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October 19, 2007



To "assume" that the Bell Curve applies is on a par with the mumbo-jumbo of the modelling of Global Warming.

Luis Enrique

"This, though, means that "probability" is not something that exists independently, and is given by the data. Instead, it's something subjective that we impose onto the data."

This may be a bit picky, but if probability does not exist independently, what is it that you are trying to figure out? Isn't it more accurate to write that while probability may exist independently, our ability to apprehend it is poor, and calculations based on data may do a worse job of describing probability than subjective evaluations.

Matt Munro

IOW probability is socially constructed. Probability is a measurement, and like all measurements it is only "true" at the point it is taken.

james c

I wonder whether oceanographers have such debates about the normal distribution of waves and the 100 s.d. tsunamis that occasionally occur.Or perhaps they realise that the tsunamis are caused by a different process than everyday waves.


If you believe returns are normally distributed, the answer - for practical purposes - is: no.

Why on earth would I believe that? I might just about be able to invoke the central limit theorem if I looked at yearly averages, and even that would be a bit of a stretch (even then, the CLT doesn't strictly apply, but I could probably construct a plausible argument that would suggest that one would expect the distribution to tend towards the normal anyway.)

But daily volitility? Why on earth should I expect that to be normally distributed? I see no reason for it to be, and every reason for it not to be.


How about Extreme Value Theory ?


The normal (Gaussian) distribution and Central Limit Theorem do not fit with stock prices. Their use in this context is an example of the lamppost effect - the convenient mathematics of the Gaussian is attractive in the way the drunk looks for his lost keys, not in the place where he dropped them, but under the lamppost where there is light enough to see.

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