A Subsampling Approach to Estimating the Distribution of Diversing Statistics with Application to Assessing Financial Market Risks
Dimitris N. Politis
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.
Resampling methods, extreme value statistics, value at risk, portofolio selection
In order to set up a list of libraries that you have access to,
you must first login
or sign up.
Then set up a personal list of libraries from your profile page by
clicking on your user name at the top right of any screen.