Given that prediction markets currently don’t really have enough liquidity, saying ‘you need 1000x more liquidity to try to entice traders into putting work into something that can only pay off 0.1% of the time’ does in fact sound like something of a flaw.
Thanks, I should add this point to the post: providing 1000x more 0.1% of the time should cost a little bit more than 1x, there would obviously be companies providing this service, it’s straightforward and uncorrelated insurance.
You can anti-correlate it by running 1000 markets on different questions you’re interested in, and announcing that all but a randomly chosen one will N/A, so as to not need to feed an insurer. This also means traders on any of your markets can get a free loan to trade on the others.
(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.)
Given that prediction markets currently don’t really have enough liquidity, saying ‘you need 1000x more liquidity to try to entice traders into putting work into something that can only pay off 0.1% of the time’ does in fact sound like something of a flaw.
Thanks, I should add this point to the post: providing 1000x more 0.1% of the time should cost a little bit more than 1x, there would obviously be companies providing this service, it’s straightforward and uncorrelated insurance.
You can anti-correlate it by running 1000 markets on different questions you’re interested in, and announcing that all but a randomly chosen one will N/A, so as to not need to feed an insurer. This also means traders on any of your markets can get a free loan to trade on the others.
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.)