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Investigating dependencies among oil price and tanker market variables by copula-based multivariate models

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  • Zhang, Yi

Abstract

Crude oil price, bunker price, and tanker freight rate are very volatile in recent years. Uncertainties about the complicated relationships among these market variables could impose substantial business risks on investors, shipowners, ship operators, and charterers in oil transportation by tankers. A better understanding of the dependencies among these variables can help improve investment and operational decisions. This study aims to develop copula-based multivariate models for analyzing oil price and tanker market variables, and associated efficient approaches to reveal the time varying effects for the relationships. Given the volatilities in oil prices over the recent years, this study analyzes the impact that the changes in oil price has on bunker price and tanker freight rates. The West Texas Intermediate, Bloomberg Weighted Average Bunker Fuel Price, Baltic Handysize Index, Baltic Supramax Index and Baltic Panamax Index are analyzed using various selected copula models, from 2008 through 2015. Findings reveal that high oil price is a factor causing a weak dependence among the studied variables in the tanker market. The use of copula has more advantages over the conventional methods and can best characterize the relationships for the tanker market variables. The time varying effects in the dependences can be well identified in the copula modeling. The results could provide valuable information for the policy makers and participants in the maritime industry. The understanding of the dynamic relationships among the oil market could help the participants to foresee the potential risks and the policy makers to organize a more efficient market.

