Analyzing Mechanism of Prediction Market

Abstract

The concept of the ``wisdom of crowds'' has attracted attention for finding new insights by appropriately processing the large amount of information possessed by crowds. A prediction market is one estimating method that uses the mechanisms of financial markets such as stock or exchange markets to realize the ``wisdom of crowds''. In this study, we use agent-based simulation to clarify the condition that makes prediction markets effective. An artificial market is a virtual financial market run on a computer. Agents participate in them as computer programs that play the role of virtual dealers. In the simulation, we confirm the influence of the following parameters: information transmission frequency, the retention of motivation, and the gap of information recieve abilities. The results of this study suggest that prediction markets realize more accurate results than opinion polls under the following conditions: the gap of information recieve abilities and relatively low motivation.