The Physics of Wall Street: A Brief History of Predicting the Unpredictable; by James Owen Weatherall

Q: What is The Physics of Wall Street all about?

A: Over the past few years, we've heard a lot about a new kind of Wall Street elite known as "quants." These are often physicists and mathematicians who have moved to finance and brought radically new ideas along with them. This book is an attempt to understand these quants and the mathematical models they use to predict market behavior. It's two parts history and one part argument: I tell the surprisingly fun story of how physicists and their ideas made it to Wall Street in the first place, and along the way I argue that this history reveals something important about how we should think about the models and practices they have introduced—especially in light of the 2007–2008 financial crisis.

Q: You say the history is surprisingly fun. Can you give an example?

A: The physicists and mathematicians I write about in the book are (or were) very smart, creative people who put their scientific training to use in surprising new ways. Their stories are fascinating. For instance, Edward Thorp, who invented the modern quantitative hedge fund, was also the first person to prove that card counting could be used to reliably get an edge in blackjack. He spent a good amount of time working the card tables in Las Vegas. And Norman Packard and Doyne Farmer, who started a pioneering financial services firm in the early 1990s, spent their graduate school years at UC Santa Cruz inventing the new science of chaos theory while trying to build a computer to beat the odds in roulette—the profits from which were intended to start a yippie commune
in the Pacific Northwest.

Q: What surprised you most about the history you uncovered?

A: One thing that surprised me was that derivatives contracts such as options, futures,, and swaps, which are often discussed as though they were a troubling new innovation, have actually been around for thousands of years. For example, scientists have found cuneiform tablets containing records of futures traded by ancient Sumerians. Even the idea of using mathematical methods to price options is quite old. I pick up the story in 1900, with the visionary work of a French physicist named Louis Bachelier, but some strands go back further, to the mid-nineteenth century. Plus, there are some striking historical connections in the book. For instance, I explain the relationship between the invention of nylon and the development of the atomic bomb — and how both influenced at least one physicist's to switch to a financial career. And I tell the story of how the space race and the Vietnam War were partly responsible for many physicists moving to Wall Street banks in the 1980s.

Q: What can this history teach us about models used in finance?

A: If you look at how the physicists and mathematicians who came up with the earliest financial models thought about what they were doing, the role of simplifying assumptions and idealizations becomes very clear. The goal was to get a toehold on some very hard problems, and not to come up with a final, overarching theory of financial markets. Making simplified assumptions can lead to the solution of a problem that you otherwise couldn't solve — but that solution is only going to be a reliable guide to how the world works when the assumptions you've made are approximately true. The important question, and the one that physicists are always trained to ask, is when do your assumptions fail and what happens when they do? I don't think the importance of this question has been recognized as widely as it should be among the traders who rely on these models.

Q: But if you know the models can fail, why would you use them?

A: I think the right way to think about these models is as a kind of tool. Tools are often useful, but you need to understand what they're for, how to use them, and most important, their limitations. Financial models provide important and valuable information about markets that you can't get any other way, but they are not the final word.

The situation is much like other areas of engineering. There, too, we use mathematical models as an essential part of the process. And the assumptions behind these models can fail. If a bird flies into a jet engine, for instance, the engine is liable to seize no matter how good the models that were used to design it. Does this mean we should abandon the models? No. Of course, markets are far more complex, but the principle is the same. So if useful tools are available, take advantage of them.

Q: At the end of the book, you describe an "Economic Manhattan Project."
What would that be like?

A: The Economic Manhattan Project was proposed in 2008 by the mathematical physicist and hedge fund manager Eric Weinstein. The idea is that economic and financial security—that is, regulating the economy to avoid future calamities—should be at the very top of our agenda. Yet the resources we devote to physical security, to military technology and defense, far outstrip what we spend on developing better economic theories. In the past, America has set goals—for the original Manhattan Project, the race to the moon, and others—when we have funneled resources into serious innovation. And whenever we have done so, we have succeeded in accomplishing great things. I think it is time to make a similar kind of commitment to developing the next generation of economic models, with the goal of finding radical new ideas to make the economy safer and more robust.

Q: You're a philosophy professor. Why did you write a book about finance?

A: The short answer is simply that I find the history and the ideas fascinating. I have a Ph.D. in physics and I like thinking about how physics can be applied to novel problems. The longer answer is that the issues in this book aren't so far removed from philosophy. Philosophers spend a lot of time thinking about what we can know about the world and how to deal with fundamental uncertainty. Philosophy has a reputation for being abstract and distant from everyday concerns. And sometimes it is. But when it comes to mathematical models, philosophical issues really matter for how we make important economic and financial decisions—decisions that have significant real-world ramifications. And for me, at least, the most interesting and important philosophical questions are those that we face as practicing scientists and policymakers—and even as investors.

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