Quotation Munim, Ziaul Haque, Schramm, Hans-Joachim. 2021. Forecasting container freight rates for the major trade routes: a comparison of artificial neural network and conventional models. Maritime Economics and Logistics. 23 (2), 310-327.


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Abstract

Major players in the maritime business such as shipping lines, charterers, shippers, and others rely heavily on container freight rate forecasts for operational decision making. The non-existence of a formal forward market in the container industry makes it necessary for them to rely on forecasts for their hedging strategy purposes, too. Thus, to identify better performing forecasting approaches, we compare three models, namely, Autoregressive Integrated Moving Average (ARIMA), Vector Autoregressive (VAR) or Vector Error Correction (VEC) and Artificial Neural Network (ANN) models. We examine the China containerised Freight Index (CCFI) as a collection of weekly freight rates published by the Shanghai Shipping Exchange (SSE) in four major trade routes. Overall, VAR/VEC models outperform ARIMA and ANN in training-sample forecasts, but ARIMA outperforms VAR and ANN taking test-samples. On route level, we observe two exceptions to this. ARIMA performs better for the Far East to Mediterranean in the training-sample, and the VEC model did the same in the Far East to US East Coast route in the test-sample. Hence, we advise the industry players to use ARIMA for forecasting container freight rates for major trade routes ex-China except for VEC in the case of the Far East to US East Coast route

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Publication's profile

Status of publication Published
Affiliation WU
Type of publication Journal article
Journal Maritime Economics and Logistics
WU-Journal-Rating new VW-D
Language English
Title Forecasting container freight rates for the major trade routes: a comparison of artificial neural network and conventional models
Volume 23
Number 2
Year 2021
Page from 310
Page to 327
Reviewed? Y
URL https://link.springer.com/journal/41278
DOI https://doi.org/10.1057/s41278-020-00156-5
Open Access N

Associations

People
Schramm, Hans-Joachim (Details)
External
Munim, Ziaul Haque (University of South-Eastern Norway, Norway)
Organization
Department of Global Business and Trade DP (Details)
Research areas (Ă–STAT Classification 'Statistik Austria')
5300 Economics (Details)
5332 Transport economics (Details)
5336 Commodity science (Details)
5337 World trade science (Details)
5344 Foreign trade (Details)
5354 Business logistics (Details)
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