Notes from the San Diego Prediction Markets Conference
June 26th, 2007If you're new here, you may want to get Mercury's Blog by Email or subscribe to my RSS feed. Thanks for visiting!
It’s been two weeks since the Second Conference on Prediction Markets took place in San Diego, CA. I wanted to give my impressions of the conference and some of the more relevant papers for real-world practitioners. (My apologies for not posting this sooner, but I took a bit of a holiday after the conference and have been suffering through some significant jet lag!)
Many of the papers presented were quite theoretical in nature. I’d like to discuss two and how they apply to your prediction market issues.
“Information Aggregation Mechanisms and Environmental Complexity“:
Authors: Paul J. Healy, John O. Ledyard, Sera Linardi, and J. Richard Lowery.
This paper discussed the results of laboratory experiments. The authors looked at which mechanisms (CDA, MSR, Pari-mutuel and iterative polling) performed best at different levels of complexity. In general, CDA performed best in less complex environments while MSR and polling performed best in more complex environments.
While this is a highly academic paper, the overall theme can help guide our future prediction markets. Where an issue is largely black or white (such as who will win an event) CDA is an effective mechanism. Where there are more shades of grey (such as a theoretical combinatorial market) MSR is a more effective mechanism.
The paper is much more specific, but this is a good “takeaway” for practitioners.
“A Field Experiment on Monetary Incentives in Prediction Markets“:
Author: Stefan Luckner
Stefan Luckner did some interesting research on incentives. He ran a series of prediction markets on last summer’s football (soccer) World Cup. By separating traders into different groups with different incentive systems, he was able to start analysing how the different systems perform.
The three systems he examined were:
- Fixed Price: Each trader earned 50 Euros without consideration of performance
- Rank Order: Top three places earned 500, 300, and 200 Euros, respectively. All other traders earned nothing.
- Performance-based: Each trader’s earnings were based on their final deposit. (Starting deposit equalled 50 Euros)
His data revealed that the Rank Order incentive system was significantly more accurate than the other two systems. In the Fixed Price system, there was no incentive to perform well, while in the Performance-based system risk-averse behaviour would be rewarded through maintaining the original stake. In the Rank Order system, traders were incentivised to speculate and maximise their market earnings to climb the rankings for the final (real-money) payout.
Like Bo Cowgill, I’m a big fan of rank order incentives. They encourage speculation and competition among traders. (It’s how I know, for example, that I performed better on the Washington Stock Exchange than prediction market luminary Prof. Justin Wolfers!) Depending on an organisations culture, this can be a fantastic motivator to keep trading levels consistent on your company’s prediction market site. Stefan’s research is a good start in this area, but much more research is due.
Summary
Overall, it was a good conference, though focused largely on academic topics in the field of prediction markets. The day finished with a good Industry Panel consisting of Dave Perry (ConsensusPoint), Emile Servan-Schreiber (NewsFutures), Russell Anderson (HedgeStreet) and Matthew Fogarty (Electronic Arts). I was pleased to finally meet in person a number of people with whom I’ve only previously traded e-mails and phone calls.
Finally, a quick bullet-point list of trivia:
- A surprising number of MacBooks among attendees! I’d estimate 50% or more.
- In honor of Chris Hibbert, a number of us went to the Zocalo restaurant on Tuesday evening in Old Town San Diego. Great food, and great conversation.
- Congrats to the organisers. It was very well-run, and everything ran on time!