{
  "annotation_id": "5c814e8d-bfb3-47a1-8f99-2c27470d56db",
  "date_created": "2026-03-02T18:01:14.003000Z",
  "date_modified": "2026-03-02T18:01:14.003000Z",
  "file_hash": "0c5a18cc8128dc960079b6740956d5b4c1fe52fe91735d428e444238d60b1683",
  "private": false,
  "record": {
    "abstract": "Volatility dynamics of wavelet - filtered stock price time series is studied.\nUsing the universal thresholding method of wavelet filtering and a principle of\nminimal linear autocorrelation of noise component we find that the quantitative\ncharacteristics of volatility dynamics of denoised series are noticeably\ndifferent from those of the raw data and the noise.",
    "arxiv_id": "physics/0612170",
    "authors": [
      "I. M. Dremin",
      "A. V. Leonidov"
    ],
    "categories": [
      "physics.soc-ph",
      "q-fin.ST"
    ],
    "title": "Volatility Dynamics of Wavelet-Filtered Stock Prices",
    "url": "https://arxiv.org/abs/physics/0612170"
  },
  "schema_id": "dorsal/arxiv",
  "source": {
    "execution_id": "1c86e882-9863-49bb-b1a4-c77a26f5ee16",
    "id": "arXiv Dataset IDs",
    "type": "Model",
    "variant": "snapshot-2026-03-01",
    "version": "0.1.0"
  },
  "user_id": 1000002
}