{
  "abstract": "We study variable screening for high-frequency continuous-time regression, targeting the support of the spot regression coefficient. Under coordinatewise truncation and finite-variation jumps, uniform entrywise bounds for local correlation estimates yield the rate $\\{(\\log p)/n\\}^{α/(2α+1)}$ under a local averaged $α$-Hölder condition, up to confidence and grid factors. These bounds imply sure screening for the marginal support. To retain the regression support under local dependence, we propose partial-residual spot iterative screening with pathwise Lepski adaptation. Under sparse eigenvalues and standardized beta-min, the procedure has the sure screening property and requires only correlation columns associated with the current active set. A list-size minimax lower bound applies to both support targets and matches the localization and multiplicity order of the marginal-screening bound when $\\log(p/d)\\asymp\\log p$. Simulations and a high-frequency factor application illustrate the procedures.",
  "abstract_shown": true,
  "affiliations": [],
  "article_type": null,
  "arxiv": "2608.08582",
  "author_total": 1,
  "authors": [
    {
      "name": "Haibin Zhu"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/fbyzcm8mgfs6m.bib",
  "cited_by": 0,
  "doi": "10.48550/arxiv.2608.08582",
  "fulltext_url": null,
  "id": "fbyzcm8mgfs6m",
  "issns": [],
  "landing_url": "https://arxiv.org/abs/2608.08582",
  "language": null,
  "licence": "CC-BY-4.0",
  "licence_label": "CC BY 4.0",
  "licence_source": "article",
  "licence_url": "http://creativecommons.org/licenses/by/4.0/",
  "metadata_licence": "CC0-1.0",
  "native_subjects": [
    [
      "arxiv",
      "math.ST"
    ],
    [
      "arxiv",
      "stat.ME"
    ],
    [
      "arxiv",
      "stat.TH"
    ],
    [
      "openalex",
      "2613|Statistical Methods and Inference"
    ]
  ],
  "openalex": "W7202191363",
  "pdf_url": "https://arxiv.org/pdf/2608.08582",
  "pmcid": null,
  "pmid": null,
  "published": "2026-10-25",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/fbyzcm8mgfs6m.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:35:40Z",
      "native_id": "2608.08582",
      "source": "arxiv",
      "url": "https://arxiv.org/abs/2608.08582"
    }
  ],
  "subjects": [
    {
      "field": "mathematics",
      "origin": "arxiv:math.ST",
      "subfield": "statistics"
    }
  ],
  "title": "Ultra-high-dimensional spot support screening in continuous-time regression",
  "title_text": "Ultra-high-dimensional spot support screening in continuous-time regression",
  "type": "preprint",
  "updated_at": "2026-10-30T12:35:49Z",
  "url": "https://research.draconitic.com/paper/fbyzcm8mgfs6m",
  "venue": "arXiv",
  "versions": []
}