As an industry to enhance the national economy and improve people's lives, it is of great significance to accurately analyze the stock price of the real estate industry. Based on this, this paper takes 13 listed companies in the Chinese real estate industry as an example, using the H-P filtering method, OLS regression, and Tobit model to analyze the price of the real estate industry. There are three main research results: (1) After HP filtering analysis, the long-term trend and cyclical fluctuation curve of the stock prices of listed companies in the real estate industry are steep, indicating that China's real estate industry's real estate industry market fluctuates greatly. (2) When making a model prediction, the average daily price of each stock obtained after the Tobit test is the same as that of the OLS prediction, indicating that the core model also has good empirical robustness. (3) During the heterogeneity analysis of stock price, it is found that the regression model fits the residential development industry better than other industries.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.