{
  "id": "1701.02814",
  "version": "v1",
  "published": "2017-01-11T00:06:08.000Z",
  "updated": "2017-01-11T00:06:08.000Z",
  "title": "Kelly betting on horse races with uncertainty in probability estimates",
  "authors": [
    "Michael R. Metel"
  ],
  "categories": [
    "math.OC"
  ],
  "abstract": "We investigate convex optimization models for Kelly betting on multiple outcome events, considering probability estimation uncertainty from multinomial logistic regression. An empirical study wagering on 15 seasons at Tokyo Racecourse was conducted to compare performance. The greatest returns were achieved using a robust optimization approach, which also resulted in a significant reduction in wagering compared to standard Kelly betting.",
  "revisions": [
    {
      "version": "v1",
      "updated": "2017-01-11T00:06:08.000Z"
    }
  ],
  "analyses": {
    "keywords": [
      "kelly betting",
      "probability estimates",
      "horse races",
      "robust optimization approach",
      "considering probability estimation uncertainty"
    ],
    "note": {
      "typesetting": "TeX",
      "pages": 0,
      "language": "en",
      "license": "arXiv",
      "status": "editable"
    }
  }
}