Premium
Correlated Errors: Why a Monotone Relationship Between Forecast Precision and Trading Profitability May Not Hold
Author(s) -
Lawrenz Jochen,
Weissensteiner Alex
Publication year - 2012
Publication title -
journal of business finance and accounting
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.282
H-Index - 77
eISSN - 1468-5957
pISSN - 0306-686X
DOI - 10.1111/j.1468-5957.2012.02291.x
Subject(s) - profitability index , earnings , econometrics , ex ante , economics , monotonic function , forecast error , monotone polygon , computer science , mathematics , finance , mathematical analysis , geometry , macroeconomics
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 by making precise but highly correlated forecasts.