The Dynamic Power Law Model
Bryan T. Kelly
University of Chicago - Booth School of Business; National Bureau of Economic Research (NBER)
May 1, 2014
Chicago Booth Research Paper No. 14-14
Fama-Miller Working Paper
I propose a new measure of common, time-varying tail risk for large cross sections of stock returns. Stock return tails are described by a power law in which the power law exponent is allowed to transition smoothly through time as a function of recent data. It is motivated by asset pricing theory and is estimable via quasi-maximum likelihood. Estimates indicate substantial time variation in stock return tails, and that the risk of extreme returns rises in weak economic conditions.
Number of Pages in PDF File: 31
Date posted: May 13, 2014
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