Weak Necessary and Sufficient Stochastic Maximum Principle for Markovian Regime-Switching Diffusion Models
Journal Article
·
· Applied Mathematics and Optimization
- Imperial College, Department of Mathematics (United Kingdom)
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.
- OSTI ID:
- 22722873
- Journal Information:
- Applied Mathematics and Optimization, Journal Name: Applied Mathematics and Optimization Journal Issue: 1 Vol. 71; ISSN 0095-4616
- Country of Publication:
- United States
- Language:
- English
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