disciplined process for integrating acquisitions into Cisco’s operations.  Cisco had made “a science” of acquisitions.  And it cared a lot about the human side—turnover rate for acquired employees was only 2.1% versus an industry average of 20%.

After the Internet stock bubble burst, business reporters completely reversed their opinion of Cisco on every major point:

  • Customer service—from excellent to poor
  • Forecasting ability—from outstanding to terrible
  • Innovation—from nearly perfect to visibly flawed
  • Acquisitions—from scientific process to binge buying
  • Senior leadership—from amazing to arrogant

Business reporters recalled that Chambers had claimed that Cisco “was faster, smarter, and just plain better than competitors.”  Rosenzweig says this is fascinating because only business reporters had said this when Cisco was doing well.  Chambers himself never said it, but now business writers seemed to recall that he had.

Rosenzweig points out that it was possible that Cisco had changed.  But that’s not what business reporters were saying.  They viewed Cisco through an entirely different lens, now that the company was struggling.

The essence of the Halo Effect: If a company is performing well, then it’s easy to view virtually everything it does through a positive lens.  If a company is doing poorly, then it’s natural to view virtually everything it does through a negative lens.  The story of Cisco certainly fits this pattern.

As Rosenzweig remarks, the fundamental problem is twofold:

  • We have little scientific knowledge of what leads to business success or failure.
  • But we do know about revenues, profits, and the stock price.  If these observable measures are positive, we intuitively jump to the conclusion that the company must be doing many things well.  If these observable measures are declining, we conclude that the company must be doing many things poorly.

 

UP AND DOWN WITH ABB

ABB is a Swedish-Swiss industrial company that was created in 1988 by the merger of two leading engineering companies, Sweden’s ASEA and Switzerland’s Brown Boveri.

(ABB Logo, via Wikimedia Commons)

Rosenzweig thought it would be interesting to look at a non-American, non-Internet company.  The Halo Effect is still clearly visible in the accounts of ABB’s rise and fall.

When it came to ABB’s rise, from the late 1980’s to the late 1990’s, we see that business experts drew similar conclusions.  First, the CEO, Percy Barnevik, was widely and highly praised.  Rosenzweig describes Barnevik as a “Scandinavian who combined old world manners and language skills with American pragmatism and an orientation for action.”  Barnevik was described in the press as very driven, but also unpretentious and accessible.  He met frequently with all levels of ABB management.  He was a speed reader and highly analytical.  Away from work, he climbed mountains and went for long jogs (lasting up to 10 hours).  On top of all this, Barnevik was viewed as humble, not arrogant.  By 1993, Barnevik had become a legend.

Another explanation for ABB’s success was its culture.  Despite its conservative Swedish and Swiss roots, ABB had a strong bias for action.  Barnevik said so on several occasions, asserting that the only unacceptable thing was to do nothing.  He claimed that if you do 50 things, and 35 are in the right direction, that is enough.

A third explanation was that the company was designed to be globally efficient, but still able to compete in local markets.  Barnevik wanted people in different locations to be able to launch new products, make design changes, or alter production methods.  ABB had a matrix structure, with fifty-one business areas and forty-one country managers.  This resulted in 5,000 profit centers, with each one empowered to achieve high performance and accountable to do so.

In 1996, ABB was named Europe’s Most Respected Company for the third year in a row by the Financial Times.  Kevin Barham and Claudia Heimer, of Ashridge Management Centre in England, published a 382-page book about ABB.  They identified five reasons for ABB’s success:  customer focus, connectivity, communication, collegiality, and convergence.  They placed ABB in the same category as Microsoft and General Electric.

In 1997, Barnevik stepped down as CEO, replaced by Goran Lindahl.  Then the company transitioned towards businesses based on intellectual capital.  ABB entered new areas, like financial services.  It exited the trains and trams business, as well as the nuclear fuels business.  Rosensweig asks if ABB was “straying from its core.”  Not at all because ABB was still seen as a success.  Lindahl was CEO of the year in 1999 according to the American publication, Industry Week.  Lindahl was the first European to get this award.

In November 2000, Lindahl abruptly stepped down, saying he wanted to be replaced by someone with more expertise in IT.  Jürgen Centerman became the new CEO.

ABB’s performance entered a steep decline.  Centerman was replaced by Jürgen Dormann in September 2002.  Dormann sold the company’s petrochemicals business and its structured finance business.  ABB focused on automation technologies and power technologies.  But the company’s market cap dipped below $4 billion, down from a peak of $40 billion.

When ABB was on the rise in terms of performance, it was described as bold and daring because of its bias for action and experimentation.  Now, with performance being poor, ABB was described as impulsive and foolish.  Moreover, whereas ABB’s decentralized strategy had been praised when ABB was rising, now the same strategy was criticized.  As for Barnevik, while he had previously been described as bold and visionary, now he was called arrogant and imperial.

Most interesting of all, notes Rosenzweig, is that neither the company nor Barnevik was thought to have changed.  It was only how they were characterized that had changed—clear examples of the Halo Effect.

Rosenzweig writes:

…one of the main reasons we love stories is that they don’t simply report disconnected facts but make connections about cause and effect, often ascribing credit or blame to individuals.  Our most compelling stories often place people at the center of events… Once widely revered, Percy Barnevik was now an exemplar of arrogance, of greed, of bad leadership.

 

HALOS ALL AROUND US

During World War I, the American psychologist Edward Thorndike studied how superiors rated their subordinates.  Thorndike noticed that good soldiers were good on nearly every attribute, whereas underperforming soldiers were bad on nearly every attribute.  Rosenzweig comments:

It was as if officers figured that a soldier who was handsome and had good posture should also be able to shoot straight, polish his shoes well, and play the harmonica, too.

Thorndike called this the Halo Effect.  Rosenzweig:

There are a few kinds of Halo Effect.  One refers to what Thorndike observed, a tendency to make inferences about specific traits on the basis of a general impression.  It’s difficult for most people to independently measure separate features; there’s a common tendency to blend them together.  The Halo Effect is a way for the mind to create and maintain a coherent and consistent picture, to reduce cognitive dissonance.

(Image by Aliaksandra Molash)

Rosenzweig gives the example of George W. Bush.  After the September 11 attacks in 2001, Bush’s approval ratings rose sharply, not surprisingly as the public rallied behind him.  But Bush’s ratings on other factors, such as his management of the economy, also rose significantly.  There was no logical reason to think Bush’s handling of the economy was suddenly much better after the attacks.  This is an instance of the Halo Effect.

By October 2005, the situation had reversed.  Support for the Iraq War waned, and people were upset about the government response to Hurricane Katrina.   Bush’s overall ratings were at 37 percent.  His rating was also lower in every individual category.

Rosenzweig then explains another kind of Halo Effect:

…the Halo Effect is not just a way to reduce cognitive dissonance.  It’s also a heuristic, a sort of rule of thumb that people use to make guesses about things that are hard to assess directly.  We tend to grasp information that is relevant, tangible, and appears to be objective, and then make attributions about other features that are more vague or ambiguous.

Rosenzweig later adds:

All of which helps explain what we saw at Cisco and ABB.  As long as Cisco was growing and profitable and setting records for its share price, managers and journalists and professors inferred that it had a wonderful ability to listen to its customers, a cohesive corporate culture, and a brilliant strategy.  And when the bubble burst, observers were quick to make the opposite attribution.  It all made sense.  It told a coherent story.  Same for ABB, where rising sales and profits led to favorable evaluations of its organization structure, its risk-taking culture, and most clearly the man at the top—and then to unfavorable evaluations when performance fell.

Rosenzweig recounts an experiment by professor Barry Staw.  Various groups of people were asked to forecast future sales and earnings based on a set of financial data.  Then some groups were told they’d done a good job, while other groups were told the opposite.  But this was done at random, completely independent of actual performance.

Later, each group was asked about how it had functioned as a group.  Groups that had been told that they did well on their forecasts reported that their group had been cohesive, with good communication, openness to change, and good motivation.  Groups that had been told that they didn’t do well on their forecasts reported that they lacked cohesion, had poor communication, and were unmotivated.

Staw’s experiment is a clear demonstration of the Halo Effect.

  • If people believe that a group is effective—irrespective of whether the group can be measured as such—then they attribute one set of characteristics to it.
  • If people believe that a group is ineffective—irrespective of whether the group can be measured as such—then they attribute the opposite set of characteristics to it.

This doesn’t mean that cohesiveness, motivation, etc., is unimportant for group communication.  Rather, it means that people typically cannot assess these types of qualities with much (or any) objectivity, especially if they already have a belief about how a given group has performed in some task.

When it’s hard to measure something objectively, people tend to look for something that is objective and use that as a heuristic, inferring that harder-to-measure attributes must be similar to whatever is objective (like financial peformance).

As yet another example, Rosenzweig mentions that IBM’s employees were viewed as smart, creative, and hardworking in 1984 when IBM was doing well.  In 1992, after IBM had faltered, the same people were described as complacent and bureauratic.

As we’ve seen, the Halo Effect is particularly frequent when people try to judge how good a leader is.  Just as we don’t have much scientific knowledge for how a company can succeed, we also don’t have much scientific knowledge about what makes a good leader.  Experts, when they look at a company that is doing well, tend to think that the leader has many good qualities such as courage, clear vision, and integrity.  When the same experts examine a company that is doing poorly, they tend to conclude that the leader lacks courage, vision, and integrity.  This happens even when experts are looking at the same company and that company is doing the same things.

(Image by Kirsty Pargeter)

When Microsoft was doing well, Bill Gates was described as ambitious, brilliant, and visionary.  When Microsoft appeared to falter in 2001, after Judge Thomas Penfield Jackson ordered Microsoft to be broken up, Bill Gates was described as arrogant and stubborn.

Rosenzweig gives two more examples:  Fortune’s World’s Most Admired Companies, and the Great Places to Work Institute’s Best Companies to Work For index.  Both lists appear to be significantly impacted by the Halo Effect.  Companies that have been doing well financially tend to be viewed and described much more favorably on a range of metrics.

Rosenzweig closes the chapter by noting that the Halo Effect is the most basic delusion, but that there are several more delusions he will examine in the coming chapters.

 

RESEARCH TO THE RESCUE?

Rosenzweig:

The Halo Effect shapes how we commonly talk about so many topics in business, from decision processes to people to leadership and more.  It shows up in our everyday conversations and in newspaper and magazine articles.  It affects case studies and large-sample surveys.  It’s not so much the result of conscious distortion as it is a natural human tendency to make judgments about things that are abstract and ambiguous on the basis of other things that are salient and seemingly objective.  The Halo Effect is just too strong, the desire to tell a coherent story too great, the tendency to jump on bandwagons too appealing.

The most fundamental business question is:

What leads to high business performance?

The Halo Effect is far from inevitable, despite being very common.  There are researchers who use careful statistical tests to isolate the effects of independent variables on dependent variables.

The dependent variables relate to company performance.  And we have good data on that, from revenues to profits to return on capital.

As for the independent variables, some of these, such as R&D spending, are not tainted.  Much trickier is what happens inside a company, such as quality of management, customer orientation, company culture, etc.

Rosenzweig explores the question of whether customer focus leads to better company performance.  It probably does.  However, in order to measure the effect of customer focus on performance objectively, we should not look at magazine and newspaper articles—since these are impacted by the Halo Effect.  Nor should we ask company employees about their customer focus.  How a company is performing—well or poorly—will impact the opinions of managers and employees regarding customer focus.

