房地产股价线性模型的变量选择实证研究

The Empirical Research on Variable Selection in Linear Model Based on Stock Price of Listed Real Estate Companies

建立了房地产上市公司财务指标和其股票价格的线性回归模型,利用最小二乘回归、主成分回归和逐步回归方法估计回归系数,对比3种方法发现基于逐步回归方法的变量选择是最全面和可靠的;进一步建立了房地产股价指数与其成分股的多元线性回归方程,运用弹性约束估计方法实现成分股变量选择问题,解决了回归系数不显著性和股指追踪问题。

In this paper, the linear regression model based on the financial indicators of listed real estate companies and their stock price was established. The least squares regression, principal component regression and stepwise regression methods were used to estimate the regression coefficients. Compared with these three methods, variable selection based on the stepwise regression method was the most comprehensive and reliable. Furthermore, multivariate linear regression equation between the index of the real estate companies and their component stocks was established, and we used the elastic restricted estimation method to implement variable selection of component stocks. Meanwhile,both problems of unsignificance of the regression coefficients and stock index tracking were also solved.