My simple AGI investment & insurance strategy
TL;DR:
Options traders think it’s extremely unlikely that the stock market will appreciate more than 30 or 40 percent over the next two to three years, as it did over the last year. So they will sell you the option to buy current indexes for 30 or 40% above their currently traded value for very cheap.
But slow takeoff, or expectations of one, would almost certainly cause the stock market to rise dramatically. Like many people here, I think institutional market makers are basically not pricing this in, and gravely underestimating volatility as a result, especially for large indexes like VTI which have never moved more than 50% in a single year.
To take advantage of this, instead of buying individual tech stocks, I allocate a sizable chunk of my portfolio to buying LEAPS (Long-term Equity AnticiPation Securities) on the broader stock market. If a slow takeoff does happen, and public companies capture some of the increased productivity, I’ll at least be duly compensated for it when my skills become worthless. If it doesn’t happen, this part of my portfolio will vanish, but that seems like an acceptable risk given the upside.
I started doing this in January, and so far the mark price of the basket of options I’ve bought has doubled.[1]
FAQ
The options contracts you’re talking about expire in “two to three years”. Does this strategy only make sense if you think visible slow takeoff will begin before 2027?
That’s not quite necessary. If large parts of the economy get automated “only” in 2030, near-term AGI progress could start to impress market makers enough that they “wake up” and increase the price of these securities and options in anticipation of a boom. Which is why I choose to buy now instead of closer to my expected timelines, while Nvidia is only a two trillion dollar company and my alpha on this could run out any given year.
But I think takeoff before 2027 is possible. As a layman, the simplest argument for shorter timelines I can empathize with is that GPT-3 was released in 2020, GPT-4 was released in 2023, and prediction markets expect GPT-5 to release later this year. That plus the enormous amount of capital investment in AI makes me think that there’s a possibility of large portions of software engineering getting automated soon, which would precede further speedups.
Why not buy futures instead of options, if your thesis is about the next ten years rather than the next three?
Futures involve lots of leveraged downside risk. If the timing is wrong, I could lose a lot more money with futures than I can with options. On the other hand, if I’m right and GDP starts speeding up dramatically, then the deep OTM call options will be more valuable than futures contracts.
The only benefit to futures is that I would get more than zero percent of my investment in the “sane” scenarios where Nasdaq and the S&P 500 rise gradually but not the stratospheric amounts I expect. That probably only happens if AGI isn’t here, in which case I’m agnostic about the performance of these indices and don’t really have a thesis either way.
What is money going to be worth to you post-AGI anyways?
Possibly a lot.
First, I expect there to be large returns before any kind of catastrophe happens. Some of those returns could be directed toward either alignment research or high-leverage political opportunities, maybe to greater effect than the opportunities I have now.
But also, from my vantage point I think there’s a strong chance that:
RLHF (and trivial improvements on RLHF such as DPO), along with some workshopping, turns out to be broadly sufficient for AI alignment.
Existing property rights get respected by the successor species.
There is no significant wealth redistribution, and the vast majority of the lightcone will go to people with absurdly disproportionate political or economic control of the substrate that houses intelligence.
I doubt that all three of these things will be true. But in this scenario, the share of global wealth I control later, which I can use to purchase galaxies, do acausal trade, and keep myself and other unmoneyed people alive, is worth comically more to me than the share of global wealth I control now, which I can only spend on cocaine and hookers. So I’m prepared to optimize for it.
- ^
To be clear these are extremely volatile contracts, and some of their success has been fortuitous timing unrelated to AI, like the fed’s recent announcements.
A few things should be made clear.
Buying in January was almost the best case scenario, it is not a good metric to generalize from.
This is not remotely as safe an investment as buying tech stocks. It is much more all or nothing. Especially people new to this should understand they should not spend more then they are willing to have completely vanish even if they are correct in direction, and stock go up, just they don’t go up enough fast enough.
Options can be complicated, and you can losing substantially more than just the initial purchase price if you don’t know what you are doing, or even if you do but are not actively managing your portfolio. One scenario is the options are in the money and you hold through execution. In the period between the execution and when you are first able to sell at open, the stock can drop in value below the execution price.
There are SPX options that expire in 2027, 2028, and 2029, those seem more attractive to me than 2-3-y-dated VTI options, especially given that they have strike prices that are much further out of the money.
Would you mind posting the specific contracts you bought?
QQQ 640 (3y), SPY 750 (3y), VTI 340 (2y), SMH 290 (2y). Those were the latest expiration dates I could get.
Those SPX options look nice too, though I wish I could pay for a derivative that only paid out if the market jumped 100% in a single year, rather than say 15% per year throughout the rest of the 2020s.
Would you mind sharing how you allocated the ratio of these positions?
Does buying shorter-term OTM derivatives each year not work here?
why do you think they’re not pricing this in?
The market makers don’t seem to be talking about it at all, and conversations I have with e.g. commodities traders says the topic doesn’t come up at work. Nowadays they talk about AI, but in terms of its near-term effects on automation, not to figure out if it will respect their property rights or something.
