Forecasting tanker freight rate using neural networks |
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Authors: | Jun Li Michael G Parsons |
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Institution: |
a University of Michigan, Ann Arbor, Michigan, U.S.A. |
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Abstract: | Improvement in forecasting accuracy is a difficult task but critical for business success. This paper investigates the potential of neural networks for short- to long-term prediction of monthly tanker freight rates. Procedures are outlined for the development of the neural networks. The problem of under-training and over-training is addressed by controlling the number of iterations during the training process of neural networks. A comparative study of predictive performance between neural networks and ARMA time series models is conducted. Our evience shows that neural networks can significantly outperform time series models, especially for longer-term forecasting. |
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