Similar logic applies to the question of how corporate culture impacts business performance.  Surveys of managers and employees will be tainted by the Halo Effect.  Yes, corporate culture impacts business performance.  But to figure out the statistical correlation, we have to be sure to avoid data likely to be skewed by the Halo Effect.

Delusion Two: The Delusion of Correlation and Causality

Rosenzweig gives the example of employee turnover and company performance.  If there is a statistical correlation between the two, then what does that mean?  Does lower employee turnover lead to higher company performance?  That sounds reasonable.  On the other hand, does higher company performance lead to lower employee turnover?  That could very well be the case.

Potential confusion about correlation versus causality is widespread when it comes to the study of business.

One way to get some insight into potential causality is to conduct a longitudinal study, looking at independent variables in one period and hypothetically dependent variables in some later period.  Rosenzweig:

One recent study, by Benjamin Schneider and colleagues at the University of Maryland, used a longitudinal design to examine the question of employee satisfaction and company performance to try to find out which one causes which.  They gathered data over several years so they could watch both changes in satisfaction and changes in company performance.  Their conclusion?  Financial performance, measured by return on assets and earnings per share, has a more powerful effect on employee satisfaction than the reverse.  It seems that being on a winning team is a stronger cause of employee satisfaction; satisfied employees don’t have as much of an effect on company performance.  How were Schneider and his colleagues able to break the logjam and answer the question of which leads to which?  By gathering data over time.

Delusion Three: The Delusion of Single Explanations

Rosenzweig describes two studies that were carefully conducted, one on the effect of market orientation on company performance, and the other on the effect of CSR—corporate social responsibility—on company performance.  The studies were careful in that they didn’t just ask for opinions.  They asked about different activities in which the company did or did not engage.

The conclusion of the first study was that market orientation is responsible for 25 percent of company performance.  The second study concluded that CSR is responsible for 40 percent of company performance.  Rosenzweig asks: Does that mean that market orientation and CSR together explain 65 percent of company performance?  Or do the variables overlap to an extent?  The problem with studying a single cause of company performance is that you don’t know if part of the effect may be due to some other variable you’re not measuring.  If a company is well-managed, then wouldn’t that be seen in market orientation and also in CSR?

(Photo by Jörg Stöber)

We could throw human resource management—HRM—into the mix, too.  Same goes for leadership.  One study found that good leadership is responsible for 15 percent of company performance.  But is that in addition to market orientation, CSR, and HRM?  Or do these things overlap to an extent?  It’s likely that there is significant overlap among these four variables.

One problem is that many researchers would like to tell a clear story about cause and effect.  Admitting that many key variables likely overlap means that the story is much less clear.  People—especially if busy or pressured—prefer simple stories where cause and effect seem obvious.

Furthermore, many important questions are at the intersection of different fields.  Rosenzweig gives the example of decision making, which involves psychology, sociology, and economics.  The trouble is that an expert in marketing will tend to exaggerate the importance of marketing.  An expert in CSR will tend to exaggerate the importance of CSR.  And so forth for other specialties.

 

SEARCHING FOR STARS, FINDING HALOS

Rosenzweig lists the eight practices of America’s best companies according to In Search of Excellence: Lessons from America’s Best-Run Companies, published by Tom Peters and Bob Waterman in 1982:

  • A bias for action—a preference for doing something—anything—rather than sending a question through cycles and cycles of analyses and committee reports.
  • Staying close to the customer—learning his preferences and catering to them.
  • Autonomy and entrepreneurship—breaking the corporation into small companies and encouraging them to think independently and competitively.
  • Productivity through people—creating in all employees the awareness that their best efforts are essential and that they will share in the rewards of the company’s success.
  • Hands-on, value-driven—insisting that executives keep in touch with the firm’s essential business.
  • Stick to the knitting—remaining with the business the company knows best.
  • Simple form, lean staff—few administrative layers, few people at the upper levels.
  • Simultaneous loose-tight properties—fostering a climate where there is dedication to the central values of the company combined with a tolerance for all employees who accept those values.

Rosenzweig points out that this list looks familiar:  Care about your customers.  Have strong values.  Create a culture where people can thrive.  Empower your employees.  Stay focused.

If these look correlated, says Rosenzweig, that’s because they are.  The best companies do all of them.  Of course, again there’s the Halo Effect.  If you isolate the top-performing companies (43 of them in this case), and then ask managers and employees about customer focus, values, culture, leadership, focus, etc., then you won’t know what caused what.  Did clear strategy, good organization, strong corporate culture, and customer focus lead to the high performance?  Or do people view high-performing companies as doing well in these areas?

(Image by Eriksvoboda)

When the book was published in 1982, there was a widespread concern among American businesses that Japanese companies were better overall.  Peters and Waterman made the point that the leading American businesses were doing well in a variety of key areas.  This message was viewed not only as inspirational, but even as patriotic.  It was the right story for the times.

Many thought that In Search of Excellence contained scientific knowledge:  if x, then y (with probability z).  People thought that if they implemented the principles highlighted by Peters and Waterman, then they would be successful in business.

However, just two years later, some of the excellent companies did not seem as excellent as before.  Some were blamed for changing—not sticking to their knitting.  Others were blamed for NOT changing—not being adaptable enough, not taking action.  More generally, some were blamed for overemphasizing certain principles, while underemphasizing other principles.

Rosenzweig examined the profitability of 35 of the 43 excellent companies—the 35 companies for which data were available because these companies were public.  He found that, in the five years after 1982, 30 out of 35 had a decline in profitability.  If these were truly excellent companies, then such a decline for 30 of 35 doesn’t make sense.

(Image by Dejan Lazarevic)

Rosenzweig observes that it’s possible that the previous success of these companies was due to more than the eight principles identified by Peters and Waterman.  And so changes in other variables may explain the subsequent declines in profitability.  It’s also possible—because Peters and Waterman identified 43 highly successful companies and then interviewed managers at those companies—that the Halo Effect came into play.  The eight principles may reflect attributions that people tend to make about currently successful companies.

Delusion Four: The Delusion of Connecting the Winning Dots

You can’t choose a sample based only on the dependent variable you’re trying to test.  The dependent variable in this case is successful companies.  If all you look at is successful companies, then you won’t be able to compare successful companies directly to unsuccessful companies in order to learn about their respective causes—the independent variables.  Rosenzweig refers to this error as the Delusion of Connecting the Winning Dots.  You can connect the dots any way you wish, but following this approach, you can’t learn about the independent variables that lead to success.

Like many areas of social science, it’s not easy.  You can’t run an experiment where you take 100 companies, and manage half of them one way, and half of them another way, and then compare results.

(Image by Macrovector)

Jim Collins and Jerry Porras isolated 18 companies based on excellent performance over a long period of time.  Also, for each of these companies, Collins and Porras identified a similar company that had been less successful.  This at least could avoid the error that Peters and Waterman made.  As Collins and Porras said, if all you looked at were successful companies, you might find that they all reside in buildings.

Collins, Porras, and their team read more than 100 books and looked at more than 3,000 documents.  All told, they had a huge amount of data.  They certainly worked very hard.  But that in itself does not increase the scientific validity of their study.

Collins and Porras claimed to have found “timeless principles,” which they listed:

  • Having a strong core ideology that guides the company’s decisions and behavior
  • Building a strong corporate culture
  • Setting audacious goals that can inspire and stretch people—so-called big hairy audacious goals, or BHAGs
  • Developing people and promoting them from within
  • Creating a spirit of experimentation and risk taking
  • Driving for excellence

Unfortunately, much of the data came from books, the business press, and company documents, all likely to contain Halos.  They also conducted interviews with managers, who were asked to look back on their success and explain the reasons.  These interviews were probably tinged by Halos in many cases.  Some of the principles identified may have led to success.  However, successful companies were also likely to be described in these terms.  The Halo Effect hadn’t been dealt with by Collins and Porras.

Rosenzweig looked at profitability over the subsequent five years.  Eleven companies saw profits decline.  One was unchanged.  Only five of the best companies had profits increase.  It seems the “master blueprint for long-term prosperity” is largely a delusion, writes Rosenzweig.

(Graph by Experimental)

It’s not just some of the companies, but most of the companies that saw profits decline.  Characterizations of the “best” companies were probably impacted significantly by the Halo Effect.  The very fact that these companies had been doing well for some time led many to see them as having positive attributes across the board.

Delusion Five: The Delusion of Rigorous Research

As noted, psychologist Philip Tetlock tracked the predictions of 284 leading experts over two decades.  Tetlock looked at over 27,000 predictions in real time of the form:  more of x, no change in x, or less of x.  He found that these predictions were no better than random chance.

Many experts have deep knowledge—historical or otherwise—that can give us valuable insights into human affairs.  Some of this expertise is probably accurate.  But until we have testable predictions, it’s difficult to say which hypotheses are true and to what degree.

We should never forget the difference between scientific knowledge and other types of knowledge, including stories.  It’s very easy for us humans to be overconfident and deluded, especially if certain stories are the result of “many years of hard work.”

Delusion Six: The Delusion of Lasting Success

Richard Foster and Sarah Kaplan looked at companies in the S&P 500 from 1957 to 1997.  By 1997, only 74 out of the original largest 500 companies were still in the S&P 500.  Of those 74 survivors, how many outperformed the S&P 500 over those 40 years?  Only 12.

Foster and Kaplan conclude:

KcKinsey’s long-term studies of corporate birth, survival, and death in America clearly show that the corporate equivalent of El Dorado, the golden company that continually performs better than the markets, has never existed.  It is a myth.  Managing for survival, even among the best and most revered corporations, does not guarantee strong long-term performance for shareholders.  In fact, just the opposite is true.  In the long run, the markets always win.

It’s not that busines success is completely random.  Of course not.  But there is usually a large degree of luck involved.  More fundamentally, capitalism is about competition through innovation, or creative destruction, as the great Austrian economist Joseph Schumpeter called it.  There is some inherent unpredictability—or luck—in this endless process.

Delusion Seven: The Delusion of Absolute Performance

Kmart improved noticeably from 1994 to 2002, but Wal-Mart and Target were ahead at the beginning of that period, and they improved even faster than Kmart.  Thus, although it would seem Kmart was doing the right things in terms of absolute performance, Kmart was falling even further behind in terms of relative performance.

In 2005, GM was making much better cars than in the 1980s.  But its market share kept slipping, from 35 percent in 1990 to 25 percent in 2005.  GM’s competitors were improving faster.

Rosenzweig sums it up:

The greater the number of rivals, and the easier for competitors to enter the market, and the more rapidly technology changes, the more difficult it is to sustain success.  That’s an uncomfortable truth, because it admits that some elements of business performance are outside of our control.  It’s far more appealing to downplay the relative nature of performance or ignore it completely.  Telling a company it can achieve high performance, regardless of what competitors do, makes for a more attractive story.

Delusion Eight: The Delusion of the Wrong End of the Stick

In Good to Great, Collins argues that a company can decide to become great and follow the blueprint in the book.  Part of the recipe is to be like a Hedgehog—to have a narrow focus and pursue it with great discipline.  The problem, again, is that the role of chance—or factors outside one’s control—is not considered.  (The terms “Hedgehog” and “Fox” come from an essay by Isaiah Berlin.  The Hedgehog knows one big thing, whereas the Fox knows many things.)

(Image by Marek Uliasz)

Statistically, it’s possible that, on the whole, more Hedgehogs than Foxes failed.  You could still argue that the potential upside for becoming a great company is so large that it’s worth taking the risk of being like a Hedgehog.  But Collins doesn’t mention risk, or chance, at all.

