We investigate the impact of firm characteristics on stock returns in the Brazilian financial market, considering a long list of characteristics found be relevant in the U.S. market. Employing Fama-MacBeth regressions, alongside machine learning techniques, we examine over 24 firm-level characteristics. Our findings highlight the stronger influence of price-related metrics, such as momentum, liquidity, size and volatility, over accounting variables. We also explore the robustness of these characteristics through the construction of various portfolios, revealing significant alphas in multiple portfolio construction methods and substantial out-of-sample performance.
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