This study addresses the challenges of missing financial data in Brazil and its implications for asset pricing and corporate finance research. We propose combining information from multiple data sources, to generate a comprehensive dataset of firm characteristics. Our approach consists of using a two-step procedure, that leverages cross-sectional and time-series dependencies, to impute the missing data of three different data sources. After that, we compute the first principal component of a PCA of each firm characteristic to generate our combined dataset. Through an empirical analysis of the Brazilian market data, we demonstrate the effectiveness of our approach in mitigating the impact of missing data. Our findings highlight the importance of considering multiple data sources and implementing robust imputation methods to enhance the reliability and accuracy of financial research in Brazil.
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