Conditional Asset Pricing with Text-Managed Portfolios

Abstract

We construct managed portfolios that exploit information extracted from firms’ earnings call transcripts and examine their asset pricing implications. Returns on these text-managed portfolios correlate with investor sentiment and predict macroeconomic outcomes. Individual stocks’ exposures to the text-managed portfolios explain as much return variation as those to the characteristics-sorted portfolios. Adding earnings call information to firm characteristics increases mean-variance efficiency, though it does not improve stock-level return predictability. Consistent with the insights from Kozak and Nagel (2024) on mean-variance spanning, our results suggest that earnings calls provide information about return covariances beyond what is captured by firm characteristics alone.

Keywords: factor models, mean-variance efficiency, conditioning information, text data

JEL Classification: C11, G11, G12