Rajiv Sethi writes about some weird things in election prediction markets, such as Donald Trump being given a one-in-eight chance of being the election winner . . . weeks after he’d lost the election.
Sethi writes:
There’s a position size limit of $850 dollars per contract in this market, which also happens to have hit a limit on the total number of participants. But dozens of other contracts are available that reference essentially the same outcome, and offer about the same prices. . . .
What prediction markets are revealing to us today is the extent of the chasm in beliefs held by Americans. . . . People actively seek information that largely confirms their existing beliefs, and social media platforms accommodate and intensify this demand. Prediction markets play an interesting and usual role in this environment. They encourage people with opposing worldviews to interact with each other in anonymous, credible, and non-violent ways. In a sense, they are the opposite of echo chambers. A market with homogeneous beliefs would have no trading volume, or would attract those with different opinions who are drawn by what they perceive to be mispriced contracts.
While most online platforms facilitate and deepen ideological segregation, prediction markets do exactly the opposite. They provide monetary reinforcement to those who get it right, and force others to question their assumptions and predispositions. While best known as mechanisms for generating forecasts through the wisdom of crowds, they also bring opposing worldviews into direct and consequential contact with each other. This is a useful function in an increasingly segregated digital ecosystem.
I dunno, seems kind of optimistic to me! We discuss prediction markets in section 2.6 of this article but come to no firm conclusions.