Of course, we’d all prefer a story where greatness is purely a matter of choice.  But it’s rarely that simple and luck nearly always plays a pivotal role.

Delusion Nine: The Delusion of Organizational Physics

For many questions in business, we can’t run experiments.  That said, with enough care, important statistical correlations can be discovered.  Other things can be measured even more precisely.

But to think that the study of business is like the science of physics is a delusion, at least for now.

It’s reasonable to suppose that, with enough scientific knowledge in neuroscience, genetics, psychology, economics, artificial intelligence, and related areas, eventually human behavior may become largely predictable.  But there’s a long way to go.

 

THE MOTHER OF ALL BUSINESS QUESTIONS, TAKE TWO

By nature, we prefer stories where business success is entirely a result of choosing to do the right things, while not reaching success must be due to a failure to do the right things.  But stories like this neglect the role of chance.  Rosenzweig writes:

…all the emphasis on steps and formulas may obscure a more simple truth.  It may further the fiction that a specific set of steps will lead, predictably, to success.  And if you never achieve greatness, well, the problem isn’t with our formula—which was, after all, the product of rigorous research, of extensive data exhaustively analyzed—but with you and your failure to follow the formula.  But in fact, the truth may be considerably simpler than these formula suggest.  They may divert our attention from a more powerful insight—that while we can do many things to improve our chances of success, at its core business performance contains a large measure of uncertainty.  Business performance may actually be simpler than it is often made out to be, but may also be less certain and less amenable to engineering with predictable outcomes.

There is a simpler way to think about business performance—suggested by Michael Porter—without neglecting the role of chance.  Strategy is doing certain things different from rivals.  Execution is people working together to create products by implementing the strategy.  This is a reasonable way to think about business performance as long as you also note the role of chance.

It’s usually hard to know how potential customers will behave.  There are, of course, many examples where, contrary to expectations, a product was embraced or rejected.  Moreover, even if you correctly understand customers, competitors may come up with a better product.

There’s also the issue of technological change, which can be a significant source of unpredictability in some industries.

(Illustration by T. L. Furrer)

Clayton Christensen has demonstrated—in The Innovator’s Dilemma—that frequently companies fail because they keep doing the right things, giving customers what they want.  Meanwhile, competitors develop a new technology that, at first, is not profitable—which is part of why the company “doing the right things” ignores it.  But then, unpredictably, some of these new technologies end up being popular and also profitable.

One good question is:  What should a company do when its core comes under pressure?  Should it redouble its focus on the core, like a Hedgehog?  Or should it be adaptable, like a Fox?  There are no good answers at the moment, says Rosenzweig.  There are too many variables.  Chance—or uncertainty—plays a key role.

Rosenzweig continues:

In the meantime, we’re left with the brutal fact that strategic choice is hugely consequential for a company’s performance yet also inherently risky.  We may look at successful companies and applaud them for what seem, in retrospect, to have been brilliant decisions, but we forget that at the time those decisions were made, they were controversial and risky.  McDonald’s bet on franchising looks smart today, but in the 1950s it was a leap in the dark.  Dell’s strategy of selling direct now seems brilliant but was attempted only after multiple failures with conventional channels.  Or, recalling companies we discussed in earlier chapters, remember Cisco’s decision to assemble a full range of product offerings through acquisitions or ABB’s bet on leading rationalization of the European power industry through consolidation and cost cutting.  The managers who took those choices appraised a wide variety of factors and decided to be different from their rivals.  We remember all of these decisions because they turned out well, but success was not inevitable.  As James March of Stanford and Zur Shapira of New York University explained, “Post hoc reconstruction permits history to be told in such a way that ‘chance,’ either in the sense of genuinely probabilistic phenomena or in the sense of unexplained variation, is minimized as an explanation.”  But chance DOES play a role, and the difference between a brilliant visionary and a foolish gambler is usually inferred after the fact, an attribution based on outcomes.  The fact is, strategic choices always involve risk.  The task of strategic leadership is to gather appropriate information and evaluate it thoughtfully, then make choice that, while risky, provide the best chances for success in a competitive industry setting.

(Image by Donfiore)

As for execution, certain practices do correlate with modestly higher performance.  If leaders can identify the few areas where better execution is needed, then some progress can be made.

But inherent unpredictability is hidden by the Halo Effect.  If a company succeeds, it’s easy to say it executed well.  If a company fails, it’s natural to conclude that execution was poor.  Often to a large extent, these conclusions are driven by the Halo Effect, even if there is some truth to them.

In brief, smart strategic choices and good execution—plus good luck—may lead to success, at least temporarily.  But success brings challengers, some of whom will take greater risks that may work.  There’s no formula to guarantee success.  And if success is achieved, there’s no way to guarantee continued success over time.

 

MANAGING WITHOUT COCONUT HEADSETS

Given that there’s no simple formula that brings business success, what should we do?  Rosenzweig answers:

A first step is to set aside the delusions that color so much of our thinking about business performance.  To recognize that stories of inspiration may give us comfort but have little more predictive power than a pair of coconut headsets on a tropical island.  Instead, managers would do better to understand that business success is relative, not absolute, and that competitive advantage demands calculated risks.  To accept that few companies achieve lasting success, and that those that do are perhaps best understood as having strung together several short-term successes rather than having consciously pursued enduring greatness.  To admit that, as Tom Lester of the Financial Times so neatly put it, “the margin between success and failure is often very narrow, and never quite as distinct or as enduring as it appears at a distance.”  By extension, to recognize that good decisions don’t always lead to favorable outcomes, that unfavorable outcomes are not always the result of mistakes, and therefore to resist the natural tendency to make attributions based solely on outcomes.  And finally, to acknowledge that luck often plays a role in company success.  Successful companies aren’t “just lucky”—high performance is not purely random—but good fortune does play a role, and sometimes a pivotal one.

Rosenzweig mentions Robert Rubin as a good example of someone who learned to make decisions in terms of scenarios and their probabilities.

(Image by Elnur)

Rubin worked for eight years in the Clinton administration, first as director of the White House National Economic Council and later as secretary of the Treasury.  Prior to working in the Clinton administration, Rubin toiled for twenty-six years at Goldman Sachs.

Rubin first learned about the fundamental uncertainties of the world when he studied philosophy as an undergraduate.  He learned to view every proposition with skepticism.  Later at Goldman Sachs, Rubin saw first-hand that one had to consider possible outcomes and their associated probabilities.

Rubin spent years in risk arbitrage.  Many times Goldman made money, but roughly one out of every seven times, Goldman lost money.  Sometimes the loss would greatly exceed Goldman’s worst-case scenario.  But occasionally large and painful losses didn’t mean that Goldman’s decision-making process was flawed.  In fact, if Goldman wasn’t taking some losses, then they almost certainly weren’t taking enough risk.

(Photo by Alain Lacroix)

Rosenzweig asks:  If a large and painful loss doesn’t mean a mistake, then what does?

We have to take a close look at the decision process itself, setting aside the eventual outcome.  Had the right information been gathered, or had some important data been overlooked?  Were the assumptions reasonable, or had they been flawed?  Were calculations accurate, or had there been errors?  Had the full set of eventualities been identified and their impact estimated?  Had Goldman Sachs’s overall risk portfolio been properly considered?

Once again, a profitable outcome doesn’t necessarily mean the decision was good.  An unprofitable outcome doesn’t necessarily mean the decision was bad.  If you’re making decisions under uncertainty—probabilistic decisions—the only way to improve is to evaluate the process of decision-making independently of specific outcomes.

Of course, often important decisions for an individual business are quite infrequent.  Rosenzweig highlights important lessons for managers:

  • If independent variables aren’t measured independently, we may find ourselves standing hip-deep in Halos.
  • If the data are full of Halos, it doesn’t matter how much we’ve gathered or how sophisticated our analysis appears to be.
  • Success rarely lasts as long as we’d like—for the most part, long-term success is a delusion based on selection after the fact.
  • Company performance is relative, not absolute.  A company can get better and fall further behind at the same time.
  • It may be true that many successful companies bet on long shots, but betting on long shots does not often lead to success.
  • Anyone who claims to have found laws of business physics either understands little about business, or little about physics, or both.
  • Searching for the secrets of business success reveals little about the world of business but speaks volumes about the searchers—their aspirations and their desires for certainty.

Getting rid of delusions is a crucial step.  Furthermore, writes Rosenzweig, a wise manager knows:

  • Any good strategy involves risk.  If you think your strategy is foolproof, the fool may well be you.
  • Execution, too, is uncertain—what works in one company with one workforce may have different results elsewhere.
  • Chance often plays a greater role than we think, or than successful managers usually like to admit.
  • The link between inputs and outcomes is tenuous.  Bad outcomes don’t always mean that managers made mistakes; and good outcomes don’t always mean they acted brilliantly.
  • But when the die is cast, the best managers act as if chance is irrelevant—persistence and tenacity are everything.

Of course, none of this guarantees success.  But the sensible goal is to improve your chances of success.

 

BOOLE MICROCAP FUND

An equal weighted group of micro caps generally far outperforms an equal weighted (or cap-weighted) group of larger stocks over time.  See the historical chart here:  http://boolefund.com/best-performers-microcap-stocks/

This outperformance increases significantly by focusing on cheap micro caps.  Performance can be further boosted by isolating cheap microcap companies that show improving fundamentals.  We rank microcap stocks based on these and similar criteria.

There are roughly 10-20 positions in the portfolio.  The size of each position is determined by its rank.  Typically the largest position is 15-20% (at cost), while the average position is 8-10% (at cost).  Positions are held for 3 to 5 years unless a stock approaches intrinsic value sooner or an error has been discovered.

The goal of the Boole Microcap Fund is to outperform the Russell Microcap Index over time, net of fees.  The Boole Fund has low fees. 

 

If you are interested in finding out more, please e-mail me or leave a comment.

My e-mail: jb@boolefund.com

 

 

 

Disclosures: Past performance is not a guarantee or a reliable indicator of future results. All investments contain risk and may lose value. This material is distributed for informational purposes only. Forecasts, estimates, and certain information contained herein should not be considered as investment advice or a recommendation of any particular security, strategy or investment product. Information contained herein has been obtained from sources believed to be reliable, but not guaranteed. No part of this article may be reproduced in any form, or referred to in any other publication, without express written permission of Boole Capital, LLC.

Value Investing: The Most Important Thing

(Image:  Zen Buddha Silence by Marilyn Barbone.)

June 17, 2018

Value investing can be a relatively low risk way for some investors to beat the market over time.  Yet it often takes a decade to get the hang of it.  Even then, you have to keep improving indefinitely.  But the great thing is that you can keep improving indefinitely as long as your health stays good.  In addition to learning from experience, an excellent way to progress is by studying the best value investors.

Howard Marks is not only a great value investor.  But he also has written an outstanding book, The Most Important Thing: Uncommon Sense for the Thoughtful Investor (Columbia University Press, 2011).  Like most classics, Marks’s book is worth re-reading periodically.

This blog post is intended for two groups:

  • People who already have some experience with value investing.  It’s worth regularly reviewing the teachings of the masters.
  • People who are interested in learning about value investing.

