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Paul Wilmott Wants To Retrain and Reform Wall Street's Quants
theodp writes "What if an aeronautics engineer couldn't reconcile his elegant design for a state-of-the-art jumbo jet with Newton's second law of motion and decided to tweak the equation to fit his design? In a way, Newsweek reports, this is what's happened in quantitative finance, which is in desperate need of reform. And 49-year-old Oxford-trained mathematician Paul Wilmott — arguably the most influential quant today — thinks he knows where to start. With his CQF program, Wilmott is out to save the quants from themselves and the rest of us from their future destruction. 'We need to get back to testing models rather than revering them,' says Wilmott. 'That's hard work, but this idea that there are these great principles governing finance and that correlations can just be plucked out of the air is totally false.'"
I'm a long way from New York, so someone correct me if I'm wrong[*], but I've always understood the problem to lie more with the people feeding data into the equations, rather than with the equations themselves.
Now, I accept that risk calculations consisted of a great deal of voodoo because, as Taleb tells us, they tended to ignore 'Black Swan' events (where the 1 in a million catastrophe wasn't going to happen just yet) and saw patterns where only chaos existed, but as I understand it, the core of the problem was simple greed: money-hungry mortgage and securities dealers deliberately feeding bad data into the system.
So-called quants may be decidedly imperfect, but if someone's willing to game the system to make a buck, nothing the quant does can stop it.
If Wilmott doesn't have an answer to that, I fear that his efforts will only obscure the real problem.
Crumb's Corollary: Never bring a knife to a bun fight.
You know, this is just tinkering. It's a way of passing the buck. It's a way of devolving blame. It MUST be the equations, or the software, or some geek or some technological prblem that caused the economics failures.
It wasn't. It isn't.
The reason why we have economic problems is the same old one from the beginning of time -- good old fashioned human greed.
Equations, and new software isn't going to change that. What you need to do is ensure that the people operating systems and processes are ethical and honest. It's really that simple, and also, unfortunately, that difficult.
...you always reach a point where there's this one number that is completely made up...
***Try a sensitivity analysis using Monte Carlo techniques. That sounds hard but it isn't. Take the parameter that you have doubts about and give it a distribution (Gaussian or rectangular or something) with the mean at your best guess and the std deviation chosen to be big enough to cover the range it might reasonably vary over.
***Use Gaussian if you have an idea of what the parameter probably is but aren't exactly sure, rectangular if you really have no idea. A rectangular distribution says "I have no idea, the parameter could be anywhere within this particular range."
***Then run your analysis a million times with the parameter selected randomly from it's distribution for each run.
***That gives you a stochastic dataset of results. You can run simple stats on that data set to find the mean and std dev of the result value. You will then know how sensitive your results are to your poorly understood input parameter. If your 2-sigma output tells you the expected rate of return on a particular investment varies between -50% to +50% then you will know your model is pretty much useless and you will be doing a better job than the vast majority of professional analysts.
****Monte Carlo is great for those of us who don't care to learn the arcane minutiae of stat math. If you have a working model it takes an hour or two to extend it so you get stochastic results. Note that it's no harder to give a distribution to all your input parameters not just one. In which case you will be doing the kind of work that people who make 500 grand a year do.
Equine Mammals Are Considerably Smaller
Nice idea, but Wilmot seems to have forgotten the most basic law of finance---nothing matters so long as you're making lots of money. Does he really think that the Quants on Wall Street and in London care about robust models and statistical significance? No! We're talking about used car salespersons in $5,000.00 suits. The financial industry is completely amoral. The only law is the law of the jungle. You can't confuse greed with a lack of quality control.