ANDRE FREDERICO MACIEL GUTIERREZ
Data: 27/02/2024, 10h, via zoom
Sala Zoom: https://meet.google.com/dwx-yacd-qpz
Orientador: Davi Michel Valladão | PUC-Rio
Resumo:
The purpose of this study is to develop an investment policy that minimizes the total contribution necessary to reach a long-term financial goal while accounting for stochastic programming that incorporates Markovian dynamics of asset returns. To achieve this objective we develop a multi-stage optimization problem that incorporates a Hidden Markov Model.
Unlike conventional portfolio optimization techniques that rely on unrealistic assumptions, our approach is grounded in the goal-oriented investment framework that provides a more practical and effective solution. In addition, by using the Hidden Markov Model in our optimization process, we obtain a more accurate estimation of asset return dynamics, which translates into more efficient investment modeling.
Collectively, these attributes yield a simple yet robust tool that empowers investors to make personalized and informed investment decisions. By employing our model, the necessary contribution to achieve a desired financial goal is minimized through an investment policy that accounts for the current stage of wealth and prevailing economic conditions.