Testing for Long Memory in REIT Returns

Emmanuel Anoruo and Habtu Braha ()
Additional contact information
Habtu Braha: Coppin State University

International Real Estate Review, 2010, vol. 13, issue 3, 261-281

Abstract: This study examines the long memory properties of composite, equity, mortgage, and hybrid real estate investment trust (REIT) returns by using semi-parametric and wavelet estimators. In particular, this paper applies the GPH semi-parametric estimator, the Haar and the Daubechies wavelet procedures to investigate the long memory properties of REIT returns. The results from the various procedures reveal that composite, equity, mortgage, and hybrid REIT returns are long memory processes with anti- persistence. The existence of long memory suggests that the dynamics which govern the four return series contain predictable components. This finding indicates that the markets for composite, equity, mortgage, and hybrid REITs are inefficient. The fact that these markets are inefficient suggests that investors can devise profitable strategies by using historical data or past information.

Keywords: REITs; Long Memory; Wavelets; Fractional Integration; NAREIT; Daubechies; Haar (search for similar items in EconPapers)
JEL-codes: L85 (search for similar items in EconPapers)
Date: 2010
References: Add references at CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
https://www.gssinst.org/irer/wp-content/uploads/20 ... -in-reit-returns.pdf Full text (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:ire:issued:v:13:n:03:2010:p:261-281

Ordering information: This journal article can be ordered from
Global Social Science Institute, 9200 Corporate Blvd., Suite 420 Rockville, MD 20850
https://www.gssinst.org/gssinst/index.html

Access Statistics for this article

International Real Estate Review is currently edited by Professor Sing Tien Foo and Professor Ko Wang

More articles in International Real Estate Review from Global Social Science Institute Global Social Science Institute, 9200 Corporate Blvd., Suite 420 Rockville, MD 20850.
Bibliographic data for series maintained by IRER Graduate Assistant/Webmaster ().