Analyst Firm Coverage and Forecast Accuracy: The Effect of Regulation Fair Disclosure

Dong, Yi; Hu, Nan; Li, Xu; Liu, Ling

doi:10.1111/abac.12120

Cited by 7 publications

(5 citation statements)

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“…This is that managers alert analysts to the insider trades, and explain the rationale behind such trades, via private communications, rather than analysts themselves referring to, and learning from, insider trades. To negate or minimize such a possibility, we restrict our sample period to the post-Reg-FD era, in which the communications between insiders and outsiders about private information are significantly more restricted (see, e.g., Koch et al, 2013;Dong et al, 2017;Hu et al, 2018). We obtain qualitatively the same results.…”

Section: Introductionmentioning

confidence: 56%

“…The communication of private information between firm management and analysts is unlikely to be fully prevented by Reg FD. Nonetheless, it is plausible to suggest that given potential legal and/or reputational penalties for noncompliance with Reg FD, private information communications between analysts and insiders would be limited, as suggested in a large body of the Reg FD literature (Koch et al, 2013;Dong et al, 2017;Hu et al, 2018). This is also evident in the dearth of legal cases regarding breaches of Reg FD, and is in line with the prior view that managers tend to be careful and "correct" in what they say to analysts, especially when the litigation risks associated with private communications are significantly heightened post Reg FD (Koch et al, 2013).…”

Section: Impact Of Insider Tradingmentioning

confidence: 99%

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The impact of insider trading on analyst coverage and forecasts

Marginson

2020

ARJ

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Purpose The purpose of this study is to examine the effect of insider trading on analyst coverage and the properties of analyst earnings forecasts. Given the central role of analysts for information diffusion in stock markets, advancing understanding of the role insider trades may play in analyst coverage and forecasts, especially in the context of a changing legal environment (e.g. the implementation of Regulation Fair Disclosure [Reg FD]), should be a worthy goal. Design/methodology/approach To address the research questions, the authors run regressions in which the authors identify and control for as many possible determinants of analyst coverage and forecasts (e.g. firm size, information asymmetry and earnings performance) that are correlated with insider trades. To alleviate endogeneity concerns, the authors use three approaches. First, the authors extend the sample period to the post-Reg-FD period in which managers are not allowed to provide private information to financial analysts. Second, the authors measure analyst coverage in a window that is lagged by insider trades. Third, the authors employ firm-fixed-effects regressions in all the multivariate tests. Finally, following Larcker and Rusticus (2010), the authors conduct the impact threshold for a confounding variable test to assure that all regression analyses are indeed immune to the potential correlated-omitted-variable bias. Findings The authors find that the level of analyst coverage is positively related to the intensity of insider trades and that analyst coverage is more strongly associated with insider purchases than with insider sales. The authors also find that the positive association between analyst coverage and insider trades is less pronounced after the passage of Reg FD. Further investigations reveal that analysts revise their earnings forecasts upward following insider purchases, the informativeness of analyst forecast revisions significantly increases following insider purchases and optimistic bias in analyst forecast revisions is reduced as a result of insider purchases; the authors do not find similar evidence for insider sales. Research limitations/implications A large body of insider trading literature (Johnson et al., 2009; Badertscher et al., 2011; Thevenot 2012; Skaife et al., 2013; Billings and Cedergren 2015; Dechow et al., 2016) provides evidence that insiders actively trade on their private information, such as their foreknowledge of price-relevant corporate events. This literature suggests that insider trades are potentially value-relevant and are informative about a firm’s future prospects. However, less research attention has been paid to investigating how insider trades might affect market participants’ (especially sophisticated participants’) behavior. This study contributes to understanding the role that insider trading may play in shaping analyst behavior. Practical implications Prior research (Frankel and Li, 2004; Lustgarten and Mande, 1995; Carpenter and Remmers, 2001; Seyhun, 1990) maintains that insider sales are less informative about a firm’s future prospects than are insider purchases because insider sales might take place for the liquidity and diversification purposes. By probing the stock price responses to insider selling activities, Lakonishok and Lee (2001), Jeng et al. (2003) and Fidrmuc et al. (2006) infer that insider selling is not informative about future firm performance. However, for such an inference, the authors cannot rule out the possibility that insider sales do convey value-relevant information, but the stock market does not react correctly to such trading information (Beneish and Vargus, 2002). Because the authors focus on examining analysts’ responses to insider sales, and analysts are supposed to be sophisticated in information processing, this study adds more compelling evidence for the notion that insider sales convey less information about a firm’s future prospects than do insider purchases. Social implications There is an ongoing debate about the benefits and drawbacks of insider trading. Opponents of insider trading view insider trades as inequitable and immoral and assert that restricting insider trades curbs resource misallocation and benefits the whole society. Proponents contend that insider trading accelerates the price discovery process, increases market efficiency (Leland, 1992; Bernhardt et al., 1995; Choi et al., 2016) and may even play a role in rewarding and motivating executives (Roulstone, 2003; Denis and Xu, 2013). The authors add to this debate by documenting that insider trading increases the amount of information valuable to analyst research activities and helps enhance analyst services. Originality/value To the best of the authors’ knowledge, this study is the first to offer firm-level evidence of a positive association between insider trades and analyst coverage. By accounting for the post-Reg-FD regime, this paper is also the first to provide evidence on how analysts, in the absence of access to management’s private information because of the regime change by Reg FD, react to insider trades.

