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Stochastic volatility and time-varying country risk in emerging markets

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  • Anders Johansson

Abstract

This study suggests an alternative method to estimate time-varying country risk. We first apply a new multivariate stochastic volatility (SV) model to a set of emerging stock markets. To estimate the SV model, we use a Bayesian Markov chain Monte Carlo simulation procedure. By applying the deviance information criterion, we show that the new model performs well relative to alternative multivariate SV models. We then compute the conditional betas for the different markets and compare the results with an often-used procedure based on multivariate GARCH models. We show that the new multivariate SV model more accurately captures the time-varying nature of country risk. The conditional betas show signs of large variations, indicating the importance of taking time-varying country risk into consideration when managing emerging market portfolios.

Suggested Citation

  • Anders Johansson, 2009. "Stochastic volatility and time-varying country risk in emerging markets," The European Journal of Finance, Taylor & Francis Journals, vol. 15(3), pages 337-363.
  • Handle: RePEc:taf:eurjfi:v:15:y:2009:i:3:p:337-363
    DOI: 10.1080/13518470802466006
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    Citations

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    Cited by:

    1. Johansson, Anders C., 2010. "Asian sovereign debt and country risk," Pacific-Basin Finance Journal, Elsevier, vol. 18(4), pages 335-350, September.
    2. Anders Johansson, 2009. "An analysis of dynamic risk in the Greater China equity markets," Journal of Chinese Economic and Business Studies, Taylor & Francis Journals, vol. 7(3), pages 299-320.
    3. Pop, Raluca Elena, 2012. "Herd behavior towards the market index: evidence from Romanian stock exchange," MPRA Paper 51595, University Library of Munich, Germany.
    4. Jaramillo, Laura & Weber, Anke, 2013. "Bond yields in emerging economies: It matters what state you are in," Emerging Markets Review, Elsevier, vol. 17(C), pages 169-185.
    5. Асатуров К.Г., 2015. "Динамические Модели Систематического Риска: Сравнение На Примере Индийского Фондового Рынка," Журнал Экономика и математические методы (ЭММ), Центральный Экономико-Математический Институт (ЦЭМИ), vol. 51(4), pages 59-75, октябрь.
    6. Yang, Hsin-Feng & Liu, Chih-Liang & Chou, Ray Yeutien, 2014. "Interest rate risk propagation: Evidence from the credit crunch," The North American Journal of Economics and Finance, Elsevier, vol. 28(C), pages 242-264.
    7. Amir Saadaoui & Younes Boujelbene, 2014. "Volatility Transmission between Bond and Stock Markets: Case of Emerging Financial Markets," Acta Universitatis Danubius. OEconomica, Danubius University of Galati, issue 10(6), pages 84-98, December.
    8. Johansson, Anders C., 2010. "Stock and Bond Relationships in Asia," Working Paper Series 2010-14, Stockholm School of Economics, China Economic Research Center.
    9. Chevapatrakul, Thanaset, 2013. "Return sign forecasts based on conditional risk: Evidence from the UK stock market index," Journal of Banking & Finance, Elsevier, vol. 37(7), pages 2342-2353.

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