(Also I would phrase it as being able to use the same money to trade on all 1000 of the markets at once. I think that is equivalent to your free loan.)
The post does indeed propose the idea of implementing the do() operator this way, but I don’t think it proposes the idea of various people running 1000 markets on different questions and chosing one not to N/A, so that the cost of providing liquidity or of trading doesn’t increase due to that structure?
- Gather proposals for a hundred RCTs … - Randomly pick 5% of the proposed projects, fund them as written, and pay off the investors who correctly predicted what would happen. - Take the other 95% of the proposed projects, give the investors their money back, and use the SWEET PREDICTIVE KNOWLEDGE [to take useful actions]
Other than the difference in the portion of the markets you run (1/20 vs 1/1000), this is equivalent.
(It does not discuss liquidity costs, just the the randomization as a way to avoid having to take many random actions.)
Just for the record, Dynomight proposed this back in 2022: https://dynomight.net/prediction-market-causation/#commit-to-randomization. (I assume that the idea has been around for longer.)
(Also I would phrase it as being able to use the same money to trade on all 1000 of the markets at once. I think that is equivalent to your free loan.)
The post does indeed propose the idea of implementing the do() operator this way, but I don’t think it proposes the idea of various people running 1000 markets on different questions and chosing one not to N/A, so that the cost of providing liquidity or of trading doesn’t increase due to that structure?
Here are the relevant quotes:
Other than the difference in the portion of the markets you run (1/20 vs 1/1000), this is equivalent.
(It does not discuss liquidity costs, just the the randomization as a way to avoid having to take many random actions.)