Subsampling the Mean of Heavy-Tailed Dependent Observations
UPF Economics and Business Working Paper No. 600
Posted: 4 Oct 2002
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 study both linear and nonlinear 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.
Keywords: Heavy tails, linear time series, subsampling
JEL Classification: C10, C14, C32
Suggested Citation: Suggested Citation
Kokoszka, Piotr and Wolf, Michael, Subsampling the Mean of Heavy-Tailed Dependent Observations. UPF Economics and Business Working Paper No. 600, Available at SSRN: https://ssrn.com/abstract=311579
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