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Range has it: decoding the information content of forecast ranges
Authors:Michael Tang  Li Zhang
Institution:1.Stern School of Business,New York University,New York,USA;2.Rutgers Business School,Rutgers University,Newark,USA
Abstract:Range forecasts have emerged as the predominant form of management forecasts, but prior research has overlooked the information conveyed by forecast ranges. This study fills this void by examining the information content of the extent to which managers’ forecast ranges overlap with the range of individual analysts’ pre-existing estimates (i.e., overlap). We expect managers to signal their superior private information by issuing low-overlap forecasts. We predict and find that, compared with high-overlap forecasts, low-overlap forecasts are associated with stronger market reactions and higher accuracy of management forecasts relative to analyst estimates. Moreover, when responding to low-overlap management forecasts, analysts with prior estimates out of management forecast ranges are more likely to revise into the management forecast range, less likely to revise toward the consensus, and more likely to improve in revised forecast accuracy. Our findings suggest that investors and analysts view low-overlap management forecasts as signals of superior private information.
Keywords:
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