Quantitative Trading Platform

A quantitative trading platform with modular architecture for data acquisition, strategy execution, risk management, and UI/UX.

Architecture

See component_diagram.md and architecture_diagram.txt in the parent directory (/home/thanthos/clawd/) for detailed system design.

UI/UX Module

Dashboard

Simple dashboard displaying key trading metrics:

• PnL (Profit and Loss)
• Drawdown
• Win Rate

Data Layer Module

Moomoo API Connector

A robust Python client for moomoo API with comprehensive error handling, rate limiting, and data normalization.

Features:

• Historical OHLCV data retrieval
• Real-time WebSocket subscription (mock)
• Instrument metadata
• Rate limiting (token bucket algorithm)
• Circuit breaker pattern for fault tolerance
• Caching with TTL
• Mock mode for development

Usage:

from data.connectors import create_moomoo_client, Interval
from datetime import datetime, timedelta

client = create_moomoo_client(mock_mode=True)
data = client.get_ohlcv(
    symbol="AAPL",
    interval=Interval.DAY_1,
    start_date=datetime.now() - timedelta(days=30),
    end_date=datetime.now()
)

See examples/demo_moomoo.py for complete demonstration.

Development

Prerequisites

• Python 3.8+
• Node.js (for frontend, optional)
• Docker (optional)
• Redis (optional, for caching)

Setup

1. Clone the repository
2. Install dependencies: pip install -r requirements.txt
3. Run the dashboard: python app.py
4. Test data connector: python examples/demo_moomoo.py

Data Layer Development

The data connector uses a modular design with base classes for easy extension:

• DataConnector abstract base class
• MoomooClient implementation with mock mode
• Rate limiting and circuit breaker patterns
• Caching support (in-memory or Redis)

To extend with real API credentials:

1. Set environment variables: MOOMOO_API_KEY, MOOMOO_SESSION_TOKEN
2. Set mock_mode=False when creating client
3. Implement actual API calls in _make_request() method

UI/UX Development

The dashboard is built with Flask (backend) and Bootstrap/Chart.js (frontend).

• Backend: app.py provides REST API endpoints
• Frontend: templates/dashboard.html with interactive charts

Interactive Prototype

A complete clickable mockup of the full platform is available in the prototype/ directory. This showcases the complete user interface with all major sections:

Features demonstrated:

• Dashboard with real-time metrics
• Data management interface
• Strategy engine configuration
• Risk management controls
• Navigation between all platform sections

To use the prototype:

1. Open prototype/index.html in a web browser
2. Click sidebar navigation to explore different sections
3. Interact with charts, forms, and controls

The prototype uses HTML/CSS/JavaScript with Bootstrap and Chart.js, and can be reused as the foundation for the actual web application.

License

Proprietary