I’ve only watched some prediction market news from the outside, so forgive my basic question, but are prediction markets supposed to bring in money besides having new entrants bring in cash?
I’ve often seen prediction markets compared to stock markets, but the stock market is generally positive-sum because you’re investing money in profitable businesses that pay dividends. In contrast, if a prediction market begins with 1000 people with $1000 each (and no one else joins or brings in more money), can it ever have more than $1,000,000 in the market?
If the answer is “no, it doesn’t generate money”, isn’t that a big problem for prediction markets as a long-term concept? It means everyone will be fighting over a limited pie, and there will be no reason for the average person to join the prediction market (they just stand to lose their money to the experts). Is this a problem holding back prediction markets now, and are there ideas to fix it?
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.
In theory, there can be information-seekers who subsidize either the operation of the market, or the payout pool for specific questions, or provide bonuses for profitable investors/market-adjusters.
But fundamentally, there’s no “outside” source of income to participants, like there is for stock ownership (theoretically; there’s a LOT of companies who’ve never paid a dividend).
It’s not zero net value because there’s information produced, and also it’s fun. A more rational alien species that does not find risk enjoyable would have less accurate prediction markets (although without such thing as “gambling” maybe their markets are actually legal and thus more accurate.)
At manifold we haven’t really found a good way to use the information value yet. Subsidization doesn’t lead to increased activity in practice unless it makes the market among the top best trading opportunities. Pay for views has been much more effective as a “pay for information” method than subsidy. Most users are bettors rather than viewers. It’s good that we’re good at converting people, but without a long tail of lurkers we aren’t generating a lot of value from the information itself.
Cool to hear from someone at manifold about this! I agree the information and enjoyment value can make it worthwhile (and even pro-social), but if it’s zero net monetary value, that surely limits their reach. I appreciate prediction markets from a perspective of “you know all that energy going into determining stock prices? That could be put towards something more useful!”, but I worry they won’t live up to that without a constant flow of money.
That’s really interesting! Is there a theory for why this happens? Maybe traders aren’t fully rational in which markets they pursue, or small subsidies move markets to “not worth it” from “very not worth it”?
Well, you can monetize info value in various ways—sell advertisements, subscriptions to get more data, access to superforecasters, directly sell “accuracy” (pay to increase trading volume) - if it is actually valuable. Alternatively, EA would probably continue to fund manifold if they find it valuable (like for pushing back AI timelines), but i still much prefer “valuable enough for people to pay for” as an objective target to hit.
I think fun mostly causes traders to accept higher losses than they would otherwise.
I don’t think it’s surprising that people don’t bet on profitable markets unless they actually know the market exists and they know there’s alpha in it. The whole purpose of marketing is to match users with deals they find valuable. And yet, do you think you have purchased every consumer good that would improve your life?
There is a situation in which information markets could be positive sum, though I don’t know how practical it is:
I own a majority stake in company X. Someone has proposed an action A that company X take, I currently think this is worse than the status quo, but I think it’s plausible that with better information I’d change my mind. I set up an exchange of X-shares-conditional-on-A for USD-conditional-on-A and the analogous exchange conditional on not-A, subsidised by some fraction of my X shares using an automatic market maker. If, by the closing date, X-shares-conditional-on-A trade at a sufficient premium to X-shares-conditional-on-not-A, I do A.
In this situation, my actions lose money vs the counterfactual of doing A and not subsidising the market, but compared to the counterfactual of not subsidising the market and not doing A I gain money because the rest of my stock is now worth more. It’s unclear how I do compared to the most realistic counterfactual of “spend $Y researching action A more deeply and act accordingly”.
(note that conditional prediction markets also have incentive issues WRT converging to the correct prices, though I’m not sure how important these are in practice)
In a good prediction market design users would not bet USD but instead something which appreciates over time or generates income (e.g. ETH, Gold, S&P 500 ETF, Treasury Notes, or liquid and safe USD-backed positions in some DeFi protocol).
Another approach would be to use funds held in the market to invest in something profit-generating and distribute part of the income to users. This is the same model which non-algorithmic stablecoins (USDT, USDC) use.
