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Asymmetric linkages among the fear index and emerging market volatility indices
Institution:1. Department of Finance, Business School, Auckland University of Technology, Private Bag 92006, Auckland 1142, New Zealand;2. Department of Economics, European University Institute Via della Piazzuola, 43, I-50133, Florence, Italy;3. Trinity Business School, Trinity College Dublin, College Green, Ireland;4. Department of Management and Engineering, Economic Division, Linkoping University, 58183, Linkoping, Sweden;1. Schulich School of Business, 4700 Keele Street, Toronto, Ontario M3J 1P3, Canada;2. Continuity Capital Partners, Level 8, 12 Moore Street, Canberra, Australian Capital Territory 2601, Australia;3. University of Western Australia Business School, 35 Stirling Highway, Crawley, Western Australia 6009, Australia
Abstract:This study explores the relationships between changes in the fear index (VIX) and changes in emerging market volatilities i.e., Chinese, Brazilian and the overall emerging volatility index, across their conditional distributions by employing a mixed Quantile regression - Copula methodological approach. Moreover, we analyze whether emerging market volatility indices would respond asymmetrically to positive and negative volatility shocks in the fear index i.e., whether the relationships are asymmetric between the VIX and the emerging market volatilities. Our results confirm that there are strong positive relationships between changes in the VIX and emerging market volatilities, and the linkages tend to be stronger for the upper-parts of the conditional distributions, namely above the median-quantiles up to the extreme-quantiles. In all cases, the nature of the relationship appears to be contemporaneous and on average is three times stronger than their lagged relationship. Further test results reveal that the relationship is highly asymmetric i.e., the effect of a positive shock in the VIX is on average about twice more pronounced than the effect of a negative shock at the extreme-tails of their conditional distributions, a stylized fact that cannot be revealed via conventional estimation methods as OLS. If we compare the effects of positive and negative VIX shocks on emerging market volatilities utilizing QRM, Copulas and OLS, our findings reveal that the effect of a positive shock by the QRM at the 95% quantile is about eight times higher than the one revealed by OLS. An exhaustive robustness analysis is also performed with respect to other volatility measures.
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