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Saturday 3 July 2010

Behavioural Finance’s Smoking Gun


Here’s a classic demonstration of behavioural finance in action, proving the irrationality of humankind. It’s the (in)famous Linda problem:

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 antinuclear demonstrations. Which of these two alternatives is more probable?
(a) Linda is a bank teller.
(b) Linda is a bank teller and is active in the feminist movement.
Most subjects choose (b) and are informed that they’re irrational because the conjunction of two events – Linda is a bank teller and active in the feminist movement – is less likely than her just being a bank teller, regardless of her leisure interests. This is known as the conjunction fallacy. Unfortunately there’s a teensy little problem with this finding.

It’s wrong and it’s the smoking gun of behavioral finance.

Probability Analysis isn't Rationality

Now, in terms of probability, the researchers are correct. It’s much more likely that Linda will only be a bank teller than be a bank teller and a feminist activist. Unfortunately to go from that position to arguing that people who choose the second option are irrational and are being affected by some behavioural bias or other is a huge jump than can only be explained by using too many narcotics. Allegedly. Probably.

Classically this “irrationality” is explained in terms of something called the representativeness heuristic, which is, roughly, a rule of thumb where people make decisions about something by judging how similar that something is to some readily available and similar data. This is an attractively simple idea but one that comes swathed in clouds of confusion: it superficially explains everything but is of little use when it comes to actually predicting behaviour – a problem that people trying to solve real-world problems, like when to invest in stocks, often level at behavioural finance.

Stat Homunculus on the Brain

Now, if you think about this for a moment what the research is telling us is that to "think rationally" is to behave as though inside our heads is a tiny statistical homunculus performing conjunctions and other statistical stuff. In fact, if we analyse the theories behind most of behavioural finance (and, to be fair, traditional economics) it all assumes that to behave rationally is to reason in terms of probability.

A number of researchers have begun to question whether this makes any logical sense in the real world. Take the Linda problem, for instance. Here’s a variation of the Linda problem carried out by Gigerenzer and colleagues:

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 antinuclear demonstrations.

There are 100 people who fit the description above. How many of them are:
(a) bank tellers
(b) bank tellers and active in the feminist movement
Guess what happens to the results? Yep, the conjunction fallacy disappears – far more participants now choose (a) than (b). Something odd and deep and important is happening that the mainstream of behavioural finance research is completely failing to understand.

Frequencies, Not Environment

The second Linda question is directly asking a question about frequencies – it’s asking us to judge a probability in a direct way that is hard to misunderstand. And lo, our statistical homunculus jumps into life and correctly figures out how to handle this.

However, the first Linda question isn’t asking us about a probability frequency, it’s asking us about Linda. In the real world how likely is it that someone will present us with loads of information about Linda’s feminist tendencies and then expect us to ignore the information? It’s just not realistic – we look at the question, decide that we’ve been told stuff that must be relevant to the answer and then use it. The homunculus barely stirs from its sleep because it’s not a statistical question.

Economic Research Fallacies

The idea that the human mind is based on an internalised statistical decision making algorithm is one we’ve met before. It’s a research fallacy which each successive generation of academics falls into by firstly using their latest research tools – statistical analysis packages, digital computers, etc – as metaphors for the way the mind works and then assuming that this is the way the mind actually works. There is a huge behavioural bias behind behavioural finance but it’s not the experimental participants who are subject to it, but the experimenters.

Behavioural finance assumes that people don’t behave rationally but would if their wetware allowed them: we only behave a bit stupidly because we don’t have the processing power up top to implement the necessary statistical decision making packages efficiently. This is a step away from homo economicus, the ideal economic, rational man but one that turns out not be useful: people correctly identify, based on the situation, that Linda’s more likely to a active feminist bank-teller, it’s only economic researchers that don’t.

Basically we’re not perfect by design, and we’re bloody good at it.

Exploding Prospect Theory

Here’s Gerd Girgerenzer again:
“It is understandable that when heuristics were first proposed as the underlying cognitive processes in the early 1970s, they were only loosely characterized. Yet, 25 years and many experiments later, explanatory notions such as representativeness remain vague, undefined, and unspecified with respect both to the antecedent conditions that elicit (or suppress) them and also to the cognitive processes that underlie them. My fear is that in another 25 years researchers will still be stuck with plausible yet nebulous proposals of the same type: that judgments of probability or frequency are sometimes influenced by what is similar (representativeness), comes easily to mind (availability), and comes first (anchoring). The problem with these heuristics is that they at once explain too little and too much.”
On its own this would be provocative but addressed as it was to Kahnemann and Tversky, the founding fathers of behavioural finance, it’s fighting talk. And, indeed, a bit of a scrap was had with predictably indeterminate results. However, you can see the thrust of Gigerenzer’s argument: everything about behavioral finance is psychologically plausible yet it doesn’t actually seem to be practically useful.

