|
|
 |
Home > MSI Degree > Course Catalogue > Course Description
SI 679: Aggregation and Prediction Markets
Covers different approaches to aggregating opinions or information from a number of sources in order to come up with a forecast. In many settings, the wealth of information on a particular subject is distributed among many entities, with no single entity having all the relevant information. Students study approaches to elicit and combine this information to come up with a forecast or estimate that reflects the combined information of all entities. The idea of aggregating information from multiple sources is an essential ingredient of many applications, including weather forecasting, predictions of election outcomes, market research on tastes, and assignment of betting odds. Prediction markets have been deployed to aggregate opinions and come up with forecasts on election outcomes, scientific advances, product delivery dates, Academy Award outcomes, and many other events. Students study theoretical and practical aspects of several aggregation tools, including opinion polls, machine-learning techniques to combine or select experts, scoring rules, and prediction markets. The course focuses on incentive-centered design techniques to elicit honest and accurate predictions.
Credits: 1.5
Term offered: Fall
Prerequisites:
SI 563 or permission of instructor (Session 2)
Home > MSI Degree > Course Catalogue > Course Description
|
|
|
|
|
|
