This Master thesis investigates factor exposures on European equities, and how to combine them most effectively in order to achieve the best portfolio based on different measures of performance and risk.
Predefined factor exposures are assessed using the five largest European stock markets. The analysed factors are limited to the market-, size-, value-, momentum-, quality-minus-junk- and betting-againstbeta factors. First, the individual factor portfolios are evaluated on a single country basis during different market conditions from 1986 until 2016. Secondly, the factors are evaluated using an equally weighted European portfolio containing the five selected countries. Based on this, dynamic meanvariance optimized portfolios (minimum-variance and tangency) are created to utilize the diversification benefits between the factor-portfolios most efficiently. As opposed to many other studies, this thesis is using sophisticated technics regarding shrinkage of the covariance matrices in order to get matrices better suited to mean-variance optimization.
As the academic litterateur suggest, this thesis uncover convincing abnormal factor returns across individual countries. More specifically the thesis finds compelling factor premiums for the momentum-, quality-minus-junk- and betting-against-beta portfolios, whereas the value- and size portfolios in particular have been a less attractive investment on an individual level. As for the combined dynamic portfolios, the minimum-variance portfolios outperform the market portfolio, the tangency portfolios, and a static benchmark consisting of a constant equal weight in all factors, both in regards to performance- and risk measures.
The thesis applies extensive testing regarding the results in the second part of the analysis. Model assumptions are tested and out-of-sample tests conducted in order to check the robustness of the portfolios. Furthermore, even after the inclusion of transaction costs, the minimum-variance portfolio is superior to the market portfolio, the tangency portfolios, and the static benchmark, and is recommended for investor as the optimal portfolio going forward.
|Educations||MSc in Finance and Accounting, (Graduate Programme) Final Thesis|
|Number of pages||131|