28 Pages Posted: 7 Jun 2001
Date Written: November 2000
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). MIT Dept. of Economics Working Paper No. 01-19. Available at SSRN: https://ssrn.com/abstract=272488 or http://dx.doi.org/10.2139/ssrn.272488