Palavras-chave
portfólio neutro
Filtro de Kalman
modelo multifatorial de precificação de ativos
Como Citar
Resumo
Objetivo – Este estudo examina uma estratégia de portfólio zero-beta que considera as incertezas nos retornos esperados e nos betas, visando melhorar o desempenho dos investimentos por meio da incorporação da incerteza dos parâmetros no processo de otimização.
Referencial Teórico – A pesquisa é fundamentada na teoria moderna de portfólio e na otimização robusta, utilizando o modelo multifatorial de precificação de ativos de Chen, Roll e Ross (1986). O estudo emprega o Filtro de Kalman para a estimação dinâmica dos betas junto com suas incertezas e incorpora as previsões de analistas para avaliar os retornos esperados e suas incertezas associadas.
Metodologia – O estudo constrói dois tipos de portfólio zero-beta: um portfólio long-short estocástico que maximiza a razão entre o retorno esperado e a incerteza dos parâmetros, e um portfólio long-short normal que foca exclusivamente na maximização do retorno esperado. O desempenho do portfólio é avaliado com dados de 2015 a 2022.
Resultados – Os resultados indicam que os portfólios long-short estocásticos superam os portfólios normais em várias métricas de desempenho. Especificamente, eles demonstram retornos realizados mais altos, menores perdas máximas (drawdowns) e índice de Sharpe superior. Além disso, a abordagem estocástica apresenta previsões mais precisas, com um erro quadrático médio significativamente menor.
Implicações Práticas e Sociais da Pesquisa – Os achados fornecem insights para investidores, gestores de fundos e profissionais que buscam melhorar a estabilidade e o desempenho do portfólio sob incerteza. No entanto, a dependência das estimativas dos analistas deve ser abordada com cautela, pois podem ocorrer desvios em relação aos valores esperados.
Contribuições – Este estudo contribui para a literatura existente ao validar empiricamente os benefícios da incorporação da incerteza dos parâmetros na otimização de portfólios.
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