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
收藏
页码：627 / 646
页数：20
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