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Updated 3:00 PM August 7, 2008
 

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  Research
Bluffing could be common in prediction markets, study shows


A new mathematical model by researchers suggests that bluffing in prediction markets is a profitable strategy more often than previously thought.

The analysis calls into question the incentives such markets create for revealing information and making accurate predictions. The researchers also pose a tactic to discourage bluffing.

A prediction market is a financial speculation market in which participants bet on the outcome of an event. In most cases, participants use fake money. But at some markets, including the Iowa Electronic Markets, it’s legal to bet a small amount of real money.

Sports betting Web sites, which are legal in other countries, could be considered prediction markets. Some companies are even using prediction markets as a management tool to allow employees to predict when a project will be completed.

Studies have indicated such markets could be more accurate than polls in predicting events. But dishonest tactics such as bluffing can cloud their accuracy.

“We’re the first to demonstrate that strategies involving deception of future traders are a real possibility under a wide range of information conditions,” says Rahul Sami, an assistant professor in the School of Information. “It could happen quite widely that bluffing is profitable.”

Sami and Stanko Dimitrov, a doctoral student in the Department of Industrial and Operations Engineering, are authors of a paper on the research that Dimitrov presented July 11 at the ACM Conference on Electronic Commerce in Chicago.

“At a certain level, you don’t care who makes money and who doesn’t. But if you’re running a prediction market, the whole point is to make predictions and you want your predictions to be reflecting the actual information the participants have,” Sami says.
“What bluffing does is worsen the predictions with the wrong information. It defeats the purpose.”

The researchers’ solution to bluffing is to penalize later trades by charging participants to make them.

The paper is called “Non-myopic strategies in prediction markets.”

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