{
  "annotation_id": "c5b26846-efe2-4581-980e-9a094abee14d",
  "date_created": "2026-03-02T18:01:14.471000Z",
  "date_modified": "2026-03-02T18:01:14.471000Z",
  "file_hash": "107f445335d8ef2890acbbb68e297a9211aa58df4665bda073b13567bdcb15a5",
  "private": false,
  "record": {
    "abstract": "We present an experimental and simulated model of a multi-agent stock market\ndriven by a double auction order matching mechanism. Studying the effect of\ncumulative information on the performance of traders, we find a non monotonic\nrelationship of net returns of traders as a function of information levels,\nboth in the experiments and in the simulations. Particularly, averagely\ninformed traders perform worse than the non informed and only traders with high\nlevels of information (insiders) are able to beat the market. The simulations\nand the experiments reproduce many stylized facts of stock markets, such as\nfast decay of autocorrelation of returns, volatility clustering and fat-tailed\ndistribution of returns. These results have an important message for everyday\nlife. They can give a possible explanation why, on average, professional fund\nmanagers perform worse than the market index.",
    "arxiv_id": "physics/0610026",
    "authors": [
      "Bence Toth",
      "Enrico Scalas",
      "Juergen Huber",
      "Michael Kirchler"
    ],
    "categories": [
      "physics.soc-ph",
      "q-fin.TR"
    ],
    "doi": "10.1140/epjb/e2007-00046-2",
    "journal_ref": "Eur. Phys. J. B 55, 115-120 (2007)",
    "title": "The value of information in a multi-agent market model",
    "url": "https://arxiv.org/abs/physics/0610026"
  },
  "schema_id": "dorsal/arxiv",
  "source": {
    "execution_id": "f2dc5a86-c305-4402-b423-ff2fa18be077",
    "id": "arXiv Dataset IDs",
    "type": "Model",
    "variant": "snapshot-2026-03-01",
    "version": "0.1.0"
  },
  "user_id": 1000002
}