Talk at the University of Westminster Business School
November 8th, 2007If you're new here, you may want to get Mercury's Blog by Email or subscribe to my RSS feed. Thanks for visiting!
Thanks to Lionel Page, I had the chance yesterday to present and talk to a group of academics across a number of different departments at the University of Westminster Business School. (Lionel is a Research Fellow there.)
My talk made a general introduction to prediction markets, and then I discussed my paper from the Journal of Prediction Markets. (The part covering my paper was largely the same as what I presented at the New York and London conferences.)
The start of the discussion, around prediction markets in general, was very useful and stimulating. In a discussion around measuring risk and probabilities, we talked about some interesting potentials for using prediction markets around credit risk, prompted by this summer’s events in the credit markets. While direct assessment of credit risk would likely be too complex for individuals to aggregate, other factors in risk equations might be very appropriate for prediction markets. This could very applicable for large international firms, as a market could aggregate information far more quickly than standard reporting routes.
We also talked about some of the challenges of prediction markets, particularly regarding incentives. Again, there is always a balance that needs to be struck when designing a market and incentive programme. A person should have incentives to participate, but never so much of an incentive (and so little a potential cost) that a trader could gain by sabotaging a project or incentive. (For example, they should not be able to massively short the chance that a project will be done on time, and then work against it being done on time.) This is a delicate question, and also reaches back to whom you invite to the market and what kind of questions you’re asking them.
Overall, it was a great afternoon with Lionel and his colleagues. I hope more of their students hear about prediction markets and how they can be used in a modern business.
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