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Extremal Quantiles, Value-at-Risk, Quasi-PORT and DPOT

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New Advances in Statistical Modeling and Applications

Part of the book series: Studies in Theoretical and Applied Statistics ((STASSPSS))

Abstract

Under the context of high quantiles, Value-at-Risk (VaR) models based on the PORT Hill estimator, VaR models based on the DPOT method and other unconditional and conditional models are compared through a out-of-sample accuracy study. To obtain a reasonable number of violations for backtesting, the log returns have been used from the Down Jones Industrial Average index, which constitutes a financial time series with a very large data size.

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Acknowledgments

Research partially supported by National Funds through FCT—Fundação para a Ciência e a Tecnologia, FCT/PROTEC, project PEst-OE/MAT/UI0006/2011, and FCT/PTDC/MAT/101736/2008, EXTREMA project.

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Authors and Affiliations

  1. Departamento de Informática e Métodos Quantitativos, Escola Superior de Gestão e Tecnologia, Instituto Politécnico de Santarém, Complexo Andaluz, Apartado 295, 2001-904, Santarém, Portugal

    P. Araújo Santos

  2. Faculdade de Ciências, Departamento de Estatística e Investigação Operacional, Universidade de Lisboa, Campo Grande, 1749-016, Lisboa, Portugal

    M. I. Fraga Alves

Authors
  1. P. Araújo Santos
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  2. M. I. Fraga Alves
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Corresponding author

Correspondence to P. Araújo Santos .

Editor information

Editors and Affiliations

  1. CEMAT and Departamento de Matemática, Instituto Superior Técnico, Universidade de Lisboa, Lisboa, Portugal

    António Pacheco

  2. CEAUL and School of Technology and Management, Polytechnic Institute of Leiria, Leiria, Portugal

    Rui Santos

  3. CEMAT and Departamento de Matemática, Instituto Superior Técnico, Universidade de Lisboa, Lisboa, Portugal

    Maria do Rosário Oliveira

  4. CEAUL and Departamento de Matemática, Instituto Superior Técnico, Universidade de Lisboa, Lisboa, Portugal

    Carlos Daniel Paulino

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Santos, P.A., Alves, M.I.F. (2014). Extremal Quantiles, Value-at-Risk, Quasi-PORT and DPOT. In: Pacheco, A., Santos, R., Oliveira, M., Paulino, C. (eds) New Advances in Statistical Modeling and Applications. Studies in Theoretical and Applied Statistics(). Springer, Cham. https://doi.org/10.1007/978-3-319-05323-3_15

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