Lies, Damn Lies and ...

Gigerenzer has expanded his thesis away from the Linda problem into all sorts of other areas of behavioural bias. So, for example, in an early paper he and his colleagues looked at overconfidence bias, a staple of behavioural research which is consistently reported as stable under all conditions. They promptly showed that they could manipulate conditions to make this appear, disappear and invert dependent on how their experimental situation was constructed.

Underlying all of this is subtle argument about the misuse of probability and statistics which is a bit too obtuse even for this journal. However, Gigerenzer basically believes that behavioural researchers looking at confidence statements are misusing statistical analysis to prove their points.

The Smoking Gun

This is, indeed, a smoking gun for behavioural finance. It also implies that there’s some other underlying mechanism of human judgement that’s common to all supposed biases, something that resolves the existing cacophony of competing biases which seem to randomly take turns in driving our behaviour.

What this might be will have to wait for another time, but it’s an encouraging thought that maybe we’re not so stupid as the legions of norm-defining economists who want to train our brains to be the same as the statistical analysis packages that sit on their PC’s think we are. But really, we knew that anyway, didn’t we?

Rationality for Mortals: How People Cope with Uncertainty (Evolution and Cognition)Simple Heuristics That Make Us SmartThinking, Fast and Slow

Related Articles: Unpredictably Rational, Investor Decisions, Experience is Not Enough, The Special Theory of Behavioural Finance


  1. everything about behavioral finance is psychologically plausible yet it doesn’t actually seem to be practically useful.

    I believe that Behavioral Finance has huge practical implications. But I agree that we are not exploring them much today. Much of what has been put forward so far leads to a dead end.

    This sort of article helps. It is by coming to recognize what leads to dead ends that we will be able to identify the sorts of insights that will have practical value.

    I love Behavioral Finance. But unless we do a far better job in showing it to have practical value, it will die. And properly so. Theory for the sake of theory is like art for the sake of art. It's boring.


  2. I am not sure that these refutations, which are based on reframing of traditional probability type questions, go very far in dismissing the practical implications of behavioral economics. The author essentially asserts that, by thinking about probability related problems in a different way, people are more likely to assess probability type problems appropriately. This appears to be strongly observed in the evidence.

    However, people are rarely presented with problems in the manner that the author prescribes. Investors are usually presented with the specific, and most people do not generalize to baseline probability frequencies. For example, an investor meets with management of a company, and is then faced with a decision to invest in that company, or an alternative. Information bias and the representative hubristic are likely to come into play so that the investor is more enamored with the familiar company than the alternatives.

    Similarly, investors are concerned with forecasts about one particular future, not the probability weighted range of possible futures. It matters little to mosr investors, even professional ones, what happens over a sample of 100 similar scenarios. Instead, investors are concerned with what is likely to happen in a particular scenario - that is, "right now", not "over time". This is clearly not a rational approach, but it is a function of peoples' bias favoring the proximate over the distant.

    Systematic investment strategies are an attempt to compel people to think about the future in terms of frequencies and the law of large numbers. They are a triumph of the general over the specific, as they are not designed to be right every time, but right over time. What they can't account for is the fact that economies and markets are complex _dynamic_ systems, which means that the probabilities change over time. However, this type of error is impossible to address, except by adaptive algorithms like neural networks.

    What the author of this paper seems to be saying is that, if by chance people were to begin to naturally frame complex problems in the context of weighted probability frequencies, instead of framing them in the specific, that they would act rationally and behave more appropriately in the context of the odds. Unfortunately, people are unlikely to alter their predisposition to view the world in the specific, so our potential to act rationally is unlikely to be tapped to any meaningful degree. Perhaps we can say that behavioral economics is generally correct, but specifically wrong.         