Large public AI companies like NVDA, which I would expect to be priced mostly based on long-run projections of AI usage, have been consistently bid up after earnings, as if the stock market is constantly readjusting their expectations of AGI takeoff by the amount that NVDA is personally earning each quarter rather than using those earnings to inform technical timelines. I think it’s more likely that they’re saying something close to “look! Nvidia’s revenues are rising!” and “wow, Nvidia has grown pretty consistently, we should increase the premium on their call options” and not really much beyond that.
Current NASDAQ futures prices are business as usual. There are only two ways to account for these prices if they are pricing things in; either they thing slow takeoff is extraordinarily (<1%) unlikely to occur before 2030, or extremely unlikely to lead to lots of growth, or both. Either of these seem like strange conclusions to me that would require unusually strong understanding of the tech tree and policy response, but as I mentioned, they’re not even talking about it so how would they know?
“Pricing this in” would require entire nation-states worth of capital. Even if there’s one ten billion dollar hedge fund out there that is considering these issues deeply, it wouldn’t have the power to move markets to where I think they ought to be.
AGI takeoff is completely out of distribution for the Great Financial Machine Learning System, being an event which has never happened before, that would break more invariants about how economies work and grow than any black swan event since the dawn of public stock exchanges. There’s no strong reason to believe, a priori, that hedge funds are selected to account for it in the same way they are selected to correctly predict fed rate adjustments, besides basic reasons like “hedge funds are filled with high IQ people”. A similar, weaker reason explains why it was a good idea to buy put options on the market in February 2020.
Existing property rights get respected by the successor species.
What makes you believe this?
if you don’t believe this will happen not much matters in financial markets. i am unsure what your investment strategy should look like if you don’t believe this. or said another way, it’s a bit of a pascals investment. either you believe this and win or you don’t believe this and lose out regardless of positive or negative outcome.
Our situation is analogous to someone who has been diagnosed with cancer and told he has a low probability of survival, but in consolation, he has identified a nifty investment opportunity.
If you don’t believe this, the strategy could be to take on as much debt as possible, and spend the money right now.
(Obviously not a financial advice)
You said you’ve been buying calls on the general stock market. Instead, why not buy calls on 20-30 tech companies that’ll likely benefit from slow takeoff?
This is very speculative, but if Anthropic/OpenAI/Google/Meta do achieve TAI and we head towards a slow takeoff, geopoltical risk from China may be a concern. To the best of my knowledge China is a few years behind us on AI, and doesn’t have the compute capability to catch up. I doubt China will just sit back and let the US achieve such a strategic advantage, and may invade Taiwan to cut out our supply of GPUs.
I do have call options on ETFs like QQQ, which are very tech-heavy, as well as SMH, which are baskets of semiconductor companies. But buying calls on individual tech stock options incurs a larger premium, because market makers see stocks as much more volatile than indices. So they’re willing to sell you options on e.g. VTI for much less, because it’s the entire stock market and that’s never appreciated more than like 50% in a single year or something. My thesis is that market makers are making a mistake, here, and so it’s higher expected value to buy call options on indices rather than companies with an AI component.
I will add this to the FAQ because I think the article doesn’t make it clear.
Implied volatility of long-dated, far-OTM calls is similar between AI-exposed indices (e.g. SMH) and individual stocks like TSM or MSFT (though not NVDA).
The more concentrated exposure you get from AI companies or AI-exposed indices compared to VTI is likely worth it, unless you expect that short-timelines slow AI takeoff will involve significant acceleration of the broader economy (not just tech giants), which I think is not highly plausible.
Note: there was previously an awful typo here; the third bullet said “buying individual tech stocks” instead of “instead of buying individual tech stocks”. The reason I’m posting about this is because it seems higher expected value than buying and holding e.g. NVDA or call options on NVDA. I wish I had caught this typo sooner as the previous post didn’t make any sense.
Have you considered using OTM call ratio backspreads? One could put them on for a credit so they make money instead of losing it if your timing is off or if the market crashes. There is still a dip around the long strike where one could lose money, but not when volatility increases (and you close/roll before expiry) nor if the market blows past it.
(Disclaimer: I’m not a financial advisor for any of you. I don’t know your financial situation. I’m not necessarily endorsing the thesis, and this is not financial advice.)
I’m trying out this strategy on Investopedia’s simulator (https://www.investopedia.com/simulator/trade/options)
The January 15 2027 call options on QQQ look like this as of posting (current price 481.48):
So, if you were following this strategy and buying today, would you buy 485 because it has the lowest OOM strike price? Would you buy 675 because it’s the lowest strike price where the ask is lower than the theoretical Black-Sholes fair price? Would you go for 720 because it’s the cheapest available? Would you look for the out-of-money option with the largest difference between Black-Sholes and the ask?
What would be your thought process? I’m definitely hoping to hear from @lc but am interested in hearing from anybody who found this line of reasoning worth investigating and has opinions about it.
So, how can we improve this further?
