Comparative Reaearch On The Residential Price An In Urumqi Based On The Gray Forecast And GARCH Model

With the rapid development of China's economy,the real estate industry plays an extremely important role in the process of economic development.It has become an important pillar of our economy.Housing prices are the most intuitive indicator of the real estate market.How to stabilize and control of housing prices is the focus of attention from all walks of life,but also an important task of macro-control of real estate in China.Urumqi is the capital city of Xinjiang.In recent years,Under the guidance of some policies issued by the government,Urumqi real estate market has maintained a rapid,healthy and orderly development trend,demand and supply of real estate is booming,commodity housing prices have an obvious upward trend.What caused the continued rise in commodity housing prices,This paper makes a quantitative analysis of this problem and makes a forecast study on the price of commodity housing in Urumqi.At the same time,the prediction model is studied.It is expected to build a prediction model which is suitable for the price prediction of residential in urumqi and has good prediction effect,and has great practical application value.Firstly,this paper makes a simple qualitative analysis of the external factors influencing the change of housing price in Urumqi.and takes the real estate market of Urumqi as the realistic basis,takes the theory of real estate price as the theoretical basis,and selects several factors that influence the price of house price from supply and demand,and quantitative analysis of various factors affecting commodity housing prices.By using grey correlation analysis,the influence degree of different factors can be compared with others,which provides a feasible reference for indirect adjustment of supply and demand balance in Urumqi real estate market,and also provides theoretical support for determining the parameters of the gray prediction model.Secondly,through the inherent change law of house price itself,we can predict the price of house price.And based on the grey system theory,the GM(1,1)model and the grey-Markov model were established respectively from 2006 to 2015.By comparing the two methods,it is find that the single gray model is far less accurate than the combined model.The grey-Markov model is better at predicting short-term housing prices and can predict the price of residential goods in Urumqi more accurately.Finally,this paper establishes the GARCH(1,1)model to forecast and analyze the volatility of the commodity housing price in Urumqi.The results show that the GARCH model is quite successful in predicting the volatility of house price.The GARCH(1,1)model in this paper is fully applicable to the forecast of commodity housing prices and can achieve the expected goal.