The volatility transmission between crude oil market and tanker freight market

Dai, Lei; Hu, Hao; Tao, Yu; Lee, Seungwon

doi:10.1504/ijstl.2020.111122

Cited by 3 publications

(2 citation statements)

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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%

Multifractal Dynamics and Complexity Transformation in the Tanker Freight Market

Chen,

Liang

2024

Preprint

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This research investigates the complex transformation of the Baltic Clean and Dirty Tankers markets from 1998 to 2023. Our study quantifies the market multifractality in two distinct periods, from 1998 to 2010 and 2010 to 2023. We compare multifractal measures of the original, surrogated, and shuffled data, which indicate high multifractality and a complex market structure influenced by temporal organization and inherent volatility. Shuffled data analysis emphasizes the critical role of temporal sequences within market behaviour. Additionally, the study delves into external factors such as regulatory changes, economic disturbances, technological innovation, and environmental concerns contributing to market complexity. A distinct shift in multifractal values between the two periods suggests an evolution from crisis-induced complexities to a market influenced by diversified and modern dynamics. Our findings offer a concise understanding of the multifractal nature of the tanker markets and how global crises can impact the markets, emphasizing the importance of considering systemic risks in freight market analysis.

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Section: Introductionmentioning

confidence: 99%

Multifractal Dynamics and Complexity Transformation in the Tanker Freight Market

Chen,

Liang

2024

Preprint

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“…Regli and Nomikos (2019) used the AIS technology as a measure of capacity input in the new tanker market, improving the price discoverability of freight rates. Dai et al (2020) used the BEKK-GARCH model to analyze Baltic Dirty Tanker Index (BDTI) and Brent crude oil prices from January 2007 to November 2015. The study showed that volatility shifted from the crude oil market to the tanker market rather than from the tanker market to the crude oil market over the long term.…”

Section: Introductionmentioning

confidence: 99%

Influencing factors of crude oil maritime shipping freight fluctuations: a case of Suezmax tankers in Europe–Africa routes

Chen

Zhao

Xiong

et al. 2022

MABR

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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 and results were tested using the 20-year data from 1999 to 2019, and the methodology and theory of this paper were proved to be effective. Results of this study provide effective reference for scholars to find the law of fluctuations in Suezmax tanker freight rates.Originality/valueThis paper provides a decision-making support tool for tanker operators to cope with fluctuation risks in the tanker shipping market.

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

Shi

Gong

Yin

et al. 2022

Energy

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The volatility transmission between crude oil market and tanker freight market

Cited by 3 publications

References 0 publications

Multifractal Dynamics and Complexity Transformation in the Tanker Freight Market

Multifractal Dynamics and Complexity Transformation in the Tanker Freight Market

Influencing factors of crude oil maritime shipping freight fluctuations: a case of Suezmax tankers in Europe–Africa routes

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

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