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Forecasting container shipping freight rates for the Far East – Northern Europe trade lane

Author

Listed:
  • Ziaul Haque Munim

    () (University of Agder)

  • Hans-Joachim Schramm

    (WU Vienna University of Economics and Business
    Copenhagen Business School)

Abstract

This study introduces a state-of-the-art volatility forecasting method for container shipping freight rates. Over the last decade, the container shipping industry has become very unpredictable. The demolition of the shipping conferences system in 2008 for all trades calling a port in the European Union (EU) and the global financial crisis in 2009 have affected the container shipping freight market adversely towards a depressive and non-stable market environment with heavily fluctuating freight rate movements. At the same time, the approaches of forecasting container freight rates using econometric and time series modelling have been rather limited. Therefore, in this paper, we discuss contemporary container freight rate dynamics in an attempt to forecast for the Far East to Northern Europe trade lane. Methodology-wise, we employ autoregressive integrated moving average (ARIMA) as well as the combination of ARIMA and autoregressive conditional heteroscedasticity (ARCH) model, which we call ARIMARCH. We observe that ARIMARCH model provides comparatively better results than the existing freight rate forecasting models while performing short-term forecasts on a weekly as well as monthly level. We also observe remarkable influence of recurrent general rate increases on the container freight rate volatility.

Suggested Citation

  • Ziaul Haque Munim & Hans-Joachim Schramm, 2017. "Forecasting container shipping freight rates for the Far East – Northern Europe trade lane," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 19(1), pages 106-125, March.
  • Handle: RePEc:pal:marecl:v:19:y:2017:i:1:d:10.1057_s41278-016-0051-7
    DOI: 10.1057/s41278-016-0051-7
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    References listed on IDEAS

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    Cited by:

    1. Zaili Yang & Esin Erol Mehmed, 2019. "Artificial neural networks in freight rate forecasting," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 21(3), pages 390-414, September.
    2. 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.
    3. Svetlana Avdasheva & Svetlana Golovanova & Gyuzel Yusupova, 2019. "Advance freight rate announcements (GRI) in liner shipping: European and Russian regulatory settlements compared," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 21(2), pages 192-206, June.

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