Physicsworld on quants

I came across these articles from Physicsworld again recently. They're quite old (1999), but made some interesting points.

Physicsworld: ...the strongest demand will be for "people who have had a rigorous training in applied sciences (physics, engineering, etc), where the emphasis is on problem solving" rather than people who have specifically trained in financial mathematics. The report has even better news for physicists, especially those with skills in probability theory, stochastic calculus and partial differential equations: "Even though mathematical skills are sought, we found a strong preference for physicists over mathematicians. As one bank explained it: 'Physicists want to find the answers to problems. Mathematicians have all the answers and want problems to solve.' "

Compare to this quote about Crick and Watson from biologist Erwin Chagraff:

It was clear to me that I was faced with a novelty: enormous ambition and aggressiveness... I could not help being baffled. I am sure that, had I had more contact with, for instance, theoretical physicists, my astonishment would have been less great. In any event, there they were, speculating, pondering, angling for information. ...

The comment in bold below is quite interesting and, I think, quite correct: physicists are often very sloppy, but they have a good nose for where the action is. I also think we just went through a phase transition in investor attitudes towards risk and the future.

Physicsworld: ...The international financial markets generate lots of data about the high-frequency variations in price of many different assets (stocks, currencies, bonds and so on), and these data are available to physicists for analysis. Physicists have their own way of analysing data, which is very different from the way econometricians (as economists who specialize in this area are called) look at data. For example, physicists are not interested in proving that a statistical model is right, but rather in extracting useful intuitions based on observation and developing computational methods to develop this intuition. As physicists we are sure that analysis of financial data will undoubtedly benefit from ideas and methods invented for statistical physics, such as critical phenomena, turbulence and various non-equilibrium phenomena.

...A topic of much research is the possible connection between financial crashes and "critical points" in statistical mechanics, where the response of a physical system to a small external perturbation becomes infinite because all the subparts of the system respond co-operatively. Classic examples include the liquid-gas critical point in water and the Curie point in magnetism (i.e. the temperature above which ferromagnetic materials become paramagnetic). Similarly, during crashes, a large proportion of the players in a market decide simultaneously to sell their stocks.

...Similarly, although it may in principle be possible to model the behaviour of each individual operator or "agent" in a financial market, this is obviously a daunting task. The fact that one of them needs to sell his stock because he wants to buy a car, or that another one wants to buy some stocks because a friend advised him to do so, might be more conveniently described, on a coarser scale, by a Langevin noise.

However, many economists - who believe that agents are rational and try to optimize their "utility function" (essentially a trade-off between profit and risk) - are reluctant to accept such a theoretical shortcut. Indeed, some economists even claim that it is "an insult to the intelligence of the market" to invoke the presence of a noise term!

Interestingly, the same debate happened recently between engineers and physicists in the context of traffic modelling, where the analogue of the rational-agent hypothesis is that each driver wants to maximize his or her speed. Without any "noise" to account for unexpected braking events (caused, for example, by the driver sneezing), the rational-driver model predicts a steady flow of cars all moving rapidly along the road. As soon as a small amount of noise is introduced, however, traffic jams appear and disrupt the steady flow - and make the model more realistic. In other words, the addition of an arbitrarily small amount of noise allows one to reproduce an everyday phenomenon that would be absent in a perfectly rational world. Similarly, one can expect that small irrational effects might completely change the picture emerging from a completely rational economic model.

...One of the primary assets that physicists bring to finance and economics is their intermediate level of mathematical sophistication - half way between the empirical knowledge of traders and the highly formal approach taken by economists, which is sometimes remote from reality. The use of intuition based on decades of research into the highly complex systems found in statistical physics - including finely honed approximation schemes and problem-solving techniques - offers a new dimension not found in economics textbooks.