Not financial advice. These are research experiments tracking algorithmic signals against real market data. No real money is at risk. Past signal performance does not predict future results. These tools are for educational and research purposes only.
Research · Phase 1
Can AI consistently beat prediction markets?
Logs daily algorithmic signals from 10 live Polymarket contracts and tracks the divergence between our AI assessments and market consensus. When the model disagrees with the crowd, we record the prediction and check back later. Phase 1 is pure signal collection and accuracy measurement — no capital deployed.
Contracts Tracked
10
Signal Frequency
Daily
Capital at Risk
$0
Prediction Markets AI vs Crowd Signal Logging
Research · Paper Trading
Can multi-indicator confluence produce statistically significant edge in digital asset markets?
Quantitative signal research platform scanning digital assets across multiple timeframes. Evaluates 20+ technical indicators — momentum oscillators (RSI, MACD, ADX), trend-following systems (EMA crossovers, Bollinger Bands), volume analysis (OBV), and 13 candlestick formations — to generate directional signals with defined entry, stop-loss, and target levels. All positions are simulated to measure signal accuracy and risk-adjusted returns over time.
Indicators
20+
Pattern Recognition
13 formations
Simulated Capital
$1k / position
Timeframes
4H / 1D / 1W
Digital Assets Quantitative Analysis Multi-Indicator Confluence Simulated Execution

What we're testing next

Every experiment starts with a question and a hypothesis. If the data says it works, it becomes a product. If it doesn't, we publish what we learned. Either way, we ship.

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