This project implements and evaluates the Jegadeesh-Titman Momentum Strategy, a widely studied financial trading strategy that aims to capitalize on market trends. The project uses Python to analyze historical stock data and simulate portfolio returns based on momentum signals.

• Momentum Signal Generation: Identifies assets with strong recent performance.
• Portfolio Construction: Constructs a diversified portfolio based on momentum rankings.
• Performance Evaluation: Analyzes returns and compares them to benchmarks.
• Data Handling: Efficiently processes financial datasets.

Jegadeesh-Titman-Momentum-Git/
├── data/               # Historical stock data files
├── src/                # Source code for momentum strategy
├── tests/              # Unit tests for the project
├── venv/               # Python virtual environment
├── .gitignore          # Git ignored files
├── LICENSE             # Project license
├── NOTES               # Project notes and insights
└── README.md           # Project documentation

1. Clone this repository:

   git clone https://github.com/yourusername/Jegadeesh-Titman-Momentum.git
   cd Jegadeesh-Titman-Momentum

2. Set up a virtual environment:

   python -m venv venv
   source venv/bin/activate  # On Windows: venv\Scripts\activate

3. Install dependencies:

   pip install -r requirements.txt

1. Prepare Data: Ensure your data is in the data/ folder.
2. Run Analysis:

   python src/main.py

3. View Results: Analyze performance metrics in the output.

• Improve data preprocessing.
• Add visualization for portfolio performance.
• Optimize signal generation.
• Extend to other financial markets.

Contributions are welcome! Please open an issue or submit a pull request for improvements.

This project is licensed under the terms of the LICENSE file.