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Portfolio Selection: An Extreme Value Approach

53 Pages Posted: 18 Sep 2011 Last revised: 27 Jul 2012

Francis DiTraglia

University of Pennsylvania

Jeffrey R. Gerlach

Federal Reserve Banks - Federal Reserve Bank of Richmond

Date Written: June 18, 2012

Abstract

We show theoretically that lower tail dependence (chi), a measure of the probability that a portfolio will suffer large losses given that the market does, contains important information for risk-averse investors. We then estimate chi for a sample of DJIA stocks and show that it differs systematically from other risk measures including variance, semi-variance, skewness, kurtosis, beta, and coskewness. In out-of-sample tests, portfolios constructed to have low values of chi outperform the market index, the mean return of the stocks in our sample, and portfolios with high values of chi. Our results indicate that chi is conceptually important for risk-averse investors, differs substantially from other risk measures, and provides useful information for portfolio selection.

Keywords: Portfolio selection, Extreme value theory, Tail dependence

JEL Classification: C58, G11

Suggested Citation

DiTraglia, Francis and Gerlach, Jeffrey R., Portfolio Selection: An Extreme Value Approach (June 18, 2012). Available at SSRN: https://ssrn.com/abstract=1929425 or http://dx.doi.org/10.2139/ssrn.1929425

Francis DiTraglia (Contact Author)

University of Pennsylvania ( email )

3718 Locust Walk
Philadelphia, PA 19104
United States
215-898-1506 (Phone)

HOME PAGE: http://www.ditraglia.com

Jeffrey R. Gerlach

Federal Reserve Banks - Federal Reserve Bank of Richmond ( email )

P.O. Box 27622
Richmond, VA 23261
United States

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