We investigate market selection and bet pricing in a repeated prediction market model. We
derive the conditions for long-run survival of more than one agent (the crowd) and quantify …

Although the idea is an old one, there has been a recent boom in research into the Wisdom
of Crowds, and this appears to be at least partly due to the now widespread availability of …

In this article, we propose a process-based definition of big data, as opposed to the size-and
technology-based definitions. We argue that big data should be perceived as a continuous …

We examine two types of binary betting markets, whose primary goal is for profit (such as
sports gambling) or to gain information (such as prediction markets). We articulate the …

We study online learning settings in which experts act strategically to maximize their
influence on the learning algorithm's predictions by potentially misreporting their beliefs …

We study the problem of eliciting and aggregating probabilistic information from multiple
agents. In order to successfully aggregate the predictions of agents, the principal needs to …

Prediction markets are economic mechanisms for aggregating information about future
events through sequential interactions with traders. The pricing mechanisms in these …

We consider the design of prediction market mechanisms known as automated market
makers. We show that we can design these mechanisms via the mold of exponential family …

We present a new model for prediction markets, in which we use risk measures to model
agents and introduce a market maker to describe the trading process. This specific choice of …

Mixability is a property of a loss which characterizes when constant regret is possible in the
game of prediction with expert advice. We show that a key property of mixability generalizes …