The Application Of Quantile Regression In The Real Estate Industry

Quantile regression theory is proposed by Koenker and Bassett.It canmeasure the effect of regression variables which distribute in center andtail.And it predicts the future on different quantile more comprehensive andaccurate than the least squares estimate.Time series analysis is used to buildmodels of time sequence data.It analyzes the dynamic structure of data andthe law of development and forecasts the future state. it is not necessary tohypotheses the random error distribution before estimating parameters oftime sequence by the quantile regression method.It can depict thedistribution characteristics fully and obtain the comprehensive analysis.Firstly,this paper introduces the basic theory of quantile regressionand derives the relevant calculation and properties. Secondly,base on thetheory of linear quantile regression and multivariate statistical to calculatethe factors those influence real estate industry development.Then grasp thedifferent quantitative relationships with economy, population, real estateitself and environment in different quantitative angle.Thirdly,this paperintroduces theory of the ARMA model in detail and provides a theoreticalbasis model in practical application. Finally, the article combines quantileregression model with the ARMA model to make the empirical analysis aboutthe Real Estate Climate Index and gets the model under different quantiles.It can simulation and forecast data in different levels according to thedifferent sequences of model.The article also clearly pointes out that themodel based on the quantile regression estimate is more accurate bycomparing the predicted values and real values in different ways.