This study investigates the long-horizon performance of open-market stock repurchases for real estate investment trusts (REITs). We develop a new methodology to model the autocorrelation of monthly returns into long-horizon buy-and-hold abnormal return estimators. Serial correlation can introduce bias (autocorrelation bias) because the bid-ask bounce may affect monthly returns for sample firms and non-sample firms in a different fashion. Previous long-horizon event studies have overlooked this source of bias. There is compelling evidence that the market underreacts to the stock repurchase announcements. The evidence holds for different measures of the variance and the effects of cross-correlation of abnormal returns. Results are also robust to the traditional buy-and-hold abnormal return and the wealth relative estimators. We investigate the nature of the underreaction and find strong support for the undervaluation hypothesis. Copyright 2005 by the American Real Estate and Urban Economics Association
Download Info
To download:
If you experience problems downloading a file, check if you have the
proper application to
view it first. Information about this may be contained
in the File-Format links below. In case of further problems read
the IDEAS help
file. Note that these files are not on the IDEAS
site. Please be patient as the files may be large.
As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.
Publisher Info
Article provided by American Real Estate and Urban Economics Association in its journal Real Estate Economics.
Volume (Year): 33 (2005) Issue (Month): 2 (06) Pages: 351-380 Download reference. The following formats are available: HTML,
plain text,
BibTeX,
RIS (EndNote),
ReDIF
For technical questions regarding this item, or to correct its listing, contact: (Christopher F. Baum).
Related research
Keywords:
Cited by: (explanations, Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.)