Prediction markets are a terrible way of aggregating probability estimates. They only enjoy the popularity they do because of a lack of competition, and because they’re cheaper to set up due to the built-in incentive to participate. They do slightly worse than simply averaging a bunch of estimates, and would be blown out of the water by even a naive histocratic algorithm (weighted average based on past predictor performance using Bayes). The performance problems of prediction markets are not just due to liquidity issues, but would inevitably crop up in any prediction market system due to bubbles, panics, hedging, manipulation, and either overly simple or dangerously complex derivatives. 90%
Hanson and his followers are irrationally attached to prediction markets because they flatter libertarian sensibilities. 60%
They do slightly worse than simply averaging a bunch of estimates, and would be blown out of the water by even a naive histocratic algorithm (weighted average based on past predictor performance using Bayes)
Fantastic. Please tell me which markets this applies to and link to the source of the algorithm that gives me all the free money.
Unfortunately you need access to a comparably-sized bunch of estimates in order to beat the market. You can’t quite back it out of a prediction market’s transaction history. And the amount of money to be made is small in any event because there’s just not enough participation in the markets.
And the amount of money to be made is small in any event because there’s just not enough participation in the markets.
Aren’t prediction markets just a special case of financial markets? (Or vice versa.) Then if your algorithm could outperform prediction markets, it could also outperform the financial ones, where there is lots of money to be made.
In prediction markets, you are betting money on your probability estimates of various things X happening. On financial markets, you are betting money on your probability estimates of the same things X, plus your estimate of the effect of X on the prices of various stocks or commodities.
The IARPA expert aggregation exercises look plausible, and have supposedly done all right predicting geopolitical events. I would not be shocked if the first to use those methods on financial markets got a bit of alpha.
There are simply too many irrational people with money, and as soon as it became popular to participate in prediction markets, the way it currently is to participate in the stock market, they will add huge amounts of noise.
The conventional reply is that noise traders improve markets by making rational prediction more profitable. This is almost certainly true for short-term noise, and my guess is that it’s false for long-term noise, i.e., if prices revert in a day, noise traders improve a market, if prices take ten years to revert, the rational money seeks shorter-term gains. Prediction markets may be expected to do better because they have a definite, known date on which the dumb money loses—you can stay solvent longer than the market stays irrational.
They do slightly worse than simply averaging a bunch of estimates, and would be blown out of the water by even a naive histocratic algorithm (weighted average based on past predictor performance using Bayes).
Congratulations. You have discovered a way to make a fortune. Mind you, while you’re making your prediction you will have made your prediction wrong. That’s the point of markets. If you can beat them you get paid to improve them.
Downvoted for agreement, but prediction markets still win because they’re possible to implement. (Will change to upvote if you explicitly deny that too.)
Irrationality Game
Prediction markets are a terrible way of aggregating probability estimates. They only enjoy the popularity they do because of a lack of competition, and because they’re cheaper to set up due to the built-in incentive to participate. They do slightly worse than simply averaging a bunch of estimates, and would be blown out of the water by even a naive histocratic algorithm (weighted average based on past predictor performance using Bayes). The performance problems of prediction markets are not just due to liquidity issues, but would inevitably crop up in any prediction market system due to bubbles, panics, hedging, manipulation, and either overly simple or dangerously complex derivatives. 90%
Hanson and his followers are irrationally attached to prediction markets because they flatter libertarian sensibilities. 60%
Fantastic. Please tell me which markets this applies to and link to the source of the algorithm that gives me all the free money.
Unfortunately you need access to a comparably-sized bunch of estimates in order to beat the market. You can’t quite back it out of a prediction market’s transaction history. And the amount of money to be made is small in any event because there’s just not enough participation in the markets.
Aren’t prediction markets just a special case of financial markets? (Or vice versa.) Then if your algorithm could outperform prediction markets, it could also outperform the financial ones, where there is lots of money to be made.
In prediction markets, you are betting money on your probability estimates of various things X happening. On financial markets, you are betting money on your probability estimates of the same things X, plus your estimate of the effect of X on the prices of various stocks or commodities.
The IARPA expert aggregation exercises look plausible, and have supposedly done all right predicting geopolitical events. I would not be shocked if the first to use those methods on financial markets got a bit of alpha.
Markets can incorporate any source or type of information that humans can understand. Which algorithm can do the same?
Down-voted for semi-agreement.
There are simply too many irrational people with money, and as soon as it became popular to participate in prediction markets, the way it currently is to participate in the stock market, they will add huge amounts of noise.
The conventional reply is that noise traders improve markets by making rational prediction more profitable. This is almost certainly true for short-term noise, and my guess is that it’s false for long-term noise, i.e., if prices revert in a day, noise traders improve a market, if prices take ten years to revert, the rational money seeks shorter-term gains. Prediction markets may be expected to do better because they have a definite, known date on which the dumb money loses—you can stay solvent longer than the market stays irrational.
A new word to me. Is this what you’re referring to?
Congratulations. You have discovered a way to make a fortune. Mind you, while you’re making your prediction you will have made your prediction wrong. That’s the point of markets. If you can beat them you get paid to improve them.
Downvoted for agreement, but prediction markets still win because they’re possible to implement. (Will change to upvote if you explicitly deny that too.)
If you think Prediction Markets are terrible, why don’t you just do better and get rich from them?