“Robust Measures of Earnings Surprises” by Prof. Jianqing Fan
Joint Seminar hosted by Finance, and Innovation and Information Management
Professor Jianqing Fan
Professor of Statistics
Frederick L. Moore Professor of Finance
Event studies of market efficiency measure an earnings surprise with the consensus error (CE), defined as earnings minus the average of professional forecasts. If a subset of forecasts can be biased, the ideal but difficult to estimate parameter-dependent alternative to CE is a nonlinear filter of individual errors that adjusts for bias. We show that CE is a poor parameter-free approximation for this ideal measure. The fraction of misses on the same side FOM, by discarding the magnitude of misses, offers a far better approximation. FOM performs particularly well against CE in predicting the returns of US stocks, where bias is potentially large, than that of international stocks.