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Academic project as part of the Quantitative Finance class of master MOSEF.

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Portfolio Construction using ML with backtesting results

In collaboration with :


This project is a part of a Quantitative Finance course (Panthéon Sorbonne).

Goals

The idea behind the project was the usage of ML prediction in portfolio construction and manage an active portfolio strategy.

We were given the task to create a portfolio given the equities and compare the results with a benchmark. The equities are US stocks categorized as ESG (aprox 50 tickers). The project will be separated in two main strategies, Long Only (LO) with the SPX as a benchmark and Long/Short benchmarked with Eonia +4%.

You could find our results in final_project.ipynb

Best regards.

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