The Research On The Commercial Housing Price And Its Impact Factors In The Region Of Kunming

The most intuitive expression of the real estate market is the market price, different factors, different regions and different markets which impact on prices are bound to be very different, especially the residential price which is closely linked with people. In recent years, the price of the real estate has been going up, making it to be the focus in the crowd, and the average price of residential real estate is always selected by the academia to be the wind vane which represents the development degree of the commercial housing market.Combining with the current situation of the real estate market in Kunming,13indicators were selected as the representative from a number of factors which affect the housing prices in this city, through the establishment of gray correlation model to screen and analyze as many as factors, then aided with the MATLAB programming to calculate the absolute correlation degree and the relative correlation degree between each factor and the commercial housing price, finally by compositely considering to determine the comprehensive correlation of each factor, and then judged the effect sizes and sequence. According to the results of the comprehensive correlation sort, seven top-ranking factors have been selected to establish GM (1,8) model which is used to predict the real estate price of Kunming from2005to2011, and it has been proved that GM (1,8) model can be used in practice for the error obtained from the residual test and after test between the predict value and actual value is very small.During the latter forecasting application, although the predictive value of each index obtains from the improved GM(1,1,x(0)) model, the accumulated error can’t be ignored, so the GM model has been improved again to increase the prediction accuracy. The Polynomial Curve Fitting from MATLAB is used to predict each indicator, with the aid of the BP neural network’ training and amending the predictive value of indicators which shall be brought into GM model again after amending, it could control the error to a large extent and obtain a more valuable, more convincing conclusion, and it also makes up for the short that people can’t use the mathematic formula to describe the relation between the price and economically variables; Finally, a short-term forecasting is given to the Kunming’ commercial housing price which is based on the different situations of future market volatility. Kunming’ regional housing prices and its impact factors are analyzed objectively in the conclusion part which also contains some policy recommendations from the macro control level. This study provides some guidance and scientific reference for the investment decision of the real estate in Kunming.