Time series of prediction market prices for the Obama and McCain contracts

The idea of relying upon futures markets prices to forecast future events has an interesting history. Nearly 25 years ago, UCLA finance professor Richard Roll published a paper in the American Economic Review entitled “Orange Juice and Weather” which showed, among other things, that the futures market in orange juice concentrate is a better predictor of Florida weather than the National Weather Service. Since the only way one can earn excess profits in a speculative market is to gain an informational advantage over the competition, traders are strongly motivated to try to do just that. If markets are informationally efficient, it follows that market prices represent unbiased forecasts concerning future events. Technically, this means that on average, the market’s estimate of the average value of the event in question is likely to be quite accurate.

Consequently, I believe that political “futures” markets provide reliable indications of the odds that a political party or candidate will win an election. Intrade.com maintains an actively traded market for futures contracts which pay 100 points (where 1 point = $.10) in the event that a specific political event occurs and 0 points otherwise. Essentially, prices represent “risk neutral” event probabilities. With this in mind, it is interesting to note that as of today (Wednesday, July 30, 2008), the intrade.com market implies 1.7:1 odds in favor of Obama, since the Obama contract implies a 61.3% probability of winning the presidence, whereas the McCain contract implies a 35.9% probability. The following graph provides a time series for the Obama and McCain contracts dating back to January 2007. The obvious reason for the spike in the time series for the Obama contract earlier this year is that Hillary Clinton (his principal Democratic opponent) dropped out of the race. Furthermore, since the time series is updated daily by intrade, it will show “current” prices of these contracts going forward (more accurately, closing prices from the previous day of trading). 

Leave a Reply