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Prediction Markets
Fundamentals, Designs, and Applications
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Gewicht:
212 g
Format:
210x148x9 mm
Beschreibung:
Dr. Stefan Luckner works as an IT strategy consultant for a leading management consulting company.
Dr. Jan Schröder is co-founder of KENFORX, a company providing methods for collective intelligence like prediction markets.
Dr. Christian Slamka works as a consultant in strategic IT management projects in the telecom industry.
Accurate predictions are essential in many areas such as corporate decision making, weather forecasting and technology forecasting. Prediction markets help to aggregate information and gain a better understanding of the future by leveraging the wisdom of the crowds. Trading prices in prediction markets thus reflect the traders' aggregated expectations on the outcome of uncertain future events and can be used to predict the likelihood of these events. This book demonstrates that markets are accurate predictors. Results from several empirical studies reported in this work show the importance of designing such markets properly in order to derive valuable predictions. Therefore, the findings are valuable for designing future prediction markets.
Fundamentals of Prediction Markets
Key Design Elements of Prediction Markets
Applications of Prediction Markets
Prediction Markets in Service Industries
Key Design Elements of Prediction Markets
Applications of Prediction Markets
Prediction Markets in Service Industries
Accurate predictions are essential in many areas such as corporate decision making, weather forecasting and technology forecasting. Prediction markets help to aggregate information and gain a better understanding of the future by leveraging the wisdom of the crowds. Trading prices in prediction markets thus reflect the traders' aggregated expectations on the outcome of uncertain future events and can be used to predict the likelihood of these events. This book demonstrates that markets are accurate predictors. Results from several empirical studies reported in this work show the importance of designing such markets properly in order to derive valuable predictions. Therefore, the findings are valuable for designing future prediction markets.