Just how did that pesky little Sars-CoV-2 virus jump from bat to humans, bringing Covid-19 with it? Steven Soderbergh’s 2011 film Contagion provides as plausible a scenario as any – from bat to half-eaten banana to pig to pork to chef to, as it were, Gwyneth Paltrow and then you’re away.
Yet, in that chain of events, had anything been ever so slightly different then the virus would not have spread, the infection would not have taken hold, the whole world would have been different. Ditto – most likely – the real life Covid-19. At work here is chaos theory, which, more formally, is known as ‘non-linear dynamics’. It is the notion that very small differences in the initial conditions of otherwise similar patterns can eventually produce enormously different outcomes essentially because there is feedback between cause and effect.
It is widely caricatured as ‘the butterfly effect’ because something as innocuous as a Blue Morpho butterfly flapping its wings at a critical juncture of four-dimensional space-time in the Amazon jungle sparks a hurricane that wrecks the east coast of the US before smashing New York.
Talking of Amazon, in finance and business, chaos theory helps explain how huge variations in the outcome can hinge on small differences at the start, which are then magnified by feedback. Why is it that the animal raised by Jeff Bezos has become a global-striding corporate beast and not, say, Barnes & Noble or Borders, both of which appeared to be revolutionising bookselling in the late 1990s? Similarly, why did AltaVista eventually fail while Google, a comparative latecomer, became the western world’s dominant search engine? On a smaller scale, how could Fevertree Drinks (FEVR) turn itself into a £2.7bn business in a matter of a few years when the flavoured sparkling water it sells is much like any other? Looking into the future, which – if any – of the 38 Chinese car makers listed by Wikipedia (excluding joint ventures with western manufacturers) will become the Sino equivalent of General Motors (US:GM)?
Whatever the rationalised answers to these questions, chaos theory will be embedded within them. Before the meltdown into the credit crunch of 2008, chaos theory’s explanation of the finance industry was seen as an entertaining sideshow. Now it’s mainstream. So much so that bankers and regulators – not just academics – talk of things such as ‘preferential attachment’, ‘self-organised criticality’ and ‘highly optimised tolerance’.
Preferential attachment tells us that the stock market, much as John Maynard Keynes once said, is like a beauty parade – investors become besotted with the prettiest stock. The company behind the stock may not even make profits. On close examination, its business model may be flaky. But its bosses tell a sweet story and it becomes popular. Then – much as Dan Brown’s books are bought and Katy Perry’s singles are streamed – every investor wants to buy the stock; and they buy it because others are buying. Similarly, investment themes can become dominant. Why else were there obsessions with Japan’s equities in the late 1980s, technology stocks in the late 1990s and developing markets at various times over the past 30 years? Mathematicians formalise this into something called Zipf’s Law. Basically this tells us that extreme popularity is both rare and contagious, and beyond a critical point it can grow at a scarily exponential rate, just like the price of a glamour stock.
Self-organised criticality is the idea that in financial markets – just as in nature – things organise themselves into complex systems that live on the edge of a chaotic breakdown and it does not take much to push them over. Just a few extra grains of sand will cause the perfect sand castle to collapse. A car braking at the wrong moment will cause a massive pile-up on the motorway. An ostensibly innocuous increase in interest rates by Germany’s Bundesbank on Friday 16 October 1987 prompted Black Monday on the 19th, still the worst day in Wall Street’s history when the Dow Jones Index fell 22.6 per cent on the day.
Highly optimised tolerance may be even more dangerous. It takes a state of self-organised criticality and assumes it can be controlled by a human agency. So it offers both the illusion of control and the opportunity to push out boundaries; such as the illusion of control of the global finance system by the world’s central banks and the opportunity for commercial banks to gorge themselves on financial instruments – in particular, collateralised debt obligations – that no one fully understood.
Perhaps scariest of all, chaos theory tells us that extreme events – be they in the world of financial contagion or viral contagion – happen much more frequently than conventional theories predict. Where feedback is running, an event that would be highly improbable otherwise, becomes a weekly event. According to research by Xavier Gabaix, a finance professor at New York University’s Stern School of Business, “the 1929 and 1987 crashes do not appear to be outliers in the power-law distribution of returns”.
The moral is to be sceptical of conventional linear explanations of why things happen; why China’s stock market is rising or Tesco’s share price is falling. That, and never let a bat discard a half-eaten banana.
