Science, Stocks and Superstition

Unreliable Science

As we’ve seen – repeatedly – people aren’t particularly good at overcoming the behavioural biases built into our nature by evolution. There’s no real reason we should be – computing the statistical probability of an above average return on the stockmarket over a twenty year period wasn’t of much value for most of human history. This was partly because twenty years was more than the average lifespan of a proto-human but largely because no one had yet got around to inventing money or stockmarkets or stocks. Or ‘years’.

If these biases are inherent and cause us to do stupid things around finance we might expect that they’ll appear in other areas as well where humanity has only recently started to apply its higher cognitive functions. So it’s unsurprising that our basic intuitions about science are about as reliable as those we have about finance. To whit: not reliable at all.

Greek Geeks

Science has been around a lot longer than modern financial theory. The Ancient Greeks developed many concepts that aren’t out of place in the modern pantheon of university science faculties – atomic theory, planetary orbits and toga parties amongst them. Unfortunately they failed to marry their scientific insights to a stable economic system and much of their knowledge was lost for the best part of a millennium. The lesson being, presumably, that disenfranchising women and relying on slave labour is a poor way of building a stable society. Global corporations take note.

During that lost thousand years or so the only real legacy of Greek knowledge in the Western world was a smattering of Aristotle, who was a bloody good thinker but a bit weak on stuff like planetary motion and mathematics. Somewhere along the line Aristotle’s ideas got mixed up with Christianity and resulted in the odd position of the Catholic Church defining God’s word on the basis of the scientific writings of an atheistic Greek who died before Christ was born. We can blame Thomas Aquinas for that one.

The period known as the Renaissance – the rebirth – was marked by a remarkable rediscovery of Ancient Greek thought. Some of this came from the Muslim world, where many ideas and writings had been sustained through the European Dark Ages, and some of it from the libraries of monasteries remote from barbarian incursion where scribes had been dutifully and ignorantly copying scrolls for centuries. Suddenly there was an explosion of ancient knowledge raining down on a world ripe for new ideas.

Childish Superstition

Yet, it’s impossible to believe that this sudden rediscovery of ancient science could wipe out the legacy of evolution. Science always has to be learned, it never comes naturally. Just like the basics of investing the concepts of science are not comfortable to the human mind, they go against the grain and for the vast majority of untrained lay people are foreign and even slightly chilling in their nature. The concept that every idea has to be exposed to public scrutiny, debated and even ridiculed before being accepted doesn’t sit easily with most of us.

In fact, our very survival may depend upon our non-scientific nature. How many amongst us didn’t experience fear of monsters and the supernatural when we were little? That’s easily explicable as an evolutionary adaptation designed to keep us near to our parents in an environment when a stray step could see us eaten by real monsters. Bruce Hood, in Supersense, for instance, reasons along these lines – that the adult human’s propensity for believing in the supernatural is a development of the child’s natural ways of reasoning about the world. As he points out, even highly educated people often believe in the supernatural: this doesn’t make much sense unless it’s somehow built into the fabric of our beings.

Of course, if superstition and difficulties in thinking in logical and scientific ways are inherent to our very beings we should see similar effects in financial markets. We should see evidence of people behaving in a stupid, irrational and wholly ridiculous way for no reason other than that’s the way that people behave. This is to go beyond people responding irrationally to the signals of the markets to them responding irrationally to absolutely nothing relevant to the markets whatsoever.

Eclipsed Stocks

Naturally evidence for such behaviour exists: researchers are nothing if not diligent in looking for new ways of spending research grants. Gabriele Lepori in “Dark Omens in the Sky: Do Superstitious Beliefs Affect Investment Decisions?” is the latest in a long line of researchers who’ve looked at the effects of good old superstition on stockmarkets and has shown that markets respond to the imminent arrival of a scientifically predictable eclipse by going into a tailspin, from which they rapidly recover when it turns out the world hasn’t ended. Again.

