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A subsampling approach to estimating the distribution of diversing statistics with application to assessing financial market risks

  • Patrice Bertail
  • Christian Haefke
  • Dimitris N. Politis
  • Halbert White

In this paper we propose a subsampling estimator for the distribution of statistics diverging at either known rates when the underlying time series in strictly stationary abd strong mixing. Based on our results we provide a detailed discussion how to estimate extreme order statistics with dependent data and present two applications to assessing financial market risk. Our method performs well in estimating Value at Risk and provides a superior alternative to Hill's estimator in operationalizing Safety First portofolio selection.

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File URL: http://www.econ.upf.edu/docs/papers/downloads/599.pdf
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Paper provided by Department of Economics and Business, Universitat Pompeu Fabra in its series Economics Working Papers with number 599.

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Date of creation: Dec 2001
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Handle: RePEc:upf:upfgen:599
Contact details of provider: Web page: http://www.econ.upf.edu/

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