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Section: Introductionmentioning

confidence: 56%

Section: Impact Of Insider Tradingmentioning

confidence: 99%

The impact of insider trading on analyst coverage and forecasts

Marginson

2020

ARJ

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“…Bradbury, ). We also include a variable for analyst coverage which has been associated with increased forecasting accuracy in recent literature (Dong et al ., )…”

Section: Institutional Background Of China and Prior Literaturementioning

confidence: 99%

Corporate distress prediction in China: a machine learning approach

Jiang

Jones

2018

Accounting & Finance

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Rapid growth and transformation of the Chinese economy and financial markets coupled with escalating default rates, rising corporate debt and poor regulatory oversight motivates the need for more accurate distress prediction modelling in China. Given China's historical, social and cultural intolerance towards corporate failure, this study examines the Special Treatment system introduced by Chinese regulators in 1998. Regulators can assign Special Treatment status to listed Chinese companies for poor financial performance, financial abnormality and other events. Using an advanced machine learning model known as TreeNet Ò we model more than 90 predictor variables, including financial ratios, market returns, macro-economic indicators, valuation multiples, audit quality factors, shareholder ownership/control, executive compensation variables, corporate social responsibility metrics and other variables. Based on out-of-sample tests, our TreeNet Ò model is 93.74 percent accurate in predicting distress (a Type I error rate of 6.26 percent) and 94.81 percent accurate in predicting active/healthy companies (a Type II error rate of 5.19 percent). Variables with the strongest predictive value in the TreeNet Ò model includes market capitalization and annual market returns, macro-economic variables such as gross domestic product growth, financial ratios such as retained earnings to total assets and return on assets; and certain non-traditional variables such as executive compensation.

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“…The first approach follows Bushee (1998, the number of covered firms and industries detracts from analyst forecast accuracy. On the other hand, Dong et al (2017) find a positive relation between the number of firms covered and earnings forecast accuracy in the post-Reg FD era.…”

Section: Model For Testing H2mentioning

confidence: 82%

Do buy‐side analysts inform sell‐side analyst research?

Cici,

Shane,

Yang

2023

Accounting & Finance

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This paper examines whether sell‐side analysts' interactions with buy‐side analysts influence the quality of sell‐side research output. We hypothesise that these interactions offer the sell side a view of the buy side's private information, which enhances the quality of sell‐side research. Our findings show that analyst earnings forecast accuracy improves with these interactions with diminishing returns. Results are robust to alternative proxies for research quality and information flow from buy‐side to sell‐side analysts. Additional tests rule out endogeneity concerns, strengthening the inference that feedback from interactions with buy‐side analysts improves the quality of sell‐side research output.

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Analyst Firm Coverage and Forecast Accuracy: The Effect of Regulation Fair Disclosure

Cited by 7 publications

References 53 publications

The impact of insider trading on analyst coverage and forecasts

The impact of insider trading on analyst coverage and forecasts

Corporate distress prediction in China: a machine learning approach

Do buy‐side analysts inform sell‐side analyst research?

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