How To Master Yourself As An Investor

(Image:  Zen Buddha Silence by Marilyn Barbone.)

March 12, 2017

James Montier, an expert in behavioral finance, has written several excellent books, including The Little Book of Behavioral Investing: How Not to Be Your Own Worst Enemy (Wiley, 2010).

Montier begins with a quote from the father of value investing, Ben Graham, who clearly understood (decades before behavioral finance was invented) that overcoming your own emotions is often the greatest challenge for an investor:

The investor’s how to write career objective for phd allusion essay example follow link population trends in china essay combien coute le cialis en belgique best college analysis essay topic gtc bio viagra follow link how to write good personal narrative essays pergotime clomid and twins here buy generic cialis without credit cards bits dissertation report sample levitra cancer prostata i have had an easy life nursing essay order coursework online go to site cheap descriptive essay proofreading service usa cialis england kaufen apa 6th edition unpublished doctoral dissertation cialis gegen vorzeitigen samenerguss euthanasia is always wrong essay diverse student body essay can bystolic casue erectile dysfunction chief problem – and even his worst enemy – is likely to be himself.

The problem, as Daniel Kahneman observes in his great book Thinking, Fast and Slow, is that we can easily recognize cognitive errors in others, but not in ourselves.  Yet we all suffer from cognitive biases.

If you can learn to recognize when your brain may make a cognitive error and if you can learn systems to overcome that, then you can do much better as an investor.  Here are three systems that can help you to minimize the impact of cognitive biases in order to maximize your long-term investment results:

  • Invest in low-cost broad market index funds. If you do this, then you’ll do better than 90% of all investors after several decades.  Also, this approach takes very little time to implement and maintain.
  • Invest in a quantitative value fund (or in several such funds). This is a fund that automatically buys the statistically cheapest stocks, year in and year out.  If done properly, this approach should do better than broad market index funds over time.  One of the most successful quantitative value investors is LSV Asset Management.  See:
  • Do value investing on your own. If you really enjoy learning about various businesses and if you enjoy the process of value investing, then with the right systems, you can learn to do well over time.  As an individual investor, you can look at tiny stocks overlooked by most professionals.  Also, you can easily concentrate your portfolio if you happen to come across any extremely cheap stocks.  (A young Warren Buffett once put his entire personal portfolio into one stock: GEICO.)

Note that the first two systems involve fully automated investing, which drastically reduces the number of decisions you make and therefore almost entirely removes the possibility of cognitive error.  The vast majority of investors are much better off using a fully automated approach, whether index funds or quantitative value funds.

(There are some actively managed value funds whose managers possess great skill, but usually it’s not possible for an ordinary investor to invest with them.  Also, many of these funds have gotten quite large, so performance over the next decade or two will likely be noticeably lower.)



It is now broadly recognized that there are two different systems operating in the human brain:

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.

As Daniel Kahneman points out (see Thinking, Fast and Slow), System 1 is amazingly good at what it does.  Its models of familiar situations are accurate.  Its short-term predictions are usually accurate.  And its initial reactions to challenges are swift and generally appropriate.  System 1 does all of these things automatically, and without needing any help from System 2.

The problem is that there are some situations in modern life – especially if a good decision requires the proper use of logic or statistics – where System 1 suffers from cognitive biases, causing systematic errors.  Most people, even if highly educated, rely largely on System 1.

System 2 can be trained over time to do logic, math, and statistics.  But in the presence of high levels of stress or fatigue, System 2 can easily be derailed or not activated at all.  Self-aware people recognize this, and can learn countermeasures such as meditation (which can dramatically reduce stress) or postponing important decisions (if possible).

To show how most people rely on System 1, even for math and logic, Montier describes the Cognitive Reflection Test (CRT), invented by Shane Frederick.

If you’re reading this, try answering these three questions:

  1. A bat and a ball together cost $1.10 in total. The bat costs a dollar more than the ball.  How much does the ball cost?
  2. If it takes five minutes for five machines to make five widgets, how long would it take 100 machines to make 100 widgets?
  3. In a lake there is a patch of lily pads. Every day the patch doubles in size.  If it takes 48 days for the patch to cover the entire lake, how long will it take to cover half the lake?

Montier writes that only 17% out of 3,500 people tested by Frederick got all three questions right.  33% got none right!  Even among the best performing group – MIT students – only 48% managed to get all three right.

Montier gave the CRT to 600 professional investors.  Only 40% got all three right.  10% didn’t get any right.

Not doing well on the CRT is correlated with many behavioral errors, says Montier.  Doing well in investing is more about temperament and rationality than it is about IQ.  Montier quotes Buffett:

Success in investing doesn’t correlate with IQ once you’re above the level of 125.  Once you have ordinary intelligence, what you need is the temperament to control the urges that get other people into trouble in investing.

It takes years of work to improve as an investor.  But the great thing is that you can improve at investing your entire life.  All the knowledge and experience is cumulative, as Buffett says.



The empathy gap is our inability to predict how we will behave while under emotional strain.  In the world of investing, many react emotionally to negative news or to falling stock prices, which leads to poor decisions.

In order to prevent ourselves from making poor decisions, we need to pre-commit to a plan, or (even better) follow a fully automated investment strategy.

Sir John Templeton explains how to do well as an investor:

The time of maximum pessimism is the best time to buy, and the time of maximum optimism is the best time to sell.

To do this consistently, we need to pre-commit to a plan or use fully automated investing.  System 1 reacts to dropping prices with fear and loss aversion.  Fear causes people to ignore great bargains when stock prices are plummeting.  And fearful people become even more fearful if they have already suffered from losses.  Many investors just say, ‘Get me out of the market [or the stock] at any price’ in order to relieve their pain.  But what they should be doing is buying (or holding) the cheapest stocks available.

In order to overcome his own cognitive biases, John Templeton pre-committed to buying cheap stocks during a bear market: he placed buy orders for many stocks well below their current prices.

Typically during a bear market, the investors who have large cash positions fail to invest until after they’ve already missed much of the market recovery.  Again, only by having pre-committed to a battle plan before a bear market can you increase the odds of buying when you should be buying – when stocks are cheap.  As Jeremy Grantham wrote (quoted by Montier):

There is only one cure for terminal paralysis: you absolutely must have a battle plan for reinvestment and stick to it.  Since every action must overcome paralysis, what I recommend is a few large steps, not many small ones….

It is particularly important to have a clear definition of what it will take for you to be fully invested.  Without a similar program, be prepared for your committee’s enthusiasm to invest (and your own for that matter) to fall with the market.  You must get them to agree now – quickly before rigor mortis sets in… Finally, be aware that the market does not turn when it sees light at the end of the tunnel.  It turns when all looks black, but just a subtle shade less black than the day before.

The legendary value investor Seth Klarman describes a bear market as follows (quoted by Montier):

The chaos is so extreme, the panic selling so urgent, that there is almost no possibility that sellers are acting on superior information; indeed, in situation after situation, it seems clear that investment fundamentals do not factor into their decision making at all… While it is always tempting to try and time the market and wait for the bottom to be reached (as if it would be obvious when it arrived), such a strategy proved over the years to be deeply flawed.  Historically, little volume transacts at the bottom or on the way back up and competition from other buyers will be much greater when the markets settle down and the economy begins to recover.  Moreover, the price recovery from a bottom can be very swift.  Therefore, an investor should put money to work amidst the throes of a bear market, appreciating that things will likely get worse before they get better.

So a battle plan for reinvestment is a “schedule of pre-commitments” that can help you overcome the fear induced by plummeting prices.  Such a plan will require that you buy stocks when they are cheap.  Such a plan will require that you average down when stocks continue to get cheaper.

Although this discussion has focused mostly on a broad market sell-off, sometimes there are sell-offs (for non-fundamental, short-term reasons) in particular industries or in individual stocks.  In these cases, too, having a battle plan can help you to ignore the crowd – which often is focused only on the short term – and buy the stocks that are likely the cheapest based on long-term fundamentals.



The majority of drivers say they are above average.  Most students say they will finish in the top half of their class.  Indeed, overconfidence is the pattern for nearly all human activities.  Montier asked 600 professional fund managers how many were above average, and 74% said they were.

Earlier I mentioned Shane Frederick’s CRT test.  People who ace that test tend to suffer from fewer cognitive biases.  However, this does not apply to overconfidence, which is a deep-seated and very wide-spread cognitive bias.  Nearly everyone suffers from overconfidence, although some people learn to tame it.

The trouble is that knowing a great deal about overconfidence does not remove the bias.  Daniel Kahneman, one of the best psychologists, especially when it comes to cognitive biases such as overconfidence, admits that he himself is still “wildly overconfident” as a default setting.  Unless there is a serious threat – a possible predator in the grass – our System 1 automatically makes us feel at ease and overconfident about nearly everything.

Now, in most spheres of human activity, overconfidence and optimism are actually good things.  Overconfident and optimistic people deal with problems better, are happier, and live longer.  Perhaps we developed overconfidence a long time ago when hunting.  Fearless hunters were generally better hunters.

The problem is that in fields (like investing) that require the proper use of logic or statistics, overconfidence leads to poor decisions and often disasters.

There are several ways that we can overcome overconfidence.  Committing to a fully automated approach to investing is the best way to minimize all cognitive biases.

  • Buying and holding a low-cost broad market index fund will allow you to do better than 90% of all investors over several decades.
  • A quantitative value strategy can be even better than an index fund. Such an approach automatically buys the statistically cheapest stocks.

If you want to do value investing yourself because you enjoy it, then using a checklist and other specific processes can greatly improve your results over time.  Guy Spier has outstanding discussions of systems and processes in The Education of a Value Investor.  See:

Montier also mentions some good questions you should ask if you’re doing value investing for yourself.  “Must I believe this?” is a better question than “Can I believe this?”  In other words, what would invalidate the investment hypothesis?

It’s important to understand that System 1 automatically looks for confirming evidence for all of its views.  Even more importantly, System 2 uses a positive test strategy, which means that System 2 also looks for confirming evidence rather than disconfirming evidence.

Yet we know that the advance of science depends directly on the search for disconfirming evidence.  Charles Darwin, for instance, trained himself always to look for disconfirming evidence.  In this careful, painstaking manner, Darwin, though not at all brilliant, was eventually able to produce some of the finest mental work ever done.  The bottom line for investors is simple:

Always look for disconfirming evidence rather than for confirming evidence.

Many of the best value investors have developed the habit of always looking for disconfirming evidence.  If you look the investment management firms run by Seth Klarman, Richard Pzena, and Ray Dalio – to give just a few examples out of many – there are processes in place to ensure that disconfirming evidence is ALWAYS sought.  For instance, if one analyst is responsible for the bullish case on a stock, another analyst will be assigned to argue the bearish case.  Investors who have a deeply ingrained process of searching for disconfirming evidence have generally enjoyed a boost to their long-term performance as a result.

Montier also writes that “Why should I own this investment?” is a better question than “Why shouldn’t I own this investment?”  The default should be non-ownership until the investment hypothesis has been formed and tested.  One major reason Buffett and Munger are among the very best investors is because of their extreme discipline and patience.  They are super selective, willing to pass on a hundred possibilities in order to find the one investment that is the most supported by the evidence.  (This was even more true when they were managing less capital.  These days, they have so much capital – as a result of their great successes over time – that they have to overlook many of the best opportunities, which involve companies too tiny to move the needle at Berkshire Hathaway.)



By nature, we tend to like people who sound confident.  Financial commentators typically sound very confident on TV.  But when it comes to financial forecasting, no one can do it well.  Some forecasters will be right on occasion, but you never know ahead of time who that will be.  And six months from now, some other forecasters – different ones – will be right.

The best thing, as strongly advised by many top investors including Warren Buffett, is to ignore all financial forecasts.  Either stick with a fully automated investment program – whether index fund or quantitative value – or stay focused on individual companies if you’re doing value investing for yourself.

If you’re doing value investing yourself, then even when the broader market is overvalued, you can usually find tiny companies that are extremely cheap.  Most professional investors never look at microcap stocks, which is why it’s usually the best place to look for the cheapest stocks.

Warren Buffett has never relied on a financial forecast while creating the greatest 57-year (and counting) track record of all time:

I have no use whatever for projections or forecasts.  They create an illusion of apparent precision.  The more meticulous they are, the more concerned you should be.

I make no effort to predict the course of general business or the stock market.  Period.

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.

Similarly, the great investor Peter Lynch never relied on financial forecasts:

Nobody can predict interest rates, the future direction of the economy, or the stock market.  Dismiss all such forecasts and concentrate on what’s actually happening to the companies in which you’ve invested.

The way you lose money in the stock market is to start off with an economic picture. I also spend fifteen minutes a year on where the stock market is going.

Henry Singleton, a business genius (100 points from being a chess grandmaster) who was easily one of the best capital allocators in American business history, never relied on financial forecasts:

I don’t believe all this nonsense about market timing.  Just buy very good value and when the market is ready that value will be recognized.

Furthermore, as noted by Montier (page 46), when people are told that someone is an expert, they partially switch off the part of the brain associated with logic and statistics.  (This has been shown in experiments.)



There are still quite a few investors who continue to listen to financial forecasters, despite the fact that financial forecasts on the whole do not add value.  There are several cognitive errors happening here.  Many investors are governed mostly by emotions.  They watch the daily fluctuations of stock prices – which have no meaning at all for long-term investors (except when they are low enough to create a buying opportunity).  They listen to financial experts giving mostly useless forecasts.  And they anchor on various forecasts.

Part of the problem is that many people will believe or do almost anything if it comes from a perceived authority.

Stanley Milgram ran a famous experiment about authority because he was trying to understand why so many previously good people decided to commit evil during WWII by joining the Nazi’s.

In Milgram’s experiment, subjects were told they would administer electric shocks to a “learner.”  If the learner answered a question incorrectly, the subject was told to deliver the shock.  The subjects met the learners before the experiment, but the learners were in a separate room during the experiment.  The subjects could hear the learners, however, as they answered questions and as they were shocked.  Behind the subject stood an authority figure wearing a white lab coat, carrying a clipboard, and telling the subject when to give the shock.

Before running the experiment, Milgram asked a panel of 40 psychiatrists what they thought the subjects would do.  The psychiatrists thought that only 1% of the subjects would go to the maximum shock level (450 volts with labels of “extreme danger” and “XXX”).  After all, they reasoned, the subjects were Americans and Americans wouldn’t do that, right?

100% of the subjects went up to 135 volts (at which point the learner is asking to be released).  80% of the subjects were willing to go up to 285 volts (at which point all they could hear were screams of agony).  And more than 62% of the subjects were willing to administer the maximum 450 volts (despite the labels of “extreme danger” and “XXX”) – at which point there was no sound at all from the learner.

Milgram ran several variants of his experiment, but the results were essentially the same.



A major reason why financial forecasters continue to forecast, despite adding no value on the whole, is simply that there are enough fearful people who need to hear financial forecasts.

But you might wonder: If a forecaster has been wrong so often, how can that person continue to forecast, even when there is a demand for it?

Montier discusses a landmark, 20-year study done by the psychologist Philip Tetlock.  (See Expert Political Judgment: How Good Is It? How Can We Know?)  Tetlock gathered over 27,000 expert predictions, and he found that they were little better than pure chance.

Tetlock also found that forecasters tend to use the same excuses over and over.  The five most common excuses for failed forecasts were the following:

The “If only” defense – If only the Federal Reserve had raised rates, then the prediction would have been true.  Effectively, the experts claim that they would have been correct if only their advice had been followed.

The ceteris paribus” defense – Something outside of the model of analysis occurred, which invalidated the forecast; therefore it isn’t my fault.

The “I was almost right” defense – Although the predicted outcome didn’t occur, it almost did.

The “It just hasn’t happened yet” defense – I wasn’t wrong, it just hasn’t occurred yet.

The “Single prediction” defense – You can’t judge me by the performance of a single forecast.

How can forecasters continue to be confident in their forecasts after years or decades of mostly being wrong?  Typically, they invoke one of the five defenses just listed.  As a result, most forecasters maintain just as high a level of overconfidence, even after a long string of mostly incorrect forecasts.



