{
  "annotation_id": "d840becb-3246-4f70-9cc2-f58225d0ee92",
  "date_created": "2026-03-02T18:01:06.617000Z",
  "date_modified": "2026-03-02T18:01:06.617000Z",
  "file_hash": "b4d786aa89fd59ad70532a910879bd143f1ac958058583d051b08bdbbf4b7c32",
  "private": false,
  "record": {
    "abstract": "We apply the concept of free random variables to doubly correlated (Gaussian)\nWishart random matrix models, appearing for example in a multivariate analysis\nof financial time series, and displaying both inter-asset cross-covariances and\ntemporal auto-covariances. We give a comprehensive introduction to the rich\nfinancial reality behind such models. We explain in an elementary way the main\ntechniques of the free random variables calculus, with a view to promote them\nin the quantitative finance community. We apply our findings to tackle several\nfinancially relevant problems, such as of an universe of assets displaying\nexponentially decaying temporal covariances, or the exponentially weighted\nmoving average, both with an arbitrary structure of cross-covariances.",
    "arxiv_id": "physics/0603024",
    "authors": [
      "Z. Burda",
      "A. Jarosz",
      "J. Jurkiewicz",
      "M. A. Nowak",
      "G. Papp",
      "I. Zahed"
    ],
    "categories": [
      "physics.soc-ph",
      "cond-mat.stat-mech",
      "math-ph",
      "math.MP"
    ],
    "license": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
    "title": "Applying Free Random Variables to Random Matrix Analysis of Financial   Data. Part I: A Gaussian Case",
    "url": "https://arxiv.org/abs/physics/0603024"
  },
  "schema_id": "dorsal/arxiv",
  "source": {
    "execution_id": "a1fff8b0-71a7-4c0e-adf9-62dae1b8a18e",
    "id": "arXiv Dataset IDs",
    "type": "Model",
    "variant": "snapshot-2026-03-01",
    "version": "0.1.0"
  },
  "user_id": 1000002
}