How To Master Yourself As An Investor

(Zen Buddha Silence by Marilyn Barbone)

(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 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.

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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.