作者：NassimNicholasTaleb
出版社：STEMAcademicPress
副标题：RealWorldPreasymptotics,Epistemology,andApplications
出版年：2020-6-30
ISBN：9781544508054
内容简介
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The book investigates the misapplication of conventional statistical techniques to fat tailed distributions and looks for remedies, when possible.
Switching from thin tailed to fat tailed distributions requires more than “changing the color of the dress.” Traditional asymptotics deal mainly with either n=1 or n=∞, and the real world is in between, under the “laws of the medium numbers”–which vary widely across specific distributions. Both the law of large numbers and the generalized central limit mechanisms operate in highly idiosyncratic ways outside the standard Gaussian or Levy-Stable basins of convergence.
A few examples:
– The sample mean is rarely in line with the population mean, with effect on “naïve empiricism,” but can be sometimes be estimated via parametric methods.
– The “empirical distribution” is rarely empirical.
– Parameter uncertainty has compounding effects on statistical metrics.
– Dimension reduction (principal components) fails.
– Inequality estimators (Gini or quantile contributions) are not additive and produce wrong results.
– Many “biases” found in psychology become entirely rational under more sophisticated probability distributions.
– Most of the failures of financial economics, econometrics, and behavioral economics can be attributed to using the wrong distributions.
This book, the first volume of the Technical Incerto, weaves a narrative around published journal articles.
作者简介
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Nassim Nicholas Taleb spent 20 years as a derivatives and mathematical trader before starting his second career in applied probability. He is the author of 5-volume Incerto, an essay on uncertainty, published in 40 languages–with parallel journal articles and technical commentaries of which this book is an organized compilation. Taleb is currently Distinguished Professor of Risk Engineering at the Tandon School of Engineering of New York University and a (passive) principal of Universa Investments. The only prize he has accepted in recent decades in the Wolfram Research Innovation Award for work on computational approaches to nonstandard probability distributions, particularly preasymptotics
评论 ······
精彩绝伦！感谢公众号 SerendipityCamp的读书笔记！
只看里面的漫画
其实他提到的小概率大赔付的理念，与复杂性科学的很多结论是完全一致的。混沌世界保持随机的特征，但是小概率大赔付的涌现改变着每个人的命运。他的策略是永远与这类事件做朋友。正是涌现改变着这个世界，不是吗？！
只看里面的漫画
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