{
  "annotation_id": "01d0fdaa-ecba-4468-84aa-280c0c1c17bd",
  "date_created": "2026-03-02T18:00:57.392000Z",
  "date_modified": "2026-03-02T18:00:57.392000Z",
  "file_hash": "ac4a889d57d165427081ae26f32747774b7b3a5c18888ab47a586602b166401b",
  "private": false,
  "record": {
    "abstract": "The definition of time is still an open question when one deals with high\nfrequency time series. If time is simply the calendar time, prices can be\nmodeled as continuous random processes and values resulting from transactions\nor given quotes are discrete samples of this underlying dynamics. On the\ncontrary, if one takes the business time point of view, price dynamics is a\ndiscrete random process, and time is simply the ordering according which prices\nare quoted in the market. In this paper we suggest that the business time\napproach is perhaps a better way of modeling price dynamics than calendar time.\nThis conclusion comes out from testing probability densities and conditional\nvariances predicted by the two models against the experimental ones. The data\nset we use contains the DEM/USD exchange quotes provided to us by Olsen \u0026\nAssociates during a period of one year from January to December 1998. In this\nperiod 1,620,843 quotes entries in the EFX system were recorded.",
    "arxiv_id": "physics/0504100",
    "authors": [
      "Luca Berardi",
      "Maurizio Serva"
    ],
    "categories": [
      "physics.soc-ph",
      "cond-mat.other",
      "q-fin.ST"
    ],
    "doi": "10.1016/j.physa.2005.01.049",
    "title": "Time and foreign exchange markets",
    "url": "https://arxiv.org/abs/physics/0504100"
  },
  "schema_id": "dorsal/arxiv",
  "source": {
    "execution_id": "d03b1730-3163-4341-ba68-40da38a165a7",
    "id": "arXiv Dataset IDs",
    "type": "Model",
    "variant": "snapshot-2026-03-01",
    "version": "0.1.0"
  },
  "user_id": 1000002
}