Very cool work! A couple of (perhaps-silly) questions:
Do these results have any practical implications for prediction markets?
Which of your results rely on there being a fixed pool of experts who have to forecast a question (as opposed to experts being free to pick and choose which questions they forecast)?
Do you know if your arbitrage-free contract function permits types of collusion that don’t leave all experts better off under every outcome, but do make each of them better off in expectation according to their own credences? (I.e. types of collusion that they would agree to in advance.) Apart from just making side bets.
I didn’t work directly on prediction markets. The one place that my thesis touches on prediction markets (outside of general background) is in Chapter 5, page 106, where I give an interpretation of QA pooling in terms of a particular kind of prediction market called a cost function market. This is a type of prediction market where participants trade with a centralized market maker, rather than having an order book. QA pooling might have implications in terms of the right way to structure these markets if you want to allow multiple experts to place trades at the same time, without having the market update in between. (Maybe this is useful in blockchain contexts if market prices can only update every time a new block is created? I’m just spitballing; I don’t really understand how blockchains work.)
I think that for most contexts, this question doesn’t quite make sense, because there’s only one question being forecast. The one exception is where I talk about learning weights for experts over the course of multiple questions (in Chapter 5 and especially 6). Since I talk about competing with the best weighted combination of experts in hindsight, the problem doesn’t immediately make sense if some experts don’t answer some questions. However, if you specify a “default thing to do” if some expert doesn’t participate (e.g. take all the other experts’ weights and renormalize them to add to 1), then you can get the question to make sense again. I didn’t explore this, but my guess is that there are some nice generalizations in this direction.
I don’t! This is Question 4.5.2, on page 94 :) Unfortunately, I would conjecture (70%) that no such contract function exists.
Very cool work! A couple of (perhaps-silly) questions:
Do these results have any practical implications for prediction markets?
Which of your results rely on there being a fixed pool of experts who have to forecast a question (as opposed to experts being free to pick and choose which questions they forecast)?
Do you know if your arbitrage-free contract function permits types of collusion that don’t leave all experts better off under every outcome, but do make each of them better off in expectation according to their own credences? (I.e. types of collusion that they would agree to in advance.) Apart from just making side bets.
Great questions!
I didn’t work directly on prediction markets. The one place that my thesis touches on prediction markets (outside of general background) is in Chapter 5, page 106, where I give an interpretation of QA pooling in terms of a particular kind of prediction market called a cost function market. This is a type of prediction market where participants trade with a centralized market maker, rather than having an order book. QA pooling might have implications in terms of the right way to structure these markets if you want to allow multiple experts to place trades at the same time, without having the market update in between. (Maybe this is useful in blockchain contexts if market prices can only update every time a new block is created? I’m just spitballing; I don’t really understand how blockchains work.)
I think that for most contexts, this question doesn’t quite make sense, because there’s only one question being forecast. The one exception is where I talk about learning weights for experts over the course of multiple questions (in Chapter 5 and especially 6). Since I talk about competing with the best weighted combination of experts in hindsight, the problem doesn’t immediately make sense if some experts don’t answer some questions. However, if you specify a “default thing to do” if some expert doesn’t participate (e.g. take all the other experts’ weights and renormalize them to add to 1), then you can get the question to make sense again. I didn’t explore this, but my guess is that there are some nice generalizations in this direction.
I don’t! This is Question 4.5.2, on page 94 :) Unfortunately, I would conjecture (70%) that no such contract function exists.