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Subsampling the Mean of Heavy-tailed Dependent Observations


Piotr Kokoszka


Utah State University - Department of Mathematics & Statistics

Michael Wolf


University of Zurich - Department of Economics Library; University of Zurich - Department of Eonomics

Journal of Time Series Analysis, Vol. 25, No. 2, pp. 217-234, March 2004

Abstract:     
We establish the validity of subsampling confidence intervals for the mean of a dependent series with heavy-tailed marginal distributions. Using point process theory, we focus on GARCH-like time series models. We propose a data-dependent method for the optimal block size selection and investigate its performance by means of a simulation study.

Number of Pages in PDF File: 18

Keywords: Estimation of the mean, heavy tails, GARCH, subsampling

Accepted Paper Series


Date posted: April 24, 2004  

Suggested Citation

Kokoszka, Piotr and Wolf, Michael, Subsampling the Mean of Heavy-tailed Dependent Observations. Journal of Time Series Analysis, Vol. 25, No. 2, pp. 217-234, March 2004. Available at SSRN: http://ssrn.com/abstract=513721

Contact Information

Piotr Kokoszka (Contact Author)
Utah State University - Department of Mathematics & Statistics ( email )
3900 Old Main Hill
Logan, UT 84322-3530
United States
435-797-0746 (Phone)
435-797-1822 (Fax)
HOME PAGE: http://www.math.usu.edu/~piotr/
Michael Wolf
University of Zurich - Department of Economics Library ( email )
Rämistrasse 71
Zurich, 8006
Switzerland
University of Zurich - Department of Eonomics ( email )
Wilfriedstrasse 6
Zurich, CH-8032
Switzerland
Feedback to SSRN (Beta)


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