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Analyzing quantile spillover effects among international financial markets

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  • Wang, Jie
  • Liu, Tangyong
  • Pan, Na

Abstract

This paper investigates the quantile-based spillover effects among 17 stock markets from January 1993 to January 2022, utilizing a quantile approach based on the variance decomposition of a quantile vector autoregression (QVAR) model. Compared with the traditional mean-based spillover measures, this new quantile approach allows for a nuanced investigation of spillovers at every quantile and capture spillovers under extreme events. The results show that: (1) the total spillover is high and exhibits strong time-varying characteristics, and the tail spillover is higher and more complex in scale and direction; (2) the spillover at each quantile level shows an upward trend, especially during the 2008 crisis and the COVID-19 epidemic; (3) developed countries (or regions) are the net exporters of stock market spillovers, while the developing countries are the net importers; and (4) the 17 stock markets constitute different local financial networks, which may be related to economic conditions and geographical location.

Suggested Citation

  • Wang, Jie & Liu, Tangyong & Pan, Na, 2023. "Analyzing quantile spillover effects among international financial markets," The North American Journal of Economics and Finance, Elsevier, vol. 64(C).
    • Handle: RePEc:eee:ecofin:v:64:y:2023:i:c:s1062940823000049
    DOI: 10.1016/j.najef.2023.101881
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    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
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets

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