This project provides a comprehensive introduction to the practical applications of quantitative finance using Python. It covers various topics related to quantitative finance, including time series analysis, statistical arbitrage, portfolio optimization, and risk management. The project is implemented using Python programming language and relevant libraries such as NumPy, pandas, scipy, pyfolio and yfinance.
Before running this project, you need to have the following software installed:
Python 3.x Jupyter Notebook NumPy pandas scipy pyfolio yfinance VaR
This project is organized into multiple modules, each covering a specific topic in quantitative finance. Each module includes a Jupyter notebook that explains the concepts and provides step-by-step guidance on how to implement them using Python. The project also includes sample datasets that can be used for testing and experimentation. All functions are stored in functions.py file.
This project includes the following modules:
Time Series Analysis Statistical Arbitrage Portfolio Optimization Risk Management Each module includes a Jupyter notebook and sample datasets.
This project is open to contributions from the community. If you find a bug or have a feature request, please open an issue on GitHub. If you would like to contribute code, please fork the repository and submit a pull request.