There is some rationale behind this. As Lepori explains:

“People tend to turn to superstitious practices when dealing with outcomes that are important to them and facing conditions of high uncertainty, competition, and stress”

“High uncertainty, competition and stress” could almost be a job description for many of the financial professionals involved in stockmarkets. It’s hardly surprising that they seem to be highly superstitious and inclined to odd behaviour such as possession of lucky bears, lucky ties or, in one rather distasteful anecdote, lucky underwear. Understandable this may be but you’ve got to ask yourself: do I really want to entrust my future to someone who’s worn the same underpants for a month?

Built to be Irrational

Mostly economists are working on one of two theories. Either humans are basically rational economic theorists and their errors are those of computational accuracy or we’re behaviourally biased and therefore behave irrationally but in a predictable fashion at a statistical level. It’s possible to discern the two sides of economics gradually moving to an accommodation where rational man is so bedevilled by the shortcuts taken by the brain that the result looks like the outcome of behavioural analysis.

However, there’s a third possibility. Maybe people are built to be irrational and their investing approaches are driven by this. Maybe the behavioural biases we’ve been discussing aren’t the main factors that drive the way people deal with stockmarkets. Maybe human irrationality goes way beyond the obvious things that researchers are looking for?

People’s lack of understanding of science is daunting – this study from the Californian Academy of Sciences recently suggested that most Americans can’t pass a basic science test. If the world’s most advanced nation can’t do better than this what hope for the rest of us? So if science is the dominant mode of thought across the planet and has lifted billions of people out of total poverty but the vast majority of people don’t understand it and would rather wear lucky pants and consult astrologers where does that leave investing, a much less well understood approach to organising the world yet one that attracts vastly more practitioners?

Insensible and Irrational

There’s little doubt that behavioural biases affect investors most of the time. There’s equally little doubt that it’s the same behavioural biases that cause the runaway feed forward processes that lead to booms and subsequent busts. However, the idea that humans are driven by relatively sensible and predictable behavioural biases is at least questionable. It’s at least as likely that humans are inherently irrational and driven by demons in the dark designed to protect us from the real monsters that lurked in our history as we dwelt in predator infested environments.

The question is not why do markets behave irrationally but why do they ever behave rationally?


Related articles: Bulletin Boards Are Bad For Your Wealth, The Media, Fear and Stockmarket Manias, Don’t Lose Money In The Stupid Corner

Investors, Embrace Your Feminine Side

Testosterone Is Not Destiny

There’ve been a lot of studies that indicate that women make better investors than men. They’re less inclined to overtrade, which reduces the fees they pay and means they start with an inbuilt advantage. However, there’s not been much analysis of why this behaviour occurs.

For it’s not self-evident that the lack of a pair of testicles should automatically make you a better investor. The pop-psychological view that this is due to surges of testosterone driving risk taking actions by red-blooded alpha males is highly seductive, but also pretty useless. Humans are uniquely evolved to allow us to override the urgings of of our genes, regardless of what sex organs they endow us with.

Cool Female Heads

However, there’s not much doubt that the basic finding – that women are less active traders and produce better returns on average over the long-term – is correct. Odean and Barber showed this in their 2001 study on overconfidence for instance. What’s more interesting, though, is how easily the idea that this is simply due to non-eradicable sex differences is accepted. In fact some observers have gone so far as to suggest that market extremes could be avoided by ensuring more women are present in investment houses – the idea being, presumably, that the cooler headed females will reduce the hot-headed male impulses to trade irrationally.

Like hell. More likely, of course, the presence of additional women would simply stimulate the men into ever more risky trades in feverish attempts to impress them: taking risks may have benefits that don’t translate into pure financial advantage. Meanwhile any women interested enough to get involved in market trading are more likely to do so in order to become rich rather than to act as a self-regulating safety valve for their male colleagues.

