AlgoStrategy

Open-source quantitative trading framework for detecting and exploiting market inefficiencies across all asset classes via Interactive Brokers TWS API.

Architecture

AlgoStrategy/
├── config.py              # Global configuration & universes
├── ib_connector.py        # IB TWS API wrapper (ib_insync)
├── quant_math.py          # FFD, HMM, GARCH, OU process
├── scanners/
│   ├── pairs_cointegration.py   # Stat arb: Engle-Granger + OU
│   ├── etf_nav_arbitrage.py     # ETF premium/discount
│   ├── futures_basis.py         # Cash-futures basis
│   ├── options_parity.py        # Put-call parity violations
│   └── microstructure.py        # OFI, VWAP, volume anomalies
├── execution/
│   ├── position_sizer.py        # Half-Kelly + correlation
│   ├── order_manager.py         # Smart routing, TWAP, brackets
│   └── risk_manager.py          # DD limits, VaR, kill switch
├── analytics/
│   ├── stats.py                 # Sharpe, Sortino, CAGR, etc.
│   └── reporter.py              # HTML dashboard (auto-refresh)
└── fund_v2.py             # Crypto momentum strategy (standalone)

Scanners

Scanner	Strategy	Expected Sharpe	Asset Classes
Pairs Cointegration	Engle-Granger stat arb with OU half-life	0.8-1.3	ETFs, Stocks
ETF NAV Arbitrage	Premium/discount vs theoretical NAV	0.5-0.8	ETFs
Futures Basis	Cash-futures basis vs cost of carry	0.5-0.9	Futures
Options Parity	Put-call parity violation detection	0.8-1.2	Options
Microstructure	OFI + VWAP deviation + volume anomalies	0.3-0.6	All

Quick Start

Prerequisites

• Python 3.10+
• Interactive Brokers TWS or IB Gateway running
• API enabled in TWS (Edit > Global Configuration > API > Settings)

Install

git clone https://github.com/CypherC0d3/AlgoStrategy.git
cd AlgoStrategy
pip install -r requirements.txt

Run (Paper Trading)

# Test IB connection
python ib_connector.py

# Run pairs scanner (offline mode - no IB needed)
python -m scanners.pairs_cointegration

# Run all scanners
python main.py

Offline Mode

All scanners work without IB connection using yfinance historical data:

from scanners import PairsScanner
scanner = PairsScanner(connector=None)  # No IB
signals = scanner.scan()

Risk Management

• Max 3% per position (Half-Kelly)
• 5% daily drawdown limit
• 15% monthly drawdown limit
• 3x max gross leverage
• Portfolio VaR at 95% confidence
• Emergency kill switch (flatten all)

Contributing

See CONTRIBUTING.md for guidelines on adding new scanners.

Disclaimer

This software is for educational and research purposes only. Trading involves substantial risk of loss. Past performance does not guarantee future results. Always validate with paper trading before risking real capital.

License

MIT License - see LICENSE