Título: | PORTFOLIO SELECTION INCORPORATING MACROECONOMIC VIEWS USING BLACK-LITTERMAN MODEL | ||||||||||||
Autor: |
CAMILLO VIANNA CANTINI |
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Colaborador(es): |
DAVI MICHEL VALLADAO - Orientador BETINA DODSWORTH MARTINS FROMENT FERNANDES - Coorientador |
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Catalogação: | 08/FEV/2021 | Língua(s): | ENGLISH - UNITED STATES |
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Tipo: | TEXT | Subtipo: | THESIS | ||||||||||
Notas: |
[pt] Todos os dados constantes dos documentos são de inteira responsabilidade de seus autores. Os dados utilizados nas descrições dos documentos estão em conformidade com os sistemas da administração da PUC-Rio. [en] All data contained in the documents are the sole responsibility of the authors. The data used in the descriptions of the documents are in conformity with the systems of the administration of PUC-Rio. |
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Referência(s): |
[pt] https://www.maxwell.vrac.puc-rio.br/projetosEspeciais/ETDs/consultas/conteudo.php?strSecao=resultado&nrSeq=51467&idi=1 [en] https://www.maxwell.vrac.puc-rio.br/projetosEspeciais/ETDs/consultas/conteudo.php?strSecao=resultado&nrSeq=51467&idi=2 |
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DOI: | https://doi.org/10.17771/PUCRio.acad.51467 | ||||||||||||
Resumo: | |||||||||||||
Black and Litterman proposed a portfolio selection model that blends
investor s views on asset returns with market equilibrium concepts to construct
optimal portfolios. However, the model efficiency relies on the performance
of investors views regarding tradable assets, which is challenging in
practice. Focusing on improving Black-Litterman practical application, this
work consists in providing new allocations based upon views on macroeconomic
factors, which are largely available but not directly tradable. The
main advantage is that predictions on these factors are usually provided
by market players. A case study based on the information disclosed by
the Brazilian Central Bank is presented to test the proposed framework.
The out-of-sample risk-adjusted returns obtained incorporating the players
macroeconomic expectations through the use of the proposed framework
outperformed the traditional mean-variance model as well as the local
benchmark.
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