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  • Zhang, Yi, 2018. "Investigating dependencies among oil price and tanker market variables by copula-based multivariate models," Energy, Elsevier, vol. 161(C), pages 435-446.
    • Handle: RePEc:eee:energy:v:161:y:2018:i:c:p:435-446
    DOI: 10.1016/j.energy.2018.07.165
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    1. Aas, Kjersti & Czado, Claudia & Frigessi, Arnoldo & Bakken, Henrik, 2009. "Pair-copula constructions of multiple dependence," Insurance: Mathematics and Economics, Elsevier, vol. 44(2), pages 182-198, April.
    2. Kenneth J. Singleton, 2014. "Investor Flows and the 2008 Boom/Bust in Oil Prices," Management Science, INFORMS, vol. 60(2), pages 300-318, February.
    3. Matthias Fischer & Christian Kock & Stephan Schluter & Florian Weigert, 2009. "An empirical analysis of multivariate copula models," Quantitative Finance, Taylor & Francis Journals, vol. 9(7), pages 839-854.
    4. You, Wanhai & Guo, Yawei & Zhu, Huiming & Tang, Yong, 2017. "Oil price shocks, economic policy uncertainty and industry stock returns in China: Asymmetric effects with quantile regression," Energy Economics, Elsevier, vol. 68(C), pages 1-18.
    5. Turhan, M. Ibrahim & Sensoy, Ahmet & Ozturk, Kevser & Hacihasanoglu, Erk, 2014. "A view to the long-run dynamic relationship between crude oil and the major asset classes," International Review of Economics & Finance, Elsevier, vol. 33(C), pages 286-299.
    6. Payman Eslami & Kihyo Jung & Daewon Lee & Amir Tjolleng, 2017. "Predicting tanker freight rates using parsimonious variables and a hybrid artificial neural network with an adaptive genetic algorithm," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 19(3), pages 538-550, August.
    7. Liu, Tie-Ying & Lee, Chien-Chiang, 2018. "Will the energy price bubble burst?," Energy, Elsevier, vol. 150(C), pages 276-288.
    8. Zhang, Xun & Lai, K.K. & Wang, Shou-Yang, 2008. "A new approach for crude oil price analysis based on Empirical Mode Decomposition," Energy Economics, Elsevier, vol. 30(3), pages 905-918, May.
    9. Wei, Yanfeng & Guo, Xiaoying, 2017. "Oil price shocks and China's stock market," Energy, Elsevier, vol. 140(P1), pages 185-197.
    10. Martín-Barragán, Belén & Ramos, Sofia B. & Veiga, Helena, 2015. "Correlations between oil and stock markets: A wavelet-based approach," Economic Modelling, Elsevier, vol. 50(C), pages 212-227.
    11. Wang, Yudong & Guo, Zhuangyue, 2018. "The dynamic spillover between carbon and energy markets: New evidence," Energy, Elsevier, vol. 149(C), pages 24-33.
    12. Shahzad, Syed Jawad Hussain & Mensi, Walid & Hammoudeh, Shawkat & Rehman, Mobeen Ur & Al-Yahyaee, Khamis H., 2018. "Extreme dependence and risk spillovers between oil and Islamic stock markets," Emerging Markets Review, Elsevier, vol. 34(C), pages 42-63.
    13. Alizadeh, Amir H. & Talley, Wayne K., 2011. "Vessel and voyage determinants of tanker freight rates and contract times," Transport Policy, Elsevier, vol. 18(5), pages 665-675, September.
    14. Javier Poblacion, 2015. "The stochastic seasonal behavior of freight rate dynamics," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 17(2), pages 142-162, June.
    15. Claudio Chist� & Gary van Vuuren, 2014. "Investigating the cyclical behaviour of the dry bulk shipping market," Maritime Policy & Management, Taylor & Francis Journals, vol. 41(1), pages 1-19, January.
    16. Chen, Feier & Miao, Yuqi & Tian, Kang & Ding, Xiaoxu & Li, Tingyi, 2017. "Multifractal cross-correlations between crude oil and tanker freight rate," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 474(C), pages 344-354.
    17. Goulas, Lambros & Skiadopoulos, George, 2012. "Are freight futures markets efficient? Evidence from IMAREX," International Journal of Forecasting, Elsevier, vol. 28(3), pages 644-659.
    18. Lutz Kilian, 2009. "Not All Oil Price Shocks Are Alike: Disentangling Demand and Supply Shocks in the Crude Oil Market," American Economic Review, American Economic Association, vol. 99(3), pages 1053-1069, June.
    19. Manolis G Kavussanos, 2003. "Time Varying Risks Among Segments of the Tanker Freight Markets," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 5(3), pages 227-250, September.
    20. Gong, Xu & Lin, Boqiang, 2018. "Time-varying effects of oil supply and demand shocks on China's macro-economy," Energy, Elsevier, vol. 149(C), pages 424-437.
    21. Angela Poulakidas & Fred Joutz, 2009. "Exploring the link between oil prices and tanker rates," Maritime Policy & Management, Taylor & Francis Journals, vol. 36(3), pages 215-233, June.
    22. Alizadeh, Amir H. & Huang, Chih-Yueh & van Dellen, Stefan, 2015. "A regime switching approach for hedging tanker shipping freight rates," Energy Economics, Elsevier, vol. 49(C), pages 44-59.
    23. Wenming Shi & Zhongzhi Yang & Kevin X. Li, 2013. "The impact of crude oil price on the tanker market," Maritime Policy & Management, Taylor & Francis Journals, vol. 40(4), pages 309-322, July.
    24. Roar Adland & Kevin Cullinane, 2005. "A Time-Varying Risk Premium in the Term Structure of Bulk Shipping Freight Rates," Journal of Transport Economics and Policy, University of Bath, vol. 39(2), pages 191-208, May.
    25. Sukcharoen, Kunlapath & Zohrabyan, Tatevik & Leatham, David & Wu, Ximing, 2014. "Interdependence of oil prices and stock market indices: A copula approach," Energy Economics, Elsevier, vol. 44(C), pages 331-339.
    26. Paul Embrechts, 2009. "Copulas: A Personal View," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 76(3), pages 639-650, September.
    27. Block, Alexander Souza & Righi, Marcelo Brutti & Schlender, Sérgio Guilherme & Coronel, Daniel Arruda, 2015. "Investigating dynamic conditional correlation between crude oil and fuels in non-linear framework: The financial and economic role of structural breaks," Energy Economics, Elsevier, vol. 49(C), pages 23-32.
    28. Xu, Jane Jing & Yip, Tsz Leung & Marlow, Peter B., 2011. "The dynamics between freight volatility and fleet size growth in dry bulk shipping markets," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 47(6), pages 983-991.
    29. Alizadeh, Amir H. & Nomikos, Nikos K., 2007. "Investment timing and trading strategies in the sale and purchase market for ships," Transportation Research Part B: Methodological, Elsevier, vol. 41(1), pages 126-143, January.
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