Publicação
Tool-assisted Validation of Factor-based Investment Strategies within the scope of the European Market
| Resumo: | This thesis is aimed towards the implementation, analysis and fusion of various factor- based investment strategies on the biggest European market. We were focused on studying a contrarian investment strategy, two value investment strategies, and a momentum strat- egy. These four different methodologies of stock selection were put to the test during the period 2015-2019 on this market and their merging provides a rich sense of how well these factors can work together. For this purpose, we utilized the Python framework Qrumble, for quick and straight-forward results of investments experiments. To accomplish such thorough analysis, we incorporated into Qrumble more portfolio evaluation metrics and two theoretically efficient portfolios from Portfolio Theory, the minimum variance port- folio and market portfolio. We found that most investment strategies didn’t succeed as expected, probably due to the limited period of experiment. On the other hand, both value strategies revealed interesting returns without much higher risk involved. Finally, we achieved better results through a multi-type factor investment strategy by combining factors from said strategies, which can be a sign that these different schools of thought can collaborate effectively. This also exhibited that theoretically efficient portfolios can have interesting outcomes within the right circumstances, which requires future work. |
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| Autores principais: | Ramos, Catarina Avelino Palma |
| Assunto: | Factor-based Investing Portfolio Theory Efficient Portfolio Decision Support System |
| Ano: | 2023 |
| País: | Portugal |
| Tipo de documento: | dissertação de mestrado |
| Tipo de acesso: | acesso aberto |
| Instituição associada: | Universidade Nova de Lisboa |
| Idioma: | inglês |
| Origem: | Repositório Institucional da UNL |
| Resumo: | This thesis is aimed towards the implementation, analysis and fusion of various factor- based investment strategies on the biggest European market. We were focused on studying a contrarian investment strategy, two value investment strategies, and a momentum strat- egy. These four different methodologies of stock selection were put to the test during the period 2015-2019 on this market and their merging provides a rich sense of how well these factors can work together. For this purpose, we utilized the Python framework Qrumble, for quick and straight-forward results of investments experiments. To accomplish such thorough analysis, we incorporated into Qrumble more portfolio evaluation metrics and two theoretically efficient portfolios from Portfolio Theory, the minimum variance port- folio and market portfolio. We found that most investment strategies didn’t succeed as expected, probably due to the limited period of experiment. On the other hand, both value strategies revealed interesting returns without much higher risk involved. Finally, we achieved better results through a multi-type factor investment strategy by combining factors from said strategies, which can be a sign that these different schools of thought can collaborate effectively. This also exhibited that theoretically efficient portfolios can have interesting outcomes within the right circumstances, which requires future work. |
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