Study On Influencing Factors Of Real Estate Price And Its Prediction

As the barometer of the real estate industry, the the price of real estate is not only an important goal of the government macroeconomic regulation and control indexes, but also important to the people’s livelihood issues concerned by the society from all walks of life. Since the commercial housing reform, China’s real estate industry has developed rapidly, effectively promoting the rapid development of national economy, and become one of the pillar industries of national economy. At the same time, the soaring real estate prices also triggered social resource misallocation, imbalance of industrial structure, and other different kinds of economic and social problems. Since2005, in order to regulate the real estate market, and effectively suppress prices from rising too fast, the government introduced a series of real estate regulation policy. However, the trend of house prices rose sharply still did not get effective control. This is due to the incorrect direction of control measures and insufficient control power. Besides, the complex influence factors of real estate prices make the control difficult. Therefore, to study the influence factors of real estate prices and to forecast the future development trend of housing prices is very important.First of all, using statistical methods such as the HP filter, taking Shanghai as an example, the paper analyzes he shape of the Shanghai housing prices and volatility between January1999and March1999, depicting the deviation degree of real house prices and the equilibrium price. And then found that prices are constantly in the volatility in Shanghai, but the overall trend is rising, with obvious increase rigidity.Secondly, on the basis of theoretical analysis of the influence factors of real estate price, taking use of Shanghai monthly data from January1999to March1999, the grey correlation degree and the VAR model are used for quantitative analysis. The empirical results show that the main factors affecting the housing prices come from the economic fundamentals. While the demand for housing, bank credit, land price is also the important driving factors of high prices. In addition, real estate prices and inflation, stock market also has an impact on housing prices. Again, according to above research, choosing three housing forecast models, namely, time series forecasting model, grey prediction model, BP neural network model to forecast the future development trend of housing prices. By comparing the predicted effect of three models, we found that the prediction effect of BP neural network model based on multiple factors is superior to the VAR (2) model and grey forecasting model. Meanwhile, the prediction results show that in the coming year, the trend of the real estate prices will continue to rlse.Finally, on the basis of summarizing the full text, we put forward some policy suggestions from four aspects, for instance, the adjustment of economic structure, real estate finance and land supply, adjusting the real estate supply and demand imbalance.We hope that by taking these measures, the trend of house price can become more rational and the real estate market develop healthy.