{
  "id": "1210.0371",
  "version": "v3",
  "published": "2012-10-01T12:27:06.000Z",
  "updated": "2013-09-14T22:51:48.000Z",
  "title": "Weak Necessary and Sufficient Stochastic Maximum Principle for Markovian Regime-Switching Diffusion Models",
  "authors": [
    "Yusong Li",
    "Harry Zheng"
  ],
  "comment": "30 pages",
  "categories": [
    "math.OC"
  ],
  "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.",
  "revisions": [
    {
      "version": "v3",
      "updated": "2013-09-14T22:51:48.000Z"
    }
  ],
  "analyses": {
    "subjects": [
      "93E20",
      "49J52"
    ],
    "keywords": [
      "sufficient stochastic maximum principle",
      "markovian regime-switching diffusion models",
      "weak necessary",
      "stochastic optimal control problems",
      "switching stochastic optimal control"
    ],
    "note": {
      "typesetting": "TeX",
      "pages": 30,
      "language": "en",
      "license": "arXiv",
      "status": "editable",
      "adsabs": "2012arXiv1210.0371L"
    }
  }
}