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A detailed comparison of value at risk estimates

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  • Abad, Pilar
  • Benito, Sonia

Abstract

This work investigates the performance of different models of value at risk. We include several methods (parametric, historical simulation, Monte Carlo, and extreme value theory) and some models to compute the conditional variance. We analyze several international stock indexes and examine two types of periods: stable and volatile periods. To choose the best model, we employ a two-stage selection approach. The result indicates that the best model is a parametric model with conditional variance estimated by an asymmetric GARCH model under Student's t-distribution of returns. This paper shows that parametric models can obtain successful VaR measures if conditional variance is estimated properly.

Suggested Citation

  • Abad, Pilar & Benito, Sonia, 2013. "A detailed comparison of value at risk estimates," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 94(C), pages 258-276.
  • Handle: RePEc:eee:matcom:v:94:y:2013:i:c:p:258-276
    DOI: 10.1016/j.matcom.2012.05.011
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    References listed on IDEAS

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    Cited by:

    1. Chia-Lin Chang & David E. Allen & Michael McAleer & Ju-Ting Tang & Teodosio Pérez Amaral, 2013. "Risk Modelling and Management: An Overview," Documentos de Trabajo del ICAE 2013-22, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
    2. repec:eee:ecosta:v:8:y:2018:i:c:p:56-77 is not listed on IDEAS
    3. repec:eee:revfin:v:34:y:2017:i:c:p:86-98 is not listed on IDEAS
    4. Pilar Abad Romero & Sonia Benito Muela & Miguel Angel Sánchez Granero & Carmen López, 2013. "Evaluating the performance of the skewed distributions to forecast Value at Risk in the Global Financial Crisis," Documentos de Trabajo del ICAE 2013-40, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.

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