{
  "annotation_id": "3a784ead-00c1-4253-8d5a-3334a0e08a15",
  "date_created": "2026-03-02T18:01:11.493000Z",
  "date_modified": "2026-03-02T18:01:11.493000Z",
  "file_hash": "9e9c3318a11044f1b6ef9446101436755fae2beb7662fc31cb8472eadbb609ca",
  "private": false,
  "record": {
    "abstract": "We study the complexity of the stock market by constructing\n$\\epsilon$-machines of Standard and Poor\u0027s 500 index from February 1983 to\nApril 2006 and by measuring the statistical complexities. It is found that both\nthe statistical complexity and the number of causal states of constructed\n$\\epsilon$-machines have decreased for last twenty years and that the average\nmemory length needed to predict the future optimally has become shorter. These\nresults support that the information is delivered to the economic agents and\napplied to the market prices more rapidly in year 2006 than in year 1983.",
    "arxiv_id": "physics/0607283",
    "authors": [
      "Joongwoo Brian Park",
      "Jeong Won Lee",
      "Jae-Suk Yang",
      "Hang-Hyun Jo",
      "Hie-Tae Moon"
    ],
    "categories": [
      "physics.soc-ph"
    ],
    "doi": "10.1016/j.physa.2006.12.042",
    "title": "Complexity analysis of the stock market",
    "url": "https://arxiv.org/abs/physics/0607283"
  },
  "schema_id": "dorsal/arxiv",
  "source": {
    "execution_id": "bd14ea53-1a93-4177-a50d-de83aeee3b01",
    "id": "arXiv Dataset IDs",
    "type": "Model",
    "variant": "snapshot-2026-03-01",
    "version": "0.1.0"
  },
  "user_id": 1000002
}