Almost sure limit theorems for the maxima of stochastic volatility models

被引：1

作者：

Xiao, Jinghong ^{[1
]}

Tan, Zhongquan ^{[1
]}

机构：

[1] Jiaxing Univ, Coll Math Phys & Informat Engn, Jiaxing, Peoples R China

来源：

STOCHASTICS-AN INTERNATIONAL JOURNAL OF PROBABILITY AND STOCHASTIC PROCESSES | 2021年 / 93卷 / 04期

基金：

中国国家自然科学基金;

关键词：

Almost sure limit theorem; maxima; stationary Gaussian sequences; stochastic volatility models; CONVERGENCE;

D O I：

10.1080/17442508.2020.1755287

中图分类号：

O29 [应用数学];

学科分类号：

070104 ;

摘要：

In this paper, we proved the almost sure limit theorems for the maxima of stochastic volatility models with both light-tailed and heavy-tailed noises, where the volatility sequence is a log-Gaussian linear process. For the light-tailed noise case, we assume that the autocorrelation function of the Gaussian linear process satisfies for some . For the heavy-tailed noise case, we assume that the Gaussian linear process is strong mixing with mixing rate satisfying for some epsilon > 0.

引用

页码：513 / 527

页数：15

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