A Subsampling Approach to Estimating The Distribution of Diverging Statistics with Applications to Assessing Financial Market Risk

Patrice Bertail, Christian Haefke, D N Politis and Halbert White

University of California at San Diego, Economics Working Paper Series from Department of Economics, UC San Diego

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 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 (search for similar items in EconPapers)
Date: 2000-01-01
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Working Paper: A Subsampling Approach to Estimating the Distribution of Diverging Statistics with Applications to Assessing Financial Markets Risks (2002)
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