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Conditional Value-at-Risk and Average Value-at-Risk: Estimation and Asymptotics

So Yeon Chun (), Alexander Shapiro () and Stan Uryasev

MPRA Paper from University Library of Munich, Germany

Abstract: We discuss linear regression approaches to conditional Value-at-Risk and Average Value-at-Risk (Conditional Value-at-Risk, Expected Shortfall) risk measures. Two estimation procedures are considered for each conditional risk measure, one is direct and the other is based on residual analysis of the standard least squares method. Large sample statistical inference of the estimators obtained is derived. Furthermore, finite sample properties of the proposed estimators are investigated and compared with theoretical derivations in an extensive Monte Carlo study. Empirical results on the real-data (different financial asset classes) are also provided to illustrate the performance of the estimators.

Keywords: Value-at-Risk; Average Value-at-Risk; Conditional Value-at-Risk; Expected Shortfall; linear regression; least squares residual; quantile regression; conditional risk measures; statistical inference (search for similar items in EconPapers)
JEL-codes: C53 D81 G32 C15 C1 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-ban, nep-ecm, nep-ore and nep-rmg
Date: 2011-04-03
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https://mpra.ub.uni-muenchen.de/30132/1/MPRA_paper_30132.pdf original version (application/pdf)
https://mpra.ub.uni-muenchen.de/33115/1/MPRA_paper_33115.pdf revised version (application/pdf)

Related works:
Journal Article: Conditional Value-at-Risk and Average Value-at-Risk: Estimation and Asymptotics (2012) Downloads
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