Varying the VAR for Unconditional and Conditional Environments

31 Pages Posted: 22 Jun 2007

See all articles by John Cotter

John Cotter

University College Dublin; UCLA Anderson School of Management

Date Written: 2006

Abstract

Accurate forecasting of risk is the key to successful risk management techniques. Using the largest stock index futures from twelve European bourses, this paper presents VaR measures based on their unconditional and conditional distributions for single and multi-period settings. These measures underpinned by extreme value theory are statistically robust explicitly allowing for fat-tailed densities. Conditional tail estimates are obtained by adjusting the unconditional extreme value procedure with GARCH filtered returns. The conditional modelling results in iid returns allowing for the use of a simple and efficient multi-period extreme value scaling law. The paper examines the properties of these distinct conditional and unconditional trading models. The paper finds that the biases inherent in unconditional single and multi-period estimates assuming normality extend to the conditional setting.

Keywords: Value at Risk, extreme value theory, GARCH filter, conditional risk

JEL Classification: G1, G10

Suggested Citation

Cotter, John, Varying the VAR for Unconditional and Conditional Environments (2006). Available at SSRN: https://ssrn.com/abstract=993930 or http://dx.doi.org/10.2139/ssrn.993930

John Cotter (Contact Author)

University College Dublin ( email )

School of Business, Carysfort Avenue
Blackrock, Co. Dublin
Ireland
353 1 716 8900 (Phone)
353 1 283 5482 (Fax)

HOME PAGE: http://www.ucd.ie/bankingfinance/staff/professorjohncotter/

UCLA Anderson School of Management ( email )

110 Westwood Plaza
Los Angeles, CA 90095-1481
United States

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