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Using abnormal analyst coverage to unlock new evidence on stock price crash risk
Author(s) -
Chowdhury Hasibul,
Faff Robert,
Hoang Khoa
Publication year - 2021
Publication title -
accounting and finance
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.645
H-Index - 49
eISSN - 1467-629X
pISSN - 0810-5391
DOI - 10.1111/acfi.12637
Subject(s) - ex ante , business , crash , econometrics , volatility (finance) , stock (firearms) , actuarial science , financial economics , monetary economics , economics , computer science , mechanical engineering , engineering , macroeconomics , programming language
We employ a characteristic‐based model to decompose total analyst coverage into abnormal and expected components and show that abnormal coverage contains valuable information about firm‐level ex ante crash risk (proxied by implied volatility smirk from options data). Specifically, one standard deviation increase in unexpected or abnormal coverage is associated with a 5.5 percent decrease in the ex ante crash risk. The abnormal coverage signal is more useful for firms with a more transparent information environment, proxied by lower probability of informed trading, lower financial opacity, and more comparable financial statements. Moreover, the abnormal coverage effect is stronger for firms followed by analysts who issue more accurate and less dispersed forecasts. Collectively, these results suggest that options market investors utilise abnormal coverage to identify and assess crash risk of mispriced firms.