An automated pipeline that transforms hypotheses into validated prediction market strategies. Seven stages, three statistical gates, zero tolerance for overfitting.
In traditional quant trading, you backtest against 20 years of continuous price data for the same instrument. In prediction markets, every market is unique — born, lives briefly, resolves to 0 or 1, and dies. You can't backtest "a strategy on ECB March 2026." You backtest "a pattern across all ECB rate decisions as a class."
The Strategy Factory solves this by shifting the unit of analysis from instruments to event-type categories.
Every strategy flows through the same pipeline. At each gate, it either passes or is rejected. No exceptions, no shortcuts, no re-tuning after failure.
An automated pipeline that transforms hypotheses into validated strategies, deploys the survivors with risk-controlled capital, monitors them against statistical benchmarks, and retires them when edge decays — while simultaneously developing replacements.
The classical mechanical trading system framework — Training, Validation, Out-of-Sample — adapted for prediction markets where samples are split across events, not time periods.
Traditional quant backtesting uses thousands of data points. PM event categories have tens to hundreds. The Strategy Factory compensates with: conservative parameter selection (wide robustness windows), mandatory paper trading before live deployment, small initial position sizes (2% of capital), rapid feedback loops, and — critically — the Structural Event Clustering that pools structurally similar events across categories to increase effective sample sizes.
The Strategy Factory runs two complementary layers: directional alpha (single-leg trade on Polymarket, edge from a trading rule or trusted external source) and arbitrage (both legs tradable, risk-free pair-trade).
In directional-alpha trades only one leg is tradable: the Polymarket position. Edge comes either from classical trading patterns or from an external source whose authority we accept.
Adaptation of classical quant patterns (mean reversion, volume spikes, trend following) onto prediction-market mechanics. Pipeline pattern is validated step by step.
Treat a trusted external source as “truth” — when Polymarket diverges by more than the threshold, trade the Polymarket leg. The source itself is usually not tradable for EU users; that's why this is single-leg, not arbitrage.
In arbitrage both platforms are tradable — the trade is mathematically risk-free as soon as the spread exceeds the sum of all costs. V1: Polymarket vs other prediction-market and sports-exchange platforms. Most second-platform adapters Q4 2026.
Overfitting is the primary risk in PM backtesting due to small sample sizes. These rules are system-enforced, not suggestions.
v1.0 running since February 2026. First strategies in the pipeline. The methodology is proven — now being productized as infrastructure.