Abu Quantitative Trading System: Open-Source Python Framework for Stocks, Options, Futures, and Cryptocurrencies

Overview

Abu is a comprehensive quantitative trading system built on Python, designed for multi-market analysis including:

• Stocks (A-shares, US, HK markets)
• Derivatives (Futures & Options)
• Cryptocurrencies (Bitcoin, Litecoin)

Leveraging machine learning and classical technical analysis (e.g., wave theory, harmonic patterns), Abu bridges algorithmic trading and accessibility for non-coders.

Key Features

🚀 AI-Driven Quantitative Models

• 18496+ trading strategies derived from self-learning seed algorithms.

• 3 AI model groups:

  • Physical Transaction Analysis
  • Dopamine-Based Behavioral Models
  • Chart Pattern Recognition

📊 Multi-System Integration

• Candlestick pattern analysis (Pinbar, Head & Shoulders, etc.).
• Wave theory, Gann trends, and breakout/consolidation signals.
• Time-series forecasting and statistical probability systems.

🌍 Market Coverage

• Equities: SHSE, NASDAQ, HKEX.
• Crypto: BTC, LTC spot markets.
• Derivatives: Futures/options backtesting.

Installation & Deployment

🛠️ Setup Guide

1. Python Environment: Use Anaconda.
2. Deployment: Clone the GitHub repo.

👉 Quickstart Guide

Core Modules

1. Timing Strategies

• Entry/Exit Signals: ML-optimized buy/sell factors.
• Backtesting: Historical simulation with customizable slippage.

2. Risk Management

• Stop-loss/take-profit protocols.
• Position sizing algorithms.

3. Multi-Asset Backtesting

• Parallelized testing for portfolios.

Technical Analysis Tools

| Feature | Application |
|-----------------------|--------------------------------------|
| Harmonic Patterns | Bat, Gartley, Cypher detections. |
| Trend Analysis | Support/resistance automation. |
| Candlestick Signals | Pinbar, Doji, and reversal patterns. |

FAQ

❓ How accurate are Abu’s AI models?

Backtests show ~78% precision in predicting trend continuations, with adaptive learning to market shifts.

❓ Can I use Abu for crypto trading?

Yes! Pre-built modules for BTC/LTC include volatility filters and arbitrage signals.

❓ Is coding experience required?

No. The system offers GUI-based strategy builders, though Python APIs allow deeper customization.

Support & Community

• Docs: Abu Quant
• License: GPLv3.

👉 Explore Advanced Features

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