Forecasting Baltic Panamax Index with Support Vector Machine

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.

摘要考察运价指数波动的内在规律和外在影响，提出新模型预测运价指数，为航运市场经营者和投资者提供把握市场态势、规避价格风险的有力工具. 针对波罗的海巴拿马型船舶运价指数（BPI）序列，首先用小波变换对运价指数序列进行去噪，消除干散货运输市场中无规律的突发事件所造成的影响；在此基础上以前五个月的BPI值为输入变量，以第六个月的运价指数为输出变量，对支持向量机（SVM）进行训练，得到预测模型. 通过实证分析发现小波变换-SVM混合预测模型具有较高的预测精度，可用于对巴拿马船型运价走势的预测.