Seeking Wisdom

(Image:  Zen Buddha Silence by Marilyn Barbone)

December 2, 2018

In his pursuit of wisdom, Peter Bevelin was inspired by Charlie Munger’s idea:

I believe in the discipline of mastering the best of what other people have ever figured out.

Bevelin was also influenced by Munger’s statement that Charles Darwin was one of the best thinkers who ever lived.  Despite the fact that many others had much higher IQ’s.  Bevelin:

Darwin’s lesson is that even people who aren’t geniuses can outthink the rest of mankind if they develop certain thinking habits.

(Photo by Maull and Polyblank (1855), via Wikimedia Commons)

In the spirit of Darwin and Munger, and with the goal of gaining a better understanding of human behavior, Bevelin read books in biology, psychology, neuroscience, physics, and mathematics.  Bevelin took extensive notes.  The result is the book, Seeking Wisdom: From Darwin to Munger.

Here’s the outline:

PART ONE:  WHAT INFLUENCES OUR THINKING

  • Our anatomy sets the limits for our behavior
  • Evolution selected the connections  that produce useful behavior for survival and reproduction
  • Adaptive behavior for survival and reproduction

PART TWO:  THE PSYCHOLOGY OF MISJUDGMENTS

  • Misjudgments explained by psychology
  • Psychological reasons for mistakes

PART THREE:  THE PHYSICS AND MATHEMATICS OF MISJUDGMENTS

  • Systems thinking
  • Scale and limits
  • Causes
  • Numbers and their meaning
  • Probabilities and number of possible outcomes
  • Scenarios
  • Coincidences and miracles
  • Reliability of case evidence
  • Misrepresentative evidence

PART FOUR:  GUIDELINES TO BETTER THINKING

  • Models of reality
  • Meaning
  • Simplification
  • Rules and filters
  • Goals
  • Alternatives
  • Consequences
  • Quantification
  • Evidence
  • Backward thinking
  • Risk
  • Attitudes

(Photo by Nick Webb)

 

Part One:  What Influences Our Thinking

OUR ANATOMY SETS THE LIMITS FOR OUR BEHAVIOR

Bevelin quotes Nobel Laureate Dr. Gerald Edelman:

The brain is the most complicated material object in the known universe.  If you attempted to count the number of connections, one per second, in the mantle of the brain (the cerebral cortex), you would finish counting 32 million years later.  But that is not the whole story.  The way the brain is connected—its neuroanatomical pattern—is enormously intricate.  Within this anatomy a remarkable set of dynamic events take place in hundredths of a second and the number of levels controlling these events, from molecules to behavior, is quite large.

Neurons can send signals—electrochemical pulses—to specific target cells over long distances.  These signals are sent by axons, thin fibers that extend from neurons to other parts of the brain.  Axons can be quite long.

(Illustration by ustas)

Some neurons emit electrochemical pulses constantly while other neurons are quiet most of the time.  A single axon can have several thousand synaptic connections.  When an electrochemical pulse travels along an axon and reaches a synapse, it causes a neurotransmitter (a chemical) to be released.

The human brain contains approximately 100 trillion synapses.  From wikipedia:

The functions of these synapses are very diverse: some are excitatory (exciting the target cell); others are inhibitory; others work by activating second messenger systems that change the internal chemistry of their target cells in complex ways.  A large number of synapses are dynamically modifiable; that is, they are capable of changing strength in a way that is controlled by the patterns of signals that pass through them.  It is widely believed that activity-dependent modification of synapses is the brain’s primary mechanism for learning and memory.

Most of the space in the brain is taken up by axons, which are often bundled together in what are called nerve fiber tracts.  A myelinated axon is wrapped in a fatty insulating sheath of myelin, which serves to greatly increase the speed of signal propagation.  (There are also unmyelinated axons).  Myelin is white, making parts of the brain filled exclusively with nerve fibers appear as light-colored white matter, in contrast to the darker-colored grey matter that marks areas with high densities of neuron cell bodies.

Genes, life experiences, and randomness determine how neurons connect.

Also, everything that happens in the brain involves many areas at once (the left brain versus right brain distinction is not strictly accurate).  This is part of why the brain is so flexible.  There are different ways for the brain to achieve the same result.

 

EVOLUTION SELECTED THE CONNECTIONS THAT PRODUCE USEFUL BEHAVIOR FOR SURVIVAL AND REPRODUCTION

Bevelin writes:

If certain connections help us interact with our environment, we use them more often than connections that don’t help us.  Since we use them more often, they become strengthened.

Evolution has given us preferences that help us classify what is good or bad.  When these values are satisfied (causing either pleasure or less pain) through the interaction with our environment, these neural connections are strengthened.  These values are reinforced over time because they give humans advantages for survival and reproduction in dealing with their environment.

(Illustration by goce risteski)

If a certain behavior is rewarding, the neural connections associated with that behavior get strengthened.  The next time the same situation is encountered, we feel motivated to respond in the way that we’ve learned brings pleasure (or reduces pain).  Bevelin:

We do things that we associate with pleasure and avoid things that we associate with pain.

 

ADAPTIVE BEHAVIOR FOR SURVIVAL AND REPRODUCTION

Bevelin:

The consequences of our actions reinforce certain behavior.  If the consequences were rewarding, our behavior is likely to be repeated.  What we consider rewarding is individual specific.  Rewards can be anything from health, money, job, reputation, family, status, or power.  In all of these activities, we do what works.  This is how we adapt.  The environment selects our future behavior.

Illustration by kalpis

Especially in a random environment like the stock market, it can be difficult to figure out what works and what doesn’t.  We may make a good decision based on the odds, but get a poor outcome.  Or we may make a bad decision based on the odds, but get a good outcome.  Only over the course of many decisions can we tell if our investment process is probably working.

 

Part Two:  The Psychology of Misjudgments

MISJUDGMENTS EXPLAINED BY PSYCHOLOGY

Illustration by intheskies

Bevelin lists 28 reasons for misjudgments and mistakes:

  1. Bias from mere association—automatically connecting a stimulus with pain or pleasure; including liking or disliking something associated with something bad or good.  Includes seeing situations as identical because they seem similar.  Also bias from Persian Messenger Syndrome—not wanting to be the carrier of bad news.
  2. Underestimating the power of incentives (rewards and punishment)—people repeat actions that result in rewards and avoid actions that they are punished for.
  3. Underestimating bias from own self-interest and incentives.
  4. Self-serving bias—overly positive view of our abilities and future.  Includes over-optimism.
  5. Self-deception and denial—distortion of reality to reduce pain or increase pleasure.  Includes wishful thinking.
  6. Bias from consistency tendency—being consistent with our prior commitments and ideas even when acting against our best interest or in the face of disconfirming evidence.  Includes Confirmation Bias—looking for evidence that confirms our actions and beliefs and ignoring or distorting disconfirming evidence.
  7. Bias from deprival syndrome—strongly reacting (including desiring and valuing more) when something we like and have (or almost have) is (or threatens to be) taken away or “lost.”  Includes desiring and valuing more what we can’t have or what is (or threatens to be) less available.
  8. Status quo bias and do-nothing syndrome—keeping things the way they are.  Includes minimizing effort and a preference for default options.
  9. Impatience—valuing the present more highly than the future.
  10. Bias from envy and jealousy.
  11. Distortion by contrast comparison—judging and perceiving the absolute magnitude of something not by itself but based only on its difference to something else presented closely in time or space or to some earlier adaptation level.  Also underestimating the consequences over time of gradual changes.
  12. The anchoring effect—People tend to use any random number as a baseline for estimating an unknown quantity, despite the fact that the unknown quantity is totally unrelated to the random number.  (People also overweigh initial information that is non-quantitative.)
  13. Over-influence by vivid or the most recent information.
  14. Omission and abstract blindness—only seeing stimuli we encounter or that grabs our attention, and neglecting important missing information or the abstract.  Includes inattentional blindness.
  15. Bias from reciprocation tendency—repaying in kind what others have done for or to us like favors, concessions, information, and attitudes.
  16. Bias from over-influence by liking tendency—believing, trusting, and agreeing with people we know and like.  Includes bias from over-desire for liking and social acceptance and for avoiding social disapproval.  Also bias from disliking—our tendency to avoid and disagree with people we don’t like.
  17. Bias from over-influence by social proof—imitating the behavior of many others or similar others.  Includes crowd folly.
  18. Bias from over-influence by authority—trusting and obeying a perceived authority or expert.
  19. The Narrative Fallacy (Bevelin uses the term “Sensemaking”)—constructing explanations that fit an outcome.  Includes being too quick in drawing conclusions.  Also Hindsight Bias: Thinking events that have happened were more predictable than they were.
  20. Reason-respecting—complying with requests merely because we’ve been given a reason.  Includes underestimating the power in giving people reasons.
  21. Believing first and doubting later—believing what is not true, especially when distracted.
  22. Memory limitations—remembering selectively and wrong.  Includes influence by suggestions.
  23. Do-something syndrome—acting without a sensible reason.
  24. Mental confusion from say-something syndrome—feeling a need to say something when we have nothing to say.
  25. Emotional arousal—making hasty judgments under the influence of intense emotions.  Includes exaggerating the emotional impact of future events.
  26. Mental confusion from stress.
  27. Mental confusion from physical or psychological pain, and the influence of chemicalsa li.
  28. Bias from over-influence by the combined effect of many psychological tendencies operating together.

 

PSYCHOLOGICAL REASONS FOR MISTAKES

Bevelin notes that his explanations for the 28 reasons for misjudgments is based on work by Charles Munger, Robert Cialdini, Richard Thaler, Robyn Dawes, Daniel Gilbert, Daniel Kahneman, and Amos Tversky.  All are psychologists except for Thaler (economist) and Munger (investor).

1. Mere Association

Bevelin:

Association can influence the immune system.  One experiment studied food aversion in mice.  Mice got saccharin-flavored water (saccharin has incentive value due to its sweet taste) along with a nausea-producing drug.  Would the mice show signs of nausea the next time they got saccharin water alone?  Yes, but the mice also developed infections.  It was known that the drug in addition to producing nausea, weakened the immune system, but why would saccharin alone have this effect?  The mere paring of the saccharin with the drug caused the mouse immune system to learn the association.  Therefore, every time the mouse encountered the saccharin, its immune system weakened making the mouse more vulnerable to infections.

If someone brings us bad news, we tend to associate that person with the bad news—and dislike them—even if the person didn’t cause the bad news.

2. Incentives (Reward and Punishment)

Incentives are extremely important.   Charlie Munger:

I think I’ve been in the top 5% of my age cohort all my life in understanding the power of incentives, and all my life I’ve underestimated it.  Never a year passes that I don’t get some surprise that pushes my limit a little farther.

Munger again:

From all business, my favorite case on incentives is Federal Express.  The heart and soul of their system—which creates the integrity of the product—is having all their airplanes come to one place in the middle of the night and shift all the packages from plane to plane.  If there are delays, the whole operation can’t deliver a product full of integrity to Federal Express customers.  And it was always screwed up.  They could never get it done on time.  They tried everything—moral suasion, threats, you name it.  And nothing worked.  Finally, somebody got the idea to pay all these people not so much an hour, but so much a shift—and when it’s all done, they can all go home.  Well, their problems cleared up over night.

People can learn the wrong incentives in a random environment like the stock market.  A good decision based on the odds may yield a bad result, while a bad decision based on the odds may yield a good result.  People tend to become overly optimistic after a success (even if it was good luck) and overly pessimistic after a failure (even if it was bad luck).

3. Self-interest and Incentives

“Never ask the barber if you need a haircut.”

Munger has commented that commissioned sales people, consultants, and lawyers have a tendency to serve the transaction rather than the truth.  Many others—including bankers and doctors—are in the same category.  Bevelin quotes the American actor Walter Matthau:

“My doctor gave me six months to live.  When I told him I couldn’t pay the bill, he gave me six more months.”

If they make unprofitable loans, bankers may be rewarded for many years while the consequences of the bad loans may not occur for a long time.

When designing a system, careful attention must be paid to incentives.  Bevelin notes that a new program was put in place in New Orleans: districts that showed improvement in crime statistics would receive rewards, while districts that didn’t faced cutbacks and firings.  As a result, in one district, nearly half of all serious crimes were re-classified as minor offences and never fully investigated.

4. Self-serving Tendencies and Overoptimism 

We tend to overestimate our abilities and future prospects when we are knowledgeable on a subject, feel in control, or after we’ve been successful.

Bevelin again:

When we fail, we blame external circumstances or bad luck.  When others are successful, we tend to credit their success to luck and blame their failures on foolishness.  When our investments turn into losers, we had bad luck.  When they turn into winners, we are geniuses.  This way we draw the wrong conclusions and don’t learn from our mistakes.  We also underestimate luck and randomness in outcomes.

5. Self-deception and Denial

Munger likes to quote Demosthenes:

Nothing is easier than self-deceit.  For what each man wishes, that he also believes to be true.

People have a strong tendency to believe what they want to believe.  People prefer comforting illusions to painful truths.

Richard Feynman:

The first principle is that you must not fool yourself—and you are the easiest person to fool.

6. Consistency

Bevelin:

Once we’ve made a commitment—a promise, a choice, taken a stand, invested time, money, or effort—we want to remain consistent.  We want to feel that we’ve made the right decision.  And the more we have invested in our behavior the harder it is to change.

The more time, money, effort, and pain we invest in something, the more difficulty we have at recognizing a mistaken commitment.  We don’t want to face the prospect of a big mistake.

For instance, as the Vietnam War became more and more a colossal mistake, key leaders found it more and more difficult to recognize the mistake and walk away.  The U.S. could have walked away years earlier than it did, which would have saved a great deal of money and thousands of lives.

Bevelin quotes Warren Buffett:

What the human being is best at doing is interpreting all new information so that their prior conclusions remain intact.

Even scientists, whose job is to be as objective as possible, have a hard time changing their minds after they’ve accepted the existing theory for a long time.  Physicist Max Planck:

A new scientific truth does not triumph by convincing its opponents and making them see the light, but rather because its opponents eventually die and a new generation grows up that is familiar with it.

7. Deprival Syndrome

Bevelin:

When something we like is (or threatens to be) taken away, we often value it higher.  Take away people’s freedom, status, reputation, money, or anything they value, and they get upset… The more we like what is taken away or the larger the commitment we’ve made, the more upset we become.  This can create hatreds, revolts, violence, and retaliations.

Fearing deprival, people will be overly conservative or will engage in cover-ups.

A good value investor is wrong roughly 40 percent of the time.  However, due to deprival syndrome and loss aversion—the pain of a loss is about 2 to 2.5 times greater than the pleasure of an equivalent gain—investors have a hard time admitting their mistakes and moving on.  Admitting a mistake means accepting a loss of money and also recognizing our own fallibility.

Furthermore, deprival syndrome makes us keep trying something if we’ve just experienced a series of near misses.  We feel that “we were so close” to getting some reward that we can’t give up now, even if the reward may not be worth the expected cost.

Finally, the harder it is to get something, the  more value we tend to place on it.

8. Status Quo and Do-Nothing Syndrome

We feel worse about a harm or loss if it results from our action than if it results from our inaction.  We prefer the default option—what is selected automatically unless we change it.  However, as Bevelin points out, doing nothing is still a decision and the cost of doing nothing could be greater than the cost of taking an action.

In countries where being an organ donor is the default choice, people strongly prefer to be organ donors.  But in countries where not being an organ donor is the default choice, people prefer not to be organ donors.  In each case, most people simply go with the default option—the status quo.  But society is better off if most people are organ donors.

9. Impatience

We value the present more than the future.  We often seek pleasure today at the cost of a potentially better future.  It’s important to understand that pain and sacrifice today—if done for the right reasons—can lead to greater happiness in the future.

10. Envy and Jealousy

Charlie Munger and Warren Buffett often point out that envy is a stupid sin because—unlike other sins like gluttony—there’s no upside.  Also, jealousy is among the top three motives for murder.

It’s best to set goals and work towards them without comparing ourselves to others.  Partly by chance, there are always some people doing better and some people doing worse.

11. Contrast Comparison

The classic demonstration of contrast comparison is to stick one hand in cold water and the other hand in warm water.  Then put both hands in a buck with room temperature water.  Your cold hand will feel warm while your warm hand will feel cold.

Bevelin writes:

We judge stimuli by differences and changes and not absolute magnitudes.  For example, we evaluate stimuli like temperature, loudness, brightness, health, status, or prices based on their contrast or difference from a reference point (the prior or concurrent stimuli or what we have become used to).  This reference point changes with new experiences and context.

How we value things depends on what we compare them with.

Salespeople, after selling the main item, often try to sell add-ons, which seem cheap by comparison.  If you buy a car for $50,000, then adding an extra $1,000 for leather doesn’t seem like much.  If you buy a computer for $1,500, then adding an extra $50 seems inconsequential.

Bevelin observes:

The same thing may appear attractive when compared to less attractive things and unattractive when compared to more attractive things.  For example, studies show that a person of average attractiveness is seen as less attractive when compared to more attractive others.

One trick some real estate agents use is to show the client a terrible house at an absurdly high price first, and then show them a merely mediocre house at a somewhat high price.  The agent often makes the sale.

Munger has remarked that some people enter into a bad marriage because their previous marriage was terrible.  These folks make the mistake of thinking that what is better based on their own limited experience is the same as what is better based on the experience of many different people.

Another issue is that something can gradually get much worse over time, but we don’t notice it because each increment is small.  It’s like the frog in water where the water is slowly brought to the boiling point.  For instance, the behavior of some people may get worse and worse and worse.  But we fail to notice because the change is too gradual.

12. Anchoring

The anchoring effect:  People tend to use any random number as a baseline for estimating an unknown quantity, despite the fact that the unknown quantity is totally unrelated to the random number.  (People also overweigh initial information that is non-quantitative.)

Daniel Kahneman and Amos Tversky did one experiment where they spun a wheel of fortune, but they had secretly programmed the wheel so that it would stop on 10 or 65.   After the wheel stopped, participants were asked to estimate the percentage of African countries in the UN.   Participants who saw “10” on the wheel guessed 25% on average, while participants who saw “65” on the wheel guessed 45% on average, a huge difference.

Behavioral finance expert James Montier has run his own experiment on anchoring.   People are asked to write down the last four digits of their phone number.   Then they are asked whether the number of doctors in their capital city is higher or lower than the last four digits of their phone number.   Results:  Those whose last four digits were greater than 7000 on average report 6762 doctors, while those with telephone numbers below 2000 arrived at an average 2270 doctors.  (James Montier, Behavioural Investing, Wiley 2007, page 120)

Those are just two experiments out of many.  The anchoring effect is “one of the most reliable and robust results of experimental psychology,” says Kahneman.  Furthermore, Montier observes that the anchoring effect is one reason why people cling to financial forecasts, despite the fact that most financial forecasts are either wrong, useless, or impossible to time.

When faced with the unknown, people will grasp onto almost anything.  So it is little wonder that an investor will cling to forecasts, despite their uselessness. 

13. Vividness and Recency

Bevelin explains:

The more dramatic, salient, personal, entertaining, or emotional some information, event, or experience is, the more influenced we are.  For example, the easier it is to imagine an event, the more likely we are to think that it will happen.

We are easily influenced when we are told stories because we relate to stories better than to logic or fact.  We love to be entertained.  Information we receive directly, through our eyes or ears has more impact than information that may have more evidential value.  A vivid description from a friend or family member is more believable than true evidence.  Statistical data is often overlooked.  Studies show that jurors are influenced by vivid descriptions.  Lawyers try to present dramatic and memorable testimony.

The media capitalizes on negative events—especially if they are vivid—because negative news sells.  For instance, even though the odds of being in a plane crash are infinitesimally low—one in 11 million—people become very fearful when a plane crash is reported in the news.  Many people continue to think that a car is safer than a plane, but you are over 2,000 times more likely to be in a car crash than a plane crash.  (The odds of being in a car crash are one in 5,000.)

14. Omission and Abstract Blindness

We see the available information.  We don’t see what isn’t reported.  Missing information doesn’t draw our attention.  We tend not to think about other possibilities, alternatives, explanations, outcomes, or attributes.  When we try to find out if one thing causes another, we only see what happened, not what didn’t happen.  We see when a procedure works, not when it doesn’t work.  When we use checklists to find out possible reasons for why something doesn’t work, we often don’t see that what is not on the list in the first place may be the reason for the problem.

Often we don’t see things right in front of us if our attention is focused elsewhere.

15. Reciprocation

Munger:

The automatic tendency of humans to reciprocate both favors and disfavors has long been noticed as it is in apes, monkeys, dogs, and many less cognitively gifted animals.  The tendency facilitates group cooperation for the benefit of members.

Unfortunately, hostility can get extreme.  But we have the ability to train ourselves.  Munger:

The standard antidote to one’s overactive hostility is to train oneself to defer reaction.  As my smart friend Tom Murphy so frequently says, ‘You can always tell the man off tomorrow, if it is such a good idea.’

Munger then notes that the tendency to reciprocate favor for favor is also very intense.  On the whole, Munger argues, the reciprocation tendency is a positive:

Overall, both inside and outside religions, it seems clear to me that Reciprocation Tendency’s constructive contributions to man far outweigh its destructive effects…

And the very best part of human life probably lies in relationships of affection wherein parties are more interested in pleasing than being pleased—a not uncommon outcome in display of reciprocate-favor tendency.

Guilt is also a net positive, asserts Munger:

…To the extent the feeling of guilt has an evolutionary base, I believe the most plausible cause is the mental conflict triggered in one direction by reciprocate-favor tendency and in the opposite direction by reward superresponse tendency pushing one to enjoy one hundred percent of some good thing… And if you, like me… believe that, averaged out, feelings of guilt do more good than harm, you may join in my special gratitude for reciprocate-favor tendency, no matter how unpleasant you find feelings of guilt.

