Commodity Housing Price Study In Chengdu On Grey System Theory

House is the necessity in human life. Improving living condition has become one of the most important things, with the increasing of economy, raising the standard of living and accelerating of urbanization. Strong demand has the commodity housing price doubled in some cities for a few years. So commodity housing price is hot topic in everyday life. Commodity housing price is the key of economic development in every city, the core problem in housing market, the indicator of the government macroscopic management and adjusting control and the important basis of investment decision making for developers. To stabilize the commodity housing price becomes critical. The fluctuations of commodity housing price relates to everyone's basic benefits. Therefore, starting with market, to study the factors affecting housing price change, to find the relations of them by quantitative analysis and to forecast scientifically the price change are very important to the government macroscopic management ,and can promote the healthy development of housing market in the future.Grey system theory is major research tool and method of this paper. Firstly, the paper analyses the factors that affect commodity housing price change. Secondly, adopting to cost theory, the operation of the market mechanism and supply and demand theory, the paper discusses the form and change course of housing price. Thirdly, the paper analyses the influential factors of commodity housing price change in Chengdu. Finally, by the use of Grey System theory, the paper analyses the relation between the influential factors, finds the main factors affecting commodity housing price in Chengdu, and forecasts the commodity housing price in Chengdu by establishing the Grey-Markov Forecast Model. According to the research of this paper, it shows that the main factors affecting commodity housing price in Chengdu are per capita disposable income, GDP and urbanization rate. And the Grey system theory application in commodity housing price is reliable and practical. By contracting, the forecasting result of the Grey-Markov Forecast Model is more exact than that by GM(1,1) Forecast Model.