利用时间序列分析股票价格和会计盈利的动态关系

Analyzing the Dynamic Relationship between the Stock Price and the Earnings by Using the Time Series

本文应用最近发明的时间序列的计量经济学方法来检测股票价格和会计利润的动态关系,应用向量式的自回归模型,把它用于构建22家取自英国金融时报指数的英国顶级公司的股票价格和会计利润的信息的模型。力求建立一个多元的向量式自回归模型系统,并在此基础上建立一个向量式纠正误差模式,来模拟股票和盈利间的长短期关系,以此来确定它们中究竟哪个可作为内生变量和外生变量。然后利用方差的分解分析模型来确定一个单位的标准差的振动对这个系统的影响。同时本文还使用另一种方法做向量自回归系统的短期动态分析,即应用广义刺激反应模型进行分析。

This thesis draws attention to the application of recently developed time series econometric methods to examining the dynamics between stock prices and earnings. We apply a vector autoregression (VAR) framework to price and earnings data of 22 top individual UK companies listed in the FTSE stock price index. We attempt to capture the endogeneity by specifying a multivariate VAR system and then apply a vector error correction model (VECM) to model the long and short-term relationships between the variables. The impact of a one standard deviation shock to a variable in the system is then modeled and a variance decomposition analysis undertaken. Meanwhile, the thesis is planned to involve another method of analyzing the short run dynamics of a VAR model, that is, by employing the generalized impulse response analysis.