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 meth-
ods. 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.