1.8 KiB
Product Overview
Clean Trading System
A modular cryptocurrency trading system that uses deep learning (CNN and RL models) for multi-timeframe market analysis and automated trading decisions.
Core Capabilities
- Multi-timeframe analysis: 1s, 1m, 5m, 1h, 4h, 1d scalping with focus on ultra-fast execution
- Neural network models: CNN for pattern recognition, RL/DQN for trading decisions, Transformer for long-range dependencies
- Real-time trading: Live market data from multiple exchanges (Binance, Bybit, Deribit, MEXC)
- Web dashboard: Real-time monitoring, visualization, and training controls
- Multi-horizon predictions: 1m, 5m, 15m, 60m prediction horizons with deferred training
Key Subsystems
COBY (Cryptocurrency Order Book Yielder)
Multi-exchange data aggregation system that collects real-time order book and OHLCV data, aggregates into standardized formats, and provides both live feeds and historical replay.
NN (Neural Network Trading)
500M+ parameter system using Mixture of Experts (MoE) approach with CNN (100M params), Transformer, and RL models for pattern detection and trading signals.
ANNOTATE
Manual trade annotation UI for marking profitable buy/sell signals on historical data to generate high-quality training test cases.
Critical Policy
NO SYNTHETIC DATA: System uses EXCLUSIVELY real market data from cryptocurrency exchanges. No synthetic, generated, simulated, or mock data is allowed for training, testing, or inference. Zero tolerance policy.
Trading Modes
- Simulation: Paper trading with simulated account
- Testnet: Exchange testnet environments
- Live: Real money trading (requires explicit configuration)
Primary Symbols
- ETH/USDT (main trading pair for signal generation)
- BTC/USDT (reference for correlation analysis)
- SOL/USDT (reference for correlation analysis)