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Subsampling the distribution of diverging statistics with applications to finance |
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| Authors: | Patrice Bertail Christian Haefke D.N.Dimitris N. Politis Halbert White |
| Affiliation: | a Laboratoire de Statistique, CREST, 3, Ave Pierre Larousse, 94205, Malakoff, France;b Department of Economics and Business, Universitat Pompeu Fabra, Ramon Trias Fargas 25–27, 08005, Barcelona, Spain;c Department of Mathematics, University of California at San Diego, La Jolla, CA 92093, USA;d Department of Economics, University of California at San Diego, La Jolla, CA 92093, USA |
| Abstract: | In this paper we propose a subsampling estimator for the distribution of statistics diverging at either known or unknown rates when the underlying time series is strictly stationary and strong mixing. Based on our results we provide a detailed discussion of 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 portfolio selection. |
| Keywords: | Resampling methods Extreme value statistics Value at Risk Portfolio selection |
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