A fully automated deep value investing strategy will probably yield excellent results over time (especially if focused on microcap stocks), when compared with most other investment strategies.  If you have doubts about that, then low-cost broad market index funds are a great choice for your long-term investing.

If you’re picking individual stocks using a value investing approach, then the key is to be a learning machine.  And there are many books you should read, including all the books I’ve written about previously on this weekly blog.

There’s one book in particular that I recommend because it essentially uses Ben Graham’s conservative approach to picking individual stocks.  The book is Value Investing: From Graham to Buffett and Beyond (Wiley, 2004), by Professor Bruce Greenwald (and others).

If you could forecast the future free cash flows of a given company, and if you had a reasonable estimate of the discount rate, then you could value that company.  The problem with this DCF approach is that very tiny changes in certain variables, like long-term growth rates or the discount rate, can dramatically change the intrinsic value estimate.

Greenwald explains two approaches that depend entirely on the currently known facts about the company:

  • Net asset value
  • Earnings power value

Many value investors over the years have done extraordinarily well by estimating net asset value and then buying below that value.  Peter Cundill, for example, is a great value investor who always focused on buying below liquidation value.  See:

Other value investors have done extremely well by estimating the earnings power value – or normalized earnings – and consistently buying below that level.

Often the earnings power value of a company will exceed its net asset value.  So in a sense, net asset value is a conservative estimate of intrinsic value, while earnings power value may represent potential upside.  But even with earnings power value, there is zero forecasting involved.  There is no estimate of future growth.  This is especially helpful for value investors because the studies have shown that the stocks of ‘high-growth’ companies underperform, while the stocks of ‘low-growth’ or ‘no-growth’ stocks outperform.  See:



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:

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 mission of the Boole Fund is to outperform the S&P 500 Index by at least 5% per year (net of fees) over 5-year periods.  We also aim to outpace the Russell Microcap Index by at least 2% per year (net).  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:




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.

Best Performers: Microcap Stocks

(Image:  Zen Buddha Silence by Marilyn Barbone.)

February 26, 2017

Are you a long-term investor?  If so, are you interested in maximizing long-term results without taking undue risk?

Warren Buffett, arguably the best investor ever, has repeatedly said that most people should invest in a low-cost broad market index fund.  Such an index fund will allow you to do better than at least 90% of all investors, net of costs, after several decades.

Buffett has also said that you can do better than an index fund by investing in microcap stocks – as long as you have a sound method.  Take a look at this summary of the CRSP Decile-Based Size and Return Data from 1927 to 2020:

Decile Market Cap-Weighted Returns Equal Weighted Returns Number of Firms (year-end 2020) Mean Firm Size (in millions)
1 9.67% 9.47% 179 145,103
2 10.68% 10.63% 173 25,405
3 11.38% 11.17% 187 12,600
4 11.53% 11.29% 203 6,807
5 12.12% 12.03% 217 4,199
6 11.75% 11.60% 255 2,771
7 12.01% 11.99% 297 1,706
8 12.03% 12.33% 387 888
9 11.55% 12.51% 471 417
10 12.41% 17.27% 1,023 99
9+10 11.71% 15.77% 1,494 199

(CRSP is the Center for Research in Security Prices at the University of Chicago.  You can find the data for various deciles here:

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 2020:

Microcap equal weighted returns = 15.8% per year

Large-cap equal weighted returns = ~10% 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 2020, versus 10% per year for an equal weighted large-cap approach.

Still, if you can do 4% 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.

  • Most professional investors ignore micro caps as too small for their portfolios.  This causes many micro caps to get very cheap.  And that’s why an equal weighted strategy – applied to micro caps – tends to work well.



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



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:



If you invest in microcap stocks, you can get about 14% a year.  If you also use a simple screen for value, that adds at least 2% a year.  If, in addition, you screen for improving fundamentals, that adds at least another 2% a year.  So that takes you to 18% a year, which compares quite well to the 10% a year you could get from an S&P 500 index fund.

What’s the difference between 18% a year and 10% a year?  If you invest $50,000 at 10% a year for 30 years, you end up with $872,000, which is good.  If you invest $50,000 at 18% a year for 30 years, you end up with $7.17 million, which is much better.

Please contact me if you would like to learn more.

    • My email:
    • My cell: 206.518.2519



An equal weighted group of micro caps generally far outperforms an equal weighted (or cap-weighted) group of larger stocks over time.

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 mission of the Boole Fund is to outperform the S&P 500 Index by at least 5% per year (net of fees) over 5-year periods.  We also aim to outpace the Russell Microcap Index by at least 2% per year (net).  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:



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.


Are Humans Rational?

(Image:  Zen Buddha Silence by Marilyn Barbone.)

February 12, 2017

I’ve always deeply admired both great scientists and great artists.  Science and art – each in its own way – attempt to grasp the nature of ultimate reality, or at least the nature of reality as far as we currently can see it.  As Einstein wrote in his essay, “The World As I See It”:

The ideals which have lighted me on my way and time after time have given me new courage to face life cheerfully, have been Truth, Goodness, and Beauty.  Without the sense of fellowship with people of like mind, of preoccupation with the objective, the eternally unattainable in the field of art and science, life would have seemed to me empty.

The pursuit of truth, goodness, and beauty is really everything that makes life worthwhile.  (This includes, by definition, friendship and love.)

As a business person, I hasten to add that having the freedom to pursue one’s passion is obviously essential.  As science moves forward and as the world economy evolves, ever more people are gaining a measure of freedom (including better access to healthcare and education).  But there is still a long way to go.

What does this have to do with investing?  Only that the scientific study of human nature – including biology, genetics, psychology, neuroscience, economics, and sociology – is as fascinating as other areas in science, such as physics and astronomy.



When people make investment decisions, they are making decisions under uncertainty – decisions where there are unknown future states of the world.  Many economists have assumed that people make rational decisions under uncertainty.  Most of these economists have held that people always maximize their expected utility.  Maximizing expected utility means that people assign a probability and a reward to each possible future state, and then make a decision (e.g., an investment) that will maximize the expected utility.  Expected utility is just the sum of each probability times each reward.

Expected Utility Example:  Atwood Oceanics

The Boole Microcap Fund bought stock in Atwood Oceanics, Inc. (NYSE: ATW) at $6.46 in late January.  Currently, ATW is at roughly $11.70, but it is still probably quite cheap, at least from a 3- to 5-year point of view.

Here is how to apply the expected utility framework.  First note that under “normal” economic conditions, the market clearing price of oil is about $60-70.  A market clearing price just means a price where the daily supply of oil meets the daily demand for oil.  Let’s consider three scenarios, any of which could occur over the next 3 to 5 years, however long it takes for the oil markets to return to “normal”:

  • Oil at $55 and ATW earns $3.00 per share. Under this scenario, ATW may be worth $30 per share (a P/E of 10).
  • Oil at $65 and ATW earns $4.50 per share. Under this scenario, ATW may be worth $45 per share (a P/E of 10).
  • Oil at $75 and ATW earns $6.00 per share. Under this scenario, ATW may be worth $60 per share (a P/E of 10).

Assume that each scenario is equally likely, so there is a 33.3% chance for each scenario to occur.  To get the expected value of an investment in ATW today at $11.70, for each scenario we take the probability times the outcome (stock price).  Then we add those numbers together.  So we have $30 x .333 = $10, plus $45 x .333 = $15, plus $60 x .333 = $20.  So we expect ATW to hit $45 = $10 + $15 + $20, and currently we can buy the stock for $11.70.  That would be an expected return of almost 300% (or nearly double that if we were lucky enough to buy the stock at $6).

We could adjust the probabilities, oil prices, earnings, and P/E ratio’s for each scenario (as long as the probabilities add up to 100%).  We could also decide to use more (or less) than three scenarios.

A Few More Expected Utility Examples

An obvious business example of expected utility is whether a company should invest in Product A.  One tries to guess different scenarios (and their associated probabilities), perhaps including one that is highly profitable and another involving large losses.  One also must compare an investment in Product A with the next best investment opportunity.

In theory, we can apply the expected utility framework to nearly any situation where the future states are unknown, even life and death. 

I don’t think George Washington explicitly did an expected utility calculation.  But like many young men of his day, Washington was eager to serve in the military.  He had a couple of horses shot from under him.  And there were several occasions when bullets went whizzing right past his head (which he thought sounded “charming”).  In short, Washington was lucky to survive, and the luck of Washington has arguably reverberated for centuries.

Had Washington been able to do an expected utility calculation about his future war experience, it might have been something like this (crudely):

  • 25% chance of death (even when he was a general, Washington often charged to the front)
  • 75% chance of honor and wealth

A more realistic expected utility calculation – but not what Washington could have guessed – might have been the following:

  • 50% chance of death
  • 50% chance of great honor (due to great service to his future country) and wealth

(I’m oversimplifying in order to illustrate the generality of the expected utility framework.)

Von Neumann and Morgenstern

What’s fascinating is that the expected utility framework does a very good job describing how any rational agent should make decisions.  The genius polymath John von Neumann and the economist Oskar Morgenstern invented this framework.  (For some details on the most general form of the framework, see:

But ever since, many economists have assumed that people actually do make decisions with full rationality.  Economists have argued that rationalist economics is the best approximation for how humans behave.

Others scientists and observers have long suspected (or, indeed, realized) that people are NOT fully rational.  But it’s one thing to hold the view that much human behavior is irrational.  It’s another thing to prove human irrationality scientifically.

The psychologists Daniel Kahneman and Amos Tversky did hundreds of experiments over the course of decades of people making decisions under uncertainty.  What Kahneman and Tversky demonstrated conclusively is that most human beings are NOT fully rational when they make decisions under uncertainty.

Behavioral economics – based on the research of Kahneman, Tversky, and many others – is a fascinating field (and the reason I went to graduate school).  But it has not yet developed to the point where its models can predict a wide range of human behavior better than the rationalist economic models.  The rationalist economic models are still the best approximation for much human behavior.



In his great book Misbehaving: The Making of Behavioral Economics (W. W. Norton, 2015), Richard Thaler discusses the development of behavioral economics.  According to Kahneman, Richard Thaler is “the creative genius who invented the field of behavioral economics.”

Thaler defines “Econs” as the fully rational human beings that traditional economists have always assumed for their models.  “Humans,” on the other hand, are the actual people who make various decisions, including often less than fully rational decisions under uncertainty.

For this blog post, I will focus on Part VI (Finance, pages 203-253).  But first, a quotation Thaler has at the beginning of his book:

The foundation of political economy and, in general, of every social science, is evidently psychology.  A day may come when we shall be able to deduce the laws of social science from the principles of psychology.  – Vilfredo Pareto, 1906



Chicago economist Eugene Fama coined the term efficient market hypothesis, or EMH for short.  Thaler writes that the EMH has two (related) components:

  • the price is right – the idea is that any asset will sell for its intrinsic value.  If the rational valuation of a company – based on normalized earnings or net assets – is $100 million, then the company’s market cap (as reflected by its stock price) will be $100 million.
  • no free lunch– EMH holds that all publically available information is already reflected in current stock prices, thus there is no reliable way to “beat the market” over time.

NOTE:  If prices are always right, that means that assets can never be overvalued (there are no bubbles) or undervalued.

Thaler observes that finance did not become a mainstream topic in economics departments before the advent of cheap computer power and great data.  The University of Chicago was the first to develop a comprehensive database of stock prices going back to 1926.  After that, research took off, and by 1970 EMH was well-established.

Thaler also points out that the economist J. M . Keynes was “a true forerunner of behavioral finance.”  Keynes, who was also an investor, thought that animal spirits – emotions – played an important role in financial markets.

Keynes also thought that professional investors were playing an intricate guessing game, similar to picking out the prettiest faces from a set of photographs:

… It is not a case of choosing those which, to the best of one’s judgment, are really the prettiest, nor even those which average opinion genuinely thinks the prettiest.  We have reached the third degree where we devote our intelligences to anticipating what average opinion expects average opinion to be.  And there are some, I believe, who practice the fourth, fifth, and higher degrees.



On average, investors overreact to recent poor performance for low P/E stocks, which is why the P/E’s are low.  And, on average, investors overreact to recent good performance for high P/E stocks, which is why the P/E’s are high.

Having said that, Thaler is quick to quote a warning by Ben Graham (the father of value investing) about timing: ‘Undervaluations caused by neglect or prejudice may persist for an inconveniently long time, and the same applies to inflated prices caused by overenthusiasm or artificial stimulus.’  Thaler gives the example of the late 1990s:  for years, Internet stocks just kept going up, while value stocks just kept massively underperforming.

According to Thaler, most academic financial economists overlooked Graham’s work:

It was not so much that anyone had refuted Graham’s claim that value investing worked;  it was more that the efficient market theory of the 1970s said that value investing couldn’t work.  But it did.  Late that decade, accounting professor Sanjoy Basu published a thoroughly competent study of value investing that fully supported Graham’s strategy.  However, in order to get such papers published at the time, one had to offer abject apologies for the results.  (page 221)

Thaler and his research partner Werner De Bondt came up with the following.  Suppose that investors are overreacting.  Suppose that investors are overly optimistic about the future growth of high P/E stocks, thus driving the P/E’s “too high.”  And suppose that investors are excessively pessimistic about low P/E stocks, thus driving the P/E’s “too low.”  Then subsequent high returns from value stocks and low returns from growth stocks represent simple reversion to the mean.  But EMH says that:

  • The price is right: Stock prices cannot diverge from intrinsic value
  • No free lunch: Because all information is already in the stock price, it is not possible to beat the market. Past stock prices and the P/E cannot predict future price changes

Thaler and De Bondt took all the stocks listed on the New York Stock Exchange, and ranked their performance over three to five years.  They isolated the worst performing stocks, which they called “Losers.”  And they isolated the best performing stocks, which they called “Winners.”  Writes Thaler:

If markets were efficient, we should expect the two portfolios to do equally well.  After all, according to the EMH, the past cannot predict the future.  But if our overreaction hypothesis were correct, Losers would outperform Winners.  (page 223)

What did they find?

The results strongly supported our hypothesis.  We tested for overreaction in various ways, but as long as the period we looked back at to create the portfolios was long enough, say three years, then the Loser portfolio did better than the Winner portfolio.  Much better.  For example, in one test we used five years of performance to form the Winner and Loser portfolios and then calculated the returns of each portfolio over the following five years, compared to the overall market.  Over the five-year period after we formed our portfolios, the Losers outperformed the market by about 30% while the Winners did worse than the market by about 10%.



In response to widespread evidence that ‘Loser’ stocks (low P/E) – as a group – outperform ‘Winner’ stocks, defenders of EMH were forced to argue that ‘Loser’ stocks are riskier as a group.

NOTE: On an individual stock basis, a low P/E stock may be riskier.  But a basket of low P/E stocks generally far outperforms a basket of high P/E stocks.  The question is whether a basket of low P/E stocks is riskier than a basket of high P/E stocks.  Furthermore, one can use other metrics such as low P/B (low price to book) and get the same results as the low P/E studies.

According to the CAPM (Capital Asset Pricing Model), the measure of the riskiness of a stock is its correlation with the rest of the market, or beta.  If a stock has a beta of 1.0, then its volatility is similar to the volatility of the whole market.  If a stock has a beta of 2.0, then its volatility is double the volatility of the whole market (e.g., if the whole market goes up or down by 10%, then this individual stock will go up or down by 20%).

According to CAPM, if the basket of Loser stocks subsequently outperforms the market while the basket of Winner stocks underperforms, then the Loser stocks must have high betas and the Winner stocks must have low betas.  But Thaler and De Bondt found the opposite.  Loser stocks (value stocks) were much less risky as measured by beta.

Eventually Eugene Fama himself, along with research partner Kenneth French, published a series of papers documenting that, indeed, both value stocks and small stocks earn higher returns than predicted by CAPM.  In short, “the high priest of efficient markets” (as Thaler calls Fama) had declared that CAPM was dead.

But Fama and French were not ready to abandon the EMH (Efficient Market Hypothesis).  They came up with the Fama-French Three Factor Model.  They showed that value stocks are correlated – a value stock will tend to do well when other value stocks are doing well.  And they showed that small-cap stocks are similarly correlated.

