Credit Information in Earnings Calls
61 Pages Posted: 9 Aug 2022 Last revised: 25 Sep 2022
Date Written: July 27, 2022
We develop a novel technique to extract credit-relevant information from the text of quarterly earnings calls. This information is not spanned by fundamental or market variables and forecasts future credit spread changes. One reason for such forecastability is that our text-based measure predicts future credit spread risk and firm profitability. More firm- and call-level complexity increase the forecasting power of our measure for spread changes. Out-of-sample portfolio tests show the information in our measure is valuable for investors. Both results suggest that investors do not fully internalize the credit-relevant information contained in earnings calls.
Keywords: Corporate credit, credit default swaps, return forecasting, NLP
JEL Classification: G11, G12, G14
Suggested Citation: Suggested Citation