16. Liking and Disliking

Munger:

One very practical consequence of Liking/Loving Tendency is that it acts as a conditioning device that makes the liker or lover tend (1) to ignore faults of, and comply with wishes of, the object of his affection, (2) to favor people, products, and actions merely associated with the object of his affection [this is also due to Bias from Mere Association] and (3) to distort other facts to facilitate love.

We’re naturally biased, so we have to be careful in some situations.

On the other hand, Munger points out that loving admirable persons and ideas can be very beneficial.

…a man who is so constructed that he loves admirable persons and ideas with a special intensity has a huge advantage in life.  This blessing came to both Buffett and myself in large measure, sometimes from the same persons and ideas.  One common, beneficial example for us both was Warren’s uncle, Fred Buffett, who cheerfully did the endless grocery-store work that Warren and I ended up admiring from a safe distance.  Even now, after I have known so many other people, I doubt if it is possible to be a nicer man than Fred Buffett was, and he changed me for the better.

Warren Buffett:

If you tell me who your heroes are, I’ll tell you how you’re gonna turn out.  It’s really important in life to have the right heroes.  I’ve been very lucky in that I’ve probably had a dozen or so major heroes.  And none of them have ever let me down.  You want to hang around with people that are better than you are.  You will move in the direction of the crowd that you associate with.

Disliking: Munger notes that Switzerland and the United States have clever political arrangements to “channel” the hatreds and dislikings of individuals and groups into nonlethal patterns including elections.

But the dislikings and hatreds never go away completely…  And we also get the extreme popularity of very negative political advertising in the United States.

Munger explains:

Disliking/Hating Tendency also acts as a conditioning device that makes the disliker/hater tend to (1) ignore virtues in the object of dislike, (2) dislike people, products, and actions merely associated with the object of dislike, and (3) distort other facts to facilitate hatred.

Distortion of that kind is often so extreme that miscognition is shockingly large…

17. Social Proof

Munger comments:

The otherwise complex behavior of man is much simplified when he automatically thinks and does what he observes to be thought and done around him.  And such followership often works fine…

Psychology professors love Social-Proof Tendency because in their experiments it causes ridiculous results.  For instance, if a professor arranges for some stranger to enter an elevator wherein ten ‘compliance practitioners’ are all standing so that they face the rear of the elevator, the stranger will often turn around and do the same.

Of course, like the other tendencies, Social Proof has an evolutionary basis.  If the crowd was running in one direction, typically your best response was to follow.

But, in today’s world, simply copying others often doesn’t make sense.  Munger:

And in the highest reaches of business, it is not at all uncommon to find leaders who display followership akin to that of teenagers.  If one oil company foolishly buys a mine, other oil companies often quickly join in buying mines.  So also if the purchased company makes fertilizer.  Both of these oil company buying fads actually bloomed, with bad results.

Of course, it is difficult to identify and correctly weigh all the possible ways to deploy the cash flow of an oil company.  So oil company executives, like everyone else, have made many bad decisions that were triggered by discomfort from doubt.  Going along with social proof provided by the action of other oil companies ends this discomfort in a natural way.

Munger points out that Social Proof can sometimes be constructive:

Because both bad and good behavior are made contagious by Social-Proof Tendency, it is highly important that human societies (1) stop any bad behavior before it spreads and (2) foster and display all good behavior.

It’s vital for investors to be able to think independently.  As Ben Graham says:

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

18. Authority

A disturbingly significant portion of copilots will not correct obvious errors made by the pilot during simulation exercises.  There are also real world examples of copilots crashing planes because they followed the pilot mindlessly.  Munger states:

…Such cases are also given attention in the simulator training of copilots who have to learn to ignore certain really foolish orders from boss pilots because boss pilots will sometimes err disastrously.  Even after going through such a training regime, however, copilots in simulator exercises will too often allow the simulated plane to crash because of some extreme and perfectly obvious simulated error of the chief pilot.

Psychologist Stanley Milgram wanted to understand why so many seemingly normal and decent people engaged in horrific, unspeakable acts during World War II.  Munger:

[Milgram] decided to do an experiment to determine exactly how far authority figures could lead ordinary people into gross misbehavior.  In this experiment, a man posing as an authority figure, namely a professor governing a respectable experiment, was able to trick a great many ordinary people into giving what they had every reason to believe were massive electric shocks that inflicted heavy torture on innocent fellow citizens…

Almost any intelligent person with my checklist of psychological tendencies in his hand would, by simply going down the checklist, have seen that Milgram’s experiment involved about six powerful psychological tendencies acting in confluence to bring about his extreme experimental result.  For instance, the person pushing Milgram’s shock lever was given much social proof from presence of inactive bystanders whose silence communicated that his behavior was okay…

Bevelin quotes the British novelist and scientist Charles Percy Snow:

When you think of the long and gloomy history of man, you will find more hideous crimes have been committed in the name of obedience than have ever been committed in the name of rebellion.

19. The Narrative Fallacy (Sensemaking)

(Bevelin uses the term “sensemaking,” but “narrative fallacy” is better, in my view.)  In The Black Swan, Nassim Taleb writes the following about the narrative fallacy:

The narrative fallacy addresses our limited ability to look at sequences of facts without weaving an explanation into them, or, equivalently, forcing a logical link, an arrow of relationship, upon them.  Explanations bind facts together.  They make them all the more easily remembered;  they help them make more sense.  Where this propensity can go wrong is when it increases our impression of understanding.

The narrative fallacy is central to many of the biases and misjudgments mentioned by Charlie Munger.  (In his great book, Thinking, Fast and Slow, Daniel Kahneman discusses the narrative fallacy as a central cognitive bias.)  The human brain, whether using System 1 (intuition) or System 2 (logic), always looks for or creates logical coherence among random data.  Often System 1 is right when it assumes causality; thus, System 1 is generally helpful, thanks to evolution.  Furthermore, System 2, by searching for underlying causes or coherence, has, through careful application of the scientific method over centuries, developed a highly useful set of scientific laws by which to explain and predict various phenomena.

The trouble comes when the data or phenomena in question are highly random—or inherently unpredictable (at least for the time being).  In these areas, System 1 makes predictions that are often very wrong.  And even System 2 assumes necessary logical connections when there may not be any—at least, none that can be discovered for some time.

Note:  The eighteenth century Scottish philosopher (and psychologist) David Hume was one of the first to clearly recognize the human brain’s insistence on always assuming necessary logical connections in any set of data or phenomena.

If our goal is to explain certain phenomena scientifically, then we have to develop a testable hypothesis about what will happen (or what will happen with probability x) under specific, relevant conditions.  If our hypothesis can’t accurately predict what will happen under specific, relevant conditions, then our hypothesis is not a valid scientific explanation.

20. Reason-respecting

We are more likely to comply with a request if people give us a reason—even if we don’t understand the reason or if it’s wrong.  In one experiment, a person approaches people standing in line waiting to use a copy machine and says, “Excuse me, I have 5 pages.  May I use the Xerox machine because I have to make some copies?”  Nearly everyone agreed.

Bevelin notes that often the word “because” is enough to convince someone, even if no actual reason is given.

21. Believe First and Doubt Later

We are not natural skeptics.  We find it easy to believe but difficult to doubt.  Doubting is active and takes effort.

Bevelin continues:

Studies show that in order to understand some information, we must first accept it as true… We first believe all information we understand and only afterwards and with effort do we evaluate, and if necessary, un-believe it.

Distraction, fatigue, and stress tend to make us less likely to think things through and more likely to believe something that we normally might doubt.

When it comes to detecting lies, many (if not most) people are only slightly better than chance.  Bevelin quotes Michel de Montaigne:

If falsehood, like truth, had only one face, we would be in better shape.  For we would take as certain the opposite of what the liar said.  But the reverse of truth has a hundred thousand shapes and a limitless field.

22. Memory Limitations

Bevelin:

Our memory is selective.  We remember certain things and distort or forget others.  Every time we recall an event, we reconstruct our memories.  We only remember fragments of our real past experiences.  Fragments influenced by what we have learned, our experiences, beliefs, mood, expectations, stress, and biases.

We remember things that are dramatic, fearful, emotional, or vivid.  But when it comes to learning in general—as opposed to remembering—we learn better when we’re in a positive mood.

Human memory is flawed to the point that eyewitness identification evidence has been a significant cause of wrongful convictions.  Moreover, leading and suggestive questions can cause misidentification.  Bevelin:

Studies show that it is easy to get a witness to believe they saw something when they didn’t.  Merely let some time pass between their observation and the questioning.  Then give them false or emotional information about the event.

23. Do-something Syndrome

Activity is not the same thing as results.  Most people feel impelled by boredom or hubris to be active.  But many things are not worth doing.

If we’re long-term investors, then nearly all of the time the best thing for us to do is nothing at all (other than learn).  This is especially true if we’re tired, stressed, or emotional.

24. Say-something Syndrome

Many people have a hard time either saying nothing or saying, “I don’t know.”  But it’s better for us to say nothing if we have nothing to say.  It’s better to admit “I don’t know” rather than pretend to know.

25. Emotions

Bevelin writes:

We saw under loss aversion and deprival that we put a higher value on things we already own than on the same things if we don’t own them.  Sadness reverses this effect, making us willing to accept less money to sell something than we would pay to buy it.

It’s also worth repeating: If we feel emotional, it’s best to defer important decisions whenever possible.

26. Stress

A study showed that business executives who are committed to their work and who have a positive attitude towards challenges—viewing them as opportunities for growth—do not get sick from stress.  Business executives who lack such commitment or who lack a positive attitude towards challenges are more likely to get sick from stress.

Stress itself is essential to life.  We need challenges.  What harms us is not stress but distress—unnecessary anxiety and unhelpful trains of thought.  Bevelin quotes the stoic philosopher Epictetus:

Happiness and freedom begin with a clear understanding of one principle: Some things are within our control, and some things are not.  It is only after you have faced up to this fundamental rule and learned to distinguish between what you can and can’t control that inner tranquility and outer effectiveness become possible.

27. Pain and Chemicals

People struggle to think clearly when they are in pain or when they’re drunk or high.

Munger argues that if we want to live a good life, first we should list the things that can ruin a life.  Alcohol and drugs are near the top of the list.  Self-pity and a poor mental attitude will also be on that list.  We can’t control everything that happens, but we can always control our mental attitude.  As the Austrian psychiatrist and Holocaust survivor Viktor Frankl said:

Everything can be taken from a man but one thing: the last of the human freedoms—to choose one’s attitude in any given set of circumstances, to choose one’s own way.

28. Multiple Tendencies

Often multiple psychological tendencies operate at the same time.  Bevelin gives an example where the CEO makes a decision and expects the board of directors to go along without any real questions.  Bevelin explains:

Apart from incentive-caused bias, liking, and social approval, what are some other tendencies that operate here?  Authority—the CEO is the authority figure whom directors tend to trust and obey.  He may also make it difficult for those who question him.  Social proof—the CEO is doing dumb things but no one else is objecting so all directors collectively stay quiet—silence equals consent; illusions of the group as invulnerable and group pressure (loyalty) may also contribute.  Reciprocation—unwelcome information is withheld since the CEO is raising the director fees, giving them perks, taking them on trips or letting them use the corporate jet.  Association and Persian Messenger Syndrome—a single director doesn’t want to be the carrier of bad news.  Self-serving tendencies and optimism—feelings of confidence and optimism: many boards also select new directors who are much like themselves; that share similar ideological viewpoints.  Deprival—directors don’t want to lose income and status.  Respecting reasons no matter how illogical—the CEO gives them reasons.  Believing first and doubting later—believing what the CEO says even if not true, especially when distracted.  Consistency—directors want to be consistent with earlier decisions—dumb or not.

 

Part Three:  The Physics and Mathematics of Misjudgments

SYSTEMS THINKING

  • Failing to consider that actions have both intended and unintended consequences.  Includes failing to consider secondary and higher order consequences and inevitable implications.
  • Failing to consider the whole system in which actions and reactions take place, the important factors that make up the system, their relationships and effects of changes on system outcome.
  • Failing to consider the likely reaction of others—what is best to do may depend on what others do.
  • Failing to consider the implications of winning a bid—overestimating value and paying too much.
  • Overestimating predictive ability or using unknowable factors in making predictions.

 

SCALE AND LIMITS

  • Failing to consider that changes in size or time influence form, function, and behavior.
  • Failing to consider breakpoints, critical thresholds, or limits.
  • Failing to consider constraints—that a system’s performance is constrained by its weakest link.

 

CAUSES

  • Not understanding what causes desired results.
  • Believing cause resembles its effect—that a big effect must have a big or complicated cause.
  • Underestimating the influence of randomness in bad or good outcomes.
  • Mistaking an effect for its cause.  Includes failing to consider that many effects may originate from one common root cause.
  • Attributing outcome to a single cause when there are multiple causes.
  • Mistaking correlation for cause.
  • Failing to consider that an outcome may be consistent with alternative explanations.
  • Drawing conclusions about causes from selective data.  Includes identifying the wrong cause because it seems the obvious one based on a single observed effect.  Also failing to consider information or evidence that is missing.
  • Not comparing the difference in conditions, behavior, and factors between negative and positive outcomes in similar situations when explaining an outcome.

 

NUMBERS AND THEIR MEANING

  • Looking at isolated numbers—failing to consider relationships and magnitudes.  Includes not using basic math to count and quantify.  Also not differentiating between relative and absolute risk.
  • Underestimating the effect of exponential growth.
  • Underestimating the time value of money.

 

PROBABILITIES AND NUMBER OF POSSIBLE OUTCOMES

  • Underestimating risk exposure in situations where relative frequency (or comparable data) and/or magnitude of consequences is unknown or changing over time.
  • Underestimating the number of possible outcomes for unwanted events.  Includes underestimating the probability and severity of rate or extreme events.
  • Overestimating the chance of rare but widely publicized and highly emotional events and underestimating the chance of common but less publicized events.
  • Failing to consider both probabilities and consequences (expected value).
  • Believing events where chance plays a role are self-correcting—that previous outcomes of independent events have predictive value in determining future outcomes.
  • Believing one can control the outcome of events where chance is involved.
  • Judging financial decisions by evaluating gains and losses instead of final state of wealth and personal value.
  • Failing to consider the consequences of being wrong.

 

SCENARIOS

  • Overestimating the probability of scenarios where all of a series of steps must be achieved for a wanted outcome.  Also underestimating opportunities for failure and what normally happens in similar situations.
  • Underestimating the probability of systems failure—scenarios composed of many parts where system failure can happen one way or another.  Includes failing to consider that time horizon changes probabilities.  Also assuming independence when it is not present and/or assuming events are equally likely when they are not.
  • Not adding a factor of safety for known and unknown risks.  Size of factor depends on the consequences of failure, how well the risks are understood, systems characteristics, and degree of control.

 

COINCIDENCES AND MIRACLES

  • Underestimating that surprises and improbable events happen, somewhere, sometime, to someone, if they have enough opportunities (large enough size or time) to happen.
  • Looking for meaning, searching for causes, and making up patterns for chance events, especially events that have emotional implications.
  • Failing to consider cases involving the absence of a cause or effect.

 

RELIABILITY OF CASE EVIDENCE

  • Overweighing individual case evidence and under-weighing the prior probability (probability estimate of an event before considering new evidence that might change it) considering for example, the base rate (relative frequency of an attribute or event in a representative comparison group), or evidence from many similar cases.  Includes failing to consider the probability of a random match, and the probability of a false positive and a false negative.  Also failing to consider a relevant comparison population that bears the characteristic we are seeking.

 

MISREPRESENTATIVE EVIDENCE

  • Failing to consider changes in factors, context, or conditions when using past evidence to predict likely future outcomes.  Includes not searching for explanations to why a past outcome happened, what is required to make the past record continue, and what forces can change it.
  • Overestimating evidence from a single case or small or unrepresentative samples.
  • Underestimating the influence of chance in performance (success and failure)
  • Only seeing positive outcomes—paying little or no attention to negative outcomes and prior probabilities.
  • Failing to consider variability of outcomes and their frequency.
  • Failing to consider regression—in any series of events where chance is involved, unique outcomes tend to regress back to the average outcome.

 

BOOLE MICROCAP FUND

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

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

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

The 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: jb@boolefund.com

 

 

 

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

Buffett’s Best: Microcap Cigar Butts

(Image:  Zen Buddha Silence by Marilyn Barbone)

November 25, 2018

Warren Buffett, the world’s greatest investor, earned the highest returns of his career from microcap cigar butts.  Buffett wrote in the 2014 Berkshire Letter:

My cigar-butt strategy worked very well while I was managing small sums.  Indeed, the many dozens of free puffs I obtained in the 1950’s made the decade by far the best of my life for both relative and absolute performance.

Even then, however, I made a few exceptions to cigar butts, the most important being GEICO.  Thanks to a 1951 conversation I had with Lorimer Davidson, a wonderful man who later became CEO of the company, I learned that GEICO was a terrific business and promptly put 65% of my $9,800 net worth into its shares.  Most of my gains in those early years, though, came from investments in mediocre companies that traded at bargain prices.  Ben Graham had taught me that technique, and it worked.

But a major weakness in this approach gradually became apparent:  Cigar-butt investing was scalable only to a point.  With large sums, it would never work well…

Before Buffett led Berkshire Hathaway, he managed an investment partnership from 1957 to 1970 called Buffett Partnership Ltd. (BPL).  While running BPL, Buffett wrote letters to limited partners filled with insights (and humor) about investing and business.  Jeremy C. Miller has written a great book— Warren Buffett’s Ground Rules (Harper, 2016)—summarizing the lessons from Buffett’s partnership letters.

This blog post considers a few topics related to microcap cigar butts:

  • Net Nets
  • Dempster: The Asset Conversion Play
  • Liquidation Value or Earnings Power?
  • Mean Reversion for Cigar Butts
  • Focused vs. Statistical
  • The Rewards of Psychological Discomfort
  • Conclusion

 

NET NETS

Here Miller quotes the November 1966 letter, in which Buffett writes about valuing the partnership’s controlling ownership position in a cigar-butt stock:

…Wide changes in the market valuations accorded stocks at some point obviously find reflection in the valuation of businesses, although this factor is of much less importance when asset factors (particularly when current assets are significant) overshadow earnings power considerations in the valuation process…

Ben Graham’s primary cigar-butt method was net nets.  Take net current asset value minus ALL liabilities, and then only buy the stock at 2/3 (or less) of that level.  If you buy a basket (at least 20-30) of such stocks, then given enough time (at least a few years), you’re virtually certain to get good investment results, predominantly far in excess of the broad market.

A typical net-net stock might have $30 million in cash, with no debt, but have a market capitalization of $20 million.  Assume there are 10 million shares outstanding.  That means the company has $3/share in net cash, with no debt.  But you can buy part ownership of this business by paying only $2/share.  That’s ridiculously cheap.  If the price remained near those levels, you could effectively buy $1 million in cash for $667,000—and repeat the exercise many times.

Of course, a company that cheap almost certainly has problems and may be losing money.  But every business on the planet, at any given time, is in either one of two states:  it is having problems, or it will be having problems.  When problems come—whether company-specific, industry-driven, or macro-related—that often causes a stock to get very cheap.

The key question is whether the problems are temporary or permanent.  Statistically speaking, many of the problems are temporary when viewed over the subsequent 3 to 5 years.  The typical net-net stock is so extremely cheap relative to net tangible assets that usually something changes for the better—whether it’s a change by management, or a change from the outside (or both).  Most net nets are not liquidated, and even those that are still bring a profit in many cases.

The net-net approach is one of the highest-returning investment strategies ever devised.  That’s not a surprise because net nets, by definition, are absurdly cheap on the whole, often trading below net cash—cash in the bank minus ALL liabilities.

Buffett called Graham’s net-net method the cigar-butt approach:

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

Link: http://intelligentinvestorclub.com/downloads/Warren-Buffett-Florida-Speech.pdf

(Photo by Sky Sirasitwattana)

When running BPL, Buffett would go through thousands of pages of Moody’s Manuals (and other such sources) to locate just one or a handful of microcap stocks trading at less than liquidation value.  Other leading value investors have also used this technique.  This includes Charlie Munger (early in his career), Walter Schloss, John Neff, Peter Cundill, and Marty Whitman, to name a few.

The cigar-butt approach is also called deep value investing.  This normally means finding a stock that is available below liquidation value, or at least below net tangible book value.

When applying the cigar-butt method, you can either do it as a statistical group approach, or you can do it in a focused manner.  Walter Schloss achieved one of the best long-term track records of all time—near 21% annually (gross) for 47 years—using a statistical group approach to cigar butts.  Schloss typically had a hundred stocks in his portfolio, most of which were trading below tangible book value.

At the other extreme, Warren Buffett—when running BPL—used a focused approach to cigar butts.  Dempster is a good example, which Miller explores in detail in his book.

 

DEMPSTER: THE ASSET CONVERSION PLAY

Dempster was a tiny micro cap, a family-owned company in Beatrice, Nebraska, that manufactured windmills and farm equipment.  Buffett slowly bought shares in the company over the course of five years.

(Photo by Digikhmer)

Dempster had a market cap of $1.6 million, about $13.3 million in today’s dollars, says Miller.

  • Note:  A market cap of $13.3 million is in the $10 to $25 million range—among the tiniest micro caps—which is avoided by nearly all investors, including professional microcap investors.

Buffett’s average price paid for Dempster was $28/share.  Buffett’s estimate of liquidation value early on was near $35/share, which is intentionally conservative.  Miller quotes one of Buffett’s letters:

The estimated value should not be what we hope it would be worth, or what it might be worth to an eager buyer, etc., but what I would estimate our interest would bring if sold under current conditions in a reasonably short period of time.

To estimate liquidation value, Buffett followed Graham’s method, as Miller explains:

  • cash, being liquid, doesn’t need a haircut
  • accounts receivable are valued at 85 cents on the dollar
  • inventory, carried on the books at cost, is marked down to 65 cents on the dollar
  • prepaid expenses and “other” are valued at 25 cents on the dollar
  • long-term assets, generally less liquid, are valued using estimated auction values

Buffett’s conservative estimate of liquidation value for Dempster was $35/share, or $2.2 million for the whole company.  Recall that Buffett paid an average price of $28/share—quite a cheap price.

