Real Estate Industry Cycles And Forecasts Based On Stock Price Indices

The real estate industry is a crucial part of a country’s economy and plays an indispensable role in economic development.First of all,the real estate industry is one of the basic industries of a country and plays an important role in the growth of GDP,employment and taxation.Second,the real estate industry can also stimulate the growth of consumption and investment.Over a couple of decades,China’s real estate market has shown signs of cyclical fluctuations.A proper grasp of the real estate industry cycle can help relevant practitioners,investors and policy makers to better grasp market changes and risks and make more effective investment and policy decisions to avoid missed opportunities during market downturns or losses during market volatility.The strong correlation between real estate market cycles and housing stock price indices has been a long-standing concern.Over the past decades,scholars have explored this issue using various methods and models and have come up with many useful conclusions.This paper aims to identify as well as forecast the cycle of real estate industry based on stock price index.We classify the cycle of national housing boom index,build probit model,and use ROC curve to measure the prediction effect.The results show that our model performs well in predicting 0-1 cycles,and the AUC value of the ROC curve is about 0.74,which indicates that our probit model has good predictability,and can be applied to investment decisions.Further introduce the Lasso Logit model to make the forecasts.We find that the forecast performance of Lasso Logit model is outstanding,which is better than the performance of Probit model.In conclusion,in-depth studies are important for understanding the mechanisms of real estate and stock markets.This study provides a new idea and method for predicting the real estate industry cycle for the stock price index,which may be useful for practical investment decisions.