Modeling Property Prices Using Neural Network Model for Hong Kong
This paper develops a forecasting model of residential property prices for Hong Kong using an artificial neural network approach. Quarterly time-series data are applied for testing and the empirical results suggest that property price index, lagged one period, rental index, and the number of agreements for sales and purchases of units are the major determinants of the residential property price performance in Hong Kong. The results also suggest that the neural network methodology has the ability to learn, generalize, and converge time series.
Volume (Year): 7 (2004)
Issue (Month): 1 ()
|Contact details of provider:|| Postal: |
Web page: http://www.asres.org/
|Order Information:|| Postal: Asian Real Estate Society, 51 Monroe Street, Plaza E-6, Rockville, MD 20850, USA|
Web: http://www.asres.org/ Email:
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.:
- Lennart Berg, 2005. "Price Indexes For Multi-dwelling Properties In Sweden," Journal of Real Estate Research, American Real Estate Society, vol. 27(1), pages 47-82.
- DiPasquale Denise & Wheaton William C., 1994. "Housing Market Dynamics and the Future of Housing Prices," Journal of Urban Economics, Elsevier, vol. 35(1), pages 1-27, January.
- Chan, Hing Lin & Lee, Shu Kam & Woo, Kai Yin, 2001. "Detecting rational bubbles in the residential housing markets of Hong Kong," Economic Modelling, Elsevier, vol. 18(1), pages 61-73, January.
- Jonathan Jingsheng Shi, 1999. "A neural network based system for predicting earthmoving production," Construction Management and Economics, Taylor & Francis Journals, vol. 17(4), pages 463-471.
- A. H. Boussabaine & A. P. Kaka, 1998. "A neural networks approach for cost flow forecasting," Construction Management and Economics, Taylor & Francis Journals, vol. 16(4), pages 471-479.
When requesting a correction, please mention this item's handle: RePEc:ire:issued:v:07:n:01:2004:p:121-138. 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: (IRER Graduate Assistant/Webmaster)
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.