Judgmental Forecasting in the Dry Bulk Shipping Business: Statistical vs. Judgmental Approach

AbstractThis paper investigates the accuracy of judgmental forecasting methods for dry bulk freight market. Judgmental forecasting is a method that implements the purely judgmental aspects of a system. The research investigates judgmental forecasting for the Baltic Dry Index, and compares it with statistical extrapolation methods. Post-sample forecasting accuracy indicates the superiority of the proposed approach over the conventional statistical methods. Empirical studies are performed with an expert group and the accuracy of judgmental point estimates is compared with exponential smoothing, the X12 ARIMA, and the TRAMO/SEATS algorithms. The results of expert predictions outperformed traditional time-series methods