You are right that by default prediction markets do not generate money, and this can mean traders have little incentive to trade.
Sometimes this doesn’t even matter. Sports betting is very popular even though it’s usually negative sum.
Otherwise, trading could be stimulated by having someone who wants to know the answer to a question provide a subsidy to the market on that question, effectively paying traders to reveal their information. The subsidy can take the form of a bot that bets at suboptimal prices, or a cash prize for the best performing trader, or many other things.
Alternately, there could be traders who want shares of YES or NO in a market as a hedge against that outcome negatively affecting their life or business, who will buy even if the EV is negative, and other traders can make money off them.
Sometimes this doesn’t even matter. Sports betting is very popular even though it’s usually negative sum.
Yes. PredictIt used to attract a lot of “dumb money”—people who just wanted to bet on their favorite candidate (or against disfavored candidates). They also used to run weekly markets on polling averages and things like the number of times Trump would tweet that tended to attract people who just wanted to do some skill-based gambling, whether they actually had the skill or not.
PredictIt charges high transaction fees with no outside subsidies, so all of the markets were extremely negative-sum. Despite this, gamblers and [Candidate X] True Believers managed to provide ample subsidy to attract some more knowledgable traders. (Based on the comments section of some of the popular markets, there were many people who lost thousands or tens of thousands. Probably some of the biggest losers were gambling addicts who destroyed their finances in the process. A pretty big negative externality of negative-sum markets where amateur participation is allowed.)
I would argue the negative effectives of losing big on prediction markets are still better then the negative effects of losing big on sports betting markets.
On first blush, I’d respond with something like “but there’s no way that’s enough!” I think I see prediction markets as (potentially) providing a lot of useful information publicly, but needing a flow of money to compensate people for risk-aversion, the cost of research, and to overcome market friction. Of your answers:
Negative-sum betting probably doesn’t scale well, especially to more technical and less dramatic questions.
Subsidies make sense, but could they run into a tragedy-of-the-commons scenario? For instance, if a group of businesses want to forecast something, they could pool their money to subsidize a prediction market. But there would be incentive to defect by not contributing to the pool, and getting the same exact information since the prediction market is public—or even to commission a classical market research study that you keep proprietary.
Hedging seems fine.
If that reasoning is correct, prediction markets are doomed to stay small. Is that a common concern (and on which markets can wager on that? :P)
Subsidies make sense, but could they run into a tragedy-of-the-commons scenario? For instance, if a group of businesses want to forecast something, they could pool their money to subsidize a prediction market. But there would be incentive to defect by not contributing to the pool, and getting the same exact information since the prediction market is public—or even to commission a classical market research study that you keep proprietary.
I don’t think this reasoning is entirely correct. The firm’s choice depends on how much extra information-value marginal increases in liquidity have in the market. If the marginal dollar increases information value more when spent in providing liquidity to a prediction market than on internal research, then prediction markets will get funded more. Reason to think this is in general the case for many firms: Specialization and fewer transaction costs for hiring/making deals with consulting agencies.
You are right that by default prediction markets do not generate money, and this can mean traders have little incentive to trade.
Sometimes this doesn’t even matter. Sports betting is very popular even though it’s usually negative sum.
Otherwise, trading could be stimulated by having someone who wants to know the answer to a question provide a subsidy to the market on that question, effectively paying traders to reveal their information. The subsidy can take the form of a bot that bets at suboptimal prices, or a cash prize for the best performing trader, or many other things.
Alternately, there could be traders who want shares of YES or NO in a market as a hedge against that outcome negatively affecting their life or business, who will buy even if the EV is negative, and other traders can make money off them.
Yes. PredictIt used to attract a lot of “dumb money”—people who just wanted to bet on their favorite candidate (or against disfavored candidates). They also used to run weekly markets on polling averages and things like the number of times Trump would tweet that tended to attract people who just wanted to do some skill-based gambling, whether they actually had the skill or not.
PredictIt charges high transaction fees with no outside subsidies, so all of the markets were extremely negative-sum. Despite this, gamblers and [Candidate X] True Believers managed to provide ample subsidy to attract some more knowledgable traders. (Based on the comments section of some of the popular markets, there were many people who lost thousands or tens of thousands. Probably some of the biggest losers were gambling addicts who destroyed their finances in the process. A pretty big negative externality of negative-sum markets where amateur participation is allowed.)
The sports betting analogy is very apt.
I would argue the negative effectives of losing big on prediction markets are still better then the negative effects of losing big on sports betting markets.
Thanks for the excellent answer!
On first blush, I’d respond with something like “but there’s no way that’s enough!” I think I see prediction markets as (potentially) providing a lot of useful information publicly, but needing a flow of money to compensate people for risk-aversion, the cost of research, and to overcome market friction. Of your answers:
Negative-sum betting probably doesn’t scale well, especially to more technical and less dramatic questions.
Subsidies make sense, but could they run into a tragedy-of-the-commons scenario? For instance, if a group of businesses want to forecast something, they could pool their money to subsidize a prediction market. But there would be incentive to defect by not contributing to the pool, and getting the same exact information since the prediction market is public—or even to commission a classical market research study that you keep proprietary.
Hedging seems fine.
If that reasoning is correct, prediction markets are doomed to stay small. Is that a common concern (and on which markets can wager on that? :P)
I don’t think this reasoning is entirely correct. The firm’s choice depends on how much extra information-value marginal increases in liquidity have in the market. If the marginal dollar increases information value more when spent in providing liquidity to a prediction market than on internal research, then prediction markets will get funded more. Reason to think this is in general the case for many firms: Specialization and fewer transaction costs for hiring/making deals with consulting agencies.