Semiparametric estimation of dynamic conditional expected shortfall models Articles uri icon

publication date

  • January 2008


  • 2


  • 1

International Standard Serial Number (ISSN)

  • 1752-0479

Electronic International Standard Serial Number (EISSN)

  • 1752-0487


  • 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. (copyright) 2008 Inderscience Enterprises Ltd.


  • coherent risk measures; conditional distribution; conditional value at risk; cvar; market risk; tail risk; tail var