The problem, again, is that there is no evidence that a basket of value stocks is riskier than a basket of growth stocks.  And there is no theoretical reason to believe that value stocks, as a group, are riskier.

According to Thaler, the debate was settled by the paper ‘Contrarian Investment, Extrapolation, and Risk’ published in 1994 by Josef Lakonishok, Andrei Shleifer, and Robert Vishny.  This paper shows clearly that value stocks outperform, and value stocks are, if anything, less risky than growth stocks.  Lakonishok, Shleifer, and Vishny launched the highly successful LSV Asset Management based on their research.  Here is a link to the paper:

(Recently Fama and French have introduced a five-factor model, which includes profitability.  Profitability was one of Ben Graham’s criteria.)



If you held a stock forever, it would be worth all future dividends discounted back to the present.  Even if you sold the stock, as long as you held it for a very long time, the distant future sales price (discounted back to the present) would be a negligible part of the intrinsic value of the stock.  The stock price is really the present value of all expected future dividend payments.

Bob Shiller collected data on stock prices and dividends starting in 1871:

… for each year he computed what he called the ‘ex post rational’ forecast of the stream of future dividends that would accrue to someone who bought a portfolio of the stocks that existed at that time.  He did this by observing the actual dividends that got paid out and discounting them back to the year in question.  After adjusting for the well-established trend that stock prices go up over long periods of time, Shiller found that the present value of dividends was… highly stable.  But stock prices, which we should interpret as attempts to forecast the present value of dividends, are highly variable….  (231-232)

October 1987 provides yet another example of stock prices moving much more than fundamental values.  The U.S. stock market dropped more than 25% from Thursday, October 15, 1987 to Monday, October 19, 1987.  This happened in the absence of any important news, financial or otherwise.  Writes Thaler:

If prices are too variable, then they are in some sense ‘wrong.’  It is hard to argue that the price at the close of trading on Thursday, October 15, and the price at the close of trading the following Monday – which was more than 25% lower – can both be rational measures of intrinsic value, given the absence of news.



It’s very important to note (again) that although the assumption of rationality and the EMH have been demonstrated not to be true, behavioral economists have not invented a model of human behavior that can supplant rationalist economics.  Therefore, rationalist economics, and not behaviorist economics, is still the chief basis by which economists attempt to predict human behavior.

In other words, scientists must learn much more – genetics, neuroscience, psychology, etc. – in order to better predict human behavior.  But even then, individual human behavior (to say nothing of group behavior) may remain partly unpredictable for a long period of time.

At the sub-atomic level, most top physicists believe that a part of reality is inherently unpredictable.  However, it’s always possible that this “inherent unpredictability” is a result of current limitations in theoretical physics.  Once physicists make further advances, it’s at least possible that what is currently “inherently unpredictable” may turn out to be predictable after all.  Einstein may be right when it comes to sub-atomic physics: “God does not play dice.”

Similarly with human behavior.  What will be the state of genetics, neuroscience, psychology, physics, artificial intelligence, etc. one thousand years from today?  Human behavior may be largely predictable.  But it then seems to get paradoxical.  How could one accurately predict one’s own behavior all the time, given that one could choose to act differently from one’s own predictions?  Or, if only a super-advanced artificial intelligence could aggregate enough data to predict all the behavior of a human being, when would it be legal to do so?  And who would own the super-advanced artificial intelligence, or would it be a benevolent entity guarding the universe?

In any case, rationalist economic models may continue to be useful for a long time.  In fact, rationalist models, including game theory, may also be central to predicting how various artificially intelligent agents will compete against one another.



In an efficient market, the same asset cannot sell simultaneously for two different prices.  Thaler gives the standard example of gold selling for $1,000 an ounce in New York and $1,010 an ounce in London.  If transaction costs were small enough, a smart trader could buy gold in New York and sell it in London.  This would eventually cause the two prices to converge.

But there is one obvious example that violates this law of one price:  closed-end funds, which had already been written about by Ben Graham.

For an open-end fund, all trades take place at NAV (net asset value).  Investors can purchase a stake in an open-end fund on the open market, without there having to be a seller.  So the total amount invested in an open-end fund can vary depending upon what investors do.

But for a closed-end fund, there is an initial amount invested in the fund, say $100 million, and then there can be no further investments and no withdrawals.  A closed-end fund is traded on an exchange.  So an investor can buy partial ownership of a closed-end fund, but this means that a previous owner must sell that stake to the buyer.

According to EMH, closed-end funds should trade at NAV.  But in the real world, many closed-end funds trade at prices different from NAV (sometimes a premium and sometimes a discount).  This is an obvious violation of the law of one price.

Charles Lee, Andrei Shleifer, and Richard Thaler wrote a paper on closed-end funds in which they identified four puzzles:

  • Closed-end funds are often sold by brokers with a sales commission of 7%. But within six months, the funds typically sell at a discount of more than 10%.  Why do people repeatedly pay $107 for an asset that in six months is worth $90?
  • More generally, why do closed-end funds so often trade at prices that differ from the NAV of its holdings?
  • The discounts and premia vary noticeably across time and across funds. This rules out many simple explanations.
  • When a closed-end fund, often under pressure from shareholders, changes its structure to an open-end fund, its price often converges to NAV.

The various premia and discounts on closed-end funds simply make no sense.  These mispricings would not exist if investors were rational because the only rational price for a closed-end fund is NAV.

Lee, Shleifer, and Thaler discovered that individual investors are the primary owners of closed-end funds.  So Thaler et al. hypothesized that individual investors have more noticeably shifting moods of optimism and pessimism.  Says Thaler:

We conjectured that when individual investors are feeling perky, discounts on closed-end funds shrink, but when they get depressed or scared, the discounts get bigger.  This approach was very much in the spirit of Shiller’s take on social dynamics, and investor sentiment was clearly one example of ‘animal spirits.’  (pages 241-242)

In order to measure investor sentiment, Thaler et al. used the fact that individual investors are more likely than institutional investors to own shares of small companies.  Thaler et al. reasoned that if the investor sentiment of individual investors changes, it would be apparent both in the discounts of closed-end funds and in the relative performance of small companies (vs. big companies).  And this is exactly what they found upon doing the research.  The greater the discounts to NAV for closed-end funds, the more the returns for small stocks lagged (on average) the returns for large stocks.



Years later, Thaler revisited the law of one price with a Chicago colleague, Owen Lamont.  Owen had spotted a blatant violation of the law of one price involving the company 3Com.  3Com’s main business was in networking computers using Ethernet technology, but through a merger they had acquired Palm, which made a very popular (at the time) handheld computer the Palm Pilot.

In the summer of 1999, as most tech stocks seemed to double almost monthly, 3Com stock seemed to be neglected.  So management came up with the plan to divest itself of Palm.  3Com sold about 4% of its stake in Palm to the general public and 1% to a consortium of firms.  As for the remaining 95% of Palm, each 3Com shareholder would receive 1.5 shares of Palm for each share of 3Com they owned.

Once this information was public, one could infer the following:  As soon as the initial shares of Palm were sold and started trading, 3Com shareholders would in a sense have two separate investments.  A single share of 3Com included 1.5 shares of Palm plus an interest in the remaining parts of 3Com – what’s called the “stub value” of 3Com.  Note that the remaining parts of 3Com formed a profitable business in its own right.  So the bottom line is that one share of 3Com should equal the “stub value” of 3Com plus 1.5 times the price of Palm.

When Palm started trading, it ended the day at $95 per share.  So what should one share of 3Com be worth?  It should be worth the “stub value” of 3Com – the remaining profitable businesses of 3Com (Ethernet tech, etc.) – PLUS 1.5 times the price of Palm, or 1.5 x $95, which is $143.

Again, because the “stub value” of 3Com involves a profitable business in its own right, this means that 3Com should trade at X (the stub value) plus $143, so some price over $143.

But what actually happened?  The same day Palm started trading, ending the day at $95, 3Com stock fell to $82 per share.  Thaler writes:

That means that the market was valuing the stub value of 3Com at minus $61 per share, which adds up to minus $23 billion!  You read that correctly.  The stock market was saying that the remaining 3Com business, a profitable business, was worth minus $23 billion.  (page 246)

Thaler continues:

Think of it another way.  Suppose an Econ is interested in investing in Palm.  He could pay $95 and get one share of Palm, or he could pay $82 and get one share of 3Com that includes 1.5 shares of Palm plus an interest in 3Com.

Thaler observes that two things are needed for such a blatant violation of the law of one price to emerge and persist:

  • You need some traders who want to own shares of the now publicly traded Palm, traders who appear not to realize the basic math of the situation. These traders are called noise traders, because they are trading not based on real information (or real news), but based purely on “noise.”  (The term noise traders was invented by Fischer Black.  See:
  • There also must be something preventing smart traders from driving prices back to where they are supposed to be. After all, the sensible investor can buy a share of 3Com for $82, and get 1.5 shares of Palm (worth $143) PLUS an interest in remaining profitable businesses of 3Com.  Actually, the rational investor would go one step further:  buy 3Com shares (at $82) and then short an appropriate number of Palm shares (at $95).  When the deal is completed and the rational investor gets 1.5 shares of Palm for each share of 3Com owned, he can then use those shares of Palm to repay the shares he borrowed earlier when shorting the publicly traded Palm stock. This was a CAN’T LOSE investment.  Then why wasn’t everyone trying to do it?

The problem was that there were very few shares of Palm being publicly traded.  Some smart traders made tens of thousands.  But there wasn’t enough publicly traded Palm stock available for any rational investor to make a huge amount of money.  So the irrational prices of 3Com and Palm were not corrected.

Thaler also tells a story about a young Benjamin Graham.  In 1923, DuPont owned a large number of shares of General Motors.  But the market value of DuPont was about the same as its stake in GM.  DuPont was a highly profitable firm.  So this meant that the stock market was putting the “stub value” of DuPont’s highly profitable business at zero.  Graham bought DuPont and sold GM short.  He made a lot of money when the price of DuPont went up to more rational levels.

In mid-2014, says Thaler, there was a point when Yahoo’s holdings of Alibaba were calculated to be worth more than the whole of Yahoo.

Sometimes, as with the closed-end funds, obvious mispricings can last for a long time, even decades.  Andrei Shleifer and Robert Vishny refer to this as the limits of arbitrage.



What are the implications of these examples?  If the law of one price can be violated in such transparently obvious cases such as these, then it is abundantly clear that even greater disparities can occur at the level of the overall market.  Recall the debate about whether there was a bubble going on in Internet stocks in the late 1990s….

Despite many market inefficiencies, the EMH – a part of rationalist economics – is still very useful:

So where do I come down on the EMH?  It should be stressed that as a normative benchmark of how the world should be, the EMH has been extraordinarily useful.  In a world of Econs, I believe that the EMH would be true.  And it would not have been possible to do research in behavioral finance without the rational model as a starting point.  Without the rational framework, there are no anomalies from which we can detect misbehavior.  Furthermore, there is not as yet a benchmark behavioral theory of asset prices that could be used as a theoretical underpinning of empirical research.  We need some starting point to organize our thoughts on any topic, and the EMH remains the best one we have.  (pages 250-251)

When it comes to the EMH as a descriptive model of asset markets, my report card is mixed.  Of the two components, using the scale sometimes used to judge claims made by political candidates, I would judge the no-free-lunch component to be ‘mostly true.’  There are definitely anomalies:  sometimes the market overreacts, and sometimes it underreacts.  But it remains the case that most active money managers fail to beat the market…

Most investors agree with Thaler on the no-free-lunch component of the EMH.  In practice, it is very difficult for any investor to beat the market over time.

But do prices always accurately reflect intrinsic value?

I have a much lower opinion about the price-is-right component of the EMH, and for many important questions, this is the more important component…

My conclusion:  the price is often wrong, and sometimes very wrong.  Furthermore, when prices diverge from fundamental value by such wide margins, the misallocation of resources can be quite big.  For example, in the United States, where home prices were rising at a national level, some regions experienced especially rapid price increases and historically high price-to-rental ratios.  Had both homeowners and lenders been Econs, they would have noticed these warning signals and realized that a fall in home prices was becoming increasingly likely.  Instead, surveys by Shiller showed that these were the regions in which expectations about the future appreciation of home prices were the most optimistic.  Instead of expecting mean reversion, people were acting as if what goes up must go up even more.

Thaler adds that policy-makers should realize that asset prices are often wrong, and sometimes very wrong, instead of assuming that prices are always right.



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:

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 mission of the Boole Fund is to outperform the S&P 500 Index by at least 5% per year (net of fees) over 5-year periods.  We also aim to outpace the Russell Microcap Index by at least 2% per year (net).  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:




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.

Lions and Tigers and Bears, Oh My!

(Image:  Zen Buddha Silence by Marilyn Barbone.)

January 29, 2017

As humans, the ancient part of our brains – including the amygdala – alerts us subconsciously if there is the slightest sight or sound of something that could be dangerous (e.g., a lion, a tiger, or a bear).  Such an alert happens so fast that our body prepares for fight or flight long before we are even conscious of the potential threat.

Unfortunately, plummeting stock prices very often trigger the same fear response in our ancient brains.  This often causes us to make bad decisions.



One key to investing is to learn to minimize the number of mistakes we make.  A great way to minimize our mistakes is to follow an automatic system for investment decisions.

For many investors, the best automatic approach is simply to buy and hold low-cost broad market index funds.  These investors, if they stick with it over several decades, will do better than 90-95% of all investors.  And this winning strategy requires very little time to implement.

For investors who want a proven, relatively low-risk way to beat the market, a quantitative value investment approach is a good option.  One of the best research papers on why a value investing strategy beats the market over time, without taking more risk, is “Contrarian Investment, Extrapolation, and Risk,” by Josef Lakonishok, Andrei Schleifer, and Robert Vishny.  Link:

Lakonishok, Schleifer, and Vishny were so convinced by the evidence that they started LSV Asset Management, which today has over $87 billion in assets under management.  LSV uses a quantitative value investment approach which automatically selects a portfolio of stocks based on the factors supported by their research, including low price to earnings and low price to cash flow.  See:



The truth is that most of us do not know ourselves very well at all.  But recent advances in psychology and neuroscience have made it possible for us to know ourselves much better.  Slowly but surely, studying our own mistakes and studying the best psychology can help us to make better decisions over time.

When it comes to decision making under uncertainty – and this includes investing – there are many great books that are absolute must-reads, including the following:

  • Daniel Kahneman, Thinking, Fast and Slow (Farrar, Straus and Giroux, 2013, 2011)
  • Charles T. Munger, Poor Charlie’s Almanack, edited by Peter Kaufman (Walsworth Publishing Company, Expanded Third Edition, 2005)

There are many more great authors on decision making under uncertainty, including Michael Mauboussin, James Montier, and Richard Thaler, to name just a few.  But in the interest of brevity, this blog post focuses on a chapter from James Montier’s Value Investing (Wiley, 2009), Chapter 13: The Psychology of Bear Markets.



Montier writes that Abraham Lincoln relayed the following story:

Solomon once charged his wise men to invent him a sentence, to be ever in view, which should be true and appropriate in all times and situations.  They presented him with the words ‘And this, too, shall pass away’.  How much it expresses!  How chastening in the hour of pride.  How consoling in the depths of affliction…  (page 123)

Unfortunately, says Montier, when it comes to investing, we are often overwhelmed by fear or greed instead of training ourselves to slow down and to use careful logical analysis.  We have two mental systems, one that is automatic and intuitive, and the other that is capable of deliberate, rational thinking.  The automatic system is the more ancient system, and we share it with many other animals.

The problem is that paper stock losses cause fear.  The fear response is very powerful and largely unconscious initially, originating in the amygdala.  It prepares the body for fight or flight even before the conscious mind has had time to analyze the situation.

Most of the time in our evolutionary history, a fear response to movement in the grass was appropriate for maximizing the chances of survival.  A rapid response to a potential threat had a low cost in the case of a false positive, notes Montier.  But a false negative – not reacting to the movement in the grass, but having it turn out to be a lion – was potentially fatal.

