Author Archives: Eric Falkenstein

Beware the Prescient

I was watching Robin’s speech at O’Reilly open source convention, and he highlights the usefulness of accumulating track records.  I want to highlight a curious bias to those successfully calling improbable events.  I am talking here about events that have no cross section, so we can not calibrate them in our lifetimes (eg,  when something has a 1% chance of happening ever year, as opposed to something like death rates that have a small probability but a wide cross section).  As Allan Greenspan noted in his Congressional testimony a couple weeks ago on the financial crisis:

the fact that there are a lot of people who raised issues about problems emerging. But there are always a lot of people raising issues, and half the time they are wrong. And the question is, what do you do?

Indeed, there are always people predicting imminent financial disaster and they are usually wrong (see Ravi Batra).   That is, from a Bayesian perspective, given a small probability of say 2% of X, and many (but proportionately few) forecasting X, when X happens, should their opinions be upgraded to a probability of 4%?  If 4%, is that sufficiently large that we should make massive adjustments to incorporate their logic? What if this just reminds us they are outliers, emphasizing 2% events?  What if X happened, but it was because of Y, and not Z as they argued ex ante?

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Howard Stern on Voter Rationalization

I don’t think Howard Stern has been published in a peer-reviewed journal, but this piece was pretty well done.  He had one of his guys interview Harlem voters  asking first who they were voting for.  They would say Obama.  Then, the interviewer mentioned McCain’s policies, pretended they were Obama’s, and the interviewees thought these were great ideas.  That is, they would ask questions like this:  "Are you more for Obama’s policy because he’s pro-life, or because he thinks he our troops should stay in Iraq and finish this war?"  And they would say something like, ‘because he’s keeping the troops in Iraq’.

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The Hope Premium

It is a strange fact that for many professions, the odds of success are extremely low, and so is the average pay.  For example, many people have dreams about getting into acting, but I’ve seen estimates that only 5% of people who call themselves actors make a living acting, as opposed waiting tables and whatnot.  Similar odds exist for would-be novelists, musicians.  There are the high profile people one thinks of for the categories that act like lotto jackpots, a focal point that overwhelms objective odds. It is somewhat unrealistic, if not cruel, to tell people that chasing their dreams is a waste of time.  People like to dream, and after all, ‘the experts’ are often wrong.  Yet I think this phenomenon suggests that perhaps people accept low average ‘return’, in exchange for the dreams these professions present. 

The inequality in these fields, where incomes have a power law distribution, is not bug, it’s a feature.  The presence of superstars, whose income and status is so high, is the offsetting basis of the dreams for those in the industry, why they are willing to accept less ‘on average’.  In dreams without such opportunities, you need security, or some other offset to compensate. If this is true, it suggests there is a general hope premium in industries, and even assets.  Many financial assets that have the highest volatilities have below average returns, if not negative returns: out-of-the-money call options, Junk bonds, highly volatile stocks, extreme-odds at the racetrack.  We pay to dream, and it can be frivolous, as with the $1 I recently spent on a $206MM lotto ticket Saturday (odds: 1 in 130 million, I did not win), but it can also be a significant part of one’s investment portfolio (not wise, in my opinion, but real). 

People take risk based on hope, and hope is a function of one’s dreams.  In 1961 Walter Gutman wrote a book You only have to get rich once, and noted that "growth stocks might better be called dream stocks", and that ‘dreams are real–we have them every day.  It’s a big mistake to think dreams are unreal and what is called real life is real’.   This is a simple, profound, model of the value effect, where stodgy, low beta firms without much upside generate a higher return than stocks that can be classified by some as the next ‘Yahoo!’ Dreams, in moderation of course, are paradoxically as real as anything, and assets that embolden dreams have extra value for investors, and they are willing to accept a lower ‘average’ return because in taking risk, because they are already ignoring the skepticism of the consensus.

Jonathan Alter recently wrote that we should perhaps pay teachers more, and pay their superstars a lot.  I think the data suggest that if we start paying really large salaries for superstar teachers, we could pay a few of them more, but pay them in aggregate less.  That is, we would have just as much supply if we offered them the hope of become very wealthy, with a lower average pay, than our current system, which pays them a rather solid pay but with very limited upside.  No one with really large ambitions goes into education precisely because they top has a low ceiling.  Hope is worth something, in terms of a higher price, and thus lower  return.

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Overconfident Investing

I was watching the 1966 classic film, A Man For All Seasons, about the Thomas Moore’s principled stance in opposition to Henry VIII’s grab for power. Ultimately, Moore is found guilty of treason, and in the final scene, after giving his executioner the customary tip for a clean blow, tells him, ‘don’t worry, you are sending me to God’. Considering the fear of death is one of the greatest anxieties for a conscious being, what a fabulous delusion!  Clearly, biases can be helpful if looked at in a broader context, in this case, the belief in God is not evaluated based on evidence of God’s existence, but rather, the effect it has on the believer. 

