It's not clear to me that prediction markets usually have natural hedging participants (maybe political operatives, but the tx costs are probably too high relative to the value at stake).
Prediction markets have been a thing for at least 25 years. I get the intellectual appeal, and they may be useful in certain niches. But I think their lack of significant uptake or impact is telling.
I remember back in 2012 InTrade had a market for the US Presidential election, the odds were wrong, stayed wrong for months, and actually got more wrong close to the event. You could get hourly liquidity in the tens of thousands almost throughout (I put on $20k in this market, I wasn't touching the sides, it was incredible).
Most of the people who talk a lot about prediction markets haven't worked in markets. Markets aren't magic. They work better with binary outcomes but they cannot be smarter than the people making bets in that market...and they aren't (I have most experience with financial markets, which just don't work well at all, but have quite a bit of experience with binary markets too...they have only become more accurate as our knowledge about the underlying events increased...if you look at binary markets where knowledge is limited in some way, markets are not efficient).
+1. This is why I'm more interested these days in prediction markets within (large) institutions, like tech companies, universities, or government agencies.
That way, the participants have (a) a shared domain of interest, and (b) can speculate about internal, nonpublic matters.
Perhaps most importantly, if the prediction market improves the wisdom of the institution, the participants benefit - even if they aren't profitable in the market itself.
They went into quite a bit of detail but can’t cover everything. Most of the examples were quite top of funnel, fire the CEO markets, economic impacts of new laws being passed. I wouldn’t expect for major bills or companies there would be any shortage of liquidity there.
It’s typical of comments in any forum to mostly be critical, but what takes more guts and cleverness is to connect the dots to improve upon the idea. You seem to have a good mind so I’d encourage you to try applying it in that way.
Going from academic ideas of markets and experiments to actual deep and useful markets is surprisingly difficult.
EDIT: the failure to create proper working markets for GDP-linked derivatives is good example of something that should but actually ain't. Not enough market making risk takers, limited hedges, unbalanced demand between long and short demand, index issues, ...
I agree it would be challenging to have deep and useful markets, but perhaps there’s more innovation to be made there — and many of these high level markets that are top of public consciousness I’d expect to have plenty of liquidity.
Markets need participants, capital, liquidity, effort, etc. to become efficient. A lot prediction markets suffer from the fact that volatility in them is limited and that the outcome is not of interest to many people, so the markets cannot really do what markets are supposed to do.
If markets are aggregating crummy data and information, no useful market will form. And that is observable even in much more developed financial markets, where some things really have trouble on price formation. And then you might use auction methods, for example.
Similarly, if stuff happens rarely and you only get very limited shots at being right, then averaging and aggregation or not so useful because you cannot get an average (e.g., can do one thing for the next five years and better be right, for example).