An Artificial Neural Network and Entropy Model for Residential Property Price Forecasting in Hong Kong

2008 ◽  
Vol 25 (4) ◽  
pp. 321-342 ◽  
Author(s):  
K. C. Lam ◽  
C. Y. Yu ◽  
K. Y. Lam
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Hong Kong ◽  
Residential Property ◽  
Price Forecasting ◽  
Entropy Model ◽  
Property Price ◽  
Artificial Neural

International Real Estate Review

2004 ◽  
Vol 7 (1) ◽  
pp. 121-138
Author(s):  
Xin J. Ge ◽  
◽  
G. Runeson ◽  
Keyword(s):  
Neural Network ◽  
Time Series ◽  
Hong Kong ◽  
Time Series Data ◽  
Series Data ◽  
Residential Property ◽  
Neural Network Approach ◽  
Price Performance ◽  
The Neural Network ◽  
Property Price

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.

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