Extrapolation Bias in Explaining the Asset Growth Anomaly: Evidence from Analysts’ Multi-Period Earnings Forecasts

Abstract

Using analysts’ multi-period earnings forecasts, this paper investigates whether analyst forecast errors are related to asset growth and, if so, to what extent analysts’ optimism for high-growth firms can explain the asset growth anomaly. We find that analyst forecasts are more optimistic for firms with high asset growth, particularly for longer-term forecasts (e.g., two- and three-year-ahead forecasts than one-year-ahead forecasts). We also find that analysts’ optimism for high-growth firms is more pronounced for (1) firms that have maintained similar levels of growth in recent periods, (2) firms with higher information uncertainty, and (3) forecasts with longer forecast horizons (e.g., forecasts issued far before fiscal year end). Adding forecast errors to a growth-return regression substantially reduces the coefficient on asset growth, suggesting an important role of forecast errors in the growth anomaly. Path analysis suggests that analysts’ long-term forecast errors, but not short-term forecast errors, are important mediators through which biased expectations about asset growth are incorporated into stock returns. Overall, our findings support the extrapolation bias explanation for the asset growth anomaly.