Research on Forecast of Beijing Housing Price based on Spatial Gray Markov Model

Abstract

In recent years, with the continuous advancement of the economy, the real estate industry has developed rapidly, which has led to the persistent rise of housing prices. How to understand the changing trend of housing prices reasonably and formulate corresponding policies to effectively control them has become a social problem for the government departments. However, to maintain the housing development, it is critical to monitor and predict housing prices accurately so as to support the decision-making process in the housing field. Based on the actual data of housing prices from January 2018 to March 2019 in Beijing, this research has built a model named Spatial Gray Markov Model, through combing the gray GM (1,1) prediction, and other models, to predict the housing price in Beijing. And the result shows that the Spatial Gray Markov Model is much better than the other models in forecasting, and we get a better outcome that the error and accuracy of the predicted has improved and its accuracy is increasing of 0.31% compared to that of the Grey GM (1, 1) prediction value.