Even though the assets were clearly there, Dempster had problems.  Stocks generally don’t get that cheap unless there are major problems.  In Dempster’s case, inventories were far too high and rising fast.  Buffett tried to get existing management to make needed improvements.  But eventually Buffett had to throw them out.  Then the company’s bank was threatening to seize the collateral on the loan.  Fortunately, Charlie Munger—who later became Buffett’s business partner—recommended a turnaround specialist, Harry Bottle.  Miller:

Harry did such an outstanding job whipping the company into shape that Buffett, in the next year’s letter, named him “man of the year.”  Not only did he reduce inventories from $4 million to $1 million, alleviating the concerns of the bank (whose loan was quickly repaid), he also cut administrative and selling expenses in half and closed five unprofitable branches.  With the help of Buffett and Munger, Dempster also raised prices on their used equipment up to 500% with little impact to sales volume or resistance from customers, all of which worked in combination to restore a healthy economic return in the business.

Miller explains that Buffett rationally focused on maximizing the return on capital:

Buffett was wired differently, and he achieves better results in part because he invests using an absolute scale.  With Dempster he wasn’t at all bogged down with all the emotional baggage of being a veteran of the windmill business.  He was in it to produce the highest rate of return on the capital he had tied up in the assets of the business.  This absolute scale allowed him to see that the fix for Dempster would come by not reinvesting back into windmills.  He immediately stopped the company from putting more capital in and started taking the capital out.

With profits and proceeds raised from converting inventory and other assets to cash, Buffett started buying stocks he liked.  In essence, he was converting capital that was previously utilized in a bad (low-return) business, windmills, to capital that could be utilized in a good (high-return) business, securities.

Bottle, Buffett, and Munger maximized the value of Dempster’s assets.  Buffett took the further step of not reinvesting cash in a low-return business, but instead investing in high-return stocks.  In the end, on its investment of $28/share, BPL realized a net gain of $45 per share.  This is a gain of a bit more than 160% on what was a very large position for BPL—one-fifth of the portfolio.  Had the company been shut down by the bank, or simply burned through its assets, the return after paying $28/share could have been nothing or even negative.

Miller nicely summarizes the lessons of Buffett’s asset conversion play:

Buffett teaches investors to think of stocks as a conduit through which they can own their share of the assets that make up a business.  The value of that business will be determined by one of two methods: (1) what the assets are worth if sold, or (2) the level of profits in relation to the value of assets required in producing them.  This is true for each and every business and they are interrelated…

Operationally, a business can be improved in only three ways: (1) increase the level of sales; (2) reduce costs as a percent of sales; (3) reduce assets as a percentage of sales.  The other factors, (4) increase leverage or (5) lower the tax rate, are the financial drivers of business value.  These are the only ways a business can make itself more valuable.

Buffett “pulled all the levers” at Dempster…

 

LIQUIDATION VALUE OR EARNINGS POWER?

For most of the cigar butts that Buffett bought for BPL, he used Graham’s net-net method of buying at a discount to liquidation value, conservatively estimated.  However, you can find deep value stocks—cigar butts—on the basis of other low “price-to-a-fundamental” ratio’s, such as low P/E or low EV/EBITDA.  Even Buffett, when he was managing BPL, used a low P/E in some cases to identify cigar butts.  (See an example below: Western Insurance Securities.)

Tobias Carlisle and Wes Gray tested various measures of cheapness from 1964 to 2011.  Quantitative Value (Wiley, 2012)—an excellent book—summarizes their results.  James P. O’Shaughnessy has conducted one of the broadest arrays of statistical backtests.  See his results in What Works on Wall Street (McGraw-Hill, 4th edition, 2012), a terrific book.

(Illustration by Maxim Popov)

  • Carlisle and Gray found that low EV/EBIT was the best-performing measure of cheapness from 1964 to 2011.  It even outperformed composite measures.
  • O’Shaughnessy learned that low EV/EBITDA was the best-performing individual measure of cheapness from 1964 to 2009.
  • But O’Shaughnessy also discovered that a composite measure—combining low P/B, P/E, P/S, P/CF, and EV/EBITDA—outperformed low EV/EBITDA.

Assuming relatively similar levels of performance, a composite measure is arguably better because it tends to be more consistent over time.  There are periods when a given individual metric might not work well.  The composite measure will tend to smooth over such periods.  Besides, O’Shaughnessy found that a composite measure led to the best performance from 1964 to 2009.

Carlisle and Gray, as well as O’Shaughnessy, didn’t include Graham’s net-net method in their reported results.  Carlisle wrote another book, Deep Value (Wiley, 2014)—which is fascinating—in which he summarizes several tests of net nets:

  • Henry Oppenheimer found that net nets returned 29.4% per year versus 11.5% per year for the market from 1970 to 1983.
  • Carlisle—with Jeffrey Oxman and Sunil Mohanty—tested net nets from 1983 to 2008.  They discovered that the annual returns for net nets averaged 35.3% versus 12.9% for the market and 18.4% for a Small Firm Index.
  • A study of the Japanese market from 1975 to 1988 uncovered that net nets outperformed the market by about 13% per year.
  • An examination of the London Stock Exchange from 1981 to 2005 established that net nets outperformed the market by 19.7% per year.
  • Finally, James Montier analyzed all developed markets globally from 1985 to 2007.  He learned that net nets averaged 35% per year versus 17% for the developed markets on the whole.

Given these outstanding returns, why didn’t Carlisle and Gray, as well as O’Shaughnessy, consider net nets?  Primarily because many net nets are especially tiny microcap stocks.  For example, in his study, Montier found that the median market capitalization for net nets was $21 million.  Even the majority of professionally managed microcap funds do not consider stocks this tiny.

  • Recall that Dempster had a market cap of $1.6 million, or about $13.3 million in today’s dollars.
  • Unlike the majority of microcap funds, the Boole Microcap Fund does consider microcap stocks in the $10 to $25 million market cap range.

In 1999, Buffett commented that he could get 50% per year by investing in microcap cigar butts.  He was later asked about this comment in 2005, and he replied:

Yes, I would still say the same thing today.  In fact, we are still earning those types of returns on some of our smaller investments.  The best decade was the 1950s;  I was earning 50% plus returns with small amounts of capital.  I would do the same thing today with smaller amounts.  It would perhaps even be easier to make that much money in today’s environment because information is easier to access.  You have to turn over a lot of rocks to find those little anomalies.  You have to find the companies that are off the map—way off the map.  You may find local companies that have nothing wrong with them at all.  A company that I found, Western Insurance Securities, was trading for $3/share when it was earning $20/share!!  I tried to buy up as much of it as possible.  No one will tell you about these businesses.  You have to find them.

Although the majority of microcap cigar butts Buffett invested in were cheap relative to liquidation value—cheap on the basis of net tangible assets—Buffett clearly found some cigar butts on the basis of a low P/E.  Western Insurance Securities is a good example.  It had a P/E of 0.15.

 

MEAN REVERSION FOR CIGAR BUTTS

Warren Buffett commented on high quality companies versus statistically cheap companies in his October 1967 letter to partners:

The evaluation of securities and businesses for investment purposes has always involved a mixture of qualitative and quantitative factors.  At the one extreme, the analyst exclusively oriented to qualitative factors would say, “Buy the right company (with the right prospects, inherent industry conditions, management, etc.) and the price will take care of itself.”  On the other hand, the quantitative spokesman would say, “Buy at the right price and the company (and stock) will take care of itself.”  As is so often the pleasant result in the securities world, money can be made with either approach.  And, of course, any analyst combines the two to some extent—his classification in either school would depend on the relative weight he assigns to the various factors and not to his consideration of one group of factors to the exclusion of the other group.

Interestingly enough, although I consider myself to be primarily in the quantitative school… the really sensational ideas I have had over the years have been heavily weighted toward the qualitative side where I have had a “high-probability insight”.  This is what causes the cash register to really sing.  However, it is an infrequent occurrence, as insights usually are, and, of course, no insight is required on the quantitative side—the figures should hit you over the head with a baseball bat.  So the really big money tends to be made by investors who are right on qualitative decisions but, at least in my opinion, the more sure money tends to be made on the obvious quantitative decisions.

Buffett and Munger acquired See’s Candies for Berkshire Hathaway in 1972.  See’s Candies is the quintessential high quality company because of its sustainably high ROIC (return on invested capital) of over 100%.

Truly high quality companies—like See’s—are very rare and difficult to find.  Cigar butts are much easier to find by comparison.

Furthermore, it’s important to understand that Buffett got around 50% annual returns from cigar butts because he took a focused approach, like BPL’s 20% position in Dempster.

The vast majority of investors, if using a cigar-butt approach like net nets, should implement a group—or statistical—approach, and regularly buy and hold a basket of cigar butts (at least 20-30).  This typically won’t produce 50% annual returns.  But net nets, as a group, clearly have produced very high returns, often 30%+ annually.  To do this today, you’d have to look globally.

As an alternative to net nets, you could implement a group approach using one of O’Shaughnessy’s composite measures—such as low P/B, P/E, P/S, P/CF, EV/EBITDA.  Applying this to micro caps can produce 15-20% annual returns.  Still excellent results.  And much easier to apply consistently.

You may think that you can find some high quality companies.  But that’s not enough.  You have to find a high quality company that can maintain its competitive position and high ROIC.  And it has to be available at a reasonable price.

Most high quality companies are trading at very high prices, to the extent that you can’t do better than the market by investing in them.  In fact, often the prices are so high that you’ll probably do worse than the market.

Consider this observation by Charlie Munger:

The model I like to sort of simplify the notion of what goes o­n in a market for common stocks is the pari-mutuel system at the racetrack.  If you stop to think about it, a pari-mutuel system is a market.  Everybody goes there and bets and the odds change based o­n what’s bet.  That’s what happens in the stock market.

Any damn fool can see that a horse carrying a light weight with a wonderful win rate and a good post position etc., etc. is way more likely to win than a horse with a terrible record and extra weight and so o­n and so on.  But if you look at the odds, the bad horse pays 100 to 1, whereas the good horse pays 3 to 2.  Then it’s not clear which is statistically the best bet using the mathematics of Fermat and Pascal.  The prices have changed in such a way that it’s very hard to beat the system.

(Illustration by Nadoelopisat)

A horse with a great record (etc.) is much more likely to win than a horse with a terrible record.  But—whether betting on horses or betting on stocks—you don’t get paid for identifying winners.  You get paid for identifying mispricings.

The statistical evidence is overwhelming that if you systematically buy stocks at low multiples—P/B, P/E, P/S, P/CF, EV/EBITDA, etc.—you’ll almost certainly do better than the market over the long haul.

A deep value (cigar-butt) approach has always worked, given enough time.  Betting on “the losers” has always worked eventually, whereas betting on “the winners” hardly ever works.

Classic academic studies showing “the losers” doing far better than “the winners” over subsequent 3- to 5-year periods:

That’s not to say deep value investing is easy.  When you put together a basket of statistically cheap companies, you’re buying stocks that are widely hated or neglected.  You have to endure loneliness and looking foolish.  Some people can do it, but it’s important to know yourself before using a deep value strategy.

In general, we extrapolate the poor performance of cheap stocks and the good performance of expensive stocks too far into the future.  This is the mistake of ignoring mean reversion.

When you find a group of companies that have been doing poorly for at least several years, those conditions typically do not persist.  Instead, there tends to be mean reversion, or a return to “more normal” levels of revenues, earnings, or cash flows.

Similarly for a group of companies that have been doing exceedingly well.  Those conditions also do not continue in general.  There tends to be mean reversion, but in this case the mean—the average or “normal” conditions—is below recent activity levels.

Here’s Ben Graham explaining mean reversion:

It is natural to assume that industries which have fared worse than the average are “unfavorably situated” and therefore to be avoided.  The converse would be assumed, of course, for those with superior records.  But this conclusion may often prove quite erroneous.  Abnormally good or abnormally bad conditions do not last forever.  This is true of general business but of particular industries as well.  Corrective forces are usually set in motion which tend to restore profits where they have disappeared or to reduce them where they are excessive in relation to capital.

With his taste for literature, Graham put the following quote from Horace’s Ars Poetica at the beginning of Security Analysis—the bible for value investors:

Many shall be restored that now are fallen and many shall fall than now are in honor.

Tobias Carlisle, while discussing mean reversion in Deep Value, smartly (and humorously) included this image of Albrecht Durer’s Wheel of Fortune:

(Albrecht Durer’s Wheel of Fortune from Sebastien Brant’s Ship of Fools (1494) via Wikimedia Commons)

 

FOCUSED vs. STATISTICAL

We’ve already seen that there are two basic ways to do cigar-butt investing: focused vs. statistical (group).

Ben Graham usually preferred the statistical (group) approach.  Near the beginning of the Great Depression, Graham’s managed accounts lost more than 80 percent.  Furthermore, the economy and the stock market took a long time to recover.  As a result, Graham had a strong tendency towards conservatism in investing.  This is likely part of why he preferred the statistical approach to net nets.  By buying a basket of net nets (at least 20-30), the investor is virtually certain to get the statistical results of the group over time, which are broadly excellent.

Graham also was a polymath of sorts.  He had wide-ranging intellectual interests.  Because he knew net nets as a group would do quite well over the long term, he wasn’t inclined to spend much time analyzing individual net nets.  Instead, he spent time on his other interests.

Warren Buffett was Graham’s best student.  Buffett was the only student ever to be awarded an A+ in Graham’s class at Columbia University.  Unlike Graham, Buffett has always had an extraordinary focus on business and investing.  After spending many years learning everything about virtually every public company, Buffett took a focused approach to net nets.  He found the ones that were the cheapest and that seemed the surest.

Buffett has asserted that returns can be improved—and risk lowered—if you focus your investments only on those companies that are within your circle of competence—those companies that you can truly understand.  Buffett also maintains, however, that the vast majority of investors should simply invest in index funds: http://boolefund.com/warren-buffett-jack-bogle/

Regarding individual net nets, Graham admitted a danger:

Corporate gold dollars are now available in quantity at 50 cents and less—but they do have strings attached.  Although they belong to the stockholder, he doesn’t control them.  He may have to sit back and watch them dwindle and disappear as operating losses take their toll.  For that reason the public refuses to accept even the cash holdings of corporations at their face value.

Graham explained that net nets are cheap because they “almost always have an unsatisfactory trend in earnings.”  Graham:

If the profits had been increasing steadily it is obvious that the shares would not sell at so low a price.  The objection to buying these issues lies in the probability, or at least the possibility, that earnings will decline or losses continue, and that the resources will be dissipated and the intrinsic value ultimately become less than the price paid.

(Image by Preecha Israphiwat)

Value investor Seth Klarman warns:

As long as working capital is not overstated and operations are not rapidly consuming cash, a company could liquidate its assets, extinguish all liabilities, and still distribute proceeds in excess of the market price to investors.  Ongoing business losses can, however, quickly erode net-net working capital.  Investors must therefore always consider the state of a company’s current operations before buying.

Even Buffett—nearly two decades after closing BPL—wrote the following in his 1989 letter to Berkshire shareholders:

If you buy a stock at a sufficiently low price, there will usually be some hiccup in the fortunes of the business that gives you a chance to unload at a decent profit, even though the long-term performance of the business may be terrible.  I call this the “cigar butt” approach to investing.  A cigar butt found on the street that has only one puff left in it may not offer much of a smoke, but the “bargain purchase” will make that puff all profit.

Unless you are a liquidator, that kind of approach to buying businesses is foolish.  First, the original “bargain” price probably will not turn out to be such a steal after all.  In a difficult business, no sooner is one problem solved than another surfaces—never is there just one cockroach in the kitchen.  Second, any initial advantage you secure will be quickly eroded by the low return that the business earns.  For example, if you buy a business for $8 million that can be sold or liquidated for $10 million and promptly take either course, you can realize a high return.  But the investment will disappoint if the business is sold for $10 million in ten years and in the interim has annually earned and distributed only a few percent on cost…

Based on these objections, you might think that Buffett’s focused approach is better than the statistical (group) method.  That way, the investor can figure out which net nets are more likely to recover instead of burn through their assets and leave the investor with a low or negative return.

However, Graham’s response was that the statistical or group approach to net nets is highly profitable over time.  There is a wide range of potential outcomes for net nets, and many of those scenarios are good for the investor.  Therefore, while there are always some individual net nets that don’t work out, a group or basket of net nets is nearly certain to work well eventually.

Indeed, Graham’s application of a statistical net-net approach produced 20% annual returns over many decades.  Most backtests of net nets have tended to show annual returns of close to 30%.  In practice, while around 5 percent of net nets may suffer a terminal decline in stock price, a statistical group of net nets has done far better than the market and has experienced fewer down years.  Moreover, as Carlisle notes in Deep Value, very few net nets are actually liquidated or merged.  In the vast majority of cases, there is a change by management, a change from the outside, or both, in order to restore earnings to a level more in line with net asset value.  Mean reversion.

 

THE REWARDS OF PSYCHOLOGICAL DISCOMFORT

We noted earlier that it’s far more difficult to find a company like See’s Candies, at a reasonable price, than it is to find statistically cheap stocks.  Moreover, if you buy a basket of statistically cheap stocks, you don’t have to possess an ability to analyze individual businesses in great depth.

That said, in order to use a deep value strategy, you do have to be able to handle the psychological discomfort of being lonely and looking foolish.

(Illustration by Sangoiri)

John Mihaljevic, author of The Manual of Ideas (Wiley, 2013), writes:

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

…Misery loves company, so it makes sense that rewards may await those willing to be miserable in solitude…

Mihaljevic explains:

If we owned nothing but a portfolio of Ben Graham-style bargain equities, we may become quite uncomfortable at times, especially if the market value of the portfolio declined precipitously.  We might look at the portfolio and conclude that every investment could be worth zero.  After all, we could have a mediocre business run by mediocre management, with assets that could be squandered.  Investing in deep value equities therefore requires faith in the law of large numbers—that historical experience of market-beating returns in deep value stocks and the fact that we own a diversified portfolio will combine to yield a satisfactory result over time.  This conceptually sound view becomes seriously challenged in times of distress…

Playing into the psychological discomfort of Graham-style equities is the tendency of such investments to exhibit strong asset value but inferior earnings or cash flows.  In a stressed situation, investors may doubt their investment theses to such an extent that they disregard the objectively appraised asset values.  After all—the reasoning of a scared investor might go—what is an asset really worth if it produces no cash flow?

Deep value investors often find some of the best investments in cyclical areas.  A company at a cyclical low may have multi-bagger potential—the prospect of returning 300-500% (or more) to the investor.

A good current example is Ensco plc (NYSE: ESV), an offshore oil driller.  Ensco is a leading offshore driller with a high-specification, globally diverse fleet.  The company also has one of the lowest cost structures, and relatively low debt levels (with the majority of debt due in 2024 or later).  In addition, Ensco has a long history of safety and operational excellence.  Ensco has been rated #1 for eight consecutive years in the leading independent customer satisfaction survey.

Intrinsic value scenarios for Ensco:

  • Low case: If oil prices languish below $60 (WTI) for the next 3 to 5 years, then Ensco will be a survivor, due to its large fleet, globally diverse customer base, industry leading performance, and well-capitalized position.  In this scenario, Ensco is likely worth at least $12 a share, over 90% higher than today’s $6.26.  (Current book value is $19.30 a share.)
  • Mid case: If oil prices are in a range of $65 to $85 over the next 3 to 5 years—which is likely based on long-term supply and demand—then Ensco is probably worth at least $25 a share, about 300% higher than today’s $6.26.
  • High case: If oil prices average $85 or more over the next 3 to 5 years, then Ensco could easily be worth $37 a share, over 490% higher than today’s $6.26.

Mihaljevic comments on a central challenge of deep value investing in cyclical companies:

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

Consider the following industries that have been pronounced permanently impaired in the past, only to rebound strongly in subsequent years:  Following the financial crisis of 2008-2009, many analysts argued that the banking industry would be permanently negatively affected, as higher capital requirements and regulatory oversight would compress returns on equity.  The credit rating agencies were seen as impaired because the regulators would surely alter the business model of the industry for the worse following the failings of the rating agencies during the subprime mortgage bubble.  The homebuilding industry would fail to rebound as strongly as in the past, as overcapacity became chronic and home prices remained tethered to building costs.  The refining industry would suffer permanently lower margins, as those businesses were capital-intensive and driven by volatile commodity prices.

Are offshore oil drillers in a cyclical or a secular decline?  It’s likely that oil will return to $65-85 in the next 3 to 5 years.  But no one knows for sure.

Ongoing improvements in technology allow oil producers to get more oil—more cheaply—out of existing fields.  Also, growth in transport demand for oil will slow significantly at some point, due to ongoing improvements in fuel efficiency.  See: https://www.spe.org/en/jpt/jpt-article-detail/?art=3286

Transport demand is responsible for over 50% of daily oil consumption, and it’s inelastic—typically people have to get where they’re going, so they’re not very sensitive to fuel price increases.

But even if oil never returns to $65+, oil will be needed for many decades.  At least some offshore drilling will still be needed.

What’s great about an investment in Ensco is that even in worst case, the company will survive and the stock would likely be worth at least $12 a share, almost double today’s $6.26.  Recall that book value is $19.30 a share, and that the company has a low cost structure.  Also note that because of its safety, reliability, high-spec assets, and well-capitalized position, Ensco has continued to win a disproportionate share of new contracts.

