Advanced analysis of prediction market inefficiencies. Identify trading edges through sentiment analysis, market anomaly detection, and quantitative research.
Our approach to identifying and exploiting prediction market inefficiencies.
Natural language processing of news, social media, and market commentary to gauge true market sentiment beyond price action.
Machine learning models identify statistically significant deviations from expected market behavior.
Analysis of order flow, liquidity patterns, and market maker behavior to identify structural edges.
Probabilistic modeling of binary events with calibration analysis to find mispriced contracts.
Instant notifications when our models detect opportunities meeting your criteria.
Validate strategies against historical data with proper statistical significance testing.
Preliminary findings from our ongoing research.
Our analysis shows prediction markets exhibit systematic biases in specific contexts—particularly around partisan events, novel situations, and low-liquidity contracts. These biases create exploitable edges for quantitative traders.
News travels through markets in predictable patterns. By monitoring information sources and measuring dissemination speed, we can front-run market movements by 15-45 minutes on average.
Fee structures, margin requirements, and liquidity constraints create systematic price distortions. Understanding these mechanisms reveals consistent arbitrage opportunities.
We're currently researching the following prediction market platforms.
Crypto-based prediction markets with high liquidity on major events.
CFTC-regulated event contracts with growing market depth.
Political prediction markets with unique regulatory constraints.
Forecasting platform with calibration data and expert predictions.
Current progress on our prediction market analysis platform.
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