This project is focused on building a Python-based algorithm for optimal portfolio construction using Modern Portfolio Theory techniques. The project includes data analysis and statistical modeling using Pandas, Matplotlib, and Plotly libraries.
To use this project, you will need to have Python installed on your computer. The project also requires the following Python libraries:
- Pandas
- Matplotlib
- Plotly
- YFinance
To use this project, you can simply clone or download the repository to your local machine. Once you have the files, you can run the portfolio_construction.ipynb notebook to explore the algorithm and conduct portfolio analysis.
The notebook includes the following sections:
- Data Cleaning and Preparation: This section focuses on cleaning and preparing the data for analysis.
- Data Analysis: This section includes statistical analysis and visualization of the data to better understand the characteristics of the assets in the portfolio.
- Optimal Portfolio Construction: This section includes the implementation of the Modern Portfolio Theory algorithm to construct the optimal portfolio.
- Portfolio Analysis: This section includes the analysis of the optimal portfolio constructed in the previous section, including risk and return metrics, efficient frontier plot, and other performance measures.
If you are interested in contributing to this project, feel free to fork the repository and submit a pull request. Any contributions are welcome!