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 ()
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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.:
- 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.
- 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.
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