Stochastic maximum principle for partially observed forward-backward stochastic differential equations with jumps and regime switching

2018 ◽  
Vol 61 (7) ◽  
Author(s):  
Shuaiqi Zhang ◽  
Jie Xiong ◽  
Xiangdong Liu
Keyword(s):  
Maximum Principle ◽  
Differential Equations ◽  
Stochastic Differential Equations ◽  
Regime Switching ◽  
Backward Stochastic Differential Equations ◽  
Stochastic Maximum Principle ◽  
Partially Observed

scholarly journals Multi-valued backward stochastic differential equations with regime switching

2019 ◽  
Vol 2019 (1) ◽  
Author(s):  
Ruijuan Deng ◽  
Yong Ren
Keyword(s):  
Markov Chain ◽  
Differential Equations ◽  
Stochastic Differential Equations ◽  
Regime Switching ◽  
Original System ◽  
Backward Stochastic Differential Equations ◽  
Lower Semi ◽  
Finite State ◽  
Uniqueness Of The Solution ◽  
Continuous Convex Function

AbstractThe paper considers a class of multi-valued backward stochastic differential equations with subdifferential of a lower semi-continuous convex function with regime switching, whose generator is a continuous-time Markov chain with a finite state space. Firstly, we get the existence and uniqueness of the solution by the penalization method. Secondly, we prove that the solution of the original system is weakly convergent. Finally, we give an application to the homogenization of a class of multi-valued PDEs with Markov chain.

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