Data science applications to investment management: leveraging in alternative data sets and unconventional tetchniques to enhance portfolio performance.
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- dc.contributor.author Ayala González, Jonathan
- dc.date.accessioned 2020-11-20T12:08:24Z
- dc.date.available 2020-11-20T12:08:24Z
- dc.date.issued 2020
- dc.description Màster universitari en Banca i Finances (UPF Barcelona School of Management) Curs 2019-2020ca
- dc.description Mentor: Luz Parrondo
- dc.description.abstract “On the other hand, investing is a unique kind of casino—one where you cannot lose in the end, so long as you play only by the rules that put the odds squarely in your favour.” (Benjamin Graham - The Intelligent Investor, 1949). This paper provides a theoretical and practical approach to the uses of data science as a mechanism to support investment decisions. Although data science applications in investment management are quite varied and numerous, this paper focuses on a data typology currently being widely used by large investment institutions worldwide: The Alternative Data Sets. Concretely, the focus is put on the uses of consumption data and 10-K filings as valuable sources of information to support investment decisions. Overall, results show that, despite data science and algorithm-based tools are essential to process and understand underlying business information, these techniques are not by themselves sufficient to develop a consistent investment strategy but, instead, can be employed as very useful systems to boost the understanding of the business that underlays every stock in the market.ca
- dc.format.mimetype application/pdf*
- dc.identifier.uri http://hdl.handle.net/10230/45818
- dc.language.iso engca
- dc.rights This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International Licenseca
- dc.rights.accessRights info:eu-repo/semantics/openAccessca
- dc.rights.uri https://creativecommons.org/licenses/by-nc-nd/4.0/ca
- dc.subject.other Treball de fi de màster – Curs 2019-2020ca
- dc.title Data science applications to investment management: leveraging in alternative data sets and unconventional tetchniques to enhance portfolio performance.ca
- dc.type info:eu-repo/semantics/masterThesisca