CR-CA_Q - Quantitative Trading System

CRCA-Q: Causal Reasoning for Quantitative Trading

CRCA-Q is a quantitative trading system that integrates causal reasoning (based on Judea Pearl's Structural Causal Models) with traditional quantitative finance techniques. Unlike correlation-based systems, CRCA-Q uses causal inference to understand WHY market movements occur, enabling more robust predictions that remain valid across different market regimes.

Key Features:

• Causal signal generation based on structural causal models (SCMs)
• Portfolio optimization using CVaR (Conditional Value at Risk)
• Multi-asset support with automatic asset discovery and rotation
• Alternative data integration (on-chain, social sentiment, news, GitHub activity)
• Risk management with circuit breakers and position limits
• Support for multiple exchanges (Kraken, Binance, Coinbase)
• Demo mode by default (no real trades unless explicitly enabled)

Installation:

1. Copy/Download the setup script

2. Run the setup script:

   python setup.py

3. Select option "1" (Install/Update) from the menu

4. The script will download CRCA-Q.py and CRCA.py from GitHub

5. Files will be saved to:

   • branches/CRCA-Q.py
   • CRCA.py

After installation, you can run CRCA-Q:

python branches/CRCA-Q.py

For longterm mode:
python branches/CRCA-Q.py --longterm-mode

For streaming mode:
python branches/CRCA-Q.py --stream

Note: CRCA-Q runs in DEMO MODE by default. No real trades will be executed unless you explicitly enable live trading mode and configure API keys.

For more information, view the complete manual by running setup.py and selecting option "2" (View Manual).

Repository: https://github.com/IlumCI/CR-CA