Maximum Principles of Markov Regime-Switching Forward-Backward\n Stochastic Differential Equations with Jumps and Partial Information

2014/03/12 by Olivier Menoukeu Pamen, Pamen, Olivier Menoukeu · 2 citations
Economics, Econometrics and Finance · #Stochastic processes and financial applications #Climate Change Policy and Economics

paper · pdf · doi:10.48550/arxiv.1403.2901

Abstract

This paper presents three versions of maximum principle for a stochastic\noptimal control problem of Markov regime-switching forward-backward stochastic\ndifferential equations with jumps (FBSDEJs). A general sufficient maximum\nprinciple for optimal control for a system driven by a Markov regime-switching\nforward and backward jump-diffusion model is developed. After, an equivalent\nmaximum principle is proved. Malliavin calculus is also employed to derive a\ngeneral stochastic maximum principle. The latter does not require concavity of\nHamiltonian. Applications of the stochastic maximum principle to non-concave\nHamiltonian and recursive utility maximization is also discussed.\n

Cited by

• A stochastic maximum principle for singular mean-field regime-switching optimal control
• An infinite horizon sufficient stochastic maximum principle for regime switching diffusions and applications

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