In essence, prediction markets let people “bet” on some feature of the economy, thereby creating a new financial derivative. A prediction market in gross domestic product, or perhaps in local rates of unemployment, could be a useful means of hedging risk. If you are afraid that GDP will fall, you could “short” GDP in a prediction market and thus protect your overall economic position, because your bet would pay out if GDP came in lower than expected.
The big puzzle is why prediction markets haven’t taken off, at least not since the earlier 19th-century history of “bucket shops.” Part of the reason is regulatory constraints, but prediction markets have not succeeded in some other parts of the world without such constraints. Intrade.com, now defunct, was based in Ireland and created active and successful markets in sporting events and presidential elections. But most of their prediction markets remained fairly illiquid, due to lack of customer interest. (...)
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. (...)
For all the obstacles facing prediction markets, there is cause for optimism about their long-run viability. There are many more financial assets and contracts today than a few decades ago, and such markets can be expected to increase. The internet lowers trading and monitoring costs, and that should make prediction markets easier to create.
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. (...)
For all the obstacles facing prediction markets, there is cause for optimism about their long-run viability. There are many more financial assets and contracts today than a few decades ago, and such markets can be expected to increase. The internet lowers trading and monitoring costs, and that should make prediction markets easier to create.
by Tyler Cowen, Bloomberg | Read more:
Image: Sébastien Thibault via Nature[ed. See also: Tales from Prediction Markets (Misinformation Underload); and, The Power of Prediction Markets (Nature).]
