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CS 269 I : Incentives in Computer Science Lecture # 18 : Prediction Markets ∗

Suppose we’re interested in an uncertain event, such as whether or not the Warriors will win the 2017 NBA Championship, whether or not the winner of the next Presidential election will be a Republican or a Democrat, or whether or not 2017 will be the hottest year on record. Each of these events is uncertain, but eventually we will know whether or not they occurred. That is, the outcomes of these uncertain events are eventually verifiable. (Similar to the setup for scoring rules in the first half of last lecture, but different from the setup for eliciting subjective opinions in the second half.) What’s the best way to predict whether or not such events will happen? For example, suppose you had to predict the winner of a sporting match, despite knowing very little about the sport. You could do a lot worse than turning to the betting markets in Vegas for help. Vegas odds don’t let you predict anything with anything close to full certainty, but even the best experts struggle to outperform betting markets with any consistency. For example, favorites cover the Vegas spread about 50% of the time, while underdogs beat the spread about 50% of the time.