{
  "annotation_id": "1bd9c0d8-e71c-42d3-98f3-7381c9f7b386",
  "date_created": "2026-03-02T18:01:14.669000Z",
  "date_modified": "2026-03-02T18:01:14.669000Z",
  "file_hash": "56ab260c17c95604d15cfcf4622aa5d5b8c5fa7e3472dd9309f49e589ca2ed01",
  "private": false,
  "record": {
    "abstract": "Hedge Funds are considered as one of the portfolio management sectors which\nshows a fastest growing for the past decade. An optimal Hedge Fund management\nrequires an appropriate risk metrics. The classic CAPM theory and its Ratio\nSharpe fail to capture some crucial aspects due to the strong non-Gaussian\ncharacter of Hedge Funds statistics. A possible way out to this problem while\nkeeping the CAPM simplicity is the so-called Downside Risk analysis. One\nimportant benefit lies in distinguishing between good and bad returns, that is:\nreturns greater or lower than investor\u0027s goal. We revisit most popular Downside\nRisk indicators and provide new analytical results on them. We compute these\nmeasures by taking the Credit Suisse/Tremont Investable Hedge Fund Index Data\nand with the Gaussian case as a benchmark. In this way an unusual transversal\nlecture of the existing Downside Risk measures is provided.",
    "arxiv_id": "physics/0610162",
    "authors": [
      "Josep Perello"
    ],
    "categories": [
      "physics.soc-ph",
      "q-fin.RM"
    ],
    "doi": "10.1016/j.physa.2007.04.079",
    "journal_ref": "Physica 382 (2007) 213-218",
    "title": "Downside Risk analysis applied to Hedge Funds universe",
    "url": "https://arxiv.org/abs/physics/0610162"
  },
  "schema_id": "dorsal/arxiv",
  "source": {
    "execution_id": "3ef0e66d-4d1f-4377-afa4-630ac4055e11",
    "id": "arXiv Dataset IDs",
    "type": "Model",
    "variant": "snapshot-2026-03-01",
    "version": "0.1.0"
  },
  "user_id": 1000002
}