完全复制Backtesting Value-at-Risk A GMM Duration-based Test的matlab代码

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完全复制Backtesting Value-at-Risk A GMM Duration-based Test的matlab代码

是进行VaR测试、风险管理建模、金融计量方面的极好材料，改一改数据就可以发表一篇高质量的论文了。



Bertrand Candelon,  Gilbert Colletaz,  Christophe Hurlin,   Sessi Tokpavi
  
Abstract

This paper proposes a new duration-based backtesting procedure for value-at-risk (VaR) forecasts. The GMM test framework proposed by Bontemps (2006) to test for the distributional assumption (i.e., the geometric distribution) is applied to the case of the VaR forecasts validity. Using simple J-statistic based on the moments defined by the orthonormal polynomials associated with the geometric distribution, this new approach tackles most of the drawbacks usually associated to duration-based backtesting procedures. An empirical application for Nasdaq returns confirms that using GMM test leads to major consequences for the expost evaluation of the risk by regulation authorities.
JEL: C22, C52, G28





Backtesting Value-at-Risk A GMM Duration-based Test.zip (15.95 KB, 需要: RMB 9 元) 本附件包括：

• Appel_GMM.m
• data_GMM_HS.xls
• Duree.m
• RunMyCode_GMM.m
• TDA_Geometric.m
• TDA_Geometric_IND.m

2017-11-28 19:15:45 上传

需要: RMB 9 元  [购买]

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