{
  "id": "1711.09833",
  "version": "v1",
  "published": "2017-11-27T17:05:12.000Z",
  "updated": "2017-11-27T17:05:12.000Z",
  "title": "A Boolean-valued model approach to conditional risk",
  "authors": [
    "José Miguel Zapata"
  ],
  "categories": [
    "math.FA"
  ],
  "abstract": "Based on Boolean-valued models we provide a method to interpret a theorem of representation of convex risk measures as a theorem for conditional risk measures which also holds thanks to transfer principle of Boolean-valued models. In particular, we establish a general robust representation theorem for conditional risk measures.",
  "revisions": [
    {
      "version": "v1",
      "updated": "2017-11-27T17:05:12.000Z"
    }
  ],
  "analyses": {
    "subjects": [
      "03C90",
      "46H25",
      "91B30"
    ],
    "keywords": [
      "boolean-valued model approach",
      "conditional risk measures",
      "general robust representation theorem",
      "convex risk measures",
      "holds thanks"
    ],
    "note": {
      "typesetting": "TeX",
      "pages": 0,
      "language": "en",
      "license": "arXiv",
      "status": "editable"
    }
  }
}