Artikel
Predictability of earnings and its impact on stock returns: Evidence from India
The purpose of this paper is to analyse the predictability of earnings information before the quarterly disclosure date. Two categories of firms are contrasted: the firms that announce better quarterly earnings than the prior period and the firms that do not. The paper uses a sample of 67 large-cap Indian stocks over 33 quarters from 2010 to 2018. Panel data estimation with fixed and random effects is applied to examine the impact of quarterly earnings announcements on stock returns. Results show that all stocks experience return premiums in the pre-announcement period, which is already documented in the literature. The paper adds to the literature by finding that the firms that report better earnings numbers than the previous period generate significantly higher stock returns. It is inferred that the market can anticipate whether the firm will announce better earnings than the prior period. The paper shows that changes in revenue and core earnings are better anticipated. Post-announcement, stock prices adjust to reflect the disclosed earnings information, and only non-performers experience a drop in stock prices. It is the first comprehensive study of liquid large-cap Indian stocks that provides evidence on the behaviour of stock returns around earnings announcements.
- Language
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Englisch
- Bibliographic citation
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Journal: Cogent Economics & Finance ; ISSN: 2332-2039 ; Volume: 9 ; Year: 2021 ; Issue: 1 ; Pages: 1-24
- Classification
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Wirtschaft
General Financial Markets: General (includes Measurement and Data)
Portfolio Choice; Investment Decisions
Asset Pricing; Trading Volume; Bond Interest Rates
Information and Market Efficiency; Event Studies; Insider Trading
- Subject
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earnings announcements
Indian stock market
information leakage
predictability of earnings
Quarterly disclosure
return premium
- Event
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Geistige Schöpfung
- (who)
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Kundu, Sayantan
Banerjee, Aditya
- Event
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Veröffentlichung
- (who)
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Taylor & Francis
- (where)
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Abingdon
- (when)
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2021
- DOI
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doi:10.1080/23322039.2021.1898112
- Handle
- Last update
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10.03.2025, 11:42 AM CET
Data provider
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. If you have any questions about the object, please contact the data provider.
Object type
- Artikel
Associated
- Kundu, Sayantan
- Banerjee, Aditya
- Taylor & Francis
Time of origin
- 2021
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