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On the Appropriateness of Inappropriate VaR Models

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Author Info
Wolfgang Härdle
Zdenek Hlavka
Gerhard Stahl

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Abstract

The Value-at-Risk calculation reduces the dimensionality of the risk factor space. The main reasons for such simplifications are, e.g., technical efficiency, the logic and statistical appropriateness of the model. In Chapter 2 we present three simple mappings: the mapping on the market index, the principal components model and the model with equally correlated risk factors. The comparison of these models in Chapter 3 is based on the literatere on the verification of weather forecasts (Murphy and Winkler 1992, Murphy 1997). Some considerations on the quantitative analysis are presented in the fourth chapter. In the last chapter, we present empirical analysis of the DAX data using XploRe.

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Publisher Info
Paper provided by Sonderforschungsbereich 649, Humboldt University, Berlin, Germany in its series SFB 649 Discussion Papers with number SFB649DP2006-003.

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Length: 26 pages
Date of creation: Jan 2006
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Handle: RePEc:hum:wpaper:sfb649dp2006-003

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Related research
Keywords: Value-at-Risk; market index model; principal components; random effects model; probability forecast;

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Find related papers by JEL classification:
C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation and Testing
G20 - Financial Economics - - Financial Institutions and Services - - - General

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  1. Murphy, Allan H. & Winkler, Robert L., 1992. "Diagnostic verification of probability forecasts," International Journal of Forecasting, Elsevier, vol. 7(4), pages 435-455, March. [Downloadable!] (restricted)
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