Yet a fear response to paper stock losses is almost always harmful for long-term investors.  When stocks drop a lot (10-40%), many long-term investors with time horizons of at least ten or twenty years are overwhelmed by fear and sell when they should be buying.  For instance, many long-term investors were overwhelmed by fear (and loss aversion) in the bear market of late 2008 to early 2009.  Long-term investors who sold missed out on a more than 200% recovery (from the lows) for the S&P 500 Index.

Conversely, long-term investors who have mastered their fears – by having an automatic investment system, or by having trained their own responses, or both – bought in late 2008 and early 2009 and are much better off as a result.



James Montier describes a study by Shiv et al. (2005).  It is a game at the start of which each player receives $20.  The game has 20 rounds.  Each round, the player can decide to bet $1 or not.  Then a fair coin is flipped.  If it comes up heads, the player who bet $1 gets $2.50 back.  If it comes up tails, the player who bet $1 loses the $1.

It is optimal for the player to bet $1 in each of the 20 rounds because the game has a clear positive expected value – the wins will outweigh the losses on average.  Also, the decision to bet $1 each round should not depend upon whether one won or lost in the previous round.  Each flip is independent of the previous flip.

What actually happened, however, was that people invested less than 40% of the time after suffering a loss.  Furthermore, the longer the game continued, the lower the percentage of players who decided to bet.

As losses add up, people become more and more fearful, and less and less willing to invest even though the best time to invest is during a period of extended losses (like late 2008 and early 2009).  Montier writes:

The parallels with bear markets are (I hope) obvious.  The evidence above suggests that it is outright fear that drives people to ignore bargains when they are available in the market, if they have previously suffered a loss.  The longer they find themselves in this position the worse their decision making appears to become.  (page 125)



Montier observes:

Investors should consider trying to adopt the Buddhist approach to time.  That is to say, the past is gone and can’t be changed, the future is unknown, and so we must focus on the present.  The decision to invest or not should be a function of the current situation (from my perspective the degree of value on offer) not governed by our prior experiences (or indeed our future hopes).  However, this blank slate is mentally very hard to achieve.  Our brains seem to be wired to focus on the short term and to fear loss in an extreme fashion.  These mental hurdles are barriers to sensible investment decision making in a bear market.  (page 127)

A bear market can occur at virtually any time.  At some point in the next five or so years – possibly even this year – there will likely be a bear market in which stocks drop at least 20-25% (and possibly much more).  It’s essential for all investors that we have an automatic, checklist-like approach to plummeting stock prices in order to maximize rational decisions and minimize irrational decisions.  It’s also essential for many of us as investors that we develop a keen understanding of our own emotional responses to plummeting stock prices.

Knowing in detail how we will feel in the face of plummeting stock prices, and having a rational set of responses (ideally automatic and preprogrammed), is one of the keys to successful long-term investing.



One important rule for long-term investors is to check stock prices as infrequently as humanly possible.  A flashing, plummeting stock price is a subliminal message that very often will activate our subconscious fear response – SELL!  SELL!

For a long-term index fund investor, it is possible to check stock prices only a few times per year or less.  Similarly for a long-term value investor, one should check prices as infrequently as possible.

If we are tempted to check stock prices, especially when prices are plummeting, there are simple techniques we can use to avoid the temptation.  Obviously being deeply engaged in a work project is ideal.  Or we can read, watch a movie, or even go to the beach.  Many long-term value investors recommend going to the beach – ideally with a stack of great books or annual reports – instead of checking or worrying about cratering prices.

Only buy something that you’d be perfectly happy to hold if the market shut down for 10 years.  – Warren Buffett

Invest only if you would be comfortable owning a stock even if you had no way of knowing its daily share price.  – Ben Graham

When we own stocks, we are part owners of the underlying businesses.  So if we are happy with the businesses we own, we should never waste time worrying about or checking falling prices.  If we understand and believe in the underlying business, then a dropping stock price is a wonderful opportunity to increase our ownership of the business.  A good rule is to add to our position for each 10% or 15% drop in price.

If we own a low-cost S&P 500 index fund, then we are part owners of five hundred American businesses.  As long as we believe the U.S. economy will do well over the coming decades – and it will do well, even if grows a bit more slowly than in the past – then when the index drops a great deal, it’s a wonderful opportunity to add to our position as a part owner of American businesses.

As long as we have uncorrelated or negatively correlated positions in our overall portfolio – such as cash, cash equivalents, or gold – it is simple to implement an automatic rebalancing rule.  For instance, during or after a period of falling stock prices, we would use some cash (or gold) to increase our ownership of the businesses we like best.  Ideally, this rebalancing is preprogrammed to occur at the end of a specified time period (e.g., quarter or year).

Just for fun, a 30-second link from the Wizard of Oz:



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:

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 mission of the Boole Fund is to outperform the S&P 500 Index by at least 5% per year (net of fees) over 5-year periods.  We also aim to outpace the Russell Microcap Index by at least 2% per year (net).  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:




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.

Security Analysis (Graham & Dodd)

(Image:  Zen Buddha Silence by Marilyn Barbone.)

January 22, 2017

This week, I am reviewing Security Analysis (McGraw Hill, 6th edition), by Benjamin Graham and David L. Dodd.  This blog post contains even more quotations than usual because the book is 730 pages (though I only read 75% of it, and have yet to look at the accompanying CD).

As with the other great value investors, it’s worth spending a long time soaking up the lessons of Graham and Dodd.



David Abrams, in his Introduction to Part VII, writes that the most important point from Security Analysis is this:  “look at the numbers and think for yourself.  All the great investors do, and that’s what makes them great.” (p. 631)

Or as Ben Graham has said:

You’re neither right nor wrong because the crowd disagrees with you.  You’re right because your data and reasoning are right.



I’ve always been deeply impressed by the kindness and generosity of many value investors, including Warren Buffett and Charlie Munger.  This is a part of the value investing tradition started by Ben Graham and David Dodd.  As Warren Buffett writes in the Forward:

In the end, that’s probably what I admire most about the two men.  It was ordained at birth that they would be brilliant; they elected to be generous and kind.

The way they behaved made as deep an impression on me – and many of my classmates – as did their ideas.  We were being taught not only how to invest wisely; we were also being taught how to live wisely.



Seth Klarman writes in the Preface to the 6th Edition – The Timeless Wisdom of Graham and Dodd:

In 1992, Tweedy, Browne Company LLC, a well-known value investment firm, published a compilation of 44 research studies entitled, ‘What Has Worked in Investing.’  The study found that what has worked is fairly simple: cheap stocks (measured by price-to-book values, price-to-earnings ratios, or dividend yields)  reliably outperform expensive ones, and stocks that have underperformed (over three- and five-year periods) subsequently beat those that have lately performed well.  In other words, value investing works!  I know of no long-time practitioner who regrets adhering to a value philosophy; few investors who embrace the fundamental principles ever abandon this investment approach for another.  (xvii)

Klarman says value investing is an art, not a science.  And there are always aspects of the future that nobody can foresee.  Even the best investors tend to be wrong about one-third of the time.  “In the end, the most successful value investors combine detailed business research and valuation work with endless discipline and patience, a well-considered sensitivity analysis, intellectual honesty, and years of analytical and investment experience.” (xviii-xix)

Klarman observes that not all value investors are alike.  Some invest in obscure micro caps, while others invest in large caps.  Some invest globally, while others focus on a single market sector like energy.  Some use a quantitative approach, while others assess “private market value.”  Some are activists, while others look for catalysts already in place (such as a spin-off, asset sale, repurchase plan, or new management).

Finally, human nature never changes.  Capital market manias regularly occur on a grand scale… Even highly capable investors can wither under the relentless message from the market that they are wrong.  The pressures to succumb are enormous;  many investment managers fear they’ll lose business if they stand too far apart from the crowd.  Some also fail to pursue value because they’ve handcuffed themselves (or been saddled by clients) with constraints preventing them from buying stocks selling at low dollar prices, small-cap stocks, stocks of companies that don’t pay dividends or are losing money, or debt instruments with below investment-grade ratings.  Many also engage in career management techniques like ‘window dressing’ their portfolios at the end of calendar quarters or selling off losers (even if they are undervalued) while buying more of the winners (even if overvalued).  Of course, for those value investors who are truly long term oriented, it is a wonderful thing that many potential competitors are thrown off course by constraints that render them unable or unwilling to effectively compete.  (xxi-xxii)

While bargains still occasionally hide in plain sight, securities today are most likely to become mispriced when they are either accidentally overlooked or deliberately avoided.  Consequently, value investors have bad to become more thoughtful about where to focus their analysis…. (xxiii)

Today’s value investors also find opportunity in the stocks and bonds of companies stigmatized on Wall Street because of involvement in protracted litigation, scandal, accounting fraud, or financial distress.  The securities of such companies sometimes trade down to bargain levels, where they become good investments for those who are able to remain stalwart in the face of bad news.

Value investors, therefore, should not try to time the market or guess whether it will rise or fall in the near term.  Rather, they should rely on a bottom-up approach, sifting the financial markets for bargains and then buying them, regardless of the level or recent direction of the market or economy.  Only when they cannot find bargains should they default to holding cash. (xxiv-xxv, my emphasis)


Another important factor for value investors to take into account is the growing propensity of the Federal Reserve to intervene in the financial markets at the first sign of trouble.  Amidst severe turbulence, the Fed frequently lowers interest rates to prop up securities prices and restore investor confidence.  While the intention of Fed officials is to maintain orderly capital markets, some money managers view Fed intervention as a virtual license to speculate.  Aggressive Fed tactics, sometimes referred to as the ‘Greenspan put’ (now the ‘Bernanke put’), create a moral hazard that encourages speculation while prolonging overvaluation…


…Selling is more difficult because it involves securities that are closer to fully priced.  As with buying, investors need a discipline for selling.  First, sell targets, once set, should be regularly adjusted to reflect all currently available information.  Second, individual investors must consider tax consequences.  Third, whether or not an investor is fully invested may influence the urgency of raising cash from a stockholding as it approaches full valuation.  The availability of better bargains might also make one a more eager seller.  Finally, value investors should completely exit a security by the time it reaches full value;  owning overvalued securities is the realm of speculation.  Value investors typically begin selling at a 10% to 20% discount to their assessment of underyling value – based on the liquidity of the security, the possible presence of a catalyst for value realization, the quality of management, the riskiness and leverage of the underlying business, and the investors’ confidence level regarding the assumptions underlying the investment.  (xxxviii)

Value investing is a get rich slow approach.  Because of innate psychological tendencies on the part of many investors, value investing is likely to continue to work over time:

The foibles of human nature that result in the mass pursuit of instant wealth and effortless gain seem certain to be with us forever.  So long as people succumb to this aspect of their natures, value investing will remain, as it has been for 75 years, a sound and low-risk approach to successful long-term investing.  (xl)



James Grant writes about the historical backdrop in the Introduction to the Sixth Edition:

Security analysis itself is a cyclical phenomenon;  it, too, goes in and out of fashion, Graham observed.  It holds a strong, intuitive appeal for the kind of businessperson who thinks about stocks the way he or she thinks about his or her own family business.  What would such a fount of common sense care about earnings momentum or Wall Street’s pseudo-scientific guesses about the economic future?  Such an investor, appraising a common stock, would much rather know what the company behind it is worth.  That is, he or she would want to study its balance sheet.  Well, Graham relates here, that kind of analysis went out of style when stocks started levitating without reference to anything except hope and prophecy.  So, by about 1927, fortune-telling and chart-reading had displaced the value discipline by which he and his partner were earning a very good living.  It is characteristic of Graham that his critique of the ‘new era’ method of investing is measured and not derisory… (11)

Grant mentions Graham’s critique of John Burr Williams’s The Theory of Investment Value.  “The rub, he pointed out, was that, in order to apply Williams’s method, one needed to make some very large assumptions about the future course of interest rates, the growth of profit, and the terminal value of the shares when growth stops.”  As Graham writes:

One wonders whether there may not be too great a discrepancy between the necessarily hit-or-miss character of these assumptions and the highly refined mathematical treatment to which they are subjected.

Grant, in similar manner to Buffett, notes the unmistakable humanity of Graham (and Dodd):

Graham’s technical accomplishments in securities analysis, by themselves, could hardly have carried Security Analysis through its five editions.  It’s the book’s humanity and good humor that, to me, explain its long life and the adoring loyalty of a certain remnant of Graham readers, myself included.  Was there ever a Wall Street moneymaker better steeped than Graham in classical languages and literature and in the financial history of his own time?  I would bet ‘no’ with all the confidence of a value investor laying down money to buy an especially cheap stock.  (18-19)



Roger Lowenstein authored the Introduction to Part I:

In 25 years as a financial journalist, virtually all of the investors of this writer’s acquaintance who have consistently earned superior profits have been Graham-and-Dodders.  (40)

It took Graham 20 years – which is to say, a complete cycle from the bull market of the Roaring Twenties through the dark, nearly ruinous days of the early 1930s – to refine his investment philosophy into a discipline that was as rigorous as the Euclidean theorems he had studied in college.  (41)

The changes in the marketplace have been so profound that it might seem astonishing that an investment manual written in the 1930s would have any relevance today.  But human nature doesn’t change.  People still oscillate between manic highs and depressive lows, and in their hunger for instant profits, their distaste for the hard labor of serious study and for independent thought, modern investors look very much like their grandfathers and even their great-grandfathers.  Then as now, it takes discipline to overcome the demons (largely emotional) that impede most investors.  And the essentials of security analysis have not much changed.  (42-43)

Finding Bargains

Individual stocks are often cheap when a whole industry or group of securities has been sold down indiscriminately. (50)

In 2001, for instance, energy stocks were cheap (as was the price of oil).  Graham and Dodd would not have advised speculating on the price of oil – which is dependent on myriad uncertain factors from OPEC to the growth rate of China’s economy to the weather.  But because the industry was depressed, drilling companies were selling for less than the value of their equipment.  Ensco International was trading at less than $15 per share, while the replacement value of its rigs was estimated at $35.  Patterson-UTI Energy owned some 350 rigs worth about $2.8 billion.  Yet its stock was trading for only $1 billion.  Investors were getting the assets at a huge discount.  Though the subsequent oil price rise made these stocks home runs, the key point is that the investments weren’t dependent on the oil price.  Graham and Dodd investors bought into these stocks with a substantial margin of safety. (51)

Forecasting Flows

In estimating future earnings (for any sort of business), Security Analysis provides two vital rules.  One, as noted, is that companies with stable earnings are easier to forecast and hence preferable.

The second point relates to the tendency of earnings to fluctuate, at least somewhat, in a cyclical pattern.  Therefore, Graham and Dodd made a vital (and oft-overlooked) distinction.  A firm’s average earnings can provide a rough guide to the future; the earnings trend is far less reliable…

An investor in U.S. securities thus faces a challenge unimaginable to Graham and Dodd.  Where the latter suffered a paucity of information, investors today confront a surfeit…



Graham defines intrinsic value as follows:

In general terms it is understood to be that value which is justified by the facts, e.g., the assets, earnings, dividends, definite prospects, as distinct, let us say, from market quotations established by artificial manipulation or distorted by psychological excess.  But it is a great mistake to imagine that intrinsic value is as definite and as determinable as is the market price. (64)

For Graham, net asset value and earnings power were two primary ways of estimating intrinsic value.  And net asset value often meant liquidation value, largely because Graham was writing during the Great Depression.  He returns to this concept later in the book.

By earnings power, Graham means normal earnings, or what today is referred to as normalized earnings:  what the company can safely be assumed to earn in a “normal” economic environment.  Net asset value – especially liquidation value – is not necessarily more precise than earnings power.  But net asset value is less subject to change than earnings power.

