Getting good information from prediction markets requires good forecasts. But what makes that? From questions to subjects to the data available, we break down the ingredients.
Does there exist/are there linchpin incidents or individuals who can cause wider ramifications? Like subprime loans leading to GFC leading to Trump/Ukraine-Russia etc. Focussing forecasting on these linchpins could be efficient provided well-worked-out theory existed.
Thank you for picking up where Nuno Sempere has stopped reporting, for now, at least. I like your format and the broader coverage than what you had in Crowd Money, which I thought was really good.
One of my big concerns is that there are many relatively new ventures in the forecasting field, but no breakthroughs to economic success that I can find. Where are the unicorns, the SPACs, the IPOs? I hope you could report on at least one such clearly successful venture.
True, although some of the more interesting ventures came online in the past couple of years which is a short time-horizon for becoming a unicorn. That being said, it's hard to see any of the current crop reaching unicorn status. Tying that back to our response to Pickles, are we just seeing poor execution preventing success or is there something more fundamental at play?
Glad to see you two back in action and glad you responded to Hoel’s piece.
I still feel that prediction markets have an arm tied behind their back and until regulations in US change it’s premature to dismiss them. To his credit Hoel mentioned the legal gray zone in his (well written) piece but I thought he underplayed that factor a tad.
That's partially true, but can't dismiss that Kalshi is up and running and receiving little traffic. Again, you could argue that regulations are preventing the real interesting questions from being offered, which is true (maybe, or maybe just the gambling questions staying away). But is it really just regulations that are getting in the way of PMs or is there something more fundamental at play?
Excellent point about the short time in operation of many such platforms. I'm in the initial stage of a summarization experiment to evaluate how to use forecasts as an integral part of a scalable news summarization + associated forecasts system. The advantage would be that forecasts, if successful, would give credibility with the associations news stories created largely via summarizations of the rationales of forecasters.
Interesting angle: linchpins.
Does there exist/are there linchpin incidents or individuals who can cause wider ramifications? Like subprime loans leading to GFC leading to Trump/Ukraine-Russia etc. Focussing forecasting on these linchpins could be efficient provided well-worked-out theory existed.
> provided well-worked-out theory existed
Atlas didn't shrug. He collapsed.
Thank you for picking up where Nuno Sempere has stopped reporting, for now, at least. I like your format and the broader coverage than what you had in Crowd Money, which I thought was really good.
One of my big concerns is that there are many relatively new ventures in the forecasting field, but no breakthroughs to economic success that I can find. Where are the unicorns, the SPACs, the IPOs? I hope you could report on at least one such clearly successful venture.
True, although some of the more interesting ventures came online in the past couple of years which is a short time-horizon for becoming a unicorn. That being said, it's hard to see any of the current crop reaching unicorn status. Tying that back to our response to Pickles, are we just seeing poor execution preventing success or is there something more fundamental at play?
Glad to see you two back in action and glad you responded to Hoel’s piece.
I still feel that prediction markets have an arm tied behind their back and until regulations in US change it’s premature to dismiss them. To his credit Hoel mentioned the legal gray zone in his (well written) piece but I thought he underplayed that factor a tad.
Keep it up!
That's partially true, but can't dismiss that Kalshi is up and running and receiving little traffic. Again, you could argue that regulations are preventing the real interesting questions from being offered, which is true (maybe, or maybe just the gambling questions staying away). But is it really just regulations that are getting in the way of PMs or is there something more fundamental at play?
Kalshi operates in a straitjacket though.
Excellent point about the short time in operation of many such platforms. I'm in the initial stage of a summarization experiment to evaluate how to use forecasts as an integral part of a scalable news summarization + associated forecasts system. The advantage would be that forecasts, if successful, would give credibility with the associations news stories created largely via summarizations of the rationales of forecasters.