Forecasting Shanghai Containerized Freight Index by Using Time Series Models

Recently, the container shipping industry has become unpredictable due to volatility and major events affecting maritime sector. At same time, approaches estimating freight rates using econometric time series modelling have very important. Therefore, in this paper, different time-series models been explored that are related Shanghai Containerized Freight Index (SCFI). SMA, EWMA, and, SES, Holt Winter method used describe data model. Afterward, SARIMA was applied model predict SCFI index. MAPE, RMSE, AIC, BIC measure performances of predictions. We observe provides comparatively better results than existing rate forecasting while performing short-term forecasts on a monthly rate. Results demonstrate increase will continue without losing momentum.