Jin, H orcid.org/0000-0003-3752-0440, Mazouz, K, Wu, Y et al. (1 more author) (2023) Can Star Analysts Make Superior Coverage Decisions in Poor Information Environment? Journal of Banking and Finance, 146. 106650. ISSN 0378-4266
Abstract
This study uses the quality of coverage decisions as a new metric to evaluate the performance of star and non-star analysts. We find that the coverage decisions of star analysts are better predictors of returns than those of non-star analysts. The return predictability of star analysts’ coverage decisions is stronger for informationally opaque stocks. We further exploit the staggered short selling deregulations, Google’s withdrawal, and the anti-corruption campaign as three quasi-natural experiments that create plausibly exogenous variations in the quality of information environment. These experiments show that the predictive power of star analysts’ coverage decisions strengthens (weakens) following a sharp deterioration (improvement) in firms’ information environment, consistent with the notion that star analysts possess superior ability to identify mispriced stocks. Overall, star analysts make better coverage decisions and play a superior role as information intermediaries, especially in poor information environment.
Metadata
Item Type: | Article |
---|---|
Authors/Creators: |
|
Copyright, Publisher and Additional Information: | © 2022 Elsevier B.V. All rights reserved. This is an author produced version of an article published in Journal of Banking & Finance. Uploaded in accordance with the publisher's self-archiving policy. |
Keywords: | Star analysts; Coverage decisions; Return predictability; Information environment |
Dates: |
|
Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Business (Leeds) > Accounting & Finance Division (LUBS) (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 24 Aug 2022 14:37 |
Last Modified: | 24 Feb 2024 01:13 |
Status: | Published |
Publisher: | Elsevier |
Identification Number: | 10.1016/j.jbankfin.2022.106650 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:190232 |