A survey of new market types that would allow people to trade on more kinds of information!
True Numeric Markets
https://manifold.markets/Austin/will-manifold-change-numeric-market
Today’s numeric markets are implemented where users can input their guess about the most likely result as a normal distribution around curve. Under the hood, we turn the range between MIN and MAX to 100 buckets using our Dynamic Parimutuel system.
Dynamic Parimutuel has the drawback here of not having a locked in payout. Instead, we can use the YES/NO market type
Use cases:
- “How many <X> will there be on <Y date>”? E.g. “How many Covid cases by the end of the year?”
- This is super general! I think many YES/NO markets today would be better framed using a point estimate of what a particular value ought to look like.
- “How many days from market creation until <X happens>? E.g. “How many days until a new #1 Billboard song is crowned?”
Drawbacks:
- With only ability to bet on MIN or MAX, you can’t put in arbitrary distributions. This means that you can’t earn as much on an outcome happening as you might, even if you have really precise information.
- Imagine we’re betting “On what day this year will Alex visit his 10th state [1-365]”, with the market predicting 100, but I’m very certain it should be 150. I can bet up the value to 150 and make guaranteed money, but it’s not the most efficient use of capital because I’ve also invested in a payout for when Alex hits that state on day 160 or 365.
Multi-category CPMM
Today’s markets are all binary, pricing two assets proportional to each other. However, the constant product market maker should work to n=3 or even more assets. For example, you could imagine 4 outcomes for “which multiple choice answer is correct?”, with a formula keeping
A * B * C * D = k
To buy up shares of B, you would take M$1, create 1 share each of A/B/C/D, and put A/C/D rest into the pool to withdrawal some additional share of B.
Use cases:
- Exclusive situations: “Who will win the Democratic primary?”