{
  "id": "1307.2218",
  "version": "v1",
  "published": "2013-07-08T19:49:06.000Z",
  "updated": "2013-07-08T19:49:06.000Z",
  "title": "Importance sampling for jump processes and applications to finance",
  "authors": [
    "Laetitia Badouraly Kassim",
    "Jérôme Lelong",
    "Imane Loumrhari"
  ],
  "categories": [
    "math.PR",
    "q-fin.CP",
    "q-fin.PR"
  ],
  "abstract": "Adaptive importance sampling techniques are widely known for the Gaussian setting of Brownian driven diffusions. In this work, we want to extend them to jump processes. Our approach relies on a change of the jump intensity combined with the standard exponential tilting for the Brownian motion. The free parameters of our framework are optimized using sample average approximation techniques. We illustrate the efficiency of our method on the valuation of financial derivatives in several jump models.",
  "revisions": [
    {
      "version": "v1",
      "updated": "2013-07-08T19:49:06.000Z"
    }
  ],
  "analyses": {
    "keywords": [
      "jump processes",
      "applications",
      "sample average approximation techniques",
      "brownian driven diffusions",
      "jump models"
    ],
    "note": {
      "typesetting": "TeX",
      "pages": 0,
      "language": "en",
      "license": "arXiv",
      "status": "editable",
      "adsabs": "2013arXiv1307.2218B"
    }
  }
}