Markets can be better or worse depending on eg liquidity. My guess would be that today’s markets are better. (The large difference between 83 and 91 cents failing to disappear from arbitrage is an indication that at least one of those markets weren’t so great, though I haven’t checked how current markets look on that metric.)
Either way, they were in the same ballpark as the other forecasts. Even if both were poor markets, that only strengthens the argument that they shouldn’t receive credit for “raising the sanity waterline” around the 2016 election.
Shankar’s original claim was that the 2016 election was BEFORE functional prediction markets, and that the bit of “raising the sanity waterline” in question happened between then and today.
I really don’t think PredictIt should count as a prediction market at all in this context, I recall that they had crazy rules that made it basically impossible for serious people to make serious money by correcting even blindingly obvious market errors. (Don’t know anything about PredictWise.)
Yes, at the time the limit at Predictit was $850 per user per market. When the CFTC originally issued its no-action letter to Predictit, it was on the basis that it was for research purposes.
Shankar’s original claim was that the 2016 election was BEFORE functional prediction markets, and that the bit of “raising the sanity waterline” in question happened between then and today.
But this argument relies on an alternative history, like “functional modern high-volume prediction markets would have called the election better than Nate Silver, had they existed at that time.” But that’s an (implicit) assertion without evidence. The confident calls for Clinton weren’t by bloviating pundits making obviously wrong calls, they were by professional data-driven forecasters with methodological disagreements and oversights.
If people want to argue that prediction markets have “raised the sanity waterline” by preventing disastrously bad forecasts about high stakes events, they need to point to examples of where functional modern prediction markets have directly competed with i.e. boutique models published by media outlets. Define the comparison!
Now, that said, I can put forth a different reason they’ve raised the sanity waterline in specific areas. Taking hotbutton issues, breaking them down into empirically verifiable factors, and getting a money-backed continuously updating estimate on those factors is genuinely helpful when I’m specifically interested in a relevant issue. Even if I think the estimate is wildly wrong, it’s useful to see where the consensus lies. But I’ve read extensively on them, participated in them, and have a pretty deep knowledge of their mechanics, limitations, etc.
But I also think there are some underappreciated dangers in prediction markets. Of course, we’re now seeing how they are being used for insider trading, providing a mechanism for information leaks, and are genuinely being used as something approaching an assassination market. They’re motivating harassment of journalists whose articles are being used to resolve the markets. That’s directly counterproductive to raising the sanity waterline.
They also take some real sophistication to interpret—particularly understanding how to parse the volume, individual bet sizes (whale activity), participant selection effects, and resolution criteria. They’re optimized for betting, not informing the public, and because of that, there’s a real risk that if you go to them for informational rather than gambling purposes, you’ll misinterpret the number and become confidently wrong. I don’t know what a study on the actual impact of prediction markets on public epistemics would measure, though it would be interesting. But to me, the jury is still out, and it really doesn’t make sense to say they’ve “obviously raised the sanity waterline.”
In general, there’s all kinds of insider trading apparently going on inside the Trump admin in prediction markets whose outcome is heavily determined by US gov actions.
We also have of course the case of Emanuel Fabian, who’s been receiving death threats for accurately reporting on a missile attack in ways that unfavorable to one faction of polymarket gamblers.
There’s an investigation into whether an airport thermometer used to resolve a polymarket bet waas tampered with.
Obviously none of these are literal assassination markets, which is why I said “something approaching” rather than “precisely an assassination market.” The general principle is people are taking destructive actions (tampering, indirectly leaking classified information through their betting behavior, threatening journalists) or are betting on while being directly involved in violent actions (the soldier) that are attached to prediction markets. And on a deeper level, we have to ask whether the fraud opportunities that prediction markets present are then going to become a systemic generator of fraud.
Big picture, the combination of prediction markets, crypto, and gambling becomes an unregulatable, permanent fraud coordination mechanism. It incentivizes a set of bad social roles:
People who can come up with situations that sound outlandish to one segment of the population, who like to gamble and who believe there’s another segment of the population that’s just dumb.
People who realize that they’re in a position to influence that outlandish situation into being. They’d never have done so if there wasn’t an easy opportunity to make money on it, but there is, so they do.
What these markets point toward is a future in which the world just becomes more chaotic, because for any outlandish situation you might consider and create a market for, you’ve now incentivized people to make that situation happen (or not happen), just because you asked the question and got people’s attention. They become general bounty markets. Bet on “no” enough, and you incentivize somebody to bet against you and make “yes” happen. If you can believe in an AI singularity, you ought to be able to believe in this possibility as well!
And the deeper issue here is that both the people attempting to manifest “no” and “yes” are now spending their effort not on some sort of economically productive task, but on forcing prediction market outcomes to happen.
If the influence they can bring to bear on the situation is substantial, and the outcome is important, then it incentivizes people investing huge amounts of money into these markets in order to motivate sufficient effort toward the preferred outcome. There are of course serious free rider problems here. If an outcome is extremely important to a special interest group, then they may be willing to fund prediction markets-based bounties by betting heavily on the opposite outcome from the one they want. This creates a new mechanism for plausible deniability, which is how bribes operate these days—no quid pro quo, just an implied mutual understanding of game theory.
Insider training seems to me like a different category than assassination markets. The concept of assassination markets seem to me to suggest that someone takes harmful real world actions to make a prediction happen.
A short seller releasing a dossier about fraud in a company for which he holds shorts looks to me more “assassination market” like than a soldier who has no choice about whether or not to capture Maduro because he has to follow the chain of command making an insider trade.
