Subsampling the mean of heavy-tailed dependent observations
Piotr Kokoszka and
Michael Wolf ()
Economics Working Papers from Department of Economics and Business, Universitat Pompeu Fabra
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 (search for similar items in EconPapers)
JEL-codes: C10 C14 C32 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-ecm, nep-ets, nep-ias and nep-pke
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Persistent link: https://EconPapers.repec.org/RePEc:upf:upfgen:600
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