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 Y-t with special reference to the case when auxiliary information is available in the form of a set of predictors X-t. We consider three classes of estimators of the conditional expected shortfall of Y-t given X-t: 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. Copyright (C) 2008 John Wiley & Sons, Ltd.
Peracchi, F., Tanase, A. (2008). On estimating the conditional expected shortfall. APPLIED STOCHASTIC MODELS IN BUSINESS AND INDUSTRY, 24(5), 471-493 [10.1002/asmb.729].
On estimating the conditional expected shortfall
PERACCHI, FRANCO;
2008-01-01
Abstract
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 Y-t with special reference to the case when auxiliary information is available in the form of a set of predictors X-t. We consider three classes of estimators of the conditional expected shortfall of Y-t given X-t: 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. Copyright (C) 2008 John Wiley & Sons, Ltd.File | Dimensione | Formato | |
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