Disclosure and liquidity management: Evidence from regulation fair disclosure

2020 ◽  
Vol 16 (3) ◽  
pp. 100205
Author(s):  
Susan Albring ◽  
Shawn Huang ◽  
Raynolde Pereira ◽  
Xiaolu Xu
Author(s):  
Susan M. Albring ◽  
Monica L. Banyi ◽  
Dan S. Dhaliwal ◽  
Raynolde Pereira

2012 ◽  
Author(s):  
Yutao Li ◽  
Anthony Saunders ◽  
Pei Shao

2016 ◽  
Vol 19 (03) ◽  
pp. 1650014 ◽  
Author(s):  
Pieter T. Elgers ◽  
May H. Lo ◽  
Wenjuan Xie ◽  
Le Emily Xu

This study addresses the impact of firm- and time-specific attributes on the accuracy of composite forecasts of annual earnings, constructed from time-series, price-based, and analysts' forecasts. The attributes examined include firm size, analysts' coverage, and time periods pre-dating and following the implementation of regulation fair disclosure. Our results indicate that the relative accuracy of the composite forecasts is time-specific. In the pre-regulation fair disclosure period, composite forecasts significantly outperform each of the three individual forecast sources. Moreover, the extent of improvement in accuracy of composite forecasts is significantly higher for the smaller and lightly-covered firms. Collectively, these results suggest that the predictive accuracy of composite forecasts is contextual.


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