AN INVERSE PROBLEM OF CALIBRATING VOLATILITY IN JUMP-DIFFUSION OPTION PRICING MODELS1

被引:0
|
作者
Jin, Chang [1 ]
Ma, Qing-Hua [1 ]
Xu, Zuo-Liang [1 ]
机构
[1] Renmin Univ China, Beijing 100872, Peoples R China
关键词
Gauss-Newton method; jump diffusion model; relative entropy; regularization; volatility;
D O I
10.1142/9789814327862_0009
中图分类号
O29 [应用数学];
学科分类号
070104 ;
摘要
This paper mainly concerns calibrating volatility from a jump diffusion model to a finite set of observed option pricing. We proposed a regularization algorithm based on Cont and Tankov's relative entropy regularization to solve this problem. We determine the regularization parameter using quasi-optimality criterion with original data error level unknown. Iteratively Guass-Newton method is developed for solving the unconstrained optimization problem. Finally, the theoretical results are illustrated by numerical experiments.
引用
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页码:102 / 112
页数:11
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