Forecasts are often evaluated by either quantitative precision or qualitative reliability. However, consumers purchase forecasts for the potential utility gains from utilizing the forecasts, not for their accuracy. This is analogous to household production theory where goods are purchased for their derivative consumption services. Using Monte Carlo techniques to incorporate the temporal heteroscedasticity inherent in asset returns, the expected utility of qualitative forecasts are simulated. The associated monetary values for directional forecasts of various reliability levels are then derived. The method goes beyond normal forecast evaluation and allows forecast consumers to price the information value of a set of forecasts given their own utility function and trading system.