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Adapting Pairs Trading to Gambling Markets A Case Study of the U.S. Presidential Election

Haoyu Liu, Len Thomas, Benjamin Baer, Carl Donovan · 2026 · arXiv (Cornell University)

DOI: 10.48550/arxiv.2609.22639 · cited by 0 works (OpenAlex) · open-access PDF

Portuguese

Os pares de negociação exploram a inversão média dos dados na relação entre os ativos relacionados. Adaptamos esta ideia aos mercados de apostas políticas modelando a probabilidade implícita combinada dos dois candidatos do partido principal com um processo latente de Ornstein-Uhlenbeck cujo nível de inversão média varia ao longo do tempo e cujas observações contêm ruído adicional. Os parâmetros do modelo são estimados a partir de dados de probabilidade de amostragem regulares usando uma probabilidade de estado-espaço, com valores repetidos consecutivos representados por uma única observação retida e o número de intervalos de amostragem ultrapassados preservados na transição de tempo contínuo. Parâmetro-bootstrap upperperperperpercition limites indicam tempos de sinal de identificação que na probabilidade implícita combin

Machine translation (Meta M2M100); the English original follows.

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.

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Topics: Odds, Econometrics, Sample (material), Economics, Presidential election, Executable

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