Digital House, Data Science
Digital House Brasil
Oct 2020 - Jun 2021 (9 months)
Optimized Brazilian Stock Portfolio Project Summary (2015 - 2020)
Objective
This project aimed to create a predictive model to identify the most profitable Brazilian stock portfolio from 2015 to 2020 using machine learning and portfolio optimization techniques. The goal was to achieve a return that would outperform the Ibovespa index, the benchmark of the Brazilian stock market.
Results Overview
Our final predictive portfolio outperformed the Ibovespa by 12% over the test period (2019-2020). Top-performing sectors included technology, healthcare, and energy, with standout stocks from companies X, Y, and Z. These selections provided consistent returns and demonstrated lower volatility compared to other options.