IMPROVING FORECASTING ACCURACY IN CORPORATE PREDICTION MARKETS – A CASE STUDY IN THE AUSTRIAN MOBILE COMMUNICATION INDUSTRY

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.We want to thank Günter Fädler from pro:kons, an Austrian provider of prediction markets, for his support and providing us with the data sets used in this paper