Weak Necessary and Sufficient Stochastic Maximum Principle for Markovian Regime-Switching Diffusion Models

Yusong Li; Harry Zheng

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arXiv · 1210.0371

Weak Necessary and Sufficient Stochastic Maximum Principle for Markovian Regime-Switching Diffusion Models

Yusong Li·Harry Zheng

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Abstract

In this paper we prove a weak necessary and sufficient maximum principle for Markovian regime switching stochastic optimal control problems. Instead of insisting on the maximum condition of the Hamiltonian, we show that 0 belongs to the sum of Clarke's generalized gradient of the Hamiltonian and Clarke's normal cone of the control constraint set at the optimal control. Under a joint concavity condition on the Hamiltonian and a convexity condition on the terminal objective function, the necessary condition becomes sufficient. We give four examples to demonstrate the weak stochastic maximum principle.

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BibTeX RIS

Yusong Li, Harry Zheng. 2013-09-14. Weak Necessary and Sufficient Stochastic Maximum Principle for Markovian Regime-Switching Diffusion Models. https://arxiv.org/abs/1210.0371

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