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On the Appropriateness of Inappropriate VaR Models

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  • Wolfgang Härdle
  • Zdenek Hlavka
  • Gerhard Stahl

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

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