Ordinis

Version: 0.2.0-dev (Development Build) Status: ✅ Ready for Testing

An AI-driven quantitative trading system with multi-source market data, paper trading simulation, and ML-driven signal generation.

Project Overview

Complete end-to-end trading pipeline featuring:

• 4 Market Data APIs (Alpha Vantage, Finnhub, Polygon/Massive, Twelve Data)
• Paper Trading Engine with realistic fill simulation
• Backtesting Framework (ProofBench)
• 5 Trading Strategies ready to deploy
• Real-time Dashboard for monitoring
• RiskGuard Framework for risk management

Project Phases

Phase	Description	Status
1	Knowledge Base & Strategy Design	✅ 100% Complete
2	Code Implementation & Backtesting	✅ 95% Complete
3	Paper Trading & Simulation	✅ 90% Complete
4	Risk Management	⚠️ 50% Complete
5	System Integration	⚠️ 60% Complete
6	Production Preparation	❌ 10% Planned

Quick Start

Run Full System Demo

# Set up environment
cp .env.example .env
# Add your API keys to .env

# Run end-to-end demo
python scripts/demo_full_system.py

Expected output:

• 3 data sources initialized
• Live market data fetched (AAPL, MSFT, GOOGL)
• 2 trading signals generated
• Orders filled with realistic slippage
• Final P&L displayed

Test Market Data APIs

python scripts/test_market_data_apis.py

Launch Dashboard

streamlit run src/dashboard/app.py

Repository Structure

intelligent-investor/
├── README.md                    # This file
├── PROJECT_STATUS_CARD.md       # Detailed status report
├── docs/                        # Documentation and knowledge base
│   ├── knowledge-base/          # Core KB sections (10 domains)
│   ├── strategies/              # Strategy specifications
│   └── architecture/            # System design documents
├── src/                         # Source code
│   ├── engines/                 # Core engines (ProofBench, RiskGuard, etc.)
│   ├── plugins/market_data/     # 4 API integrations
│   ├── strategies/              # 5 implemented strategies
│   └── dashboard/               # Streamlit monitoring dashboard
├── scripts/                     # Executable scripts and demos
│   ├── demo_full_system.py      # Full pipeline demonstration
│   ├── test_market_data_apis.py # API validation tests
│   └── test_live_trading.py     # Paper trading tests
├── tests/                       # Test suites (413 tests, 67% coverage)
└── data/                        # Sample market data

Features

Market Data Integration

• Alpha Vantage: 25 calls/day, comprehensive fundamentals
• Finnhub: 60 calls/min, real-time quotes + news
• Polygon/Massive: Market data and status
• Twelve Data: 800 calls/day, technical indicators

Paper Trading

• Realistic order fill simulation with slippage (5 bps)
• Commission calculation ($0.005/share)
• Position tracking with real-time P&L
• Integration with live market data
• Pending order management

Backtesting

• Event-driven simulation engine (ProofBench)
• Performance metrics: Sharpe, Sortino, Max Drawdown
• Equity curve tracking
• Walk-forward validation ready

Strategies

1. Moving Average Crossover (50/200 SMA)
2. RSI Mean Reversion
3. Momentum Breakout
4. Bollinger Bands
5. MACD

Dashboard

• Real-time position monitoring
• P&L visualization
• Trade history
• Performance metrics
• Multi-timeframe analysis

Disclaimer

IMPORTANT:

• All trading involves risk of loss. There are no guarantees of profit.
• Past performance in backtests does not assure future results.
• This system is a research and engineering project, not personalized financial advice.
• The authors and contributors are not licensed financial advisors.

License

[To be determined]