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Looking at the data behind prediction markets

asteriskmag.com

31–40 of 55 posts

Re: Looking at the data behind prediction markets

#31
post #6

Random aside: I distinctly remember getting on a phone call with people from the SEC (US Gov't) with the goal of understanding if I could legally start a prediction market. This was during 2020 or 2021. I recall them saying basically "no way" and that it wouldn't be legal, and would be rife with abuse. Fun times.

[deleted]

Re: Looking at the data behind prediction markets

#32
post #6

Random aside: I distinctly remember getting on a phone call with people from the SEC (US Gov't) with the goal of understanding if I could legally start a prediction market. This was during 2020 or 2021. I recall them saying basically "no way" and that it wouldn't be legal, and would be rife with abuse. Fun times.

Too bad open bribes weren't as popular back then. A lil grease goes a long way these days (͡° ͜ʖ ͡°)

Re: Looking at the data behind prediction markets

#33

It sounds like they should be called "indicator markets" rather than "prediction markets", as the data shows they largely just summarize the current knowledge, with little predictive ability.

>as the data shows they largely just summarize the current knowledge, with little predictive ability.

What counts as "little predictive ability"? Do weather forecasts count as "predictions", or are they "indicators" too? Sure, they might have a more consistent track record, but then again weather is less susceptible to human interference than whatever happens in geopolitics within the next year. Prognostications about future climate might be less reliable, do those have to be downgraded to "indicators" too? On the flip side, prediction markets have a very good track record when forecasting certain events, such as interest rate decisions. Does that mean whether it's a "prediction" or a "indicator" depends on what you're forecasting?

Re: Looking at the data behind prediction markets

#34
Good source.

The only complain I have ( not really directed at the article, but.. ) is to put all these theories and somewhat private experiments into the same room as pure gambling schemes turbocharged by "the algorithm" and political corruption.

While far from Heaven's gates, some guy trying to predict the price of corn next year is not in the same plane as those who had the "very original" idea every guy in his early 20s had at some point but never went further because he read some articles about "the law". Like it or not, the laws or the remnants of it were put in place due to the obvious degenerate attitudes and it's consequences gambling was always known for.

And no, it's not a "market", even Uber appears to have some usefulness to offset all the lying, corruption and criminality they had to do in order to become what they are. These ones don't even take you places other than gambler addiction.

End of run, sorry.

Re: Looking at the data behind prediction markets

#35
post #24
post #19

Nice article. One small comment, it's very hard to conclude anything about accuracy over time because the comparisons may not be apples to apples. For example if there used to be lots of questions about if it will rain in Boston and now there are lots of questions about if it will rain in Phoenix, it will look like predictions are getting more accurate, but the questions are just getting easier.

Author here. Agree, and I wrote in that section "Absolute accuracy is hard to compare across markets on one platform, and across platforms, because different forecasting questions have different difficulties. I addressed this by tracking similar markets on a single platform over time." Even doing this, it's not apples-to-apples. One thing is, in this article, I filter only to "interesting" markets, so that controls f…

Thanks for the reply. Yeah, I think all of your filtering and categorizing makes these analyses really nice.

Re: Looking at the data behind prediction markets

#36

It sounds like they should be called "indicator markets" rather than "prediction markets", as the data shows they largely just summarize the current knowledge, with little predictive ability.

I don't understand the distinction you are making.

Obviously they are based on current knowledge. Nobody has any actual crystal ball.

But the outcomes are with regard to future events. So the correct term is predictions.

And they don't "just summarize the current knowledge". The whole point is that they better reflect the knowledge of people who presumably know better because they are willing to put their money where their mouth is, and ignore the vast majority of nonsense. That's not summarization. That's judgment. That's the whole point.

Re: Looking at the data behind prediction markets

#37

Most people don't know, that "prediction markets" are acutally based on an idea by DARPA in 2002, after 9/11/2001.

> Most people don't know, that "prediction markets" are acutally based on an idea by DARPA in 2002, after 9/11/2001.

Did they then use a time machine to go back to the mid-90's to pass the idea to Jim Bell so he could take the fall for some of the less attractive possible outcomes?

Re: Looking at the data behind prediction markets

#39

I recently tried to launch a site for friends and family that allowed people to make confidence predictions on various outcomes so they could track their calibration over time. It was like "I'm 84% certain Kansas City will beat Buffalo." I had a lot of fun with it since I'm a nerd about this stuff, and I actually demonstrably improved my calibration. But the only sources I could find for rapid repeatable bets were sp…

Check out manifold markets, sounds like that is what you are looking for?

Re: Looking at the data behind prediction markets

#40
> Try it yourself. Pick a topic that is important to you. Try searching Polymarket for probabilities, versus asking Claude about it. I wager you’ll prefer Claude’s take, even if it is less accurate. For one thing, Claude can speak to issues that are not properly resolvable forecasting questions.

I thought this was the very thing we wanted to avoid by creating reputation or money based prediction platforms rewarding statistical accuracy. We already have plenty of pundits speculating inaccurately about vague things they don't know much about.

We don't need AI to get more of that!

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