Risky Sociobiology

Now before we can investigate this more we need to take a careful look at what causes sex differences. It’s perfectly obvious that our genes have fitted males and females differently for the purposes of reproduction but beyond that it’s surprisingly difficult to definitively tease apart the influences of genes and environment. Even the well known male map reading advantage can be traced to the greater willingness of parents to allow young sons to roam more freely. This environmental conditioning is nowhere more true than in the area of risk-taking.

The standard sociobiological view is that women are less likely to take risks than men because of their need to nurture and protect their children: a woman makes significant investment in each child and needs to carefully manage the risks associated with their upbringing. Men, on the other hand, are able to liberally cast their gametes around like some kind of agricultural sperm-spreader and are, therefore, less concerned about the risks associated with an individual child’s safety. Men are, in the parlance, rewarded for risk-taking and faithlessness.

Mum Doesn’t Know Anything

Although sociobiology has a lot of explanatory value there are significant reasons to be suspicious of this deconstruction of gender – none more so than the way it fits neatly into the majority world view of the roles of men and women. Moreover, the evidence of child psychology suggests that there are other powerful influences on gender related risk taking behaviour.

Child psychologists are amongst the most devious and cunning of their ilk, spending their lives devising clever methods of teasing out evidence of psychological development from children and their parents: when you’re dealing with dumb babies and attached moms you’ve got to be pretty smart to get real evidence. One of the more eye-opening studies comes from analysis of how mothers treat babies of apparently different sexes.

As Lloyd and Duveen describe in their book, wittily entitled Social Representations and the Development of Knowledge, if you take a bunch of babies, randomly dress them as boys and girls, and stick them in a room with a bunch of mothers you get a bunch of completely predictable and quite remarkable results. The babies dressed as boys are bounced about, encouraged to behave aggressively and rewarded for exhibiting “male” risk-taking behaviours. Those dressed as girls are treated gently, expected to behave relatively passively and rewarded for exhibiting “female” risk-aversion behaviours. And the mothers don’t recognise they’re doing this.

Feminine Personality

In the face of such powerful environmental conditioning it’s impossible to separate out the genetic component of gender related risk-taking behaviour. The best we can do is to acknowledge that some element of this is likely to be due to upbringing. However, if that’s true it ought to be possible to see varying risk-taking behaviour – and relative returns – across the sexes, since traits associated with “feminine” risk-aversion won’t be determined by genes alone.

There’s not a whole lot of research around this – but one hint comes from the generally fringe investigations of personality traits. Personality psychology is mired in a whole bunch of problems, the most significant being that there’s no agreed underpinning theory that explains personality traits. Indeed the researchers often can’t even agree on what the traits are that they’re investigating without getting very annoyed with each other.

That said the evidence does show that empirically – experimentally – certain traits do seem to mildly correlate with certain behaviours, suggesting that there’s something going on under the covers even if we don’t quite know what. Most personality traits are operated as scales, so that individuals are more or less extrovert, more or less analytic, etc. In what’s really a limited study, in terms of participants, Durand, Newby and Sanghani have looked at masculinity – femininity as a scale, associating more risk taking behaviour with the masculine end of the scale, regardless of the subjects’ actual genders. Some women are inveterate risk-takers, some men avoid it like a plague.

Risk and Gender

The results suggest that investor return is correlated not with gender but with risk taking attitude: those people at the lower risk feminine end of the scale in general got better investment results than those at the masculine end, regardless of whether they were male or female. Encouraging women to join investment houses would probably simply add more risk taking women to the ranks. Of course the risk adverse feminine investor isn’t likely to be much interested in those kinds of jobs anyway.

All of which leads us to the not particularly startling conclusion that to reliably obtain the best returns possible we need to invest cautiously and avoid taking any risks that we can. The more active an investor you are the more opportunity you provide to exhibit irrational behaviour and the more money you donate to the investment industry. After all charity should start at home and shouldn’t involve enriching those already better off than ourselves.

Embrace Your Feminine Side

Trying to tease apart the relative effects of nature and nurture on anything is always and everywhere difficult but it’s more important to recognise that our destiny doesn’t lie in our genes. We have a choice – to stay ignorant and allow nature to take its course or to educate ourselves and turn nature to our advantage.

