This paper investigates the accuracy of judgmental forecasting methods
for dry bulk freight market. Judgmental forecasting is a method that imple-
ments the purely judgmental aspects of a system. The research investigates
judgmental forecasting for the Baltic Dry Index, and compares it with statis-
tical 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.