{
  "abstract": "This paper investigates cost-sensitive online window size selection for portfolio management under changing market conditions. Specifically, we propose a two-level framework that constructs portfolios using candidate window sizes and dynamically aggregates them through online learning. By treating candidate window sizes as ``experts,'' we dynamically update their aggregation weights using turnover-inclusive losses. Moreover, we derive finite-horizon cost-sensitive tracking-regret bounds that account for turnover of the aggregated portfolio, with static regret as a special case. Under bounded losses and cost rates, suitably tuned Fixed Share achieves asymptotically no tracking regret for sublinear switching budgets, with Hedge covering the static case.",
  "abstract_shown": true,
  "affiliations": [],
  "article_type": null,
  "arxiv": "2609.29887",
  "author_total": 2,
  "authors": [
    {
      "name": "Yi-Chen Liu"
    },
    {
      "name": "Chung-Han Hsieh"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/6qad818at5p82.bib",
  "cited_by": 0,
  "doi": "10.48550/arxiv.2609.29887",
  "fulltext_url": null,
  "id": "6qad818at5p82",
  "issns": [],
  "landing_url": "https://arxiv.org/abs/2609.29887",
  "language": null,
  "licence": "LicenseRef-arXiv-nonexclusive-1.0",
  "licence_label": "arXiv licence",
  "licence_source": "article",
  "licence_url": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
  "metadata_licence": "CC0-1.0",
  "native_subjects": [
    [
      "arxiv",
      "cs.LG"
    ],
    [
      "arxiv",
      "math.OC"
    ],
    [
      "arxiv",
      "q-fin.PM"
    ],
    [
      "openalex",
      "1803|Advanced Bandit Algorithms Research"
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  "openalex": "W7214280332",
  "pdf_url": "https://arxiv.org/pdf/2609.29887",
  "pmcid": null,
  "pmid": null,
  "published": "2026-09-28",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/6qad818at5p82.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:25:17Z",
      "native_id": "2609.29887",
      "source": "arxiv",
      "url": "https://arxiv.org/abs/2609.29887"
    }
  ],
  "subjects": [
    {
      "field": "mathematics",
      "origin": "arxiv:math.OC",
      "subfield": "optimisation-control"
    }
  ],
  "title": "Cost-Sensitive Online Window Size Selection for Portfolio Management",
  "title_text": "Cost-Sensitive Online Window Size Selection for Portfolio Management",
  "type": "preprint",
  "updated_at": "2026-10-30T12:25:17Z",
  "url": "https://research.draconitic.com/paper/6qad818at5p82",
  "venue": "arXiv",
  "versions": []
}