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Risk quantification in turmoil markets

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Abstract

The aim of this paper is to examine the performance of the Value-at-Risk measure under different distributional models in the highly demanding context of the recent financial crisis. This task is one of the main challenges of the financial industry. In addition to the normal and Student’s t distributions, we analyze three distributions especially appropriate for capturing tail risk: the generalized Pareto distribution (GPD), the α-stable distribution, and the g-and-h distribution. We also address the problem of efficiently estimating the parameters of these distributions. Our backtesting analysis shows that GPD and α-stable distributions perform well for this risk measurement purpose.

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Acknowledgements

This work was supported by the Spanish Ministerio de Ciencia e Innovación (ECO2014-59664-P), Spanish Ministerio de Economía y Competitividad (MTM2016-77501-P), Junta de Comunidades de Castilla-La Mancha (PEII-2014-019-P) and FAPA-Uniandes (P16.100322.001). Any errors are solely the responsibility of the authors.

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Authors and Affiliations

  1. Department of Economics and Finance, Universidad de Castilla-La Mancha, Plaza de la Universidad 1., 02071, Albacete, Spain

    Antonio Díaz

  2. Department of Economics and Finance and Instituto de Desarrollo Regional, Universidad de Castilla-La Mancha, Plaza de la Universidad 1., 02071, Albacete, Spain

    Gonzalo García-Donato

  3. School of Management, Universidad de los Andes, Calle 21 No. 1-20, Bogotá, Colombia

    Andrés Mora-Valencia

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  1. Antonio Díaz
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Correspondence to Antonio Díaz.

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Díaz, A., García-Donato, G. & Mora-Valencia, A. Risk quantification in turmoil markets. Risk Manag 19, 202–224 (2017). https://doi.org/10.1057/s41283-017-0018-8

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