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dc.contributor.authorAggarwal, Taroon
dc.contributor.authorValerdi, Ricardo
dc.contributor.authorPotoski, Matthew
dc.date30-Apr-10
dc.date.accessioned2013-05-08T21:20:05Z
dc.date.available2013-05-08T21:20:05Z
dc.date.issued2010-04-30
dc.identifier.urihttp://hdl.handle.net/10945/33483
dc.descriptionProceedings Paper (for Acquisition Research Program)en_US
dc.descriptionApproved for public release; distribution unlimited.en_US
dc.description.abstractThis paper discusses the applicability of prediction markets in Defense Acquisition projects, specifically in estimating their cost and schedule. Several temporal and political factors can sometimes limit the effectiveness of traditional methods of project tracking and cost estimation, which may be overcome by using prediction markets. A prediction market provides an environment for traders to buy and sell contracts whose values are tied to uncertain future events. Efficient prediction markets have been shown to outperform available polls and other forecasting mechanisms. There are various prediction markets based on different models and algorithms. Our focus is not to analyze these models, but to identify the design principles of implementing a proven prediction market model in a defense acquisition project. Some pilot studies have been carried out that provide insight into the behavior of the market participants. We found increased involvement of participants and greater interest in the projects to be major benefits. The areas that need to be considered in the design and implementation of markets are related to the participants (like, which traders to include); the information to be collected, or the stocks; the marketplace to be used; and the incentive structure to keep the participants motivated to trade.en_US
dc.description.sponsorshipNaval Postgraduate School Acquisition Research Programen_US
dc.publisherMonterey, California. Naval Postgraduate Schoolen_US
dc.rightsThis publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. Copyright protection is not available for this work in the United States.en_US
dc.titleWhen More is Better : Design Principles for Prediction Markets in Defense Acquisition Cost Forecastingen_US
dc.contributor.departmentAcquisition Management
dc.contributor.departmentOther Research Faculty
dc.subject.authorPrediction Marketsen_US
dc.identifier.npsreportNPS-AM-10-050


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