The Sequential Empirical Process of Nonlinear Long-Range Dependent Random Vectors

2014/11/24 by Jannis Buchsteiner, Buchsteiner, Jannis
Economics, Econometrics and Finance · Mathematics · #FOS: Mathematics #Financial Risk and Volatility Modeling #Probability (math.PR) #Statistical Methods and Inference #Stochastic processes and financial applications

paper · pdf · doi:10.48550/arxiv.1411.6442

openalex publication_date 2014/11/24 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

Let (G(X_j))_j≥1 be a multivariate subordinated Gaussian process, which exhibits long-range dependence. We study the asymptotic behaviour of the corresponding sequential empirical process under two different types of subordination. The limiting process is either a product of a deterministic function and a Hermite process as in the one-dimensional case or a sum of various processes of this kind.

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