Aug

24

 I read a very entertaining article in Scientific American yesterday: "Can Math Beat Financial Markets ".

Stefan Jovanovich writes: 

Check out the author's home page.

Gary Rogan writes: 

Looking at the page brings up the age-old question: can the same techniques that are used in natural science to study the universe that doesn't change from being studied and where the fundamental rules don't change at all be applied to a system where nothing prevents most rules (other than that old "human nature") from being changed at any time? He cut his teeth on never-changing, but how will it play with ever-changing? Somehow fractal coastlines are just not the same as fractal security price charts. Fat tails and non-gaussian distributions are great, but then what? We can evidently estimate the risk of something happening he says. But can we???

Ralph Vince adds: 

Yes, when he speaks of their raison d'etre "To quantify risk" I think, "Huh? How? VAR? Just HOW DO they 'Quantify Risk.'

If alluding to using it ("algorithmic trading," in the context of some sort of proce prediction a la quant, I assume he means modelling prices using models based on SDEs. Again, "Huh? How? Does this guy know what he is talking about?")

Quant-dom, traces it's roots to pricing of various securities — warrants, options, spread on futures/forwards, backwardations, and the pricing of the plethora of derivative creatures who climbed out of the ooze of ercent decades. This is NOT predicting markets, or "Quantifying Risk," (the latter, clearly, has utterly failed using their conventional models).

The entire article smacks to me of something dumbed down to the point of being useless and silly


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