This conference paper presents the analysis and visualization of the "Swing Direto V3" swing trading strategy through an interactive application developed in Python using Streamlit and Plotly. The study evaluates historical backtesting results obtained from highly liquid stocks traded on the Brazilian stock exchange (B3) between 2019 and 2024. Performance metrics such as Compound Annual Growth Rate (CAGR), Win Rate, Payoff Ratio, and Maximum Drawdown are analyzed and displayed through interactive dashboards. The platform also incorporates Monte Carlo simulations to assess robustness and risk. Results indicate consistent performance and demonstrate the usefulness of open-source tools for quantitative trading research and financial data visualization. This work was developed within the QuantInovarum research group at the Federal University of Rio Grande do Norte (UFRN), Brazil. This work was presented at the VIII Semana de Ciências e Tecnologia da Escola de Ciências e Tecnologia (ECT/UFRN), Federal University of Rio Grande do Norte (UFRN), Brazil. The extended abstract was accepted for publication in the conference proceedings.