Alocação ótima de portfóliosuma abordagem quântica para o mercado acionário brasileiro

Resumo

This study investigates the efficacy of quantum algorithms Variational Quantum Eigensolver (VQE) and Quantum Approximate Optimization Algorithm (QAOA) in the context of portfolio optimization, comparing them in terms of Sharpe Ratio with the solution of the classical meanvariance model and the broad market index (IBOVESPA). The research conducts backtesting of strategies using monthly data from the Brazilian stock market, covering the period from 2007 to 2023, and includes analyses on both real quantum computers and simulators. The study reveals that quantum algorithms prove to be competitive, outperforming the mean-variance model in terms of Sharpe Ratio with statistical significance, and showing a lower index of losses. These results indicate that quantum computing can contribute innovative and efficient solutions within the field of finance, and open new perspectives for future research on the application of quantum computing in the investment management industry. The study also addresses the current challenges of quantum computing, including the limited availability of devices, long wait times in queues, and backends with a reduced number of QUBITS.

Ficha do documento

Tipo

Dissertação

Ano

2024

Instituição

Fundação Getulio Vargas

Fonte

Repositório da FGV

Idioma

Português

Acesso

Acesso aberto

Identificador

oai:repositorio.fgv.br:10438/35233

Temas

Economia

Palavras-chave

Otimização de portfóliosComputação quânticaAçõesVQEQAOAMVPortfolio optimizationQuantum computingStocksEconomiaFinançasAções (Finanças)Investimentos - AnáliseAlocação de ativos