Modeling Property Prices Using Neural Network Model for Hong Kong
作者： G Runeson , J Ge
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摘要: 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 testing and the empirical results suggest that price index, lagged one period, rental number agreements sales purchases units major determinants performance in Kong. The also methodology has ability to learn, generalize, converge time series.
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