Value investing including intangibles

Detalhes bibliográficos
Autor(a) principal: Gerla, Micha Sebastiaan
Data de Publicação: 2022
Tipo de documento: Dissertação
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10362/161068
Resumo: 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
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spelling Value investing including intangiblesValue investingGrowth investingHmlIhmlIntangiblesHigh Ii industriesLow Ii industriesInvestment strategyDomínio/Área Científica::Ciências Sociais::Economia e GestãoThis 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 approachRUNGerla, Micha Sebastiaan2023-12-11T12:59:29Z2023-01-182022-12-162023-01-18T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisapplication/pdfhttp://hdl.handle.net/10362/161068TID:203311655enginfo:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2024-03-11T05:43:48Zoai:run.unl.pt:10362/161068Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T03:58:19.198820Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv Value investing including intangibles
title Value investing including intangibles
spellingShingle Value investing including intangibles
Gerla, Micha Sebastiaan
Value investing
Growth investing
Hml
Ihml
Intangibles
High Ii industries
Low Ii industries
Investment strategy
Domínio/Área Científica::Ciências Sociais::Economia e Gestão
title_short Value investing including intangibles
title_full Value investing including intangibles
title_fullStr Value investing including intangibles
title_full_unstemmed Value investing including intangibles
title_sort Value investing including intangibles
author Gerla, Micha Sebastiaan
author_facet Gerla, Micha Sebastiaan
author_role author
dc.contributor.none.fl_str_mv RUN
dc.contributor.author.fl_str_mv Gerla, Micha Sebastiaan
dc.subject.por.fl_str_mv Value investing
Growth investing
Hml
Ihml
Intangibles
High Ii industries
Low Ii industries
Investment strategy
Domínio/Área Científica::Ciências Sociais::Economia e Gestão
topic Value investing
Growth investing
Hml
Ihml
Intangibles
High Ii industries
Low Ii industries
Investment strategy
Domínio/Área Científica::Ciências Sociais::Economia e Gestão
description 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
publishDate 2022
dc.date.none.fl_str_mv 2022-12-16
2023-12-11T12:59:29Z
2023-01-18
2023-01-18T00:00:00Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/masterThesis
format masterThesis
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/10362/161068
TID:203311655
url http://hdl.handle.net/10362/161068
identifier_str_mv TID:203311655
dc.language.iso.fl_str_mv eng
language eng
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instacron:RCAAP
instname_str Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
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reponame_str Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
collection Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
repository.name.fl_str_mv Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
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