Investment portfolio tracking using model predictive control

Página do item simplificado
dc.creatorMaisa Kelyde Melo
dc.creatorRodrigo Tomás Nogueira Cardoso
dc.creatorTales Argolo Jesus
dc.creatorGuilherme Vianna Raffo
dc.date.accessioned2025-05-27T13:41:23Z
dc.date.accessioned2025-09-08T22:57:27Z
dc.date.available2025-05-27T13:41:23Z
dc.date.issued2023
dc.identifier.doi10.1002/oca.2937
dc.identifier.issn01432087
dc.identifier.urihttps://hdl.handle.net/1843/82510
dc.languageeng
dc.publisherUniversidade Federal de Minas Gerais
dc.relation.ispartofOptimal Control Applications and Methods
dc.rightsAcesso Restrito
dc.subjectTeoria do controle
dc.subject.othermodel predictive control, optimal control, portfolio tracking and selection
dc.titleInvestment portfolio tracking using model predictive control
dc.typeArtigo de periódico
local.citation.epage274
local.citation.issue1
local.citation.spage259
local.citation.volume44
local.description.resumoThe composition of an investment portfolio aiming to increase the financial returns while reducing the exposure to risk is a topic of growing interest in the world. In this direction, we propose a model predictive control (MPC) strategy in order to optimize the investment portfolio selection taking into account the tracking of a reference portfolio with desired return. In addition, an analysis comparing different sizes of the prediction horizon according to VPH‐MPC (Varying Predictive Horizon‐MPC) and FPH‐MPC (Fixed Predictive Horizon‐MPC) algorithms is conducted. Finally, we propose an optimal control problem using the tracking error as a function of loss of CVaR (Conditional Value at Risk) measurement. Numerical experiments are run based on Brazilian Stock Exchange data. The experimental results are compared with the Markowitz portfolio optimization model, a conventional tracking strategy, and benchmarks from the Brazilian financial market. This comparison indicates a good tracking performance obtained by the proposed MPC in the two versions while satisfying the constraints.
local.publisher.countryBrasil
local.publisher.departmentENG - DEPARTAMENTO DE ENGENHARIA ELETRÔNICA
local.publisher.initialsUFMG
local.url.externahttps://onlinelibrary.wiley.com/doi/10.1002/oca.2937

Arquivos

Licença do pacote

Agora exibindo 1 - 1 de 1
Imagem de Miniatura
Nome:
License.txt
Tamanho:
1.99 KB
Formato:
Plain Text
Descrição:
Baixar

Coleções

Artigo de Periódico

Logo UFMG