Getting bad news out early: does it really help stock prices?
Divisions of Research & Statistics and Monetary Affairs, Federal Reserve Board, 2003 - Business & Economics - 50 pages
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12-week revision abnormal return analyst forecasts Athanasios Orphanides Brian Sack conﬁdence intervals cross-validation cumulative return deﬁned early sample early-quarter forecasts earnings announcement earnings forecasts earnings report earnings surprises EPS|-scaled equivalent number estimated evidence ﬁg ﬁgure ﬁgure displays ﬁnd ﬁndings ﬁrm-quarter ﬁt ﬁtted ﬁtting forecast revisions high-growth ﬁrms Inﬂation information policy lines iso-return contours iso-return lines Kasznik late period late sample locally weighted loess long-term growth forecasts low-growth ﬁrms M-plot M-statistics meet expectations meeting or beating Monetary Policy negative surprises nonlinearities null hypothesis number of parameters optimal smoothing parameter Panel percentiles policy line represent preannouncing bad previous quarter’s price scaling factor quarter quarterly earnings reﬂect regression revision period Revision Surprise revisions and earnings revisions and surprises sample split Sample Statistics scaling factor scatterplots signiﬁcant speciﬁcation statistical Steve Sharpe stock price beneﬁt stock returns subsamples suggest that ﬁrms surfaces total forecast error weighted least squares