Select your localized edition:

Close ×

More Ways to Connect

Discover one of our 28 local entrepreneurial communities »

Be the first to know as we launch in new countries and markets around the globe.

Interested in bringing MIT Technology Review to your local market?

MIT Technology ReviewMIT Technology Review - logo


Unsupported browser: Your browser does not meet modern web standards. See how it scores »

{ action.text }

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.

4 comments. Share your thoughts »

Tagged: Business

Reprints and Permissions | Send feedback to the editor

From the Archives


Introducing MIT Technology Review Insider.

Already a Magazine subscriber?

You're automatically an Insider. It's easy to activate or upgrade your account.

Activate Your Account

Become an Insider

It's the new way to subscribe. Get even more of the tech news, research, and discoveries you crave.

Sign Up

Learn More

Find out why MIT Technology Review Insider is for you and explore your options.

Show Me