That is the topic of my latest Bloomberg column, here is one excerpt:
A skeptic might say that demand is limited because there are already so many good and highly informative markets in other assets. In 2009, for instance, was a market necessary to predict how well the iPhone was going to do? The share price of Apple might have served to perform a broadly similar function.
The question, then, is which prediction markets might prove most useful. Nobel Laureate economist Robert J. Shiller has promoted the idea of prediction markets in GDP, but most people face major risks at a more local, less aggregated level. One of the risks I face, for example, concerns the revenue of the university where I teach. This year enrollments rose slightly even though U.S. GDP fell sharply. So a GDP-based hedge probably is not very useful to me.
How about a prediction market in local real-estate prices, so that home buyers and real-estate magnates may hedge their purchases? Maybe, but then the question is whether enough professional traders would be attracted to such markets to keep them liquid. So-called binary options, particularly when the bet is on the price of a financial asset, often have remained unfairly priced or manipulated, and are viewed poorly by regulators.
For a prediction market to take off, it probably has to satisfy a few criteria: general enough to attract widespread interest; important enough to matter; and unusual enough not to be replicable by trading in existing assets. The outcomes also need to be sufficiently well-defined that contract settlement is not in dispute.
It remains to be seen how many new assets can meet all these standards.
Recommended, and the “hook” of the piece is the new attempt to jump-start prediction markets through the start-up Kalshi.