Downside Risk Aplicado a Carteiras de Ações Brasileiras Durante Período Pandêmico da COVID-19

Authors

DOI:

https://doi.org/10.5540/tcam.2023.024.03.00557

Keywords:

Programação Quadrática, Downside Risk, Pandemia COVID-19

Abstract

O objetivo desse artigo é a formação e a otimização de carteiras de investimento e com ações negociadas na B3 e baseada na teoria de diversificação do modelo de Markowitz e na Programação Quadrática. Considerou-se a minimização do risco da carteira pelo sistema Downside Risk, modelado e implementado computacionalmente. O período de coleta de dados iniciou-se em 2020, ano em que houve uma crise econômica mundial em razão da pandemia da Sars-CoV-2 e consequentes medidas de isolamento que afetaram profundamente a economia. Foram formadas três carteiras que performaram entre Janeiro de 2021 a Março de 2022 e mostraram resultados acima do esperado em comparação à variação percentual do Ibovespa.

References

M. S. Bazaraa, J. J. Jarvis, and H. F. Sherali. Linear Programming and Network Flows. John Wiley & Sons - fourth edition, New York, second edition, 2009.

S. M. S. Carvalho and A. R. L. Oliveira. Interior point methods applied to the predispatch hydroelectric system with simulated modification in the network topology. Magazine IEEE Latin America, 13:143–149, 2015.

S.M.S. Carvalho, C. Lyra, and A. R. L. Oliveira. Predispatch of hydroelectric power systems with modifications in network topologies. Annals of Operations Research - Springer, 2:1 – 19, 2018.

S.M.S. Carvalho and A. R. L Oliveira. Interior point method applied to the predispatch problem of a hydroelectric with scheduled line manipulations. American Journal of Operations Research, 1:266 – 271, 2012.

Bolsa de Valores B3. Disponível em www.b3.com.br. Acesso março/2022.

J. Elton, J. Gruber, and M. Padberg. Simple rules for optimal portfolio selection: The multi group case. Journal of Financial and Quantitative Analysis, 12:329–345, 1977,.

J. Estrada. Mean-semivariance optimization: A heuristic approach. Journal of Applied Finance (Formerly Financial Practice and Education), 18(1), 2008.

H. L. Feyisa. The world economy at covid-19 quarantine: contemporary review.

International journal of economics, finance and management sciences, 8(2):6374, 2020.

Robert Hagstrom. The Warren Buffett Way. 2013.

D. G. Luenberger. Linear and Nonlinear Programming. Addison-Wesley fourth edition, Reading, 2015.

H. Markowitz. Portfolio selection. Journal of Finance, 1, 1952.

Douglas Martin, Andrew Clark, and Christopher Green. Robust Portfolio Construction. Springer, New York, second edition, 2010.

P. L. Meyer. Probabilidade: aplicações a estatística. LTC, Reading, 2009.

Hossein Moosaei and Milan Hladík. Minimum norm solution of the Markowitz mean-variance portfolio optimization model. pages 383–388, 2020.

J. Nocedal and S.J. Wright. Numerical Optimization. Springer, New York, second edition, 2006.

Beatriz Quesada. Revista Exame. Editora e Comércio Valongo Ltda, São Paulo, 1232 edition, 2021.

M. Rubinstein. Markowitz’s portfolio selection: A fifty-year retrospective. The Journal of finance, 57(3):1041–1045, 2002.

W. F. Sharpe. A simplified model for portfolio analysis. Management Science, 9:277–293, 1963.

R. J. Vanderbei. Linear Programming – Foundations and Extensions. Kluwer Academics Publishers - fourth edition, Boston, USA, 2017.

Downloads

Published

2023-07-20

How to Cite

Freitas, C. M., Santiago, Y. V., & Carvalho, S. M. S. (2023). Downside Risk Aplicado a Carteiras de Ações Brasileiras Durante Período Pandêmico da COVID-19. Trends in Computational and Applied Mathematics, 24(3), 557–574. https://doi.org/10.5540/tcam.2023.024.03.00557

Issue

Vol. 24 No. 3 (2023)

Section

Original Article

License

Copyright

Authors of articles published in the journal Trends in Computational and Applied Mathematics retain the copyright of their work. The journal uses Creative Commons Attribution (CC-BY) in published articles. The authors grant the TCAM journal the right to first publish the article.

Intellectual Property and Terms of Use

The content of the articles is the exclusive responsibility of the authors. The journal uses Creative Commons Attribution (CC-BY) in published articles. This license allows published articles to be reused without permission for any purpose as long as the original work is correctly cited.

The journal encourages Authors to self-archive their accepted manuscripts, publishing them on personal blogs, institutional repositories, and social media, as long as the full citation is included in the journal's website version.