Do analysts treat winners and losers differently when forecasting earnings?

Jung, Jay Heon; Pae, Jinhan; Yoo, Choong‐Yuel

doi:10.1016/j.ijforecast.2014.02.006

Cited by 4 publications

(4 citation statements)

References 33 publications

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“…The means of analyst‐ and firm‐specific characteristics such as firm‐specific experience ( FEXP ), the number of firms the analyst follows ( NFIRM ), brokerage size ( BSIZE ), book‐to‐market ratio ( BM ), and firm size ( SIZE ) are also similar to those in Clement et al. () and Jung et al ()…”

Section: Samplesupporting

confidence: 69%

“…indicating that analysts on average revise their earnings forecasts downwards as the year progresses (e.g., Lys & Sohn, 1990). The means of analyst-and firm-specific characteristics such as firm-specific experience (FEXP), the number of firms the analyst follows (NFIRM), brokerage size (BSIZE), book-to-market ratio (BM), and firm size (SIZE) are also similar to those in Clement et al (2011) and Jung et al (2015). 12…”

Section: Summary Statisticsmentioning

confidence: 82%

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Do analysts who understand accounting conservatism exhibit better forecasting performance?

Jung

Lim

Pae

et al. 2017

Business Fin & Account

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This study investigates the performance of analysts when they match the asymmetric timeliness of their earnings forecast revisions (i.e., asymmetric forecast timeliness) with the asymmetric timeliness of firms’ reported earnings (i.e., asymmetric earnings timeliness). We find that better timeliness‐matching analysts produce more accurate earnings forecasts and elicit stronger market reactions to their forecast revisions. Further, better timeliness‐matching analysts issue less biased earnings forecasts, more profitable stock recommendations and have more favorable career outcomes. Overall, our results indicate that analysts’ ability to incorporate conditional conservatism into their earnings forecasts is an important reflection of analyst expertise and professional success.

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Section: Samplesupporting

confidence: 69%

Section: Summary Statisticsmentioning

confidence: 82%

Do analysts who understand accounting conservatism exhibit better forecasting performance?

Jung

Lim

Pae

et al. 2017

Business Fin & Account

Self Cite

View full text Add to dashboard Cite

show abstract

“…Equally, the characteristics of the covered firms also matter, such as their intangible information (Higgins, ), continuity of capital gains (Jung et al ., ), product market power and market concentration (Datta et al ., ), earnings distribution (Gu and Wu, ; Clement et al ., ), return predictability (Chen and Martin, ), overconfidence of managers (Hilary and Hsu, ), use of corporate non‐financial information (Orens and Lybaert, ), and accounting information system (Wang, ).…”

Section: Literature Review and Hypothesis Developmentmentioning

confidence: 99%

Do Business Relationships Affect the Accuracy of Analyst Earnings Forecasts? Evidence from China

Wang

Wei

Han

2017

Asia-Pac J of Fin Stud

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Supporting the "conflicts of interest hypothesis," we show that, in China, better-informed analysts issue more optimistically biased forecasts and the reputation of financial analysts mitigates the bias. We contribute to the literature by showing that such an adverse information effect varies over types of investment banking relationships and a better developed local legal environment reduces forecast bias. Our results call for a better developed market mechanism to discipline analysts so as to issue independent and accurate earnings forecasts in China.

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“…Muslu and Xue (2013) report that financial analysts' momentum recommendations reflect different sides of stocks' past returns. Jung et al (2015) find that analysts incorporate the information of stocks' past returns when making revisions on earnings forecasts. Based on these findings, it suggests that analysts may not be fully rational when making earnings forecasts in using the information about stocks' past returns.…”

Section: Introductionmentioning

confidence: 99%

An investigation on impacts of structural changes in stocks’ past returns on financial analysts’ earnings forecasting rationality

Kang

2019

JCMS

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Purpose The purpose of this paper is to test whether financial analysts’ rationality in making stocks’ earnings forecasts is homogenous or not across different information regimes in stocks’ past returns. Design/methodology/approach By treating stocks’ past returns as the information variable in this study, the authors employ a threshold regression model to capture and test threshold effects of stocks’ past returns on financial analysts’ rationality in making earnings forecasts in different information regimes. Findings The results show that three significant structural breaks and four respective information regimes are identified in stocks’ past returns in the threshold regression model. Across the four different information regimes, financial analysts react to stocks’ past returns quite differently when making one-quarter ahead earnings forecasts. Furthermore, the authors find that financial analysts are only rational in a certain information regime of stocks’ past returns depending on a certain return-window such as one-quarter, two-quarter or four-quarter time period. Originality/value This study is different from those in the existing literature by arguing that there could exist heterogeneity in financial analysts’ rationality in making earnings forecasts when using stocks’ past returns information. The finding that financial analysts react to stocks’ past returns differently in the different information regimes of past returns adds value to the research on financial analysts’ rationality.

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Do analysts treat winners and losers differently when forecasting earnings?

Cited by 4 publications

References 33 publications

Do analysts who understand accounting conservatism exhibit better forecasting performance?

Do analysts who understand accounting conservatism exhibit better forecasting performance?

Do Business Relationships Affect the Accuracy of Analyst Earnings Forecasts? Evidence from China

An investigation on impacts of structural changes in stocks’ past returns on financial analysts’ earnings forecasting rationality

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