Keyword: freight rates


Impacts of a bunker levy on decarbonizing shipping: A tanker case study

Sotiria Lagouvardou, Harilaos N. Psaraftis, Thalis Zis

The pressure on shipping to reduce its carbon footprint is increasing. Various measures are being proposed at the International Maritime Organization (IMO), including MarketBased Measures (MBMs). This paper investigates the potential of a bunker levy in achieving short-term CO2 emissions reductions. The analysis focuses on the tanker market and uses data from the latest IMO GHG studies and a variety of other sources. The connection between fuel prices and freight rates on the one hand and vessel speeds on the other is investigated for the period 2010-2018. A model to find a tanker’s optimal laden and ballast speeds is also developed and applied to a variety of scenarios. Results show that a bunker levy, depending on the scenario, can lead to short-term CO2 emissions reductions of up to 43%. Policy implications are also discussed, particularly vis-à-vis recent IMO and European Union (EU) action on MBMs.

Transportation Research. Part D: Transport & Environment / 2022
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Forecasting container shipping freight rates for the Far East – Northern Europe trade lane

Munim, Ziaul Haque; Schramm, Hans-Joachim

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.

Maritime Economics and Logistics / 2017
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