发表于2025-06-05
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
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.
Statistical Consequences of Fat Tails 下载 mobi pdf epub txt 电子书 格式 2025
Statistical Consequences of Fat Tails 下载 mobi epub pdf 电子书你相信:历史上极少数极端事件的影响会超过绝大多数平常事件吗? 比如2013年的非典,2019年的新冠…… 比如1987年的黑色星期一,2008年的全球金融危机…… 如果你认同这一观点,那其实代表你已经初步懂得了肥尾效应。 什么是肥尾效应呢? 这一概念是指极端行情发生的机率增加,...
评分其实想要理解肥尾效应并不是一件难事。大家拿到这本书的时候,一定会想这本书怎么全是数学概念?非数学专业的人能否看懂?其实没有必要有这种顾虑。里面的知识都是在大家已经掌握的知识上进行拓展。以此来描述经济市场里的“肥尾”这一概念。 肥尾,就是指没有预料到的厚尾或者...
评分 评分 评分##简评 这是一本将近500页的新书,内容非常详细,包括一些论文中的内容,数学推导很详细。 书中有部分关于新冠疫情的内容,可以推断成书时间比较近,反映了很多最新的思想。 作为第一次阅读塔勒布的书的作者,刚开始有点懵,不知道作者是什么职业、背景,网上查了下资料才了解。...
评分你相信:历史上极少数极端事件的影响会超过绝大多数平常事件吗? 比如2013年的非典,2019年的新冠…… 比如1987年的黑色星期一,2008年的全球金融危机…… 如果你认同这一观点,那其实代表你已经初步懂得了肥尾效应。 什么是肥尾效应呢? 这一概念是指极端行情发生的机率增加,...
评分##毫无疑问的是,我们生活在一个充满未知,充满不确定性的世界。数学家们试图通过一些概率学上的统计,来向我们描绘不确定性的图景。 正态分布就是数学家提出的一种模型,这种模型确实可以在很多情况下符合事实。正态分布像一只倒扣的钟。两头低,中间高,左右对称。应用到实际中...
评分##很惊讶这本书的评分如此低,是因为通篇都是数学吗? 我倒认为该书为今年必读书籍,因为作者进一步阐述了他的“黑天鹅”理论,必然让2022年这个黑天鹅事件频发的年份,让我们对世界有更深的理解。 黑天鹅世界理解起来并不困难,“我们终将一死”;“我们不知道明天和死亡哪一个...
Statistical Consequences of Fat Tails mobi epub pdf txt 电子书 格式下载 2025