Implement, demonstrate, reproduce and extend the results of the Risk articles 'Differential Machine Learning' (2020) and 'PCA with a Difference' (2021) by Huge and Savine, and cover implementation details left out from the papers.

Notes and examples about Portfolio Construction and Analysis with Python (Jupyter notebooks)

Jupyter notebooks and data files of the new EDHEC specialization on quantitative finance (completed Aug 2022)

iPython notebook which allows the calculation of historical VaR for a variable range of user defined US equities. The lookback period is manually user defined.

Notebooks in financial mathematics. Ranging from risk management to portfolio management and stochastic processes for financial markets.

Validation checks for EIOPA technical submissions written and documented in Jupyter notebooks.