If the worst-case scenario means that you’ll double your money—over a 3- to 5-year holding period—that’s an interesting investment.  And if the base case scenario means that you’ll quadruple your money (or better), well…

Notes:

  • The Boole Fund had an investment in Atwood Oceanics.  Because Ensco acquired Atwood in 2017, the Boole Fund now own shares in Ensco.
  • The Boole Fund holds positions for 3 to 5 years.  The fund doesn’t sell an investment that is still cheap, even if the stock in question is no longer a micro cap.
  • On October 8, Ensco plc (ESV) and Rowan Companies plc (RDC) announced that they are merging in an all-stock transaction.  The new entity is probably even more undervalued than Ensco was prior to the announcement.  That’s based partly on projected cost savings of $150 million a year—which is credible based on track record.  In addition, besides being a leader in ultra-harsh and modern harsh environment jackups, Rowan has a groundbreaking partnership (ARO Drilling) with Saudi Aramco that will likely create billions of dollars in value for shareholders.

 

CONCLUSION

Buffett has made it clear, including in his 2014 letter to shareholders, that the best returns of his career came from investing in microcap cigar butts.  Most of these were mediocre businesses (or worse).  But they were ridiculously cheap.  And, in some cases like Dempster, Buffett was able to bring about needed improvements when required.

When Buffett wrote about buying wonderful businesses in his 1989 letter, that’s chiefly because investable assets at Berkshire Hathaway had grown far too large for microcap cigar butts.

Even in recent years, Buffett invested part of his personal portfolio in a group of cigar butts he found in South Korea.  So he’s never changed his view that an investor can get the highest returns from microcap cigar butts, either by using a statistical group approach or by using a more focused method.

 

BOOLE MICROCAP FUND

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

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

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

The 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: jb@boolefund.com

 

 

 

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

Capitalism without Capital

(Image:  Zen Buddha Silence by Marilyn Barbone.)

November 11, 2018

Capitalism without Capital: The Rise of the Intangible Economy, by Jonathan Haskel and Stian Westlake, is an excellent book that everyone should read.

Historically most assets were tangible rather than intangible.  Houses, castles, temples, churches, farms, farm animals, equipment, horses, weapons, jewels, precious metals, art, etc.  These types of tangible assets tended to hold their value, and naturally they were included on accountants’ balance sheets.

(Photo by W. Scott McGill)

Intangible assets are different.  It’s harder to account for investing in intangibles.  But intangible investment is important.  Haskel and Westlake explain why:

Investment is what builds up capital, which, together with labor, constitutes the two measured inputs to production that power the economy, the sinews and joints that make the economy work.  Gross domestic product is defined as the sum of the value of consumption, investment, government spending, and net exports; of these four, investment is often the driver of booms and recessions, as it tends to rise and fall in response to monetary policy and business confidence.

The problem is that national statistical offices have, until very recently, measured only tangible investments.

The Dark Matter of Investment

In 2002 in Washington, at a meeting of the Conference on Research in Income and Wealth, economists considered investments people made in the “new economy.”  Carol Corrado and Dan Sichel of the US Federal Reserve Board and Charles Hulten of the University of Maryland developed a framework for thinking about different types of investments.

Haskel and Westlake mention Microsoft as an example.  In 2006, Microsoft’s market value was about $250 billion.  There was $70 billion in assets, $60 billion of which was cash and cash equivalents.  Plant and equipment totaled only $3 billion, 4 percent of Microsoft’s assets and 1 percent of its market value.  In a sense, Microsoft is a miracle:  capitalism without capital.

(Photo by tashatuvango)

Charles Hulten sought to explain Microsoft’s value by using intangible assets:

Examples include the ideas generated by Microsoft’s investments in R&D and product design, the value of its brands, its supply chains and internal structures, and the human capital built up by training.

Such intangible assets are similar to tangible assets in that the company had to spend time and money on them up-front, while the value to the company was delivered over time.

Why Intangible Investment is Different

Businesses change what they invest in all the time, so how is intangible investment different?  Haskel and Westlake:

Our central argument in this book is that there is something fundamentally different about intangible investment, and that understanding the steady move to intangible investment helps us understand some of the key issues facing us today:  innovation and growth, inequality, the role of management, and financial and policy reform.

We shall argue there are two big differences with intangible assets.  First, most measurement conventions ignore them.  There are some good reasons for this, but as intangibles have become more important, it means we are now trying to measure capitalism without counting all the capital.  Second, the basic economic properties of intangibles make an intangible-rich economy behave differently from a tangible-rich one.

Outline for this blog post:

Part I  The Rise of the Intangible Economy

  • Capital’s Vanishing Act:  The Rise of Intangible Investment
  • How to Measure Intangible Investment
  • What’s Different About Intangible Investment?  The Four S’s of Intangibles

Part II  The Consequences of the Rise of the Intangible Economy

  • Intangibles, Investment, Productivity, and Secular Stagnation
  • Intangibles and the Rise of Inequality
  • Infrastructure for Intangibles, and Intangible Infrastructure
  • The Challenge of Financing an Intangible Economy
  • Competing, Managing, and Investing in the Intangible Economy
  • Public Policy in an Intangible Economy:  Five Hard Questions

 

Part I  The Rise of the Intangible Economy

CAPITAL’S VANISHING ACT

Investment has changed:

The type of investment that has risen inexorably is intangible: investment in ideas, in knowledge, in aesthetic content, in software, in brands, in networks and relationships.

Investment, assets, and capital all have multiple meanings.

For investment, Haskel and Westlake stick with the internationally agreed upon definition as given by the UN’s System of National Accounts:

Investment is what happens when a producer either acquires a fixed asset or spends resources (money, effort, raw materials) to improve it.

An asset is an economic resource that is expected to provide a benefit over a period of time.  A fixed asset is an asset that results from using up resources in the process of its production.

Spending resources:  To be an investment, the business doing the investing has to acquire the asset or pay some cost to produce it themselves.

Haskel and Westlake offer some examples of intangible investments:

Suppose a solar panel manufacturer researches and discovers a cheaper process for making photovoltaic cells:  it is incurring expense in the present to generate knowledge it expects to benefit from in the future.  Or consider a streaming music start-up that spends months designing and negotiating deals with record labels to allow it to use songs the record labels own—again, short-term expenditure to create longer-term gain.  Or imagine a training company pays for the long-term rights to run a popular psychometric test:  it too is investing.

(Photo by magele-picture)

Intangible investing results in intangible assets.  More examples of intangible investments:

  • Software
  • Databases
  • R&D
  • Mineral exploration
  • Creating entertainment, literary or artistic originals
  • Design
  • Training
  • Market research and branding
  • Business process re-engineering

Intangible Investment Has Steadily Grown

Supermarkets have developed complex pricing systems, more ambitious branding and marketing campaigns, and more detailed processes and systems (including better use of bar codes).  Moreover, as you might expect, tech firms make heavy use of intangible investments, as Haskel and Westlake explain:

Fast-growing tech companies are some of the most intangible-intensive of firms.  This is in part because software and data are intangibles, and the growing power of computers and telecommunications is increasing the scope of things that software can achieve.  But the process of “software eating the world,” in venture capitalist Marc Andreesen’s words, is not just about software:  it involves other intangibles in abundance.  Consider Apple’s designs and its unrivaled supply chain, which has helped it to bring elegant products to market quickly and in sufficient numbers to meet customer demand, or the networks of drivers and hosts that sharing-economy giants like Uber and AirBnB have developed, or Tesla’s manufacturing know-how.  Computers and the Internet are important drivers of this change in investment, but the change is long running and predates not only the World Wide Web but even the Internet and the PC.

By the mid-1990s, intangible investment in the United States exceeded tangible investment.  There is a similar pattern for the UK, Sweden, and Finland.  But tangible investment is still greater than intangible investment in Spain, Italy, Germany, Austria, Denmark, and the Netherlands.

Reasons for the Growth of Intangible Investment

Because the productivity of the manufacturing sector typically increases faster than that of the services sector, labor-intensive services gradually become more expensive compared to manufactured goods.  (This is called Baumol’s Cost Disease.)  This implies that intangible investing will grow faster than tangible investing over time.

Furthermore, new technology seems to create greater opportunities for businesses to invest productively in intangibles.  Haskel and Westlake give Uber as an example.  It would have been possible before computers and smartphones for Uber to develop its large network of drivers.  But smartphones—which connect people quickly, allow the rating of drivers, and make payment quick and easy—significantly boosted the return on investment for Uber.

It’s natural to wonder if computers are the cause of increased intangible investment.  Haskel and Westlake suggest that while computers may be a primary cause, they do not seem to be the only cause:

First of all, as we saw earlier, the rise of intangible investment began before the semiconductor revolution, in the 1940s and 1950s and perhaps before.  Second, while some intangibles like software and data strongly rely on computers, others do not:  brands, organizational development, and training, for example.  Finally, a number of writers in the innovation studies literature argue that it may be that it was the rise of intangibles that led to the development of modern IT as much as the other way around.

 

HOW TO MEASURE INTANGIBLE INVESTMENT

Productivity growth in the United States starting in the mid-1970s and throughout the 1980s seemed quite low.  Economists found this puzzling because computers seemed to be making a difference in a variety of areas.  Statistical agencies, led by the US Bureau of Economic Analysis (BEA), made two adjustments:

First, in the 1980s, in conjunction with IBM, the BEA started to produce indexes of computer prices that were quality adjusted.  This turned out to make a very big difference to measuring how much investment businesses were making in computer hardware.

In most cases—for products, for example—prices for the same good tend to rise gently in line with overall inflation.  But even if sticker prices for computers were rising, they were decidedly not the same good, since every dimension of their quality (speed, memory, and space) was improving incredibly.  So their “quality-adjusted” prices were, in fact, falling and falling very fast, meaning that the quality you could buy per dollar spent on computers was in fact rising very fast.

In the 1990s, statisticians looked at business spending that creates computer software.  Haskel and Westlake comment that banks are huge spenders on the creation of software (at one point, Citibank employed more programmers than Microsoft).  Software is an intangible good—knowledge written down in lines of code.

(Photo by Krisana Antharith)

By the early 2000s, many business economists realized that knowledge more generally is an intangible investment that should be included in GDP and productivity measures.  Gradually statistical offices began to incorporate various intangible investments into GDP statistics.  Haskel and Westlake:

And these changes added up.  In the United States, for example, the capitalization of software added about 1.1 percent to 1999 US GDP and R&D added 2.5 percent to 2012 GDP, with these numbers growing all the time…

What Sorts of Intangibles Are There?

Corrado, Hulten, and Sichel divided intangible investment into three broad types:

  • Computerized Information:  Software development;  Database development.
  • Innovative Property:  R&D;  Mineral exploration;  Creating entertainment and artistic originals;  Design and other product development costs.
  • Economic Competencies:  Training;  Market research and branding;  Business process re-engineering.

Right now, design and other product development costs are not included in official GDP measures.  Also not included:  training, market research and branding, and business process re-engineering.

Measuring Investment in Intangibles

Haskel and Westlake:

Measuring investment requires a number of steps.  First, we need to find out how much firms are spending on the intangible.  Second, in some cases, not all of that spending will be creating a long-lived asset… So we may have to adjust that spending to measure investment—that is, that part of spending creating a long-lived asset.  Third, we need to adjust that investment for inflation and quality change so we can compare investment in different periods when prices and quality are changing.

For most investment goods, national accountants simply send out a survey to companies asking them how much there are spending on each good.  It’s trickier, however, if it’s an intangible good that the company makes for itself, like writing its own software or doing its own R&D.  In this case, statisticians can figure out how much it costs a company—over and above wages—to produce the intangible good.  Statisticians also must estimate how much of that additional spending is an investment that will last for more than a year.  The third step is to adjust for inflation and quality changes.

To measure the intangible asset created by intangible investment, economists have to estimate depreciation.  Once you know the flow of intangible investment and you adjust for depreciation, you can then estimate the stock—the value of intangible assets in a given year.  For software, design, marketing, and training, depreciation is about 33 percent a year.  For R&D, depreciation is roughly 15 percent a year.  For entertainment and artistic originals and mineral exploration, depreciation is lower.

 

WHAT’S DIFFERENT ABOUT INTANGIBLE INVESTMENT?

An intangible-rich economy has four characteristics—the four S’s—that distinguish it from a tangible-rich economy.  Intangible assets:

  • Are more likely to be scalable;
  • Their costs are more likely to be sunk;
  • They are inclined to have spillovers;
  • They tend to exhibit synergies with each other.

Scalability

Why Are Intangibles Scalable?

Scalability derives from what economists call “non-rivalry” goods.  A rival good is like a loaf of bread.  Once one person eats the loaf of bread, no one else can eat that loaf.  In contrast, a non-rival good is not used up when one person uses it.  For instance, once a software program has been created, it can be reproduced an infinite number of times at almost no cost.  There’s virtually no limit to how many people can make use of that one software program.  Another example, given by Paul Romer—a pioneer of how economists think about economic growth—is oral rehydration therapy (ORT).  ORT is a simple treatment that has saved many lives in the developing world by stopping children’s deaths from diarrhea.  The idea of ORT can be used again and again—it’s never used up.

Note:  Scalability can really take off if there are “network effects.”  Haskel and Westlake mention networks like Uber drivers or Instagram users as examples.

(Illustration by Aquir)

Why Does Scalability Matter?

Haskel and Westlake say that we will see three unusual things happening in an economy where more investments are clearly scalable:

  • There will be some highly intangible-intensive businesses that have gotten very large.  Google, Microsoft, and Facebook are good examples.  Their software can be reproduced countless times at almost no cost.
  • Given the prospects of such large markets, ever more firms feel incentivized to go for it.
  • Businesses who compete with owners of scalable assets are in a tough position.  In markets with hugely scalable assets, the rewards for runners-up are often meager.

Sunkenness

Why Are Intangibles Sunk Costs?

Intangible assets are much harder to sell than tangible assets.  If an intangible investment works, creating value for the company that made the investment, then there’s no issue.  However, if an intangible investment doesn’t work or the company wants to back out, it’s often hard to sell.  Specifically, if knowledge isn’t protected by intellectual property rights, it’s often impossible to sell.

(Image by OpturaDesign)

Why Does Sunkenness Matter?

Because intangible investments frequently involve unrecoverable costs, they can be difficult to finance, especially with debt.  There’s a reason why many small business loans require a lien on directors’ houses:  a house is a tangible asset with ascertainable value.

Moreover, people tend to fall for the sunk-cost fallacy, whereby they overvalue an intangible asset that hasn’t worked out because of the time, energy, and resources they’ve poured into it.  People are inclined to continue putting in more time and resources.  This may contribute to bubbles.

Spillovers

Why Do Intangibles Generate Spillovers?

Intangible investments can be used relatively easily by companies that didn’t make the investments.  Consider R&D.  Unless it is protected by patents, knowledge gained through R&D can be re-used again and again.  Haskel and Westlake remark:

Patents and copyrights are, on the whole, less secure and more subject to challenge than the title deeds to farmland or the ownership of a shipping container or a computer.

One reason is that property rights related to tangible assets have been around for thousands of years.

Why Do Spillovers Matter?

(Photo by Vs1489)

Haskel and Westlake remark that spillovers matter for three reasons:

  • First, in a world where companies can’t be sure they will obtain the benefits of their investments, we would expect them to invest less.
  • Second, there is a premium on the ability to manage spillovers:  companies that can make the most of their own investments in intangibles, or that are especially good at exploiting the spillovers from others’ investments, will do particularly well.
  • Third, spillovers affect the geography of modern economies.

The U.S. government funds 30 percent of the R&D that happens in the country.  It’s the classic answer to the issue of companies being unsure about the benefits of intangible investments they’re considering.  Public R&D is particularly important for basic research.

Haskel and Westlake:

Patent trolls and copyright lawsuits catch our attention because they are newsworthy, but other ways of capturing the spillovers of intangible investment are common—in fact, they’re part of the invisible fabric of everyday business life.  They often involve reciprocity rather than compulsion or legal threats.  Software developers use online repositories like GitHub to share code; being an active contributor and an effective user of GitHub is a badge of honor for some developers.  Firms sometimes pool their patents; they realize that the spillovers from each company’s technologies are valuable, and that enforcing everyone’s individual legal rights is not worth it.  (Indeed, the US government helped end the patent war between the Wright Brothers and Curtiss Aeroplane and Motor Company that was holding back the US aircraft industry in the 1910s by getting everyone to set up a patent pool, the Manufacturers Aircraft Association.)

Synergies

Why Do Intangibles Exhibit Synergies?

Haskel and Westlake give the example of the microwave.  Near the end of World War II, Raytheon was mass-producing cavity magnetrons (similar to a vacuum tube), a crucial part of the radar defenses the British had invented.  A Raytheon engineer, Percy Spenser, realized the microwaves from magnetrons could heat food by creating electromagnetic fields in a box.

Haskel and Westlake write:

A few companies tried to sell domestic microwave ovens, but none were very successful.  Then, in the 1960s, Raytheon bought Amana, a white goods manufacturer, and combined their microwave expertise with Amana’s kitchen appliance knowledge to build a more successful product.  At the same time, Litton, another defense contractor, invented the modern microwave oven shape and tweaked the magnetron to make it safer.

In 1970 forty thousand microwaves were sold.  By 1975 it was a million.  What made this possible was the gradual accumulation of ideas and innovations.  The magnetron on its own wasn’t very useful to a customer, but combined with other incremental bits of R&D and the design and marketing ideas of Litton and Amana, it became a defining innovation of the late twentieth century.

The point of the microwave story is that intangible assets have synergies with one another.  Also, it’s hard to predict where innovations will come from or how they will combine.  In this example, military technology led to a kitchen appliance.

(Synergies in digital business, science, and technology:  Illustration by Agsandrew)

Intangible assets have synergies with tangible assets as well.  In the 1990s, productivity increased and at first people didn’t know why.  Haskel and Westlake explain:

In 2000 the McKinsey Global Institute analyzed the sources of this productivity increase.  Counterintuitively, they found that the bulk of it came from the way big chains retailers, in particular Walmart, were using computers and software to reorganize their supply chains, improve efficiency, and lower prices.  In a sense, it was a technological revolution.  But the gains were realized through organizational and business practice changes in a low-tech sector.  Or, to put it another way, there were big synergies between Walmart’s investment in computers and its investment in processes and supply chain development to make the most of the computers.

Why Do the Synergies of Intangible Assets Matter?

While spillovers cause firms to be protective of their intangible investments, synergies have the opposite effect and lead to open innovation.

In its simplest form, open innovation happens when a firm deliberately connects with and benefits from new ideas that arise outside the firm itself.  Cooking up ideas in a big corporate R&D lab is not open innovation; getting ideas by buying start-ups, partnering with academic researchers, or undertaking joint ventures with other companies is.

(Illustration by mindscanner)

Besides open innovation, there’s a second reason why synergies matter:

They also matter because they create an alternative way for firms to protect their intangible investments against competition:  by building synergistic clusters of intangible investments, rather than by protecting individual assets.

 

Part II  The Consequences of the Rise of the Intangible Economy

INTANGIBLES, INVESTMENT, PRODUCTIVITY, AND SECULAR STAGNATION

Two characteristics of secular stagnation are low investment and low interest rates.  Investment fell in the 1970s, recovered some in the mid-1980s, but fell sharply in the financial crisis (2008) and hasn’t recovered.

What’s puzzling is that investment hasn’t recovered despite low interest rates.  In the past, central banks relied on lowering rates to spur investment activity.  But that seems not to have worked this time.

(Illustration by ibreakstock)

One possible explanation is that technological progress has slowed.  Robert Gordon makes this argument in The Rise and Fall of American Growth (2016).  But technological progress is quite difficult to measure.

There are three more aspects to secular stagnation.

  • Corporate profits in the United States are higher than they’ve been for decades, and they seem to keep increasing.  Return on invested capital (ROIC) has grown significantly since the 1990s.
  • When it comes to both profitability and productivity, there is a growing gap between leaders and laggards.
  • Productivity growth has slowed due mostly to a decline in total factor productivity—workers are working less effectively with the capital they have.

Haskel and Westlake note that a good explanation for secular stagnation should explain four facts:

  • A fall in measured investment at the same time as a fall in interest rates
  • Strong profits
  • Increasingly unequal productivity and profits
  • Weak total factor productivity growth

Intangibles can help explain these facts.

Mismeasurement:  Intangibles and Apparently Low Investment

Intangible investment exceeds tangible investment in countries including the United States and the UK.  Are economies growing faster than reported because the value of intangibles is not being properly measured?  Haskel and Westlake show that including intangibles does not noticeably change investment/GDP.

Profits and Productivity Differences:  Scale, Spillovers, and the Incentives to Invest

Haskel and Westlake state:

…leading firms, which are confident of their ability to create scalable assets and to appropriate most of their benefits, will continue to invest (and enjoy a high rate of return on those investments); but laggard firms, expecting low private returns from their investments, will not.  In a world where there are a few leaders and many laggards, the net effect of this could be lower aggregate rates of investment, combined with high returns on those investments that do get made.

Spillovers:  Intangibles and Slowing TFP Growth A Lower Pace of Intangible Growth?

The slowdown in intangible investment since the financial crisis does seem to account for slowing TFP (Total Factor Productivity) growth, although the data are noisy and more exploration is needed.

Are Intangibles Generating Fewer Spillovers?

Lagging firms may be less able to absorb spillovers from leaders, possibly because leading firms can gain from synergies between different intangibles to a much greater extent than laggards.

 

INTANGIBLES AND THE RISE OF INEQUALITY

In addition to inequality of income and inequality of wealth, there is also what Haskel and Westlake call “inequality of esteem.”  Some communities feel left-behind and overlooked by America’s prosperous coastal cities.

Standard explanations for inequality

One standard explanation for inequality is that new technologies replace workers, which causes wages to fall and profits to rise.

A second explanation relates to trade.  In the 1980s, before the collapse of the Soviet Union and before market reforms in China and India, the global economy had 1.46 billion workers.  Then in the 1990s, the number of workers doubled to 2.93 billion workers.  This puts pressure on lower-skilled workers in developed economies.  The flip side is that lower-skilled workers in China and India end up far better off than they were before.

A third explanation for inequality is that capital tends to accumulate.  Capital tends to grow faster than the economy—this is Thomas Piketty’s famous r > g inequality—which causes capital to build up over time.

