Can Asymmetric Conditional Volatility Imply Asymmetric Tail Dependence?


Kim, Jong-Min / Hojin, Jung



In this article, we investigate two types of asymmetries, that is, the asymmetry of conditional volatility and the asymmetry of tail dependence in the crude oil markets. We employ the two different sample datasets in which each dataset covers the time period of stable and unstable oil prices, individually. A variety of different copulas and three asymmetric GARCH regression models are used in order to capture the two types of asymmetries. In particular, we extend the TBL-GARCH model proposed by Choi et. al. (2012) to the asymmetric GARCH regression type model. The findings from the two different approaches are congruent, in that there is no asymmetry of tail dependence and no asymmetric conditional volatility in crude oil returns over the two different sample periods. Our study reconfirms the findings of Aboura and Wagner (2016) by showing that asymmetric conditional volatility relates to asymmetric tail dependence.


Copula, Granger's causality, Tail dependence, Asymmetric GARCH regression, Asymmetric conditional volatility

Kim, J. / Jung, H.: Can Asymmetric Conditional Volatility Imply Asymmetric Tail Dependence?, in: Economic Modelling, Vol. 64 August 2017, pp. 409-418

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