Forecasting with fat tailed distro

Random variables in the power law class with tail exponent α ≤ 1 are, simply, not forecastable. They do not obey the LLN. But we can still understand their properties.”

“If one claims fitness or nonfitness of a forecasting ability based on a single observation = 1, she or he would be deemed to be making an unscientific claim. For fat tailed variables that “= 1″ error can be made with n = 106. In the case of pandemics, n = ∞ is still anecdotal. (..) It takes 1014 observations for a “Pareto 80/20” (the most commonly referred to probability distribution, that is withα ≈ 1.13) for the average thus obtained to emulate the significance of a Gaussian with only 30 observations.”

Taleb justifying the precautionary principle on statistcis ground, in a challenge with Ioannidis who called for reopening the economy based on poor data


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