The Transfer Function Relationship between Earnings and Market-Industry Indices: An Empirical Study
使用Box-Jenkins传递函数方法，将市场和行业指数纳入盈利预测模型，以克服单变量ARIMA模型忽略外部因素的局限，对金融分析师评估公司财务趋势有参考价值。
In recent years, there has been an increased emphasis on the forecasting of accounting earnings using the Box-Jenkins method of forecasting via autoregressive integrated moving average (ARIMA) models.' Generally, however, these models are univariate by definition and do not provide for the statistical modeling of events which occur outside of the earnings series. The purpose of this study is to explore the impact of this limitation by employing a more general approach which incorporates market and industry index data into the forecast model. One reason for exploring this more general approach is that Financial analysts have long recognized that economy-wide and industry-wide factors affect the financial numbers of individual firms. Index models enable quantification of the effects of these factors. Such quantification can be important when assessing financial trends in a firm and forecasting financial variables (Foster [1978, p. 155]; see also Brown and Ball [1967] for further motivation for index models). This objective can be achieved through the use of the single-input transfer-function method developed by Box and Jenkins [1970]. The transfer function provides a more generalized form of the ARIMA model by incorporating an additional predictor variable, in addition to past earnings, in the form of a market or industry price index. Section 1 contains a brief discussion of the transfer function and