Statistical Consequences of Fat Tails: Real World Preasymptotics, Epistemology, and Applications

exactly what it was intended to do for its clients when COVID-19 became a pandemic. > your lizard brain is designed to handle futures on the order of seconds and minutes, not months and years, and certainly not decades and centuries. I guess I should eat my words for using an imprecise phrase like lizard brain but I'm talking about the limbic system which is most assuredly involved in decisions involving fear and ignorance and long term behavior, not snap decisions. Fear in ignorance is good if the possibility space you're ignorant of contains catastrophic consequences. If you have to make a decision that is beyond your intellectual capacity, you should be cautious. We evolved from very stupid creatures that needed to survive phenomena they did not understand. We have not transcended that need. Rationality is also knowing the limits of your rationality. > the appropriate reaction to an unpredictable event is no reaction at all, since by definition, you can't predict what it is, much less when it will happen. I'm sorry but this is collective suicide in the face of a pandemic. In the face of an exponentially self-propagating phenomenon that has a wide possibility of effects including: death, permanent injury and the collapse of the healthcare system, waiting around to get more information just means it would be too late if action was needed. Even if it turns out we could have gotten away without it this time, that doesn't mean we overreacted. > edit: also, fat-tailed typically means a tiny bit fatter than a guassian tail, not some wavy, unknownably fat "tail". otherwise, we'd have enough known events from which to draw reasonable predictions, making it not extreme and unpredictable, nor even a tail at all. Is this a philosophical point? Are you saying that if I cannot draw enough samples to approximate it that the population distribution doesn't exist? I'm arguing that there are limits to empirical methods in the face of extraordinary events and I'm making that claim somewhat more concrete by appealing to the divergence in behavior between the population and sample statistics of heavy-tailed, e.g. something with power law decaying tails like a pareto distribution. Is it ridiculous to conclude that in the face of extraordinary events that cannot be reasonably predicted empirically whose outcomes would be A) widespread, basically affecting everyone and B) potentially catastrophic, we have to be cautious? I don't see how.

twitter to raise his profile. He targets people who he thinks are likely to engage him (Nate Silver, Elon Musk etc), although most are too smart to take the bait. He fancies himself a powerlifter although he has physique of Homer Simpson. The man is generally a sad caricature of someone who traded volatility once. I personally mathematically model volatility for a living, and although I wouldn't pretend to have done as much as Bergomi I still feel I have the right to find Taleb grotesque. I agree that a mathematical history of non-Gaussian mathematics would be a fascinating thing, especially the recent past. I also would agree that just following links from "alpha Levy-stable" might not be as digestible as Taleb. But his pretensions and self-importance, in the face of completely superficial understanding and achievement, is gross. If history records his name and not Gatheral's it would be a crime.