Some things I’m going to look into, please tell me if it’s a waste of time:
Seeing if there are any REITs that specialize in server farms or chip fabs and have long-term options
Apparently McKinsey has a report about what white-collar jobs are most amenable to automation. Tracking down this report (they have lots) if it’s not paywalled or at least learning enough about it to get the gist of which (non-AI) companies would save the most money by “intelligent automation”.
From first principles I’d expect companies/industries which have a large proportion of their operating expenses going to salaries and benefits as the first in line to automate.
Industries that are essentially aggregators and resellers of labor would have to do this to survive at all
...and the ones among them that lag in AI adoption would be candidates for short positions
A risk I see is China blockading Taiwan and/or limiting trade with the US and thus slowing AI development until a new equilibrium is reached through onshoring (and maybe recycling or novel sources of materials or something?)
On the other hand maybe even the current LLMs already have the potential to eliminate millions of jobs and it’s just going to take companies a while to do the planning and integration work necessarily to actually do it.
So one question is, will the resulting increase in revenue offset the revenue losses from a proxy war with China?
What gives you confidence that much value will accrue to the equity of the companies in those indices?
It seems like, in the past, technological revolutions mostly increase churn and are anti-incumbent in some way e.g. (this may be false in particular, but just to illustrate my argument with a concrete-sounding example) ORCL has over 150k employees whose jobs might get nuked if AGI can painlessly and securely transfer its clients to OSS instead of expensive enterprise solutions.
If I try to think about what’s the most incumbent-friendly environment, almost by definition it ought to be one where not much is changing, but you’re trying to capture value in the opposite scenario.
VTI is basically the entire US market, and companies are added to the index as they go public. You will gain unless the value goes to private companies, but then you couldn’t invest in them anyway. There are other indices for international equities.
Right—successful private companies (like nearly all the hot AI labs) are staying private for far longer (indefinitely?) so this bet will not capture any of the value they create for themselves.
It might also be that AGI is broadly deflationary, in that it will mostly melt moats and, with them, corporate margins (in most cases, except maybe the ones of the first company to roll out AGI).
Daniel Gross’ [AGI Trades](https://dcgross.com/agitrades) (in particular the first question under “Markets”) comes to mind.
It just seems far from certain to me that this bet will benefit from the outcome it’s trying to hedge / capture, and given the possible implications here, I’d just urge whoever is considering putting this kind of bet on to get comfortable with that linkage (between real-world outcome and financial outcome) and not just take it for granted.
Maybe the key is not to assume the entire economy will win, but make some attempt to distinguish winners from losers and then find ETFs and other instruments that approximate these sectors.
So, some wild guesses...
AI labs and their big-tech partners: winners
Cloud hosting: winners
Commercial real estate specializing in server farms: winners
Whoever comes up with tractable ways to power all these server farms: winners
AI-enabling hardware companies: winners until the Chinese blockade Taiwan and impose an embargo on raw materials… after that… maybe losers except the ones that have already started diversifying their supply-chains?
Companies which inherently depend on aggregating and reselling labor: tricky, because if they do nothing, they’re toast, but some of them can turn themselves into resellers of AI… e.g. a temp agency rolling out AI services as a cheaper product line
Professional services: same as above but less exposed
Businesses that are needed only in proportion to other businesses having human employees: travel, office real estate, office furniture and supplies: losers
As the effects ripple out and more and more workers are displaced...
Low to mid-end luxury goods and eventually anything that depends on mass discretionary spending: losers
Though what I really would like to do is create some sort of rough model of an individual non-AI company with the following parameters:
Recurring costs attributable to employees
Other recurring costs
Revenue
Fraction of employees whose jobs can be automated at the current state of the art
Variables representing of how far along this company is in planning or implementing AI-driven consolidation and how quickly it is capable of cutting over to AI
Fixed costs of cut-over to AI
Variable costs of cut-over to AI (depending on aggregate workload being automated)
Whatever other variables people who unlike me actually know something about fundamental analysis would put in such a model.
...and then be able to make a principled guess about where on the AI-winners vs AI-losers spectrum a given company is. I even started sketching out a model like this until I realized that someone with relevant expertise must have already written a general-purpose model of this sort and I should find it and adapt it to the AI-automation scenario instead of making up my own.
The private hot AI labs are often partially owned by publicly traded companies. So, you still capture some of the value.
The LessWrong Review runs every year to select the posts that have most stood the test of time. This post is not yet eligible for review, but will be at the end of 2025. The top fifty or so posts are featured prominently on the site throughout the year.
Hopefully, the review is better than karma at judging enduring value. If we have accurate prediction markets on the review results, maybe we can have better incentives on LessWrong today. Will this post make the top fifty?
I also started doing something similar. I’ve thought about rolling over every 6 months in case a black swan flash crashes the value of the options at the time of exercising/selling. Any thoughts on this?
If bid-ask spreads are large, consider doing so less often + holding calls that expire at different times so that every time you roll you’re only rolling half of your calls.