Download Prediction Markets by Stefan Luckner, Jan Schröder, Christian Slamka PDF

By Stefan Luckner, Jan Schröder, Christian Slamka

Exact predictions are crucial in lots of components resembling company choice making, climate forecasting and expertise forecasting. Prediction markets support to combination details and achieve a greater knowing of the longer term by way of leveraging the knowledge of the crowds. buying and selling costs in prediction markets therefore mirror the investors’ aggregated expectancies at the final result of doubtful destiny occasions and will be used to foretell the possibility of those occasions. This e-book demonstrates that markets are actual predictors. effects from numerous empirical stories pronounced during this paintings convey the significance of designing such markets adequately which will derive beneficial predictions. accordingly, the findings are beneficial for designing destiny prediction markets.

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Prediction Markets

Exact predictions are crucial in lots of parts comparable to company determination making, climate forecasting and know-how forecasting. Prediction markets aid to combination details and achieve a greater knowing of the longer term through leveraging the knowledge of the crowds. buying and selling costs in prediction markets therefore mirror the investors’ aggregated expectancies at the consequence of doubtful destiny occasions and will be used to foretell the possibility of those occasions.

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2. Trading Activity In general, the incentive scheme should influence the level of trading in a prediction market. In case of a fixed payment there is no monetary incentive to trade more than the minimum trading volume whereas a competitive incentive scheme such as the rank-order Key Design Elements of Prediction Markets 27 tournament should stimulate trading. Table 5 shows the total and mean number of trades as well as the standard deviation in the three treatments of the field experiment. 74 Table 5: Trading activity in the three treatments Perhaps somewhat surprisingly, with a total of 1,520 the number of trades is highest in case of the treatment with the fixed payment and lowest in case of the rank-order tournament with a total of 962 trades.

Nevertheless, there was no trading activity for four matches and also no significant correlation between trading prices and outcome frequencies in case of the FP treatment. A fixed payment consequently does not seem to be a well-suited incentive scheme to remunerate traders in a play-money prediction market. Still, intrinsic motivation does not explain the higher prediction accuracy of the RO treatment compared to the DV treatment since there is no obvious reason why intrinsic motivation should be different in these treatments.

Based on earlier work by Luckner and Weinhardt (2007), we discuss selected incentive schemes for play-money markets and their impact on the accuracy of prediction in the following. Three different monetary incentive schemes for play-money prediction markets are compared with regard to their impact on the accuracy of predictions. In order to do so, predictions from three groups of traders corresponding to three treatments with different incentive schemes are studied in a field experiment. Subjects of the first group received a fixed amount of money, subjects of the second group were paid according to their ordinal rank, and in the third group the subjects’ payment depended linearly on their deposit value in the prediction market.

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