Subsampling the mean of heavy-tailed dependent observations
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.
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- McElroy, Tucker & Politis, Dimitris N., 2002. "Robust Inference For The Mean In The Presence Of Serial Correlation And Heavy-Tailed Distributions," Econometric Theory, Cambridge University Press, vol. 18(05), pages 1019-1039, October.
- Carrasco, Marine & Chen, Xiaohong, 2002. "Mixing And Moment Properties Of Various Garch And Stochastic Volatility Models," Econometric Theory, Cambridge University Press, vol. 18(01), pages 17-39, February.
- Cline, Daren B. H. & Brockwell, Peter J., 1985. "Linear prediction of ARMA processes with infinite variance," Stochastic Processes and their Applications, Elsevier, vol. 19(2), pages 281-296, April.
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