The majority of people in the money business rely on our ignorance so we need to arm ourselves. Knowledge is power, caution is wisdom, to be feminine is to embrace wealth. It’s an irony, of course, that the world puts most of its money into the pockets of men and most of its financial wisdom into the minds of women. As a father of daughters it’s time we broke a few moulds methinks.


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Get An Emotional Margin of Safety

Businesslike Investment

Warren Buffett states, quite frequently, that the most important investment statement ever made was that of his mentor, the father of value investing, Ben Graham:

“Investment is at its most intelligent when it is most businesslike”

Now if you’ve ever wondered exactly what that means you’re not alone. But it’s really one of the most important business lessons any of us can ever learn. It encapsulates the idea that investment isn’t about individual subjective feelings but about general objective rationale. To be good investors we need to learn to control our emotions. Unfortunately it’s got a bit more difficult since Graham first wrote those words.

Unemotional Investment

We find Graham’s statement difficult to understand because we don’t understand Graham’s – or Buffett’s – viewpoint. Although both men are amongst the best communicators the world of top-class investment has ever thrown up they still sit in the rarefied atmosphere of that elite group of investors who are able to step away from their own emotions when they come to investing.

By “businesslike” Graham meant “unemotional”. At the root of all good investment, he believed, was a focus on the underlying numbers. Graham, far more so than Buffett, was focused on the investment ratios and balance sheets of his investments. To be “businesslike” the individual investor needs to ruthlessly focused on the numbers, not the stories associated with them. Thus Graham and Buffett aim to remove the behavioural biases that affect most investors.

Of course, there’s no doubt that there are a select group of people who are more easily able to ignore the impact of group psychology than the rest of us. It’s possible – even probable – that the great investors of the world are simply psychologically unusual people who are capable of ignoring the impact of normal behavioural biases. These people are so rare that it would be interesting to take one of them and wire up their brain to a computer to see whether their responses are different from that of normal humans. Only trouble is they’re so rich that they can employ really big bodyguards and generally reckon their brains are their own concern.

Emotionless Delusions

Antonio Damasio has conducted lots of research on the effects on reasoning of damage to the areas of the brain implicated in emotion – probably best encapsulated in his book Descartes’ Error: Emotion, Reason, and the Human Brain. The results are largely counterintuitive. What he shows is that emotion and reasoning seem to be linked at the hip, or at least at the prefrontal cortex. Emotion doesn’t make us irrational, rather it seems that it’s part and parcel of whatever rationality we actually possess.

In essence emotions are heavily tied into the business of decision making: you probably wouldn’t want to entrust your safety to someone whose emotional reactions were damaged. For instance there are a range of rather nasty syndromes associated with the loss of emotional arousal including Cotard’s syndrome where the person thinks they’re dead and the Capgras delusion which causes the sufferer to think that a person or persons close to them have been replaced by an identical clone. Although these may sound odd or even amusing they’re not: Capgras sufferers have been known to behead their nearest and dearest to prove that they’ve been replaced by machines and been found burrowing in the remains looking for the batteries.

Emotions and Decision Making

Human decision making is one of the main puzzles facing psychology. How do we decide what considerations to take into account and what to leave out? This is hard enough at the best of times but is especially difficult under conditions of ambiguity or uncertainty. Technically the problem of deciding what to take into account when making a decision is known as the philosopher’s frame problem – given limited time and limited intelligence how do we manage to do anything other than stare at our navels?

The philosopher Ronald de Sousa (who provides a good introduction to theories of emotion at the Stanford Encyclopedia of Philosophy) has argued that rational decision making is critically dependent on emotions – emotions are the way evolution has fitted us to focus on the important issues involved in any decision. Emotions are a rapid response mechanism to filtering out the unimportant features of any situation. When you’re about to be eaten by a tiger then the colour of your kimono shouldn’t really matter.