(Illustration by manakil)

How Intangibles Affect Income, Wealth, and Esteem Inequality

Intangibles, Firms, and Income Inequality

The best firms—owning scalable intangibles and able to extract spillovers from other businesses—will be highly productive and profitable while their competitors will lose out.  But that doesn’t necessarily mean the best firms pays all their workers more.  To explain rising wage inequality, more is needed.

Who is Benefiting from Intangible-Based Firm Inequality?

“Superstars” benefit by being associated with exceptionally valuable intangibles that can scale massively.  Whereas in most markets a top worker could probably be replaced by two not-as-fast workers, this isn’t true for superstar markets:  you can’t replace the best opera singer or the best basketball player with two not-quite-as-good ones.  Tech billionaires also tend to be superstars with large equity stakes in companies they founded—companies that probably scaled massively.

However, senior managers have also done very well.  Haskel and Westlake explain why:

Intangible investment increases.  Because of its scalability and the benefits to companies that can appropriate intangible spillovers, leading companies pull ahead of laggards in terms of productivity, especially in the more intangible-intensive industries.  The employees of these highly productive companies benefit from higher wages.  Because intangibles are contestable, companies are especially eager to hire people who are good at contesting them—appropriating spillovers from other firms or identifying and maximizing synergies.

Why are CEOs at many companies being paid so much more than other workers?  One reason relates to a “fundamental attribution error” whereby people explain a good business outcome by referring to what is simple and salient—like the skill of the CEO—rather than by acknowledging complexity and the fact that luck typically plays a major role.  It’s also possible, say Haskel and Westlake, that shareholders—especially those who are most diversified—are not paying much attention to CEO pay.

Housing Prices, Cities, Intangibles, and Wealth Inequality

Intangibles can help explain wealth inequality.  First, intangibles tend to drive up property prices.  Second, the mobility of intangible capital means it’s harder to tax.

In a world where intangibles are becoming more abundant and a more important part of the way businesses create value, the benefits to exploiting spillovers and synergies increase.  And as these benefits increase, we would expect businesses and their employees to want to locate in diverse, growing cities where synergies and spillovers abound.

Haskel and Westlake summarize how intangibles impact long-run inequality:

  • First, inequality of income.  The synergies and spillovers that intangibles create increase inequality between competing companies, and this inequality leads to increasing differences in employee pay… In addition, managing intangibles requires particular skills and education, and people with these skills are clustering in high-paid jobs in intangible-intensive firms.  Finally, the growing economic importance of the kind of people who manage intangibles helps foster myths that can be used to justify excessive pay, especially for top managers.
  • Second, inequality of wealth.  Thriving cities are places where spillovers and synergies abound.  The rise of intangibles makes cities increasingly attractive places to be, driving up the prices of prime property.  This type of inflation has been shown to be one of the major causes of the increase in the wealth of the richest.  In addition, intangibles are often mobile; they can be shifted across firms and borders.  This makes capital more mobile, which makes it harder to tax.  Since capital is disproportionately owned by the rich, this makes redistributive taxation to reduce wealth inequality harder.
  • Finally, inequality of esteem.  There is some evidence that supporters of populist movements… are more likely to hold traditional views and to score low on tests for the psychological trait of openness to experience.

 

INFRASTRUCTURE FOR INTANGIBLES, AND INTANGIBLE INFRASTRUCTURE

On the one hand, in order to thrive, the intangible economy needs new buildings in and around cities.  On the other hand, artistic and creative institutions are important for combinatorial innovation.  In the longer term, face-to-face interaction may eventually be phased out, but often these kinds of changes can take much longer than initially supposed.

(Illustration by Panimoni)

Haskel and Westlake comment:

The death of distance has failed to take place.  Indeed, the importance of spillovers and synergies has increased the importance of places where people come together to share ideas and the importance of the transport and social spaces that make cities work.

But the death of distance may have been postponed rather than cancelled.  Information technologies are slowly, gradually, replacing some aspects of face-to-face interaction.  This may be a slow-motion change, like the electrification of factories—if so, the importance of physical infrastructure will radically change.

Soft infrastructure will also matter increasingly.  The synergies between intangibles increase the importance of standards and norms, which together make up a kind of social infrastructure for intangible investment.  And standards and norms are underpinned by trust and social capital, which are particularly important in an intangible economy.

 

THE CHALLENGE OF FINANCING AN INTANGIBLE ECONOMY

Banks are often criticized for not providing enough capital for businesses to succeed.  Equity markets are criticized for being too short-term and also too influential.  Managers seem to fixate more and more on shorter term stock prices.  Managers may cut R&D to try to please short-term investors.  Haskel and Westlake remark:

These concerns drive public policy across the developed world:  most governments to some extent subsidize or coerce banks to lend to businesses, and they give tax advantages to companies that finance using debt.  Many countries are considering measures to make equity investors take a longer-term perspective, such as imposing taxes on short-term shareholdings or changing financial reporting requirements.  And most governments have spent money trying to encourage alternative forms of financing, particularly venture capital (VC), which is regarded as providing a big potential source of business growth and national wealth.

Banking:  The Problem of Lending in a World of Intangibles

When a bank lends money to a business, the bank usually has some recourse to the assets of the business if the debt isn’t repaid.  However, intangible assets are typically much harder to value than tangible assets, and frequently intangible assets don’t have much value at all when a business fails.  Thus it is difficult for a bank to lend to a business whose assets are mostly intangible.

This is why industries with mostly tangible assets—like oil and gas producers—have high leverage (are funded more with debt than equity), while industries with mostly intangible assets—like software—have less debt and more equity.

One way to increase bank lending to businesses with more intangible assets is for the government to cofund or guarantee bank loans.  A second way is financial innovation, such as finding ways to value intangible assets—like patents—more accurately.  A third way to deal with the issue of lending against intangibles is to get businesses to rely more on equity than debt.

Haskel and Westlake on how equity markets impact intangible investing:

There is some evidence that markets are short-termist, to the extent that management can sometimes boost their company’s share price by cutting intangible investment to preserve or increase profits, or cut investment to buy back stock.  But it also seems that some of what is happening is a sharpening of managerial incentives:  publicly held companies whose managers own stock focus on types of intangible investment that are more likely to be successful.  And the extent of market myopia varies:  companies with more concentrated, sophisticated investors are less likely to feel pressure to cut intangible investment than those with dispersed, unsophisticated ones.

Why VC Works for Intangibles

(Photo by designer491)

Haskel and Westlake observe:

VC has several characteristics that make it especially well-suited to intangible-intensive businesses:  VC firms take equity stakes, not debt, because intangible-rich businesses are unlikely to be worth much if they fail—all those sunk investments.  Similarly, to satisfy their own investors, VC funds rely on home-run successes, made possible by the scalability of assets like Google’s algorithms, Uber’s driver network, or Genentech’s patents.  Third, VC is often sequential, with rounds of funding proceeding in stages.  This is a response to the inherent uncertainty of intangible investment.

Leading VC firms and their partners are well-connected and credible, which helps in building networks to exploit synergies.

 

COMPETING, MANAGING, AND INVESTING IN THE INTANGIBLE ECONOMY

Businesses look to improve their performance in a way that is sustainable.  How can this be done?  The advice has always been to build and maintain distinctive assets.  Tangible assets are usually not distinctive, or at least not for long.  Haskel and Westlake:

It’s much more likely that the types of intangible assets we have talked about in this book are going to be distinctive:  reputation, product design, trained employees providing customer service.  Indeed, perhaps the most distinctive asset will be the ability to weave all these assets together; so a particularly valuable intangible asset will be the organization itself.

When it comes to management, Haskel and Westlake suggest replacing the question, “What are managers for?” with a deeper question, “What’s the role of authority in an economy?”

Markets work with minimal government interference.  However, firms can do a better job than dispersed individuals at organizing certain activities.  Managers are people at firms who have authority.  This is usually more efficient:  managers tell employees what to do rather than discussing or arguing about every step.

But if management is largely just monitoring, and software can do the job of monitoring, then what is the role of managers in an intangible-intensive economy?  For one, note Haskel and Westlake, the stakes tend to be much higher in the intangible economy.  Moreover, in synergistic firms, only managers may understand the big picture.

How can managers build a good organization in an intangible-intensive firm?  Haskel and Westlake explain:

…if you are primarily a producer of intangible assets (writing software, doing design, producing research) you probably want to build an organization that allows information to flow, helps serendipitous interactions, and keeps the key talent.  That probably means allowing more autonomy, fewer targets, and more access to the boss, even if that is at the cost of influence activities.

Leadership is important in an intangible economy.

(Photo by Raywoo)

Having voluntary followers is really useful in an intangible economy.  A follower will stay loyal to the firm, which keeps the tacit intangible capital at the firm.  Better, if they are inspired by and empathize with the leader, they will cooperate with each other and feed information up to the leader.  This is why leadership is going to be so valued in an intangible economy.  It can at best replace, and likely mitigate, the costly and possibly distortive aspects of managing by authority.

Investing

How can an investor discern if a business is building intangible assets?  Can investors learn about intangibles from accounting data?

Accountants try to match revenues with costs.  If the company has a long-lived asset that produces revenues, then the company measures the annual cost by depreciation or amortization of that asset.

The other way to measure the cost of a long-lived asset is to expense the entire cost of creating the asset in the year in which the expenditures are made.  However, this can lead to distortions.  First, the costs in creating the asset can make profits in that year appear unusually low.  By the same logic, if the asset in question continues producing revenues, then in future years profits will appear unusually high.

In the case of intangible assets, if the asset is bought from outside the company, then it is capitalized (and annual expenses are calculated based on depreciation or amortization).  If the asset is created within the company, then the costs are recognized when they are spent (even if the asset is long-lived).

The result is that much intangible investment is hidden because it is expensed.  This is a challenge for investors because economies are coming to rely increasingly on intangible assets.  Book value—which is frequently based largely on tangible assets—is less relevant for a company that relies on intangible assets—especially if the company develops those assets internally.

What Should Investors Do?

The simplest solution for investors is to invest in low-cost broad market index funds.  In this way, the investor will benefit from companies that rely on intangible assets.

Because index funds outpace 90-95% of all active investors if you measure performance over several decades, it already makes excellent sense for many investors to invest in index funds.

Haskel and Westlake sum up the chapter:

The growth of intangible investment has significant implications for managers, but it will affect different firms in different ways.  Firms that produce intangible assets will want to maximize synergies, create opportunities to learn from the ideas of others (and appropriate the spillovers from others’ intangibles), and retain talent.  These workplaces may end up looking rather like the popular image of hip knowledge-based companies.  But companies that rely on exploiting existing intangible assets may look very different, especially where the intangible assets are organizational structure and processes.  These may be much more controlled environments—Amazon’s warehouses rather than its headquarters.  Leadership will be increasingly prized, to the extent that it allows firms to coordinate intangible investments in different areas and exploit their synergies.

Financial investors who can understand the complexity of intangible-rich firms will also do well.  The greater uncertainty of intangible assets and the decreasing usefulness of company accounts put a premium on good equity research and on insight into firm management.

 

PUBLIC POLICY IN AN INTANGIBLE ECONOMY:  FIVE HARD QUESTIONS

Haskel and Westlake highlight five of the most important challenges in an intangible-rich economy:

  • First, intangibles tend to be contested:  it is hard to prove who owns them, and even then their benefits have a tendency to spill over to others.  Good intellectual property frameworks are important for an economy increasingly dependent on intangibles.
  • Second, in an intangible economy, synergies are very important. Combining different ideas and intangible assets is central to successful business innovation.  An important objective for policy makers is to create conditions for ideas to come together.
  • The third challenge relates to finance and investment.  Businesses and financial markets seem to underinvest in scalable, sunk intangible investments with a tendency to generate spillovers and synergies.  The current system of business finance exacerbates the problem.  A thriving intangible economy will significantly improve its financial system to make it easier for companies to invest in intangibles.
  • Fourth, it will probably be harder for most businesses to appropriate the benefits of capital investment in the economies of the future than in the tangible-rich economies we are familiar with.  Successful intangible-rich economies will have higher levels of public investment in intangibles.
  • Fifth, governments must work out how to deal with the dilemma of the particular type of inequality that intangibles seem to encourage.
(Illustration by Robert Wilson)

Clearer Rules and Norms about the Ownership of Intangibles

Stronger IP rights are not necessarily best because while they can increase incentive to invest, productivity gains are lowered.  Also, strengthening IP rights might accidentally favor incumbent rights-holders and patent trolls.

Clearer IP rights can be helpful, though.  They can reduce lawsuits that often end up in the notoriously troll-friendly Eastern District of Texas court.

Moreover, since intangible assets are often much more difficult to value than tangible assets, there are ways to help with this.  For instance, Ian Hargreaves in 2011 suggested that the UK have a Digital Copyright Exchange.  Another example is patent pools where firms coinvest in research and agree to share the resulting rights.

Helping Ideas Combine:  Maximizing the Benefits of Synergies

Good public policy should be just as assiduous about creating the conditions for knowledge to spread, mingle, and fructify as it is about creating property rights for those who invest in intangibles.

It should be easy to build new workplaces and homes in cities.  But simultaneously, cities have to be connected and livable.

A Financial Architecture for Intangible Investment

Governments should encourage new forms of debt that facilitate the ability to borrow against intangible assets.  Longer term, governments should help a shift from debt to equity financing.  Currently, debt is cheaper than equity due to the tax benefits of debt.  This must change, but it will be very difficult because vested interests still rely on debt.  Furthermore, new institutions will be required that provide equity financing to small and medium-size businesses.  Although these shifts will be challenging, the rewards will be ever greater, note Haskel and Westlake.

Solving the Intangible Investment Gap

Some large firms seem able to gain from both their own intangible investments and from intangible investments made by others.  These companies—like Google or Facebook—can be expected to continue making intangible investments.

Outside of these companies, the government and other public interest bodies (like large non-profit foundations) must make intangible investments.

The government is the investor of last resort.  Here are three practical tips given by Haskel and Westlake for government investment in intangibles:

  • Public R&D Funding.  This means the government spending more on university research, public research institutes, or research undertaken by businesses.  This type of government spending is not at all ideologically controversial and it can help a great deal over time.
  • Public Procurement.  When the US military funded the development of the semiconductor industry in the 1950s, they also acted as a lead customer.  This helped Texas Instruments and other firms not just to invest in R&D, but also to build the capacity to produce and sell chips.
  • Training and Education. Because it’s hard to predict what skills will be needed in 20 to 30 years, adult education may be a good area in which to invest.  This could also help with inequality to some extent.

 

BOOLE MICROCAP FUND

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

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

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

The 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: jb@boolefund.com

 

 

 

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

Ten Attributes of Great Investors

(Image:  Zen Buddha Silence by Marilyn Barbone.)

October 28, 2018

Michael Mauboussin is the author of several excellent books, including More Than You Know and Think Twice.  I wrote about these books here:

He has also written numerous papers, including Thirty Years: Reflections on the Ten Attributes of Great Investorshttps://bit.ly/2zlaljc

When it comes to value investing, Mauboussin is one of the best writers in the world.  Mauboussin highlights market efficiency, competitive strategy analysis, valuation, and decision making as chief areas of focus for him the past couple of decades.  Mauboussin:

What we know about each of these areas today is substantially greater than what we did in 1986, and yet we have an enormous amount to learn.  As I like to tell my students, this is an exciting time to be an investor because much of what we teach in business schools is a work-in-progress.

(Image by magele-picture)

Here are the Ten Attributes of Great Investors:

  • Be numerate (and understand accounting).
  • Understand value (the present value of free cash flow).
  • Properly assess strategy (or how a business makes money).
  • Compare effectively (expectations versus fundamentals).
  • Think probabilistically (there are few sure things).
  • Update your views effectively (beliefs are hypotheses to be tested, not treasures to be protected).
  • Beware of behavioral biases (minimizing constraints to good thinking).
  • Know the difference between information and influence.
  • Position sizing (maximizing the payoff from edge).
  • Read (and keep an open mind).

 

BE NUMERATE (AND UNDERSTAND ACCOUNTING)

Mauboussin notes that there are two goals when analyzing a company’s financial statements:

  • Translate the financial statements into free cash flow.
  • Determine how the competitive strategy of the company creates value.

The value of any business is the future free cash flow it will produce discounted back to the present.

(Photo by designer491)

Free cash flow is cash earnings minus investments that must be made to grow future earnings.  Free cash flow represents what owners of the business receive.  Warren Buffett refers to free cash flow as owner earnings.

Earnings alone cannot give you the value of a company.  You can grow earnings without growing value.  Whether earnings growth creates value depends on how much money the company invests to generate that growth.  If the ROIC (return on invested capital) of the company’s investment is below the cost of capital, then the resulting earnings growth destroys value rather than creates it.

After calculating free cash flow, the next goal in financial statement analysis is to figure out how the company’s strategy creates value.  For the company to create value, the ROIC must exceed the cost of capital.  Analyzing the company’s strategy means determining precisely how the company can get ROIC above the cost of capital.

Mauboussin writes that one way to analyze strategy is to compare two companies in the same business.  If you look at how the companies spend money, you can start to understand competitive positions.

Another way to grasp competitive position is by analyzing ROIC.

Photo by stanciuc

You can break ROIC into two parts:

  • profitability (net operating profit after tax / sales)
  • capital velocity (sales / invested capital)

Companies with high profitability but low capital velocity are using a differentiation strategy.  Their product is positioned in such a way that the business can earn high profit margins.  (For instance, a luxury jeweler.)

Companies with high capital velocity but low profitability have adopted a cost leadership strategy.  These businesses may have very thin profit margins, but they still generate high ROIC because their capital velocity is so high.  (Wal-Mart is a good example.)

Understanding how the company makes money can lead to insight about how long the company can maintain a high ROIC (if ROIC is high) or what the company must do to improve (if ROIC is low).

 

UNDERSTAND VALUE (THE PRESENT VALUE OF FREE CASH FLOW)

Mauboussin:

Great fundamental investors focus on understanding the magnitude and sustainability of free cash flow.  Factors that an investor must consider include where the industry is in its life cycle, a company’s competitive position within its industry, barriers to entry, the economics of the business, and management’s skill at allocating capital.

It’s worth repeating: The value of any business (or any financial asset) is the future free cash flow it will produce discounted back to the present.  Successful investors understand the variables that impact free cash flow.

Illustration by OpturaDesign

 

PROPERLY ASSESS STRATEGY (OR HOW A COMPANY MAKES MONEY)

Mauboussin says this attribute has two elements:

  • How does the company make money?
  • Does the company have a sustainable competitive advantage, and if so, how durable is it?

To see how a business makes money, you have to figure out the basic unit of analysis.  Mauboussin points out that the basic unit of analysis for a retailer is store economics:  How much does it cost to build a store?  What revenues will it generate?  What are the profit margins?

Regarding sustainable competitive advantage, Warren Buffett famously said:

The key to investing is not assessing how much an industry is going to affect society, or how much it will grow, but rather determining the competitive advantage of any given company and, above all, the durability of that advantage.

If a company has a sustainable competitive advantage, then ROIC (return on invested capital) is above the cost of capital.  To assess the durability of that advantage, you have to analyze the industry and how the company fits in.  Looking at the five forces that determine industry attractiveness is a common step.  You should also examine potential threats from disruptive innovation.

Mauboussin:

Great investors can appreciate what differentiates a company that allows it to build an economic moat around its franchise that protects the business from competitors.  The size and longevity of the moat are significant inputs into any thoughtful valuation.

Bodiam Castle, Photo by valeryegorov

Buffett popularized the term economic moat to refer to a sustainable competitive advantage.  Here’s what Buffett said at the Berkshire annual meeting in 2000:

So we think in terms of that moat and the ability to keep its width and its impossibility of being crossed as the primary criterion of a great business.  And we tell our managers we want the moat widened every year.  That doesn’t necessarily mean the profit will be more this year than it was last year because it won’t be sometimes.  However, if the moat is widened every year, the business will do very well.

 

COMPARE EFFECTIVELY (EXPECTATIONS VERSUS FUNDAMENTALS)

Mauboussin:

Perhaps the most important comparison an investor must make, and one that distinguishes average from great investors, is between fundamentals and expectations.  Fundamentals capture a sense of a company’s future financial performance.  Value drivers including sales growth, operating profit margins, investment needs, and return on investment shape fundamentals.  Expectations reflect the financial performance implied by the stock price.

Mauboussin mentions pari-mutuel betting, specifically horse racing.

(Photo by Elshaneo)

Fundamentals are how fast the horse will run, while expectations are the odds.

  • If a company has good fundamentals, but the stock price already reflects that, then you can’t expect to beat the market by investing in the stock.
  • If a company has bad fundamentals, but the stock price is overly pessimistic, then you can expect to beat the market by investing in the stock.

The best business in the world will not bring excess returns if the stock price already fully reflects the high quality of the business.  Similarly, a terrible business can produce excess returns if the stock price indicates that investors have overreacted.

To make money by investing in a stock, you have to have what great investor Michael Steinhardt calls a variant perception—a view at odds with the consensus view (as reflected in the stock price).  And you have to be right.

Mauboussin observes that humans are quick to compare but aren’t good at it.  This includes reasoning by analogy, e.g., asking whether a particular turnaround is similar to some other turnaround.  However, it’s usually better to figure out the base rate:  What percentage of all turnarounds succeed?  (Not a very high number, which is why Buffett quipped, “Turnarounds seldom turn.)

Another limitation of humans making comparisons is that people tend to see similarities when they’re looking for similarities, but they tend to see differences when they’re looking for differences.  For instance, Amos Tversky did an experiment in which the subjects were asked which countries are more similar, West Germany and East Germany, or Nepal and Ceylon?  Two-thirds answered West Germany and East Germany.  But then the subjects were asked which countries seemed more different.  Logic says that they would answer Nepal and Ceylon, but instead subjects again answered West Germany and East Germany.

