Analysis of Reddit User's Event Contract Arbitrage Strategy Outperforming ML Models

The analysis is based on a Reddit post [1] where a user reported their simple event contract arbitrage algorithm outperformed a complex ML model. The strategy leverages price gaps between Kalshi event contracts and Fed funds futures (5%+ threshold), closing positions 24h before events [1]. Market segmentation (retail traders on Kalshi vs institutional investors in futures) creates inefficiencies [4]. For example, Kalshi’s Dec 2025 Fed 25bps cut contract was priced at53% vs FedWatch’s71% [3].

1. Simple arbitrage can outperform complex ML models when exploiting market inefficiencies [1].
2. Market segmentation (retail vs institutional) drives price gaps between event contracts and derivatives [4].
3. Transient opportunities fade as more traders adopt the strategy [1].

• Risks
  : Strategy may stop working by Monday due to adoption [1], gaps narrowing [7].
• Opportunities
  : Short-term gains for early adopters before inefficiencies erase [1].

The strategy uses a5%+ gap threshold between Kalshi and Fed funds futures, closing positions24h before events. Kalshi’s Dec 2025 Fed cut contract expires Dec 10,2025 [2]. The user’s ML model (Sharpe ratio ~1.2) underperformed due to historical data focus [1].