Semiparametric estimation of dynamic conditional expected shortfall models
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.
Volume (Year): 1 (2008)
Issue (Month): 2 ()
|Contact details of provider:|| Web page: http://www.inderscience.com/browse/index.php?journalID=218|
When requesting a correction, please mention this item's handle: RePEc:ids:ijmefi:v:1:y:2008:i:2:p:106-120. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Graham Langley)
If references are entirely missing, you can add them using this form.