• Medientyp: E-Book
  • Titel: Can Star Analysts Make Superior Coverage Decisions in Poor Information Environment?
  • Beteiligte: Jin, Han [VerfasserIn]; Mazouz, Khelifa [VerfasserIn]; Wu, Yuliang [VerfasserIn]; Xu, Bin [VerfasserIn]
  • Erschienen: [S.l.]: SSRN, [2022]
  • Umfang: 1 Online-Ressource (69 p)
  • Sprache: Englisch
  • DOI: 10.2139/ssrn.4169764
  • Identifikator:
  • Entstehung:
  • Anmerkungen: Nach Informationen von SSRN wurde die ursprüngliche Fassung des Dokuments August 25, 2020 erstellt
  • Beschreibung: 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
  • Zugangsstatus: Freier Zugang