If de Sousa’s ideas are even roughly correct then we can’t simply become unemotional by choice, because emotions are implicit in who we are. However, we can learn to control our emotions in specific situations in order to restrict our behaviour: we can learn practical rationality. So, implementation of Graham’s mantra requires a real determination to ignore all the churned up feelings of the primordial ape within us and resolution to focus on the few certainties that we can latch onto in the investment world.

Brain Damaged Investors

Some research we’ve looked at before by Baba Shiv and others, including Damasio, into the impact of emotional centre brain damage on investor decisions suggests that a lack of emotion is actually a benefit to investors. While such damaged people might not be able to judge the danger of walking into a Hell’s Angel’s convention and disrespecting facial hair they are remarkably good at making sensible investment decisions. So while in real life a failure to take contextual information into account may be exceptionally dangerous it seems to be a benefit when investing.

Lest all of this seem to suggest that the great investors of the world are simply people who’ve been hit on the head one too many times let’s be clear that what we’re ultimately talking about is the ability to inhibit emotional reactions to investing situations, rather than advocating some process of self-induced brain trauma. So, it would seem that these emotional responses are getting triggered inappropriately in investing situations, leading to decisions that are simply stupid. Which suggests that learning to control these responses should make us better investors or, as Ben Graham would put it, would make us more businesslike.

Beyond Asset Value – Back to Rent Seeking

In Graham’s heyday this was simpler than today: his mechanical strategy looked for clear mispricing of stocks in terms of discount to net asset value. Most, if not all companies, were valued based on their assets. What Warren Buffett realised, earlier than most, is that this has changed. The corporations of today are valuable more for their future earnings streams than their assets. The most valuable companies are those successfully engaged in rent seeking – gaining value by extracting fees without making any contribution to productivity. It’s those companies who can make money simply by existing that are most valuable.

The trouble with this is that it’s far harder to value rent seeking corporations like American Express and Coca Cola than the traditional Graham-type discount to net asset value opportunities. Which brings us back to the messy business of emotions: we can’t simply put aside our emotions by running a spreadsheet. We have to engage in the difficult job of identifying the must-have rent seekers and then waiting for the price to fall to a level at which we can rationally judge it rational to invest.

Businesslike Under Uncertainty

Only when this point comes it’s most likely that it’s on the back of some dramatic and stomach churning market event. Most people can’t ignore their emotions at these points – the overwhelming evidence of mutual fund investment flows is that people buy at the top and sell at the bottom. Short of beating ourselves around the head regularly we have to learn to stop listening to our in-built emotional warning systems and embrace the uncertainty. Only then will be truly businesslike in our investment habits.


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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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The Malthusian Prophesy

Doubting Thomas

Of the great triumvirate of men who invented the concept of economics Thomas Malthus is the one who’s received the bad press. Admittedly this is because, unlike Adam Smith and David Ricardo, his most famous prediction – that human population growth was ultimately limited by the capacity of the environment to produce enough food to support it – has so far been wrong. Although only by a few billion mouths or so.

However, the failure of the Malthusian Prophesy can only be temporary if human growth continues unabated. The Earth's an island and we’re marooned. Somehow, somewhere, sometime human population growth will run up against a lack of sustainable resources. Worryingly our best hope of avoiding catastrophe probably lies in the dismal science of economics, a strange superhero if there ever was one.

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Bacteria, Boids and Market Instability

The Gaps Between People

Old-time economics saw investors as rational individuals, all behaving autonomously in a logical fashion, rather like Mr. Spock umbilically attached to Deep Thought. Today not even economists really believe that this is how people actually operate, but figuring out something better is a not insignificant task. Psychologists, however, have long known that what happens in the gaps between people is as important as what happens in the gaps between their ears – so is there something going on in the interactions between investors, which causes market instability?

One possible answer comes from the study of bacteria. Just as we might have suspected all along, stockmarket investor behaviour can be modelled by examining the way a bunch of brainless, single celled and barely animate creatures interested only in food and reproduction disport themselves on a Petri plate. Sometimes analogies are just too sweet.

