Self-resolving markets are markets that resolve based on the market itself, instead of the author deciding how to resolve them. In general, this isn't a very good idea, as many experiments have demonstrated: the reason markets work is because participants make profits based on whether they are correct or not, and in a self-resolving market there is nothing to actually tie the market resolution to the real-world question that was asked, so there's no reason to expect the market to have anything to do with the question.
But there are several reasons people are interested in exploring them:
1) Asking questions where determining an answer is expensive. For example, it might take a massive amount of data collection work or it might cost millions of dollars to run a randomized controlled trial.
2) Asking highly subjective questions, such as:
At the end of 2023 will manifold users think Twitter has changed for the better?
These questions are often poll-like, and indeed resolving to the result of a poll is a common way to design them.
3) Many blockchain systems use protocols for forming a consensus resolution that are similar to self-resolution, and they have similar dangers, and it's interesting to explore how to make them more robust. For example, Polymarket uses an oracle where token holders essentially vote with cryptocurrency to settle disputed resolutions, and there are a couple examples of misresolutions.
I think it's valuable to find tweaks to make such markets work better, and valuable to have experiments demonstrating how they can go wrong.
If you are an author thinking about creating a market along these lines, I think these methods work much better:
Resolving to the result of a poll. Examples: https://manifold.markets/SneakySly/at-the-end-of-2023-will-manifold-us and https://manifold.markets/jack/will-we-believe-sbf-committed-willf. While they aren't perfect, polls tend to work a lot better at getting a reasonable result and being mostly (but not 100%) robust to market manipulation.
Some random chance of resolving the normal way, otherwise resolve N/A. Imagine a market predicting the result of an expensive experimental trial. This mechanism means you only have to actually run the trial some fraction of the time, and it is incentive-compatible (you can't profit on the market by manipulating it). Example: https://manifold.markets/jack/does-gdpr-require-selfserviceautoma. Downside is that profit incentives for making good predictions are correspondingly lower.
And, if you really want to resolve-to-mkt despite the flaws:
If you are ok with some author subjectivity, you can say "Resolves to MKT but the author will override if it looks like market manipulation". This has empirically worked ok for many low-stakes markets, but you do have to acknowledge that it becomes very subjective. The line between voting your beliefs and manipulating the market can be very blurry.
Or, if you want to avoid that sort of subjective resolution mechanism, you should at least include a) a random chance of resolving the normal way based on external data, and b) protections against last-minute price manipulation such as a randomized close time or quiescence criteria. E.g. https://manifold.markets/Yev/will-biden-be-president-on-october-fb3d01633429 I do not believe this is as robust against manipulation as a simple poll, while being far more complicated, but at least it's better than a resolve-to-mkt without those features.
The problem is that the reason prediction markets work is that participants profits are based on whether they are correct or not. If the market resolution is instead based only on what the market participants say, and not based on any external data about the actual question, then it can become completely disconnected from the question it is trying to answer - it's a Keynesian beauty contest.
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