{
  "abstract": "This study extends an existing single-period mixed-integer linear programming (MILP) formulation to a multi-period index-tracking problem. The proposed model allows the tracking portfolio to be rebalanced at predetermined times while limiting the associated transaction costs. Two benchmark strategies are considered: a fixed portfolio with no rebalancing and a portfolio reselected under a large transaction-cost limit intended to approximate unrestricted rebalancing. The models are evaluated using constituent data for the SSE 50 and CSI 100 indices. Tracking performance is measured in-sample and out-of-sample for different portfolio cardinalities, sample lengths, and transaction-cost limits. Among the parameter values examined, at least one multi-period specification produces a lower out-of-sample root-mean-square error (RMSE) than both benchmarks in seven of the eight reported configurations. However, the optimal transaction-cost limit varies across configurations, indicating that tracking performance is sensitive to the permitted degree of rebalancing.",
  "abstract_shown": true,
  "affiliations": [
    "School of Economics, Peking University, Beijing 100871, China",
    "Bay Area International Business School, Beijing Normal University, Zhuhai 519087, China",
    "School of Economics, Sichuan University, Chengdu 610065, China"
  ],
  "article_type": null,
  "arxiv": null,
  "author_total": 4,
  "authors": [
    {
      "affs": [
        0
      ],
      "name": "Yanzhe Dong",
      "orcid": "0009-0009-3155-5248"
    },
    {
      "affs": [
        1
      ],
      "name": "Binwei Xu"
    },
    {
      "affs": [
        2
      ],
      "name": "Yujia Liu"
    },
    {
      "affs": [
        1
      ],
      "name": "Liang Wu"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/37167836qje8q.bib",
  "cited_by": 0,
  "doi": "10.3390/math14203836",
  "fulltext_url": null,
  "id": "37167836qje8q",
  "issns": [
    "2227-7390"
  ],
  "landing_url": "https://www.mdpi.com/2227-7390/14/20/3836",
  "language": null,
  "licence": "CC-BY-4.0",
  "licence_label": "CC BY 4.0",
  "licence_source": "article",
  "licence_url": "https://creativecommons.org/licenses/by/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "openalex",
      "1803|Risk and Portfolio Optimization"
    ]
  ],
  "openalex": "W7223185969",
  "pdf_url": null,
  "pmcid": null,
  "pmid": null,
  "published": "2026-10-21",
  "publisher": "MDPI AG",
  "ris": "https://research.draconitic.com/paper/37167836qje8q.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:18:29Z",
      "native_id": "10.3390/math14203836",
      "source": "crossref",
      "url": "https://www.mdpi.com/2227-7390/14/20/3836"
    }
  ],
  "subjects": [
    {
      "field": "mathematics",
      "origin": "issn:2227-7390",
      "subfield": "general"
    }
  ],
  "title": "A Multi-Period MILP Model for Dynamic Index Tracking",
  "title_text": "A Multi-Period MILP Model for Dynamic Index Tracking",
  "type": "peer-reviewed",
  "updated_at": "2026-10-30T12:18:29Z",
  "url": "https://research.draconitic.com/paper/37167836qje8q",
  "venue": "Mathematics",
  "versions": []
}