Macro Factors' Based Neural Networks to Predict House Price Index in Fars Province

The purpose of this paper is to investigate the influence of macro factors on the house price and then to predict house price in Fars province (in Iran) with the aid of neural networks. The data set consists of 13 years of information was taken from Iran's statistical yearbook of 2006. The information includes house price index, per capita income, inflation rate, liquidity, bank facilities to housing sector, and the total price of the traded shares in Iran stock exchange. In order to compensate the lack of data, nonlinear interpolation methods were employed to create some data points. The results presented in this paper support the potential of neural network for house price prediction with a consideration of macro factors.

کلیدواژه ها:

house price ، neural network ، macro factors