Investing Earthquakes

The critical thing about any economic model is that it arrives at results that look like what we actually see in markets. Mostly the jargon fixated commentators who dominate the media are happy to talk in terms of business cycles when, in reality, the only cycles seen in most investing circles are the ones used by the boys and girls delivering lunchboxes. What we actually get, if we look at stockmarkets and stock prices, is something that looks like the readout we see from a seismograph when an earthquake occurs.

If we start by making a few assumptions about what investors actually do in real life – like, for instance, that they don’t behave rationally and that they tend to copy successful behaviour from people they’re closely connected to – we can rapidly create a model that produces outputs that look very different from those generated by models of people who behave independently and rationally. In fact the output of these models looks a lot like the readout we see from a seismograph when an earthquake occurs.

So it seems that the interactions between investors and how these interactions affect their willingness or otherwise to invest is the critical thing in these models. Fundamental value is, in fact, not the most important issue most of the time. Indeed, what seems to be really important is the internal behaviour of the participants, not the external behaviour of companies out in the real-world. Which simply confirms the suspicions of harassed leaders of industrial companies – the markets don’t care about real business issues.

Of Birds and Bacteria

Oddly enough the synchronised behaviour necessary to generate the type of herding needed to make this model work has been seen in various naturally occurring systems, including birds and self-propelled flagellant bacteria. The vast flocks of birds that sometimes arise, wheeling in perfect synchronicity, are utter marvels of the animal world. How can one bird, at the edge of the flock, move in tandem with another on the other side? Some deep thinkers have suggested that this can only be due to animal telepathy, but these people are, frankly, idiots.

The explanation is much more prosaic. It turns out that we can replicate this behaviour simply by using a few rules about how any given bird interprets the behaviour of the birds around it. A change at one edge of the flock can ripple through the whole in a matter of seconds purely by each individual bird reacting to the ones around it. There’s been lots of computer modelling done to show this working with so-called boids. Certain types of self-propelling bacteria demonstrate the same type of behaviour. However, if you introduce noise into the system, so that the creatures can’t communicate very effectively, then the synchronisation breaks down.

If the standard unsynchronised bacteria are our investors in their normal modes and the synchronised ones are what happens at market extremes when noise levels drop it’s fairly easy to see how the connectivity of the various agents is critical. In a world in which mass, instantaneous communication is prevalent it’s perhaps no surprise that we’re seeing more instability in markets and economies. The transmission of information, fear and greed is simply faster and easier than ever before – and we should therefore expect far greater and faster displays of irrational exuberance.

Phase Transitions in Markets

These types of models where we see sudden switches between different states are characteristic of something known as a phase transition. Phase transitions occur naturally and are unquestionably hard-wired into the structure of reality. Only we don’t quite know how or why.

For example, we see a phase transitions when water boils. This transition happens across the whole substance instantaneously, as if all of the molecules simultaneously decide to stop doing one thing and start doing another. This looks an awful lot like what we witness in our bird flocks as each molecule reacts to the ones around it and the change flows through the material.

A number of researchers have suggested that a type of phase transition (technically known as log periodic) marks the point at which markets crash: when suddenly all the parts of the system instantaneously align their behaviour and everything changes on the lazy flap of a single butterfly’s wings. Indeed they go further and argue that because such events have a typical signature in terms of oscillatory behaviour it’s possible to detect them ahead of time.

Marxist Instability Rules

Lots of work has gone on to prove this by looking at historical records of crashes. This research by Sornette and Johansen gives an overview but is a few years old now and work has continued apace in the meantime. The fits that the researchers have been able to obtain have been rather impressive. Unfortunately hindsight doesn’t make anyone rich and attempts to predict future market crashes have so far been, and let’s be kind here, completely, utterly and abysmally wrong. Worse still, if the predictions did come true and people started to believe their models then the predictions would start to fail because behaviour would change to incorporate the new reality. It’s really, really tough being an economics researcher.

