The Special Theory of Behavioural Finance

What's Wrong With Behavioural Finance?

We’ve seen time and again that the standard model of rational financial economics is next to useless at predicting anything at all useful about stockmarkets. Yet despite this the model is retained and used in many forms, often disguised and packaged to look like something new and valuable. Inevitably it turns out to be neither as soon as it’s needed.

Putting to one side the unworthy thought that the world’s major financial institutions are managed by idiots, the fact that these models continue to attract support and investment seems to suggest that there’s something wrong with the alternative. If behavioural finance – the study of how human psychological biases distort markets – is so much better than the models of rational, calculating, utility balancing economic man why do we cling so to the old ways? Although as there are world leaders out there who still use astrology to make decisions perhaps we shouldn’t be too surprised.

One Funeral At A Time

One possible reason is the power of the old guard, protecting the citadel of established economics. It was the scientist Max Plank who pointed out that science advances “one funeral at a time”: it literally requires the old, controlling generation to die before new ideas that threaten their conception of the universe can take hold.

By way of example in 1915, Alfred Wegener pointed out the odd, if obvious fact, that the coastline of eastern South America and western Africa look like they fit together. This wasn’t a unique suggestion, but Wegener was able to bring together a formidable set of evidence from the fossil record, living animals and geology to back his claim. Yet in the absence of an actual mechanism to explain continental drift his ideas were ignored until after his death.

Wegener is far from alone – perhaps the best known recent example is that of Barry Marshall and Robin Warren who correctly identified the bacterium Helicobacter pylon as the cause of stomach ulcers and were then roundly ignored for many years. However, it’s far too simple to characterise this process as science turning a blind eye to new ideas: science is rightly resistant to ideas that challenge the current norm because even wrong old ideas will have significant, if misinterpreted, evidence to support them.

Behavioural Finance is Not a Sideline

To be honest it’s hard to believe that lack of acceptance of behavioural finance is holding back its universal adoption. Since Tversky and Kahneman’s initial Prospect Theory publication back in the seventies there have been thousands of papers, books and presentations on the subject to the point where no one can seriously doubt that behavioural biases are a critical factor in the way markets move.

No, as far as academic psychology is concerned behavioural finance is in the mainstream. It’s in the less rarefied and practical world of investing institutions that efficient market theories still hold sway. We’ve seen this in the Capital Asset Pricing Model, in Value at Risk models and in the Black-Scholes option pricing model. With all of these if you peer closely enough the idea of human rationality re-asserts itself, shorn of all the psychological twitches and ticks that really drive our daily lives.

Now the odd thing about this is that while academics can afford to go off at a tangent, on some pipe dream of a theory, those people who make their money through the practical application of these theories have no such luxury. So why is the “obviously” wrong efficient market hypothesis still dominant amongst institutions?

The Failures of Behavioural Finance

The Efficient Market Hypothesis (EMH) enshrines the spurious quest for precision lusted after by economists – the idea that economics is underpinned by a set of physics-like rules that can be modelled, simulated and used to predict. The beauty of classical financial economics is that it allows just this sort of modelling – once you've made the necessary assumptions needed to remove any vestige of real human behaviour.

Behavioural finance, however, offers no such comfort. Worse, it doesn’t allow you to make market predictions because there’s no overall model of human behaviour lying behind it. Many psychological biases pull us in different directions – are we overconfident or loss averse, are we drawn by the availability of information or repelled by fear? Under the investment industry’s prime directive to generate returns the overriding importance of developing models that allow prediction has led to a focus on what can be modelled rather than what is real.

Better an unreal world we can simulate in a computer than a real one that we can’t, they say. Implying that a model that makes wrong predictions is better than one that can’t make any. This, of course, is utter madness but offers a kind of deranged logic that wouldn’t look amiss in a five year planning session of the Soviet Union led by the politburo’s head goat. Truth becomes another variable element in the model, subject to manipulation at the programmer’s fingertips.

Short-Term Returns or Long-Term Stability

At root, of course, these models are all about making money. If institutions believe that they can use the models to generate profits over any period they’ll use them: short term incentives for management will see that longer term problems are ignored. The difficulty for behavioural finance, and one of the reasons that despite the overwhelming evidence that psychological biases dominate market movements, is that unless behaviour based models can be developed to take advantage of these there’s no impetus for the dominant financial organisations to stop using the old models.

As Jay Ritter suggests, the problem seems to stem from the frequency of events in the market. High frequency events – those that occur often – generally behave in line with the predictions of classical economic theory. If asset valuations start to deviate too far from an accepted norm the normal processes of supply and demand will generally act to bring them back in line. This is why most short term trading strategies are doomed to failure.

However, there are also low frequency events which don’t accord with efficient market theories and people simply don’t expect. When these occur the most obvious trading strategies, based on efficient markets, can turn out to be disastrous as the deviations from sensible valuations become ever more pronounced rather than self-correcting at a reasonable level. Rational economic theories can’t explain such events.

The Special Theory of Behavioural Finance

A hypothesis, then, is that behavioural biases effect investors all of the time but while there’s a reasonable balance between different types of investors in the market any deviation in valuation is corrected, leading to a market that exhibits the hallmarks of a standard efficient model. However, this is only correct at the gross level – look under the covers and you’ll find a whole bunch of behavioural biases twitching away but doing so fairly randomly, cancelling each other out.

At some point, though, for some reason external to the market, such as excitement over the internet or the Space Race or railroads or tulips or bronze helmets or fig leaves or something, a majority of investors start to exhibit the same biases - usually starting in the form of people losing their fear of losing money. Markets take off on a roll attracting more and more loose money until such time as the boom can’t be sustained and everything goes into terrified reverse.

This, at least, explains why efficient market theory appears to work a lot of the time and why it then suddenly appears to fail. It’s analogous to the relationship between Newton’s Laws of Gravity and Einstein’s Theory of Relativity. It turned out the former was an approximation to the latter with all the odd stuff about the speed of light taken out: it worked right up until you needed to figure out how to get off a laser beam.

The trouble is that this doesn’t get us any further in figuring out how to predict what’s going to happen next. Mostly EMH works and investing for the long haul is OK but occasionally it all goes horribly wrong and behavioural finance can tell us why but not when. It’s hard to feel sorry for institutional investment houses but you can see why they’re not very interested in behavioural finance. After all, all it tells them is that they’re living on borrowed time. Best to make those bonuses while you can, eh?


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