Estimating serial cross-correlation in real estate returns
Appraisal smoothing understates the true volatility of real estate returns, and consequently affects asset allocation decisions. The high level of smoothing observed in commercial property index returns can be shown to be largely influenced by the effect of serial cross-correlation. This paper examines this phenomenon by analysing the time series properties of a sample of individual property returns using the generalized autoregressive conditional heteroskedasticity (GARCH) model. The autoregressive conditional heteroskedasticity (ARCH) model, proposed by Engle (1982) and Bollerslev (1986), is used to characterize time series data that exhibits clustering in the residuals. The time-varying conditional variance in ARCH models is often used as a measure of intertemporal risk. We use this property to analyse the cross-correlation coefficients of a sample of properties. Our results suggest that there is positive skewness in the serial cross-correlations. This is consistent with a process that would generate high serial correlation at the index level. We demonstrate that serial cross-correlation can be used as a proxy of the proportion of sticky values in an index. The results indicate that serial cross-correlation is time varying and positively skewed. Copyright © 2001 John Wiley & Sons, Ltd.
Volume (Year): 22 (2001)
Issue (Month): 7 ()
|Contact details of provider:|| Web page: http://www3.interscience.wiley.com/cgi-bin/jhome/7976|
References listed on IDEAS
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.:
- David Geltner, 1989. "Bias in Appraisal-Based Returns," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 17(3), pages 338-352.
- Geltner, David Michael, 1991. "Smoothing in Appraisal-Based Returns," The Journal of Real Estate Finance and Economics, Springer, vol. 4(3), pages 327-45, September.
- Ross, Stephen A & Zisler, Randall C, 1991. "Risk and Return in Real Estate," The Journal of Real Estate Finance and Economics, Springer, vol. 4(2), pages 175-90, June.
- Carmelo Giaccotto & John Clapp, 1992. "Appraisal-Based Real Estate Returns under Alternative Market Regimes," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 20(1), pages 1-24.
- Lawrence R. Glosten & Ravi Jagannathan & David E. Runkle, 1993.
"On the relation between the expected value and the volatility of the nominal excess return on stocks,"
157, Federal Reserve Bank of Minneapolis.
- Glosten, Lawrence R & Jagannathan, Ravi & Runkle, David E, 1993. " On the Relation between the Expected Value and the Volatility of the Nominal Excess Return on Stocks," Journal of Finance, American Finance Association, vol. 48(5), pages 1779-1801, December.
When requesting a correction, please mention this item's handle: RePEc:wly:mgtdec:v:22:y:2001:i:7:p:381-387. See general 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: (Wiley-Blackwell Digital Licensing)or (Christopher F. Baum)
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If references are entirely missing, you can add them using this form.
If the full references list an item that is present in RePEc, but the system did not link to it, you can help with this form.
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your profile, as there may be some citations waiting for confirmation.
Please note that corrections may take a couple of weeks to filter through the various RePEc services.