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Can asymmetric conditional volatility imply asymmetric tail dependence?

Jong-Min Kim and Hojin Jung

Economic Modelling, 2017, vol. 64, issue C, 409-418

Abstract: 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.

Keywords: Copula; Granger's causality; Tail dependence; Asymmetric GARCH regression; Asymmetric conditional volatility (search for similar items in EconPapers)
JEL-codes: C10 G10 Q40 (search for similar items in EconPapers)
Date: 2017
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