A maximum principle for stochastic differential games with g-expectations and partial information

DOI10.1080/17442508.2010.532875zbMath1251.93137OpenAlexW2007710820MaRDI QIDQ4648579

Ta Thi Kieu An, Bernt Øksendal

Publication date: 9 November 2012

Published in: Stochastics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/17442508.2010.532875

zbMATH Keywords

stochastic control\(g\)-expectationstochastic differential gameforward-backward stochastic differential equationsjump diffusionsufficient maximum principle

Mathematics Subject Classification ID

Processes with independent increments; Lévy processes (60G51) Differential games (aspects of game theory) (91A23) Optimal stochastic control (93E20) Applications of stochastic analysis (to PDEs, etc.) (60H30) Financial applications of other theories (91G80) Stochastic games, stochastic differential games (91A15) Stochastic calculus of variations and the Malliavin calculus (60H07) Optimality conditions for problems involving randomness (49K45) Stochastic integral equations (60H20)

Related Items (7)

Maximum principle via Malliavin calculus for regular-singular stochastic differential games ⋮ Linear-quadratic partially observed forward-backward stochastic differential games and its application in finance ⋮ Non-zero sum differential games of anticipated forward-backward stochastic differential delayed equations under partial information and application ⋮ Nonzero sum differential game of mean-field BSDEs with jumps under partial information ⋮ Forward-backward stochastic differential games and stochastic control under model uncertainty ⋮ Mean-field type forward-backward doubly stochastic differential equations and related stochastic differential games ⋮ Stochastic maximum principle, dynamic programming principle, and their relationship for fully coupled forward-backward stochastic controlled systems

Cites Work

• Maximum principle for stochastic differential games with partial information
• Convex measures of risk and trading constraints
• Maximum Principles for Optimal Control of Forward-Backward Stochastic Differential Equations with Jumps
• Financial Modelling with Jump Processes

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