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dc.contributor.advisorSrinidhi, Bin
dc.creatorHsu, Wei
dc.date.accessioned2018-06-05T17:43:15Z
dc.date.available2018-06-05T17:43:15Z
dc.date.created2018-05
dc.date.issued2018-05-04
dc.date.submittedMay 2018
dc.identifier.uri
dc.identifier.urihttp://hdl.handle.net/10106/27425
dc.description.abstractI examine how firm-specific private and public information affect analyst forecast revisions. I find that when managers easily beat (struggle to meet) the consensus forecasts in the previous quarter, financial analysts revise their earnings forecasts upward (downward). The revision magnitudes are higher when there is more private information. Similarly, I find that when managers provide upward (downward) earnings guidance, analysts revise their forecasts upward (downward) more when there is more private information. In contrast, the revision magnitudes are lower when there is more public information. Additionally, I find that the magnitudes of analysts’ downward revisions increase with private information prior to the stock option grant dates. I attribute these results to the analysts’ dependence on managers in gleaning relevant private information. The effect of private information is smaller for firms covered by star analysts, consistent with star analysts acting as sophisticated skeptics and being more confident in their forecasts than other analysts. Further, for well-governed firms, upward revisions for positive earnings surprises are smaller when there is more private information. This is consistent with stronger governance attenuating analysts' concerns about firms’ earnings quality, which in turn increases their reliance on public earnings numbers and reduces their need to accommodate managers for private information. Finally, I find that private information is negatively associated with target price forecast accuracy, and positively associated with target price forecast optimism. These results suggest that greater information asymmetry adversely affects forecast accuracy and creates incentives for analysts to appease managers to access private information.
dc.format.mimetypeapplication/pdf
dc.subjectFirm-specific Information
dc.subjectPrivate Information
dc.subjectAnalyst forecast
dc.subjectStar analyst
dc.titleFirm-Specific Information Environment and Analyst Forecast
dc.typeThesis
dc.degree.departmentAccounting
dc.degree.nameDoctor of Philosophy in Accounting
dc.date.updated2018-06-05T17:45:22Z
thesis.degree.departmentAccounting
thesis.degree.grantorThe University of Texas at Arlington
thesis.degree.levelDoctoral
thesis.degree.nameDoctor of Philosophy in Accounting
dc.type.materialtext


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