What’s the best way to understand what markets think about AGI timelines? Polymarket has a couple of semi-related markets with $5k-$8k of liquidity in each:
The mean P/E ratio for the Nasdaq is ~30. That’s a pretty high ratio for Nvidia (considering it comes on top of being the world’s most valuable company). But it’s not THAT high.
Is there something else to look at? Perhaps options prices for the above stocks? Implied volatility measures? Something else?
I don’t think markets are likely to correlate very strongly to this. Whether prediction markets or stock/commodity that has a bit of correlation to what you care about, the fundemental problem is “if the economy changes by enough, the units of measure for the market (money!) change”. Which means that payoff risk overwhelms prediction risk. You can be spot-on correct about timelines, and STILL not get paid. So why participated in that prediction at al?
There are some other prediction markets on Manifold/Metaculus that address the question more directly but they’re small.
Some economists have argued that you should look at long run real interest rates—the idea being that AGI boosts the return on capital, so bondholders should demand higher rates in order to lock up their money in bonds.
I think it’s pretty hard to infer much from the stock prices of tech companies because it’s kinda ambiguous what AGI would do to those companies (and depends on what exactly counts) plus sub-AGI advances in AI can confuse the price effect. Nvidia, for example, is the market’s favorite AI play but AGI in the “dominates humans at all white collar work” sense is almost certainly bad for Nvidia because then the AGI can just design better chips than Nvidia engineers (but then factor in that Nvidia has invested in a whole web of other AI companies so maybe that pushes the other way, and so on and so on).
One thesis here is that white-collar replacement AGI is bearish for fabless semiconductor companies but bullish for the fabs—so maybe if Nvidia starts tanking while TSMC starts rising?
The valuations of the frontier labs are maybe better, but it’s hard to tell if the market is predicting AGI or just placing bets on OpenAI becoming the next Alphabet.
Another idea is that AGI is very bearish for the value of white collar human capital generally, and thus especially for the higher ed sector. In basically any scenario, AGI is the apocalypse for your average university. You can’t really trade those in equity markets, but maybe something like interest rates on university debt or credit default swaps?
Markets pricing in AGI also is also conditional on markets believing something like the current legal/property rights system will continue to hold after AGI. If it is possible that AI is a bubble, and it’s not obvious that you will win anything if you get the AGI trade right, then traders won’t “price in” AGI even if it is extremely economically valuable and coming soon.
My argument is also not that markets won’t price in AI in its current form or increasing capabilities, it is specifically at the point where we actually have strong AGI systems phase shift.
I think fraction of GDP invested into AI development should be an indicator, but in order to infer the markets timelines it needs a lot of additional hard-to-estimate parameters. Claude wasn’t able to make a satisfying estimate from this as a starting point
What’s the best way to understand what markets think about AGI timelines? Polymarket has a couple of semi-related markets with $5k-$8k of liquidity in each:
https://polymarket.com/event/openai-announces-it-has-achieved-agi-before-2027
https://polymarket.com/event/ai-data-center-moratorium-passed-before-2027
But these aren’t great, since either of those events seem like they could easily happen despite no AGI or fail to happen even with AGI.
You can look at stock prices for public companies. Here are some current P/E ratios from somewhat affiliated companies:
Nvidia: ~48
Alphabet: ~33
Meta: ~23
Apple: ~34
Microsoft: ~32
The mean P/E ratio for the Nasdaq is ~30. That’s a pretty high ratio for Nvidia (considering it comes on top of being the world’s most valuable company). But it’s not THAT high.
Is there something else to look at? Perhaps options prices for the above stocks? Implied volatility measures? Something else?
I don’t think markets are likely to correlate very strongly to this. Whether prediction markets or stock/commodity that has a bit of correlation to what you care about, the fundemental problem is “if the economy changes by enough, the units of measure for the market (money!) change”. Which means that payoff risk overwhelms prediction risk. You can be spot-on correct about timelines, and STILL not get paid. So why participated in that prediction at al?
There are some other prediction markets on Manifold/Metaculus that address the question more directly but they’re small.
Some economists have argued that you should look at long run real interest rates—the idea being that AGI boosts the return on capital, so bondholders should demand higher rates in order to lock up their money in bonds.
I think it’s pretty hard to infer much from the stock prices of tech companies because it’s kinda ambiguous what AGI would do to those companies (and depends on what exactly counts) plus sub-AGI advances in AI can confuse the price effect. Nvidia, for example, is the market’s favorite AI play but AGI in the “dominates humans at all white collar work” sense is almost certainly bad for Nvidia because then the AGI can just design better chips than Nvidia engineers (but then factor in that Nvidia has invested in a whole web of other AI companies so maybe that pushes the other way, and so on and so on).
One thesis here is that white-collar replacement AGI is bearish for fabless semiconductor companies but bullish for the fabs—so maybe if Nvidia starts tanking while TSMC starts rising?
The valuations of the frontier labs are maybe better, but it’s hard to tell if the market is predicting AGI or just placing bets on OpenAI becoming the next Alphabet.
Another idea is that AGI is very bearish for the value of white collar human capital generally, and thus especially for the higher ed sector. In basically any scenario, AGI is the apocalypse for your average university. You can’t really trade those in equity markets, but maybe something like interest rates on university debt or credit default swaps?
Markets pricing in AGI also is also conditional on markets believing something like the current legal/property rights system will continue to hold after AGI. If it is possible that AI is a bubble, and it’s not obvious that you will win anything if you get the AGI trade right, then traders won’t “price in” AGI even if it is extremely economically valuable and coming soon.
My argument is also not that markets won’t price in AI in its current form or increasing capabilities, it is specifically at the point where we actually have strong AGI systems phase shift.
I think fraction of GDP invested into AI development should be an indicator, but in order to infer the markets timelines it needs a lot of additional hard-to-estimate parameters. Claude wasn’t able to make a satisfying estimate from this as a starting point