FORECAST SELECTION WHEN ALL FORECASTS ARE NOT EQUALLY RECENT

Little is known about which forecasts to select when all forecasts are not equally recent. This paper uses security analysts' annual earnings forecasts to examine this issue. The comparative predictive accuracy of the mean and three timely composites is examined, where the three timely composites are the most recent forecast, the average of the three most recent forecasts, and the 30-day average. The mean is shown to be less accurate than all three timely composites, and the 30-day average is shown to be the most accurate timely composite. The findings suggest that tradeoffs exist between recency and aggregation, and that these tradeoffs are related to firm size.