Stochastic differential games with inside information

被引：6
|
作者：
Draouil, Olfa [1 ]
Oksendal, Bernt [2 ]
机构：
[1] Univ Tunis El Manar, Dept Math, Tunis, Tunisia
[2] Univ Oslo, Dept Math, POB 1053 Blindern, N-0316 Oslo, Norway
来源：
INFINITE DIMENSIONAL ANALYSIS QUANTUM PROBABILITY AND RELATED TOPICS | 2016年 / 19卷 / 03期
关键词：
Optimal control; inside information; white noise; Hida-Malliavin calculus; Donsker delta functional; anticipative stochastic calculus; maximum principle; BSDE; optimal insider consumption and optimal insider portfolio under model uncertainty; DONSKER DELTA-FUNCTION; CALCULUS; INSIDER;
D O I：
10.1142/S0219025716500168
中图分类号：
O29 [应用数学];
学科分类号：
070104 ;
摘要：
We study stochastic differential games of jump diffusions, where the players have access to inside information. Our approach is based on anticipative stochastic calculus, white noise, Hida-Malliavin calculus, forward integrals and the Donsker delta functional. We obtain a characterization of Nash equilibria of such games in terms of the corresponding Hamiltonians. This is used to study applications to insider games in finance, specifically optimal insider consumption and optimal insider portfolio under model uncertainty.
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页数：31
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