Dermans autobiography ‘My Life as a Quant‘ is a lovely nontechnical read. It follows from his childhood in South Africa, his desire to study physics and later disillusionment with postdoc study, through developing symbolic math software at Bell Labs, to his career as a rocket scientist on Wall St and top quant at Goldman Sachs. He comes across as a refined and honest intellectual with a real passion for his craft and the journey makes for a good story.
I just discovered an online video of a very punchy talk he gave at NYU on whats wrong with models [.mov format ~90Mb ~10mins].
This is awesome and he doesnt hold back. His main point is that although Black Scholes is a great advance, an elegant useful model, its only gonna give you a ballpark figure…
Unlike QED or other physics theories which are deeply descriptive of nature and can be accurate to 8 decimal places in predictive power, quantitative models interpolate. He makes an analogy with models like Black Scholes – Imagine you need to approximate the value of a manhattan apartment if you only have the square foot market value of a lower east side apartment for comparison… ok, I got the NY areas mixed up, but its clear we value one instrument in terms of another, making all sorts of reasonable ad hoc adjustments, such as higher comparative building maintenance service charges etc.. and factor all that into an ‘implied’ price per square foot price.
I guess his point is we have these ever more sophisticated models, more precise but not really more accurate, because they dont seem to uncover the Nature of how the markets work en mass. I particularly like the graph below showing Brownian versus Levy processes versus real market data – both real market and Levy are nonvanishing at 15+ standard deviations! Apparently nature does have a long fat tail
[ The above graph is from a talk given by Eugene Stanley of Boston university – talk slides here. Many of Stanley’s econophysics papers discuss the topic of scaling in markets and firm size, fairly convincingly – preprints list here. ]
Derman seems to suggest there are more fundamental truths to be discovered about markets, on the order of the ‘no-arbitrage’ idea, that might give real insight. [ When I hear smart people say things like volatility is sticky… I wonder whether flocking algorithms might describe the human behavior aspects of markets better. ]
Dammit, I’m nominating Derman for ‘the Feynman award 2008’ !