Whitepaper
Technical documentation and methodology
PolySync: AI-Driven Prediction Market Analytics
Abstract
PolySync introduces a novel approach to prediction market analysis by combining order flow data, sentiment analysis, whale activity detection, and historical price patterns through ensemble machine learning models. Our system generates predictive signals that forecast probability shifts before they are reflected in market prices.
Methodology
1. Data Collection: We aggregate trade data, order sizes, timestamps, and price movements from public prediction markets in real-time.
2. Feature Engineering: Extract features including volume-weighted average prices, order imbalances, whale activity indicators, and sentiment scores.
3. Model Architecture: Deploy ensemble models (Random Forest, Gradient Boosting, LSTM networks) to predict probability shifts over various time horizons.
4. Signal Generation: Generate confidence-weighted signals that indicate mispricing opportunities and projected market movements.
Key Features
- Real-time order flow monitoring and analysis
- Whale activity detection using statistical anomaly detection
- Multi-source sentiment aggregation and weighting
- Ensemble prediction models with confidence intervals
- Historical pattern matching and correlation analysis
Disclaimers
PolySync provides analytical tools and predictive signals for informational purposes only. Past performance does not guarantee future results. Users should conduct their own research and risk assessment before making trading decisions. Prediction markets involve substantial risk of loss.
Future Roadmap
- Integration with additional prediction market platforms
- Enhanced sentiment analysis using LLMs
- Custom alert and notification system
- Portfolio optimization and risk management tools
- API access for institutional traders
Version 1.0 • Last updated: January 2025