Balanceamento de carteira de renda variável com base na Teoria Moderna do Portfólio

• Autor(a) principal: Real, João Paulo Garcez
• Data de Publicação: 2023
• Tipo de documento: Trabalho de conclusão de curso
• Idioma: por
• Título da fonte: Repositório Institucional da UNESP
• Texto Completo: https://hdl.handle.net/11449/252808
• topic: Portfolio management; Renda; Risco; Ações (Finanças); Títulos imobiliários

The Brazilian population's engagement in investments related to stocks and real estate funds has been growing each year, given the more than 10-fold increase in registered “Cadastro de Pessoa Física” (CPF) on B3 between 2015 and 2022. This study employs the Markowitz optimization model to optimize 11,400 unique portfolios composed of three stocks from different sectors and one real estate fund. The portfolios were determined by combining 20 different stocks, two from each sector, and 10 real estate funds. A total of 10,000 simulations of asset weights were conducted for each portfolio, with a maximum limit of 70% for the weight of any single asset. Asset selection criteria included liquidity, absence of bankruptcy cases, and sector diversification. The historical stock price data used to feed the model spanned from 2015 to 2021. The performance measurement period for the portfolios was the year 2022, and the appreciation or depreciation of the portfolios was calculated, taking into account dividend payments during the period. The results demonstrated that the model effectively mitigated portfolio risk, such that portfolios with higher expected volatility exhibited greater dispersion in portfolio appreciation or depreciation. However, the model did not exhibit the same efficiency in the relationship between expected return and portfolio appreciation. Additionally, through linear regression of the results and dispersion calculation, it was observed that a higher calculated simplified Sharpe ratio for the portfolio corresponded to lower dispersion. Among the top 100 portfolios with the highest calculated index, only three experienced portfolio depreciation.