Portfolio Selection: An Extreme Value Approach

Authors:
Preprint
Publisher website
Google Scholar
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.

This publication has 57 references indexed in Scilit: