Dividend Smoothing and Predictability
Long Chen (),
Zhi Da () and
Richard Priestley ()
Additional contact information
Long Chen: Cheung Kong Graduate School of Business, 100738 Beijing, China; and Olin School of Business, Washington University in St. Louis, St. Louis, Missouri 63130
Zhi Da: Mendoza College of Business, University of Notre Dame, Notre Dame, Indiana 46556
Management Science, 2012, vol. 58, issue 10, 1834-1853
Abstract:
The relative predictability of returns and dividends is a central issue because it forms the paradigm to interpret asset price variation. A little studied question is how dividend smoothing, as a choice of corporate policy, affects predictability. We show that even if dividends are supposed to be predictable without smoothing, dividend smoothing can bury this predictability. Because aggregate dividends are dramatically more smoothed in the postwar period than before, the lack of dividend growth predictability in the postwar period does not necessarily mean that there is no cash flow news in stock price variations; rather, a more plausible interpretation is that dividends are smoothed. Using two alternative measures that are less subject to dividend smoothing--net payout and earnings--we reach the consistent conclusion that cash flow news plays a more important role than discount rate news in price variations in the postwar period. This paper was accepted by Wei Xiong, finance.
Keywords: dividend-price ratio; earning-price ratio; dividend growth; earnings growth; return; predictability; dividend smoothing (search for similar items in EconPapers)
Date: 2012
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (64)
Downloads: (external link)
http://dx.doi.org/10.1287/mnsc.1120.1528 (application/pdf)
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:inm:ormnsc:v:58:y:2012:i:10:p:1834-1853
Access Statistics for this article
More articles in Management Science from INFORMS Contact information at EDIRC.
Bibliographic data for series maintained by Chris Asher ().