 

THINK PROBABILISTICALLY (THERE ARE FEW SURE THINGS)

Great investors are always seeking an edge, where the price of an asset misrepresents the probabilities or the outcomes.  By similar logic, great investors evaluate each investment decision based on the process used rather than based on the outcome.

  • A good investment decision is one that if repeatedly made would be profitable over time.
  • A bad investment decision is one that if repeatedly made would lead to losses over time.

However, a good decision will sometimes lead to a bad outcome, while a bad decision will sometimes lead to a good outcome.  Investing is similar to other forms of betting in that way.

Photo by annebel146

Furthermore, what matters is not how often an investor is right, but rather how much the investor makes when he is right versus how much he loses when he is wrong.  In other words, what matters is not batting average but slugging percentage.  This is hard to put into practice due to loss aversion—the fact that as humans we feel a loss at least twice as much as an equivalent gain.

There are three ways of determining probabilities.  Subjective probability is a number that corresponds with your state of knowledge or belief.  Mauboussin gives an example:  You might come up with a probability that two countries will go to war.  Propensity is usually based on the physical properties of the system.  If a six-sided die is a perfect cube, then you know that the odds of a particular side coming up must be one out of six.  Frequency is the third approach.  Frequency—also called the base rate—is measured by looking at the outcomes of a proper reference class.  How often will a fair coin land on heads?  If you gather all the records you can of a fair coin being tossed, you’ll find that it lands on heads 50 percent of the time.  (You could run your own trials, too, by tossing a fair coin thousands or millions of times.)

Often subjective probabilities are useful as long as you remain open to new information and properly adjust your probabilities based on that information.  (The proper way to update such beliefs is using Bayes’s theorem.)  Subjective probabilities are useful when there’s no clear reference class—no relevant base rate.

When you’re looking at corporate performance—like sales or profit growth—it’s usually best to look at frequencies, i.e., base rates.

An investment decision doesn’t have to be complicated.  In fact, most good investment decisions are simple.  Mauboussin quotes Warren Buffett:

Take the probability of loss times the amount of possible loss from the probability of gain times the amount of possible gain.  That is what we’re trying to do.  It’s imperfect, but that’s what it’s all about.

Buffett again:

Investing is simple, but not easy.

 

UPDATE YOUR VIEWS EFFECTIVELY (BELIEFS ARE HYPOTHESES TO BE TESTED, NOT TREASURES TO BE PROTECTED)

People have a strong preference for consistency when it comes to their own beliefs.  And they expect others to be consistent.  The problem is compounded by confirmation bias, the tendency to look for and see only information that confirms your beliefs, and the tendency to interpret ambiguous information in a way that supports your beliefs.  As long as you feel like your beliefs are consistent, you’ll feel comfortable and won’t challenge your beliefs.

Illustration by intheskies

Great investors seek data and arguments that challenge their views.  Great investors also update their beliefs when they come across evidence that suggests they should.  The proper way to update beliefs is using Bayes’s theorem.  To see Bayes’s theorem and also a clear explanation and example, see: http://boolefund.com/the-signal-and-the-noise/

Mauboussin:

The best investors among us recognize that the world changes constantly and that all of the views that we hold are tenuous.  They actively seek varied points of view and update their beliefs as new information dictates.  The consequence of updated views can be action: changing a portfolio stance or weightings within a portfolio.  Others, including your clients, may view this mental flexibility as unsettling.  But good thinking requires maintaining as accurate a view of the world as possible.

 

BEWARE OF BEHAVIORAL BIASES (MINIMIZING CONSTRAINTS TO GOOD THINKING)

Mauboussin:

Keith Stanovich, a professor of psychology, likes to distinguish between intelligence quotient (IQ), which measures mental skills that are real and helpful in cognitive tasks, and rationality quotient (RQ), the ability to make good decisions.  His claim is that the overlap between these abilities is much lower than most people think.  Importantly, you can cultivate your RQ.

Rationality is only partly genetic.  You can train yourself to be more rational.

Great investors relentlessly train themselves to be as rational as possible.  Typically they keep an investment journal in which they write down the reasoning for every investment decision.  Later they look back on their decisions to analyze what they got right and where they went wrong.

Great investors also undertake a comprehensive study of cognitive biases.  For a list of cognitive biases, see these two blog posts:

It’s rarely enough just to know about cognitive biases.  Great investors take steps—like using a checklist—designed to mitigate the impact that innate cognitive biases have on investment decision-making.

Photo by Kenishirotie

 

KNOW THE DIFFERENCE BETWEEN INFORMATION AND INFLUENCE

A stock price generally represents the collective wisdom of investors about how a given company will perform in the future.  Most of the time, the crowd is more accurate than virtually any individual investor.

(Illustration by Marrishuanna)

However, periodically a stock price can get irrational.  (If this weren’t the case, great value investors could not exist.)  People regularly get carried away with some idea.  For instance, as Mauboussin notes, many investors got rich on paper by investing in dot-com stocks in the late 1990’s.  Investors who didn’t own dot-com stocks felt compelled to jump on board when they saw their neighbor getting rich (on paper).

Mauboussin mentions the threshold model from Mark Granovetter, a professor of sociology at Stanford University.  Mauboussin:

Imagine 100 potential rioters milling around in a public square.  Each individual has a “riot threshold,” the number of rioters that person would have to see in order to join the riot.  Say one person has a threshold of 0 (the instigator), one has a threshold of 1, one has a threshold of 2, and so on up to 99.  This uniform distribution of thresholds creates a domino effect and ensures that a riot will happen.  The instigator breaks a window with a rock, person one joins in, and then each individual piles on once the size of the riot reaches his or her threshold.  Substitute “buy dotcom stocks” for “join the riot” and you get the idea.

The point is that very few of the individuals, save the instigator, think that rioting is a good idea.  Most would probably shun rioting.  But once the number of others rioting reaches a threshold, they will jump in.  This is how the informational value of stocks is set aside and the influential component takes over.

Great investors are not influenced much at all by the behavior of other investors.  Great investors know that the collective wisdom reflected in a stock price is usually right, but sometimes wrong.  These investors can identify the occasional mispricing and then make an investment while ignoring the crowd.

 

POSITION SIZING (MAXIMIZING THE PAYOFF FROM EDGE)

Great investors patiently wait for situations where they have an edge, i.e., where the odds are in their favor.  Many investors understand the need for an edge.  However, fewer investors pay much attention to position sizing.

If you know the odds, there’s a formula—the Kelly criterion—that tells you exactly how much to bet in order to maximize your long-term returns.  The Kelly criterion can be written as follows:

  • F = p – [q/o]

where

  • F = Kelly criterion fraction of current capital to bet
  • o = Net odds, or dollars won per $1 bet if the bet wins (e.g., the bet may pay 5 to 1, meaning you win $5 per each $1 bet if the bet wins)
  • p = probability of winning
  • q = probability of losing = 1 – p

The Kelly criterion has a unique mathematical property: if you know the probability of winning and the net odds (payoff), then betting exactly the percentage determined by the Kelly criterion leads to the maximum long-term compounding of capital.  (This assumes that you’re going to make a long series of bets.)  Betting any percentage that is not equal to that given by the Kelly criterion will inevitably lead to lower compound growth over a long period of time.

Mauboussin adds:

Proper portfolio construction requires specifying a goal (maximize sum for one period or parlayed bets), identifying an opportunity set (lots of small edge or lumpy but large edge), and considering constraints (liquidity, drawdowns, leverage).   Answers to these questions suggest an appropriate policy regarding position sizing and portfolio construction.

In brief, most investors are ineffective at position sizing, but great investors are good at it.

 

READ (AND KEEP AN OPEN MIND)

Great investors generally read a ton.  They also read widely across many disciplines.  Moreover, as noted earlier, great investors seek to learn about the arguments of people who disagree with them.  Mauboussin:

Berkshire Hathaway’s Charlie Munger said that he really liked Albert Einstein’s point that “success comes from curiosity, concentration, perseverance and self-criticism. And by self-criticism, he meant the ability to change his mind so that he destroyed his own best-loved ideas.”  Reading is an activity that tends to foster all of those qualities.

(Photo by Lapandr)

Mauboussin continues:

Munger has also said, “In my whole life, I have known no wise people (over a broad subject matter area) who didn’t read all the time—none, zero.”  This may be hyperbolic, but seems to be true in the investment world as well.

 

BOOLE MICROCAP FUND

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

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

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

The 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: jb@boolefund.com

 

 

 

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

The Outsiders: Radically Rational CEOs

(Image:  Zen Buddha Silence by Marilyn Barbone.)

October 21, 2018

William Thorndike is the author of The Outsiders: Eight Unconventional CEOs and Their Radically Rational Blueprint for Success (Harvard Business Review Press, 2012).  It’s an excellent book profiling eight CEOs who compounded shareholder value at extraordinary rates over decades.

Through this book, value investors can improve their understanding of how to identify CEOs who maximize long-term returns to shareholders.  Also, investors can become better businesspeople, while businesspeople can become better investors.

I am a better investor because I am a businessman and a better businessman because I am an investor. – Warren Buffett

Thorndike explains that you only need three things to evaluate CEO performance:

  • the compound annual return to shareholders during his or her tenure
  • the return over the same period for peer companies
  • the return over the same period for the broader market (usually measured by the S&P 500)

Thorndike notes that 20 percent returns is one thing during a huge bull market—like 1982 to 1999.  It’s quite another thing if it occurs during a period when the overall market is flat—like 1966 to 1982—and when there are several bear markets.

Moreover, many industries will go out of favor periodically.  That’s why it’s important to compare the company’s performance to peers.

Thorndike mentions Henry Singleton as the quintessential outsider CEO.  Long before it was popular to repurchase stock, Singleton repurchased over 90% of Teledyne’s stock.  Also, he emphasized cash flow over earnings.  He never split the stock.  He didn’t give quarterly guidance.  He almost never spoke with analysts or journalists.  And he ran a radically decentralized organization.  Thorndike:

If you had invested a dollar with Singleton in 1963, by 1990, when he retired as chairman in the teeth of a severe bear market, it would have been worth $180.  That same dollar invested in a broad group of conglomerates would have been worth only $27, and $15 if invested in the S&P 500.  Remarkably, Singleton outperformed the index by over twelve times.

Thorndike observes that rational capital allocation was the key to Singleton’s success.  Thorndike writes:

Basically, CEOs have five essential choices for deploying capital—investing in existing operations, acquiring other businesses, issuing dividends, paying down debt, or repurchasing stock—and three alternatives for raising it—tapping internal cash flow, issuing debt, or raising equity.  Think of these options collectively as a tool kit.  Over the long term, returns for shareholders will be determined largely by the decisions a CEO makes in choosing which tools to use (and which to avoid) among these various options.  Stated simply, two companies with identical operating results and different approaches to allocating capital will derive two very different long-term outcomes for shareholders.

Warren Buffett has noted that most CEOs reach the top due to their skill in marketing, production, engineering, administration, or even institutional politics.  Thus most CEOs have not been prepared to allocate capital.

Thorndike also points out that the outsider CEOs were iconoclastic, independent thinkers.  But the outsider CEOs, while differing noticeably from industry norms, ended up being similar to one another.  Thorndike says that the outsider CEOs understood the following principles:

  • Capital allocation is a CEO’s most important job.
  • What counts in the long run is the increase in per share value, not overall growth or size.
  • Cash flow, not reported earnings, is what determines long-term value.
  • Decentralized organizations release entrepreneurial energy and keep both costs and ‘rancor’ down.
  • Independent thinking is essential to long-term success, and interactions with outside advisers (Wall Street, the press, etc.) can be distracting and time-consuming.
  • Sometimes the best investment opportunity is your own stock.
  • With acquisitions, patience is a vital… as is occasional boldness.

(Illustration by yiorgosgr)

Here are the sections in the blog post:

  • Introduction
  • Tom Murphy and Capital Cities Broadcasting
  • Henry Singleton and Teledyne
  • Bill Anders and General Dynamics
  • John Malone and TCI
  • Katharine Graham and The Washington Post Company
  • Bill Stiritz and Ralston Purina
  • Dick Smith and General Cinema
  • Warren Buffett and Berkshire Hathaway
  • Radical Rationality

 

INTRODUCTION

Only two of the eight outsider CEOs had MBAs.  And, writes Thorndike, they did not attract or seek the spotlight:

As a group, they shared old-fashioned, premodern values including frugality, humility, independence, and an unusual combination of conservatism and boldness.  They typically worked out of bare-bones offices (of which they were inordinately proud), generally eschewed perks such as corporate plans, avoided the spotlight wherever possible, and rarely communicated with Wall Street or the business press.  They also actively avoided bankers and other advisers, preferring their own counsel and that of a select group around them.  Ben Franklin would have liked these guys.

Thorndike describes how the outsider CEOs were iconoclasts:

Like Singleton, these CEOs consistently made very different decisions than their peers did.  They were not, however, blindly contrarian.  Theirs was an intelligent iconoclasm informed by careful analysis and often expressed in unusual financial metrics that were distinctly different from industry or Wall Street conventions.

Thorndike compares the outsider CEOs to Billy Beane as described by Michael Lewis in Moneyball.  Beane’s team, despite having the second-lowest payroll in the league, made the playoffs in four of his first six years on the job.  Beane had discovered newand unorthodoxmetrics that were more correlated with team winning percentage.

Thorndike mentions a famous essay about Leo Tolstoy written by Isaiah Berlin.  Berlin distinguishes between a “fox” who knows many things and a “hedgehog” who knows one thing extremely well.  Thorndike continues:

Foxes… also have many attractive qualities, including an ability to make connections across fields and to innovate, and the CEOs in this book were definite foxes.  They had familiarity with other companies and industries and disciplines, and this ranginess translated into new perspectives, which in turn helped them to develop new approaches that eventually translated into exceptional results.

(Photo by mbridger68)

 

TOM MURPHY AND CAPITAL CITIES BROADCASTING

When Murphy became CEO of Capital Cities in 1966, CBS’ market capitalization was sixteen times than that of Capital Cities.  Thirty years later, Capital Cities was three times as valuable as CBS.  Warren Buffett has said that in 1966, it was like a rowboat (Capital Cities) against QE2 (CBS) in a trans-Atlantic race.  And the rowboat won decisively!

Bill Paley, who ran CBS, used the enormous cash flow from its network and broadcast operations and undertook an aggressive acquisition program of companies in entirely unrelated fields.  Paley simply tried to make CBS larger without paying attention to the return on invested capital (ROIC).

Without a sufficiently high ROIC, growth destroys shareholder value instead of creating it.  But, like Paley, many business leaders at the time sought growth for its own sake.  Even if growth destroys value (due to low ROIC), it does make the business larger, bringing greater benefits to the executives.

Murphy’s goal, on the other hand, was to make his company as valuable as possible.  This meant maximizing profitability and ROIC:

…Murphy’s goal was to make his company more valuable… Under Murphy and his lieutenant, Dan Burke, Capital Cities rejected diversification and instead created an unusually streamlined conglomerate that focused laser-like on the media businesses it knew well.  Murphy acquired more radio and TV stations, operated them superbly well, regularly repurchased his shares, and eventually acquired CBS’s rival broadcast network ABC.

(Capital Cities/ABC, Inc. logo, via Wikimedia Commons)

Burke excelled in operations, while Murphy excelled in making acquisitions.  Together, they were a great team—unmatched, according to Warren Buffett.  Burke said his ‘job was to create free cash flow and Murphy’s was to spend it.’

During the mid-1970s, there was an extended bear market.  Murphy aggressively repurchased shares, mostly at single-digit price-to-earnings (P/E) multiples.

Thorndike writes that in January 1986, Murphy bought the ABC Network and its related broadcasting assets for $3.5 billion with financing from his friend Warren Buffett.  Thorndike comments:

Burke and Murphy wasted little time in implementing Capital Cities’ lean, decentralized approach—immediately cutting unnecessary perks, such as the executive elevator and the private dining room, and moving quickly to eliminate redundant positions, laying off fifteen hundred employees in the first several months after the transaction closed.  They also consolidated offices and sold off unnecessary real estate, collecting $175 million for the headquarters building in midtown Manhattan…

In the nine years after the transaction, revenues and cash flows grew significantly in every major ABC business line, including the TV stations, the publishing assets, and ESPN.  Even the network, which had been in last place at the time of the acquisition, was ranked number one in prime time ratings and was more profitable than either CBS or NBC.

In 1993, Burke retired.  And in 1995, Murphy, at Buffett’s suggestion, met with Michael Eisner, the CEO of Disney.  Over a few days, Murphy sold Capital Cities/ABC to Disney for $19 billion, which was 13.5 times cash flow and 28 times net income.  Thorndike:

He left behind an ecstatic group of shareholders—if you had invested a dollar with Tom Murphy as he became CEO in 1966, that dollar would have been worth $204 by the time he sold the company to Disney.  That’s a remarkable 19.9 percent internal rate of return over twenty-nine years, significantly outpacing the 10.1 percent return for the S&P 500 and 13.2 percent return for an index of leading media companies over the same period.

Thorndike points out the decentralization was one the keys to success for Capital Cities.  There was a single paragraph on the inside cover of every Capital Cities annual report:

‘Decentralization is the cornerstone of our philosophy.  Our goal is to hire the best people we can and give them the responsibility and authority they need to perform their jobs.  All decisions are made at the local level… We expect our managers… to be forever cost conscious and to recognize and exploit sales potential.’

Headquarters had almost no staff.  There were no vice presidents in marketing, strategic planning, or human resources.  There was no corporate counsel and no public relations department.  The environment was ideal for entrepreneurial managers.  Costs were minimized at every level.

Burke developed an extremely detailed annual budgeting process for every operation.  Managers had to present operating and capital budgets for the coming year, and Burke (and his CFO, Ron Doerfler) went through the budgets line-by-line:

The budget sessions were not perfunctory and almost always produced material changes.  Particular attention was paid to capital expenditures and expenses.  Managers were expected to outperform their peers, and great attention was paid to margins, which Burke viewed as ‘a form of report card.’  Outside of these meetings, managers were left alone and sometimes went months without hearing from corporate.

High margins resulted not only from cost minimization, but also from Murphy and Burke’s focus on revenue growth and advertising market share.  They invested in their properties to ensure leadership in local markets.

When it came to acquisitions, Murphy was very patient and disciplined.  His benchmark ‘was a double-digit after-tax return over ten years without leverage.’  Murphy never won an auction as a result of his discipline.  Murphy also had a unique negotiating style.

Murphy thought that, in the best transactions, everyone comes away happy.  He believed in ‘leaving something on the table’ for the seller.  Murphy would often ask the seller what they thought the property was worth.  If Murphy thought the offer was fair, he would take it.  If he thought the offer was high, he would counter with his best price.  If the seller rejected his counter-offer, Murphy would walk away.  He thought this approach saved time and avoided unnecessary friction.

Thorndike concludes his discussion of Capital Cities:

Although the focus here is on quantifiable business performance, it is worth noting that Murphy built a universally admired company at Capital Cities with an exceptionally strong culture and esprit de corps (at least two different groups of executives still hold regular reunions).

 

HENRY SINGLETON AND TELEDYNE

Singleton earned bachelor’s, master’s, and PhD degrees in electrical engineering from MIT.  He programmed the first student computer at MIT.  He won the Putnam Medal as the top mathematics student in the country in 1939.  And he was 100 points away from being a chess grandmaster.

Singleton worked as a research engineer at North American Aviation and Hughes Aircraft in 1950.  Tex Thornton recruited him to Litton Industries in the late 1950s, where Singleton invented an inertial guidance system—still in use—for commercial and military aircraft.  By the end of the decade, Singleton had grown Litton’s Electronic Systems Group to be the company’s largest division with over $80 million in revenue.

Once he realized he wouldn’t succeed Thornton as CEO, Singleton left Litton and founded Teledyne with his colleague George Kozmetzky.  After acquiring three small electronics companies, Teledyne successfully bid for a large naval contract.  Teledyne became a public company in 1961.

(Photo of Teledyne logo by Piotr Trojanowski)

In the 1960’s, conglomerates had high price-to-earnings (P/E) ratios and were able to use their stock to buy operating companies at relatively low multiples.  Singleton took full advantage of this arbitrage opportunity.  From 1961 to 1969, he purchased 130 companies in industries from aviation electronics to specialty metals and insurance.  Thorndike elaborates:

Singleton’s approach to acquisitions, however, differed from that of other conglomerateurs.  He did not buy indiscriminately, avoiding turnaround situations, and focusing instead on profitable, growing companies with leading market positions, often in niche markets… Singleton was a very disciplined buyer, never paying more than twelve times earnings and purchasing most companies at significantly lower multiples.  This compares to the high P/E multiple on Teledyne’s stock, which ranged from a low of 20 to a high of 50 over this period.

In mid-1969, Teledyne was trading at a lower multiple, while acquisition prices were increasing.  So Singleton completely stopped acquiring companies.

Singleton ran a highly decentralized company.  Singleton also did not report earnings, but instead focused on free cash flow (FCF)—what Buffett calls owner earnings.  The value of any business is all future FCF discounted back to the present.

FCF = net income + DDA – capex

(There are also adjustments to FCF based on changes in working capital.  DDA is depreciation, depletion, and amortization.)

At Teledyne, bonus compensation for all business unit managers was based on the maximization of free cash flow.  Singleton—along with his roommate from the Naval Academy, George Roberts—worked to improve margins and significantly reduce working capital.  Return on assets at Teledyne was greater than 20 percent in the 1970s and 1980s.  Charlie Munger calls these results from Teledyne ‘miles higher than anybody else… utterly ridiculous.’  This high profitability generated a great deal of excess cash, which was sent to Singleton to allocate.

Starting in 1972, Singleton started buying back Teledyne stock because it was cheap.  During the next twelve years, Singleton repurchased over 90 percent of Teledyne’s stock.  Keep in mind that in the early 1970s, stock buybacks were seen as a lack of investment opportunity.  But Singleton realized buybacks were far more tax-efficient than dividends.  And buybacks done when the stock is noticeably cheap create much value.  Whenever the returns from a buyback seemed higher than any alternative use of cash, Singleton repurchased shares.  Singleton spent $2.5 billion on buybacks—an unbelievable amount at the time—at an average P/E multiple of 8.  (When Teledyne issued shares, the average P/E multiple was 25.)

