Felix Salmon recently wrote of the Quants, wondering what the physicists, mathematicians and financial wizards behind of all of those exotic quantitative trading options that performed so disasterously during the past two years are doing these days (emphasis ours):

I was talking about quant funds this afternoon, and got to wondering what on earth they're doing these days, given that their m.o., up until say the summer of 2007, was to find trading ideas, backtest them, try them out in real life for a while, and then pull the trigger and actually trade on them.

The question then becomes: what now? When you backtest, do you backtest through the quant blow-up of 2007 and the stock-market meltdown of 2008? If so, do you really think that's going to give you the kind of trading idea which will make money going forwards? And if not, then what do you ignore, and why do you ignore it, and what makes you think you won't run into a third period of high volatility which will lie well outside any reasonable assumptions you might make?

Up until 2007, the problems with quant funds was that the models didn't remotely conceive of the world as it transpired. Now, the problem with quant funds is that they can't help but conceive of the world as it transpired -- and basing your trading strategy on black-swan events which happen only very rarely is not a way to make lots of money.

I did express some hope, over the course of a fine bourbon, that the quants in question would find something rather more useful to do, rather than try to predict the future path of the ridiculously complex system that is the global financial system. But quants, anecdotally, are still in demand -- I get the feeling that many investors seem to believe that if they've blown up once, they're somehow less likely to blow up again. Which is something for which there is no empirical evidence at all.

Now, compare the history of the quants to their promise, as recorded in a 3 June 1999 editorial from Physics World, which reported on the findings of a study commissioned by the Centre for the Study of Financial Innovation (CSFI) that considered what the London-based banks hiring PhD-level physicists (aka "rocket scientists") expected them to bring to the world of finance (emphasis ours):

The report has good news for postgraduates in science and engineering: "There is little doubt that the City will continue to demand PhD-level quants." Moreover, 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.' "

This begs a question: "what specific problems did the financial institutions want the quants they hired to solve? The Physics World editorial provides the answer (emphasis ours):

The report is refreshingly direct in places: "Put bluntly, the City is depressingly unenthusiastic about university research." Or, as one US banker explained: "Academics are looking for market perfection, practitioners are trying to make a living out of imperfections." One reason for the lack of interest in funding external research is that most banks are interested in the short-term development of new financial products based on existing knowledge.

The same kind of new financial products that blew up in 2007 and 2008, less than a decade later. We can ask the question today: Didn't they know any better? We find the answer, again in Physics World, in an article that appeared in the January 1999 edition of the publication, Mutual Attractions: Physics and Finance, which considered the opportunity for physicists seen in options and futures in the then fairly new derivative markets (again, emphasis ours):

Options involve two basic questions. First, what price should the buyer agree to pay? (or how much should the writer of the option charge?). And second, what is the best strategy for the writer to follow - in terms of the number of stocks they should buy or sell during the lifetime of the contract - in order to minimize their risk?

One of the major achievements of modern finance is the Black-Scholes theory of option pricing, which addresses the above two questions. The theory was developed by the late Fischer Black - who had a first degree in physics and a PhD in applied mathematics - and Myron Scholes, an economist at Stanford University in California. Scholes shared the 1997 Nobel Prize for Economics with Robert Merton of Harvard, whose first degrees are in engineering and applied maths. Black would almost certainly have shared the prize had he still been alive. The Black-Scholes theory serves as a common language for all participants in option markets, and it underpins most of the software used in the business.

Unfortunately, the model used by Black and Scholes is Gaussian. This is very convenient from a mathematical point of view because one can rely on a score of useful tools, such as stochastic calculus, to solve it. However, as shown in figure 1, the markets are far from Gaussian. Moreover, in the Black-Scholes world, option writing can be made a completely risk-free operation - which is completely at odds with common sense (see Hull in further reading). The idea that risk can be reduced to zero can lead to a misleading - and potentially disastrous - sense of security on the financial markets.

So we confirm that the quants did indeed know there were serious problems with what they were doing. But very likely, the profits generated from the new financial instruments they did develop to exploit the imperfections found in Black-Scholes-based products were the motivating factor for their employers to never really set them to work in developing new financial products based upon more realistic assessments of risk. Which perhaps now helps explain Felix' anecdotal observation that the quants would seem to still be in such high demand:

However, it has recently been shown that this risk-free property is very specific to the Gaussian model and is not true for more realistic models (see Bouchaud and Potters in further reading). In reality, the residual risk is not, perhaps not surprisingly, that small compared with the price of the option. Developing a theory of derivative products in which the risk is properly estimated is a major challenge for econometricians and physicists alike.

Indeed.

Labels: none really

- posted by Ironman at 1:11 PM | Permalink | Home |