So it’s a problem, but definitely a solvable one, even easily solvable. The major problem is that prediction markets are basically illegal in the US (and probably some other countries as well).
Also, Manifold solves it in a different way—positions are used to receive loans, so you can free your liquidity from long (timewise) markets and use it to e.g. leverage. The loans are automatically repaid when you sell your positions. It is easy for Manifold because it doesn’t use real money, but the same concept can be implemented in the “real” markets, although it would be more challenging (there will be occasional losses for the provider due to bad debt but it’s the same with any other kind of credit, it can be managed).
Isn’t this just changing the denominator without changing the zero- or negative-sum nature? If everyone shows up to your prediction market with 1 ETH instead of $1k, the total amount of ETH in the market won’t increase, just as the total amount of USD would not have increased. Maybe “buy ETH and gamble it” has a better expected return than holding USD, but why would it have a better expected return than “buy ETH”? Again, this is in contrast to a stock market, where “give a loan to invest in a long-term-profitable-but-short-term-underfunded business” is positive-sum in USD terms (as long as the business succeeds), and can remain positive sum when averaged over the whole stock market.
I must confess I don’t understand what you mean here. If 1000 people show up with $1000 each, and wager against each other on some predictions that resolve in 12 months, are you saying they can use those positions as capital to get loans and make more bets that resolve sooner? I can see how this would let the total value of the bets in the market sum to more than $1M, but once all the markets resolve, the total wealth would still be $1M, right? I guess if someone ends up with negative value and has to pay cash to pay off their loan, that brings more dollars into the market, but it doesn’t increase the total wealth of the prediction market users.
I feel like you are mixing two problems here: an ethical problem and a practical problem. UPD: on second thought, maybe you just meant the second problem, but still I think my response would be clearer by considering them separately.
The ethical problem is that it looks like prediction markets do not generate income, thus they are not useful and shouldn’t be endorsed, they don’t differ much from gambling.
While it’s true that they don’t generate income and are zero-sum games in a strictly monetary sense, they do generate positive externalities. For example, there could be a prediction market about an increase of <insert a metric here> after implementing some policy. The market will allow us to estimate the policy efficiently and make better decisions. Therefore, the market will be positive-sum because of the “better judgement” externality.
The practical problem is that the zero-sum monetary nature of prediction markets disincentives participation (especially in year+ long markets) because on average it’s more profitable to invest in something else (e.g. S&P 500). It can be solved by allowing to bet other assets, so people would bet their S&P 500 shares and on average get the same expected value, so it will be not disincentivising anymore.
Also, there are many cases where positive externalities can be beneficial for some particular entity. For example, an investment company may want to know about the risk of a war in a particular country to decide if they want to invest in the country or not. In such cases, the company can provide rewards for market participants and make it a positive-sum game for them even from the monetary perspective.
This approach is beneficial and used in practice, however, it is not always applicable and also can be combined with other approaches.
Additionally, I would like to note that there is no difference between ETH and “giving a loan to a business” from a mechanism design perspective, you could tokenize your loan (and it’s not crypto-related, you could use traditional finance as well, I am just not sure what “traditional” word fits here) and use the tokenized loan to bet at the prediction market.
Yes, the total amount will still be the same. However, your money will not be locked during the duration of the market, so you will be able to use it to do something else, be it buying a nice home or giving a loan to a real company.
Of course, not all your money will be unlocked and probably not immediately, but it doesn’t change much. Even if only 1% will be unlocked and only in certain conditions, it’s still an improvement.
Also, I encourage you to look at it from another perspective:
What problem do we have? Users don’t want to use prediction markets.
Surely, they would be more interested if they had free loans (of course they are not going to be actually free, but they can be much cheaper than ordinary uncollateralized loans).
Meta-comment: it’s very common in finance to put money through multiple stages. Instead of just buying stock, you could buy stock, then use it as collateral to get a loan, then buy a house on this loan, rent it to somebody, sell the rent contract and use the proceeds to short the original stock to get into a delta-neutral position. Risks multiply after each stage, so it should be done carefully and responsibly. Sometimes the house of cards crumbles, but it’s not a bad strategy per se.