In the insurance portfolios, Singleton invested 77 percent in equities, concentrated on just a few stocks.  His investments were in companies he knew well that had P/E ratios at or near record lows.

In 1986, Singleton started going in the opposite direction:  deconglomerating instead of conglomerating.  He was a pioneer of spinning off various divisions.  And in 1987, Singleton announced the first dividend.

From 1963 to 1990, when Singleton stepped down as chairman, Teledyne produced 20.4 percent compound annual returns versus 8.0 percent for the S&P 500 and 11.6 percent for other major conglomerates.  A dollar invested with Singleton in 1963 would have been worth $180.94 by 1990, nearly ninefold outperformance versus his peers and more than twelvefold outperformance versus the S&P 500.

 

BILL ANDERS AND GENERAL DYNAMICS

In 1989, the Berlin Wall came down and the U.S. defense industry’s business model had to be significantly downsized.  The policy of Soviet containment had become obsolete almost overnight.

General Dynamics had a long history selling major weapons to the Pentagon, including the B-29 bomber, the F-16 fighter plane, submarines, and land vehicles (such as tanks).  The company had diversified into missiles and space systems, as well as nondefense business including Cessna commercial planes.

(General Dynamics logo, via Wikimedia Commons)

W(hen Bill Anders took over General Dynamics in January 1991, the company had $600 million in debt and negative cash flow.  Revenues were $10 billion, but the market capitalization was just $1 billion.  Many thought the company was headed into bankruptcy.  It was a turnaround situation.

Anders graduated from the Naval Academy in 1955 with an electrical engineering degree.  He was an airforce fighter pilot during the Cold War.  In 1963 he earned a master’s degree in nuclear engineering and was chosen to join NASA’s elite astronaut corps.  Thorndike writes:

As the lunar module pilot on the 1968 Apollo 8 mission, Anders took the now-iconic Earthrise photograph, which eventually appeared on the covers of Time, Life, and American Photography.

Anders was a major general when he left NASA.  He was made the first chairman of the Nuclear Regulatory Commission.  Then he served as ambassador to Norway.  After that, he worked at General Electric and was trained in their management approach.  In 1984, Anders was hired to run the commercial operations of Textron Corporation.  He was not impressed with the mediocre businesses and the bureaucratic culture.  In 1989, he was invited to join General Dynamics as vice-chairman for a year before becoming CEO.

Anders realized that the defense industry had a great deal of excess capacity after the end of the Cold War.  Following Welch’s approach, Anders concluded that General Dynamics should only be in businesses where it was number one or two.  General Dynamics would stick to businesses it knew well.  And it would exit businesses that didn’t meet these criteria.

Anders also wanted to change the culture.  Instead of an engineering focus on ‘larger, faster, more lethal’ weapons, Anders wanted a focus on metrics such as return on equity (ROE).  Anders concluded that maximizing shareholder returns should be the primary business goal.  To help streamline operations, Anders hired Jim Mellor as president and COO.  In the first half of 1991, Anders and Mellor replaced twenty-one of the top twenty-five executives.

Anders then proceeded to generate $5 billion in cash through the sales of noncore businesses and by a significant improvement in operations.  Anders and Mellor created a culture focused on maximizing shareholder returns.  Anders sold most of General Dynamics’ businesses.  He also sought to grow the company’s largest business units through acquisition.

When Anders went to acquire Lockheed’s smaller fighter plane division, he met with a surprise:  Lockheed’s CEO made a high counteroffer for General Dynamics’ F-16 business.  Because the fighter plane division was a core business for General Dynamics—not to mention that Anders was a fighter pilot and still loved to fly—this was a crucial moment for Anders.  He agreed to sell the business on the spot for a very high price of $1.5 billion.  Anders’ decision was rational in the context of maximizing shareholder returns.

With the cash pile growing, Anders next decided not to make additional acquisitions, but to return cash to shareholders.  First he declared three special dividends—which, because they were deemed ‘return of capital,’ were not subject to capital gains or ordinary income taxes.  Next, Anders announced an enormous $1 billion tender offer for 30 percent of the company’s stock.

A dollar invested when Anders took the helm would have been worth $30 seventeen years later.  That same dollar would have been worth $17 if invested in an index of peer companies and $6 if invested in the S&P.

 

JOHN MALONE AND TCI

While at McKinsey, John Malone came to realize how attractive the cable television business was.  Revenues were very predictable.  Taxes were low.  And the industry was growing very fast.  Malone decided to build a career in cable.

Malone’s father was a research engineer and his mother a former teacher.  Malone graduated from Yale with degrees in economics and electrical engineering.  Then Malone earned master’s and PhD degrees in operations research from Johns Hopkins.

Malone’s first job was at Bell Labs, the research arm of AT&T.  After a couple of years, he moved to McKinsey Consulting.  In 1970, a client, General Instrument, offered Malone the chance to run its cable television equipment division.  He jumped at the opportunity.

After a couple of years, Malone was sought by two of the largest cable companies, Warner Communications and Tele-Communications Inc. (TCI).  Malone chose TCI.  Although the salary would be 60 percent lower, he would get more equity at TCI.  Also, he and his wife preferred Denver to Manhattan.

(TCI logo, via Wikimedia Commons)

The industry had excellent tax characteristics:

Prudent cable operators could successfully shelter their cash flow from taxes by using debt to build new systems and by aggressively depreciating the costs of construction.  These substantial depreciation charges reduced taxable income as did the interest expense on the debt, with the result that well-run cable companies rarely showed net income, and as a result, rarely paid taxes, despite very healthy cash flows.  If an operator then used debt to buy or build additional systems and depreciated the newly acquired assets, he could continue to shelter his cash flow indefinitely.

Just after Malone took over as CEO of TCI in 1973, the 1973-1974 bear market left TCI in a dangerous position.  The company was on the edge of bankruptcy due to its very high debt levels.  Malone spent the next few years meeting with bankers and lenders to keep the company out of bankruptcy.  Also during this time, Malone instituted new discipline in operations, which resulted in a frugal, entrepreneurial culture.  Headquarters was austere.  Executives stayed together in motels while on the road.

Malone depended on COO J. C. Sparkman to oversee operations, while Malone focused on capital allocation.  TCI ended up having the highest margins in the industry as a result.  They earned a reputation for underpromising and overdelivering.

In 1977, the balance sheet was in much better shape.  Malone had learned that the key to creating value in cable television was financial leverage and leverage with suppliers (especially programmers).  Both types of leverage improved as the company became larger.  Malone had unwavering commitment to increasing the company’s size.

The largest cost in a cable television system is fees paid to programmers (HBO, MTV, ESPN, etc.).  Larger cable operators can negotiate lower programming costs per subscriber.  The more subscribers the cable company has, the lower its programming cost per subscriber.  This led to a virtuous cycle:

[If] you buy more systems, you lower your programming costs and increase your cash flow, which allows more financial leverage, which can then be used to buy more systems, which further improves your programming costs, and so on… no one else at the time pursued scale remotely as aggressively as Malone and TCI.

Malone also focused on minimizing reported earnings (and thus taxes).  At the time, this was highly unconventional since most companies focused on earnings per share.  TCI gained an important competitive advantage by minimizing earnings and taxes.  Terms like EBITDA were introduced by Malone.

Between 1973 and 1989, the company made 482 acquisitions.  The key was to maximize the number of subscribers.  (When TCI’s stock dropped, Malone repurchased shares.)

By the late 1970s and early 1980s, after the introduction of satellite-delivered channels such as HBO and MTV, cable television went from primarily rural customers to a new focus on urban markets.  The bidding for urban franchises quickly overheated.  Malone avoided the expensive urban franchise wars, and stayed focused on acquiring less expensive rural and suburban subscribers.  Thorndike:

When many of the early urban franchises collapsed under a combination of too much debt and uneconomic terms, Malone stepped forward and acquired control at a fraction of the original cost.

Malone also established various joint ventures, which led to a number of cable companies in which TCI held a minority stake.  Over time, Malone created a great deal of value for TCI by investing in young, talented entrepreneurs.

From 1973 to 1998, TCI shareholders enjoyed a compound annual return of 30.3 percent, compared to 20.4 percent for other publicly traded cable companies and 14.3 percent for the S&P 500.  A dollar invested in TCI at the beginning was worth over $900 by mid-1998.  The same dollar was worth $180 if invested in other publicly traded cable companies and $22 if invested in the S&P 500.

Malone never used spreadsheets.  He looked for no-brainers that could be understood with simple math.  Malone also delayed capital expenditures, generally until the economic viability of the investment had been proved.  When it came to acquisitions—of which there were many—Malone would only pay five times cash flow.

 

KATHARINE GRAHAM AND THE WASHINGTON POST COMPANY

Katharine Graham was the daughter of financier Eugene Meyer.  In 1940, she married Philip Graham, a brilliant lawyer.  Meyer hired Philip Graham to run The Washington Post Company in 1946.  He did an excellent job until his tragic suicide in 1963.

(The Washington Post logo, via Wikimedia Commons)

Katharine was unexpectedly thrust into the CEO role.  At age forty-six, she had virtually no preparation for this role and she was naturally shy.  But she ended up doing an amazing job.  From 1971 to 1993, the compound annual return to shareholders was 22.3 percent versus 12.4 percent for peers and 7.4 percent for the S&P 500.  A dollar invested in the IPO was worth $89 by the time she retired, versus $5 for the S&P and $14 for her peer group.  These are remarkable margins of outperformance.

After a few years of settling into the new role, she began to take charge.  In 1967, she replaced longtime editor in chief Russ Wiggins with the brash Ben Bradlee, who was forty-four years old.

In 1971, she took the company public to raise capital for acquisitions.  This was what the board had recommended.  At the same time, the newspaper encountered the Pentagon Papers crisis.  The company was going to publish a highly controversial (and negative) internal Pentagon opinion of the war in Vietnam that a court had barred the New York Times from publishing.  The Nixon administration threatened to challenge the company’s broadcast licenses if it published the report:

Such a challenge would have scuttled the stock offering and threatened one of the company’s primary profit centers.  Graham, faced with unclear legal advice, had to make the decision entirely on her own.  She decided to go ahead and print the story, and the Post’s editorial reputation was made.  The Nixon administration did not challenge the TV licenses, and the offering, which raised $16 million, was a success.

In 1972, with Graham’s full support, the paper began in-depth investigations into the Republican campaign lapses that would eventually become the Watergate scandal.  Bradlee and two young investigative reporters, Carl Bernstein and Bob Woodward, led the coverage of Watergate, which culminated with Nixon’s resignation in the summer of 1974.  This led to a Pulitzer for the Post—one of an astonishing eighteen during Bradlee’s editorship—and established the paper as the only peer of the New York Times.  All during the investigation, the Nixon administration threatened Graham and the Post.  Graham firmly ignored them.

In 1974, an unknown investor eventually bought 13 percent of the paper’s shares.  The board advised Graham not to meet with him.  Graham ignored the advice and met the investor, whose name was Warren Buffett.  Buffett quickly became Graham’s business mentor.

In 1975, the paper faced a huge strike led by the pressmen’s union.  Graham, after consulting Buffett and the board, decided to fight the strike.  Graham, Bradlee, and a very small crew managed to get the paper published for 139 consecutive days.  Then the pressmen finally agreed to concessions.  These concessions led to significantly improved profitability for the paper.  It was also the first time a major city paper had broken a strike.

Also on advice from Buffett, Graham began aggressively buying back stock.  Over the next few years, she repurchased nearly 40 percent of the company’s stock at very low prices (relative to intrinsic value).  No other major papers did so.

In 1981, the Post’s rival, the Washington Star, ceased publication.  This allowed the Post to significantly increase circulation.  At the same time, Graham hired Dick Simmons as COO.  Simmons successfully lowered costs and improved profits.  Simmons also emphasized bonus compensation based on performance relative to peer newspapers.

In the early 1980s, the Post spent years not acquiring any companies, even though other major newspapers were making more deals than ever.  Graham was criticized, but stuck to her financial discipline.  In 1983, however, after extensive research, the Post bought cellular telephone businesses in six major markets.  In 1984, the Post acquired the Stanley Kaplan test prep business.  And in 1986, the paper bought Capital Cities’ cable television assets for $350 million.  All of these acquisitions would prove valuable for the Post in the future.

In 1988, Graham sold the paper’s telephone assets for $197 million, a very high return on investment.  Thorndike continues:

During the recession of the early 1990s, when her overleveraged peers were forced to the sidelines, the company became uncharacteristically acquisitive, taking advantage of dramatically lower prices to opportunistically purchase cable television systems, underperforming TV stations, and a few education businesses.

When Kay Graham stepped down as chairman in 1993, the Post Company was by far the most diversified among its major newspaper peers, earning almost half its revenues and profits from non-print sources.  This diversification would position the company for further outperformance under her son Donald’s leadership.

 

BILL STIRITZ AND RALSTON PURINA

Bill Stiritz was at Ralston seventeen years before becoming CEO at age forty-seven.

This seemingly conventional background, however, masked a fiercely independent cast of mind that made him a highly effective, if unlikely, change agent.  When Stiritz assumed the CEO role, it would have been impossible to predict the radical transformation he would effect at Ralston and the broader influence it would have on his peers in the food and packaged goods industries.

(Purina logo, via Wikimedia Commons)

Stiritz attended the University of Arkansas for a year but then joined the navy for four years.  While in the navy, he developed his poker skills enough so that poker eventually would pay for his college tuition.  Stiritz completed his undergraduate degree at Northwestern, majoring in business.  (In his mid-thirties, he got a master’s degree in European history from Saint Louis University.)

Stiritz first worked at the Pillsbury Company as a field rep putting cereal on store shelves.  He was promoted to product manager and he learned about consumer packaged goods (CPG) marketing.  Wanting to understand advertising and media better, he started working two years later at the Gardner Advertising agency in St. Louis.  He focused on quantitative approaches to marketing such as the new Nielsen ratings service, which gave a detailed view of market share as a function of promotional spending.

In 1964, Stiritz joined Ralston Purina in the grocery products division (pet food and cereals).  He became general manager of the division in 1971.  While Stiritz was there, operating profits increased fiftyfold due to new product introductions and line extensions.  Thorndike:

Stiritz personally oversaw the introduction of Purina Puppy and Cat Chow, two of the most successful launches in the history of the pet food industry.  For a marketer, Stiritz was highly analytical, with a natural facility for numbers and a skeptical, almost prickly temperament.

Thorndike continues:

On assuming the CEO role in 1981, Stiritz wasted little time in aggressively restructuring the company.  He fully appreciated the exceptionally attractive economics of the company’s portfolio of consumer brands and promptly reorganized the company around these businesses, which he believed offered an attractive combination of high margins and low capital requirements.  He immediately began to remove the underpinnings of his predecessor’s strategy, and his first moves involved actively divesting businesses that did not meet his criteria for profitability and returns.

After a number of divestitures, Ralston was a pure branded products company.  In the early 1980s, Stiritz began repurchasing stock aggressively.  No other major branded products company was repurchasing stock at that time.

Stiritz then bought Continental Baking, the maker of Twinkies and Wonder Bread.  He expanded distribution, cut costs, introduced new products, and increased cash flow materially, creating much value for shareholders.

Then in 1986, Stiritz bought the Energizer Battery division from Union Carbide for $1.5 billion.  The business had been a neglected operation at Union Carbide.  Stiritz thought it was undermanaged and also part of a growing duopoly market.

By the late 1980s, almost 90 percent of Ralston’s revenues were from consumer packaged goods.  Pretax profit margins increased from 9 to 15 percent.  ROE went from 15 to 37 percent.  Since the share base was reduced by aggressive buybacks, earnings and cash flow per share increased dramatically.  Stiritz continued making very careful acquisitions and divestitures, with each decision based on an in-depth analysis of potential returns for shareholders.

Stiritz also began spinning off some businesses he thought were not receiving the attention they deserved—either internally or from Wall Street.  Spin-offs not only can highlight the value of certain business units.  Spin-offs also allow the deferral of capital gains taxes.

Finally, Stiritz sold Ralston itself to Nestle for $10.4 billion, or fourteen times cash flow.  This successfully concluded Stiritz’ career at Ralston.  A dollar invested with Stiritz when he became CEO was worth $57 nineteen years later.  The compound return was 20.0 percent versus 17.7 percent for peers and 14.7 percent for the S&P 500.

Stiritz didn’t like the false precision of detailed financial models.  Instead, he focused only on the few key variables that mattered, including growth and competitive dynamics.  When Ralston bought Energizer, Stiritz and his protégé Pat Mulcahy, along with a small group, took a look at Energizer’s books and then wrote down a simple, back of the envelope LBO model.  That was it.

Since selling Ralston, Stiritz has energetically managed an investment partnership made up primarily of his own capital.

 

DICK SMITH AND GENERAL CINEMA

In 1922, Phillip Smith borrowed money from friends and family, and opened a theater in Boston’s North End.  Over the next forty years, Smith built a successful chain of theaters.  In 1961, Phillip Smith took the company public to raise capital.  But in 1962, Smith passed away.  His son, Dick Smith, took over as CEO.  He was thirty-seven years old.

(General Cinema logo, via Wikimedia Commons)

Dick Smith demonstrated a high degree of patience in using the company’s cash flow to diversify away from the maturing drive-in movie business.

Smith would alternate long periods of inactivity with the occasional very large transaction.  During his tenure, he would make three significant acquisitions (one in the late 1960s, one in the mid-1980s, and one in the early 1990s) in unrelated businesses:  soft drink bottling (American Beverage Company), retailing (Carter Hawley Hale), and publishing (Harcourt Brace Jovanovich).  This series of transactions transformed the regional drive-in company into an enormously successful consumer conglomerate.

Dick Smith later sold businesses that he had earlier acquired.  His timing was extraordinarily good, with one sale in the late 1980s, one in 2003, and one in 2006.  Thorndike writes:

This accordion-like pattern of expansion and contraction, of diversification and divestiture, was highly unusual (although similar in some ways to Henry Singleton’s at Teledyne) and paid enormous benefits for General Cinema’s shareholders.

Smith graduated from Harvard with an engineering degree in 1946.  He worked as a naval engineer during World War II.  After the war, he didn’t want an MBA.  He wanted to join the family business.  In 1956, Dick Smith’s father made him a full partner.

Dick Smith recognized before most others that suburban theaters were benefitting from strong demographic trends.  This led him to develop two new practices.

First, it had been assumed that theater owners should own the underlying land.  But Smith realized that a theater in the right location could fairly quickly generate predictable cash flow.  So he pioneered lease financing for new theaters, which significantly reduced the upfront investment.

Second, he added more screens to each theater, thereby attracting more people, who in turn bought more high-margin concessions.

Throughout the 1960s and into the early 1970s, General Cinema was getting very high returns on its investment in new theaters.  But Smith realized that such growth was not likely to continue indefinitely.  He started searching for new businesses with better long-term prospects.

In 1968, Smith acquired the American Beverage Company (ABC), the largest, independent Pepsi bottler in the country.  Smith knew about the beverage business based on his experience with theater concessions.  Smith paid five times cash flow and it was a very large acquisition for General Cinema at the time.  Thorndike notes:

Smith had grown up in the bricks-and-mortar world of movie theaters, and ABC was his first exposure to the value of businesses with intangible assets, like beverage brands.  Smith grew to love the beverage business, which was an oligopoly with very high returns on capital and attractive long-term growth trends.  He particularly liked the dynamics within the Pepsi bottler universe, which was fragmented and had many second- and third-generation owners who were potential sellers (unlike the Coke system, which was dominated by a smaller number of large independents).  Because Pepsi was the number two brand, its franchises often traded at lower valuations than Coke’s.

ABC was a platform companyother companies could be added easily and efficiently.  Smith could buy new franchises at seemingly high multiples of the seller’s cash flow and then quickly reduce the effective price through reducing expenses, minimizing taxes, and improving marketing.  So Smith acquired other franchises.

Due to constant efforts to reduce costs by Smith and his team, ABC had industry-leading margins.  Soon thereafter, ABC invested $20 million to launch Sunkist.  In 1984, Smith sold Sunkist to Canada Dry for $87 million.

Smith sought another large business to purchase.  He made a number of smaller acquisitions in the broadcast media business.  But his price discipline prevented him from buying very much.

Eventually General Cinema bought Carter Hawley Hale (CHH), a retail conglomerate with several department store and specialty retail chains.  Woody Ives, General Cinema’s CFO, was able to negotiate attractive terms:

Ives negotiated a preferred security that guaranteed General Cinema a 10 percent return, allowed it to convert its interest into 40 percent of the common stock if the business performed well, and included a fixed-price option to buy Waldenbooks, a wholly owned subsidiary of CHH…

Eventually General Cinema would exchange its 40 percent ownership in CHH shares for a controlling 60 percent stake in the company’s specialty retail division, whose primary asset was the Neiman Marcus chain.  The long-term returns on the company’s CHH investment were an extraordinary 51.2 percent.  The CHH transaction moved General Cinema decisively into retailing, a new business whose attractive growth prospects were not correlated with either the beverage or the theater businesses.

In the late 1980s, Smith noticed that a newly energetic Coke was attacking Pepsi in local markets.  At the same time, beverage franchises were selling for much higher prices as their good economics were more widely recognized.  So Smith sold the bottling business in 1989 to Pepsi for a record price.  After the sale, General Cinema was sitting on $1 billion in cash.  Smith started looking for another diversifying acquisition.

