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 International Journal of Monetary Economics and Finance.
Volume (Year): 1 (2008)
Issue (Month): 2 (January)
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Web page: http://inderscience.metapress.com/link.asp?target=journal&id=120880
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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- Escanciano, Juan Carlos & Velasco, Carlos, 2010.
"Specification tests of parametric dynamic conditional quantiles,"
Journal of Econometrics,
Elsevier, vol. 159(1), pages 209-221, November.
- J. Carlos Escanciano & Carlos Velasco, 2010. "Specification tests of parametric dynamic conditional quantiles," Post-Print peer-00732534, HAL.
- 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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