Here’s an outline.  Each section can be read independently:

  • A Value Investing Philosophy
  • Second-Level Thinking
  • Understanding Market Efficiency
  • Value
  • The Relationship Between Price and Value
  • Understanding Risk
  • Recognizing Risk
  • Controlling Risk
  • Being Attentive to Cycles
  • Awareness of the Pendulum
  • Combating Negative Influences
  • Contrarianism
  • Finding Bargains
  • Patient Opportunism
  • Knowing What You Don’t Know
  • Having a Sense of Where We Stand
  • Appreciating the Role of Luck
  • Investing Defensively

(https://amzn.to/2JQgQRG)

The title of the book is based on the fact that Marks wrote a series of memos to clients identifying “the most important thing.”  Looking back, Marks realized that there were many “most important things.”

The thing I find most interesting about investing is how paradoxical it is: how often the things that seem most obvious—on which everyone agrees—turn out not to be true. — Howard Marks

 

A VALUE INVESTING PHILOSOPHY

A value investing philosophy takes time to develop, as Marks notes:

A philosophy has to be the sum of many ideas accumulated over a long period of time from a variety of sources.  One cannot develop an effective philosophy without having been exposed to life’s lessons.  In my life I’ve been quite fortunate in terms of both rich experiences and powerful lessons.

Good times teach only bad lessons: that investing is easy, that you know its secrets, and that you needn’t worry about risk.  The most valuable lessons are learned in tough times.

(Photo by Yuryz)

 

SECOND-LEVEL THINKING

Marks first points out how variable the investing landscape is:

No rule always works.  The environment isn’t controllable, and circumstances rarely repeat exactly.  Psychology plays a major role in markets, and because it’s highly variable, cause-and-effect relationships aren’t reliable.

The goal for an investor is to do better than the market over time.  Otherwise, the best option for most investors is simply to buy and hold low-cost broad market index funds.  Doing better than the market requires an identifiable edge:

Since other investors may be smart, well-informed and highly computerized, you must find an edge they don’t have.  You must think of something they haven’t thought of, see things they miss or bring insight they don’t possess.  You have to react differently and behave differently.  In short, being right may be a necessary condition for investment success, but it won’t be sufficient.  You must be more right than others… which by definition means your thinking has to be different.

(Photo by Andreykuzmin)

Marks gives some examples of second-level thinking:

First-level thinking says, ‘It’s a good company; let’s buy the stock.’ Second-level thinking says, ‘It’s a good company, but everyone thinks it’s a great company, and it’s not.  So the stock’s overrated and overpriced; let’s sell.’

First-level thinking says, ‘The outlook calls for low growth and rising inflation. Let’s dump our stocks.’   Second-level thinking says, ‘The outlook stinks, but everyone else is selling in panic.  Buy!’

First-level thinking says, ‘I think the company’s earnings will fall; sell.’ Second-level thinking says, ‘I think the company’s earnings will fall less than people expect, and the pleasant surprise will lift the stock; buy.’

Marks explains that first-level thinking is generally simplistic.  By contrast, second-level thinking requires thinking of the full range of possible future outcomes, along with estimating probabilities for each possible outcome.  Second-level thinking means understanding what the consensus thinks, why you have a different view, and the likelihood that one’s contrarian view is correct.  Marks observes that second-level thinking is far more difficult than first-level thinking, thus few investors truly engage in second-level thinking.  First-level thinkers cannot expect to outperform the market.

To outperform the average investor, you have to be able to outthink the consensus.  Are you capable of doing so?  What makes you think so?

 

UNDERSTANDING MARKET EFFICIENCY

Marks holds a view of market efficiency similar to that of Warren Buffett:  The market is usually efficient, but it is far from always efficient.

(Illustration by Lancelotlachartre)

Marks says that the market reflects the consensus view, but the consensus is not always right:

In January 2000, Yahoo sold at $237.  In April 2001 it was $11.  Anyone who argues that the market was right both times has his or her head in the clouds; it has to have been wrong on at least one of those occasions.  But that doesn’t mean many investors were able to detect and act on the market’s error.

Marks summarizes his view:

The bottom line for me is that, although the more efficient markets often misvalue assets, it’s not easy for any one person—working with the same information as everyone else and subject to the same psychological influences—to consistently hold views that are different from the consensus and closer to being correct.  That’s what makes the mainstream markets awfully hard to beat—even if they aren’t always right.

Marks makes an important point about riskier investments:

Once in a while we experience periods when everything goes well and riskier investments deliver the higher returns they seem to promise.  Those halcyon periods lull people into believing that to get higher returns, all they have to do is make riskier investments.  But they ignore something that is easily forgotten in good times: this can’t be true, because if riskier investments could be counted on to produce higher returns, they wouldn’t be riskier.

Marks notes that inefficient prices imply that for each investor who buys at a cheap price, another investor must sell at that cheap price.  Inefficiency essentially implies that each investment that beats the market implies another investment that trails the market by an equal amount.

Generally it is exceedingly difficult to beat the market.  To highlight this fact, Marks asks a series of questions:

  • Why should a bargain exist despite the presence of thousands of investors who stand ready and willing to bid up the price of anything that is too cheap?
  • If the return appears so generous in proportion to the risk, might you be overlooking some hidden risk?
  • Why would the seller of the asset be willing to part with it at a price from which it will give you an excessive return?
  • Do you really know more about the asset than the seller does?
  • If it’s such a great proposition, why hasn’t someone else snapped it up?

Market inefficiency alone, argues Marks, is not a sufficient condition for outperformance:

All that means is that prices aren’t always fair and mistakes are occurring: some assets are priced too low and some too high.  You still have to be more insightful than others in order to regularly buy more of the former than the latter.  Many of the best bargains at any point in time are found among the things other investors can’t or won’t do.

(Photo by Marijus Auruskevicius)

Marks ends this section by saying that a key turning point in his career was when he concluded that he should focus on relatively inefficient markets.

Important Note:  One area of the stock market that is remarkably inefficient is microcap stocks, especially when compared with midcap or largecap stocks.  See: http://boolefund.com/cheap-solid-microcaps-far-outperform-sp-500/

A few comments about deep value investing:

In order to buy a stock that is very cheap in relation to its intrinsic value, some other investor must be willing to sell the stock at such an irrationally low price.  Sometimes such sales happen due to forced selling.  The rest of the time, the seller must be making a mistake in order for the value investor to make a market-beating investment.

And yet many deep value approaches are fully quantitative, relying on statistical rules for stock selection.  The quantitative deep value investor does not typically make a detailed judgment on each individual stock—a judgment which would imply that the buyer is correct and the seller is incorrect in the individual case.  Rather, the quantitative deep value investor forms a portfolio of the statistically cheapest stocks.  All of the studies have shown that a basket of quantitatively cheap stocks does better than the market over time, and is less risky (especially during down markets).

Blog post on quantitative deep value investing: http://boolefund.com/quantitative-deep-value-investing/

A concentrated deep value approach, by contrast, involves the effort to select the most promising and the cheapest individual stocks available.  Warren Buffett and Charlie Munger—both inspired in part by Philip Fisher—followed this approach when they were managing smaller amounts of capital.  They would usually have between 3 and 8 positions making up nearly the entire portfolio.

 

VALUE

Marks begins by saying that “buy low; sell high” is one of the oldest rules in investing.  But since selling will occur in the future, how can you figure out a price today that will be lower than some future price?  What’s needed is an ability to accurately assess the intrinsic value of the asset.  The intrinsic value of a stock can be derived from the price that an informed buyer would pay for the entire company, based on net asset value or normalized earnings.  Writes Marks:

The quest in value investing is for cheapness.  Value investors typically look at financial metrics such as earnings, cash flow, dividends, hard assets and enterprise value and emphasize buying cheap on these bases.  The primary goal of value investors, then, is to quantify the company’s current value and buy its securities when they can do so cheaply.

(Photo by Farang)

Marks notes that a successful value investment requires a non-consensus view on net asset value or normalized earnings.  Successful growth investing, by contrast, requires a non-consensus view on future earnings (based on growth).  Sometimes the rewards for growth investing are higher, but a value investing approach is much more repeatable and achievable.

Buying assets below fair value, however, does not mean those assets will outperform right away.  Value investing requires having a firmly held view because quite often after buying, cheap assets will continue to underperform the market.  Marks elaborates:

If you liked it at 60, you should like it more at 50… and much more at 40 and 30.  But it’s not that easy.  No one’s comfortable with losses, and eventually any human will wonder, ‘Maybe it’s not me who’s right.  Maybe it’s the market.’…

Thus, successful value investing requires not only the consistent ability to identify assets available at cheap prices; it also requires the ability to ignore various signals (many of which are subconscious) flashing the message that one is wrong.  As Marks writes:

Value investors score their biggest gains when they buy an underpriced asset, average down unfailingly and have their analysis proved out.  Thus, there are two essential ingredients for profit in a declining market: you have to have a view on intrinsic value, and you have to hold that view strongly enough to be able to hang in and buy even as price declines suggest that you’re wrong.  Oh yes, there’s a third: you have to be right.

 

THE RELATIONSHIP BETWEEN PRICE AND VALUE

Many investors make the mistake of thinking that a good company is automatically a good investment, while a bad company is automatically a bad investment.  But what really matters for the value investor is the relationship between price and value:

For a value investor, price has to be the starting point.  It has been demonstrated time and time again that no asset is so good that it can’t become a bad investment if bought at too high a price.  And there are few assets so bad that they can’t be a good investment when bought cheaply enough.

In the 1960’s, there was a group of stocks called the Nifty Fifty—companies that were viewed as being so good that all you had to do was buy at any price and then hold for the long term.  But it turned out not to be true for many stocks in the basket.  Moreover, the early 1970’s led to huge declines:

Within a few years, those price/earnings ratios of 80 or 90 had fallen to 8 or 9, meaning investors in America’s best companies had lost 90 percent of their money.  People may have bought into great companies, but they paid the wrong price.

Marks explains the policy at his firm Oaktree:

‘Well bought is half sold.’  By this we mean we don’t spend a lot of time thinking about what price we’re going to be able to sell a holding for, or to whom, or through what mechanism.  If you’ve bought it cheap, eventually those questions will answer themselves.  If your estimate of intrinsic value is correct, over time an asset’s price should converge with its value.

Marks, similar to Buffett and Munger, holds that psychology plays a central role in value investing:

Whereas the key to ascertaining value is skilled financial analysis, the key to understanding the price/value relationship—and the outlook for it—lies largely in insight into other investor’s minds.  Investor psychology can cause a security to be priced just about anywhere in the short run, regardless of its fundamentals.  

The safest and most potentially profitable thing is to buy something when no one likes it.  Given time, its popularity, and thus its price, can only go one way: up.

A successful value investor must build systems or rules for self-protection because all investors—all humans—suffer from cognitive biases, which often operate subconsciously.

(Illustration by Alain Lacroix)

Marks again on the importance of cheapness:

Of all the possible routes to investment profit, buying cheap is clearly the most reliable.  Even that, however, isn’t sure to work.  You can be wrong about the current value.  Or events can come along that reduce value.  Or deterioration in attitudes or markets can make something sell even further below its value.  Or the convergence of price and intrinsic value can take more time than you have…

Trying to buy below value isn’t infallible, but it’s the best chance we have.

 

UNDERSTANDING RISK

As Buffett frequently observes, the future is always uncertain.  Prices far below probable intrinsic value usually only exist when the future is highly uncertain.  When there is not much uncertainty, asset prices will be much higher than otherwise.  So high uncertainty about the future is the friend of the value investor.

(Photo by Alain Lacroix)

On the other hand, in general, assets that promise higher returns entail higher risk.  If a potentially higher-returning asset was obviously as low risk as a U.S. Treasury, then investors would rush to buy the higher-returning asset, thereby pushing up its price to the point where it would promise returns on par with a U.S. Treasury.

