Semi-Parametric Estimation of Joint Large Movements of Risky Assets

25 Pages Posted: 23 Mar 2009

Date Written: March 18, 2009

Abstract

This article presents a semi-parametric framework for estimating the probability of joint large movements of asset prices using extreme value theory. The advantages of this approach are: no parametric form for the dependence structure of the joint large movements has to be specified, avoiding the model misspecification; it addresses specifically the scarcity of data, a problem when fitting fully parametric models; it is suitable for portfolios of many assets, there is no dimension explosion.

We show the strength of the approach using returns on three international equity indices: S&P500, Nikkei250 and FTSE100. We find that although the S&P500 and FTSE100 have similar univariate tail heaviness, the former makes a much larger contribution to the probability of large losses on an equally weighted portfolio.

Keywords: portfolio tail probability,risk management,multivariate extreme value theory

JEL Classification: C51,G11

Suggested Citation

Dias, Alexandra, Semi-Parametric Estimation of Joint Large Movements of Risky Assets (March 18, 2009). Available at SSRN: https://ssrn.com/abstract=1364519 or http://dx.doi.org/10.2139/ssrn.1364519

Alexandra Dias (Contact Author)

University of York ( email )

Freboys Lane
Heslington
York, North Yorkshire YO10 5DD
United Kingdom

Do you have negative results from your research you’d like to share?

Paper statistics

Downloads
3
Abstract Views
114
PlumX Metrics