Forecasting Baltic Panamax Index with Support Vector Machine

Abstract This paper develops a model to forecast the freight index through studying the internal mechanism and the external influence factors. The model can provide a powerful tool for the operators and investors to understand the market trend and avoid the price risk. By taking the freight index of Panamax bulk carriers as subject, firstly, in order to eliminate the impact of random incidents in dry bulk market, wavelet transform is adopted to de-noise the Baltic Panamax Index (BPI). Then, the wavelet transform and support vector machine (SVM) combined model to predict BPI is established. The inputs of the model are the values of the five prior consecutive monthly BPI, and the output is the sixth monthly BPI. The model and the forecasted results are obtained through SVM training. Finally, the numerical analysis shows that the wavelet transform and SVM combined model has higher accuracy and can be used to predict the trend of the freight rates of the Panamax bulk carriers.

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