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Dynamics and interactions between spot and forward freights in the dry bulk shipping market

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  • Jingbo Yin
  • Meifeng Luo
  • Lixian Fan

Abstract

Analyzing the interactions between spot and forward freight agreement (FFA) prices in the dry bulk shipping is important as they play a significant role for shipping companies to secure their profits and avoid potential risks in the volatile market. By applying the vector autoregression (VAR) and the vector error correction model (VECM), this paper identifies the long-run and mutual causal relationship between the spot and FFA prices on the BPI T/C and BCI C7 routes. Along with these cointegrating rates, exogenous factors such as the market demand and supply and some economic indices are also recognized as contributing variables for the dynamic movement of the spot and FFA prices. Importantly, the mean-reverting process is justified on both routes with different mechanisms. When the spot and FFA prices deviate from their equilibrium level in the short run, they will be adjusted to their long-run equilibrium more directly and clearly on the BPI T/C route than those on the BCI C7 route. It also indicates that this adjusting power has direction and size asymmetries on both routes. In addition, the impulse analysis indicates that the spot rate is more volatile than its corresponding FFA prices confronting innovations. The results of this study provide a reference to the participants in the dry bulk shipping market on the causes of fluctuation in spot and FFA prices and their interactions, which can be used to promote the risk management in the market.

Suggested Citation

  • Jingbo Yin & Meifeng Luo & Lixian Fan, 2017. "Dynamics and interactions between spot and forward freights in the dry bulk shipping market," Maritime Policy & Management, Taylor & Francis Journals, vol. 44(2), pages 271-288, February.
    • Handle: RePEc:taf:marpmg:v:44:y:2017:i:2:p:271-288
    DOI: 10.1080/03088839.2016.1253884
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    5. Sun, Xiaolin & Haralambides, Hercules & Liu, Hailong, 2019. "Dynamic spillover effects among derivative markets in tanker shipping," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 122(C), pages 384-409.
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    9. Ziaul Haque Munim & Hans-Joachim Schramm, 2021. "Forecasting container freight rates for major trade routes: a comparison of artificial neural networks and conventional models," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 23(2), pages 310-327, June.
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    14. Adland, Roar & Alizadeh, Amir H., 2018. "Explaining price differences between physical and derivative freight contracts," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 118(C), pages 20-33.
    15. Angelopoulos, Jason & Sahoo, Satya & Visvikis, Ilias D., 2020. "Commodity and transportation economic market interactions revisited: New evidence from a dynamic factor model," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 133(C).
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    17. Ko, Byoung-Wook, 2018. "Dynamic patterns of dry bulk freight spot rates through the lens of a time-varying coefficient model," Transportation Research Part A: Policy and Practice, Elsevier, vol. 118(C), pages 319-330.

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