Statistical Consequences of Fat Tails by Nassim Nicholas Taleb

Statistical Consequences of Fat Tails by Nassim Nicholas Taleb

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 na ve 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.

SKU	Unavailable
ISBN 13	9781544508054
ISBN 10	1544508050
Title	Statistical Consequences of Fat Tails
Author	Nassim Nicholas Taleb
Series	Technical Incerto
Condition	Unavailable
Binding Type	Hardback
Publisher	STEM Academic Press
Year published	2020-06-30
Number of pages	446
Cover note	Book picture is for illustrative purposes only, actual binding, cover or edition may vary.
Note	Unavailable