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Time Varying Risks Among Segments of the Tanker Freight Markets

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  • Manolis G Kavussanos

    (Athens University of Economics and Business, 76 Patission St, 10434, Athens, Greece.)

Abstract

The aim of this paper is to investigate the relative risks involved in owning and operating tanker vessels of different sizes in world spot and time-charter (TC) markets. Cointegrating Error Correction ARCH models are used to model spot and TC rates for each ship size and the associated time varying risks involved. The advantage of using this class of models for analysis is that the error correction term can capture the short-run dynamic behaviour of rates, while the estimation of time varying volatilities allows for the explicit comparison of risks at each point in time. Indeed, levels and patterns of freight risk are shown to vary over time. Broadly, comparison of these risks across markets point to TC rates having lower volatilities in comparison to the spot rates, and freight rates of larger vessels having higher volatilities compared to the freight volatilities of smaller vessels. Thus, for risk averse owners, wishing to reduce risks, results suggest operating tanker ships in TC rather than spot markets, and using smaller size vessels to diversify the higher risks involved in owning and operating larger size vessels. Maritime Economics & Logistics (2003) 5, 227–250. doi:10.1057/palgrave.mel.9100079

Suggested Citation

  • 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.
    • Handle: RePEc:pal:marecl:v:5:y:2003:i:3:p:227-250
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    Cited by:

    1. Zheng, Shiyuan & Lan, Xiangang, 2016. "Multifractal analysis of spot rates in tanker markets and their comparisons with crude oil markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 444(C), pages 547-559.
    2. Konstantinos D. Melas & Photis M. Panayides & Dimitris A. Tsouknidis, 2022. "Dynamic volatility spillovers and investor sentiment components across freight-shipping markets," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 24(2), pages 368-394, June.
    3. Alexandridis, George & Kavussanos, Manolis G. & Kim, Chi Y. & Tsouknidis, Dimitris A. & Visvikis, Ilias D., 2018. "A survey of shipping finance research: Setting the future research agenda," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 115(C), pages 164-212.
    4. Abdou, Hussein A. & Pointon, John & El-Masry, Ahmed & Olugbode, Moji & Lister, Roger J., 2012. "A variable impact neural network analysis of dividend policies and share prices of transportation and related companies," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 22(4), pages 796-813.
    5. 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.
    6. Albert W. Veenstra & Sébastien De La Fosse, 2006. "Contributions to maritime economics—Zenon S. Zannetos, the theory of oil tankship rates," Maritime Policy & Management, Taylor & Francis Journals, vol. 33(1), pages 61-73, February.
    7. Hossein Jafari & Ghazaleh Rahimi, 2018. "Forecasting dirty tanker freight rate index by using stochastic differential equations," International Journal of Financial Engineering (IJFE), World Scientific Publishing Co. Pte. Ltd., vol. 5(04), pages 1-15, December.
    8. Jiao Zhang & Qingcheng Zeng, 2017. "Modelling the volatility of the tanker freight market based on improved empirical mode decomposition," Applied Economics, Taylor & Francis Journals, vol. 49(17), pages 1655-1667, April.
    9. Tsouknidis, Dimitris A., 2016. "Dynamic volatility spillovers across shipping freight markets," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 91(C), pages 90-111.
    10. Bai, Xiwen, 2021. "Tanker freight rates and economic policy uncertainty: A wavelet-based copula approach," Energy, Elsevier, vol. 235(C).
    11. Lin, Arthur J. & Chang, Hai Yen & Hsiao, Jung Lieh, 2019. "Does the Baltic Dry Index drive volatility spillovers in the commodities, currency, or stock markets?," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 127(C), pages 265-283.
    12. 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.
    13. Kavussanos, Manolis G. & Tsouknidis, Dimitris A., 2014. "The determinants of credit spreads changes in global shipping bonds," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 70(C), pages 55-75.
    14. Kavussanos, Manolis G. & Tsouknidis, Dimitris A., 2016. "Default risk drivers in shipping bank loans," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 94(C), pages 71-94.
    15. Wolfgang Drobetz & Tim Richter & Martin Wambach, 2012. "Dynamics of time-varying volatility in the dry bulk and tanker freight markets," Applied Financial Economics, Taylor & Francis Journals, vol. 22(16), pages 1367-1384, August.
    16. Kavussanos, Manolis G. & Dimitrakopoulos, Dimitris N., 2011. "Market risk model selection and medium-term risk with limited data: Application to ocean tanker freight markets," International Review of Financial Analysis, Elsevier, vol. 20(5), pages 258-268.
    17. 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.
    18. Maitra, Debasish & Rehman, Mobeen Ur & Dash, Saumya Ranjan & Kang, Sang Hoon, 2021. "Oil price volatility and the logistics industry: Dynamic connectedness with portfolio implications," Energy Economics, Elsevier, vol. 102(C).
    19. Peter Nielsen & Liping Jiang & Niels Gorm Malý Rytter & Gang Chen, 2014. "An investigation of forecast horizon and observation fit's influence on an econometric rate forecast model in the liner shipping industry," Maritime Policy & Management, Taylor & Francis Journals, vol. 41(7), pages 667-682, December.
    20. 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.
    21. 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.
    22. Fred Espen Benth & Steen Koekebakker, 2016. "Stochastic modeling of Supramax spot and forward freight rates," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 18(4), pages 391-413, December.
    23. Syriopoulos, Theodore C., 2007. "Chapter 6 Financing Greek Shipping: Modern Instruments, Methods and Markets," Research in Transportation Economics, Elsevier, vol. 21(1), pages 171-219, January.
    24. Papapostolou, Nikos C. & Pouliasis, Panos K. & Kyriakou, Ioannis, 2017. "Herd behavior in the drybulk market: an empirical analysis of the decision to invest in new and retire existing fleet capacity," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 104(C), pages 36-51.

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