A successful value investor has to determine whether the potential return on an ostensibly cheap asset is worth the risk.  High risk is not necessarily bad as long as it is properly controlled and as long as the potential return is high enough.  But if the risk is too high, then it’s not the type of repeatable bet that can produce long-term success for a value investor.  Repeatedly taking too much risk virtually guarantees long-term failure.

Consider the Kelly criterion.  If the probability of success and the returns from a potential investment can be quantified, then the Kelly criterion tells you exactly how much to bet in order to maximize the long-term compound returns from a long series of such bets.  Betting any other amount than what the Kelly criterion says will inevitably lead to less than the maximum potential returns.  Most importantly, betting more than what the Kelly criterion says guarantees negative long-term returns.  Repeatedly overbetting guarantees long-term failure.

This is part of why Howard Marks, Warren Buffett, Charlie Munger, Seth Klarman and other great value investors often point out that minimizing big mistakes is more important for long-term success in investing than hitting home runs.

Again, while riskier investments promise higher returns, those higher returns are not guaranteed, otherwise riskier investments wouldn’t be riskier!  The probability distribution of potential returns is wider for riskier investments, typically including some large potential losses.  A certain percentage of future outcomes will be negative for riskier investments.

(Photo by Wittayayut Seethong)

Marks agrees with Buffett and Munger that the best definition of risk is the potential to experience loss.

Of course, even the best investors are generally right only two-thirds of the time, while they are wrong one-third of the time.  Thus, following a successful long-term value investing framework where you consistently and carefully pays cheap prices for assets still entails being wrong once every three tries, whether due to a mistake, bad luck, or unforeseen events.

More Notes on Deep Value

Investors are systematically too pessimistic about companies that have been doing poorly, and systematically too optimistic about companies that have been doing well.  This is why a deep value approach, if applied systematically, is very likely to produce market-beating returns over a long enough period of time.

Marks explains:

Dull, ignored, possibly tarnished and beaten-down securities—often bargains exactly because they haven’t been performing well—are often ones value investors favor for high returns…. Much of the time, the greatest risk in these low-luster bargains lies in the possibility of underperforming in heated bull markets.  That’s something the risk-conscious value investor is willing to live with.

Measuring Risk-Adjusted Returns

Marks mentions the Sharpe ratio—or excess return compared to the standard deviation of the return.  While far from perfect, the Sharpe ratio is a solid measure of risk-adjusted return for many public market securities.

It’s important to point out again that risk can no more be objectively measured after an investment than it can be objectively measured before the investment.  Marks:

The point is that even after an investment has been closed out, it’s impossible to tell how much risk it entailed.  Certainly the fact that an investment worked doesn’t mean it wasn’t risky, and vice versa.  With regard to a successful investment, where do you look to learn whether the favorable outcome was inescapable or just one of a hundred possibilities (many of them unpleasant)?  And ditto for a loser: how do we ascertain whether it was a reasonable but ill-fated venture, or just a wild stab that deserved to be punished?

Did the investor do a good job of assessing the risk entailed?  That’s another good question that’s hard to answer.  Need a model?  Think of the weatherman.  He says there’s a 70 percent chance of rain tomorrow.  It rains; was he right or wrong?  Or it doesn’t rain; was he right or wrong?  It’s impossible to assess the accuracy of probability estimates other than 0 and 100 except over a very large number of trials.

Marks believes (as do Buffett, Munger, and other top value investors) that there is some merit to the expected value framework whereby you attempt to identify possible future scenarios and the probabilities of their occurrence:

If we have a sense for the future, we’ll be able to say which outcome is most likely, what other outcomes also have a good chance of occurring, how broad the range of possible outcomes is and thus what the ‘expected result’ is.  The expected result is calculated by weighing each outcome by its probability of occurring; it’s a figure that says a lot—but not everything—about the likely future.

Again, though, having a reasonable estimate of the future probability distribution is not enough.  You must also make sure that your portfolio can withstand a run of bad luck; and you must recognize when you have experienced a run of good luck.  Marks quotes his friend Bruce Newberg (with whom he has played cards and dice): “There’s a big difference between probability and outcome.  Probable things fail to happen—and improbable things happen—all the time.”  This is one of the most important lessons to know about investing, asserts Marks.

(via Wikimedia Commons)

Marks defines investment performance in the context of risk:

… investment performance is what happens when a set of developments—geopolitical, macro-economic, company-level, technical and psychological—collide with an extant portfolio.  Many futures are possible, to paraphrase Dimson, but only one future occurs.  The future you get may be beneficial to your portfolio or harmful, and that may be attributable to your foresight, prudence or luck.  The performance of your portfolio under the one scenario that unfolds says nothing about how it would have fared under the many ‘alternative histories’ that were possible.

A portfolio can be set up to withstand 99 percent of all scenarios but succumb because it’s the remaining 1 percent that materializes.  Based on the outcome, it may seem to have been risky, whereas the investor might have been quite cautious.

Another portfolio may be structured so that it will do very well in half the scenarios and very poorly in the other half.  But if the desired environment materializes and it prospers, onlookers can conclude that it was a low-risk portfolio.

The success of a third portfolio can be entirely contingent on one oddball development, but if it occurs, wild aggression can be mistaken for conservatism and foresight.

It’s tough to quantify risk without a large number of repeated trials under similar circumstances.  Marks:

Risk can be judged only by sophisticated, experienced second-level thinkers.

The past seems very definite: for every evolving set of possible scenarios, only one scenario happened at each point along the way.  But that does not at all mean that the scenarios that actually occurred were the only scenarios that could have occurred.

Furthermore, most people assume that the future will be like the past, especially the more recent past.  As Ray Dalio suggests, the biggest mistake most investors make is to assume that the recent past will continue into the future.

Marks also reminds us that the “worst-case” assumed by most investors is typically not negative enough.  Marks relates a funny story his father told about a gambler who bet everything on a race with only one horse in it.  How could he lose?  “Halfway around the track, the horse jumped over the fence and ran away.  Invariably things can get worse than people expect.”  Taking more risk usually leads to higher returns, but not always.  “And when risk bearing doesn’t work, it really doesn’t work, and people are reminded what risk’s all about.”

 

RECOGNIZING RISK

(Photo by Shawn Hempel)

The main source of risk, argues Marks, is high prices.  When stock prices move higher, for instance, most investors feel more optimistic and less concerned about downside risk.  But value investors have the opposite point of view: risk is typically very low when stock prices are very low, while risk tends to increase significantly when stock prices have increased significantly.

Most investors are not value investors:

So a prime element in risk creation is a belief that risk is low, perhaps even gone altogether.  That belief drives up prices and leads to the embrace of risky actions despite the lowness of prospective returns.

Marks emphasizes that recognizing risk—which comes primarily from high prices—has nothing to do with predicting the future, which cannot be done with any sort of consistency when it comes to the overall stock market or the economy.

Marks also highlights, again, how the psychology of eager buyers—who are unworried about risk—is precisely what creates greater levels of risk as they drive prices higher:

Thus, the market is not a static arena in which investors operate.  It is responsive, shaped by investors’ own behavior.  Their increasing confidence creates more that they should worry about, just as their rising fear and risk aversion combine to widen risk premiums at the same time as they reduce risk.  I call this the ‘perversity of risk.’

In a nutshell:

When everyone believes something is risky, their unwillingness to buy usually reduces its price to the point where it’s not risky at all.  Broadly negative opinion can make it the least risky thing, since all optimism has been driven out of its price.

And, of course, as demonstrated by the experience of Nifty Fifty investors, when everyone believes something embodies no risk they usually bid it up to the point where it’s enormously risky.  No risk is feared, and thus no reward for risk bearing—no ‘risk premium’—is demanded or provided.  That can make the thing that’s most esteemed the riskiest.

This paradox exists because most investors think quality, as opposed to price, is the determinant of whether something’s risky.  But high quality assets can be risky, and low quality assets can be safe.  It’s just a matter of the price paid for them…

 

CONTROLLING RISK

Outstanding investors, in my opinion, are distinguished at least as much for their ability to control risk as they are for generating return.

Great investors generate high returns with moderate risk, or moderate returns with low risk.  If they generate high returns with “high risk,” but they do so consistently for many years, then perhaps the high risk “either wasn’t really high or was exceptionally well-managed.”  Mark says that great investors such as Buffett or Peter Lynch tend to have very few losing years over a relatively long period of time.

It’s important, notes Marks, to see that risk leads to loss only when lower probability negative scenarios occur:

… loss is what happens when risk meets adversity.  Risk is the potential for loss if things go wrong.  As long as things go well, loss does not arise.  Risk gives rise to loss only when negative events occur in the environment.

We must remember that when the environment is salutary, that is only one of the environments that could have materialized that day (or that year).  (This is Nassim Nicholas Taleb’s idea of alternative histories…)  The fact that the environment wasn’t negative does not mean that it couldn’t have been.  Thus, the fact that the environment wasn’t negative doesn’t mean risk control wasn’t desirable, even though—as things turned out—it wasn’t needed at that time.

The absence of losses does not mean that there was no risk.

(Photo by Michele Lombardo)

Only a skilled investor can look at a portfolio during good times and tell how much risk has been taken.

Bottom line: risk control is invisible in good times but still essential, since good times can so easily turn into bad times.

Marks says that an investment manager adds value by generating higher than market returns for a given level of risk.  Achieving the same return as the market, but with less risk, is adding value.  Achieving better than market returns without undue risk is also adding value.

Many value investors, such as Marks and Buffett, somewhat underperform during up markets, but far outperform during down markets.  The net result over a long period of time is market-beating performance with very little incremental risk.  But it does take some time in order to see the value added.

Controlling the risk in your portfolio is a very important and worthwhile pursuit.  The fruits, however, come only in the form of losses that don’t happen.  Such what-if calculations are difficult in placid times.

On the other hand, the intelligent acceptance of recognized risk for profit underlies some of the wisest, most profitable investments—even though (or perhaps due to the fact that) most investors dismiss them as dangerous speculations.

Marks’ firm Oaktree invests in high yield bonds.  High yield bonds can be good investments over time if the prices are low enough:

I’ve said for years that risky assets can make for good investments if they’re cheap enough.  The essential element is knowing when that’s the case.  That’s it: the intelligent bearing of risk for profit, the best test for which is a record of repeated success over a long period of time.

Risk bearing per se is neither wise nor unwise, says Marks.  Investing in the more aggressive niches with risk properly controlled is ideal.  But controlling risk always entails being prepared for bad scenarios.

Extreme volatility and loss surface only infrequently.  And as time passes without that happening, it appears more and more likely that it’ll never happen—that assumptions regarding risk were too conservative.  Thus, it becomes tempting to relax rules and increase leverage.  And often this is done just before the risk finally rears its head…

Marks quotes Nassim Taleb:

Reality is far more vicious than Russian roulette.  First, it delivers the fatal bullet rather infrequently, like a revolver that would have hundreds, even thousands of chambers instead of six.  After a few dozen tries, one forgets about the existence of the bullet, under a numbing false sense of security… Second, unlike a well-defined precise game like Russian roulette, where the risks are visible to anyone capable of multiplying and dividing by six, one does not observe the barrel of reality… One is thus capable of unwittingly playing Russian roulette—and calling it by some alternative ‘low risk’ name.

A good example, which Marks does mention, is large financial institutions in 2004-2007.  Virtually no one thought that home prices could decline on a nationwide scale, since they had never done so before.

