Testing The Predictive Power Of Dividend Yields
AbstractThis paper reexamines the ability of dividend yields to predict long-horizon stock returns. The authors use the bootstrap methodology, as well as simulations, to examine the distribution of test statistics under the null hypothesis of no forecasting ability. These experiments are constructed so as to maintain the dynamics of regressions with lagged dependent variables over long horizons. They find that the empirically observed statistics are well within the 95 percent bounds of their simulated distributions. Overall there is no strong statistical evidence indicating that dividend yields can be used to forecast stock returns. Copyright 1993 by American Finance Association.
Download InfoTo our knowledge, this item is not available for download. To find whether it is available, there are three options:
1. Check below under "Related research" whether another version of this item is available online.
2. Check on the provider's web page whether it is in fact available.
3. Perform a search for a similarly titled item that would be available.
Bibliographic InfoPaper provided by Columbia - Graduate School of Business in its series Papers with number fb-_90-12.
Length: 22 pages
Date of creation: 1990
Date of revision:
Contact details of provider:
Postal: U.S.A.; COLUMBIA UNIVERSITY, GRADUATE SCHOOL OF BUSINESS, PAINE WEBBER , New York, NY 10027 U.S.A
Phone: (212) 854-5553
Web page: http://www.columbia.edu/cu/business/
More information through EDIRC
econometric models ; long term ; capital gains ; time factor;
Other versions of this item:
You can help add them by filling out this form.
CitEc Project, subscribe to its RSS feed for this item.
This item has more than 25 citations. To prevent cluttering this page, these citations are listed on a separate page. reading list or among the top items on IDEAS.Access and download statisticsgeneral information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Thomas Krichel).
If references are entirely missing, you can add them using this form.