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Semiparametric estimation of dynamic conditional expected shortfall models

Author

Listed:
  • 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.

Suggested Citation

  • Juan Carlos Escanciano & Silvia Mayoral, 2008. "Semiparametric estimation of dynamic conditional expected shortfall models," International Journal of Monetary Economics and Finance, Inderscience Enterprises Ltd, vol. 1(2), pages 106-120.
    • Handle: RePEc:ids:ijmefi:v:1:y:2008:i:2:p:106-120
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    Citations

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    Cited by:

    1. Escanciano, Juan Carlos & Velasco, Carlos, 2010. "Specification tests of parametric dynamic conditional quantiles," Journal of Econometrics, Elsevier, vol. 159(1), pages 209-221, November.
    2. repec:hal:journl:peer-00732534 is not listed on IDEAS
    3. Escanciano, Juan Carlos & Velasco, Carlos, 2010. "Specification tests of parametric dynamic conditional quantiles," Journal of Econometrics, Elsevier, vol. 159(1), pages 209-221, November.
    4. Juan Carlos Escanciano, 2020. "Uniform Rates for Kernel Estimators of Weakly Dependent Data," Papers 2005.09951, arXiv.org.

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