Semiparametric estimation of dynamic conditional expected shortfall models
AbstractThe 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 InfoArticle provided by Inderscience Enterprises Ltd in its journal Int. J. of Monetary Economics and Finance.
Volume (Year): 1 (2008)
Issue (Month): 2 ()
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Web page: http://www.inderscience.com/browse/index.php?journalID=218
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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- J. Carlos Escanciano & Carlos Velasco, 2010.
"Specification tests of parametric dynamic conditional quantiles,"
- Escanciano, Juan Carlos & Velasco, Carlos, 2010. "Specification tests of parametric dynamic conditional quantiles," Journal of Econometrics, Elsevier, vol. 159(1), pages 209-221, November.
- 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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