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An empirical test of signalling theory

Burze Yasar (TED University, Ankara, Turkey)
Thomas Martin (Eastern Kentucky University, Richmond, Richmond, USA)
Timothy Kiessling (Sabanci University, Istanbul, Turkey)

Management Research Review

ISSN: 2040-8269

Article publication date: 30 April 2020

Issue publication date: 13 November 2020

1477

Abstract

Purpose

This study aims to support and extend signalling theory because of information asymmetry. This study also aims to answer the call to further negative signalling and explore immediate reactions to signals, thus alleviating a gap with regard to temporality of signalling.

Design/methodology/approach

The study used two separate data sources, the S&P 500 and 51,500 pages of the public papers between 1981 and 1999, nearly 20 years of data. Inter-rater reliability, controlled for all macroeconomic announcements identified in the literature, is used, and the data are empirically tested using generalized autoregressive conditional heteroscedasticity (GJR-GARCH) modelling.

Findings

In accordance with signalling theory and the efficient market hypothesis, the study found that receivers do react to positive signals from a credible insider signaller to obviate information asymmetry. In line with previous research, the study also finds that receivers react much stronger to negative signals.

Practical implications

Investors, financial managers and top executives responsible for their stock price need to focus on presidential signalling as these directly affect market volatility. In particular, investors and financial managers can predict stock price volatility based upon signals from the president.

Originality/value

This is the first research study that explores the correlation between presidential signalling and market volatility. This study is important for investors and financial managers.

Keywords

Citation

Yasar, B., Martin, T. and Kiessling, T. (2020), "An empirical test of signalling theory", Management Research Review, Vol. 43 No. 11, pp. 1309-1335. https://doi.org/10.1108/MRR-08-2019-0338

Publisher

:

Emerald Publishing Limited

Copyright © 2020, Emerald Publishing Limited

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