Effects of Institutional Investors as Independent Outside Block-holders on Analysts’ Earnings Forecast Errors

2018 ◽  
Vol 16 (3) ◽  
pp. 27-53
Author(s):  
Sang Cheol Lee ◽  
Yunkeun Lee ◽  
Yong Sun Shin
Keyword(s):  
Institutional Investors ◽  
Earnings Forecast ◽  
Forecast Errors ◽  
Block Holders

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.

Bulk and block holders herding behaviour

2018 ◽  
Vol 7 (2) ◽  
pp. 150-171
Author(s):  
Ganesh R. ◽  
Naresh Gopal ◽  
Thiyagarajan S.
Keyword(s):  
Economic Performance ◽  
Institutional Investors ◽  
Design Methodology ◽  
Indian Market ◽  
Foreign Investors ◽  
Content Type ◽  
Industrial Sectors ◽  
Block Data ◽  
Block Holders

Purpose The purpose of this paper is to examine industry herding among the institutional investors and to find whether their herding behaviour is intentional or unintentional. Design/methodology/approach The study uses Lakonishok et al. (1992) model to examine the presence of industry herding behaviour among institutional investors. To determine whether the herding observed is intentional or unintentional, herding measure is regressed with volatility, volume, beta and return. The period of the study is from 1 April 2005-31 March 2015. Findings The findings of the study showed that though institutional investors have herding tendency towards most of the industries, in the overall period industry herding was not significant. The herding found in some industrial sectors was linked to economic performance of those sectors in India during the period of study and hence the herding was unintentional in nature. Research limitations/implications This is the first attempt to study industry herding among institutional investors and their intent in Indian market ever since the country opened its market to foreign investors in a big way. Present study is limited to the use of only bulk/block data instead of the entire trading data for the period. Originality/value This study is the first attempt to investigate industry herding behaviour of institutional investors in the market using their bulk and block trading data. The herding observed in well performing industries has been shown to be unintentional and hence rational. The results indicate that the entry of big institutional investors, including foreign institutions into the Indian market has not destabilised the market by irrational herding.

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

Implications of Cost Behavior for Analysts' Earnings Forecasts

2015 ◽  
Vol 28 (1) ◽  
pp. 57-80 ◽  
Author(s):  
Mustafa Ciftci ◽  
Raj Mashruwala ◽  
Dan Weiss
Keyword(s):  
Earnings Forecasts ◽  
Earnings Forecast ◽  
Forecast Errors ◽  
Clear Pattern ◽  
Earnings Prediction ◽  
Cost Behavior ◽  
Cost Variability ◽  
Available Information ◽  
Cost Stickiness ◽  
Jel Classifications

ABSTRACT Recent work in management accounting offers several novel insights into firms' cost behavior. This study explores whether financial analysts appropriately incorporate information on two types of cost behavior in predicting earnings—cost variability and cost stickiness. Since analysts' utilization of information is not directly observable, we model the process of earnings prediction to generate empirically testable hypotheses. The results indicate that analysts “converge to the average” in recognizing both cost variability and cost stickiness, resulting in substantial and systematic earnings forecast errors. Particularly, we find a clear pattern—inappropriate incorporation of available information on cost behavior in earnings forecasts leads to larger errors in unfavorable scenarios than in favorable ones. Overall, enhancing analysts' awareness of the expense side is likely to improve their earnings forecasts, mainly when sales turn to the worse. JEL Classifications: M41; M46; G12.

Sign in / Sign up

Export Citation Format

Share Document