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Toward a Well-Diversified Risk Measure: A DARE Approach
Year Of Publication: 2010
Month Of Publication: February
Pages: 47
Download Count: 10
View Count: 1778
Comment Num: 0
Language: English
Source: working paper
Who Can Read: Free
Date: 9-11-2010
Publisher: Administrator
Summary
This paper provides a complete framework to aggregate different quantile and expectile models for obtaining more diversified Value-at-Risk (VaR) and Expected Shortfall (ES) measures, by applying the diversification principle to model extreme market risks. Following Taylor (2008a) and (2008b), Gouri'eroux and Jasiak (2008) and Kuan et ali (2009), we introduce a new class of models for the VaR and ES modeling called Dynamic AutoRegressive Expectiles (DARE). We first briefly present the main literature about VaR and ES estimations, and we secondly explain the DARE approach and how expectiles can be used to estimate quantile risk measures. We use the main and recent validation tests developed in the literature to compare the DARE approach to other traditional methods for computing extreme risk measures on the French stock market. Finally, we illustrate several conditional weighting functions (Hansen, 2008) of the various risk models aggregated within the DARE Approach, in order to dynamic
Author(s)
Hurlin, C_hristophe Sign in to follow this author
Maillet, Bertrand B. Sign in to follow this author
Kouontchou, Patrick Sign in to follow this author
Hamidi, Benjamin Sign in to follow this author
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