Country risk ratings and stock market returns in Brazil, Russia, India, and China (Brics) countries: A nonlinear dynamic approach

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 s...

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Bibliographic Details
Main Authors: Cunado, J. (Author), Demirer, R. (Author), Gupta, R. (Author), Nasr, A.B (Author)
Format: Article
Language:English
Published: MDPI AG 2018
Subjects:
Online Access:View Fulltext in Publisher
LEADER 01899nam a2200217Ia 4500
001 10.3390-risks6030094
008 220706s2018 CNT 000 0 und d
020 |a 22279091 (ISSN) 
245 1 0 |a Country risk ratings and stock market returns in Brazil, Russia, India, and China (Brics) countries: A nonlinear dynamic approach 
260 0 |b MDPI AG  |c 2018 
856 |z View Fulltext in Publisher  |u https://doi.org/10.3390/risks6030094 
520 3 |a 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. © 2018 by the authors. Licensee MDPI, Basel, Switzerland. 
650 0 4 |a Asymmetric responses 
650 0 4 |a Country risk ratings 
650 0 4 |a NARDL models 
650 0 4 |a Stock market returns 
700 1 |a Cunado, J.  |e author 
700 1 |a Demirer, R.  |e author 
700 1 |a Gupta, R.  |e author 
700 1 |a Nasr, A.B.  |e author 
773 |t Risks