Regarding earnings power, Graham writes:

But the phrase ‘earnings power’ must imply a fairly confident expectation of certain future results.  It is not sufficient to know what the past earnings have averaged, or even that they disclose a definite line of growth or decline.  There must be plausible grounds for believing that this average or this trend is a dependable guide to the future.  Experience has shown only too forcibly that in many instances this is far from true.  This means that the concept of ‘earnings power,’ expressed as a definite figure, and the derived concept of intrinsic value, as something equally definite and ascertainable, cannot be safely accepted as a general premise of security analysis.  (65)

Intrinsic value, whether based on asset value or earnings power, is always an estimate.  But in many cases, an estimate is all that is needed:

The essential point is that security analysis does not seek to determine exactly what is the intrinsic value of a given security.  It needs only to establish either that the value is adequate – e.g., to protect a bond or to justify a stock purchase – or else that the value is considerably higher or considerably lower than the market price.  For such purposes an indefinite and approximate measure of the intrinsic value may be sufficient.  To use a homely simile, it is quite possible to decide by inspection that a woman is old enough to vote without knowing her age or that a man is heavier than he should be without knowing his exact weight.  (66)

It would follow that even a very indefinite idea of the intrinsic value may still justify a conclusion if the current price falls far outside either the maximum or minimum appraisal.  (67)

Human emotion often plays a significant role in determining stock prices:

…the market is not a weighing machine, on which the value of each issue is recorded by an exact and impersonal mechanism, in accordance with specific qualities.  Rather should we say that the market is a voting machine, whereon countless individuals register choices which are the product partly of reason and partly of emotion.  (70)



Nearly every issue might conceivably be cheap in one price range and dear in another. (80)

Not only can one overpay for a good business.  But what appears to be a good business may not remain a good business.

Many of the leading enterprises of yesterday are today far back in the ranks.  Tomorrow is likely to tell a similar story.  The most impressive illustration is afforded by the persistent decline in the relative investment position of the railroads as a class during the past two decades.

Graham always emphasizes skepticism and independent thinking:

The analyst must pay respectful attention to the judgment of the market place and to the enterprises which it strongly favors, but he must retain an independent and critical viewpoint.  Nor should he hesitate to condemn the popular and espouse the unpopular when reasons sufficiently weighty and convincing are at hand. (81)

Graham writes that quantitative factors are more easily analyzed than qualitative factors:

Broadly speaking, the quantitative factors lend themselves far better to thoroughgoing analysis than do the qualitative factors.  The former are fewer in number, more easily obtainable, and much better suited to the forming of definite and dependable conclusions.  Furthermore the financial results will themselves epitomize many of the qualitative elements, so that a detailed study of the latter may not add much of importance to the picture.  (81-82)

The qualitative factors upon which most stress is laid are the nature of the business and the character of management.  These elements are exceedingly important, but they are also exceedingly difficult to deal with intelligently.  (83)

Most businesses and industries experience reversion to the mean, according to Graham:

Abnormally good or abnormally bad conditions do not last forever.  This is true not only of general business but of particular industries as well.  Corrective forces are often set in motion which tend to restore profits where they have disappeared, or to reduce them where they are excessive in relation to capital.

The best measurement of management is a superior track record over time.  It’s important not to double count the quality of management:

The most convincing proof of capable management lies in a superior comparative record over a period of time.  But this brings us back to the quantitative data.

There is a strong tendency in the stock market to value the management factor twice in its calculations.  Stock prices reflect the large earnings which the good management has produced, plus a substantial increment for ‘good management’ considered separately.  This amounts to ‘counting the same trick twice,’ and it proves a frequent cause of overvaluation. (84)

But while a trend shown in the past is a fact, a ‘future trend’ is only an assumption.  The factors that we mentioned previously as militating against the maintenance of abnormal prosperity or depression are equally opposed to the indefinite continuance of an upward or downward trend.  By the time the trend has become clearly noticeable, conditions may well be ripe for a change. (84)

During the Great Depression, many companies were trading below liquidation value because their earnings were weak or inconsistent.  Given this extended bad economic environment, it stands to reason that Graham emphasized definite values – such as liquidation values – as opposed to future earnings.  Again here:

Analysis is concerned primarily with values which are supported by the facts and not with those which depend largely upon expectations.  In this respect the analyst’s approach is diametrically opposed to that of the speculator, meaning thereby one whose success turns upon his ability to forecast or to guess future developments.  Needless to say, the analyst must take possible future changes into account, but his primary aim is not so much to profit from them as to guard against them.  Broadly speaking, he views the business future as a hazard which his conclusions must encounter rather than as the source of his vindication. (86)

It follows that the qualitative factor in which the analyst should properly be most interested is that of inherent stability.  For stability means resistance to change and hence greater dependability for the results shown in the past…. in our opinion stability is really a qualitative trait, because it derives in the first instance from the character of the business and not from its statistical record.  A stable record suggest that the business is inherently stable, but this suggestion may be rebutted by other considerations.  (87)

In the mathematical phrase, a satisfactory statistical exhibit is a necessary though by no means a sufficient condition for a favorable decision by the analyst.  (88)



It must never be forgotten that a stockholder is an owner of the business and an employer of its officers.  He is entitled not only to ask legitimate questions but also to have them answered, unless there is some persuasive reason to the contrary.

Insufficient attention has been paid to this all-important point.  The courts have generally held that a bona fide stockholder has the same right to full information as a partner in a private business.  This right may not be exercised to the detriment of the corporation, but the burden of proof rests upon the management to show an improper motive behind the request or that disclosure of the information would work an injury to the business.

Compelling a company to supply information involves expensive legal proceedings and hence few shareholders are in a position to assert their rights to the limit.  Experience shows, however, that vigorous demands for legitimate information are frequently acceded to even by the most recalcitrant managements.  This is particularly true when the information asked for is no more than that which is regularly published by other companies in the same field.  (98)



An investment operation is one which, upon thorough analysis, promises safety of principal and a satisfactory return.  Operations not meeting these requirements are speculative.

… We speak of an investment operation rather than an issue or a purchase, for several reasons.  It is unsound to think always of investment character as inhering in an issue per se.  The price is frequently an essential element, so that a stock (and even a bond) may have investment merit at one price level but not at another.  Furthermore, an investment might be justified in a group of issues, which would not be sufficiently safe if made in any one of them singly.  In other words, diversification might be necessary to reduce the risk involved in the separate issues to the minimum consonant with the requirements of investment.  (This would be true, in general, of purchases of common stocks for investment.)

In our view it is also proper to consider as investment operations certain types of arbitrage and hedging commitments which involve the sale of one security against the purchase of another.  In these operations the element of safety is provided by the combination of purchase and sale.  This is an extension of the ordinary concept of investment, but one which appears to the writers to be entirely logical.  (106)



J. Ezra Merkin, in the Introduction to Part III, writes that a new valuation benchmark was established in 1958:

A few years later, in 1958, equity dividend yields fell below bond yields for the first time.  A sensible investor putting money to work at the time could hardly credit the change as part of a permanent new reality.  To the contrary, it must have seemed a mandate to short the stock market.  Think of all the money lost over all the years by the true believers who have argued: ‘This time is different.’  Yet the seasoned professionals of that time were cautious and wrong, and the irreverent optimists were right.  This time, it really was different.  From the safe perspective of a half century, it seems incontrovertible that a new valuation benchmark had been established. (287-288)

In 1963, Ben Graham gave a fascinating lecture.  Graham stated that, because of a permanently more stimulative policy by the U.S. government, the U.S. stock market should be valued 50% higher than before.  Here is a link to the lecture:

This is relevant today.  If U.S. interest rates return to 3%, 4%, 5%, or more within the next decade or so, then the S&P 500 Index today is quite overvalued (based on measures such as the CAPE and the q-ratio).  However, if U.S. interest rates stay near 0% for several decades, then the S&P 500 Index today may not be overvalued at all.  Very low rates, if extended far enough into the future, would actually make the S&P 500 undervalued today.  As Warren Buffett has noted, near-zero rates for many decades would eventually lead to a normal P/E level of 40, 50, or even higher.

Currently the high debt levels and relatively slow growth in the U.S. mean that rates could stay near zero for a long time.  (This may be more true for Europe and Japan.)  On the other hand, there could be an economically significant innovation explosion – perhaps driven by artificial intelligence, renewable energy, and/or space colonization – in which case the U.S. would grow faster, debts would come down, and interest rates would move higher again.



In the Introduction to Part IV, Bruce Berkowitz explains how to calculate the intrinsic value of any business:

… That’s the amount of cash an owner can pocket after paying all expenses and making whatever investments are necessary to maintain the business.  This free cash flow is the well from which all returns are drawn, whether they are dividends, stock buybacks, or investments capable of enhancing future returns.  (339)

Free cash flow is what Buffett calls owner earnings, because it represents what can be taken out of the business without impairing its competitive position.  Intrinsic value can thus be estimated by all future free cash flow or by all future dividends.  Berkowitz writes:

Graham and Dodd were among the first to apply careful financial analysis to common stocks… With bonds, the returns consist of specific payments made under contractual commitments.  With stocks, the returns consist of dividends that are paid from the earnings of the business, or cash that could have been used to pay dividends that was instead reinvested in the business.

By examining the assets of a business and their earnings (or cash flow) power, Graham and Dodd argued that the value of future returns could be calculated with reasonable accuracy.  (340)

To value equities, we at Fairholme begin by calculating free cash flow.  We start with net income as defined under Generally Accepted Accounting Principles (GAAP).  Then we add back noncash charges such as depreciation and amortization, which are formulaic calculations based on historical costs (depreciation for tangible assets, amortization for intangibles) and may not reflect a reduction in those assets’ true worth.

Even so, most assets deteriorate in value over time, and we have to account for that.  So we subtract an estimate of the company’s cost of maintaining tangible assets such as the office, plant, inventory, and equipment;  and intangible assets like customer traffic and brand identity.  Investment at this level, properly deployed, should keep the profits of the business in a steady state.

That is only the beginning.  For instance, companies often misstate the costs of employees’ pension and postretirement medical benefits…

Companies often lowball what they pay management.  For instance, until the last several years, most companies did not count the costs of stock option grants as employee compensation, nor did the costs show up in any other line item…

Another source of accounting-derived profits comes from long-term supply contracts.  For instance, when now-defunct Enron entered into a long-term trading or supply arrangement, the company very optimistically estimated the net present value of future profits from the deal and put that into the current year’s earnings even though no cash was received…

Some companies understate free cash flow because they expense the cost of what are really investments in growth…

All of these noncash accounting conventions illustrate the difficulty of identifying a company’s current free cash flow.  Still, we are far from done.  My associates and I next want to know (a) how representative is current cash flow of average past flow, and (b) is it increasing or decreasing – that is, does the company face headwinds or ride on tailwinds?  (341-342)



Speculation, in its etymology, meant looking forward;  investment was allied to ‘vested interests’ – to property rights and values taking root in the past.  The future was uncertain, therefore speculative;  the past was known, therefore the source of safety.  (354)

Another useful approach to the attitude of the prewar common-stock investor is from the standpoint of taking an interest in a private business.  The typical common-stock investor was a business man, and it seemed sensible to him to value any corporate enterprise in much the same manner as he would value his own business.  This meant that he gave at least as much attention to the asset values behind the shares as he did to their earnings records.  It is essential to bear in mind the fact that a private business has always been valued primarily on the basis of the ‘net worth’ as shown by its statement.  A man contemplating the purchase of a partnership or stock interest in a private undertaking will always start with the value of that interest as shown ‘on the books,’ i.e., the balance sheet, and will then consider whether or not the record and prospects are good enough to make such a commitment attractive.  An interest in a private business may of course be sold for more or less than its proportionate asset value;  but the book value is still invariably the starting point of the calculation, and the deal is finally made and viewed in terms of the premium or discount from book value involved. (355)

Broadly speaking, the same attitude was formerly taken in an investment purchase of a marketable common stock.  The first point of departure was the par value, presumably representing the amount of cash or property originally paid into the business;  the second basal figure was the book value, representing the par value plus a ratable interest in the accumulated surplus.  Hence in considering a common stock, investors asked themselves: ‘Is this issue a desirable purchase at the premium above book value, or the discount below book value, represented by the market price?’

… We thus see that investment in common stocks was formerly based upon the threefold concept of:  (1) a suitable and established dividend return, (2) a stable and adequate earnings record, and (3) a satisfactory backing of tangible assets.  Each of these three elements could be made the subject of careful analytical study, viewing the issue both by itself and in comparison with others of its class.  Common-stock commitments motivated by any other viewpoint were characterized as speculative, and it was not expected that they should be justified by a serious analysis. (356)

In the bull market leading up to 1929, people had developed a completely different attitude.  In the new-era theory, the value of a stock depended entirely on what it would earn in the future.  From this dictum the following corollaries were drawn:

  • That the dividend rate should have slight bearing upon the value.
  • That since no relationship apparently existed between assets and earnings power, the asset value was entirely devoid of importance.
  • That past earnings were significant only to the extent that they indicated what changes in the earnings were likely to take place in the future.

One reason for the new-era theory of common stocks was that a long historical record of dividends or earnings was not found to be a good guide to the future of a business.  Some businesses – after a decade of prosperity – went into insolvency.  Other companies – after being small or unsuccessful or of doubtful repute – quickly became large businesses with strong earnings and the highest rating.  As Graham explains:

In the face of all this instability it was inevitable that the threefold basis of common-stock investment should prove totally inadequate.  Past earnings and dividends could no longer be considered, in themselves, an index of future earnings and dividends.  Furthermore, these future earnings showed no tendency whatever to be controlled by the amount of the actual investment in the business – the asset values – but instead depended entirely upon a favorable industrial position and upon capable or fortunate managerial policies.  In numerous cases of receivership, the current assets dwindled, and the fixed assets proved almost worthless.  Because of this absence of any connection between both assets and earnings and between assets and realizable values in bankruptcy, less and less attention came to be paid either by financial writers or by the general public to the formerly important question of ‘net worth,’ or ‘book value’;  and it may be said that by 1929 book value had practically disappeared as an element in determining the attractiveness of a security issue. (357-358)

Another part of the new-era theory of common stocks was that common stocks were the most profitable long-term investment.  The record showed that common stocks produced both higher income and greater principal profit than standard bonds.  Thus, according to Graham, the new-era theory was as follows:

  • The value of a common stock depends on what it can earn in the future.
  • Good common stocks are those which have shown a rising trend of earnings.
  • Good common stocks will prove sound and profitable investments.

Graham comments:

These statements sound innocent and plausible.  Yet they concealed two theoretical weaknesses that could and did result in untold mischief.  The first of these defects was that they abolished the fundamental distinctions between investment and speculation.  The second was that they ignored the price of a stock in determining whether or not it was a desirable purchase. (359)

In essence, then, the new-era theory of investment was “old-style speculation”:  Common stocks were preferred to bonds, capital gains were preferred to dividends, and future estimates were more important than past records.  And most incredibly of all, the desirability of a common stock “was entirely independent of its price.”  Paying $100 per share for earnings of $2.50 per share was typical.  And the same reasoning was used as a basis to pay $200, $1,000, or any price for the same $2.50 per share in earnings.  Graham continues:

An alluring corollary of this principle was that making money in the stock market was now the easiest thing in the world.  It was only necessary to buy ‘good’ stocks, regardless of price, and then to let nature take her upward course…  (360)

Graham found it ironic that the investment trusts of the day completed adopted the new-era view of investments.

…The investment process consisted merely of finding prominent companies with a rising trend of earnings and then buying their shares regardless of price.  Hence the sound policy was to buy only what every one else was buying – a select list of highly popular and exceedingly expensive issues, appropriately known as ‘blue chips.’  The original idea of searching for the undervalued and neglected issues dropped completely out of sight.  Investment trusts actually boasted that their portfolios consisted exclusively of the active and standard (i.e., the most popular and highest priced) common stocks.  With but slight exaggeration, it might be asserted that under this convenient technique of investment, the affairs of a ten-million dollar investment trust could be administered by the intelligence, the training and the actual labors of a single thirty-dollar-a-week clerk.

The man in the street, having been urged to entrust his funds to the superior skill of investment experts – for substantial compensation – was soon reassuringly told that the trusts would be careful to buy nothing except what the man in the street was buying himself.

Thus, investors were deceiving themselves based on the long-term superior record of stocks as compared to bonds.  Here is the problem with that argument, says Graham:

… This would be true, typically, of a stock earning $10 and selling at 100.  But as soon as the price was advanced to a much higher price in relation to earnings, this advantage disappeared, and with it disappeared the entire theoretical basis for investment purchases of common stocks.  When in 1929 investors paid $200 per share for a stock earning $8, they were buying an earning power no greater than the bond-interest rate, without the extra protection afforded by a prior claim.  Hence in using the past performances of common stocks as the reason for paying prices 20 to 40 times their earnings, the new-era exponents were starting with a sound premise and twisting it into a woefully unsound conclusion. (362)



Is it possible to tell when a stock price is too high?

