This is the third in a series of four posts dedicated to the subject of financial market predictability. In this month’s letter, I look at financial bubbles and the work of physicist turned bubble-spotter Didier Sornette.
"Both are driven by a vast multitude of positive and negative feedback loops"
Use of the word ‘bubble’ with respect to financial markets dates back to 1720 and the passing in June of that year by the British parliament of what was known as The Bubble Act, a response to the 87% collapse in the stock price of the South Sea Company and consequent bankruptcy of numerous and important investors.
Financial bubbles – also known as asset bubbles and speculative bubbles – have been described in many different ways but most definitions seem to relate in some way to prices that rise far above intrinsic value. Following this meteoric rise, a bubble then goes ‘pop’, with prices falling sharply back towards or below intrinsic value.
Yale’s Robert Shiller defined a speculative bubble as “a social epidemic whose contagion is mediated by price movements. News of price increase enriches the early investors, creating word-of-mouth stories about their successes, which stir envy and interest. The excitement then lures more and more people into the market, which causes prices to increase further, attracting yet more people and fuelling “new era” stories, and so on, in successive feedback loops as the bubble grows. After the bubble bursts, the same contagion fuels a precipitous collapse, as falling prices cause more and more people to exit the market, and to magnify negative stories about the economy.”
Former Federal Reserve governors Alan Greenspan and Ben Bernanke both said that it was impossible to spot bubbles in asset prices until after they had burst. It is possible they believed this. More likely, they realised that an admission to the contrary would impose on them a responsibility to pop bubbles, perhaps complicating or, at worst, endangering their key objectives with respect to inflation and employment.
In the aftermath of the 2008/9 financial crisis, and in order to study bubbles in a formal setting, Sornette established the Financial Crisis Observatory (FCO). He wanted to understand how a few hundred billion of losses in 2008 in one small corner area of the financial world – US subprime lending – triggered a US$5 trillion contraction in world GDP and almost US$30 trillion of losses in global stock market capitalisation. Also, whether the carnage was directly related to the 30 or so years of stability – known as The Great Moderation – that preceded it.
The FCO was established as “a scientific platform aimed at testing and quantifying rigorously, in a systematic way and on a large scale the hypothesis that financial markets exhibit a degree of inefficiency and a potential for predictability, especially during regimes when bubbles develop.” In other words, not only can you spot asset bubbles, but you can also predict when they’ll burst.
Sornette’s own, and simpler, definition of bubbles is that they are “significant persistent deviations from fundamental value”. It is the study of complex systems that links the financial world with that of physics and thus what attracted Sornette to the field of bubbles. The weather and the stock market may not at first appear related, but both are driven by a vast multitude of positive and negative feedback loops that can be described using a common framework.
Sornette and his colleagues at the FCO developed a theory called “dragon kings” as a framework for understanding asset bubbles. Unlike so-called black swans – events that come completely out of the blue – “dragon kings” are catastrophic occurrences but ones whose origins are very much traceable. In financial markets, “dragon kings” are evidenced by price movements that fall far outside a normal expected probability.
The term “dragon king” is a reference both to the mythical creature that falls far outside a normal classification scheme – Sornette himself describes dragons as “extraordinary animals of extraordinary properties” – and to the “King Effect”, in which a simple linear relationship describes the distribution of wealth of all members of a society other than those at the very top. According to Sornette,“The root mechanism of a “dragon king” is a slow maturation towards instability, which is the bubble, and the climax of the bubble is often the crash.”
Getting a little more technical, one particular signal that a bubble is developing is super-exponential growth with positive feedback. Rather than being followed by a price reversal as is often the case, a 1% price rise instead triggers a 2% price rise which in turn triggers a 4% price rise, etc. In the real world, of course, things are not so simple, but Sornette’s theoretical models not only appear to mimic closely the growth phase of financial asset bubbles but also to define a “finite-time singularity”, the point at which a bubble bursts. This bursting may be quick - a crash - or slow – a plateau. Either way, according to Sornette, “the information about the critical time is contained in the early development of this super-exponential growth.”
Sornette has had some success in identifying ex ante a number of asset bubbles. In September 2007 he predicted that the bubble in Hong Kong and Chinese shares would “change regime” by the end of the year and that there “might be a crash”. More recently, in May 2013, he noted that the US stock market was on an unsustainable trend and that there would be a correction – as indeed there was – but that this was only part of a “massive bubble in the making”.
Perhaps in response to criticism, and to add rigour to his approach, Sornette now encrypts his predictions, posts them on an international archive, then releases a public key six months later. He also now regularly posts on his website an FCO Cockpit – an assessment of bubble tendencies of 435 systemic assets or indices.
The main argument against the notion that it is possible to identify bubbles and predict when they’ll burst is that if that were indeed possible, investors would anticipate them such that they’d never have a chance to develop in the first place. However, that assumes investors behave rationally whereas the reality is that at times, and en masse, they don’t. This may be not only what supports Sornette’s model, but all arguments that financial markets are predictable.
Published in Investment Letter, October 2019
The views expressed in this communication are those of Peter Elston at the time of writing and are subject to change without notice. They do not constitute investment advice and whilst all reasonable efforts have been used to ensure the accuracy of the information contained in this communication, the reliability, completeness or accuracy of the content cannot be guaranteed. This communication provides information for professional use only and should not be relied upon by retail investors as the sole basis for investment.