DPOT Methodology: An Application to Value-at-Risk

Chapter
Part of the Studies in Theoretical and Applied Statistics book series (STAS)

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, a model-based approach within the POT framework, which uses the durations between excesses as covariates, is presented. Based on this approach we suggest models to forecast one-day-ahead Value-at-Risk and apply these models to the Standard & Poor’s 500 Index. Out of sample results provide evidence that they can perform better than state-of-the art risk models.

Keywords

Generalize Pareto Distribution Independence Test Financial Time Series Extreme Value Theory Interval Forecast 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgements

This research was partially supported by National Funds through FCT - Fundação para a Ciência e a Tecnologia, FCT//PTDC/MAT/101736/2008, EXTREMA project.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  1. 1.Faculdade de Ciências, Departamento de Estatística e Investigação OperacionalUniversidade de LisboaLisboaPortugal
  2. 2.Instituto Politécnico de Santarém, Departamento de Informática e Métodos QuantitativosEscola Superior de Gestão e TecnologiaSantarémPortugal

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