One particular area where the cognitive bias of overconfidence can be helpful is in entrepreneurship or investing.  Keynes hypothesized in The General Theory that if "spontaneous optimism falters, leaving us to depend on nothing but a mathematical expectation, enterprise will fade and die". Indeed, if you look at the data on stock picking, or investing with professionals, it is a puzzle why people don’t merely all use passive indices because their average alpha is negative, and further, the average returns to highly undiversified C-corps or partnerships, seems woefully insufficient to justify their significant volatility   But over-confidence of entrepreneurs is helpful because it offsets the underestimation in other benefits of investing or entrepreneurship. Basically, the totally rational investor won’t count what he can’t quantify, but much of the value in investing, or entrepreneurship, comes from an option value that is impossible to quantify. I know someone who built a product based on an optimization routine for superior investment strategy—the flagship idea failed, it never had a chance, but his system is now a popular risk management tool. I know someone else who created a system to consolidate earnings expectations in order to beat the market—it too failed, but his database of earning expectations was put together thoughtfully, and it became successful platform for disseminating this data. Actions affect one’s knowledge, reputation, and contacts in ways extremely difficult to quantify, because you can’t really define the probability state space.  But the idea is simple, that people often get into some field to find gold, but then make their fortune selling shovels. 

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Hofstadter’s Law

I read Douglas Hofstadter’s new book I am a Strange Loop, which argues that consciousness happens spontaneously after a system of dynamic patterns is sufficiently complex.  Strange loops of self-awareness  existing on multiple levels (as in Godel’s famous proof) create hallucinations of a hallucination, and so an "I" forms.  Anyway, as I often do when reading nonfiction, I read a little bit more about the author, and was struck by Hofstadter’s law: It always takes longer than you expect, even when you take into account Hofstadter’s law (note this is recursive and paradoxical, which is Hofstader’s specialty). This turns out to be pretty well known among programmers where everyone has read Hofstadter’s Godel, Escher, Bach.

As they say, Hofstadter’s Law is funny because it rings true to many programmers, who often work on complex projects that take years to complete.  Clearly an alternative to the Law of Iterated expectations.  Why might people involved in sufficiently complicated tasks–writing a paper, a book, building a deck–generally underestimate their length?  I think the main reason is that goals become self-fulfilling, so any lengthening of a goal time would add to the total time  the way bureaucracies spend the limit of their budget whatever it is.  Just like a group of people, people themselves have multiple goals; to watch tv, to get a project done, to be a better golfer.  A successful goal needs a  bias to compete with your other goals, who probably also have biased homunculus advocating for them in your mind. 

On one level an unbiased expectation is optimal because it allows us to allocate our resources more efficiently.  But there are many cases where this is not true, where a little too much hope and faith actually makes you a more successful person, and more fun to be around.  Just think about how annoying ‘brutally frank’ people are–they are jerks.  Think about the guy who thinks he is a better dancer than he really his confidence actually makes him a better dancer, because part of good dancing is not being self-conscious.  Robert Trivers has pointed out that self-deception is, in moderation, an evolutionary advantage, in that a liar who believes his own lies is a more effective persuader than a lie who knows he is lying, and fundamentally we are social animals trying to convince others to do this or think that.

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Are Almost All Investors Biased?

The data suggest, yes almost all are.  But there’s another interpretation, mainly, that people mistakenly apply a rule of thumb (higher risk-higher return) to areas where it doesn’t, and can’t, hold.  Let me explain.

Risk that can be diversified away does not generate returns in theory (see the CAPM ) or practice (see Ang, et al ).  That is, taking more of this risk does not imply a greater average return.  Given the general massive lack of diversification, the only conclusion is that most people think they can pick stocks or funds that will rise more than average. They must be wrong (on average investors are average), but they are the vast majority of investors.  Thus the traditional theory of mean-variance optimization is more prescriptive than descriptive, in that most people are not rational about their forecasts, they are biased upwards in an area of proficiency that seems to be more costly than trivial overestimation of one’s driving ability.  How can this massive delusion be an equilibrium? 

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Ideologues or Fools?

Bias in regular discourse is a matter of one man’s principle versus another man’s dogma. This is complicated because it is often rational to pursue a theory in spite of inconsistencies because no theory is perfect (e.g., Newtonian mechanics do not work at some level, but are still pretty good ‘laws’). It is difficult to know when to deviate from principle in light of evidence, and how to distinguish between principle and dogma. Bias, dogma, fundamentalism, fanaticism, are all bad things, while principle and theory are good.

In contrast, market disagreements are a refreshingly empirical and rational alternative to those with different prior beliefs about politics. Portfolio managers consistently ‘agree to disagree’ and no portfolio managers use the words dogmatic or biased. Instead they use the terms fool, idiot, and moron. These are less morally charged words, aimed at errors in thinking, as opposed to malice. One mutual fund manager may be long Google, the other may ignore it. In the hedge fund world, things can be crazier because investors aren’t constrained to be long: one investor can be short something another investor is long. In markets these disagreements are common, and investors consider their own beliefs ‘wiser’ than the others. Market participants realize, however, that this is largely an empirical matter, and further, that small sample sizes relevant to investors are tentative (eg, the market can be irrational longer than you can be liquid).  Further, they worry much more about their beliefs, as to whether they are correct or wrong, much more so than a typical pro/anti-abortion zealot. No one talks about a ‘dogmatic’ investor, because if he invests based on dogma, he will suffer—he’s merely a fool, full of hubris, thus posterity will punish him so you don’t have to. There is no ill-will towards those who disagree, only envy when you are wrong, and (patronizing) pity when they are wrong.

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