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Determinants of dynamic dependence between the crude oil and tanker freight markets: a mixed-frequency data sampling copula model

Shi, W ORCID: 0000-0001-6551-0499, Gong, Y, Yin, J, Nguyen, S and Liu, Q 2022 , 'Determinants of dynamic dependence between the crude oil and tanker freight markets: a mixed-frequency data sampling copula model' , Energy, vol. 254 , pp. 1-12 , doi: 10.1016/j.energy.2022.124354.

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Abstract

Discovering how different oil price shocks influence dynamic dependence between the crude oil and tanker freight markets is vital to ship operators and owners responses to different shocks. This study proposes a mixed-frequency data sampling copula model to identify the determinants and analyze their impacts on dynamic dependence between the two markets. Using a dataset covering 2 January 2002 to 30 November 2021, the proposed copula model achieved better goodness-of-fit performance by incorporating the monthly explanatory variables into the dynamic evolution of the daily correlations. As indicated, oil non-supply shocks primarily determined their correlations without considering extreme market conditions, which lasted for approximately 24 months. Additionally, the determinants of the dynamic correlations were oil supply and non-supply shocks in the jointly crashing markets, which were found to be oil non-supply and tanker-specific shocks in the jointly booming markets. Their impacts can last up to six months. These findings enable ship operators and owners to better understand how oil price shocks affect dynamic dependence between the two markets, thus improving their decisions regarding ship chartering, ship selling/purchasing, operating speed, and derivative product investments.

Item Type: Article
Authors/Creators:Shi, W and Gong, Y and Yin, J and Nguyen, S and Liu, Q
Keywords: shipping, mixed-frequency data sampling, nonlinearity, asymmetric tail dependence structure, operational decisions
Journal or Publication Title: Energy
Publisher: Pergamon-Elsevier Science Ltd
ISSN: 0360-5442
DOI / ID Number: 10.1016/j.energy.2022.124354
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© 2022 Elsevier Ltd. All rights reserved.

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