Of course, it’s also possible to be too conservative.

You can’t run a business on the basis of worst-case assumptions.  You wouldn’t be able to do anything.  And anyway, a ‘worst-case assumption’ is really a misnomer; there’s no such thing, short of a total loss.  Now, we know the quants shouldn’t have assumed there couldn’t be a nationwide decline in home prices.  But once you grant that such a decline can happen… what should you prepare for?  Two percent?  Ten?  Fifty?

(Photo by Donfiore)

Marks continues:

If every portfolio was required to be able to withstand declines on the scale we’ve witnessed this year [2008], it’s possible no leverage would ever be used.  Is that a reasonable reaction?

Even if we realize that unusual, unlikely things can happen, in order to act we make reasoned decisions and knowingly accept that risk when well paid to do so.  Once in a while, a ‘black swan’ will materialize.  But if in the future we always said, ‘We can’t do such-and-such, because the outcome could be worse than we’ve ever seen before,’ we’d be frozen in inaction.

Marks sums it up:

… It’s by bearing risk when we’re well paid to do so—and especially by taking risks toward which others are averse in the extreme—that we strive to add value for our clients.

 

BEING ATTENTIVE TO CYCLES

  • Rule number one: most things will prove to be cyclical.
  • Rule number two: some of the greatest opportunities for gain and loss come when other people forget rule number one.

Marks explains:

… processes in fields like history and economics involve people, and when people are involved, the results are variable and cyclical.  The main reason for this, I think, is that people are emotional and inconsistent, not steady and clinical.

Objective factors do play a large part in cycles, of course—factors such as quantitative relationships, world events, environmental changes, technological developments and corporate decisions.  But it’s the application of psychology to these things that causes investors to overreact or underreact, and thus determines the amplitude of the cyclical fluctuations.

(Image by Anhluong.tdnb, via Wikimedia Commons)

Because people inevitably overreact or underreact, both business activity and stock prices overshoot on the upside and on the downside:

Economies will wax and wane as consumers spend more or less, responding emotionally to economic factors or exogenous events, geopolitical or naturally occurring.  Companies will anticipate a rosy future during the up cycle and thus overexpand facilities and inventories; these will become burdensome when the economy turns down.  Providers of capital will be too generous when the economy’s doing well, abetting overexpansion with cheap money, and then they’ll pull the reins too tight when things cease to look as good.  Investors will overvalue companies when they’re doing well and undervalue them when things get difficult.

 

AWARENESS OF THE PENDULUM

Marks holds that there are two risks in investing:

  • the risk of losing money
  • the risk of missing opportunity

Most investors consistently do the wrong thing at the wrong time:  when prices are high, most investors rush to buy;  when prices are low, most investors rush to sell.  Thus, the value investor can profit over time by following Warren Buffett’s advice:

Be fearful when others are greedy.  Be greedy when others are fearful.

Marks:

Stocks are cheapest when everything looks grim.  The depressing outlook keeps them there, and only a few astute and daring bargain hunters are willing to take new positions.

 

COMBATING NEGATIVE INFLUENCES

(Photo by Nikki Zalewski)

Like Buffett and Munger, Marks believes that temperament, or the ability to master your emotions, is more important than intellect for success in investing:

Many people possess the intellect needed to analyze data, but far fewer are able to look more deeply into things and withstand the powerful influence of psychology.  To say this another way, many people will reach similar cognitive conclusions from their analysis, but what they do with those conclusions varies all over the lot because psychology influences them differently.  The biggest investing errors come not from factors that are informational or analytical, but from those that are psychological.  Investor psychology includes many separate elements, which we will look at in this chapter, but the key thing to remember is that they consistently lead to incorrect decisions.  Much of this falls under the heading of ‘human nature.’

Marks writes about the following psychological tendencies:

  • Greed
  • Fear
  • Self-deception
  • Conformity to the crowd
  • Envy
  • Ego or overconfidence
  • Capitulation

How might these psychological tendencies have been useful in our evolutionary history? 

When food was often scarce, being greedy by hoarding food made sense.  When a movement in the grass frequently meant the presence of a dangerous predator, immediate fear—triggered by the amygdala even before the conscious mind is aware of it—was essential for survival.  When hunting for food was dangerous, often with low odds of success, self-deception—accompanied by various naturally occurring chemicals—helped hunters to persevere over long periods of time, regardless of danger and injury.  (Chemical reactions would cause an injured hunter not to feel much pain.)  If everyone in your tribe was running away as fast as possible, following the crowd was usually the most rational response.  If a starving hunter saw another person with a huge pile of food, envy would trigger a strong desire to possess it.  This would often lead to a hunting expedition with a heightened level of determination.  When hunting a dangerous prey, with low odds of success, ego or overconfidence would cause the hunter to be convinced that he would succeed.  From the point of view of the community, having self-deceiving and overconfident hunters was a net benefit because the hunters would persevere despite difficulties, injuries, and even deaths.

How do these psychological tendencies cause people to make errors in modern activities such as investing?

Greed causes people to follow the crowd by paying high prices for stocks in the hope that there will be even higher prices in the future.  Fear causes people to sell or to avoid ugly stocks—stocks trading at low multiples because the businesses in question are facing major difficulties.

As humans, we have an amazingly strong tendency towards self-deception:

  • The first principle is that you must not fool yourself, and you are the easiest person to fool. – Richard Feynman
  • Nothing is easier than self-deceit. For what each man wishes, that he also believes to be true. – Demosthenes, as quoted by Charlie Munger

There have been many times in history when self-deception was probably crucial for the survival of a given individual or community.  I’ve mentioned hunters pursuing dangerous prey.  A much more recent example might be Winston Churchill, who was firmly convinced—even when virtually all the evidence was against it—that England would defeat Germany in World War II.  Churchill’s absolute belief helped sustain England long enough for both good luck and aid to arrive:  the Germans ended up overextended in Russia, and huge numbers of American troops (along with mass amounts of equipment) arrived in England.

Thus, like other psychological tendencies, self-deception often plays a constructive role.  However, when it comes to investing, self-deception is generally harmful, especially as the time horizon is extended so that luck virtually disappears.

Conformity to the crowd is another psychological tendency that many (if not most) investors seem to display.  Marks notes the famous experiment by Solomon Asch.  The subject is shown lines of obviously different lengths.  But in the same room with the subject are shills, who unbeknownst to the subject have already been instructed to say that two lines of obviously different lengths actually have the same length.  So the subject of the experiment has to decide between the obvious evidence of his eyes—the two lines are clearly different lengths—and the opinion of the crowd.  A significant number (36.8 percent) ignored their own eyes and went with the crowd, saying that the two lines had equal length, despite the obvious fact that they didn’t.

(The experiment involved a control group in which there were no shills.  Almost every subject—over 99 percent—gave the correct answer under these circumstances.)

Greed, conformity, and envy together operate powerfully on the brains of many investors:

Time and time again, the combination of pressure to conform and the desire to get rich causes people to drop their independence and skepticism, overcome their innate risk aversion and believe things that don’t make sense.

A good example from history is the tulip mania in Holland, during which otherwise rational people ended up paying exorbitant sums for colorful tulip bulbs.  See: https://en.wikipedia.org/wiki/Tulip_mania

At the peak of tulip mania, in March 1637, some single tulip bulbs sold for more than 10 times the annual income of a skilled craftsman.

The South Sea Bubble is another example, during which even the extremely intelligent Isaac Newton, after selling out early for a solid profit, could not resist buying in again as prices seemed headed for the stratosphere.  Newton and many others lost huge sums when prices inevitably returned to earth.

Envy may have been useful for hunter-gatherers.  But today envy has a very powerful and often negative effect on most human brains.  And as Charlie Munger always points out, envy is particularly stupid because it’s a sin that, unlike other sins, is no fun at all.  There are many people who could easily learn to be very happy—grateful for blessings, grateful for the wonders of life itself, etc.—who become miserable because they fixate on other people who have more of something, or who are doing better in some way.  Envy is fundamentally irrational and stupid, but it is powerful enough to consume many people.  Buffett: “It’s not greed that drives the world, but envy.”  Envy and jealousy have caused the downfall of human beings for millenia.  This certainly holds true in investing.

Ego and overconfidence are powerful psychological tendencies that humans have.  Overconfidence will kill any investor eventually.  The antidote is humility and objectivity.  Many of the best investors—from Warren Buffett to Ray Dalio—are fundamentally humble and objective.  And women tend to be better investors than men on the whole because women are not as overconfident.  Marks writes:

[Thoughtful] investors can toil in obscurity, achieving solid gains in the good years and losing less than others in the bad years.  They avoid sharing in the riskiest behavior because they’re so aware of how much they don’t know and because they have their egos in check.  This, in my opinion, is the greatest formula for long-term wealth creation—but it doesn’t provide much ego gratification in the short run.  It’s just not that glamorous to follow a path that emphasizes humility, prudence, and risk control.  Of course, investing shouldn’t be about glamour, but often it is.

Capitulation is a final phenomenon that Marks emphasizes.  In general, people become overly negative about a stock that is deeply out of favor because the business in question is going through hard times.  Moreover, when overly negative investors are filled with fear and when they see everyone selling in a panic, they themselves often sell near the very bottom.  Often these investors know analytically that the stock is cheap, but their emotions (fear of loss, conformity to the crowd, etc.) are too strong, so they disbelieve their own sound logic.  The rational, contrarian, long-term value investor does just the opposite:  he or she buys near the point of maximum pessimism (to use John Templeton’s phrase).

Similarly, most investors become overly optimistic when a stock is near its all-time highs.  They see many other investors who have done well with the sky-high stock, and so they tend to buy at a price that is near the all-time highs.  Again, many of these investors—like Isaac Newton—know analytically that buying a stock when it is near its all-time highs is often not a good idea.  But greed, envy, self-deception, crowd conformity, etc. (fear of missing out, dream of a sure thing), overwhelm their own sound logic.  By contrast, the rational, long-term value investor does the opposite:  he or she sells near the point of maximum optimism.

Marks gives a marvelous example of psychological excess from the tech bubble of 1998-2000:

From the perspective of psychology, what was happening with IPOs is particularly fascinating.  It went something like this: The guy next to you in the office tells you about an IPO he’s buying.  You ask what the company does.  He says he doesn’t know, but his broker told him it’s going to double on the day of issue.  So you say that’s ridiculous.  A week later he tells you it didn’t double… it tripled.  And he still doesn’t know what it does.  After a few more of these, it gets hard to resist.  You know it doesn’t make sense, but you want protection against continuing to feel like an idiot.  So, in a prime example of capitulation, you put in for a few hundred shares of the next IPO… and the bonfire grows still higher on the buying from new converts like you.

 

CONTRARIANISM

(Illustration by Sasinparaksa)

Sir John Templeton:

To buy when others are despondently selling and to sell when others are euphorically buying takes the greatest courage, but provides the greatest profit.

Superior value investors buy when others are selling, and sell when others are buying.  Value investing is simple in concept, but it is very difficult in practice.

Of course, it’s not enough just to be contrarian.  Your facts and your reasoning also have to be right, as Buffett points out:

You’re neither right nor wrong because the crowd disagrees with you.  You’re right because your data and reasoning are right—and that’s the only thing that makes you right.  And if your facts and reasoning are right, you don’t have to worry about anybody else.

Only by being right about the facts and the reasoning can a long-term value investor hold (or add to) a position when everyone else continues to sell.  Getting the facts and reasoning right still involves being wrong roughly one-third of the time, whether due to bad luck, unforeseen events, or a mistake.  But getting the facts and reasoning right leads to ‘being right’ roughly two-third of the time.