I think we’re in agreement here. My concern is “prediction markets could be generating positive externalities for society, but if they aren’t positive-sum for the typical user, they will be underinvested in (relative to what is societally optimal), and there may be insufficient market mechanisms to fix this”. See my other comment here.
Good to know :)
I do agree that subsidies run into a tragedy-of-commons scenario. So despite subsidies are beneficial, they are not sufficient.
But do you find my solution to be satisfactory?
I thought about it a lot, I even seriously considered launching my own prediction market and wrote some code for it. I strongly believe that simply allowing the usage of other assets solves most of the practical problems, so I would be happy to hear any concerns or further clarify my point.
Or another, perhaps easier solution (I updated my original answer): just allow the market company/protocol to invest the money which are “locked” until resolution to some profit generating strategy and share the profit with users. Of course, it should be diversified, both in terms of investment portfolio and across individual markets (users get the same annual rate of return, no matter what particular thing they bet on). It has some advantages and disadvantages, but I think it’s a more clear-cut solution.
This might not be the problem you’re trying to solve, but I think if predictions markets are going to break into normal society they need to solve “why should a normie who is somewhat risk-averse, doesn’t enjoy wagering for its own sake, and doesn’t care about the information externalities, engage with prediction markets”. That question for stock markets is solved via the stock market being overall positive-sum, because loaning money to a business is fundamentally capable of generating returns.
Now let me read your answer from that perspective:
Why not just hold Treasury Notes or my other favorite asset? What does the prediction market add?
Why wouldn’t I just put my funds directly into something profit-generating?
I appreciate that less than 100% of my funds will be tied up in the prediction market, but why tie up any?
But once I have an S&P 500 share, why would I want to put it in a prediction market (again, assuming I’m a normie who is somewhat risk-averse, etc)
So if I put $1000 into a prediction market, I can get a $1000 loan (or a larger loan using my $1000 EV wager as collateral)? But why wouldn’t I just get a loan using my $1000 cash as collateral?
Overall I feel listed several mechanisms that mitigate potential downsides of prediction markets, but they still pull in a negative direction, and there’s no solid upside to a regular person who doesn’t want to wager money for wager’s sake, doesn’t think they can beat the market, and is somewhat risk averse (which I think is a huge portion of the public).
This I see as workable, but runs into a scale issue and the tragedy of the commons. Let’s make up a number and say the market needs a 1% return on average to make it worthwhile after transaction fees, time investment, risk, etc. Then $X of incentive could motivate $100X of prediction market. But I think the issue of free-riders makes it very hard to scale X so that $100X ≈ [the stock market].
Overall, in order to make prediction markets sustainably large, I feel like you’d need some way to internalize the positive information externalities generated by them. I think most prediction markets are not succeeding at that right now (judging from them not exploding in popularity), but maybe there would be better monetization options if they weren’t basically regulated out of existence.
Thanks, I think I understand your concern well now.
I am generally positive about the potential of prediction markets if we will somehow resolve the legal problems (which seems unrealistic in the short term but realistic in the medium term).
Here is my perspective on “why should a normie who is somewhat risk-averse, don’t enjoy wagering for its own sake, and doesn’t care about the information externalities, engage with prediction markets”
First, let me try to tackle the question at face value:
“A normie” can describe a large social group, but it’s too general to describe a single person. You can be a normie, but maybe you work at a Toyota dealership. Maybe you just accidentally overheard that the head of your department was talking on the phone and said that recently there were major problems with hydrogen cars which are likely to delay deployment by a few years. If there is a prediction market for hydrogen cars, you can bet and win (or at least you can think that you will win). It’s relatively common among normies to think along the lines “I bought a Toyota car and it’s amazing, I will buy Toyota stock and it will make me rich”. Of course, such thinking is usually invalid, Toyota’s quality is probably already priced in, so it’s a toss of a coin if it will overperform the broader market or not. Overall, it’s probably not a bad idea to buy Toyota stock, but some people do it not because it’s an ok idea but because they think it’s an amazing idea. I expect the same dynamics to play in prediction markets.
