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

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Highly relevant for quantitative traders interested in statistical arbitrage, mean-reversion strategies, and alternative data sources (prediction markets). The adaptation of pairs trading logic to a non-standard asset class demonstrates transferable methodology, though practical implementation requires addressing execution frictions.

Requires knowledge of stochastic differential equations (OU process), state-space modeling (Kalman filter), and bootstrap methods. The two-step estimation procedure (smoothing then MLE) and handling of irregular sampling intervals add complexity. Code is provided, lowering the barrier for replication.

The authors provide a GitHub repository containing the R code for all analyses, simulations, and graphical outputs. The data source (BetData/Betfair) is identified, and the purchase agreement allows redistribution of the specific datasets used.