{
  "annotation_id": "b689dbc3-63dd-40f7-8643-172bb0c8e9a1",
  "date_created": "2026-03-02T18:01:14.574000Z",
  "date_modified": "2026-03-02T18:01:14.574000Z",
  "file_hash": "ed891ea28d6521c4f0ed66832da9acad636c71b30937b1fb9f50114e010d31e8",
  "private": false,
  "record": {
    "abstract": "We adapt continuous time random walk (CTRW) formalism to describe asset price\nevolution and discuss some of the problems that can be treated using this\napproach. We basically focus on two aspects: (i) the derivation of the price\ndistribution from high-frequency data, and (ii) the inverse problem, obtaining\ninformation on the market microstructure as reflected by high-frequency data\nknowing only the daily volatility. We apply the formalism to financial data to\nshow that the CTRW offers alternative tools to deal with several complex issues\nof financial markets.",
    "arxiv_id": "physics/0611138",
    "authors": [
      "J. Masoliver",
      "M. Montero",
      "J. Perello",
      "G. H. Weiss"
    ],
    "categories": [
      "physics.soc-ph",
      "q-fin.ST"
    ],
    "doi": "10.1016/j.jebo.2004.07.015",
    "journal_ref": "Journal of Economic Behaviour and Organization 61 (2006) 577-598.",
    "title": "The continuous time random walk formalism in financial markets",
    "url": "https://arxiv.org/abs/physics/0611138"
  },
  "schema_id": "dorsal/arxiv",
  "source": {
    "execution_id": "3202a4fd-ecde-4ab3-a121-fef724cbb23d",
    "id": "arXiv Dataset IDs",
    "type": "Model",
    "variant": "snapshot-2026-03-01",
    "version": "0.1.0"
  },
  "user_id": 1000002
}