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Semiparametric estimation of dynamic conditional expected shortfall models

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  • Juan Carlos Escanciano
  • Silvia Mayoral

Abstract

The paper proposes a simple estimator for a class of Conditional Expected Shortfall risk measures. The estimator is semiparametric, in the sense that it does not require a full specification of the conditional distribution of the data, and it is very simple to compute, being a least squares estimator with a closed form expression. We establish its consistency and asymptotic normality under mild regularity conditions. A simulation study provides evidence of the excellent finite-sample properties of the estimator and an application to some exchange rates highlights the semiparametric aspect of the new estimator.

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Bibliographic Info

Article provided by Inderscience Enterprises Ltd in its journal Int. J. of Monetary Economics and Finance.

Volume (Year): 1 (2008)
Issue (Month): 2 ()
Pages: 106-120

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Handle: RePEc:ids:ijmefi:v:1:y:2008:i:2:p:106-120

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Web page: http://www.inderscience.com/browse/index.php?journalID=218

Related research

Keywords: conditional value at risk; CVaR; Tail VaR; coherent risk measures; tail risk; market risk; conditional distribution; semiparametric estimation; conditional expected shortfall models.;

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Cited by:
  1. Juan Carlos Escanciano & Carlos Velasco, 2008. "Specification Tests of Parametric Dynamic Conditional Quantiles," Caepr Working Papers 2008-021, Center for Applied Economics and Policy Research, Economics Department, Indiana University Bloomington.

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