{
  "id": "1407.3256",
  "version": "v1",
  "published": "2014-07-11T19:19:03.000Z",
  "updated": "2014-07-11T19:19:03.000Z",
  "title": "Sufficient stochastic maximum principle for the optimal control of semi-Markov modulated jump-diffusion with application to Financial optimization",
  "authors": [
    "Amogh Deshpande"
  ],
  "comment": "Forthcoming in Stochastic Analysis and Applications",
  "categories": [
    "math.OC"
  ],
  "abstract": "The finite state semi-Markov process is a generalization over the Markov chain in which the sojourn time distribution is any general distribution. In this article we provide a sufficient stochastic maximum principle for the optimal control of a semi-Markov modulated jump-diffusion process in which the drift, diffusion and the jump kernel of the jump-diffusion process is modulated by a semi-Markov process. We also connect the sufficient stochastic maximum principle with the dynamic programming equation. We apply our results to finite horizon risk-sensitive control portfolio optimization problem and to a quadratic loss minimization problem.",
  "revisions": [
    {
      "version": "v1",
      "updated": "2014-07-11T19:19:03.000Z"
    }
  ],
  "analyses": {
    "keywords": [
      "sufficient stochastic maximum principle",
      "semi-markov modulated jump-diffusion",
      "optimal control",
      "financial optimization",
      "control portfolio optimization problem"
    ],
    "note": {
      "typesetting": "TeX",
      "pages": 0,
      "language": "en",
      "license": "arXiv",
      "status": "editable",
      "adsabs": "2014arXiv1407.3256D"
    }
  }
}