Desenvolvimento de uma ferramenta para backtesting de estratégias de investimento baseadas em ordenação de ativos

The financial market serves as a channel for resource allocation among investors, corporations, and governments, providing liquidity and aiding in asset price determination. Investment strategies, in turn, are structured methods that guide buy and sell decisions, aiming to optimize returns and minimize risks. With technological advancements, individual investors have gained access to tools capable of creating and executing complex strategies, previously exclusive to large corporations. Autonomous agents employ both fundamental and technical analysis to operate continuously while avoiding emotional biases. The effectiveness of these strategies is evaluated through backtesting. This study presents a functional architecture for backtesting strategies, already validated, enabling performance evaluation across varied scenarios and exploring different parameter combinations. The tool manipulates parameters, identifies effective configurations, and ranks strategies in specific asset lists. The experiments conducted demonstrated the system’s flexibility and its ability to support informed decision-making. The results highlight the approach’s potential to capture market dynamics and validate hypotheses clearly and reproducibly, contributing to the adoption of more efficient investment strategies in financial market.