@article{3234cfb5ad4e4169922870cfd5a01b5b,
title = "Economic persistence, earnings informativeness, and stock return regularities",
abstract = "We propose a simple framework for understanding accounting-based stock return regularities. A firm{\textquoteright}s accounting reports provide noisy information about hidden economic states that evolve according to a Markov process. In response to the accounting reports, a representative Bayesian investor forms beliefs about the underlying state and hence the value of the firm. For a population of such firms, the model provides predictions consistent with two sets of well-documented regularities: (i) the market reaction to an earnings announcement that ends a string of consecutive earnings increases and (ii) the return predictabilities based on accruals and book-tax differences. The model also yields novel cross-sectional predictions about the distinct roles of economic persistence and earnings informativeness. We confirm these predictions through empirical tests.",
author = "Kai Du and Steven Huddart",
note = "Funding Information: We are grateful to Stefan Reichelstein (the editor) and two anonymous reviewers for numerous helpful comments. We thank Jianhong Chen, Lei Dong, Pingyang Gao, Robert G{\"o}x, Jeremiah Green, Tina Huynh, Lawrence Jin, Rick Laux, Jonathan Lewellen, Stefan Lewellen, Jia Li, Pierre Liang, John Liechty, Lyndon Orton, Hong Qu, Jalal Sani, Jack Stecher, Mark Tippett (discussant), Biqin Xie, and workshop participants at Pennsylvania State University, University of Southern Denmark, Michigan State University, Carnegie Mellon University, University of Waterloo, University of Zurich, the 10th MEAFA Research Meeting at University of Sydney, and Munich School of Management for helpful comments. We especially acknowledge the input of Lingzhou Xue on an earlier project related to the paper. All errors are our own. Financial support from Penn State{\textquoteright}s Smeal College of Business is gratefully acknowledged. An earlier version of this paper was titled “Reporting systems, investor learning, and stock return regularities”. Funding Information: We are grateful to Stefan Reichelstein (the editor) and two anonymous reviewers for numerous helpful comments. We thank Jianhong Chen, Lei Dong, Pingyang Gao, Robert G?x, Jeremiah Green, Tina Huynh, Lawrence Jin, Rick Laux, Jonathan Lewellen, Stefan Lewellen, Jia Li, Pierre Liang, John Liechty, Lyndon Orton, Hong Qu, Jalal Sani, Jack Stecher, Mark Tippett (discussant), Biqin Xie, and workshop participants at Pennsylvania State University, University of Southern Denmark, Michigan State University, Carnegie Mellon University, University of Waterloo, University of Zurich, the 10th MEAFA Research Meeting at University of Sydney, and Munich School of Management for helpful comments. We especially acknowledge the input of Lingzhou Xue on an earlier project related to the paper. All errors are our own. Financial support from Penn State?s Smeal College of Business is gratefully acknowledged. An earlier version of this paper was titled ?Reporting systems, investor learning, and stock return regularities?. Publisher Copyright: {\textcopyright} 2020, Springer Science+Business Media, LLC, part of Springer Nature.",
year = "2020",
month = dec,
day = "1",
doi = "10.1007/s11142-020-09531-2",
language = "English (US)",
volume = "25",
pages = "1263--1300",
journal = "Review of Accounting Studies",
issn = "1380-6653",
publisher = "Springer New York",
number = "4",
}