2022
DOI: 10.1108/mabr-04-2021-0033
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Influencing factors of crude oil maritime shipping freight fluctuations: a case of Suezmax tankers in Europe–Africa routes

Abstract: PurposeThe paper aims to identify the contributors to freight rate fluctuations in the Suezmax tanker market; this study selected the refinery output, crude oil price, one-year charter rate and fleet development as the main influencing factors for the market analysis.Design/methodology/approachThe paper used the VEC (vector error correction) model to evaluate the degree of impact of each influencing factor on Suezmax tanker freight rates, as well as the interplay between these factors.FindingsThe conclusion an… Show more

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Cited by 2 publications
(1 citation statement)
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“…The paramount aim of this analytical framework is to elucidate the statistical attributes inherent to time-series data, thereby gaining insight into the intrinsic dynamical systems [28,29]. The array of studies on tanker freight rate volatility represents a vital component of maritime economics, with ramifications extending into the broader global economy [30][31][32][33][34]. These time series analyses delve into the interplay between numerous variables affecting freight rates, such as crude oil prices, charter rates, fleet size, and policy changes, aiming to enhance forecasting models and risk management practices within the shipping industry [35][36][37][38][39][40].…”
Section: Introductionmentioning
confidence: 99%
“…The paramount aim of this analytical framework is to elucidate the statistical attributes inherent to time-series data, thereby gaining insight into the intrinsic dynamical systems [28,29]. The array of studies on tanker freight rate volatility represents a vital component of maritime economics, with ramifications extending into the broader global economy [30][31][32][33][34]. These time series analyses delve into the interplay between numerous variables affecting freight rates, such as crude oil prices, charter rates, fleet size, and policy changes, aiming to enhance forecasting models and risk management practices within the shipping industry [35][36][37][38][39][40].…”
Section: Introductionmentioning
confidence: 99%