Publicação
Analysis of quantitative investment strategies
| datacite.subject.fos | Ciências Sociais::Economia e Gestão | pt_PT |
| dc.contributor.advisor | Hirschey, Nicholas H. | |
| dc.contributor.author | Eusébio, Hugo | |
| dc.date.accessioned | 2023-12-13T10:15:47Z | |
| dc.date.available | 2023-12-13T10:15:47Z | |
| dc.date.issued | 2022-12-16 | |
| dc.date.submitted | 2022-12-16 | |
| dc.description.abstract | This paper tests the combination of five different sub-strategies, resembling the performance of a multi-strategy hedge fund benchmarked against the popular buy-and-hold S&P 500 investing approach. The sub-strategies are: residual momentum, value including intangibles, value and momentum, volatility forecasting, and a long short-term memory strategy, the latter two being machine-learning-based, and all investing in the U.S. universe. The combined strategy’s performance is analyzed by three weighting schemes: equal-weight, momentum, and mean-variance, resulting in a gamut of robustness and performance. The combined strategies reap diversification benefits, thereby giving investors a superior risk-reward trade-off compared to the buy-and-hold S&P 500 approach. | pt_PT |
| dc.identifier.tid | 203311620 | pt_PT |
| dc.identifier.uri | http://hdl.handle.net/10362/161183 | |
| dc.language.iso | eng | pt_PT |
| dc.relation | UID/ECO/00124/2013 | pt_PT |
| dc.subject | Systematic trading strategy | pt_PT |
| dc.subject | Momentum | pt_PT |
| dc.subject | Value | pt_PT |
| dc.subject | Volatility forecasting | pt_PT |
| dc.subject | Machine learning | pt_PT |
| dc.subject | Neural networks | pt_PT |
| dc.subject | Quantitative trading strategy | pt_PT |
| dc.title | Analysis of quantitative investment strategies | pt_PT |
| dc.type | master thesis | |
| dspace.entity.type | Publication | |
| rcaap.rights | openAccess | pt_PT |
| rcaap.type | masterThesis | pt_PT |
| thesis.degree.name | A Work Project, presented as part of the requirements for the Award of a Master’s degree in Finance from the Nova School of Business and Economics. | pt_PT |