A robust process correctly followed should produce positive results—on both an absolute and relative basis—over most rolling five-year periods, and over nearly all rolling ten-year periods.

It’s never easy to consistently follow a careful, contrarian value investing approach.  Marks quotes David Swensen:

Investment success requires sticking with positions made uncomfortable by their variance with popular opinion… Only with the confidence created by a strong decision-making process can investors sell speculative excess and buy despair-driven value.

… Establishing and maintaining an unconventional investment profile requires acceptance of uncomfortably idiosyncratic portfolios, which frequently appear downright imprudent in the eyes of conventional wisdom.

Marks puts it in his own words:

The ultimately most profitable investment actions are by definition contrarian:  you’re buying when everyone else is selling (and the price is thus low) or you’re selling when everyone else is buying (and the price is high).  These actions are lonely and… uncomfortable.

(Illustration by Sangoiri)

Marks writes about the paradoxical nature of investing:

The thing I find most interesting about investing is how paradoxical it is: how often the things that seem most obvious—on which everyone agrees—turn out not to be true.

The best bargains are typically only available when pessimism and uncertainty are high.  Many investors say, ‘We’re not going to try to catch a falling knife; it’s too dangerous… We’re going to wait until the dust settles and the uncertainty is resolved.’  But waiting until uncertainty gets resolved usually means missing the best bargains, as Marks says:

The one thing I’m sure of is that by the time the knife has stopped falling, the dust has settled and the uncertainty has been resolved, there’ll be no great bargains left.  When buying something has become comfortable again, its price will no longer be so low that it’s a great bargain.  Thus, a hugely profitable investment that doesn’t begin with discomfort is usually an oxymoron.

It’s our job as contrarians to catch falling knives, hopefully with care and skill.  That’s why the concept of intrinsic value is so important.  If we hold a view of value that enables us to buy when everyone else is selling—and if our view turns out to be right—that’s the route to the greatest rewards earned with the least risk.

 

FINDING BARGAINS

It cannot be too often repeated:

A high-quality asset can constitute a good or bad buy, and a low-quality asset can constitute a good or bad buy.  The tendency to mistake objective merit for investment opportunity, and the failure to distinguish between good assets and good buys, gets most investors into trouble.

What is the process by which some assets become cheap relative to intrinsic value?  Marks explains:

  • Unlike assets that become the subject of manias, potential bargains usually display some objective defect. An asset class may have weaknesses, a company may be a laggard in its industry, a balance sheet may be over-levered, or a security may afford its holders inadequate structural protection.
  • Since the efficient-market process of setting fair prices requires the involvement of people who are analytical and objective, bargains usually are based on irrationality or incomplete understanding.  Thus, bargains are often created when investors either fail to consider an asset fairly, or fail to look beneath the surface to understand it thoroughly, or fail to overcome some non-value-based tradition, bias or stricture.
  • Unlike market darlings, the orphan asset is ignored or scorned. To the extent it’s mentioned at all by the media and at cocktail parties, it’s in unflattering terms.
  • Usually its price has been falling, making the first-level thinker ask, ‘Who would want to own that?’ (It bears repeating that most investors extrapolate past performance, expecting the continuation of trends rather than the far-more-dependable regression to the mean.  First-level thinkers tend to view price weakness as worrisome, not as a sign that the asset has gotten cheaper.)
  • As a result, a bargain asset tends to be one that’s highly unpopular. Capital stays away from it or flees, and no one can think of a reason to own it.

(Illustration by Chris Dorney)

Where is the best place to look for underpriced assets?  Marks observes that a good place to start is among things that are:

  • little known and not fully understood;
  • fundamentally questionable on the surface;
  • controversial, unseemly or scary;
  • deemed inappropriate for ‘respectable’ portfolios;
  • unappreciated, unpopular and unloved;
  • trailing a record of poor returns; and
  • recently the subject of disinvestment, not accumulation.

Marks puts it briefly:

To boil it all down to just one sentence, I’d say the necessary condition for the existence of bargains is that perception has to be considerably worse than reality.  That means the best opportunities are usually found among things most others won’t do.  After all, if everyone feels good about something and is glad to join in, it won’t be bargain-priced.

Marks started a fund for high yield bonds—junk bondsin 1978.  One rating agency described high yield bonds as “generally lacking the characteristics of a desirable investment.”  Marks remarks:

if nobody owns something, demand for it (and thus the price) can only go up and…. by going from taboo to even just tolerated, it can perform quite well.

In 1987, Marks formed a fund to invest in distressed debt:

Who would invest in companies that already had demonstrated their lack of financial viability and the weakness of their management?  How could anyone invest responsibly in companies in free fall?  Of course, given the way investors behave, whatever asset is considered worst at a given point in time has a good likelihood of being the cheapest.  Investment bargains needn’t have anything to do with high quality.  In fact, things tend to be cheaper if low quality has scared people away.

 

PATIENT OPPORTUNISM

(Illustration by Marek)

Marks makes the same point that Buffett and Munger often make: Most of the time, by far the best thing to do is absolutely nothing.  Finding one good idea a year is enough to get outstanding returns over time.  Marks offers:

So here’s a tip: You’ll do better if you wait for investments to come to you rather than go chasing after them.  You tend to get better buys if you select from the list of things sellers are motivated to sell rather than start with a fixed notion as to what you want to own.  An opportunist buys things because they’re offered at bargain prices.  There’s nothing special about buying when prices aren’t low.

Marks took five courses in Japanese studies as an undergraduate business major in order to fulfill his requirement for a minor.  He learned the Japanese value of mujo:

mujo means cycles will rise and fall, things will come and go, and our environment will change in ways beyond our control.  Thus we must recognize, accept, cope and respond.  Isn’t that the essence of investing?

… What’s past is past and can’t be undone.  It has led to the circumstances we now face.  All we can do is recognize our circumstances for what they are and make the best decisions we can, given the givens.

Marks quotes Buffett, who notes that there are no called strikes in investing:

Investing is the greatest business in the world because you never have to swing.  You stand at the plate; the pitcher throws you General Motors at 47!  U.S. steel at 39!  And nobody calls a strike on you.  There’s no penalty except opportunity.  All day you wait for the pitch you like; then, when the fielders are asleep, you step up and hit it.

It’s dumb to invest when the opportunities are not there.  But when the overall market is high, there are still a few ways to do well as a long-term value investor.  If you are able to ignore short-term volatility and focus on the next five to ten years, then you can probably find some undervalued stocks, especially if you look at microcaps.  At some point—the precise timing of which is unpredictable—there will be a bear market.  But that would create many bargains for the long-term value investor.

 

KNOWING WHAT YOU DON’T KNOW

John Kenneth Galbraith:

We have two classes of forecasters: Those who don’t know—and those who don’t know they don’t know.

Marks, like Buffett, Munger, and most other top value investors, thinks that financial forecasting simply cannot be done with any sort of consistency.  But Marks has two caveats:

The more we concentrate on smaller-picture things, the more it’s possible to gain a knowledge advantage.  With hard work and skill, we can consistently know more than the next person about individual companies and securities, but that’s much less likely with regard to markets and economies.  Thus, I suggest people try to ‘know the knowable.’

An exception comes in the form of my suggestion, on which I elaborate in the next chapter, that investors should make an effort to figure out where they stand at a moment in time in terms of cycles and pendulums.  That won’t render the future twists and turns knowable, but it can help one prepare for likely developments.

Marks has tracked (in a limited way) many macro predictions, including of U.S. interest rates, the U.S. stock market, and the yen/dollar exchange rate.  He found quite clearly that most forecasts were not correct.

(Illustration by Maxim Popov)

I can elaborate on two examples that I spent much time on (when I should have stayed focused on finding individual companies available at cheap prices):

  • shorting the U.S. stock market
  • shorting the Japanese yen

See my detailed discussion of these two “can’t lose” investments here: http://boolefund.com/the-art-value-investing/

Every year, there are many people making financial forecasts, and so purely as a matter of chance, a few forecasters will be correct in a given year.  But the ones correct this year are almost never the ones correct the next time around, because what they’re trying to predict can’t be predicted with any consistency.  Marks writes thus:

I am not going to try to prove my contention that the future is unknowable.  You can’t prove a negative, and that certainly includes this one.  However, I have yet to meet anyone who consistently knows what lies ahead macro-wise…

One way to get to be right sometimes is to always be bullish or always be bearish; if you hold a fixed view long enough, you may be right sooner or later.  And if you’re always an outlier, you’re likely to eventually be applauded for an extremely unconventional forecast that correctly foresaw what no one else did.  But that doesn’t mean your forecasts are regularly of any value…

It’s possible to be right about the macro-future once in a while, but not on a regular basis.  It doesn’t do any good to possess a survey of sixty-four forecasts that includes a few that are accurate; you have to know which ones they are.  And if the accurate forecasts each six months are made by different economists, it’s hard to believe there’s much value in the collective forecasts.

Marks gives one more example: How many predicted the crisis of 2007-2008?  Of those who did predict it—there was bound to be some from pure chance alone—how many of those then predicted the recovery starting in 2009 and continuing until today (mid-2018)?  The answer is “very few.”  The reason, observes Marks, is that those who got 2007-2008 right “did so at least in part because of a tendency toward negative views.”  They probably were negative well before 2007-2008, and more importantly, they probably stayed negative afterwards, during which the U.S. stock market increased (from the lows) roughly 300% as the U.S. economy expanded from 2009 to today (mid-2018).

Marks has a description for investors who believe in the value of forecasts.  They belong to the “I know” school, and it’s easy to identify them:

  • They think knowledge of the future direction of economies, interest rates, markets and widely followed mainstream stocks is essential for investment success.
  • They’re confident it can be achieved.
  • They know they can do it.
  • They’re aware that lots of other people are trying to do it too, but they figure either (a) everyone can be successful at the same time, or (b) only a few can be, but they’re among them.
  • They’re comfortable investing based on their opinions regarding the future.
  • They’re also glad to share their views with others, even though correct forecasts should be of such great value that no one would give them away gratis.
  • They rarely look back to rigorously assess their record as forecasters.

Marks contrasts the confident “I know” folks with the guarded “I don’t know” folks.  The latter believe you can’t predict the macro-future, and thus the proper goal for investing is to do the best possible job analyzing individual securities.  If you belong to the “I don’t know” school, eventually everyone will stop asking you where you think the market’s going.  Marks:

You’ll never get to enjoy that one-in-a-thousand moment when your forecast comes true and the Wall Street Journal runs your picture.  On the other hand, you’ll be spared all those times when forecasts miss the mark, as well as the losses that can result from investing based on overrated knowledge of the future.

Marks continues by noting that no one likes investing on the assumption that the future is unknowable.  But if the future IS largely unknowable, then it’s far better as an investor to acknowledge that fact than to pretend otherwise.

(Photo by Elnur)

Furthermore, says Marks, the biggest problems for investors tend to happen when investors forget the difference between probability and outcome (i.e., the limits of foreknowledge):

  • when they believe the shape of the probability distribution is knowable with certainty (and that they know it),
  • when they assume the most likely outcome is the one that will happen,
  • when they assume the expected result accurately represents the actual result, or
  • perhaps most important, when they ignore the possibility of improbable outcomes.

In a word:

Overestimating what you’re capable of knowing or doing can be extremely dangerous—in brain surgery, transocean racing or investing.  Acknowledging the boundaries of what you can know—and working within those limits rather than venturing beyond—can give you a great advantage.

