Best Bet for Next President: Prediction Markets

Going into the Democratic convention this week, most polls of registered voters were showing the presidential race to be a statistical dead heat between Obama and McCain (although today’s Gallup Poll Daily tracking poll is beginning to reflect the typical convention “bounce” that Gallup has observed in most party conventions in recent decades). However, a more reliable indicator of what’s really going on is provided by intrade.com, which trades “all or nothing” futures contracts on a number of different contingent events, including who is likely to be elected the President of the United States. These contracts pay 100 points (where 1 point = $.10) if a specific contingent event occurs and 0 points otherwise otherwise; consequently the prices for these contracts represent discounted, risk neutral probabilities.

According to intrade.com, Obama currently has a nearly 3:2 edge over McCain (which is actually down considerably from the 2:1 advantage which Obama had a few months ago after he became the presumptive Democratic presidential nominee). An important problem with national polls such as Gallup is that these polls are designed to provide an overall snapshot at a given point in time of the nation’s political mood. However, the nation’s political mood doesn’t elect presidents; the electoral college does. While the race may appear to be close nationally, once you do the math state-by-state, you get a very different picture. This information is provided by the intrade political futures contracts, since they represent unbiased bets on the electoral college outcome. While information on overall popularity amongst registered voters is not without interest, the election obviously will come down to who actually turns up to vote, how the undecided segment is swayed, and how all this is distributed on a state-by-state basis. These important subtleties are implicitly captured by prediction markets prices but are completely lacking in the national polling data.

For more information concerning the topic of “prediction markets”, I recommend a Wall Street Journal essay entitled “Best Bet for Next President: Prediction Markets” by Wharton professor Justin Wolfers. Wolfers and Zitzewitz also published the following article in 2004 in the Journal of Economic Perspectives:

Wolfers, Justin and Eric Zitzewitz, 2004, “Prediction Markets“, Journal of Economic Perspectives, Vol. 18, No. 2 (Spring), pp. 107-126.

prediction markets update

Today’s Gallup tracking poll of registered voters shows a 1 point margin (45-44) favoring Barack Obama over John McCain. Similarly, a WSJ/NBC poll was published today showing a statistical dead heat between these two candidates. However, a more reliable indicator of what’s really going on is provided by intrade.com, which trades “all or nothing” futures contracts on a number of different contingent events, including who is likely to be elected the President of the United States. These contracts pay 100 points (where 1 point = $.10) if a specific contingent event occurs and 0 points otherwise otherwise; consequently the prices for these contracts represent discounted, risk neutral probabilities 

According to intrade.com, Obama currently has a nearly 3:2 edge over McCain (which is actually down considerably from the 2:1 advantage which Obama had a few months ago after he became the presumptive presidential nominee). An important problem with national polls such as Gallup or WSJ/NBC is that these polls are designed to provide an overall snapshot at a given point in time of the nation’s political mood. However, the nation’s political mood doesn’t elect presidents; the electoral college does. While the race may appear to be close nationally, once you do the math state-by-state, you get a very different picture. This information is provided by the intrade political futures contracts, since they represent unbiased bets on the electoral college outcome. While information on overall popularity amongst registered voters is not without interest, the election obviously will come down to who actually turns up to vote, how the undecided segment is swayed, and how all this is is distributed on a state-by-state basis. These important subtleties are implicitly captured by prediction markets prices but are completely lacking in the national polling data.

On the "science" behind the International Gymnastics Federation’s tie-breaking rules

I was interested to learn today that in spite of the fact that the American gymnast Nastia Liukin and the Chinese gymnast He Kexin both posted scores of 16.725 for their uneven bars performances in the Beijing Olympics, He was awarded the gold medal whereas Liukin received the silver medal. Apparently ties were allowed in Olympic gymnastics until 2000; in such cases, both athletes would be awarded the same medal type. However, since 2000, the International Olympic Committee (IOC) has adopted so-called “tiebreaker” rules conceived of by the International Gymnastics Federation (FIG) which effectively penalize the athlete who receives the least consistent, or most highly variable set of scores across 6 judges.

The technical details concerning the actual algorithm used by FIG are provided here. For starters, the highest and lowest scores provided by 6 judges are tossed out so the “execution” score is based upon the average of the remaining four scores. Effectively, the data are “winsorized”, presumably for the purpose of discounting the effects of overly generous and overly miserly judges. Once this calculation has been made, then the first tie-break calculation requires throwing out the highest and lowest deductions from a perfect”execution score of 10 and then averaging the remaining four deductions. If there is a tie after the first tie-break (as there was in this case), then the rules call for a second tie-break in which the highest remaining deduction is thrown out, leaving a total of 3 of the original 6 deductions to averaged. When this calculation was performed, He had an average deduction of .933 versus Liukin’s .966. Liukin lost primarily because after the second pass, she had a higher average deduction among the remaining three judges. He won because her average deduction from 10 by the 3 remaining judges was lower than it was for Liukin.