Welcome to the Quantitative Finance Notebooks repository, a comprehensive collection of Jupyter Notebooks covering a wide range of topics related to quantitative finance. The notebooks include tutorials, examples, and applications of financial mathematics, statistical methods, and machine learning in finance.

To run the notebooks, you will need to have Python 3.7 or later and Jupyter Notebook installed. You can download Python from the official website and install Jupyter Notebook using pip:

pip install jupyter

You can download the notebooks from the Quant-Finance-Notebooks repository using git or as a ZIP file.

To clone the repository using git, run:

git clone https://github.com/notabombe/Quant-Finance-Notebooks.git

Once you have downloaded the notebooks, you can launch Jupyter Notebook from the command line by running:

jupyter notebook

This will open a new tab in your web browser with the Jupyter Notebook interface. From there, you can navigate to the folder where you downloaded the notebooks and open any notebook by clicking on its filename.

The notebooks are organized into folders based on topic, such as time series analysis, option pricing, portfolio optimization, risk management, trading strategies, and machine learning for finance. Each notebook includes explanations, code, and examples to help you understand and apply the concepts presented.

We welcome contributions to the Quantitative Finance Notebooks repository! To contribute, please follow the contribution guidelines and the code of conduct .

For more resources on quantitative finance, check out the following:

• Quantitative Finance Books
• Quantitative Finance Blogs and Websites

The Quantitative Finance Notebooks are released under the MIT License .