Or as Warren Buffett has written:

Intelligent investing is not complex, though that is far from saying that it is easy.  What an investor needs is the ability to correctly evaluate selected businesses.  Note that word ‘selected’:  You don’t have to be an expert on every company, or even many.  You only have to be able to evaluate companies within your circle of competence.  The size of that circle is not very important;  knowing its boundaries, however, is vital.

 

HAVING A SENSE FOR WHERE WE STAND

Marks believes that market cycles—inevitable ups and downs—cannot be predicted as to extent and (especially) as to timing, but have a profound influence on us as investors.  The only thing we can predict is that market cycles are inevitable.

Marks holds that as investors, we can have a rough idea of market cycles.  We can’t predict what will happen exactly or when.  But we can at least develop valuable insight into various future events.

So look around, and ask yourself:  Are investors optimistic or pessimistic?  Do the media talking heads say the markets should be piled into or avoided?  Are novel investment schemes readily accepted or dismissed out of hand?  Are securities offerings and fund openings being treated as opportunities to get rich or possible pitfalls?  Has the credit cycle rendered capital readily available or impossible to obtain?  Are price/earnings ratios high or low in the context of history, and are yield spreads tight or generous?  All of these things are important, and yet none of them entails forecasting.  We can make excellent investment decisions on the basis of present observations, with no need to make guesses about the future.

Marks likens the process of assessing the current cycle with “taking the temperature” of the market.  Again, one can never precisely time market turning points, but one can at least become aware of when markets are becoming overheated, or when they’ve become unusually cheap.

(Image by Walta, via Wikimedia Commons)

It may be more difficult today to take the market’s temperature because of the policy of low interest rates in many of the world’s major economies.  This obviously distorts all asset prices.  As Buffett remarked recently, if U.S. rates were going to stay very low for many decades into the future, U.S. stocks would eventually be much higher than they are today.  Zero rates indefinitely would easily mean price/earnings ratios of 50 or more.

If you are able to buy enough cheap stocks, while maintaining a focus on the next five or ten years, and if you are psychologically prepared for the occasional bear market—the precise timing of which is always unpredictable—then you will be in good position.

It can also help if you find cheap stocks that have low or even negative correlation with the broad stock market:

  • Gold mining stocks have often been negatively correlated with the broad market.  The great economist and value investor J. M. Keynes recommended having a gold mining stock—as long as you know the company well—in your portfolio .
  • Oil stocks have low correlation with the broad stock market.  Many oil-related stocks are very cheap today as long as you can hold for at least five years.
  • Cheap turnarounds also have low correlation with the broad stock market.  If the company is turned around, the stock is likely to do well even in a bear market.

 

APPRECIATING THE ROLE OF LUCK

Luck—chance or randomness—influences investment outcomes.  Marks considers Nassim Taleb’s Fooled by Randomness to be essential reading for investors.  Writes Marks:

Randomness (or luck) plays a huge part in life’s results, and outcomes that hinge on random events should be viewed as different from those that do not.

(Albrecht Durer’s Wheel of Fortune from Sebastien Brant’s Ship of Fools (1494) via Wikimedia Commons)

Marks quotes Taleb:

If we have heard of [history’s great generals and inventors], it is simply because they took considerable risks, along with thousands of others, and happened to win.  They were intelligent, courageous, noble (at times), had the highest possible obtainable culture in their day—but so did thousands of others who live in the musty footnotes of history.

A central concept from Taleb is that of “alternative histories.”  What actually has happened in history is merely a small subset of all the things that could have happened, at least as far as we know.  As long as there is a component of indeterminacy in human behavior (not to mention the rest of reality), you must usually assume that many “alternative histories” were possible.

As an investor, given a future that is currently unknowable in many respects, you need to develop a reasonable set of scenarios along with estimated probabilities for each scenario.  And, when judging the quality of past decisions, you should think carefully about various possible histories.  What actually happened is a small subset of what could have happened.

Thus, the fact that a stratagem or action worked—under the circumstances that unfolded—doesn’t necessarily prove that the decision behind it was wise.

Marks says he agrees with all of Taleb’s important points:

  • Investors are right (and wrong) all the time for the ‘wrong reason.’ Someone buys a stock because he or she expects a certain development; it doesn’t occur; the market takes the stock up anyway; the investor looks good (and invariably accepts credit).
  • The correctness of a decision can’t be judged from the outcome.  Nevertheless, that’s how people assess it.  A good decision is one that’s optimal at the time it’s made, when the future is by definition unknown.  Thus, correct decisions are often unsuccessful, and vice versa.
  • Randomness alone can produce just about any outcome in the short run.  In portfolios that are allowed to reflect them fully, market movements can easily swamp the skillfulness of the manager (or lack thereof).  But certainly market movements cannot be credited to the manager (unless he or she is the rare market timer who’s capable of getting it right repeatedly).
  • For these reasons, investors often receive credit they don’t deserve.  One good coup can be enough to build a reputation, but clearly a coup can arise out of randomness alone.  Few of these “geniuses” are right more than once or twice in a row.
  • Thus, it’s essential to have a large number of observations—lots of years of data—before judging a given manager’s ability.

Over the long run, the rational investor learns, refines, and sticks with a robust investment process that reliably produces good results.  In the short run, when a good process sometimes leads to bad outcomes (often due to bad luck but sometimes due to a mistake), you must simply be stoic and patient.

Marks continues:

The actions of the ‘I know’ school are based on a view of a single future that is knowable and conquerable.  My ‘I don’t know’ school thinks of future events in terms of a probability distribution.  That’s a big difference.  In the latter case, we may have an idea which one outcome is most likely to occur, but we also know there are many other possibilities, and those other outcomes may have a collective likelihood much higher than the one we consider most likely.

Marks concludes:

  • We should spend our time trying to find value among the knowable—industries, companies and securities—rather than base our decisions on what we expect from the less-knowable macro world of economies and broad market performance.
  • Given that we don’t know exactly which future will obtain, we have to get value on our side by having a strongly held, analytically derived opinion of it and buying for less when opportunities to do so present themselves.
  • We have to practice defensive investing, since many of the outcomes are likely to go against us. It’s more important to ensure survival under negative outcomes than it is to guarantee maximum returns under favorable ones.
  • To improve our chances of success, we have to emphasize acting contrary to the herd when it’s at extremes, being aggressive when the market is low and cautious when it’s high.
  • Given the highly indeterminate nature of outcomes, we must view strategies and their results—both good and bad—with suspicion until proved over a large number of trials.

 

INVESTING DEFENSIVELY

Unlike professional tennis, where a successful outcome depends on which player hits the most winners, successful investing generally depends on minimizing mistakes more than it does on finding winners.

… investing is full of bad bounces and unanticipated developments, and the dimensions of the court and the height of the net change all the time.  The workings of economies and markets are highly imprecise and variable, and the thinking and behavior of the other players constantly alter the environment.  Even if you do everything right, other investors can ignore your favorite stock;  management can squander the company’s opportunities;  government can change the rules;  or nature can serve up a catastrophe.

Marks argues that successful investing is a balance between offense and defense, and that this balance often differs for each individual investor.  What’s important is to stick with an investment process that works over the long term:

… Few people (if any) have the ability to switch tactics to match market conditions on a timely basis.  So investors should commit to an approach—hopefully one that will serve them through a variety of scenarios.  They can be aggressive, hoping they’ll make a lot on the winners and not give it back on the losers.  They can emphasize defense, hoping to keep up in good times and excel by losing less than others in bad times.  Or they can balance offense and defense, largely giving up on tactical timing but aiming to win through superior security selection in both up and down markets.

Marks continues:

And by the way, there’s no right choice between offense and defense.  Lots of possible routes can bring you to success, and your decision should be a function of your personality and leanings, the extent of your belief in your ability, and the peculiarities of the markets you work in and the clients you work for.

Marks argues that defense can be viewed as aiming for higher returns, but through the avoidance of mistakes and through consistency, rather than through home runs and occasional flashes of brilliancy.

Avoiding losses first involves buying assets at cheap prices (well below intrinsic value).  Another element to avoiding losses is to ensure that your portfolio can survive a bear market.  If the five-year or ten-year returns appear to be high enough, an investor still may choose to play more offense than defense, even when the broad market appears to be high.  But you must be fully prepared—psychologically and in your portfolio—for stocks that are already very cheap to get cut in half or worse during a bear market.

Again, some investors can accept higher volatility in exchange for higher long-term returns.  Know thyself.  You must really think through all the possible scenarios, because things can get much worse than you can imagine during bear markets.  And bear markets are inevitable, though unpredictable.

There is usually a trade-off between potential return and potential downside.  Choosing to aim for higher long-term returns means accepting higher downside volatility over shorter periods of time.

It’s important to keep in mind that many investors fail not due to lack of home runs, but due to having too many strikeouts.  Overbetting—either betting too often (investing in too many different stocks) or betting too much (having position sizes that are too large)—is thus a common cause of failure for long-term investors.  We know from the Kelly criterion that overbetting guarantees negative long-term returns.  Therefore, it’s wise for most investors to aim for consistency—a high batting average based on many singles and doubles—rather than to aim for the maximum number of home runs.

Put differently, it is easier for most investors to minimize losses than it is to hit a lot of home runs.  Thus, most investors are more likely to achieve long-term success by minimizing losses and mistakes, than by hitting a lot of home runs.

As Marks concludes:

Investing defensively can cause you to miss out on things that are hot and get hotter, and it can leave you with your bat on your shoulder in trip after trip to the plate.  You may hit fewer home runs than another investor… but you’re also likely to have fewer strikeouts and fewer inning-ending double plays.

Defensive investing sounds very erudite, but I can simplify it: Invest scared!  Worry about the possibility of loss.  Worry that there’s something you don’t know.  Worry that you can make high-quality decisions but still be hit by bad luck or surprise events.  Investing scared will prevent hubris;  will keep your guard up and your mental adrenaline flowing;  will make you insist on adequate margin of safety;  and will increase the chances that your portfolio is prepared for things going wrong.  And if nothing does go wrong, surely the winners will take care of themselves.

 

BOOLE MICROCAP FUND

An equal weighted group of micro caps generally far outperforms an equal weighted (or cap-weighted) group of larger stocks over time.  See the historical chart here:  http://boolefund.com/best-performers-microcap-stocks/

This outperformance increases significantly by focusing on cheap micro caps.  Performance can be further boosted by isolating cheap microcap companies that show improving fundamentals.  We rank microcap stocks based on these and similar criteria.

There are roughly 10-20 positions in the portfolio.  The size of each position is determined by its rank.  Typically the largest position is 15-20% (at cost), while the average position is 8-10% (at cost).  Positions are held for 3 to 5 years unless a stock approaches intrinsic value sooner or an error has been discovered.

The goal of the Boole Microcap Fund is to outperform the Russell Microcap Index over time, net of fees.  The Boole Fund has low fees.   

 

If you are interested in finding out more, please e-mail me or leave a comment.

My e-mail: jb@boolefund.com

 

 

 

Disclosures: Past performance is not a guarantee or a reliable indicator of future results. All investments contain risk and may lose value. This material is distributed for informational purposes only. Forecasts, estimates, and certain information contained herein should not be considered as investment advice or a recommendation of any particular security, strategy or investment product. Information contained herein has been obtained from sources believed to be reliable, but not guaranteed. No part of this article may be reproduced in any form, or referred to in any other publication, without express written permission of Boole Capital, LLC.