Correlated Errors - Why a Monotone Relationship between Forecast Precision and Trading Profitability May Not Hold
40 Pages Posted: 14 Feb 2009 Last revised: 29 Dec 2018
Date Written: February 27, 2012
This paper argues that the relation between financial analysts' earnings forecast accuracy and their recommendation profitability has to be augmented by the extent of commonality in their forecast errors. We show that while accuracy is positively related to expected performance, the correlation in forecasting errors has a negative impact. This implies that a monotonic relationship between ex ante identifiable forecast accuracy and ex post recommendation profitability does not need to hold. Thus, agents may be better off by making comparatively large but less correlated errors, than making precise but highly correlated forecasts.
Keywords: Forecast accuracy, analysts recommendation profitability, learning, Kalman filter
JEL Classification: M4, G14
Suggested Citation: Suggested Citation