  3. Sorry, that's representative heuristic - my iPad spelling correction went haywire.

  4. This doesn't seem like a refutation, just a confirmation: people are highly sensitive to how problems are framed.

    IPOs, for example, are Lindas. The average investor looking at Tesla may be willing to say that the it's likely that, in five years, Tesla will be a profitable company selling a billion dollars worth of cars and parts each year. That same investor might say "Yes, out of a hundred companies with growing sales that are losing money, selling a product for which the long-term demand is unknown, and competing with established firms, perhaps ninety will be bankrupt within a few years."

    That investor just got Linda'd. You rarely hear the bulls talking about aggregate IPO performance, because the average IPO doesn't do that well. But they often talk about the specific company. The bulls are looking at one Linda at a time, not a hundred bank tellers.

  5. I dunno, I think the representative hubristic has a lot to teach economics :)

    The thrust of the article, and the research, is not that people frame things in terms of probability or not - merely that the effect of behavioral financial researchers in framing things in a particular way dictates the outcome of their experiments. Framing in a different way changes the result and casts doubt on some of the standard theories upon which behavioral finance is built. That's science for you - a single problem can collapse an entire carefully constructed theory, even if it's a complex adaptive one.

    This doesn't say anything about whether we should or we shouldn't attempt to model and think about investment decisions in terms of frequencies, probabilities or random casts of pink fluffy dice. Nor does it refute the reality that human behavior lies behind the way we choose to invest - but it does suggest that standard behavioral finance may itself be behaviorally compromised.

    As it happens, the representative heuristic is heavily implicated in Gigerenzer's proposed reworking of behavioral finance. But that's a story for another day.

  6. Behavioral finance is still young, and seems focused on proving its own thesis, that humans are systematically irrational.

    Hopefully as the field matures, it will come to explore in more detail our decision making processes, and under what specific conditions we need to slow down and question our own instincts.

  7. This says more about academia and the disconnect between abstract research and the real world than anything else.

    In terms of Behavioral economics, it also supports the Thaler "Nudge" idea -- how we frame choices, what the context of presented options are matters as much as the answer choices themselves.

  8. Nit-pick: presumable, "How many of them are:" should be, "Are the majority of them:"?

  9. Your argument is that since the findings of "behavioral economics" are sensitive to context and in any case do not lead to practical prescriptions, researchers must be foolish and the rest of us very smart.

    This argument has a more serious flaw than the obvious non-sequitur. Those who work in marketing, advertising, and politics appear to be eons ahead of official researchers and in fact are able to use the vagaries of human thinking to influence our behavior routinely.

    I might note in passing that your faith in the powers of evolution to produce smart humans is misplaced. Antelopes do not run as fast as antelopes can be made to run, and snails do not have the strongest possible snail shells. They are as fast and as hard-shelled as optimal - a big difference. Why should humans be so different from the rest of the animal world?

  10. Hi Ritholtz

    This says more about academia and the disconnect between abstract research and the real world than anything else.

    Which would be less of a concern if the revolving door between academia, finance and politics wasn't spinning quite so fast :-/

    In terms of Behavioral economics, it also supports the Thaler "Nudge" idea -- how we frame choices, what the context of presented options are matters as much as the answer choices themselves.

    Maybe. The classical kind of behavorial finance is kind of derived from traditional economics, so this casts doubt on whether behavioral economics really understands what's going on. If it doesn't then nudging people may have unexpected and surprising consequences. We'll see.

  11. Hi Phil Koop

    Your argument is that since the findings of "behavioral economics" are sensitive to context and in any case do not lead to practical prescriptions, researchers must be foolish and the rest of us very smart.

    Well, that wasn't what I intended to say, so if it was it's a bit disappointing ...

    The main idea was that there's reason to believe that the standard metaphor behind behavioral finance is flawed. Now if it is then a view that sees us as irrational is itself irrational. That doesn't mean we're smart - merely that we're not quite as stupid as economists keep telling us we are. The side argument is that if the theory behind behavioral finance is flawed it might explain why it doesn't lead to useful practice.

    None of which should be taken to mean that I don't believe that psychology is key to understanding market behavior or that behavioral finance isn't on the right track. It's like there's something not quite right in the mechanics which everyone who's invested in the standard theories would prefer to ignore. Perhaps it's the economic equivalent of Michelson-Morley?

  12. Kahneman covers this in Thinking, Fast and Slow summed up wisely in the chapter title "Answering an easier question." he also gives a robust defence Gigerenzer's comments and critic of Tversky and Kahneman's work in the notes to the chapter. See also Oppenheimer's work Not so fast (and not so frugal).