Markets can be better or worse depending on eg liquidity. My guess would be that today’s markets are better. (The large difference between 83 and 91 cents failing to disappear from arbitrage is an indication that at least one of those markets weren’t so great, though I haven’t checked how current markets look on that metric.)
Either way, they were in the same ballpark as the other forecasts. Even if both were poor markets, that only strengthens the argument that they shouldn’t receive credit for “raising the sanity waterline” around the 2016 election.
Shankar’s original claim was that the 2016 election was BEFORE functional prediction markets, and that the bit of “raising the sanity waterline” in question happened between then and today.
I really don’t think PredictIt should count as a prediction market at all in this context, I recall that they had crazy rules that made it basically impossible for serious people to make serious money by correcting even blindingly obvious market errors. (Don’t know anything about PredictWise.)
Yes, at the time the limit at Predictit was $850 per user per market. When the CFTC originally issued its no-action letter to Predictit, it was on the basis that it was for research purposes.
But this argument relies on an alternative history, like “functional modern high-volume prediction markets would have called the election better than Nate Silver, had they existed at that time.” But that’s an (implicit) assertion without evidence. The confident calls for Clinton weren’t by bloviating pundits making obviously wrong calls, they were by professional data-driven forecasters with methodological disagreements and oversights.
If people want to argue that prediction markets have “raised the sanity waterline” by preventing disastrously bad forecasts about high stakes events, they need to point to examples of where functional modern prediction markets have directly competed with i.e. boutique models published by media outlets. Define the comparison!
Now, that said, I can put forth a different reason they’ve raised the sanity waterline in specific areas. Taking hotbutton issues, breaking them down into empirically verifiable factors, and getting a money-backed continuously updating estimate on those factors is genuinely helpful when I’m specifically interested in a relevant issue. Even if I think the estimate is wildly wrong, it’s useful to see where the consensus lies. But I’ve read extensively on them, participated in them, and have a pretty deep knowledge of their mechanics, limitations, etc.
But I also think there are some underappreciated dangers in prediction markets. Of course, we’re now seeing how they are being used for insider trading, providing a mechanism for information leaks, and are genuinely being used as something approaching an assassination market. They’re motivating harassment of journalists whose articles are being used to resolve the markets. That’s directly counterproductive to raising the sanity waterline.
They also take some real sophistication to interpret—particularly understanding how to parse the volume, individual bet sizes (whale activity), participant selection effects, and resolution criteria. They’re optimized for betting, not informing the public, and because of that, there’s a real risk that if you go to them for informational rather than gambling purposes, you’ll misinterpret the number and become confidently wrong. I don’t know what a study on the actual impact of prediction markets on public epistemics would measure, though it would be interesting. But to me, the jury is still out, and it really doesn’t make sense to say they’ve “obviously raised the sanity waterline.”
Can you elaborate on this please?
In general, there’s all kinds of insider trading apparently going on inside the Trump admin in prediction markets whose outcome is heavily determined by US gov actions.
We also have of course the case of Emanuel Fabian, who’s been receiving death threats for accurately reporting on a missile attack in ways that unfavorable to one faction of polymarket gamblers.
There’s an investigation into whether an airport thermometer used to resolve a polymarket bet waas tampered with.
Obviously none of these are literal assassination markets, which is why I said “something approaching” rather than “precisely an assassination market.” The general principle is people are taking destructive actions (tampering, indirectly leaking classified information through their betting behavior, threatening journalists) or are betting on while being directly involved in violent actions (the soldier) that are attached to prediction markets. And on a deeper level, we have to ask whether the fraud opportunities that prediction markets present are then going to become a systemic generator of fraud.
Big picture, the combination of prediction markets, crypto, and gambling becomes an unregulatable, permanent fraud coordination mechanism. It incentivizes a set of bad social roles:
People who can come up with situations that sound outlandish to one segment of the population, who like to gamble and who believe there’s another segment of the population that’s just dumb.
People who realize that they’re in a position to influence that outlandish situation into being. They’d never have done so if there wasn’t an easy opportunity to make money on it, but there is, so they do.
What these markets point toward is a future in which the world just becomes more chaotic, because for any outlandish situation you might consider and create a market for, you’ve now incentivized people to make that situation happen (or not happen), just because you asked the question and got people’s attention. They become general bounty markets. Bet on “no” enough, and you incentivize somebody to bet against you and make “yes” happen. If you can believe in an AI singularity, you ought to be able to believe in this possibility as well!
And the deeper issue here is that both the people attempting to manifest “no” and “yes” are now spending their effort not on some sort of economically productive task, but on forcing prediction market outcomes to happen.
If the influence they can bring to bear on the situation is substantial, and the outcome is important, then it incentivizes people investing huge amounts of money into these markets in order to motivate sufficient effort toward the preferred outcome. There are of course serious free rider problems here. If an outcome is extremely important to a special interest group, then they may be willing to fund prediction markets-based bounties by betting heavily on the opposite outcome from the one they want. This creates a new mechanism for plausible deniability, which is how bribes operate these days—no quid pro quo, just an implied mutual understanding of game theory.
Insider training seems to me like a different category than assassination markets. The concept of assassination markets seem to me to suggest that someone takes harmful real world actions to make a prediction happen.
A short seller releasing a dossier about fraud in a company for which he holds shorts looks to me more “assassination market” like than a soldier who has no choice about whether or not to capture Maduro because he has to follow the chain of command making an insider trade.