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Evaluating Value-at-Risk Models via Quantile Regression
Year Of Publication: 2008
Month Of Publication: August
Pages: 30
Download Count: 20
View Count: 2154
Comment Num: 0
Language: English
Source: working paper
Who Can Read: Free
Date: 8-3-2010
Publisher: Administrator
This paper is concerned with evaluating value at risk estimates. It is well known that using only binary variables to do this sacrifices too much information. However, most of the specification tests available in the literature are based on such variables. In this paper we propose a new backtest that does not rely solely on binary variable. It is shown that the new backtest provides a sufficient condition to assess the performance of a quantile model whereas the existing ones do not.
This document is published in the Journal of Business and Economic Statistics (volume 29, number 1) January 2011, pp. 150-160
Renato Lima, Luiz Sign in to follow this author
Linton, Oliver Sign in to follow this author
Gaglianone, Wagner Piazza Sign in to follow this author
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