The Dynamic Informativeness of Scheduled News - Crego, Julio A.; Gider, Jasmin (Management Science, 2024)
We propose a method to identify the informativeness of a future scheduled announcement at the daily level, exploiting the discontinuity it creates in the term structure of option volatility. We implement the strategy in a panel data model to estimate the relation between prior signals and the future announcement. This method allows us to separate substitutes from complements, it can isolate multiple signals within the same quarter, and it can condition on the timing and signal characteristics. We find that analyst forecasts substitute earnings announcement information and that recommendations do not provide extra information on top of forecasts. Moreover, our evidence suggests that insiders sell to avoid uncertainty when the announcement is far away but pull forward earnings information when they trade one month before. This paper was accepted by Eric So, accounting. Funding: This publication is part of the project “Eliciting the properties of private signals” (with project number VI.Veni.201E.029 of the research program VENI SGW, which is (partly) financed by the Dutch Research Council (NWO). Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2023.4970 .