How would you model the expected investment rate of return? I generally assume a 5% real return, which is small enough that it wouldn’t affect the model in OP very much. If want to incorporate a large expected return on AI investments, then I don’t know how to do that anymore.
I’m thinking of AI-thesis hedge funds like VARA and SALP, but they are difficult to get access to without being very wealthy. My understanding is @Austin is considering setting up a DAF vehicle for people to get exposure to such funds, so I would recommend talking with him.
But I think expecting returns something like 50-100% p.a. would be reasonable, based on historic performance of these funds. As one intuition pump, suppose that AI and robotics and semiconductors and associated supply chains are about 3% of total capital today, and will grow to be the vast majority of capital after an intelligence explosion, then just being exposed to those industries gives ~30x returns over the coming ~decade, and it is likely possible to do better than this with more targeted bets.
But one might think that this is all lunacy and we should rely more on base rates and the efficient market hypothesis. Seems mistaken to me, but I respect that view too.
But I think expecting returns something like 50-100% p.a. would be reasonable, based on historic performance of these funds.
You can’t have it both ways. Either you can extrapolate from historical performance, in which case you should use long-run market returns of ~5%. Or you have a specific view on what’s going to outperform, in which case it’s a question of what your expectations are. You can’t just take a fund that performed extremely well over the last 3–5 years and then say that level of performance will continue. If some thesis did really well in the past, then everyone else can also see that it did well, and you should assume it’s now priced in unless you have some marginal thesis for why it’s not priced in.
In fact, in the long run, stocks have exhibited 3–5 year reversals—that is, stocks that perform particularly well over the last 3–5 years tend to underperform the market going forward.[1] Mutual funds haven’t exhibited reversals, but funds that outperform tend to regress to average performance.[2] At minimum, your thesis needs to have some explanation of why that’s not going to happen this time.
I’m not saying you’re wrong. AI stocks may well be a good investment. But I am pretty unimpressed by most arguments I’ve seen. “The last 5 years saw 50–100% return, therefore that same level of return will continue” is not a good argument—by (weak) default, it’s evidence that future returns will be lower than the market, not higher. (I wrote more on my thoughts in a recent post, especially this section.)
[1] Fama, E. F., & French, K. R. (1988). Permanent and Temporary Components of Stock Prices. Journal of Political Economy, 96(2), 246–273. http://www.jstor.org/stable/1833108
[2] Berk, J. B., & Green, R. C. (2004). Mutual Fund Flows and Performance in Rational Markets. Journal of Political Economy, 112(6), 1269–1295. https://doi.org/10.1086/424739
Nice!
This seems like a pretty key thing to include given the huge rates of return seen thus far (and arguably likely to continue) for AI thesis investing.
How would you model the expected investment rate of return? I generally assume a 5% real return, which is small enough that it wouldn’t affect the model in OP very much. If want to incorporate a large expected return on AI investments, then I don’t know how to do that anymore.
I’m thinking of AI-thesis hedge funds like VARA and SALP, but they are difficult to get access to without being very wealthy. My understanding is @Austin is considering setting up a DAF vehicle for people to get exposure to such funds, so I would recommend talking with him.
But I think expecting returns something like 50-100% p.a. would be reasonable, based on historic performance of these funds. As one intuition pump, suppose that AI and robotics and semiconductors and associated supply chains are about 3% of total capital today, and will grow to be the vast majority of capital after an intelligence explosion, then just being exposed to those industries gives ~30x returns over the coming ~decade, and it is likely possible to do better than this with more targeted bets.
But one might think that this is all lunacy and we should rely more on base rates and the efficient market hypothesis. Seems mistaken to me, but I respect that view too.
You can’t have it both ways. Either you can extrapolate from historical performance, in which case you should use long-run market returns of ~5%. Or you have a specific view on what’s going to outperform, in which case it’s a question of what your expectations are. You can’t just take a fund that performed extremely well over the last 3–5 years and then say that level of performance will continue. If some thesis did really well in the past, then everyone else can also see that it did well, and you should assume it’s now priced in unless you have some marginal thesis for why it’s not priced in.
In fact, in the long run, stocks have exhibited 3–5 year reversals—that is, stocks that perform particularly well over the last 3–5 years tend to underperform the market going forward.[1] Mutual funds haven’t exhibited reversals, but funds that outperform tend to regress to average performance.[2] At minimum, your thesis needs to have some explanation of why that’s not going to happen this time.
I’m not saying you’re wrong. AI stocks may well be a good investment. But I am pretty unimpressed by most arguments I’ve seen. “The last 5 years saw 50–100% return, therefore that same level of return will continue” is not a good argument—by (weak) default, it’s evidence that future returns will be lower than the market, not higher. (I wrote more on my thoughts in a recent post, especially this section.)
[1] Fama, E. F., & French, K. R. (1988). Permanent and Temporary Components of Stock Prices. Journal of Political Economy, 96(2), 246–273. http://www.jstor.org/stable/1833108
[2] Berk, J. B., & Green, R. C. (2004). Mutual Fund Flows and Performance in Rational Markets. Journal of Political Economy, 112(6), 1269–1295. https://doi.org/10.1086/424739