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Research Article

Abnormal tone in management earnings forecast, media negative coverage, and insider trading

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Pages 939-963 | Received 16 Mar 2019, Accepted 21 Jul 2020, Published online: 18 Aug 2020
 

ABSTRACT

Based on previous studies, we define the term abnormal language tone, used in management earnings forecasts, as the extent to which the language tone in the forecast deviates from the regular language tone that is used to describe business performance. We posit that the use of abnormal language tone is associated with insider trading. We specifically analyze a sample of Chinese listed firms during the period of 2010–2017. Our results indicate that, when managers intend to sell their shares, they release information in an abnormally optimistic tone. When they intend to buy shares, they release information in an abnormally pessimistic tone in order to bring down the stock price. However, we found that the media can exert supervision and corporate governance control on listed firms. If the media reports negative news prior to the earnings forecast, the relationship between abnormal language tone and insider trading will be weaker. Our findings complement prior studies in two ways. First, we provide evidence that the managers manipulate the tone of the language in earnings forecasts to facilitate insider trading. Second, we show that the media not only exposes the immoral behaviors of listed firm but can also prevent future manipulation of the tone in management earnings forecasts

Disclosure statement

No potential conflict of interest was reported by the authors.

Notes

1. To prove whether our findings are robust when the criterion to identify the ‘insiders’ get stricter, we distinguish the insiders trade between managers’ trades and relatives’ trades. Among which, manager is further divided into senior manager and other manager. After adopting this criterion, we use subsample test to rerun our model. The results show the regression results of subsample groups are consistent with our main analysis.

Additional information

Funding

National Social Science Foundation of China (19CJY008); Social Science Foundation of Jiangxi (17YJ40)

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