RaptorDCA Pro

RaptorDCA Pro is an advanced cryptocurrency strategy backtesting and simulation platform designed for high-precision Dollar Cost Averaging (DCA), Grid simulations, and custom algorithmic trading strategies. It features a modern web-based interface, Monte Carlo simulations, and a robust backtesting engine.

🚀 Key Features

• Advanced Backtesting Engine: Test your strategies against historical market data with precision.
• Web-Based Interface: Fully interactive dashboard built with Flask for configuring and running simulations.
• Monte Carlo Simulations: Run thousands of simulations to stress-test your strategy against random variations (app/monte_carlo.py).
• Custom Strategy Support: Modular strategy system allowing for custom implementations (app/strategies/).
• Detailed Analytics:
  • Visual Reports: Interactive charts for Portfolio Value, Drawdown, and Returns distribution.
  • Metrics: CAGR, Max Drawdown, Sharpe Ratio, and more.
• Lockdown Manager: Integrated risk management and system state monitoring (app/lockdown.py).
• Strategy Configuration: Save and load strategy parameters via JSON configuration files.
• Leaderboard & History: Track and compare the performance of different strategy runs.

🛠 Technology Stack

• Core: Python 3.x
• Web Framework: Flask
• Data Analysis: Pandas, NumPy
• Market Data: Yahoo Finance (via yfinance)
• Database: SQLite (for session storage and result history)
• Visualization: Matplotlib / JSON-based plotting for frontend

📦 Installation

1. Clone the repository:

   git clone <repository-url>
   cd "RaptorDCA Pro"

2. Install Dependencies: It is recommended to use a virtual environment.

   python -m venv venv
   source venv/bin/activate  # On Windows: venv\Scripts\activate
   pip install flask pandas numpy yfinance matplotlib requests

▶️ Usage

1. Start the Application: Run the entry point script. The application will automatically attempt to open your default web browser.

   python run.py

2. Access the Dashboard: If the browser doesn't open automatically, navigate to: http://127.0.0.1:5000

3. Run a Simulation:

   • Select a Strategy from the dropdown menu.
   • Enter a Ticker symbol (e.g., BTC-USD).
   • Configure parameters (Initial Investment, DCA Multiplier, Take Profit, etc.).
   • Click Run Backtest.

4. View Reports: Once the simulation is complete, you will be redirected to a detailed report page showing the performance metrics and charts.

⚙️ Configuration

• Strategies: Located in app/strategies/. You can extend the Strategy class in app/core.py to create new strategies.
• Configs: Saved strategy configurations are stored in configs/ as JSON files.
• Database: System data is stored in db_data/lockdown.db.

📁 Project Structure

• app/core.py: Core trading engine and base classes.
• app/web.py: Flask web server routes.
• app/strategies/: Strategy implementations.
• app/services/: Business logic services (Backtesting, etc.).
• app/visualizer.py: Chart generation logic.
• run.py: Application entry point.

⚠️ Disclaimer

This software is for educational and research purposes only. Do not use it as financial advice. Trading cryptocurrencies involves significant risk.