Abstract
This study analyzes the impact of VIX spillovers on market activities during extreme market conditions in 42 international equity markets from 1998 to 2014. Specifically, tail cross-dependence suggests that a small change in VIX significantly influences global market activities during extreme market conditions. The impact of VIX is asymmetric, which is more pronounced in bearish, highly volatile, and low trading volume markets. Moreover, VIX spillovers exhibit a stronger impact on returns in developed markets and on volatility in emerging markets. In terms of geographical location, the impact of VIX spillovers is more pronounced on returns in Europe and on volatility in Latin America. These findings indicate that international investors can potentially benefit from international portfolio diversification and can serve as useful guidance to policymakers in designing appropriate policies.
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Notes
Nevertheless, a number of related studies assess the spillover effect of the CBOE’s implied volatility indices among countries. For instance, Chen (2014) finds significant dependences, contagions, and causalities among the USA, Canada, Japan, and Germany, with the USA being the most dominant market. Moreover, asymmetric dynamic linkages are more pronounced when investor fear rises, particularly during periods of financial crisis. Jiang, Konstantinidi, and Skiadopoulos (2012) find spillover effects of news announcements on implied volatility between the USA and European markets.
White et al. (2015) highlight three main advantages of MVMQ. First, it directly measures tail dependences among interested variables. Second, the model begins from a traditional quantile regression model given by Koenker and Bassett (1978) that is robust to outliers when analyzing a financial time series. Third, the MVMQ model, as a semi-parametric technique, imposes minimal distributional assumptions on the data-generating process. Thus, it offers greater flexibility to estimate coefficients in the model in different market scenarios.
The unit-root test for all variables is less than one, thereby satisfying the stationarity requirement. The AIC optimal lag length is four for all countries. In general, one-way relationships are noted; changes in VIX Granger cause stock market returns, stock market volatility, and stock market abnormal trading volume, respectively, but not vice versa. The results are available upon request.
The Granger causality and VAR results are available upon request.
The sample includes Argentina, Austria, Canada, China, Czech Republic, Hong Kong, India, Indonesia, Japan, Korea, Malaysia, Mexico, Pakistan, the Philippines, Spain, Sweden, Taiwan, Thailand, Turkey, and the UK.
For brevity, we do not present the results of robustness tests. The results of the in-sample and the out-of-sample performance evaluation are available upon request.
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Acknowledgements
Special thanks go to Markus Schmid (the editor), the anonymous referee, Ben R. Marshall, Bart Frijns, Pornchai Chunchinda, Seksak Jumroenvong, Tatre Jantarakolica, and Termkiat Kanchanapoom for their suggestions and comments. We also thank Maria E. De Boyrie (the discussant) and the participants of the 2016 Annual Auckland Finance Meeting.
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Cheuathonghua, M., Padungsaksawasdi, C., Boonchoo, P. et al. Extreme spillovers of VIX fear index to international equity markets. Financ Mark Portf Manag 33, 1–38 (2019). https://doi.org/10.1007/s11408-018-0323-6
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DOI: https://doi.org/10.1007/s11408-018-0323-6