Conditional Value-at-Risk: Aspects of Modeling and Estimation
Massachusetts Institute of Technology (MIT) - Department of Economics; New Economic School
Stanford University - Management Science & Engineering
MIT Dept. of Economics Working Paper No. 01-19
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.
Number of Pages in PDF File: 28
Keywords: Conditional Quantiles, Quantile Regression, Extreme Quantiles, Extreme Value Theory, Extreme Risk
JEL Classification: C14, C13, C21, C51, C53, G12, G19working papers series
Date posted: June 7, 2001
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