Contemporaneous and Delayed Market Response to Information in the Tails of the Distribution of Financial Analystss Quarterly Earnings Forecast Errors

2016 ◽  
Author(s):  
Philip B. Shane ◽  
Cameron Truong ◽  
Qiuhong Zhao
Keyword(s):  
Market Response ◽  
Earnings Forecast ◽  
Forecast Errors ◽  
Quarterly Earnings

Predictability of Analyst Earnings Forecast Errors and Institutional and Individual Investors’ Reactions to Earnings News

2020 ◽  
pp. 0148558X2093933
Author(s):  
Nilhabra Bhattacharya ◽  
Per Olsson ◽  
Hyungshin Park
Keyword(s):  
Institutional Investors ◽  
Forecast Error ◽  
Individual Investors ◽  
Earnings Forecast ◽  
Forecast Errors ◽  
Financial Reports ◽  
Earnings Announcement ◽  
Quarterly Earnings ◽  
Earnings Information ◽  
Analyst Earnings

We decompose analysts’ earnings forecast error into predictable and unpredictable components and investigate individual vis-à-vis institutional investors’ reactions to each of these components. We find that in the immediate post-earnings announcement window, only individuals under-react to the predictable component, while both individuals and institutions under-react to the unpredictable component. The price drift in this window is driven primarily by investors’ under-reaction to the unpredictable component. This drift remains highly significant in larger firms and intensifies in firms with complex financial reports, suggesting that it likely represents the slow and noisy process of price discovery. Around the next quarterly earnings announcement, only individuals under-react to the previous quarter’s predictable component, and this fixation drives the entire price drift in this window. This drift disappears in larger firms and gets exacerbated in firms with greater forecast error autocorrelations, suggesting that it is likely attributable to incomplete processing of earnings information by individuals.

Refining financial analysts’ forecasts by predicting earnings forecast errors

2017 ◽  
Vol 25 (2) ◽  
pp. 256-272 ◽  
Author(s):  
Tatiana Fedyk
Keyword(s):  
Serial Correlation ◽  
Design Methodology ◽  
Financial Analysts ◽  
Earnings Forecasts ◽  
Autoregressive Process ◽  
Earnings Forecast ◽  
Forecast Errors ◽  
Content Type ◽  
Quarterly Earnings ◽  
Prior Literature

Purpose The purpose of this paper is to examine the way serial correlation in quarterly earnings forecast errors varies with firm and analyst attributes such as the firm’s industry and the analyst’s experience and brokerage house affiliation. Prior research on financial analysts’ quarterly earnings forecasts has documented serial correlation in forecast errors. Design/methodology/approach Finding that serial correlation in forecast errors is significant and seemingly independent of firm and analyst attributes, the consensus forecast errors are modeled as an autoregressive process. The model of forecast errors that best fits the data is AR(1), and the obtained autoregressive coefficients are used to predict consensus forecast errors. Findings Modeling the consensus forecast errors as an autoregressive process, the present study predicts future consensus forecast errors and proposes a series of refinements to the consensus. Originality/value These refinements were not presented in prior literature and can be useful to financial analysts and investors.

The Association between Unsystematic Security Returns and the Magnitude of Earnings Forecast Errors

1979 ◽  
Vol 17 (2) ◽  
pp. 316 ◽  
Author(s):  
William H. Beaver ◽  
Roger Clarke ◽  
William F. Wright
Keyword(s):  
Earnings Forecast ◽  
Forecast Errors ◽  
Security Returns

Regulation FD and the Financial Information Environment: Early Evidence

2003 ◽  
Vol 78 (1) ◽  
pp. 1-37 ◽  
Author(s):  
Frank Heflin ◽  
K. R. Subramanyam ◽  
Yuan Zhang
Keyword(s):  
Stock Prices ◽  
Earnings Announcements ◽  
Relevant Information ◽  
Financial Information ◽  
Earnings Forecast ◽  
Forecast Errors ◽  
Informational Efficiency ◽  
The Public ◽  
Fair Disclosure ◽  
Regulation Fd

On October 23, 2000, the SEC implemented Regulation FD (Fair Disclosure), which prohibits firms from privately disclosing value-relevant information to select securities markets professionals without simultaneously disclosing the same information to the public. We examine whether Regulation FD's prohibition of selective disclosure impairs the flow of financial information to the capital markets prior to earnings announcements. After implementation of FD, we find (1) improved informational efficiency of stock prices prior to earnings announcements, as evidenced by smaller deviations between pre-and post-announcement stock prices; (2) no reliable evidence of change in analysts' earnings forecast errors or dispersion; and (3) a substantial increase in the volume of firms' voluntary, forward-looking, earnings-related disclosures. Overall, we find no evidence Regulation FD impaired the information available to investors prior to earnings announcements, and some of our evidence is consistent with improvement.

scholarly journals A note on analysts’ earnings forecast errors distribution

2003 ◽  
Vol 36 (1-3) ◽  
pp. 147-164 ◽  
Author(s):  
Daniel A Cohen ◽  
Thomas Z Lys
Keyword(s):  
Earnings Forecast ◽  
Forecast Errors

The Effect of Beating and Missing Analysts' Forecasts on the Information Content of Unexpected Earnings

2002 ◽  
Vol 17 (2) ◽  
pp. 155-184 ◽  
Author(s):  
Thomas J. Lopez ◽  
Lynn Rees
Keyword(s):  
Information Content ◽  
Stock Prices ◽  
Forecast Error ◽  
Earnings Forecasts ◽  
Bad News ◽  
Market Response ◽  
Forecast Errors ◽  
Unexpected Earnings ◽  
Systematic Component ◽  
History Of

This study investigates whether the market rewards (penalizes) firms for meeting (not meeting) analysts' earnings forecasts. Specifically, we examine the market response to positive and negative forecast errors. In addition, we examine whether the sensitivity of stock prices to positive or negative forecast errors is affected by the firms' history of consistently beating or missing analysts' forecasts. The results indicate that the earnings multiple applied to positive unexpected earnings is significantly greater than for negative unexpected earnings. In addition, we find that after controlling for the magnitude of the forecast error and bad news preannouncements, the market penalty for missing forecasts is significantly greater in absolute terms than the response to beating forecasts. We document evidence that, while the market recognizes and partially discounts the systematic component of positive analysts' forecast errors, a higher multiple is attached to the unsystematic component of unexpected earnings of firms that consistently beat analysts' forecasts. Overall, the evidence suggests that the increasing frequency of positive forecast errors as documented in previous research is a rational response by managers to market-related incentives.

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