Karl Marx theorised that the capitalist model demanded that there was inherent instability – that the periodic booms and busts we see are an inevitable property of the market economy. He went on to draw some rather larger conclusions about the result of these fluctuations which ultimately led to the deaths of tens of millions of people and some really bad architecture so we shouldn’t be blasé about the power of economics to affect our world. Still, his underlying premise seems to be as sound as ever: markets are fundamentally inclined to instability. There is no end to boom and bust and there never can be.

And if you don’t believe me, ask a bacterium.


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Panic!

Economic Stability Is Not The Norm

The exceptional market conditions of the last couple of years are a reminder that we should regard stable markets as a pleasant interlude rather than the normal state of affairs. In general, of course, people tend to expect tomorrow to be much the same as yesterday and to behave as such. It’s little wonder, then, that when everything goes wrong people start to panic, assuming the world is coming to an end.

Of course, so far, the world hasn’t come to an end – although a lot of people have lost lots of money in the meantime. What we can see from history is not that market panics are exceptional but that they’re the norm.

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Regret

Behavioural Biases (4): Regret

If you’ve ever done something and then regretted it you’re in the fine company of the rest of the human race. If you’ve never regretted anything then you’re probably a sociopath and need to stop attacking people with spatulas and get a nice quiet hobby instead. Something like misdirecting people into buying stupid stocks on internet bulletin boards should do nicely.

If you are fairly normal, however, you’ll be aware that regret is an unpleasant and queasy feeling which you’d generally rather avoid if at all possible. As ever, when it comes to finance, obeying the urgings of your intestines comes at a cost. In investment it pays it to pays to regret nothing: although it’s certainly true that pride comes before a fall in your portfolio value.

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Holes in Black-Scholes

Betting on Getting Flattened

It’s a rite of passage these days to diss the Black-Scholes option pricing model. Maybe this is because it’s the best known of the quantitative models that underlie the problems in global finance, although the fact it’s known to fail in unusual market conditions probably doesn’t help. On the flip side, if we know that Black-Scholes doesn’t work at market extremes you’d have thought there’d be ways of making money out of its failures.

Unsurprisingly it turns out that there are people looking at this. It also turns out that only a few have the mental discipline to achieve success because you spend a lot of time losing. You’re throwing pennies under the steamroller and watching others gather them while betting big money on the penny-gathers getting flattened eventually. It’s a discipline requiring courage, intelligence, patience and knowledge of history. So that rules most traders out, then.

Black, Scholes and Merton

Back in the 1970’s Fischer Black and Myron Scholes developed a method of pricing options which, with the typical inventiveness of economists, they called the “Black-Scholes method.” Following adaptations by Robert Merton it’s become the standard method of pricing options and earned all three a Nobel Prize. It’s also become the target of many other economists who either wish they’d thought of it first or reckon it shouldn’t ever have been thought of at all.

Options allow us to take a bet on the future price of some asset like a share without actually going to the trouble of buying it. They give the buyer the right, but not the obligation, to buy or sell the underlying asset at a pre-agreed price by a pre-agreed date. They’re a type of derivative – their value is derived from the underlying asset. Derivatives have been given a bad name over the years, being associated with many of the truly horrible things that the nastier investment gnomes are apt to get up to. However, used correctly, they can be hugely beneficial as they allow the risk associated with any asset to be transferred from where it can’t be dealt with to where it can be.

Essentially an option is a trade in uncertainty. If you can’t, for instance, afford to take the risk that your share portfolio will fall below a certain value then you can use options to protect yourself against this. If the portfolio falls below the trigger point you sell the option and pocket the cash. If it doesn’t then the option will expire and the money you spent on it disappears. Used like this options are a form of insurance. Of course, some financiers have found other more ‘creative’ ways of using them.

Volatility, Liquidity and LTCM

Black-Scholes allows traders to plug in values for asset prices, dividends, interest rates, time and volatility to produce a valuation. Volatility – the amount by which an asset’s price may vary over any given period – is often the critical factor. An asset with high volatility is more attractive to buyers of options because there’s a greater probability that, at some point, it’ll be in the money. Conversely assets with low volatility are more likely to be favoured by option sellers.

