Second-Generation Prediction Markets for Information Aggregation: A Comparison of Payoff Mechanisms

Abstract

Initial applications of prediction markets (PMs) indicate they provide good forecasting instruments in many settings, such as elections, the box office, or product sales. One particular characteristic of these “first-generation” (G1) PMs is that they link the payoff value of a stock’s share to the outcome of an event. Recently, “second-generation” (G2) PMs have introduced alternative mechanisms to determine payoff values which allow them to be used as preference markets for determining preferences for product concepts or as idea markets for generating and evaluating new product ideas. Three different G2 payoff mechanisms appear in existing literature, but they have never been compared. This study conceptually and empirically compares the forecasting accuracy of the three G2 payoff mechanisms and investigates their influence on participants’ trading behavior. We find that G2 payoff mechanisms perform almost as well as their G1 counterpart, and trading behavior is very similar in both markets (i.e., trading prices and trading volume), except during the very last trading hours of the market. These results indicate that G2 PMs are valid instruments and support their applicability shown in previous studies for developing new product ideas or evaluating new product concepts.