A DARE for VaR

Benjamin Hamidi, Christophe Hurlin, Patrick Kouontchou and Bertrand Maillet

Finance, 2015, vol. 36, issue 1, 7-38

Abstract: This paper introduces a new class of models for the Value-at-Risk (VaR) and Expected Shortfall (ES), called the Dynamic AutoRegressive Expectiles (DARE) models. Our approach is based on a weighted average of expectile-based VaR and ES models, i.e. the Conditional Autoregressive Expectile (CARE) models introduced by Taylor (2008a) and Kuan et al. (2009). First, we briefly present the main non-parametric, parametric and semi-parametric estimation methods for VaR and ES. Secondly, we detail the DARE approach and show how the expectiles can be used to estimate quantile risk measures. Thirdly, we use various backtesting tests to compare the DARE approach to other traditional methods for computing VaR forecasts on the French stock market. Finally, we evaluate the impact of several conditional weighting functions and determine the optimal weights in order to dynamically select the more relevant global quantile model.

Date: 2015
References: Add references at CitEc
Citations: View citations in EconPapers (4)

Downloads: (external link)
http://www.cairn.info/load_pdf.php?ID_ARTICLE=FINA_361_0007 (application/pdf)
http://www.cairn.info/revue-finance-2015-1-page-7.htm (text/html)
free

Related works:
Working Paper: A DARE for VaR (2015)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:cai:finpug:fina_361_0007

Access Statistics for this article

More articles in Finance from Presses universitaires de Grenoble
Bibliographic data for series maintained by Jean-Baptiste de Vathaire (operations@cairn.info).