Conditional Value-at-Risk: Aspects of Modeling and Estimation

Chernozhukov, Victor; Umantsev, Len

doi:10.2139/ssrn.272488

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Conditional Value-at-Risk: Aspects of Modeling and Estimation

28 Pages Posted: 7 Jun 2001

See all articles by Victor Chernozhukov

Victor Chernozhukov

Massachusetts Institute of Technology (MIT) - Department of Economics

Len Umantsev

Stanford University - Department of Management Science & Engineering

Date Written: November 2000

Abstract

This paper considers flexible conditional (regression) measures of market risk. Value-at-Risk modeling is cast in terms of the quantile regression function - the inverse of the conditional distribution function. A basic specification analysis relates its functional forms to the benchmark models of returns and asset pricing. We stress important aspects of measuring very high and intermediate conditional risk. An empirical application illustrates.

Keywords: Conditional Quantiles, Quantile Regression, Extreme Quantiles, Extreme Value Theory, Extreme Risk

JEL Classification: C14, C13, C21, C51, C53, G12, G19

Suggested Citation: Suggested Citation

Chernozhukov, Victor and Umantsev, Len, Conditional Value-at-Risk: Aspects of Modeling and Estimation (November 2000). Available at SSRN: https://ssrn.com/abstract=272488 or http://dx.doi.org/10.2139/ssrn.272488