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.

Sprache
Englisch

Erschienen in
Journal: Cogent Economics & Finance ; ISSN: 2332-2039 ; Volume: 9 ; Year: 2021 ; Issue: 1 ; Pages: 1-24

Klassifikation
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
Thema
earnings announcements
Indian stock market
information leakage
predictability of earnings
Quarterly disclosure
return premium

Ereignis
Geistige Schöpfung
(wer)
Kundu, Sayantan
Banerjee, Aditya
Ereignis
Veröffentlichung
(wer)
Taylor & Francis
(wo)
Abingdon
(wann)
2021

DOI
doi:10.1080/23322039.2021.1898112
Handle
Letzte Aktualisierung
10.03.2025, 11:42 MEZ

Datenpartner

Dieses Objekt wird bereitgestellt von:
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.

Objekttyp

  • Artikel

Beteiligte

  • Kundu, Sayantan
  • Banerjee, Aditya
  • Taylor & Francis

Entstanden

  • 2021

Ähnliche Objekte (12)