I've always thought theoretical physics was the best training for applying mathematical techniques to real world problems. Mathematicians seldom look at data, so are less likely to have the all-important intuition for developing simple models of messy systems, and for testing models empirically. Computer scientists generally don't study the broad variety of phenomena that physicists do, and although certain sub-specialties (e.g., machine learning) look at data, many do not. Some places where physics training can be somewhat weak (or at least uneven) include statistics, computation, optimization and information theory, but I've never known a theorist who couldn't pick those things up quickly.
Physicists have a long record of success in invading other disciplines (biology, computer science, economics, engineering, etc. -- I can easily find important contributions in those fields from people trained in physics, but seldom the converse). Part of the advantage might be pure horsepower -- the threshold for completing a PhD in theoretical physics is pretty high. However, a colleague once pointed out that the standard curriculum of theoretical physics is basically a collection of the most practically useful mathematical techniques developed by man -- the high points and greatest hits! Someone trained in that tradition can't help but have an advantage over others when asked to confront a new problem.
Having dabbled in fields like finance, computer science and even biology, I've come to consider myself as a kind of applied mathematician (someone who applies mathematical ideas to the real world) who happens to have had most of his training from working on physical systems. I suspect that physicists who have left the field, as well as practitioners of biophysics, econophysics, etc. might feel the same way.
Readers of this blog sometimes accuse me of a negative perspective towards physics. Quite the contrary. Although I might not be optimistic about career prospects within physics, or the current state of the field, I can't think of any education which gives a richer understanding of the world, or a greater chance of contributing to it.
...Finkelstein, who also grew up in Kharkov, has a Ph.D. in theoretical physics from New York University and a master’s degree in the same discipline from the Moscow Institute of Physics and Technology. Before joining Horton Point as chief science officer, he was head of quantitative credit research at Citadel Investment Group in Chicago.
Most of the 12 Ph.D.s at Horton Point’s Manhattan office are researching investment strategies and ways to apply scientific principles to finance. The firm runs what Finkelstein, 54, describes as a factory of strategies, with new models coming on line all the time. “It’s not like we plan to build ten strategies and sit on them,” he says. “The challenge is to keep it going, to keep this factory functioning.”
Along with his reservations about statistical arbitrage, Sogoloff is wary of quants who believe the real world is obliged to conform to a mathematical model. He acknowledges the difficulty of applying scientific disciplines like genetics or chaos theory — which purports to find patterns in seemingly random data — to finance. “Quantitative work will be much more rewarding to the scientist if one concentrates on those theories or areas that attempt to describe nonstable relationships,” he says.
Sogoloff sees promise in disciplines that deal with causal relationships rather than historical ones — like mathematical linguistics, which uses models to analyze the structure of language. “These sciences did not exist five or ten years ago,” he says. “They became possible because of humongous computational improvements.”
However, most quant shops aren’t exploring such fields because it means throwing considerable resources at uncertain results, Sogoloff says. Horton Point has found a solution by assembling a global network of academics whose research could be useful to the firm. So far the group includes specialists in everything from psychology to data mining, at such schools as the Beijing Institute of Technology, the California Institute of Technology and Technion, the Israel Institute of Technology.
Sogoloff tells the academics that the goal is to create the Bell Labs of finance. To align both parties’ interests, Horton Point offers them a share of the profits should their work lead to an investment strategy. Scientists like collaborating with Horton Point because it combines intellectual freedom with the opportunity to test their theories using real data, Sogoloff says. “You have experiments that can be set up in a matter of seconds because it’s a live market, and you have the potential for an amazing economic benefit.” ...
