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Country Risk Ratings and Stock Market Returns in BRICS Countries: A Nonlinear Dynamic Approach

Author

Listed:
  • Adnen Ben Nasr

    (Université de Tunis, ISGT, BESTMOD, Le Bardo, Tunisia)

  • Juncal Cunado

    (University of Navarra, Pamplona, Spain)

  • Rıza Demirer

    (Department of Economics & Finance, Southern Illinois University Edwardsville, Edwardsville, USA)

  • Rangan Gupta

    (Department of Economics, University of Pretoria, Pretoria, South Africa)

Abstract

This study examines the linkages between BRICS stock market returns, country risk ratings and international factors via Non-linear Auto Regressive Distributed Lags models (NARDL) that allow 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.

Suggested Citation

  • Adnen Ben Nasr & Juncal Cunado & Rıza Demirer & Rangan Gupta, 2017. "Country Risk Ratings and Stock Market Returns in BRICS Countries: A Nonlinear Dynamic Approach," Working Papers 201758, University of Pretoria, Department of Economics.
    • Handle: RePEc:pre:wpaper:201758
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    Cited by:

    1. Hasan Dinçer & Serhat Yüksel & Seçil Şenel, 2018. "Analyzing the Global Risks for the Financial Crisis after the Great Depression Using Comparative Hybrid Hesitant Fuzzy Decision-Making Models: Policy Recommendations for Sustainable Economic Growth," Sustainability, MDPI, vol. 10(9), pages 1-15, September.

    More about this item

    Keywords

    Asymmetric responses; NARDL models; Stock market returns; Country risk ratings;
    All these keywords.

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • F21 - International Economics - - International Factor Movements and International Business - - - International Investment; Long-Term Capital Movements
    • G32 - Financial Economics - - Corporate Finance and Governance - - - Financing Policy; Financial Risk and Risk Management; Capital and Ownership Structure; Value of Firms; Goodwill

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