forecasting.substack.com
In short…
- Forecasting platforms and prediction markets are partially making the pie bigger together, and partially undercutting each other.
- The forecasting ecosystem adjusted after the loss of plentiful FTX money.
- Dustin Moskovitz’s foundation (Open Philanthropy) is increasing their presence in the forecasting space, but my sense is that chasing its funding can sometimes be a bad move.
- As AI systems improve, they become more relevant for judgmental forecasting practice.
- Betting with real money is still frowned upon by the US powers that be–but the US isn’t willing to institute the oversight regime that would keep people from making bets over the internet in practice.
- Forecasting hasn’t taken over the world yet, but I’m hoping that as people try out different iterations, someone will find a formula to produce lots of value in a way that scales.
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Notes -
Good writeup I read your article.
The biggest gap I see in prediction markets is a lack of actual large stakes betting without a house spread. It is either play money, or amounts too small to matter, or it is rigged against you by spreads in Vegas.
I would say the biggest betting markets you've missed are the actual financial, governmental and business markets. That is where the rubber hits the road and huge fortunes are gambled on directional bets. If every country that can is investing in nukes then nukes are probably important on the world stage; if every company that can invest in AI is doing so, the AI is probably key to business going forward.
There is another problem with forecasting that I'm sure people have written doctorial dissertations on. If it gets really good and really common then how would one extract any value from it? It would lack the informational asymmetry that might bring you value today if you had the only good predictive model for something important.
The final issue is that if it is common and good then it will alter the very things it is trying to predict. Does predicting it make it true when we trust predictions at a 99.9% confidence ratio? Is there then a rebound effect where they become worthless and you need a meta meta meta meta meta prediction market to determine the accuracy of the prediction market you're trusting to verify the accuracy of prediction market that you're using to make the initial prediction?
Postscriptum for my deterministic peeps out there-
Eventually everyone will have to accept total hard determinism, because after all, what are scientific physical laws but predictions that are right 100% of the time. But until then, there are hurdles to jump over in finding value in this space.
Thanks for the comment. Some points:
To quantify this, there are some markets in which you can bet >100k, particularly around US elections. Kalshi is also trying to change this in the US. But yeah.
Different niche, though. One important difference is that in normal markets "the market can stay irrational longer than you can stay solvent". Not so in prediction markets/forecasting questions: there is a definite date.
Not all goods are rival, not all games are zero sum. E.g., people can and do get value from weather forecasting.
Sure. You do have fixed point problems. You can also make predictions conditional on a level of investment. It's still a consideration, though.
You can make large stakes bets, but as I said they are handicapped to the point where your odds are less than 50% of winning because of spreads.
Is the market irrational? Or are you?
Fair point there are a lot of positives to be had from certain predictive algorithms.
I don't know what this last one means.
The last one is: I agree that sometimes predictions influence what happens. A few cases people have studied is alarmist Ebola predictions making Ebola spread less because people invested more early on, and optimistic predictions about Hillary Clinton leading to lower turnout.
You can solve these problems in various ways. For the Ebola one, instead of giving one probability, you could give a probability for every "level of effort" to prevent it early on. For the Hillary Clinton one, you could find the fixed point, the probability which takes into account that it lowers turnout a little bit (https://en.wikipedia.org/wiki/Fixed_point_(mathematics)).
Unfortunately, the level of effort option can still lead people to think it'll be fine if they just take the measures, then not get concerned and don't take the measures.
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