Analysis of Real Estate Industry Based on H-P Filter and Tobit Model—— cited 3,614 trading days for 15 companies

Abstract

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.