Betting and prediction markets
Market design for good guesses
2017-08-12 — 2025-06-20
Wherein prediction markets are examined, and their use for estimating wicked tail risks via betting exchanges and reputation platforms is described in mechanistic, comparative terms, and links to causal‑inference arguments are provided.
A couple of notes on mechanism design and on the theory of how to predict the future through betting.
These ideas are popularly argued to be state-of-the-art for wicked tail risk estimation.
- Metaculus Monday 2/8/21 lists some emerging prediction markets.
- Metaculus AI.
LessWrong’s prediction markets wiki entry:
People who buy low and sell high are rewarded for improving the market prediction, while those who buy high and sell low are punished for degrading the market prediction. Evidence so far suggests that prediction markets are at least as accurate as other institutions predicting the same events with a similar pool of participants.
It also indexes some explanatory blog posts. I cannot find a whole lot of published academic research in this area. Curious.
Zvi, When do prediction work?:
If I bet on a nuclear war, and win, how exactly am I getting paid?
These signals are, of course, noisy — see some nice plots from David Rothschild via Andrew Gelman.
1 Examples
Metaculus is a prediction market without currency apart from reputation. I don’t have sufficient OCD for that.
Only a few of these markets offer service in Australia, for reasons that are unclear to me. Don’t bother telling me to use a VPN to access them; my bank account’s still in Australia, and that’s how they check.
2 Causal validity
Dynomight attempts to connect prediction market inference to causal inference, which is a simple and great idea I’m embarrassed not to have thought of earlier.