Microsoft Technology Licensing, LLC

Henry G Berg

Todd A Proebsting

A user participates in trading securities in a prediction market which represent different outcomes of an event, using an interface which allows the user to understand a trade in terms of a bet. The interface also allows the user to explore different bet amounts while receiving feedback on potential payoffs in real time. In one approach, a tool is used which is moved in one direction by the user to indicate a larger trade for an outcome, or in the opposite direction to indicate a larger trade against the outcome. A bet for an outcome can be translated into a purchase of a corresponding security which represents the outcome. A bet against a particular outcome can be translated into a purchase of securities which represents all other outcomes. The user interfaces hides complexities of the market from the user while surfacing relevant information.

Continuous betting interface to prediction market

Users participate in an estimate contest and a prediction market for forecasting an outcome of a future event. Data from the estimate contest and the prediction market can be combined to obtain accurate information about overall group beliefs and individual or sub-groups beliefs. In the estimate contest, users provide estimated probabilities of occurrence for different possible outcomes of the event. Trades can be proposed, or automatically executed, based on differences between the user's estimated probabilities and probabilities obtained from a prediction market in which the user can buy and sell securities which represent the different outcomes. For example, a buying opportunity may be present when the user's estimated probability exceeds the prediction market's probability. Further, the user can express a risk level which is factored into the proposed trades.

Combined estimate contest and prediction market

A user interface allows a user to freehand draw a probability density curve, or to select from predetermined probability densities, such as a normal distribution. The probability density represents the user's opinion regarding the probability of occurrence for different outcomes of a future event. The user can easily manipulate the shape of the probability density by dragging portions of the curve using an input device, such as to change the mean or standard deviation. Further, a scoring rule is applied to the probability density so that an updated score is displayed as the probability density is manipulated. The probability density can be input to an estimate contest or a prediction market, for instance. The user interface can also allow the user to freehand draw a scoring curve from which a probability density can be computed based on a scoring rule.

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Redmond, WA, United States of America

Henry G Berg