It didn’t take him long to find one.  In 1991, after a tortuous eighteen-month process, Smith made his largest and last acquisition, buying publisher Harcourt Brace Jovanovich (HBJ) in a complex auction process and assembling General Cinema’s final third leg.  HBJ was a leading educational and scientific publisher that also owned a testing business and an outplacement firm.  Since the mid-1960s, the firm had been run as a personal fiefdom by CEO William Jovanovich.  In 1986, the company received a hostile takeover bid from the renegade British publisher Robert Maxwell, and in response Jovanovich had taken on large amounts of debt, sold off HBJ’s amusement park business, and made a large distribution to shareholders.

General Cinema management concluded, after examining the business, that HBJ would fit their acquisition criteria.  Moreover, General Cinema managers thought HBJ’s complex balance sheet would probably deter other buyers.  Thorndike writes:

After extensive negotiations with the company’s many debt holders, Smith agreed to purchase the company for $1.56 billion, which represented 62 percent of General Cinema’s enterprise value at the time—an enormous bet.  This price equaled a multiple of six times cash flow for HBJ’s core publishing assets, an attractive price relative to comparable transactions (Smith would eventually sell those businesses for eleven times cash flow).

Thorndike continues:

Following the HBJ acquisition in 1991, General Cinema spun off its mature theater business into a separate publicly traded entity, GC Companies (GCC), allowing management to focus its attention on the larger retail and publishing businesses.  Smith and his management team proceeded to operate both the retail and the publishing businesses over the next decade.  In 2003, Smith sold the HBJ publishing assets to Reed Elsevier, and in 2006 he sold Neiman Marcus, the last vestige of the General Cinema portfolio, to a consortium of private equity buyers.  Both transactions set valuation records within their industries, capping an extraordinary run for Smith and General Cinema shareholders.

From 1962 to 1991, Smith had generated 16.1 percent compound annual return versus 9 percent for the S&P 500 and 9.8 percent for GE.  A dollar invested with Dick Smith in 1962 would be worth $684 by 1991.  The same dollar would $43 if invested in the S&P and $60 if invested in GE.

 

WARREN BUFFETT AND BERKSHIRE HATHAWAY

Buffett was first attracted to the old textile mill Berkshire Hathaway because its price was cheap compared to book value.  Thorndike tells the story:

At the time, the company had only a weak market position in a brutally competitive commodity business (suit linings) and a mere $18 million in market capitalization.  From this undistinguished start, unprecedented returns followed;  and measured by long-term stock performance, the formerly crew-cut Nebraskan is simply on another planet from all other CEOs.  These otherworldly returns had their origin in that aging New England textile company, which today has a market capitalization of $140 billion and virtually the same number of shares.  Buffett bought his first share of Berkshire for $7;  today it trades for over $120,000 share.  [Value of Berkshire share as of 10/21/18:  $517.2 billion market capitalization, or $314,477 a share]

(Company logo, by Berkshire Hathaway Inc., via Wikimedia Commons)

Buffett was born in 1930 in Omaha, Nebraska.  His grandfather ran a well-known local grocery store.  His father was a stockbroker in downtown Omaha and later a congressman.  Starting at age six, Buffett started various entrepreneurial ventures.  He would buy a 6-pack of Coke for 25 cents and resell each one for 5 cents.  He later had several paper routes and then pinball machines, too.  Buffett attended Wharton, but didn’t feel he could learn much.  So he returned to Omaha and graduated from the University of Nebraska at age 20.

He’d always been interested in the stock market.  But it wasn’t until he was nineteen that he discovered The Intelligent Investor, by Benjamin Graham.  Buffett immediately realized that value investing—as explained by Graham in simple terms—was the key to making money in the stock market.

Buffett was rejected by Harvard Business School, which was a blessing in that Buffett attended Columbia University where Graham was teaching.  Buffett was the star in Graham’s class, getting the only A+ Graham ever gave in more than twenty years of teaching.  Others in that particular course said the class was often like a conversation between Graham and Buffett.

Buffett graduated from Columbia in 1952.  He applied to work for Graham, but Graham turned him down.  At the time, Jewish analysts were having a hard time finding work on Wall Street, so Graham only hired Jewish people.  Buffett returned to Omaha and worked as a stockbroker.

One idea Buffett had tried to pitch while he was a stockbroker was GEICO.  He realized that GEICO had a sustainable competitive advantage:  a permanently lower cost structure because GEICO sold car insurance direct, without agents or branches.  Buffett had trouble convincing clients to buy GEICO, but he himself loaded up in his own account.

Meanwhile, Buffett regularly mailed investment ideas to Graham.  After a couple of years, in 1954, Graham hired Buffett.

In 1956, Graham dissolved the partnership to focus on other interests.  Buffett returned to Omaha and launched a small investment partnership with $105,000 under management.  Buffett himself was worth $140,000 at the time (over $1 million today).

Over the next thirteen years, Buffett crushed the market averages.  Early on, he was applying Graham’s methods by buying stocks that were cheap relative to net asset value.  But in the mid-1960s, Buffett made two large investments—in American Express and Disney—that were based more on normalized earnings than net asset value.  This was the beginning of a transition Buffett made from buying statistically cheap cigar butts to buying higher quality companies.

  • Buffett referred to deep value opportunities—stocks bought far below net asset value—as cigar butts. Like a soggy cigar butt found on a street corner, a deep value investment would often give “one free puff.”  Such a cigar butt is disgusting, but that one puff is “all profit.”

Buffett started acquiring shares in Berkshire Hathaway—a cigar butt—in 1965.  In the late 1960s, Buffett was having trouble finding cheap stocks, so he closed down the Buffett partnership.

After getting control of Berkshire Hathaway, Buffett put in a new CEO, Ken Chace.  The company generated $14 million in cash as Chace reduced inventories and sold excess plants and equipment.  Buffett used most of this cash to acquire National Indemnity, a niche insurance company.  Buffett invested National Indemnity’s float quite well, buying other businesses like the Omaha Sun, a weekly newspaper, and a bank in Rockford, Illinois.

During this period, Buffett met Charlie Munger, another Omaha native who was then a brilliant lawyer in Los Angeles.  Buffett convinced Munger to run his own investment partnership, which he did with excellent results.  Later on, Munger became vice-chairman at Berkshire Hathaway.

Partly by reading the works of Phil Fisher, but more from Munger’s influence, Buffett realized that a wonderful company at a fair price was better than a fair company at a wonderful price.  A wonderful company would have a sustainably high ROIC, which meant that its intrinsic value would compound over time.  In order to estimate intrinsic value, Buffett now relied more on DCF (discounted cash flow) and private market value—methods well-suited to valuing good businesses (often at fair prices)—rather than an estimate of liquidation value—a method well-suited to valuing cigar butts (mediocre businesses at cheap prices).

In the 1970s, Buffett and Munger invested in See’s Candies and the Buffalo News.  And they bought large stock positions in the Washington Post, GEICO, and General Foods.

In the first half of the 1980s, Buffett bought the Nebraska Furniture Mart for $60 million and Scott Fetzer, a conglomerate of niche industrial businesses, for $315 million.  In 1986, Buffett invested $500 million helping his friend Tom Murphy, CEO of Capital Cities, acquire ABC.

Buffett then made no public market investments for several years.  Finally in 1989, Buffett announced that he invested $1.02 billion, a quarter of Berkshire’s investment portfolio, in Coca-Cola, paying five times book value and fifteen times earnings.  The return on this investment over the ensuing decade was 10x.

(Coca-Cola Company logo, via Wikimedia Commons)

Also in the late 1980s, Buffett invested in convertible preferred securities in Salomon Brothers, Gillette, US Airways, and Champion Industries.  The dividends were tax-advantaged, and he could convert to common stock if the companies did well.

In 1991, Salomon Brothers was in a major scandal based on fixing prices in government Treasury bill auctions.  Buffett ended up as interim CEO for nine months.  Buffett told Salomon employees:

“Lose money for the firm and I will be understanding.  Lose even a shred of reputation for the firm, and I will be ruthless.”

In 1996, Salomon was sold to Sandy Weill’s Travelers Corporation for $9 billion, which was a large return on investment for Berkshire.

In the early 1990s, Buffett invested—taking large positions—in Wells Fargo (1990), General Dynamics (1992), and American Express (1994).  In 1996, Berkshire acquired the half of GEICO it didn’t own.  Berkshire also purchased the reinsurer General Re in 1998 for $22 billion in Berkshire stock.

In the late 1990s and early 2000s, Buffett bought a string of private companies, including Shaw Carpets, Benjamin Moore Paints, and Clayton Homes.  He also invested in the electric utility industry through MidAmerican Energy.  In 2006, Berkshire announced its first international acquisition, a $5 billion investment in Iscar, an Israeli manufacturer of cutting tools and blades.

In early 2010, Berkshire purchased the nation’s largest railroad, the Burlington Northern Santa Fe, for $34.2 billion.

From June 1965, when Buffett assumed control of Berkshire, through 2011, the value of the company’s shares increased at a compound rate of 20.7 percent compared to 9.3 percent for the S&P 500.  A dollar invested in Berkshire was worth $6,265 forty-five years later.  The same dollar invested in the S&P 500 was worth $62.

The Nuts and Bolts

Having learned from Murphy, Buffett and Munger created Berkshire to be radically decentralized.  Business managers are given total autonomy over everything except large capital allocation decisions.  Buffett makes the capital allocation decisions, and Buffett is an even better investor than Henry Singleton.

Another key to Berkshire’s success is that the insurance and reinsurance operations are profitable over time, and meanwhile Buffett invests most of the float.  Effectively, the float has an extremely low cost (occasionally negative) because the insurance and reinsurance operations are profitable.  Buffett always reminds Berkshire shareholders that hiring Ajit Jain to run reinsurance was one of the best investments ever for Berkshire.

As mentioned, Buffett is in charge of capital allocation.  He is arguably the best investor ever based on the longevity of his phenomenal track record.

Buffett and Munger have always believed in concentrated portfolios.  It makes sense to take very large positions in your best ideas.  Buffett invested 40 percent of the Buffett partnership in American Express after the salad oil scandal in 1963.  In 1989, Buffett invested 25 percent of the Berkshire portfolio—$1.02 billion—in Coca-Cola.

Buffett and Munger still have a very concentrated portfolio.  But sheer size requires them to have more positions than before.  It also means that they can no longer look at most companies, which are too small to move the needle.

Buffett and Munger also believe in holding their positions for decades.  Over time, this saves a great deal of money by minimizing taxes and transaction costs.

Thorndike:

Buffett’s approach to investor relations is also unique and homegrown.  Buffett estimates that the average CEO spends 20 percent of his time communicating with Wall Street.  In contrast, he spends no time with analysts, never attends investment conferences, and has never provided quarterly earnings guidance.  He prefers to communicate with his investors through detailed annual reports and meetings, both of which are unique.

… The annual reports and meetings reinforce a powerful culture that values frugality, independent thinking, and long-term stewardship.

 

 

RADICAL RATIONALITY:  THE OUTSIDER’S MINDSET

You’re neither right nor wrong because other people agree with you.  You’re right because your facts are right and your reasoning is right—and that’s the only thing that makes you right.  And if your facts and reasoning are right, you don’t have to worry about anybody else. – Warren Buffett

Thorndike sums up the outsider’s mindset:

  • Always Do the Math
  • The Denominator Matters
  • A Feisty Independence
  • Charisma is Overrated
  • A Crocodile-Like Temperament That Mixes Patience with Occasional Bold Action
  • The Consistent Application of a Rational, Analytical Approach to Decisions Large and Small
  • A Long-Term Perspective

Always Do the Math

The outsider CEOs always focus on the ROIC for any potential investment.  They do the analysis themselves just using the key variables and without using a financial model.  Outsider CEOs realize that it’s the assumptions about the key variables that really matter.

The Denominator Matters

The outsider CEOs focus on maximizing value per share.  Thus, the focus is not only on maximizing the numerator—the value—but also on minimizing the denominator—the number of shares.  Outsider CEOs opportunistically repurchase shares when the shares are cheap.  And they are careful when they finance investment projects.

A Feisty Independence

The outsider CEOs all ran very decentralized organizations.  They gave people responsibility for their respective operations.  But outsider CEOs kept control over capital allocation decisions.  And when they did make decisions, outsider CEOs didn’t seek others’ opinions.  Instead, they liked to gather all the information, and then think and decide with as much independence and rationality as possible.

Charisma Is Overrated

The outsider CEOs tended to be humble and unpromotional.  They tried to spend the absolute minimum amount of time interacting with Wall Street.  Outsider CEOs did not offer quarterly guidance and they did not participate in Wall Street conferences.

A Crocodile-Like Temperament That Mixes Patience With Occasional Bold Action

The outsider CEOs were willing to wait very long periods of time for the right opportunity to emerge.

Like Katharine Graham, many of them created enormous shareholder value by simply avoiding overpriced ‘strategic’ acquisitions, staying on the sidelines during periods of acquisition feeding frenzy.

On the rare occasions when there was something to do, the outsider CEOs acted boldly and aggressively.  Tom Murphy made an acquisition of a company (ABC) larger than the one he managed (Capital Cities).  Henry Singleton repeatedly repurchased huge amounts of stock at cheap prices, eventually buying back over 90 percent of Teledyne’s shares.

The Consistent Application of a Rational, Analytical Approach to Decisions Large and Small

The total value that any company creates over time is the cumulative difference between ROIC and the cost of capital.  The outsider CEOs made every capital allocation decision in order to maximize ROIC over time, thereby maximizing long-term shareholder value.

These CEOs knew precisely what they were looking for, and so did their employees.  They didn’t overanalyze or overmodel, and they didn’t look to outside consultants or bankers to confirm their thinking—they pounced.

A Long-Term Perspective

The outsider CEOs would make investments in their business as long as they thought that it would contribute to maximizing long-term ROIC and long-term shareholder value.  The outsiders were always willing to take short-term pain for long-term gain:

[They] disdained dividends, made disciplined (occasionally large) acquisitions, used leverage selectively, bought back a lot of stock, minimized taxes, ran decentralized organizations, and focused on cash flow over reported net income.

Thorndike notes that the advantage the outsider CEOs had was temperament, not intellect (although they were all highly intelligent).  They understood that what mattered was rationality and patience.

 

BOOLE MICROCAP FUND

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

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

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

The 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: jb@boolefund.com

 

 

 

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

Quantitative Deep Value Investing

(Image:  Zen Buddha Silence by Marilyn Barbone.)

October 14, 2018

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

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

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

Buffett has called deep value investing the cigar butt approach:

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

(Photo by Sensay)

Outline for this blog post:

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

 

RARE TEMPERAMENT

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

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

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

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

(Photo by Nikki Zalewski)

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

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

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

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

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

 

EARLY BUFFETT: DEEP VALUE INVESTOR

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

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

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

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

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

 

INVESTORS MUCH PREFER INCOME OVER ASSETS

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

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

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

(Illustration by Teguh Jati Prasetyo)

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

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

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

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

 

COMPANIES AT CYCLICAL LOWS

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

(Illustration by Prairat Fhunta)

Mihaljevic:

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

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

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

Example: Ensco plc (ESV)

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

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

Here are intrinsic value scenarios:

  • Low case: If oil prices languish below $60 (WTI) for the next 3 to 5 years, then Ensco will be a survivor, due to its large fleet, globally diverse customer base, industry leading performance, and well-capitalized position.  In this scenario, Ensco is likely worth at least $12, over 35% higher than today’s $8.70.
  • Mid case: If oil prices are in a range of $65 to $85 over the next 3 to 5 years—which is likely based on long-term supply and demand—then Ensco is probably worth at least $25 a share, over 185% higher than today’s $8.70.
  • High case: If oil prices average $85 or more over the next 3 to 5 years, then Ensco could easily be worth $37 a share, about 325% higher than today’s $8.70.

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

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

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

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

 

BOOLE MICROCAP FUND

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

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

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

The 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: jb@boolefund.com

 

 

 

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

Quantitative Microcap Value

(Image:  Zen Buddha Silence by Marilyn Barbone.)

October 7, 2018

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

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

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

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

(Photo by USA International Trade Administration)

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

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

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

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

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

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

What’s the catch?

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

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

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

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

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

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

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

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

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

Bottom Line

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

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

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

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

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

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

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

 

BOOLE MICROCAP FUND

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

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

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

The 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: jb@boolefund.com

 

 

 

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

Cheap, Solid Microcaps Far Outperform the S&P 500

(Image: Zen Buddha Silence, by Marilyn Barbone)

September 30, 2018

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

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

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

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

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

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

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

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

Microcap equal weighted returns = 16.14% per year

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

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

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

 

VALUE SCREEN: +2-3%

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

 

IMPROVING FUNDAMENTALS: +2-3%

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

 

BOTTOM LINE

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

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

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

 

BOOLE MICROCAP FUND

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

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

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

The 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: jb@boolefund.com

 

 

 

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

Think Twice

(Image:  Zen Buddha Silence by Marilyn Barbone.)

September 23, 2018

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

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

 

RQ vs IQ

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

Illustration by hafakot

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

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

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

 

THE OUTSIDE VIEW

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

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

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

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

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

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

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

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

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

Illustration by OptureDesign

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

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

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

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

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

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

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

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

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

Illustration by OpturaDesign

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

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

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

 

OPEN TO OPTIONS

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

Anchoring is an important example of this mistake.  Mauboussin:

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

(Illustration by Olga Vainshtein)

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

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

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

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

The Representativeness Heuristic

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

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

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

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

Another example Kahneman gives:

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

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

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

Availability Bias, Vividness Bias, Recency Bias

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

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

Extrapolating the Recent Past

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

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

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

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

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

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

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

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

Illustration by intheskies

Doubt Avoidance

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

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

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

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

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

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

Inconsistency Avoidance and Confirmation Bias

Munger on the Inconsistency-Avoidance Tendency:

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

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

Photo by Marek

Munger continues:

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

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

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

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

Selective Attention and Inattentional Blindness

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

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

Struggles and Stresses

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

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

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

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

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

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

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

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

Incentives

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

Incentives are extremely important:

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

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

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

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

 

THE EXPERT SQUEEZE

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

 

SITUATIONAL AWARENESS

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

(Photo by D-janous, via Wikimedia Commons)

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

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

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

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

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

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

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

Priming

Mauboussin:

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

(Subconscious as brain under water, Illustration by Agawa288)

Scientists did the following experiment:

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

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

Mauboussin gives some examples of priming:

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

The Fault of the Default

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

Illustration by hafakot

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

The Power of Inertia

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

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

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

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

 

MORE IS DIFFERENT

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

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

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

 

EVIDENCE OF CIRCUMSTANCE

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

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

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

What’s especially important, writes Mauboussin:

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

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

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

The Colonel Blotto Game

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

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

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

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

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

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

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

Bottom Line on Attributes vs. Circumstances

Mauboussin sums up the  main lesson on attributes versus circumstances:

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

 

PHASE TRANSITIONS—“GRAND AH-WHOOMS”

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

(Illustration by Designua)

Critical Points, Extremes, and Surprise

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

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

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

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

Mauboussin continues:

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

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

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

The Problem of Induction, Reductive Bias, and Bad Predictions

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

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

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

Black swan, Photo by Dr. Jürgen Tenckhoff

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

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

Most people would rather die than think;  many do.

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

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

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

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

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

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

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

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

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

Music Lab

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

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

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

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

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

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

(Illustration by Mindscanner)

Mauboussin summarizes the lessons:

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

 

SORTING LUCK FROM SKILL

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

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

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

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

Skill, Luck, and Outcomes

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

Success = Some talent + luck

Great success = Some talent + a lot of luck

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

Illustration by iQoncept

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

 

TIME TO THINK TWICE

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

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

Raise Your Awareness

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

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

Put Yourself in the Shoes of Others

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

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

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

Finally, leaders must develop empathy for people.

Recognize the Role of Skill and Luck

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

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

Get Feedback

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

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

 

(Photo by Vinay_Mathew)

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

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

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

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

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

Create a Checklist

Mauboussin:

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

Photo by Andrey Popov

Mauboussin again:

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

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

Perform a Premortem

Mauboussin explains:

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

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

Know What You Can’t Know

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

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

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

 

BOOLE MICROCAP FUND

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

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

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

The 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: jb@boolefund.com

 

 

 

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

Invest Like Sherlock Holmes

(Image:  Zen Buddha Silence by Marilyn Barbone.)

September 16, 2018

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

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

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

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

Top investigative journalists follow a similar method.

Outline for this blog post:

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

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

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

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

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

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

 

THE DETECTIVE AND THE INVESTOR

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

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

How can investors develop better habits?  Hagstrom:

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

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

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

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

 

AUGUSTE DUPIN

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

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

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

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

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

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

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

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

 

JONATHAN LAING AND SUNBEAM

(Sunbeam logo, via Wikimedia Commons)

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

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

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

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

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

(Photo by Evgeny Ivanov)

Hagstrom continues:

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

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

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

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

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

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

 

TOP INVESTIGATIVE JOURNALISTS

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

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

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

(Photo by Robyn Mackenzie)

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

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

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

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

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

Photo by intheskies

Time equals truth:

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

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

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

 

EDNA BUCHANAN—PULITZER PRIZE WINNER

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

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

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

 

SHERLOCK HOLMES

Image by snaptitude

Sherlock Holmes approaches every problem by following three steps:

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

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

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

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

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

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

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

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

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

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

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

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

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

Hagstrom then adds:

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

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

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

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

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

Image by snaptitude

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

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

Hagstrom observes that many investors are susceptible to confirmation bias:

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

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

 

ARTHUR CONAN DOYLE

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

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

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

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

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

Photo by davehanlon

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

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

 

HOLMES ON WALL STREET

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Sherlock Holmes As Investor

How would Holmes approach investing?  Hagstrom:

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

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

 

FATHER BROWN

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Hagstrom mentions that psychology can be useful for investing:

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

 

HOW TO BECOME A GREAT DETECTIVE

Hagstrom lists the habits of mind of the Great Detectives:

Auguste Dupin

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

Sherlock Holmes

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

Father Brown

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

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

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

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

Illustration by yadali

Hagstrom continues:

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

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

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

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

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

 

BOOLE MICROCAP FUND

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

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

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

The 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: jb@boolefund.com

 

 

 

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