Thanks to Black-Scholes, options pricing no longer had to rely on educated guesses. Derivatives trading got a huge boost and quants poured into the industry. By 2005 they accounted for 5% of all finance jobs, against 1.2% in 1980, says Thomas Philippon of New York University—and probably a much higher proportion of pay. By 2007 finance was attracting a quarter of all graduates from the California Institute of Technology.
These eggheads are now in the dock, along with their probabilistic models. In America a congressional panel is investigating the models’ role in the crash. Wired, a publication that can hardly be accused of technophobia, has described default-probability models as “the formula that killed Wall Street”. Long-standing critics of risk-modelling, such as Nassim Nicholas Taleb, author of “The Black Swan”, and Paul Wilmott, a mathematician turned financial educator, are now hailed as seers. Models “increased risk exposure instead of limiting it”, says Mr Taleb. “They can be worse than nothing, the equivalent of a dangerous operation on a patient who would stand a better chance if left untreated.”
Modelling is not going away; indeed, number-crunchers who are devising new ways to protect investors from outlying fat-tail risks are gaining influence. Pimco, for instance, offers fat-tail hedging programmes for mutual-fund clients, using cocktails of options and other instruments. These are built on specific risk factors rather than on the broader and increasingly fluid division of assets between equities, currencies, commodities and so on. The relationships between asset classes “have become less stable”, says Mohamed El-Erian, Pimco’s chief executive. “Asset-class diversification remains desirable but is not sufficient.”
In some areas the need may be for more computing power, not less. Financial firms already spend more than any other industry on information technology (IT): some $500 billion in 2009, according to Gartner, a consultancy. Yet the quality of information filtering through to senior managers is often inadequate.
The way forward is not to reject high-tech finance but to be honest about its limitations, says Emanuel Derman, a professor at New York’s Columbia University and a former quant at Goldman Sachs. Models should be seen as metaphors that can enlighten but do not describe the world perfectly. Messrs Derman and Wilmott have drawn up a modeller’s Hippocratic oath which pledges, among other things: “I will remember that I didn’t make the world, and it doesn’t satisfy my equations,” and “I will never sacrifice reality for elegance without explaining why I have done so.” Often the problem is not complex finance but the people who practise it, says Mr Wilmott. Because of their love of puzzles, quants lean towards technically brilliant rather than sensible solutions and tend to over-engineer: “You may need a plumber but you get a professor of fluid dynamics.”
One way to deal with that problem is to self-insure. JPMorgan Chase holds $3 billion of “model-uncertainty reserves” to cover mishaps caused by quants who have been too clever by half. If you can make provisions for bad loans, why not bad maths too?
http://www.economist.com/specialreports/displaystory.cfm?story_id=15474075
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