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Does Country Risks Predict Stock Returns and Volatility? Evidence from a Nonparametric Approach

Author

Listed:
  • Tahir Suleman

    (School of Economics and Finance, Victoria University of Wellington, New Zealand and School of Business, Wellington Institute of Technology, New Zealand)

  • Rangan Gupta

    (Department of Economics, University of Pretoria, Pretoria, 0002, South Africa; IPAG Business School, Paris, France)

  • Mehmet Balcilar

    (Department of Economics, Eastern Mediterranean University, Famagusta, via Mersin 10, Northern Cyprus,Turkey and Department of Economics, University of Pretoria, Pretoria, 0002, South Africa; IPAG Business School, Paris, France)

Abstract

We use the k-th order nonparametric causality test at monthly frequency over the period of 1984:1 to 2015:12 to analyze whether aggregate country risk, and its components (economic, financial and political) can predict movements in stock returns and volatility of eighty-three developed and developing economies. The nonparametric approach controls for the existing misspecification of a linear framework of causality, and hence, the weak evidence of causality obtained under the standard Granger tests cannot be relied upon. When we apply the nonparametric test, we find that, while there is no evidence of predictability of squared stock returns barring one case, at times, there are nearly 50 percent of the countries where the aggregate risks and its components tend to predict stock returns and realized volatility.

Suggested Citation

  • Tahir Suleman & Rangan Gupta & Mehmet Balcilar, 2016. "Does Country Risks Predict Stock Returns and Volatility? Evidence from a Nonparametric Approach," Working Papers 201675, University of Pretoria, Department of Economics.
  • Handle: RePEc:pre:wpaper:201675
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    References listed on IDEAS

    as
    1. Bekiros, Stelios & Gupta, Rangan & Kyei, Clement, 2016. "On economic uncertainty, stock market predictability and nonlinear spillover effects," The North American Journal of Economics and Finance, Elsevier, vol. 36(C), pages 184-191.
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    3. Bekiros, Stelios & Gupta, Rangan & Majumdar, Anandamayee, 2016. "Incorporating economic policy uncertainty in US equity premium models: A nonlinear predictability analysis," Finance Research Letters, Elsevier, vol. 18(C), pages 291-296.
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    5. Mehmet Balcilar & Stelios Bekiros & Rangan Gupta, 2017. "The role of news-based uncertainty indices in predicting oil markets: a hybrid nonparametric quantile causality method," Empirical Economics, Springer, vol. 53(3), pages 879-889, November.
    6. Goodness C. Aye & Mehmet Balcilar & Rangan Gupta, 2017. "International stock return predictability: Is the role of U.S. time-varying?," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 44(1), pages 121-146, February.
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    Citations

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    Cited by:

    1. Christos Bouras & Christina Christou & Rangan Gupta & Tahir Suleman, 2020. "Geopolitical Risks, Returns, and Volatility in Emerging Stock Markets: Evidence from a Panel GARCH Model," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 55(8), pages 1841-1856, July.
    2. Gupta, Rangan & Kollias, Christos & Papadamou, Stephanos & Wohar, Mark E., 2018. "News implied volatility and the stock-bond nexus: Evidence from historical data for the USA and the UK markets," Journal of Multinational Financial Management, Elsevier, vol. 47, pages 76-90.
    3. Zhang, Hongwei & Wang, Ying & Yang, Cai & Guo, Yaoqi, 2021. "The impact of country risk on energy trade patterns based on complex network and panel regression analyses," Energy, Elsevier, vol. 222(C).
    4. Gkillas, Konstantinos & Gupta, Rangan & Wohar, Mark E., 2018. "Volatility jumps: The role of geopolitical risks," Finance Research Letters, Elsevier, vol. 27(C), pages 247-258.
    5. Refk Selmi & Christos Kollias & Stephanos Papadamou & Rangan Gupta, 2017. "A Copula-Based Quantile-on-Quantile Regression Approach to Modeling Dependence Structure between Stock and Bond Returns: Evidence from Historical Data of India, South Africa, UK and US," Working Papers 201747, University of Pretoria, Department of Economics.
    6. Adam Zaremba, 2019. "The Cross Section of Country Equity Returns: A Review of Empirical Literature," JRFM, MDPI, vol. 12(4), pages 1-26, October.
    7. Lee, Chi-Chuan & Lee, Chien-Chiang & Li, Yong-Yi, 2021. "Oil price shocks, geopolitical risks, and green bond market dynamics," The North American Journal of Economics and Finance, Elsevier, vol. 55(C).
    8. Elie Bouri & Riza Demirer & Rangan Gupta & Hardik A. Marfatia, 2019. "Geopolitical Risks and Movements in Islamic Bond and Equity Markets: A Note," Defence and Peace Economics, Taylor & Francis Journals, vol. 30(3), pages 367-379, April.
    9. Qazi, Abroon, 2023. "Exploring Global Competitiveness Index 4.0 through the lens of country risk," Technological Forecasting and Social Change, Elsevier, vol. 196(C).
    10. Hemrit, Wael & Nakhli, Mohamed Sahbi, 2021. "Insurance and geopolitical risk: Fresh empirical evidence," The Quarterly Review of Economics and Finance, Elsevier, vol. 82(C), pages 320-334.

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    More about this item

    Keywords

    Country risks; returns; volatility; nonparametric higher-order causality;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)

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