… We think that there is no good answer to this question – in fact we are inclined to think that even if one knew for a certainty just what a company is fated to earn over a long period of years, it would still be impossible to tell what is a fair price to pay for it today.  It follows that once the investor pays a substantial amount for the growth factor, he is inevitably assuming certain kinds of risks;  viz., that the growth will be less than he anticipates, that over the long pull he will have paid too much for what he gets, that for a considerable period the market will value the stock less optimistically than he does.

Graham argues that it’s advantageous to buy unpopular stocks at prices that are low or at prices that accord with private market value (what a prudent business man would pay for the business if it were private):

On the other hand, assume that the investor strives to avoid paying a high premium for future prospects by choosing companies about which he is personally optimistic, although they are not favorites of the stock market.  No doubt this is the type of judgment that, if sound, will prove most remunerative.  But, by the very nature of the case, it must represent the activity of strong-minded and daring individuals rather than investment in accordance with accepted rules and standards.

… we repeat that this method may be followed successfully if it is pursued with skill, intelligence and diligent study.  If so, is it appropriate to call such purchases by the name ‘investment’?  Our answer is ‘yes,’ provided that two factors are present:  the first, already mentioned, that the elements affecting the future are examined with real care and a wholesome scepticism, rather than accepted quickly via some easy generalization;  the second, that the price paid be not substantially different from what a prudent business man would be willing to pay for a similar opportunity presented to him to invest in a private undertaking over which he could exercise control. (371-372)



In the Introduction to Part V, Glenn Greenberg writes:

[Security Analysis] is the more remarkable because it was written during the uniquely depressed circumstances of 1934, a nation of 25% unemployment with most businesses struggling to survive.  Yet Graham and Dodd were able to codify the principles that have inspired great investors through 75 years of remarkable prosperity.  Their insights are as applicable now as ever.  (396)

Graham holds that past earnings are an important, but not very reliable, guide to the future:

… This is at once the most important and the least satisfactory aspect of security analysis.  It is the most important because the sole practical value of our laborious study of the past lies in the clue it may offer to the future;  it is the least satisfactory because this clue is never thoroughly reliable and it frequently turns out to be quite valueless.  These shortcomings detract seriously from the value of the analyst’s work, but they do not destroy it.  The past exhibit remains a sufficiently dependable guide, in a sufficient proportion of cases, to warrant its continued use as the chief point of departure in the valuation and selection of securities.  (472)

When Graham discusses earnings power, he means normal earnings:

The concept of earnings power has a definite and important place in investment theory.  It combines a statement of actual earnings over a period of years, with a reasonable expectation that these will be approximated in the future, unless extraordinary conditions supervene.  The record must cover a number of years, first because a continued or repeated performance is always more impressive than a single occurrence and secondly because the average of a fairly long period will tend to absorb and equalize the distorting influences of the business cycle.

A distinction must be drawn, however, between an average that is the mere arithmetical resultant of an assortment of disconnected figures and an average that is ‘normal’ or ‘modal,’ in the sense that the annual results show a definite tendency to approximate the average. (472)

According to Graham, a qualitative study of the nature of the business – e.g., its competitive position – is an important part of determining normal earnings:

In order for a company’s business to be regarded as reasonably stable, it does not suffice that the past record should show stability.  The nature of the undertaking, considered apart from any figures, must be such as to indicate an inherent permanence of earning power.  (474)

Given the importance of normal earnings, it follows that current earnings are not a primary basis for estimating intrinsic value.  Graham writes:

The market level of common stocks is governed more by their current earnings than by their long-term average.  This fact accounts in good part for the wide fluctuations in common-stock prices, which largely (though by no means invariably) parallel the changes in their earnings between good years and bad.  Obviously the stock market is quite irrational in thus varying its valuation of a company proportionately with the temporary changes in its reported profits.  A private business might easily earn twice as much in a boom year as in poor times, but its owner would never think of correspondingly marking up or down the value of his capital investment.

This is one of the most important lines of cleavage between Wall Street practice and the canons of ordinary business.  Because the speculative public is clearly wrong in its attitude on this point, it would seem that its errors should afford profitable opportunities to the more logically minded to buy common stocks at the low prices occasioned by temporarily reduced earnings and to sell them at inflated levels created by abnormal prosperity.

… We have here the long-accepted and classical formula for ‘beating the stock market.’  Obviously it requires strength of character in order to think and to act in opposite fashion from the crowd and also patience to wait for opportunities that may be spaced years apart.  But there are still other considerations that greatly complicate this apparently simple rule for successful operations in stocks.  In actual practice the selection of suitable buying and selling levels becomes a difficult matter…. (476-477)

Graham makes it clear that most of the time, abnormally low current earnings later recover to normal levels, while abnormally high current earnings later revert to more normal levels.  However, sometimes low earnings do not recover, and sometimes high earnings remain high or go higher.  Thus, the analyst must carefully assess each situation in order to determine the approximate level of normal earnings, and whether this level has changed from before.  Yet to be conservative, argues Graham, if normal earnings are higher than in the past, the analyst should use the past level as a basis for estimating intrinsic value.

If earnings show a downward trend, that often will create an irrationally low stock price.  In these cases, Graham argues that one should view such a business as a sensible businessman would:  considering the pros and cons, what would the enterprise be worth to a private owner?



A given common stock is generally considered to be worth a certain number of times its current earnings.

Subsequent to 1932 there developed a tendency for prices to rule higher in relation to earnings because of the sharp drop in long-term interest rates. (497)

Intrinsic value is an estimate rather than an exact figure.  Net asset value is an estimate.  And current earnings change all the time.  Moreover, investor emotions are a component of stock prices:

… Hence the prices of common stocks are not carefully thought out computations but the resultants of a welter of human reactions.  The stock market is a voting machine rather than a weighing machine.  It responds to factual data not directly but only as they affect the decisions of buyers and sellers.  (497)

Graham explains the conditions under which current earnings may be considered normal earnings.  Graham also explains when the analyst may even set future normal earnings as higher than at any time in the past:

… His fundamental basis of appraisal must be an intelligent and conservative estimate of the future earning power.  But his measure of future earnings can be conservative only if it is limited by actual performance over a period of time.  We have suggested, however, that the profits of the most recent year, taken singly, might be accepted as the gage of future earnings, if (1) general business conditions in that year were not exceptionally good, (2) the company has shown an upward trend of earnings for some years past and (3) the investor’s study of the industry gives him confidence in its continued growth.  In a very exceptional base, the investor may be justified in counting on higher earnings in the future than at any time in the past.  This might follow from developments involving a patent or the discovery of new ore in a mine or some similar specific and significant occurrence.  But in most instances he will derive the investment value of a common stock from the average earnings of a period between five and ten years.  This does not mean that all common stocks with the same average earnings should have the same value.  The common-stock investor (i.e., the conservative buyer) will properly accord a more liberal valuation to those issues which have current earnings above the average or which may reasonably be considered to possess better than average prospects or an inherently stable earnings power.  But it is the essence of our viewpoint that some moderate upper limit must in every case be placed on the multiplier in order to stay within the bounds of conservative valuation.  We would suggest that about 20 times average earnings is as high a price as can be paid in an investment purchase of a common stock.

Most of the time, average earnings based on five or ten years is a reasonable estimate for normal earnings.  But the analyst should also make adjustments for companies with better than average prospects and for companies with more stable earnings.

Graham suggests that 20 times earnings is as high a price as a conservative investor should ever pay for an investment (as opposed to a speculation):

… it is difficult to see how average earnings of less than 5% upon the market price could ever be considered as vindicating that price.

Given that 20 times earnings is the upper limit, it is natural to ask what the typical multiple might be.  Graham answers:

… This suggests that about 12 or 12 ½ times average earnings may be suitable for the typical case of a company with neutral prospects.  We must emphasize also that a reasonable ratio of market price to average earnings is not the only requisite for a common-stock investment.  It is a necessary but not a sufficient condition.  The company must be satisfactory also in its financial set-up and management, and not unsatisfactory in its prospects. (499)



… there is some tendency for speculatively capitalized enterprises to sell at relatively high values in the aggregate during good times or good markets.  Conversely, of course, they may be subject to a greater degree of undervaluation in depression.  There is, however, a real advantage in the fact that such issues, when selling on a deflated basis, can advance much further than they can decline. (512-513)

Graham gives an example of 400-bagger (American Water Works and Electric Company).  Because the company was highly indebted, when gross revenues grew about 160%, per share earnings increased dramatically more.

Highly indebted companies tend to sell at very low prices when their earnings are abnormally low, which often creates an investment opportunity:

The overdeflation of a speculative issue … in unfavorable markets creates the possibility of an amazing price advance when conditions improve, because the earnings per share then show so violent an increase. (517)

In effect, the equity holder of a highly indebted enterprise operates with relatively little capital relative to the debt holders.  The equity holder in this case may have a similar downside to the debt holder, but dramatically higher upside.  Graham says the equity holder has a “cheap call” on the future profits of the highly indebted enterprise.



Low-priced stocks seem to have an “inherent arithmetical advantage” because they can increase much more than they can decrease.  What often creates a low-priced stock is when current profits are low in relation to the size of the enterprise.  Thus, like an equity stub, a low-priced stock can be thought of as a “cheap call” on the future profits of the enterprise.

Graham notes that unusually high operating or production costs can have the same effect as high debt levels:

The speculative or marginal position may arise from any cause that reduces the percentage of gross available for the common to a subnormal figure and that therefore serves to create a subnormal value for the common stock in relation to the volume of business.  Unusually high operating or production costs have the identical effect as excessive senior charges in cutting down the percentage of gross available for common…. (525)



In the Introduction to Part VI, Bruce Greenwald notes how Graham and Dodd define intrinsic value:

that value which is justified by the facts, e.g., the assets, earnings, dividends, [and] definite prospects, as distinct, let us say, from market quotations established by market manipulation or distorted by psychological excesses. (64)

If perfect information were possible, then intrinsic value would be identical to true value.  But Graham and Dodd understood that there are always uncertainties, both with regard to current information and with regard to the future.  Therefore, intrinsic value must be an estimate.  But even as an estimate, intrinsic value plays a vital role, as Greenwald explains:

… It served first of all to organize examination and use of the available information, ensuring that the relevant facts would be brought to bear and irrelevant noise ignored.  Second, it would produce an appreciation of the range of uncertainty associated with any particular intrinsic value calculation.  Graham and Dodd recognized that even a very imperfect intrinsic value would be useful in making investment decisions. 

The purchase of securities should then be made only at prices far enough below the intrinsic value to provide a margin of safety that would offer appropriate protection against this ‘indistinctness’ in the calculated intrinsic value.  In essence, what Graham and Dodd required was that an investor, as opposed to a speculator, should know as far as possible the value of any security purchased and also the degree of uncertainty attached to that value.  (536)

Greenwald identifies four areas that Graham and Dodd describe as being useful for balance sheet analysis:

…First, the balance sheet identifies the quantity and nature of resources tied up in a business.  For an economically viable enterprise, these resources are the basis of its returns.  In a competitive environment, a firm without resources cannot generally expect to earn any significant profits.  If an enterprise is not economically viable, then the balance sheet can be used to identify the resources that can be recovered in liquidation and how much cash the resources might return.

Second, the resources on a balance sheet provide a basis for analyzing the nature and stability of sources of income… earnings estimates will be more realistic and accurate if they are supported by appropriate asset values…

Third, the liabilities side of the balance sheet, which identifies sources of funding, describes the financial condition of the firm…

Fourth, the evolution of the balance sheet over time provides a check on the quality of earnings…

A balance sheet is a snapshot of a company’s assets and liabilities at a particular time.  It can be checked for accuracy and value at that moment.  This places significant constraints on the degree to which the assets and liabilities can be manipulated.  In contrast, flow variables such as revenue and earnings measure changes over time that by their nature are evanescent.  If they are to be monitored, they must be monitored over an extended period.  In 1934, and today, this fundamental difference accounts for the superior reliability (in theory) of balance sheet figures.  (538-539)

Greenwald discusses the net-net approach advocated and used by Graham and Dodd.  If current assets minus all liabilities is positive, and if the stock can be purchased below that level, then the downside is typically limited, while the upside is often substantial.  There were many net-nets during the Great Depression, but there are far fewer these days, although occasionally they show up during bear markets and/or in foreign markets.  (Value investors bought net-nets in South Korea some years ago.)  Despite the virtual disappearance of net-nets, Greenwald observes that the general lessons still hold:

However, the broader lessons that led Graham and Dodd to focus on the balance sheets of firms continue to apply, with extensions that are much within the spirit of their original approach.  First, it is now recognized that for economically viable firms, assets wear out or become obsolete and have to be replaced.  Thus, replacement value – the lowest possible cost of reproducing a firm’s net assets by the competitors who are best positioned to do it – continues to serve the role that Graham and Dodd recognized.  If projected profit levels for a firm imply a return on assets well above the cost of capital, then competitors will be drawn in.  That, in turn, will drive down profits and with them the value of the firm.  Thus, earnings power unsupported by asset values – measured as reproduction values – will, absent special circumstances, always be at risk from erosion due to competition.  Both ‘safety of principal’ and the promise of a ‘satisfactory return,’ therefore, require that ‘thorough’ investors support their earnings projections with a careful assessment of the replacement values of a firm’s assets.  Investors who do this will have an advantage over those who do not, and they should outperform these less thorough investors in the long run.  (541-542)



Book value often means asset value, or tangible asset value, or tangible book value.  Graham introduces his definition of net-nets based upon current-asset value, which is current assets minus all liabilities.  A net-net is when the stock can be purchased below current-asset value.  Later, Graham discusses financial reasoning versus business reasoning:

We have here the point that brings home more strikingly perhaps than any other the widened rift between financial thought and ordinary business thought.  It is an almost unbelievable fact that Wall Street never asks, ‘How much is the business selling for?’  Yet this should be the first question on considering a stock purchase.  If a business man were offered a 5% interest in some concern for $10,000, his first mental process would be to multiply the asked price by 20 and thus establish a proposed value of $200,000 for the entire undertaking.  The rest of his calculation would turn about the question whether or not the business was a ‘good buy’ at $200,000.  (555-556)

Graham explains the reasons why buying above tangible book is often not a good idea, while buying below tangible book is often a good idea:

There are indeed certain presumptions in favor of purchases made far below asset value and against those made at a high premium above it.  (It is assumed that in the ordinary case the book figures may be accepted as roughly indicative of the actual cash invested in the enterprise.)  A business that sells at a premium does so because it earns a large return upon its capital;  this large return attracts competition, and, generally speaking, it is not likely to continue indefinitely.  Conversely in the case of a business selling at a large discount because of abnormally low earnings.  The absence of new competition, the withdrawal of old competition from the field, and other natural economic forces may tend eventually to improve the situation and restore a normal rate of profit on the investment.  (557)

Graham then points out that while this is often true, it is not certain enough to be used categorically.  Rather, Graham advises that the analyst work to understand each individual case in order to act sensibly.



Graham begins by noting that with regards to unprofitable businesses, the liquidation of private businesses is “infinitely more frequent” than the liquidation of public businesses.  When Security Analysis was written, during the Great Depression, there were many public businesses selling below liquidation value.

Graham outlines a conservative way to calculate liquidation value:

A company’s balance sheet does not convey exact information as to its value in liquidation, but it does supply clues or hints which may prove useful.  The first 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.  The following schedule indicates fairly well the relative dependability of various types of assets in liquidation.  (560)

In a table, Graham explains that cash assets are valued at 100% of book value, receivables at roughly 80%, inventories at roughly 66.7%, and fixed assets at approximately 15%.  Of course, notes Graham, there is a wide range in most of these categories depending upon the business or industry in question.

