Large deviations for affine diffusion processes on R+m x Rn

被引:3
|
作者
Kang, Wanmo [1 ]
Kang, Chulmin [2 ]
机构
[1] Korea Adv Inst Sci & Technol, Dept Math Sci, Taejon, South Korea
[2] Natl Inst Math Sci, Taejon, South Korea
基金
新加坡国家研究基金会;
关键词
Large deviation principles; Affine processes; Affine transform formula; STOCHASTIC VOLATILITY; TERM STRUCTURE; OPTIONS;
D O I
10.1016/j.spa.2014.02.002
中图分类号
O21 [概率论与数理统计]; C8 [统计学];
学科分类号
020208 ; 070103 ; 0714 ;
摘要
This paper proves the large deviation principle for affine diffusion processes with initial values in the interior of the state space R-+(m) x R-n. We approach this problem in two different ways. In the first approach, we first prove the large deviation principle for finite dimensional distributions, and then use it to establish the sample path large deviation principle. For this approach, a more careful examination of the affine transform formula is required. The second approach exploits the exponential martingale method of Donati-Martin et al. for the squares of Ornstein-Uhlenbeck processes. We provide an application to importance sampling of affine diffusion models. (C) 2014 Elsevier B.V. All rights reserved.
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页码:2188 / 2227
页数:40
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