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Forecasting Value-at-Risk with a duration-based POT method

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  • Araújo Santos, P.
  • Fraga Alves, M.I.

Abstract

Threshold methods, based on fitting a stochastic model to the excesses over a threshold, were developed under the acronym POT (peaks over threshold). To eliminate the tendency to clustering of violations, we propose a model-based approach within the POT framework that uses the durations between excesses as covariates. Based on this approach we suggest models for forecasting one-day-ahead Value-at-Risk. A simulation study was performed to validate the estimation procedure. Comparative studies with global stock market indices provide evidence that the proposed models can perform better than state-of-the art risk models and better than the widely used RiskMetrics model in terms of unconditional coverage, clustering of violations and capital requirements under the Basel II Accord.

Suggested Citation

  • Araújo Santos, P. & Fraga Alves, M.I., 2013. "Forecasting Value-at-Risk with a duration-based POT method," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 94(C), pages 295-309.
    • Handle: RePEc:eee:matcom:v:94:y:2013:i:c:p:295-309
    DOI: 10.1016/j.matcom.2012.07.016
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    Cited by:

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    6. Reboredo, Juan C. & Ugando, Mikel, 2015. "Downside risks in EU carbon and fossil fuel markets," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 111(C), pages 17-35.
    7. Marco Bee & Luca Trapin, 2018. "Estimating and Forecasting Conditional Risk Measures with Extreme Value Theory: A Review," Risks, MDPI, vol. 6(2), pages 1-16, April.

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