Modeling Property Prices Using Neural Network Model for Hong Kong

Asian Real Estate Society
Publication Type:
Journal Article
International Real Estate Review, 2004, 7 (1), pp. 121 - 138
Issue Date:
Full metadata record
Files in This Item:
Filename Description Size
2006006564OK.pdf1.13 MB
Adobe PDF
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.
Please use this identifier to cite or link to this item: