Finance Gets Physical

Jamie Bernardin has a PhD in optical physics. He has no training in finance, and until recently, he had no interest in the subject, either. But now, instead of aiming lasers at mirrors, Bernardin designs options-pricing software for Bank of America. Surprisingly, Bernardin’s career change isn’t much of a change at all. Sure, he now […]

Jamie Bernardin has a PhD in optical physics. He has no training in finance, and until recently, he had no interest in the subject, either. But now, instead of aiming lasers at mirrors, Bernardin designs options-pricing software for Bank of America.

Surprisingly, Bernardin's career change isn't much of a change at all. Sure, he now wears a suit and holds meetings with high-powered traders, but the essence of his work remains true to the discipline he studied for eight years: physics.

And he's not alone. Since the advent of computers helped make possible the efficiency of today's sophisticated financial markets, thousands of lab jockeys like Bernardin have been quietly applying their hard-science training to the world of high finance ­ and quietly revolutionizing the way big financial institutions do business. "Financial engineering" they call it, and it's a field that's closer to physics than classical economics.

"The basic starting point for pricing simple options is the Black-Scholes equation, which is basically a heat-diffusion equation," says Bernardin. "The same computational methods apply. For instance, I'm now applying the work I did on transverse soliton coupling in laser crystals to increase the efficiency of our risk-management tools. It's the same math."

It's the same math. Meaning that flnancial markets behave in ways similar to the natural processes that govern, say, heat transfer?

"Yes," Bernardin says. "Exactly."

The explanation for this is both simple and profound. Although flnancial markets are arbitrary, human-driven entities ­ and thus are not subject to strict mathematical laws ­ the cumulative effect of millions of individual decisions to buy or sell is to create a system that is effectively random. Not truly random, but close enough.

This means that the same mathematics used to describe and predict random systems in the physical world can also be unleashed on pork bellies and mutual funds. It also means that the people most qualified to design financial instruments and analytical software may have PhDs in science instead of MBAs in economics.

But as David Rowe, a senior vice president at Bank of America with a PhD in economics, stresses, finance is still not a science. "The work these financial engineers do is invaluable. The traders use their models, but at the end of the day, they still have to make gut-level decisions. A PhD in physics doesn't help you much then."

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