{"title":"Financial Information and Diverging Beliefs","authors":"C. Armstrong, M. Heinle, Irina Maxime Luneva","doi":"10.2139/ssrn.3780824","DOIUrl":null,"url":null,"abstract":"This paper theoretically and empirically shows that, when investors are uncertain about how precise is the signal they receive, their beliefs may further diverge after they receive the same piece of information. We test this prediction using trading volume around quarterly earnings announcements of public U.S. firms. Under signal-precision uncertainty, trading volume increases for intermediate levels of earnings surprise and dampens for extreme levels. Dampening is more pronounced when signal-precision uncertainty is high. We propose a novel measure of earnings-announcement-precision uncertainty and show that, first, S-shaped earnings response coefficient and, second, trading volume's dampening for extreme signals are more pronounced for high levels of earnings-announcement-precision uncertainty. Our findings might lead researchers to reconsider their widespread usage of trading volume as a simple proxy for market liquidity.","PeriodicalId":11757,"journal":{"name":"ERN: Other Microeconomics: General Equilibrium & Disequilibrium Models of Financial Markets (Topic)","volume":"88 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2021-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"ERN: Other Microeconomics: General Equilibrium & Disequilibrium Models of Financial Markets (Topic)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2139/ssrn.3780824","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
This paper theoretically and empirically shows that, when investors are uncertain about how precise is the signal they receive, their beliefs may further diverge after they receive the same piece of information. We test this prediction using trading volume around quarterly earnings announcements of public U.S. firms. Under signal-precision uncertainty, trading volume increases for intermediate levels of earnings surprise and dampens for extreme levels. Dampening is more pronounced when signal-precision uncertainty is high. We propose a novel measure of earnings-announcement-precision uncertainty and show that, first, S-shaped earnings response coefficient and, second, trading volume's dampening for extreme signals are more pronounced for high levels of earnings-announcement-precision uncertainty. Our findings might lead researchers to reconsider their widespread usage of trading volume as a simple proxy for market liquidity.