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ETDs @PUC-Rio
Estatística
Título: GOAL-BASED INVESTMENTS: A DYNAMIC STOCHASTIC PROGRAMMING APPROACH
Autor: ANDRE FREDERICO MACIEL GUTIERREZ
Colaborador(es): DAVI MICHEL VALLADAO - Orientador
Catalogação: 13/JUN/2024 Língua(s): ENGLISH - UNITED STATES
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.
Referência(s): [pt] https://www.maxwell.vrac.puc-rio.br/projetosEspeciais/ETDs/consultas/conteudo.php?strSecao=resultado&nrSeq=67019&idi=1
[en] https://www.maxwell.vrac.puc-rio.br/projetosEspeciais/ETDs/consultas/conteudo.php?strSecao=resultado&nrSeq=67019&idi=2
DOI: https://doi.org/10.17771/PUCRio.acad.67019
Resumo:
The aim of this study is to develop an investment policy that minimizes the total contribution required to achieve a long-term financial objective. To achieve this goal, we developed a multi-stage optimization problem that integrates a Hidden Markov Model to capture the stochastic dynamics of asset returns. Unlike conventional portfolio optimization models which are based on unrealistic assumptions, our approach is based on the goal oriented investment framework which provides a more practical and effective solution. In addition, by using the Hidden Markov Model in our optimization process, we obtain a more accurate estimate of the dynamics of asset returns, which translates into better investment decision-making. By using our model, the contribution required to achieve a desired financial goal is minimized through an investment policy that considers current levels of wealth and prevailing economic conditions.
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