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On estimating the conditional expected shortfall
Peracchi Franco and Tanase Andrei V.
CEIS Research Paper

Published in Applied Stochastic Models in Business and Industry, Vol.24, n., 2008

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.

Number: 122

Keywords: risk measures, quantile regression, logistic regression

JEL-codes: C13, E44, G11

Volume: 6

Issue: 6

Date: 14/07/2008

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