Unlike the value at risk, the expected shortfall is a coherent measure of risk. In this paper, we discuss estimation of the expected shortfall of a random variable Yt with special reference to the case when auxiliary information is available in the form of a set of predictors Xt. We consider three classes of estimators of the conditional expected shortfall of Yt given Xt: a class of fully non-parametric estimators and two classes of analog estimators based, respectively, on the empirical conditional quantile function and the empirical conditional distribution function. We study their sampling properties by means of a set of Monte Carlo experiments and analyze their performance in an empirical application to financial data.
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Paper provided by Tor Vergata University, CEIS in its series CEIS Research Paper with number
122.
Length: 29 pages Date of creation: 14 Jul 2008 Date of revision:
14 Jul 2008 Handle: RePEc:rtv:ceisrp:122
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References listed on IDEAS Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
Koenker, Roger W & Bassett, Gilbert, Jr, 1978.
"Regression Quantiles,"
Econometrica,
Econometric Society, vol. 46(1), pages 33-50, January.
[Downloadable!] (restricted)
Shorrocks, Anthony F, 1983.
"Ranking Income Distributions,"
Economica,
London School of Economics and Political Science, vol. 50(197), pages 3-17, February.
[Downloadable!] (restricted)