Using nonparametric copulas to measure crude oil price co-movements

Anson Ho (), Kim Huynh and David Jacho-Chávez

Energy Economics, 2019, vol. 82, issue C, 211-223

Abstract: Tail dependence of crude oil price returns between four major benchmark markets are analyzed through the lenses of nonparametric copula models. This paper illustrates that nonparametric copula is flexible to incorporate important empirical patterns of tail dependence and provides better goodness-of-fit to the data than the optimal parametric copula. Estimation results show that the level and the structure of tail dependence of crude oil returns vary significantly depending on data frequency and the time period covered.

Keywords: Crude oil prices; Nonparametric copula; Tail dependence; Co-movement (search for similar items in EconPapers)
JEL-codes: C22 C46 C51 F41 G32 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:eneeco:v:82:y:2019:i:c:p:211-223

DOI: 10.1016/j.eneco.2018.05.022

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