Even if you don’t enjoy “wagering for its own sake”, prediction markets can be more than mere wagering. Although it’s a bit similar in spirit, gamification is applicable to prediction markets, for example, Manifold is doing it pretty successfully (from my perspective as an active user, it’s quite addictive) although it hasn’t led to substantial user growth yet. Even the wagering itself can be different—you can bet “all on black” because you desperately need money and it’s your only chance, you can be drawn by the dopamine-driving experience of the slots, you can believe in your team and bet as kind of confirmation of your belief, you can make a bet to make watching the game more interesting. There are many aspects of gambling which have a wide appeal, and many of them are applicable to prediction markets.
Second, I am not sure it has to be a thing for the masses. In general, normies usually don’t have much valuable information, so why would we want them to participate? Of course, it will attract professionals who will correct mispricings and make money but ordinary people losing money is a negative externality which can even outweigh the positive ones.
I consider myself at least a semi-professional market participant. I bet on Manifold and use Metaculus a lot for a few years. I used Polymarket before but don’t do it anymore and resort to funny money ones despite they have problems (and of course can’t make me money).
Why I am not using Polymarket anymore:
As a real market should be, it’s far from trivial to make money on Polymarket. Despite that fact, I do (perhaps incorrectly) believe that my bets would be +EV. However, I don’t believe that I can be much better than random, so I don’t find it to be more profitable than investing in something else. However, if I could bet with “my favourite asset” it would become profitable for me (at least in my eyes, which is all that matters) and I would use it.
There are not enough interesting markets, mostly politics or sports. Which is mostly caused by the legal situation. Even Polymarket, a grey-area crypto-based market is very limited by that. PredictIt is even worse. Even if I am wrong here and it’s not the reason, still, there will be definitely more platforms which would experiment more if it was legal in the U.S.
The user experience is (or at least was) not great. Again, I believe it’s mostly caused by legal problems, it’s hard to raise money to improve your product if it’s not legal.
I do agree with your point, definitely “internalize the positive information externalities generated by them” is something which prediction markets should aspire to, an important (and interesting!) problem.
However, I don’t believe it’s essential for “making prediction markets sustainably large” unless we have a very different understanding of “sustainably large”. I am confident that it would be possible to achieve 1% of the global gambling market which would be billions of revenue and a lot of utility. It even seems to be a modest goal, given that it’s a serious instrument. But unfortunately, prediction markets are “basically regulated out of existence” :(
Sidenote on funny money market problems:
Metaculus’s problem is that it’s not a market at all. Perhaps it’s a correct decision but makes it boring, less competitive and less accurate (there are many caveats here, probably making Metaculus a market right now would make it less accurate, but from the highest-level perspective markets are a better mechanism).
Manifold’s problem is that serious markets draw serious people and unserious markets draw unserious people. As a result, serious markets are significantly more accurately priced which disincentivises competitive users to participate in them. That kinda defies the whole point. And also, perhaps even more importantly, users are not engaged enough (because they don’t have money at stake) so winning at Manifold is mostly information arbitrage which is tedious and unfulfilling.
Any position that could be considered safe enough to back a market is only going to appreciate in proportion to inflation, which would just make the market zero-sum after adjusting for inflation. Something like ETH or gold wouldn’t be a good solution because it’s going to be massively distorted on questions that are correlated with the performance of that asset, plus there’s always the possibility that they just go down, which would be the opposite of what you want.
Why does it have to be “safe enough”? If all market participants agree to bet using the same asset, it can bear any degree of risk.
I think I should have said that a good prediction market allows users to choose what asset will a particular “pair” use. It will cause a liquidity split which is also a problem, but it’s also manageable and, in my opinion, it would be much closer to an imaginary perfect solution than “bet only USD”.
I am not sure I understand your second sentence, but my guess is that this problem will also go away if each market “pair” uses a single (but customizable) asset. If I got it wrong, could you please clarify?
A lot of the money comes from the bad traders. If you have no bad traders, the prices are correct.
A better mechanism though is to “subsidize the market”, meaning the person who wants the information incentives the market to collect it. In particular, you can set up subsidy schemes where the average cost to the subsidizer is proportional to the number of bits of information they gained.