There is no smoke without fire: Does the context of earnings management contain information about future stock returns?

Iqbal, Abdullah and Nguyen, Nguyet Thi Minh and Shiwakoti, Radha K. (2015) There is no smoke without fire: Does the context of earnings management contain information about future stock returns? In: American Accounting Association Annual Meeting, 07-12 Aug 2015, Chicago, USA. (Unpublished) (The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided)

The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided. (Contact us about this Publication)

Abstract

This paper constructs a signal-based composite index, namely ESCORE, which captures the context of earnings management. Specifically, ESCORE aggregates 15 individual signals related to earnings management based on prior relevant literature. Empirical results using UK data shows that when ESCORE is higher, firms do manage earnings with greater magnitude and are more likely to be most aggressive, both in accruals and real earnings management. The study also finds that low ESCORE firms outperform those with high ESCORE by 1.37% per month after controlling for risk loadings on the market, size, book-to-market and momentum factors up to one year after portfolio formation.

Item Type:	Conference or workshop item (Paper)
Uncontrolled keywords:	Earnings management; market anomaly; stock returns predictability; earnings management detection models.
Subjects:	H Social Sciences > HF Commerce > HF5601 Accounting H Social Sciences > HG Finance
Divisions:	Faculties > Social Sciences > Kent Business School Faculties > Social Sciences > Kent Business School > Accounting and Finance
Depositing User:	Abdullah Iqbal
Date Deposited:	28 Nov 2017 11:24 UTC
Last Modified:	29 Nov 2017 12:24 UTC
Resource URI:	https://kar.kent.ac.uk/id/eprint/64815 (The current URI for this page, for reference purposes)
Iqbal, Abdullah:	https://orcid.org/0000-0002-3013-1007