Recent literature on the accuracy of forecasting in financial markets reveals contradictory results. These discrepancies can be attributed to the differences in forecasting environments as well as the differences in forecaster expertise that are employed by the researchers. Since the use of point and interval predictions by themselves do not aid in explaining the various aspects of forecaster performance, probabilistic forecasting provides a better alternative that can be used to gain insight into forecasting accuracy in such settings. This study aims to test the effects of forecaster expertise and forecasting environment on forecasting accuracy. Accordingly, various aspects of forecasting performance are studied in a developing stock-market framework.