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:	Refereed Article
Keywords:	shipping, mixed-frequency data sampling, nonlinearity, asymmetric tail dependence structure, operational decisions
Research Division:	Commerce, Management, Tourism and Services
Research Group:	Transportation, logistics and supply chains
Research Field:	Maritime transportation and freight services
Objective Division:	Transport
Objective Group:	Water transport
Objective Field:	International sea freight transport (excl. live animals, food products and liquefied gas)
UTAS Author:	Shi, W (Dr Wenming Shi)
UTAS Author:	Nguyen, S (Mr Son Nguyen)
ID Code:	150160
Year Published:	2022
Deposited By:	Maritime and Logistics Management
Deposited On:	2022-05-30
Last Modified:	2022-10-10
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