Corporate prediction markets forecast business issues like market shares, sales volumes or the success rates of new product developments. The improvement of its accuracy is a major topic in prediction market research. Mostly, such markets are using a continuous double auction market mechanism. We propose a method that aggregates the data provided by such a prediction market in a different way by only accounting for the most knowledgeable market participants. We demonstrate its predictive ability with a real world experiment.