Black-Scholes came in for criticism due to its involvement in the collapse of Long Term Capital Management (LTCM) in 1998. LTCM imploded when Russia defaulted on its bonds because the model didn’t cope with the “impossible” liquidity crisis that followed: it didn’t handle the extreme conditions that resulted in no one being willing to accept the other side of LTCM’s deals.

Peer under the covers of Black-Scholes and you find our old friend, the Gaussian distribution, assuming that extreme events are impossible instead of just rather unlikely. The unlikely happens all the time in markets, usually because of human behavioural biases which kick in at extreme moments and lead to sustained overshoots in valuations and liquidity.

Taleb on Black-Scholes

Nicolas Taleb is a vehement critic of Black-Scholes as can be seen in “Why We Have Never Used the Black-Scholes-Merton Option Pricing Formula“:

“Option traders call the formula they use the “Black-Scholes-Merton” formula without being aware that by some irony, of all the possible options formulas that have been produced in the past century, what is called the Black-Scholes-Merton “formula” … is the one the furthest away from what they are using. In fact of the formulas written down in a long history it is the only formula that is fragile to jumps and tail events.”

Taleb profits from the deficiencies of the model by betting that the markets will go mad, eventually. He may lose small amounts of money most of the time but when things go really wrong he makes a huge killing. However, he’s not the only famed investor to look at the inadequacies of the model.

Buffett on Black-Scholes

Just this year Warren Buffett has shown that Black-Scholes can lead to irrational pricing, even during non-extreme conditions, over very long periods. By looking at the effect including volatility has on option valuations he concludes that this leads to stupid outcomes:

“The ridiculous premium that Black-Scholes dictates in my extreme example is caused by the inclusion of volatility in the formula and by the fact that volatility is determined by how much stocks have moved around in some past period of days, months or years. This metric is simply irrelevant in estimating the probability weighted range of values of American business 100 years from now. (Imagine, if you will, getting a quote every day on a farm from a manic-depressive neighbor and then using the volatility calculated from these changing quotes as an important ingredient in an equation that predicts a probability-weighted range of values for the farm a century from now.)”

Buffett’s suggesting a value investing approach to making money from the indiscriminate application of such models – invest over long enough periods to make short-term human irrationality, aka volatility, an irrelevance. Unfortunately most of us don’t have the lifespans to wait the decades he envisages, but maybe there’s yet another way of profiting from irrational option pricing.

Longshot-Favourite Bias versus Black-Scholes

Back in 1947 Richard Griffith showed that there was an irrational behavioural bias being applied to horseracing odds. The favourite-longshot bias states that favourites are consistently underpriced and longshots consistently overpriced. So a 2-1 favourite is more likely to win than its odds suggest and the 100-1 outsider is less likely to win. This finding has been replicated time and again. In fact you wouldn’t need to add much in the way of skill and judgement to make betting on the favourite consistently a winning strategy. Some other researchers have wondered whether the bias also applies to people investing in options.

Options are either “out of the money” – i.e. trading at a level where they won’t make any money if exercised at the moment – or “in the money” – trading at a level where they are currently worth exercising. Buying an option that’s a long way out of the money is the equivalent of betting on a longshot, buying a deep in the money option, a favourite.

Black-Scholes predicts that calls which are further out of the money will provide greater returns, the opposite of what favourite-longshot bias suggests. The limited evidence so far suggests that it’s the bias which drives the price rather than the model. This would be consistent with irrational investors doing irrational things – exactly the conditions under which Black-Scholes might be expected to fail.

It isn’t yet clear that this research amounts to a way of actually making money but it does, at least, add weight to two conclusions. Firstly, before you put your trust in any automated model make sure you understand it. And secondly, always assume that irrational people will find a way of breaking it, no matter how careful you are.


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