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Reexamining the time-varying volatility spillover effects: A Markov switching causality approach

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  • Zheng, Tingguo
  • Zuo, Haomiao

Abstract

This paper intends to examine the volatility spillover effect between selective developed markets including U.S., U.K., Germany, Japan and Hong Kong over the sample period from 1996 to 2011. We introduce a Markov switching causality method to model the potential instability of volatility spillover relationships over market tranquil or turmoil periods. This method is more flexible as no prior information on the changing points or size of sample window is needed. From the empirical results, we find the evidence of the existence of spillover effects among most markets, and the bilateral volatility spillover effects are more prominent over turmoil or crisis episodes, especially during Asia crisis and subprime mortgage crisis periods. Moreover, the distinct role of each market is also investigated.

Suggested Citation

  • Zheng, Tingguo & Zuo, Haomiao, 2013. "Reexamining the time-varying volatility spillover effects: A Markov switching causality approach," The North American Journal of Economics and Finance, Elsevier, vol. 26(C), pages 643-662.
  • Handle: RePEc:eee:ecofin:v:26:y:2013:i:c:p:643-662
    DOI: 10.1016/j.najef.2013.05.001
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    Cited by:

    1. 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.
    2. Huo, Rui & Ahmed, Abdullahi D., 2017. "Return and volatility spillovers effects: Evaluating the impact of Shanghai-Hong Kong Stock Connect," Economic Modelling, Elsevier, vol. 61(C), pages 260-272.
    3. Balcilar, Mehmet & Gungor, Hasan & Hammoudeh, Shawkat, 2015. "The time-varying causality between spot and futures crude oil prices: A regime switching approach," International Review of Economics & Finance, Elsevier, vol. 40(C), pages 51-71.
    4. Balcilar, Mehmet & Demirer, Rıza & Hammoudeh, Shawkat, 2014. "What drives herding in oil-rich, developing stock markets? Relative roles of own volatility and global factors," The North American Journal of Economics and Finance, Elsevier, vol. 29(C), pages 418-440.
    5. Liu, Xueyong & An, Haizhong & Huang, Shupei & Wen, Shaobo, 2017. "The evolution of spillover effects between oil and stock markets across multi-scales using a wavelet-based GARCH–BEKK model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 465(C), pages 374-383.
    6. repec:taf:oaefxx:v:4:y:2016:i:1:p:1210996 is not listed on IDEAS
    7. Majdoub, Jihed & Mansour, Walid, 2014. "Islamic equity market integration and volatility spillover between emerging and US stock markets," The North American Journal of Economics and Finance, Elsevier, vol. 29(C), pages 452-470.
    8. Alotaibi, Abdullah R. & Mishra, Anil V., 2015. "Global and regional volatility spillovers to GCC stock markets," Economic Modelling, Elsevier, vol. 45(C), pages 38-49.
    9. repec:eee:eneeco:v:66:y:2017:i:c:p:108-115 is not listed on IDEAS

    More about this item

    Keywords

    Volatility spillover; Markov switching; Granger causality; Range;

    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
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics

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