Simulation and inference for stochastic volatility models driven by Levy processes

被引：18

作者：

Gander, Matthew P. S. ^{[1
]}

Stephens, David A.

机构：

[1] Univ London Imperial Coll Sci Technol & Med, Dept Math, London SW7 2AZ, England

[2] McGill Univ, Dept Math & Stat, Montreal, PQ H3A 2K6, Canada

来源：

BIOMETRIKA | 2007年 / 94卷 / 03期

关键词：

fractional; long-memory; ornstein-uhlenbeck process; power decay process; volatility;

D O I：

10.1093/biomet/asm048

中图分类号：

Q [生物科学];

学科分类号：

07 ; 0710 ; 09 ;

摘要：

We study Ornstein-Uhlenbeck stochastic processes driven by Levy processes, and extend them to more general non-Ornstein-Uhlenbeck models. In particular, we investigate the means of making the correlation structure in the volatility process more flexible. For one model, we implement a method for introducing quasi long-memory into the volatility model. We demonstrate that the models can be fitted to real share price returns data.

引用

页码：627 / 646

页数：20

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