Prediction markets

While the Hollywood markets have drawn many participants simply on the basis of their entertainment value, the HP and Siemens experiences suggested that motivating employees to trade was a major challenge. In each case, the firms ran real money exchanges, with only a relatively small trading population, and subsidised participation in the market, by either endowing traders with a portfolio, or matching initial deposits.

The predictive performance of even these very thin markets was quite striking. Yet as the Google example discussed in the opening paragraph of this article suggests, internal market with hundreds of traders are likely to have even greater forecasting power.

In another recent prediction market, traders in “Economic Derivatives” predict the likelihood that economic data released later in the week will take on specific values. The traditional approach to aggregating forecasts is to simply take an average or a “consensus estimate” from a survey of 30 or so professional forecasters.

Comparing average market and consensus forecasts for four variables (non-farm payrolls, retail trade, unemployment claims and business confidence), shows that the market-based predictions of these economic indicators are not only extremely close to the corresponding “consensus” forecast, but also typically closer to the actual outcome, outperforming the experts on average.

Market design

The success of prediction markets, like any market, can depend on their design and implementation. For a prediction market to work well, contracts must be clear, easily understood, and easily adjudicated. This requirement for clarity can sometimes turn out to be complex. For example, in the course of Siemens’ internal prediction market on whether a software project would be delivered to the client on schedule, the client changed the deadline.

One intriguing question is how much difference it makes whether prediction markets are run with real money or with some form of play money. Legal restrictions on gambling have led some groups like NewsFutures.com to adopt play money exchanges, with those who amass the largest play-fortunes eligible for prizes.

One suggestive experiment compared the predictive power of the prices from a real-money and play-money exchanges over the 2003 NFL football season, finding that both yielded predictions that were approximately equally accurate. Interestingly, both sets of prices also outperformed all but a dozen of 3,000 people in an online contest, and also easily outperformed the average assessments of these “experts”.

On “play money” exchanges, such as Foresight Exchange, one often sees quite loosely worded “contracts” such as that a “scientific study will conclude that astrology is a statistically significant predictive method to describe an individual’s personality traits”.

Some prediction markets will work better when they concern events that are widely discussed, since trading on such events will have higher entertainment value and there will be more information on whose interpretation traders can disagree.

Ambiguous public information may be better in motivating trade than private information, especially if the private information is concentrated, since a cadre of highly informed traders can easily drive out the partly informed, repressing trade to the point that the market barely exists. Indeed, attempts to set up markets on topics where there are insiders with substantial information advantages have typically failed.

For instance, the Centrebet market on who will lead the Liberal Party to the 2007 federal election has generated very little trade despite the inherent interest in these questions.

Legal constraints

In the United States, the legal environment has forced onshore prediction markets to make compromises that have limited their attractiveness. The Iowa Electronic Markets agreed to limit positions to $500 in order to receive a “no action” letter from the Commodity Futures Trading Commission. This compromise limits the scope and depth of their markets, and possibly their efficiency.