Empirical Economics

, Volume 26, Issue 1, pp 271–292

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

  • Victor Chernozhukov
  • Len Umantsev

DOI: 10.1007/s001810000062

Cite this article as:
Chernozhukov, V. & Umantsev, L. Empirical Economics (2001) 26: 271. doi:10.1007/s001810000062

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.

Key words: Value-at-RiskQuantilesExtreme Value Theory
JEL classification: C14D81G11G28

Copyright information

© Springer-Verlag Berlin Heidelberg 2001

Authors and Affiliations

  • Victor Chernozhukov
    • 1
  • Len Umantsev
    • 2
  1. 1.Department of Economics, MIT, Cambridge, MA 02139 (e-mail: vchern@leland.stanford.edu)XX
  2. 2.Department of Management Science and Engineering, Stanford University, Stanford, CA 94305-4026 (e-mail: uman@stanford.edu)XX