One has recently read a provacative article by Taleb and Mandelbrot on the errors and problems that investors make by relying on the normal distribution rather than the power law distributions for analyzing market behavior. They point to the inordinate number of large 12 sigma events they note in past market behavior, and how risk exposure is much greater than would be ascertained by naive or Rube Goldbergesque extensions of the normal distribution. And yet, the distribution of the sums of many different kinds of random variables converges under various degrees of restriction to the normal distribution, both theoretically and empirically.One wonders what are the predictive properties of these opposing views. Recently ,for example, we have had a spell of 4 years without a decline of 10% from top to bottom in the market, a duration longer than any since 1997,while at the same time the normal measures of volatility based on squared changes have decline from an average of say 20% retrospectively to 10%. Is there any such movement in markets that is consistent with one theory or the other and does this have any relevance to the very pointed discussions on the original thread of the waiting time till disaster. Sincerely, Proturf
