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A study of the relationships between the time charter and spot freight rates

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  • Hong Zhang
  • Qingcheng Zeng

Abstract

A time charter contract is a shipping contract that allows for freight rate risk avoidance and hedging. Defining the relationship between time charter and spot freight rates will illuminate the fluctuation mechanism of the spot freight market. In this article, three types of dry bulk ships – Capsize, Panamax and Supramax – are chosen to investigate the relationship between time charter and spot freight rates and to analyse the price discovery function of time charter contracts. A vector error correction model is developed, and an impulse response function is used to analyse the influence of time charter rates on spot freight rates. Empirical studies indicate that there are two-way lead–lag relationships between the time charter and spot freight rates and that a time charter contract has a price discovery function. Smaller ship sizes and longer durations lead to a stronger price discovery function.

Suggested Citation

  • Hong Zhang & Qingcheng Zeng, 2015. "A study of the relationships between the time charter and spot freight rates," Applied Economics, Taylor & Francis Journals, vol. 47(9), pages 955-965, February.
    • Handle: RePEc:taf:applec:v:47:y:2015:i:9:p:955-965
    DOI: 10.1080/00036846.2014.985371
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    Citations

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    Cited by:

    1. Ziaul Haque Munim & Hans-Joachim Schramm, 0. "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. 0, pages 1-18.
    2. Jaeung Cha & Jinwoo Lee & Changhee Lee & Yulseong Kim, 2021. "Legal Disputes under Time Charter in Connection with the Stranding of the MV Ever Given," Sustainability, MDPI, vol. 13(19), pages 1-25, September.
    3. Zhong, Huiling & Zhang, Fa & Gu, Yimiao, 2021. "A Stackelberg game based two-stage framework to make decisions of freight rate for container shipping lines in the emerging blockchain-based market," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 149(C).
    4. Ioannis Karaoulanis & Theodore Pelagidis, 2021. "Panamax markets behaviour: explaining volatility and expectations," Journal of Shipping and Trade, Springer, vol. 6(1), pages 1-24, December.
    5. 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.
    6. Majid Taghavi & Kai Huang, 2016. "A multi‐stage stochastic programming approach for network capacity expansion with multiple sources of capacity," Naval Research Logistics (NRL), John Wiley & Sons, vol. 63(8), pages 600-614, December.
    7. Evangelia Kasimati & Nikolaos Veraros, 2017. "Is there accuracy of forward freight agreements in forecasting future freight rates? An empirical investigation," Working Papers 230, Bank of Greece.

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