{
  "abstract": "Pairs trading exploits mean reversion in the relationship between related assets. We adapt this idea to political betting markets by modelling the combined implied probability of the two major-party nominees with a latent Ornstein-Uhlenbeck process whose mean-reversion level varies over time and whose observations contain additive noise. Model parameters are estimated from regularly sampled odds data using a state-space likelihood, with consecutive repeated values represented by a single retained observation and the elapsed number of sampling intervals preserved in the continuous-time transition. Parametric-bootstrap upper prediction bounds identify signal times at which the combined implied probability is likely to decline, and a no-intercept Bradley-Terry-type model selects the candidate-specific odds quote. The candidate-selection model is trained on 2020 U.S. presidential-election data and evaluated out of sample on 2024 data. The 2024 analysis produced 130 signals, empirical one-step coverage of 95.1%, a mean synthetic odds-price return of 1.86%, and an unannualized per-trade Sharpe-type ratio of 1.12. These returns are frictionless descriptive quantities rather than executable betting-exchange profits. The results support the integrated framework as a proof of concept for two-candidate electoral markets.",
  "abstract_shown": true,
  "affiliations": [],
  "article_type": null,
  "arxiv": "2609.22639",
  "author_total": 4,
  "authors": [
    {
      "name": "Haoyu Liu"
    },
    {
      "name": "Len Thomas"
    },
    {
      "name": "Benjamin Baer"
    },
    {
      "name": "Carl Donovan"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/0m9kfy9zy317d.bib",
  "cited_by": 0,
  "doi": "10.48550/arxiv.2609.22639",
  "fulltext_url": null,
  "id": "0m9kfy9zy317d",
  "issns": [],
  "landing_url": "https://arxiv.org/abs/2609.22639",
  "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",
      "q-fin.ST"
    ],
    [
      "arxiv",
      "stat.AP"
    ],
    [
      "openalex",
      "2002|Sports Analytics and Performance"
    ]
  ],
  "openalex": "W7214020337",
  "pdf_url": "https://arxiv.org/pdf/2609.22639",
  "pmcid": null,
  "pmid": null,
  "published": "2026-09-18",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/0m9kfy9zy317d.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:23:33Z",
      "native_id": "2609.22639",
      "source": "arxiv",
      "url": "https://arxiv.org/abs/2609.22639"
    }
  ],
  "subjects": [
    {
      "field": "mathematics",
      "origin": "arxiv:stat.AP",
      "subfield": "statistics"
    }
  ],
  "title": "Adapting Pairs Trading to Gambling Markets A Case Study of the U.S. Presidential Election",
  "title_text": "Adapting Pairs Trading to Gambling Markets A Case Study of the U.S. Presidential Election",
  "type": "preprint",
  "updated_at": "2026-10-30T12:23:33Z",
  "url": "https://research.draconitic.com/paper/0m9kfy9zy317d",
  "venue": "arXiv",
  "versions": []
}