Survival of the Richest
Financial markets are supposed to pool the knowledge of market participants to come to the most efficient decision about matters like what a stock is worth. They’re supposed to be rational – driven by the numbers and facts. But, in fact, financial markets are better understood as biological systems, argues Andrew W. Lo, professor at MIT’s Sloan School of Management and director of the MIT Laboratory for Financial Engineering.
Lo, also a partner in the AlphaSimplex hedge fund, combines mathematics, neurology, and psychology to study how markets work. One of his research projects actually involves putting traders in an magnetic resonance imaging (MRI) machine and measuring their brain activity. Once a disciple of the Efficient Markets Hypothesis – the premise that markets operate rationally and efficiently – Lo wants to replace that model with the biologically driven Adaptive Markets Hypothesis.
Technology Review: When did you decide that biology might help you to understand how markets behave?
Andrew W. Lo: I’ve always been interested in biology, and evolution is one of most important topics in modern science and society. So little by little I tried to think about how it is that evolution affects economic interactions. I remember about ten years ago, where at the end of the year I felt so frustrated that [the Efficient Market Hypothesis] didn’t make sense to me. And then the year after, when I started really taking more seriously the notion of evolution and its impact on financial markets, it somehow all fell into place. It’s such a simple idea: namely, that financial market participants adapt to changing market conditions. That seemed to explain pretty much everything. In the last five or six years I’ve used this paradigm to explain one anomaly after another. And at this point I really feel like there isn’t a single anomaly that financial market participants have documented that I cannot explain with this framework.
TR: Can you give us an example of evolution working in financial markets?
AL: An example of behavioral bias is what psychologists like to call “loss aversion.” When you’re faced with losses you become much more risk-seeking; and when you’re faced with large gains, you become much more conservative, much more risk-averse. And that, people have documented, is generally not conducive to building wealth. It’s rational to cut your losses and ride your gains. Instead, in practice what people do when they’re losing is to double their bets in the hopes of getting back to even – traders call it doubling down. And when you’re making money you cash out right away and preserve your gains. That is irrational behavior in financial markets.
I’ve derived a simple mathematical model to show that loss aversion is really the outcome of a survival instinct. This notion of loss aversion, being more aggressive when you’re losing and more conservative when you’re winning, is a very, very smart thing to do when you’re being hunted on the plains of the African savannah. However, it’s not a smart thing to do when you’re on the floor of the New York Stock Exchange.
TR: And what you’ve found is that people can evolve past that instinct?
AL: It’s really survival of the richest. The traders that are successful are the ones that survive and make money. The ones that engage in the kind of loss aversion most of us are subject to end up losing their money and they leave the [trading] population.
TR: You’ve studied actual traders from a couple of perspectives. [Lo has published papers on the psychophysiology of traders, measuring skin conductance, heart rates, and the like, and correlating these measurements to market activity.] Where does the functional magnetic resonance imaging (FMRI) come in to play?
AL: We have a conjecture that there are certain components of the brain that are responsible for trading, and we want to see whether or not we’re right.
TR: You literally have people hooked up to an MRI during their trading day?
AL: The test subject is a day trader. He lies in the MRI machine and can see the screen of a laptop computer using a mirror in the MRI machine. His hands are free to use a mouse and he simply pulls up his trading software and we have a mouse that’s made of all plastic components – it costs $5,000 – and he uses it to monitor the markets while we’re imaging him, and makes trades.
TR: What do you gain from knowing what parts of the brain are used in trading?
AL: We know that emotional responses – things like sweaty palms and increased heart rate – correlate with fluctuations in the market. MRI provides us with a more refined understanding of how financial decisions get made. Is there specific circuitry in the brain that’s designed for financial decision-making versus a combination of existing components that are used for other kinds of decision-making that happen to get borrowed for financial decision-making? From very preliminary evidence, it looks like the answer is that there isn’t a financial market decision-making center in the brain.
This is important because I think it supports and confirms the Adaptive Markets Hypothesis. It says that humans are not ideally suited for economic decisions. The same faculties or heuristics for deciding whether or not to cross a busy street are used to decide whether to buy Microsoft or sell General Electric. Those heuristics will fail because they are not optimized for a financial context – they are optimized for the physical world. So one needs to be a little more cautious about making [financial] decisions using those kinds of heuristics.
TR: What else are you working on now?
AL: I’m also looking at hedge funds, as a kind of laboratory for studying the impact of the evolution of the markets. Hedge funds are the Galapagos Islands of financial markets: the barriers to entry are low, the rewards are very high, and therefore the competition is fierce and species are coming and going all the time.
TR: What kinds of things nag at you about your hypothesis?
AL: The open questions are what are the dynamics that drive evolution? There’s always this tension between environmental conditions and the genetic predisposition of the population. I don’t have a clear understanding of the notion of genes. I haven’t worked out the dynamics of the generational transfer of genetic material in a corporate and financial context.
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