Financial information and diverging beliefs

Christopher S. Armstrong (), Mirko S. Heinle () and Irina Luneva ()
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Christopher S. Armstrong: Stanford University, Knight Management Center
Mirko S. Heinle: University of Pennsylvania
Irina Luneva: University of Pennsylvania

Review of Accounting Studies, 2024, vol. 29, issue 3, No 2, 2082-2124

Abstract: Abstract Standard Bayesians’ beliefs converge when they receive the same piece of new information. However, when agents initially disagree and have uncertainty about the precision of a signal, their disagreement might instead increase, despite receiving the same information. We demonstrate that this divergence of beliefs leads to a unimodal effect of the absolute surprise in the signal on trading volume. We show that this prediction is consistent with the empirical evidence using trading volume around earnings announcements of U.S. firms. We find evidence of elevated volume following moderate surprises and depressed volume following more extreme surprises, a pattern that is more pronounced when investors hold more distant prior beliefs and are more uncertain about earnings’ precision. The evidence is consistent with the model where investors disagree about stocks’ expected returns and do not know the precision of earnings as a signal about the firm’s value.

Keywords: Divergence of beliefs; Signal-precision; Trading volume; Uncertainty; Disclosure (search for similar items in EconPapers)
JEL-codes: G12 G14 M41 (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1007/s11142-024-09832-w

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