Subsampling the mean of heavy-tailed dependent observations
نویسندگان
چکیده
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. JEL CLASSIFICATION NOS: C10, C14, C32.
منابع مشابه
Inference for the mean in the heavy-tailed case
In this article, asymptotic inference for the mean of i.i.d. observations in the context of heavy-tailed distributions is discussed. While both the standard asymptotic method based on the normal approximation and Efron's bootstrap are inconsistent when the underlying distribution does not possess a second moment, we propose two approaches based on the subsampling idea of Politis and Romano (199...
متن کاملSubsampling Inference for the Mean of Heavy-tailed Long Memory Time Series
In this paper we revisit a time series model introduced by McElroy and Politis (2007a) and generalize it in several ways to encompass a wider class of stationary, nonlinear, heavy-tailed time series with long memory. The joint asymptotic distribution for the sample mean and sample variance under the extended model is derived; the associated convergence rates are found to depend crucially on the...
متن کاملEstimation of confidence intervals for the mean of heavy tailed loss distributions: a comparative study using a simulation method
This paper uses nonparametric methods to estimate the confidence intervals for the mean of asymmetric heavy tailed loss distributions. The nonparametric methods employed are the m out of n bootstrap, subsampling bootstrap, refined bootstrap, empirical likelihood ratio method, and bootstrap calibrated empirical likelihood methods. We evaluate the accuracy and compare the performance of the confi...
متن کاملRatio Tests for Persistence Change with Heavy Tailed Observations
This paper considers how to detect structural change in persistence between (0) I and (1) I behaviour with innovations in the domain of attraction of a -stable law. Conventional ratio-based tests developed in Kim [J. Econ. 95(2000)] are unreliable in the presence of such behavior, having non-pivotal asymptotic null distributions. In this paper we propose a subsampling approach to ratiobased t...
متن کاملAsymptotic Behavior of Weighted Sums of Weakly Negative Dependent Random Variables
Let be a sequence of weakly negative dependent (denoted by, WND) random variables with common distribution function F and let be other sequence of positive random variables independent of and for some and for all . In this paper, we study the asymptotic behavior of the tail probabilities of the maximum, weighted sums, randomly weighted sums and randomly indexed weighted sums of heavy...
متن کامل