<p>The rapid advancement of artificial intelligence, exemplified by tools such as Chat-GPT, has significantly transformed the landscape of stock market analysis. This paper aims to leverage these technological developments to predict the daily returns of the Ibovespa by utilizing predictors derived from technical indicators and sentiment indices extracted from textual data and Chat-GPT-generated sentiment indices. Our findings reveal that the Chat-GPT-based sentiment index does not enhance the out-of-sample prediction of Ibovespa returns. Conversely, the sentiment index derived from financial news data, utilizing a time-varying dictionary, demonstrates improved out-of-sample predictive accuracy for the Ibovespa. Notably, the predictor based on the technical indicator Accumulation–Distribution (AD) outperforms the historical average benchmark, establishing itself as the superior forecasting model. This study contributes to the ongoing discourse on the integration of artificial intelligence and traditional financial analysis, offering insights into the efficacy of sentiment indices and technical indicators for forecasting stock market returns in the Brazilian context.</p>