Quantitative Finance Project: Risk Analysis & Modeling

This project serves as the culmination of our Market Risk Management course, allowing us to delve deeper into the practical implementation of concepts introduced during the course and further explored in our guided studies.

You can find the code used for each question in the "Appendix" section at the end of this report.

Data preparation is a crucial step in this project, and the Python pandas library plays a pivotal role in ensuring efficient data manipulation and cleaning.

Once the data is appropriately prepared, the subsequent phase involves performing calculations to derive various risk measures. For numerical computations, we rely on numpy, and for statistical functions, we utilize scipy.stats.

To create informative charts and graphs for visualization, we heavily rely on matplotlib.pyplot.