Kurtosis risk

[Siegmund]

Wellll...

For a start, kurtosis is a dimensionless quantity. If you calculated something that came out with units of BB/100, then you probably have the wrong number.

Still, it is true that high kurtosis means a lot of observations very near and very far from the mean, and not very many numbers on the order of 1 standard deviation away from the mean. You DO expect poker results to be like that since you have a lot of breakeven (early fold) hands and a few big-loss and big-win hands.

There isn't a simple one-size-fits-all adjustment for you to make based on the kurtosis (and kurtosis takes a lot longer to converge to a stable value than means and standard deviations do.)

If you are paranoid and want a completely worst-case situation (which you can think of as kurtosis approaching infinity), for simple confindence intervals you can resort to using Chebyshev's theorem, which says that at least 1-(1/k)^2 of your observations are within k standard deviations of your mean -- that is, 75% within 2 SDs, ~89% within 3, ~95% within 4. But there won't be a tidy risk of ruin formula for you.