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Modeling dynamic conditional correlations in WTI oil forward and futures returns

Authors: Alessandro Lanza; Alessandro Lanza; Alessandro Lanza; Michael McAleer; Michael McAleer; Michael McAleer; Matteo Manera; +1 Authors

Modeling dynamic conditional correlations in WTI oil forward and futures returns

Abstract

This paper estimates the dynamic conditional correlations in the returns on WTI oil one-month forward prices, and one-, three-, six-, and twelve-month futures prices, using recently developed multivariate conditional volatility models. The dynamic correlations enable a determination of whether the forward and various futures returns are substitutes or complements, which are crucial for deciding whether or not to hedge against unforeseen circumstances. The models are estimated using daily data on WTI oil forward and futures prices, and their associated returns, from 3 January 1985 to 16 January 2004. At the univariate level, the estimates are statistically significant, with the occasional asymmetric effect in which negative shocks have a greater impact on volatility than positive shocks. In all cases, both the short- and long-run persistence of shocks are statistically significant. Among the five returns, there are ten conditional correlations, with the highest estimate of constant conditional correlation being 0.975 between the volatilities of the three-month and six-month futures returns, and the lowest being 0.656 between the volatilities of the forward and twelve-month futures returns. The dynamic conditional correlations can vary dramatically, being negative in four of ten cases and being close to zero in another five cases. Only in the case of the dynamic volatilities of the three-month and six-month futures returns is the range of variation relatively narrow, namely (0.832, 0.996). Thus, in general, the dynamic volatilities in the returns in the WTI oil forward and future prices can be either independent or interdependent over time.

Country
Italy
Keywords

Q40, WTI oil prices, ARCH-Modell, Ölmarkt, dynamic conditional correlations; volatility; oil prices; WTI oil price; forward oil prices; futures oil prices, Futures prices and returns, Dynamic conditional correlations, G10, Constant conditional correlations, C32, Constant conditional correlations, Dynamic conditional correlations, Multivariate GARCH models, Forward prices and returns, Futures prices and returns, WTI oil prices, Rohstoffderivat, Multivariate GARCH models, Effizienzmarkthypothese, Ölpreis, Forward prices and returns, Korrelation, jel: jel:Q40, jel: jel:C32, jel: jel:G10, ddc: ddc:330

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
38
Top 10%
Top 10%
Average
Related to Research communities
Energy Research