This project was part of the "Data Science in Finance with Python" course at the Catholic University of Eichstätt-Ingolstadt. The tasks of the final case and presentation ware as follows:
-
Select 15 companies that have been listed on the stock exchange since 1997. Determine the portfolios with the minimum variance, the minimum VaR and the maximum Sharpe ratio for your 15 stocks. Use daily data for your 15 stocks from 1997-2001.
-
Implement buy-and-hold strategies for your three portfolios from 2002-2021 based on the calculated weights of your 15 stocks.
-
Discuss the performance of your three portfolios.
-
Create a graph for the period 2002-2021 that compares the price performance of your three portfolio strategies with an equally weighted portfolio of the 15 stocks as a benchmark.
-
Calculate the portfolios with the minimum variance, the minimum VaR and the maximum Sharpe ratio for the period 2017-2021 and compare the portfolio weights with yours.
-
How would you improve the implementation of your portfolio strategy? What else could you consider?
-
For master students only: Develop a momentum strategy for your 15 shares at monthly level. This is structured as follows: You invest in the tercile of companies with the highest return in the previous month. You hold these 5 companies until the end of the following month. At the end of the month there is always a portfolio rebalancing, whereby the companies with the highest return in the previous month are bought. Does this strategy work? Evaluate the performance.
The notebooks of the final case and the presentation can be found in the 05_Final Case folder.