Regime-Switching Momentum Strategy

A quantitative trading framework that leverages daily OHLCV stock data and a Hidden Markov Model (HMM) to dynamically identify market regimes and generate momentum-based trading signals.

Table of Contents

• About
• Features
• Installation
• Usage
• Project Structure
• Contributing
• License
• Contact

About

The Regime-Switching Momentum Strategy is designed for quantitative traders, financial analysts, and researchers. The project uses daily OHLCV data and advanced statistical methods (HMM) to:

• Detect market regimes (e.g., bullish, bearish, neutral)
• Generate regime-dependent momentum trading signals
• Backtest performance and assess risk management measures

This repository includes planning documents, core modules for data ingestion, feature engineering, regime detection, signal generation, and a backtesting engine.

Features

• Dynamic Regime Detection: Uses a Hidden Markov Model to identify market conditions.
• Momentum Signal Generation: Generates buy, hold, and sell signals based on regime-specific momentum.
• Robust Backtesting: Simulates historical performance and computes key metrics (Sharpe ratio, drawdown, etc.).
• Integrated Risk Management: Implements dynamic risk controls based on market regimes.

Installation

1. Clone the repository:

   git clone https://github.com/Abdullah-BA/RegimeSwitchingMomentumStrategy.git
   cd RegimeSwitchingMomentumStrategy

2. Install dependencies:

   pip install -r requirements.txt

Usage

• Data Ingestion:
  Run the data ingestion script to load and preprocess OHLCV data:

  python src/data_ingestion.py

• Feature Engineering:
  Generate technical indicators:

  python src/feature_engineering.py

• Regime Detection:
  Train and apply the HMM for regime detection:

  python src/regime_detection.py

• Signal Generation and Backtesting:
  Generate trading signals and run the backtesting framework:

  python src/signal_generation.py
  python src/backtesting.py

Project Structure

RegimeSwitchingMomentumStrategy/
│
├── data/
│   ├── PRD.md                # Product Requirements Document
│   ├── color-palette.md      # UI/Visualization Guidelines
│   ├── database-design.md    # Database schema and data flow
│   └── project-structure.md  # Folder structure and conventions
│
├── src/
│   ├── data_ingestion.py     # Load and preprocess OHLCV data
│   ├── feature_engineering.py# Compute technical indicators
│   ├── regime_detection.py   # HMM-based regime detection logic
│   ├── signal_generation.py  # Trading signal generation
│   └── backtesting.py        # Backtesting framework and performance metrics
│
├── .gitignore                # Files to ignore in Git
├── requirements.txt          # Python dependencies
└── README.md                 # Project overview and documentation

Contributing

Contributions are welcome! Please follow these steps:

1. Fork the repository.
2. Create a new branch for your feature or bug fix.
3. Commit your changes with descriptive messages.
4. Submit a pull request.

License

This project is licensed under the MIT License.

Contact

For questions or feedback, please reach out to:

• Name: Abdullah-BA