Looking at the data behind prediction markets
asteriskmag.com
Looking at the data behind prediction markets
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Re: Looking at the data behind prediction markets
#2All: HN has had many threads with generic arguments about how prediction markets are/aren't useless, casinos, social ills, and so on. It would be good to avoid that in this case, because OP is full of specific information and arguments. It deserves a less generic discussion.
It's fine, of course, to be for/against/etc. and have whatever view you have. Just please engage with the specific article. It will make for a less repetitive and (therefore) more interesting thread.
Re: Looking at the data behind prediction markets
#3It 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.
Re: Looking at the data behind prediction markets
#4It 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.
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Re: Looking at the data behind prediction markets
#5It 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 tend to go back to this article when I discuss these markets with people https://en.wikipedia.org/wiki/Wisdom_of_the_crowd ... in particular, these markets are designed to tease out the "surprisingly popular" answer https://en.wikipedia.org/wiki/Surprisingly_popular because they incentivize divergence from average response.
Re: Looking at the data behind prediction markets
#6Random 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.
Re: Looking at the data behind prediction markets
#7I dove into the prediction markets rabbit hole a number of years back. And I’ve personally seen witnessed scenarios where the wisdom of crowds seems to really work. What I have not really—including in this piece—read is rigorous theory of what makes it effective or not. There are hints here and in the Wisdom of Crowds book but I’ve never read a really comprehensive theory.
Re: Looking at the data behind prediction markets
#8Interesting read. Regarding the relationship between volume and accuracy, there need not be one in limit-order-book markets like Kalshi and Polymarkets. In theory, as long as quotes are accurate and adjust quickly to new information, there is no need (and no incentive) to trade since prices are efficient. This is the case in US equity markets: most price discovery occurs through quote updates, not through trades.
Studying prediction markets is one of my current research areas. In my latest paper (preprint at https://papers.ssrn.com/sol3/papers.cfm?abstract_id=6443103), we find that on Polymarkets, markets are, on average, quite accurate and unbiased. We did see a similar non-pattern between trade volume and accuracy, past a certain threshold.
Re: Looking at the data behind prediction markets
#9I 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 sports predictions. And I definitely did not want to include money or betting for all the annoying legal reasons. People had fun using it once for March Madness 2025 but traffic really dwindled after that. My conclusion was that the overall subject just wasn't inherently fun enough to do it without money involved, so I made the site dormant.
Getting better calibrated really is worthwhile, I just wish there was more of an appetite to do that without involving money.
Re: Looking at the data behind prediction markets
#10Interesting read. Regarding the relationship between volume and accuracy, there need not be one in limit-order-book markets like Kalshi and Polymarkets. In theory, as long as quotes are accurate and adjust quickly to new information, there is no need (and no incentive) to trade since prices are efficient. This is the case in US equity markets: most price discovery occurs through quote updates, not through trades. Stu…
I will definitely take a look. Anecdote but I’m familiar with one multi-year example of a small casual prediction market that seemed like a very good predictor and another one that I don’t have the data from that seemed effective as well over time. I’ve hypothesized why that might be the case but never came to firm conclusions.