"The study investigated the hypothesis that univariate ARIMA forecasts can be improved upon by using a more general transfer function model which consists of an ARIMA model with a market or industry index added. Statistical analysis of the data indicated that firms' forecasts have a tendency to perform either very well or very poorly under the transfer function model as compared to the ARIMA model (using an absolute value error metric)."

"It was demonstrated that it is possible to develop an a priori rule for the determination of when the transfer function will outperform the univariate model. In particular it was found that if a transfer function outperforms an ARIMA model for the majority of the first three periods in the forecast horizon, then there is a significant probability that it will do the same for periods four through ten."