Graham tries to explain the wide availability of businesses below liquidation values:

…Evidently the phenomena of 1932 (and 1938) were the direct out-growth of the new-era doctrine which transferred all the tests of value to the income account and completely ignored the balance-sheet picture.  In consequence, a company without current earnings was regarding as having very little real value, and it was likely to sell in the market for the merest fraction of its realizable resources.  Most of the sellers were not aware that they were disposing of their interest at far less than its scrap value.  Many, however, who might have known the fact would have justified the low price on the ground that the liquidating value was of no practical importance, since the company had no intention of liquidating.  (563)

Graham holds that the wide availability of businesses selling below liquidation values was highly illogical.  If a business is worth more than its liquidation value, then steps should be taken to realize this higher value.  If a business is worth more in liquidation than as a going concern, then it should be liquidated.

Part of the problem is that there is a conflict of interest between the managers and the owners (stockholders).  The managers of a given business typically prefer that the business be continued rather than liquidated, since they want to retain their jobs and benefits.  On the other hand, unless steps can be taken to improve the value of the business as a going concern, the stockholders benefit if the business is liquidated.

As far as the attractiveness of investing in net-nets, Graham observes that the chief danger is that the net asset value will be dissipated.  But this only happens occasionally.  Usually something happens that causes a net-net to be a profitable investment.  Often the normal earnings power of the company is restored, either by general improvement in the industry or by a change in operating policies (as well as, in some cases, new management).  Sometimes a sale or merger occurs because another business is able to utilize the assets more efficiently.  Sometimes the company is liquidated, either partially or fully.

Net-nets are statistically very good investments, but the analyst still must be careful, says Graham:

… the securities analyst should exercise as much discrimination as possible in the choice of issues falling within this category.  He will lean toward those for which he sees a fairly imminent prospect of some one of the favorable developments listed above.  Or else he will be partial to such as reveal other attractive statistical features besides their liquid-asset position, e.g., satisfactory current earnings and dividends or a high average earning power in the past.  The analyst will avoid issues that have been losing their current assets at a rapid rate and show no definite signs of ceasing to do so.  (568-569)



It is a notorious fact… that the typical American stockholder is the most docile and apathetic animal in captivity.  He does what the board of directors tell him to do and rarely thinks of asserting his individual rights as owner of the business and employer of its paid officers.  The result is that the effective control of many, perhaps most, large American corporations is exercised not by those who together own a majority of the stock but by a small group known as ‘the management.’… (575-576)

… Certain elementary facts, once well-nigh forgotten, might well be emphasized here:  Corporations are in law the mere creatures and property of stockholders who own them;  the officers are only paid employees of the stockholders;  the directors, however chosen, are virtually trustees, whose legal duty it is to act solely in behalf of the owners of the business.

To make these general truths more effective in practice, it is necessary that the stock-owning public be educated to a clearer idea of what are the true interests of the stockholders in such matters as dividend policies, expansion policies, the use of corporate cash to repurchase shares, the various methods of compensating management, and the fundamental question of whether the owners’ capital shall remain in the business or be taken out by them in whole or in part.  (590)



In the Introduction to Part VII, David Abrams writes:

… as Graham and Dodd understood, how markets work, how companies are run, and how people – both investors and corporate managers – tend to act in certain situations never change.  (617)

… every successful investor I’ve ever known makes a calculation that compares an asset’s purchase price to its present or future value.  (618)

Abrams describes his own evolution from overconfident and ignorant to humble and knowledgeable:

I realized that, in all likelihood, the guy on the other side was probably smarter than I was.  Embarrassed by my own ignorance, I vowed to wade into new situations with a greater respect for those on the other side of the trade and with more humility about the limits of my own knowledge.  Never again would I be the patsy.  That approach has served me well throughout my career.  (624)

Graham and Dodd knew that market forecasting doesn’t work:

In market analysis there are no margins of safety;  you are either right or wrong, and if you are wrong, you lose money. (703)

Abrams says that the most important point in Security Analysis is the following:

look at the numbers and think for yourself.  All the great investors do, and that’s what makes them great.



Long before behavioral economics was invented, Graham and Dodd (and also Keynes) understood the significant role of human emotions in determining market prices:

Our exposition of the technique of security analysis has included many different examples of overvaluation and undervaluation.  Evidently the processes by which the securities market arrives at its appraisals are frequently illogical and erroneous.  These processes, as we pointed out in our first chapter, are not automatic or mechanical but psychological, for they go on in the minds of people who buy or sell.  The mistakes of the market are thus the mistakes of groups or masses of individuals.  Most of them can be traced to one or more of three basic causes:  exaggeration, oversimplification or neglect.  (669)

How does one find cheap stocks?

Since we have emphasized that analysis will lead to a positive conclusion only in the exceptional case, it follows that many securities must be examined before one is found that has real possibilities for the analyst.  By what practical means does he proceed to make his discoveries?  Mainly by hard and systematic work.  (669)

Graham writes of opportunities in obscure or ignored stocks:

… although overvaluation or undervaluation of leading issues occurs only at certain points in the stock-market cycle, the large field of ‘nonrepresentative’ or ‘secondary’ issues is likely to yield instances of undervaluation at all times.  When market leaders are cheap, some of the less prominent common stocks are likely to be a good deal cheaper.

Graham gives the example of a market leader (Great Atlantic and Pacific Tea Company) that ended up selling below liquidation value:

… Here, then, was a company whose spectacular growth was one of the great romances of American business, a company that was without doubt the largest retail enterprise in America and perhaps in the world, that had an uninterrupted record of earnings and dividends for many years – and yet was selling for less than its net current assets alone.  Thus one of the outstanding businesses of the country was considered by Wall Street in 1938 to be worth less as a going concern than if it were liquidated.  Why?  First, because of chain-store tax threats;  second, because of a recent decline in earnings;  and, third, because the general market was depressed.

We doubt that a better illustration can be found of the real nature of the stock market, which does not aim to evaluate businesses with any exactitude but rather to express its likes and dislikes, its hopes and fears, in the form of daily changing quotations.  There is indeed enough sound sense and selective judgment in the market’s activities to create on most occasions some degree of correspondence between market prices and ascertainable or intrinsic value… But, on enough occasions to keep the analyst busy, the emotions of the stock market carry it in either direction beyond the limits of sound judgment.  (673-674)

As noted earlier by Seth Klarman, litigation, scandal, accounting fraud, or financial distress often create bargains for the intrepid – those who can ignore bad news and remain focused on long-term fundamentals.  Graham writes about these types of dislocations.  Here is Graham on litigation:

The tendency of Wall Street to go to extremes is illustrated… by its tremendous dislike of litigation.  A lawsuit of any significance casts a damper on the securities affected, and the extent of the decline may be out of all proportion to the merits of the case.  (681)

Graham gives several examples where the potential impact of the lawsuit was tiny, and yet the stock had irrationally declined a large amount.



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:

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 mission of the Boole Fund is to outperform the S&P 500 Index by at least 5% per year (net of fees) over 5-year periods.  We also aim to outpace the Russell Microcap Index by at least 2% per year (net).  The Boole Fund has low fees.


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

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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.

Index Funds Beat 90-95% of All Investors Over Time

(Image:  Zen Buddha Silence by Marilyn Barbone.)

January 8, 2017

John Bogle wrote The Little Book of Common Sense Investing in 2007 (Wiley).  It’s a terrific book for all investors.  Here are some key points:


INTRODUCTION – Don’t Allow a Winner’s Game to Become a Loser’s Game

Owning a slice of all American businesses is a positive-sum game, especially over the course of many decades.  On the whole, the capitalist system creates enormous wealth for its owners over the very long term due to innovation and growth.

Trying to do better than long-term owners of all American businesses—that is, trying to beat the broad market index over time—is a zero-sum game.  For each investor who does better than the broad market index, another investor must do worse.  Beating the stock market is a zero-sum game, but that is BEFORE the deduction of costs.

AFTER the deduction of costs, beating the market is a loser’s game.  Bogle explains:

So who wins?  You know who wins.  The man in the middle (actually, the men and women in the middle, the brokers, the investment bankers, the money managers, the marketers, the lawyers, the accountants, the operations departments of our financial system) is the only sure winner in the game of investing.  Our financial croupiers always win.  In the casino, the house always wins.  In horse racing, the track always wins.  In the powerball lottery, the state always wins.  Investing is no different.

The vast majority of investors who invest directly in stocks trail the market, net of costs, over the longer term.  Even more so, the vast majority of investors who invest in mutual funds trail the market, net of costs, over the longer term.

The basic arithmetic has a simple bottom line:  The vast majority of all investors would be best off, over the longer term (several decades or more), by simply buying and holding low-cost broad market index funds.

Many top investors, including Warren Buffett and Charlie Munger, have emphatically agreed with John Bogle’s conclusion.


A PARABLE – The Gotrocks Family

Warren Buffett tells the parable of the Gotrocks family in the 2005 Berkshire Hathaway Annual Letter:

Bogle gives his version of the parable:  At the beginning, a large family called the Gotrocks owns 100 percent of every stock in the United States, thus benefitting from the long-term productivity of all businesses.

Their investment had compounded over the decades, creating enormous wealth, because the Gotrocks family was playing a winner’s game.

But then a few ‘fast-talking Helpers’ arrive, and they convince some ‘smart’ Gotrocks cousins that they can earn a larger share than their relatives by selling some of their shares to other family members and by buying some shares from others in return.

The net result is that the family wealth starts compounding at a slower rate overall because some of the return is now given to the Helpers as trading fees.

The cousins decide that they need more help in order to actually do better than their relatives, so they hire another set of Helpers to pick which stocks to buy and which to sell.  Now the family wealth overall compounds at an even slower rate, since it is reduced by two layers of fees to Helpers.

So the cousins decide to hire even more Helpers, who promise to help the cousins pick the right stock-picking Helpers.  Once again, the family wealth overall now compounds even more slowly.

After some period of time, the family calls a meeting.  They ask:

“How is it that our original 100 percent share of the pie—made up each year of all those dividends and earnings—has dwindled to just 60 percent?”

The wisest family member, an old uncle, notes that the entire reduction in overall returns is exactly equal to the fees and expenses related to all of the Helpers.  Thus, in order for the family to again benefit from 100 percent of the growth of all American businesses, they should simply get rid of all the Helpers.

The family follows the uncle’s advice and soon they are again benefitting 100 percent from the wealth created by all American businesses over time.

Owning a low-cost index fund is exactly the same idea.  Bogle quotes Jack R. Meyer, former president of Harvard Management Company:

Most people think they can find managers who can outperform, but most people are wrong.  I will say that 85 to 90 percent of managers fail to match their benchmarks.  Because managers have fees and incur transaction costs, you know that in the aggregate they are deleting value.

Burton Malkiel:

Active management as a whole cannot achieve gross returns exceeding the market as a whole and therefore they must, on average, underperform the indexes by the amount of these expense and transaction costs disadvantages.


RATIONAL EXUBERANCE – Business Reality Trumps Market Expectations

Warren Buffett:

The most that owners in the aggregate can earn between now and Judgment Day is what their businesses in the aggregate earn.

Bogle adds:

… History, if only we would take the trouble to look at it, reveals the remarkable, if essential, linkage between the cumulative long-term returns earned by business—the annual dividend yield plus the annual rate of earnings growth—and the cumulative returns earned by the U.S. stock market.

From 1900 to 2005, the average annual return on stocks was 9.6 percent, nearly equal to the investment return of 9.5 percent—4.5 percent from dividend yield and 5 percent from earnings growth.

The extra 0.1 percent can be related to a speculative return, or it may reflect “an upward long-term trend in stock valuations.”

The results from 106 years of compounding:

Each dollar initially invested in 1900 at an investment return of 9.5 percent grew by the close of 2005 to $15,062.

The initial amount is thus multiplied over 15,000 times.  Bogle calls this “the ultimate winner’s game.”

Borrowing from John Maynard Keynes, Bogle says there are two components that drive long-term stock market returns:  a fundamental component and a speculative component.  The fundamental driver of long-term stock market returns has averaged 9.5 percent, 4.5 percent from dividends and 5 percent from earnings growth.

The speculative component of long-term stock market returns is determined by changes in P/E multiples.  Some periods see P/E multiples rise, causing the average annual returns to be higher than what the fundamental component alone would dictate.  Other periods see P/E multiples fall, causing the average annual returns to be lower than what the fundamental component alone would dictate.

These speculative swings are due to many factors, including investor confidence, the level of interest rates, and changes in general price levels (high inflation or deflation).  However, the speculative swings cannot be predicted at all.  Bogle says:

After more than 55 years in this business, I have absolutely no idea how to forecast these swings… I’m not alone.  I don’t know anyone who has done so successfully, or even anyone who knows anyone who has done so.  In fact, 70 years of financial research shows that no one has done so.

Great investors such as Warren Buffett and Peter Lynch have made the same point: No one can forecast accurately with any sort of consistency.  By chance alone, there will always be some forecasters in any given period who turn out to be correct.  But it’s impossible to say ahead of time which forecasters those will be.  And when one does find, after the fact, the forecasters who were correct, that says nothing about which forecasters will be correct in the next period.

By the mid 1990’s, P/E multiples had been increasing for at least a decade and were high by historical standards, so one would have thought they would then go lower.  But they kept increasing until they reached a new record in 2000, far higher than ever before.  Similarly, in 2012 to 2013, assuming history was any guide, one would have thought that P/E multiples would decline for awhile, but that hasn’t been true at all.

In fact, if one assumes that most major central banks are going to keep rates very low for decades, then P/E multiples will continue to be much higher on average than has been the case historically.  As Warren Buffett remarked recently, near-zero rates indefinitely would mean P/E multiples of 50 or more.

Moreover, the return on invested capital—on the whole—may be structurally higher, since technology companies have become much more important in the U.S. and global economies.  All else equal, this also implies higher P/E multiples than has been the case historically.

Some of the smartest have been predicting lower U.S. stocks since 2012-2013, but the opposite has happened.  This is just one example out of many throughout history where very smart folks made highly confident financial forecasts that turned out to be completely wrong.

The rational investor simply buys and holds for the longer term, keeping fees and expenses at an absolute minimum, without trying to time the market.  This approach, buying and holding low-cost broad market index funds, will allow any investor to beat roughly 90-95% of all investors over the course of decades.  Writes Bogle:

So how do you cast your lot with business?  Simply by buying a portfolio that owns the shares of every business in the United States and then holding it forever.  It is a simple concept that guarantees you will win the investment game played by most other investors who—as a group—are guaranteed to lose.



After subtracting the costs of financial intermediation—all those management fees, all those brokerage commissions, all those sales loads, all those advertising costs, all those operating costs—the returns of investors as a group must, and will, and do fall short of the market return by an amount precisely equal to the aggregate amount of those costs.

It’s obvious based on humble arithmetic that:

(1) Beating the market BEFORE costs is a zero-sum game;

(2) Beating the market AFTER costs is a loser’s game.

Most individual investors choose mutual funds rather than individual stocks.  Bogle describes the costs:

In equity mutual funds, management fees and operating expenses—combined, called the expense ratio—average about 1.5 percent per year of fund assets.  Then add, say, another 0.5 percent in sales charges, assuming that a 5 percent initial sales charge is spread over a 10-year holding period.  If the shares are held for five years, the cost would be twice that figure—1 percent per year.

But then add a giant additional cost, all the more pernicious by being invisible.  I am referring to the hidden cost of portfolio turnover, estimated at a full 1 percent per year.

Bottom line

… the ‘all-in’ cost of equity fund ownership can come to as much as 3 percent to 3.5 percent per year.

Nonetheless, observes Bogle, most investors continue to ignore this reality, perhaps because “it flies in the face of their deep-seated beliefs, biases, overconfidence, and uncritical acceptance of the way that financial markets have worked, seemingly forever.”

Of course, financial intermediaries on the whole have very strong financial incentives to ignore the fact that low-cost index funds would be best for the vast majority of investors.  Bogles paraphrases Upton Sinclair:

It’s amazing how difficult it is for a man to understand something if he’s paid a small fortune not to understand it.

Moreover, it’s easy for investors to ignore the costs of investing, writes Bogle.  Many costs (including transaction costs, sales charges, and taxes) are largely hidden from view.  Moreover, if it has been a good period for the market—with reasonably high returns—then the ‘all-in’ costs of 2.5 or 3 percent per year can be much less noticeable.  Finally, investors tend to focus on short-term returns (a few years).  But it’s only after several decades that the enormous superiority of a low-cost index fund—versus the average equity mutual fund—is obvious.

