When Prediction Markets Fail

A few years ago, David Rothschild and I wrote:

Prediction markets have a strong track record and people trust them. And that actually may be the problem right now. . . . a trader can buy a contract on an outcome, such as the Democratic nominee to win the 2016 presidential election, and it will be worth $1 if the outcome occurs and $0 if the outcome does not occur. The price at which people are willing to buy and sell that contract can be interpreted as the probability of the outcome occurring, or at least the collective subjective probability implicitly assigned by the crowd of people who trade in these markets. . . .

But more recently, prediction markets have developed an odd sort of problem. There seems to be a feedback mechanism now whereby the betting-market odds reify themselves. . . .

Traders are treating market odds as correct probabilities and not updating enough based on outside information. Belief in the correctness of prediction markets causes them to be too stable. . . . pollsters and pundits were also to some extent anchoring themselves off the prediction odds. . . .

And that’s what seems to have happened in the recent Australian election. As Adrian Beaumont wrote:

The poll failure was caused in part by “herding”: polls were artificially too close to each other, afraid to give results that may have seemed like outliers.

While this was a failure for the polls, it was also a failure of the betting markets, which many people believe are more accurate than the polls. . . . the Betfair odds . . . implying that the Coalition had only an 8% chance of winning. . . . It is long past time that the “betting markets know best” wisdom was dumped. . . .

I don’t want to overstate the case here. The prediction markets are fine for what they are. But they’re a summary of what goes into them, nothing more.

P.S. Yes, if all is calibrated, if the stated probability is 8%, then the event will occur 8% of the time. You can’t demonstrate lack of calibration from one prediction. So let me flip it around: why should we assume that the prediction markets are some sort of oracle? Prediction markets are a particular information aggregation tool that can be useful, especially if you don’t take them too seriously. The same goes for any other approach to information aggregation, including those that I’ve promoted.