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Conditional value-at-risk: Aspects of modeling and estimation

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  • Len Umantsev

    ()
    (Department of Management Science and Engineering, Stanford University, Stanford, CA 94305-4026)

  • Victor Chernozhukov

    ()
    (Department of Economics, MIT, Cambridge, MA 02139)

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 the extremal and intermediate conditional risk. An empirical application characterizes the key economic determinants of various levels of conditional risk.

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Bibliographic Info

Article provided by Springer in its journal Empirical Economics.

Volume (Year): 26 (2001)
Issue (Month): 1 ()
Pages: 271-292

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Handle: RePEc:spr:empeco:v:26:y:2001:i:1:p:271-292

Note: Received: September 30, 1999/Revised version: November 20, 2000
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Related research

Keywords: Value-at-Risk · Quantiles · Extreme Value Theory;

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