Bogle gives an example: Assume, reasonably enough, that the stock market total return will be 8 percent per year over the coming 50 years.  The costs of the average mutual fund can be estimated at 2.5 percent per year.  After the first ten years, an index investment will be $21,600, while the average mutual fund investment will reach $17,100.  Many investors may not really notice it at this point.  But after 50 years, a simple index investment will reach $469,000, while the average mutual fund investment will reach $145,400.

Thus, after 50 years, costs for the mutual fund investor will have taken almost 70 percent of the index returns:

The investor, who put up 100 percent of the capital and assumed 100 percent of the risk, earned only 31 percent of the market return.  The system of financial intermediation, which put up zero percent of the capital and assumed zero percent of the risk, essentially confiscated 70 percent of that return—surely the lion’s share.  What you see here—and please don’t ever forget it!—is that over the long term, the miracle of compounding returns is overwhelmed by the tyranny of compounding costs.


THE GRAND ILLUSION – Surprise!  The Returns Reported by Mutual Funds Aren’t Actually Earned by Mutual Fund Investors

Historically, while mutual funds have trailed the index by roughly 2.5 percent per year on average, the average investor in mutual funds has done much worse (typically 2-3 percent worse, meaning the average investor in mutual funds trailed the market by 4.5 to 5.5 percent per year).

The average investor in mutual funds has repeatedly made two large mistakes: (1) buying after an extended period during which the stock market has done well, and selling after the stock market has done poorly; (2) buying mutual funds that have done well recently, and selling mutual funds that have done poorly recently.  This is just the opposite of what generally would help individual investors.  The late 1990’s are a good example given by Bogle:

As the market soared, investors poured ever larger sums of money into equity funds.  They invested a net total of only $18 billion in 1990 when stocks were cheap, but $420 billion in 1999 and 2000, when stocks were overvalued… What’s more, they also chose overwhelmingly the highest-risk growth funds, to the virtual exclusion of more conservative value-oriented funds.  While only 20 percent of their money went into risky aggressive growth funds in 1990, they poured fully 95 percent into such funds when they peaked during 1999 and early 2000.

Bogle continues:

When the annual returns of these aggressive funds are compounded over the full period, the deterioration is stunning: a cumulative fund return averaging more than 112 percent; a cumulative shareholder return averaging negative 4.5 percent.  That’s a lag of more than 117 percentage points!  This astonishing penalty, then, makes clear the perils of fund selection and timing.  It also illustrates the value of indexing and the necessity of setting a sound course and then sticking to it, come what may.

One great virtue of buying and holding low-cost index funds is that it can neutralize cognitive biases.  Cognitive biases are largely innate, and if left unchecked, they inevitably lead most investors to make the certain mistakes again and again, such as overconfidently extrapolating the recent past.  For more on cognitive biases, see:

Another virtue of index fund investing, as mentioned, is that it requires very little effort or time to implement.  The index fund investor need not worry about individual stocks or mutual funds, nor need she waste time trying to predict what the stock market or the economy will do in any given year.

Bogle quotes Charles Schwab, who himself prefers index funds:

It’s fun to play around… it’s human nature to try to select the right horse… (But) for the average person, I’m more of an indexer… The predictability is so high… For 10, 15, 20 years you’ll be in the 85th percentile of performance.  Why would you screw it up?

Finally, for investors with taxable accounts, index fund investors have had roughly a third the taxes as the average mutual fund investor.  This is due to the much lower turnover of index funds.



Bogle looks back (from 2007) to 1970 to see how many mutual funds from that year have done well over time.  In 1970, there were 355 mutual funds.  223 of those were no longer in business by 2007.  In addition to the 223 mutual funds that closed, there was another 60 mutual funds that significantly underperformed the S&P 500 Index by more than 1% per year.  So together, 283 funds—almost 80% of the original 355—were not long-term winners.  And another 48 funds provided returns that essentially matched the S&P 500 Index.

So that leaves only 24 mutual funds—one out of every 14—that did better than the S&P 500 Index from 1970 to 2007.  Writes Bogle:

Let’s face it: those are terrible odds!  What’s more, the margin of superiority of 15 of those 24 funds over the S&P 500 Index was less than 2 percentage points per year, a superiority that may be due as much to luck as skill.

Bogle says that there were nine long-term winners, funds that outpaced the market by 2 percentage points or more of annual return over 35 years.  But Bogle points out that six out of those nine long-term winners achieved their superior records many years ago, often when they were of much smaller size.  Increasing fund size is an inevitable drag on long-term investment performance.  Bogle says that one of these funds peaked in 1982, and two others peaked in 1983.  The other three peaked in 1993.

So there are only three funds out of the original 355—only 8/10 of 1%—that both survived and created an excellent long-term record that is still ongoing (as of 2007).

For the individual investor looking at the next 35 years, what are the odds of picking a mutual fund that will be able to clearly outpace the broad market, net of costs?  If the last 35 years are any guide, the odds may be 1-3% (or even less).

Thus, writes Bogle, a low-cost index fund tends to grow its margin of superiority over time.  After several decades, an investor in low-cost index funds is likely to be better off, net of costs, than roughly 90% of all investors.  After 50 years, an investor in low-cost index funds is likely to be better off, net of costs, than roughly 95% (or more) of all investors.

If one can be virtually guaranteed, by simple arithmetic, to outpace roughly 90-95% (or more) of all investors over time, with very little time or effort required, why wouldn’t one choose this option?  It is, in fact, the best option for the vast majority of investors.



Bogle shows a fascinating chart of the top 10 performing mutual funds from 1997 to 1999.  These top performing mutual funds had the following rankings in 2000 to 2002, out of a total of 851 mutual funds altogether:

  • 841
  • 832
  • 845
  • 791
  • 801
  • 798
  • 790
  • 843
  • 851
  • 793

If you think those rankings are bad, the average investor in these funds, on a cumulative basis, did much worse!  Over the six year period of 1997 to 2002, these funds had a net gain of 13 percent overall.  But investors in these funds, by piling in largely after the funds had gone up, and by selling largely after the funds had gone down, incurred a net loss of 57 percent overall.

The biggest mistake that most investors make is overconfidently extrapolating the recent past, i.e., buying after a fund has done well and selling after a fund has done poorly.  But market timing very rarely works except by luck.  (One approach that can work well is to have a portion in stocks and a portion in fixed-income and cash – with the portions decided ahead of time based on risk tolerance and age – and then rebalance to the target allocations periodically.)



Warren Buffett himself, arguably the best investor ever, has very consistently argued that the vast majority of all investors would be best off just buying and holding a simple, low-cost index fund.

By periodically investing in an index fund, for example, the know-nothing investor can actually out-perform most investment professionals. Paradoxically, when ‘dumb’ money acknowledges its limitations, it ceases to be dumb. — Warren Buffett, 1993 Letter to shareholders.


See also the 2014 Berkshire Letter, such as this passage (page 19):

If the investor, instead, fears price volatility, erroneously viewing it as a measure of risk, he may, ironically, end up doing some very risky things.  Recall, if you will, the pundits who six years ago bemoaned falling stock prices and advised investing in ‘safe’ Treasury bills or bank certificates of deposit.  People who heeded this sermon are now earning a pittance on sums they had previously expected would finance a pleasant retirement.  (The S&P 500 was then below 700; now it is about 2,100.)  If not for their fear of meaningless price volatility, these investors could have assured themselves of a good income for life by simply buying a very low-cost index fund whose dividends would trend upward over the years and whose principal would grow as well (with many ups and downs, to be sure).

Investors, of course, can, by their own behavior, make stock ownership highly risky.  And many do.  Active trading, attempts to ‘time’ market movements, inadequate diversification, the payment of high and unnecessary fees to managers and advisors, and the use of borrowed money can destroy the decent returns that a life-long owner of equities would otherwise enjoy.  Indeed, borrowed money has no place in the investor’s tool kit:  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.

The commission of the investment sins listed above is not limited to ‘the little guy.’  Huge institutional investors, viewed as a group, have long underperformed the unsophisticated index-fund investor who simply sits tight for decades.  A major reason has been fees: Many institutions pay substantial sums to consultants who, in turn, recommend high-fee managers.  And that is a fool’s game.

There are a few investment managers, of course, who are very good—though in the short run, it’s difficult to determine whether a great record is due to luck or talent.  Most advisors, however, are far better at generating high fees than they are at generating high returns.  In truth, their core competence is salesmanship.  Rather than listen to their siren songs, investors—large and small—should instead read Jack Bogle’s The Little Book of Common Sense Investing.




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:

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:




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.

The Piotroski F_Score

(Image:  Zen Buddha Silence by Marilyn Barbone.)

December 18, 2016

There are several ways to measure cheapness, including low EV/EBIT, low P/E, and low P/B.  Historically, these metrics have effectively identified groups of cheap stocks that outperform the market over time.  Many academic studies of value investing have focused on low P/B stocks (equivalently, high book-to-market stocks).

If you look at the cheapest group of low P/B stocks (quintile or decile), you find that, during most historical periods, this group has outperformed the market and has done so with less risk.  Here “risk” is defined—following Lakonishok, Shleifer, and Vishny—in terms of performance in bear markets, recessions, or other “bad states” of the world, and in terms of more traditional betas and standard deviations.  Link to the 1994 paper by Lakonishok, Schleifer, and Vishny:

And yet each individual low P/B stock is more likely than the average stock to underperform the market and is, in that sense, riskier.

Joseph Piotroski, a professor of accounting at the University of Chicago (currently at Stanford), noticed this disparity.  Even though low P/B stocks as a group have beaten the market during most historical time periods, Piotroski found that 57% of the low P/B stocks underperformed the market.  The outperformance of the low P/B group has been driven by only 43% of the stocks in the group, while it has been held back by the other 57%.

Given that low P/B stocks are often distressed, Piotroski wondered whether you could distinguish between “cheap and strong” companies and “cheap but weak” companies.  Piotroski invented a measure called the F_Score for this purpose.  Applying the F_Score to the group of low P/B stocks (the cheapest quintile) improved performance by 7.5% per year between 1976 and 1996.  The biggest improvements in performance were concentrated in cheap micro caps with no analyst coverage.



Piotroski invented his F_Score by thinking about what measures you would expect to distinguish between “cheap and strong” companies and “cheap but weak” companies.  He focused on recent changes in fundamentals that could be detected in a company’s financial statements.  Piotroski identified three areas to look for improving fundamentals:

  • Profitability and Cash Flow
  • Leverage and Liquidity
  • Operating Efficiency

Piotroski thought of four measures for profitability and cash flow, three for leverage and liquidity, and two for operating efficiency.  Each measure is binary, “1” for good and “0” for bad.  Thus for a given cheap company, a total score of “9”—a “1” on each of the nine measures—would indicate the maximum possible financial strength, whereas a “0” would indicate the minimum.  Because the F_Score is applied to cheap—often distressed—stocks, it’s reasonable to expect it to help in general.  And it does.

Link to Piotroski’s paper, “Value Investing: The Use of Historical Financial Statement Information to Separate Winners from Losers” (2002, University of Chicago Graduate School of Business):



As Piotroski notes, current profitability and cash flow are indicative of a firm’s ability to generate cash internally.  A distressed company showing a positive trend in earnings and cash flows is more likely to do well.

Piotroski has four measures for profitability and cash flow:

  • ROA measures current net income before extraordinary items.
  • CFO measures current cash flow from operations.
  • ΔROA measures this year’s ROA minus last year’s ROA.
  • ACCRUAL measures cash flow from operations versus net income before extraordinary items.

If ROA > 0—if net income before extraordinary items is positive—then the indicator variable F_ROA = 1, otherwise F_ROA = 0.

If CFO > 0—if cash flow from operations is positive—then the indicator variable F_CFO = 1, otherwise F_CFO = 0.

If ΔROA > 0—if net income before extraordinary items has increased from the prior year—then the indicator variable F_ΔROA = 1, otherwise F_ΔROA = 0.

If CFO > ROA—if cash flow from operations is greater than net income before extraordinary items—then F_ACCRUAL = 1, otherwise F_ACCRUAL = 0.

The logic is straightforward.  If the firm in question—which is cheap and likely to be distressed—is showing positive net income and cash flow, the firm is generating cash internally.  Similarly, an improvement in net income is a positive signal.  Finally, cash flow from operations being larger than net income before extraordinary items is positive:  distressed firms have an incentive to distort or “manage” earnings (to prevent covenant violations), but it is much harder to distort cash.



Because many cheap firms are distressed, an increase in debt, a decrease in liquidity, or the use of external financing is a bad signal.  Thus, Piotroski invented the following three simple measures:

  • ΔLEVER captures change in the firm’s long-term debt level.
  • ΔLIQUID measures change in the firm’s current ratio.
  • EQ_OFFER indicates whether the firm has issued common equity.

If ΔLEVER < 0—if the long-term debt level fell—then the indicator variable F_ΔLEVER = 1, otherwise F_ΔLEVER = 0.

If ΔLIQUID > 0—if the current ratio (current assets divided by current liabilities) improved—then the indicator variable F_ΔLIQUID = 1, otherwise F_ΔLIQUID = 0.

If the firm did not issue common equity, then the indicator variable EQ_OFFER = 1, otherwise EQ_OFFER = 0.

If a distressed firm does not have to raise external capital via an increase in long-term debt, that is a positive signal about its ability to generate sufficient cash internally.  Also, an improvement in liquidity bodes well for the firm’s ability to service current debt obligations.  If a distressed firm has to issue new equity to raise cash, that’s not a good signal, especially if the new equity is cheaply priced.



Piotroski looked at two key constructs in a decomposition of return on assets: gross margin ratio and asset turnover.  Both are signals of the efficiency of the firm’s operations.

  • ΔMARGIN measures the firm’s current gross margin ratio relative to the previous year.
  • ΔTURN measures the firm’s current asset turnover relative to the previous year.

If ΔMARGIN > 0—if the gross margin ratio has improved—then the indicator variable F_ΔMARGIN = 1, otherwise F_ΔMARGIN = 0.

If ΔTURN > 0—if asset turnover increased—then the indicator variable F_ΔTURN = 1, otherwise F_ΔTURN = 0.

An improvement in margins means a reduction in costs or an increase in the price of the firm’s product.  An increase in asset turnover—greater productivity of the asset base—can result from more efficient operations (greater sales/assets) or an increase in sales.  Increased sales may signify improved market conditions for the firm’s product.



The overall F_SCORE is the sum of the nine individual binary signals:



From the low P/B quintile, Piotroski isolated all the companies that had F_SCORES of 8 or 9.  This low P/B, high F_SCORE portfolio outperformed the low P/B quintile by 7.5% per year between 1976 and 1996.  The biggest improvements in performance were concentrated in cheap micro caps with no analyst coverage.



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:

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:




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.

Simple Quant Models Beat Experts in a Wide Variety of Areas

(Image:  Zen Buddha Silence by Marilyn Barbone.)

December 11, 2016


William Grove, David Zald, Boyd Lebow, Beth Snitz, and Chad Nelson did a meta-analysis (a study of studies) of 136 different studies of human experts vs. simple quant models.  Here is a link to the paper by Grove et al. (2000):

Here is what Grove et al. discovered about 136 different studies:

  • 64 clearly favored the model
  • 64 showed approximately the same result between the model and human judgment
  • 8 found in favor of human judgment

(NOTE:  All eight cases where human judgment prevailed had one thing in common:  the humans had more information than the quant models.)

Across all 136 studies that Grove et al. examined, experts were correct in 66.5% of the cases, while the quant models did significantly better with an average hit ratio of 73.2%.

Paul Meehl, one of the founding fathers of the importance of quant models versus human judgments, had this to say:

There is no controversy in social science which shows such a large body of qualitatively diverse studies coming out so uniformly in the same direction as this one… predicting everything from the outcomes of football games to the diagnosis of liver disease.  And when you can hardly come up with a half a dozen studies showing even a weak tendency in favor of the clinician, it is time to draw a practical conclusion.



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:

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:




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.