Country risk ratings and stock market returns in Brazil, Russia, India, and China (BRICS) countries: a nonlinear dynamic approach
Keywords: 
Asymmetric responses
NARDL models
Stock market returns
Country risk ratings
Issue Date: 
2018
Publisher: 
MDPI AG
Project: 
info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2013-2016/ECO2017-83183-R/ES/PRECIOS DEL PETROLEO Y DE LAS MATERIAS PRIMAS, INCERTIDUMBRE ECONOMICA, Y SU INTERACCION CON VARIABLES ECONOMICAS Y FINANCIERAS. IMPLICACIONES DE POLITICA
ISSN: 
2227-9091
Note: 
This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
Citation: 
Ben-Nasr, A. (Adnen); Cuñado, J. (Juncal); Demirer, R. (Riza); et al. "Country risk ratings and stock market returns in Brazil, Russia, India, and China (BRICS) countries: a nonlinear dynamic approach". Risks. 6 (3), 2018, 94
Abstract
This study examines the linkages between Brazil, Russia, India, and China (BRICS) stock market returns, country risk ratings, and international factors via Non-linear Auto Regressive Distributed Lags models (NARDL) that allow for testing the asymmetric effects of changes in country risk ratings on stock market returns. We show that BRICS countries exhibit quite a degree of heterogeneity in the interaction of their stock market returns with country-specific political, financial, and economic risk ratings. Positive and negative rating changes in some BRICS countries are found to have significant implications for both local stock market returns, as well as commodity price dynamics. While the commodity market acts as a catalyst for these emerging stock markets in the long-run, we also observe that negative changes in the country risk ratings generally command a higher impact on stock returns, implying the greater impact of bad news on market dynamics. Our findings suggest that not all BRICS nations are the same in terms of how they react to ratings changes and how they interact with global market variables.

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