Predictor

This study examines the profitability of mean-reversion trading strategies applied to binary outcome contracts on Polymarket, the world’s largest decentralized prediction market platform. We analyze three distinct contracts representing varying risk profiles: a quasi-risk-free instrument (No to “Will Jesus Christ return in 2025?”) and two high-yield speculative contracts (No to “Will China invade Taiwan in 2025?” and “Will the US confirm that aliens exist in 2025?”). Using high-frequency price data sampled at 10-minute intervals over approximately one year, we implement a parameterized mean-reversion framework across twelve strategy variants, testing robustness under varying liquidity constraints and transaction cost assumptions. Our findings reveal that while mean-reversion signals generate substantial alpha under passive limit-order execution (zero-spread scenario), strategy performance degrades significantly when more aggressive market orders are accounted for.

In recent times, we have observed heightened volatility across financial markets. Concerns surrounding government shutdowns, as well as the uncertainty they create, do little to calm these fluctuations. Rather than being purely disruptive, however, such events raise an intriguing question: could these episodes of political and economic uncertainty actually be leveraged to our advantage in investment strategies? In this article, we will examine several asset classes and attempt to assess whether this phenomenon provides a sufficiently relevant signal for investment decisions.