Dry bulk freight rate modelling and forecasting
Date of Issue2009
School of Civil and Environmental Engineering
This study focuses on analysis of internal patterns and forecasting models in the short-term dry bulk time charter (T/C) rate market. The study has concentrated on several models, such as linear regression model, psychological model, time series model and so on. Linear regression model turns out to be the best approach for forecasting short-term dry bulk T/C rate. Fourteen indicators for forecasting T/C rate are identified in the linear regression model. Spot rate is the most efficient leading indicator for the short-term T/C rate, and it generated very good results in the forecasting model. In the forecasting model, time series model is divided into two time regimes and different model is built under each regime. The choice of model is found to depend on prevailing market condition.
Final Year Project (FYP)
Nanyang Technological University