Invest Like the Best with Patrick O'Shaughnessy
00:52:31 · Patrick O'Shaughnessy, Cliff Sosin
[00:52:31] S0: I have a good friend who has been running this very cool experiment where if you break investing down into picking what to own, and then how much to own of each thing that you've picked, overly simplified but interesting way of thinking about it, He'd been running this experiment where he continues to pick the things to own, but then runs his own portfolio construction as he would have in the past in one lane. And then the second lane is just completely handing that off to an AI harness thing that he's built and says, You do all the portfolio construction, but stick with the stuff that I've picked. And what he's found so far is that that is drastically outperforming his version of portfolio construction, which itself is quite sophisticated. And the simple argument that he would make is, well, AIs are just really good at optimization. And they've read every paper on portfolio construction and all this kind of stuff and bet sizing and Kelly criterion. They know it all. And that in the future, perhaps we make that transition where the investor's job is just picking what to own and not how much of each to own. And I ask you this question, what do think about this idea and the future? Because you have such an unusual portfolio where, again, 80% of it is in one specific asset. And my guess is if you were in lane two, AI would weight your portfolio very differently than you have chosen to do it. [00:53:46] S1: I'm underweight. [00:53:52] S0: So I'm just... I'm dying to know what you think about this idea. That's clever. Underweight kirvana. It should be 90.
00:53:52 · Patrick O'Shaughnessy, Cliff Sosin
[00:53:52] S0: So I'm just... I'm dying to know what you think about this idea. That's clever. Underweight kirvana. It should be 90. [00:53:59] S1: Time skills probably are interesting on that to think about too. I think about how AI is gonna encroach into this business, I think it's gonna start at shorter timescales and work its way up to longer timescales. Because one of the challenges is that there's no verification loop. Your friend's ability to say that is based on results over... I mean, certainly not twenty year results. I strongly suspect that the march of AI into markets... And maybe it already started. I don't know how Renaissance Technologies did it, but I assume... [00:54:26] S0: Seems like they might have discovered the transformer for everybody else. It's like... I'm not kidding.
00:54:26 · Patrick O'Shaughnessy, Cliff Sosin
[00:54:26] S0: Seems like they might have discovered the transformer for everybody else. It's like... I'm not kidding. [00:54:31] S1: It wouldn't shock me if people who invest over shorter time scales starting with seconds and working their way out to minutes, hours, weeks, months, find themselves delegating more and more to models. Makes perfect sense. And that you could definitely imagine bifurcating that between trying to enrich the model. I think other people do things like this already, and this is just a more sophisticated version. But you can have a fully quantitative strategy, and then you can enrich it with what you think is qualitative human designed analysis. And then you can have a quantitative strategy to incorporate the qualitative. I think many of these multi strats do these sorts of things. And what he's doing is just a slightly different flavor of that. Makes perfect sense. There are so many ways to be successful, and models have just added more dimensions of freedom. [00:55:13] S0: But what about your own portfolio? Word more about how you feel comfortable having a position, forget the company that it is. Sure. That's that big, in the face of so much research that would suggest that's a crazy way to build a portfolio.
00:55:13 · Patrick O'Shaughnessy, Cliff Sosin
[00:55:13] S0: But what about your own portfolio? Word more about how you feel comfortable having a position, forget the company that it is. Sure. That's that big, in the face of so much research that would suggest that's a crazy way to build a portfolio. [00:55:27] S1: A lot of that research, I think, is more looking at price changes in terms of securities prices. And less focused on thinking about it the way someone who owns a company might think about it. Mean, we're talking about Carvana. Were it not for my sense that Carvana's infrastructure and brand and everything else is just so differentiated that there are few scenarios where it works out really badly, then I wouldn't feel so comfortable owning so much of it. It might just be as simple as that. That portfolio approach would have worked absolutely. Certainly, if you discovered Walmart or Home Depot or Fastenal or something back in the day, you wouldn't have taken full advantage of it. And that's kind of my sense with Carvana. If you read history, of course, all the people who did really great tended to be very concentrated. But, of course, the history is literate... [00:56:12] S0: Drivers your bias on
00:56:12 · Patrick O'Shaughnessy, Cliff Sosin
[00:56:12] S0: Drivers your bias on [00:56:12] S1: it. Yeah. You know, or the history of people who didn't. I also think that a lot of that literature is what most people who are looking for average or slightly better than average results should do, and it's totally the right thing to do. But that's not what I'm looking for. I like Carvana a lot. It wouldn't upset me any if stock went up a bunch and I felt compelled to diversify it, that would also be okay. It's just more of a trade off between expected returns and knowingly taking an unusual risk. [00:56:39] S0: What do you think about education? You and I have kids of roughly similar ages. Comment a little bit on how you're thinking about their educations, the institutions that have driven education in this country that have been really important in that whole path dependent story you've described. What do you think the present and future of education looks like or should look like?
00:56:57 · Cliff Sosin
[00:56:57] S1: I've been talking to the head of my kid's school about this, and more and more, it seems to be that his thinking and my thinking are heading in this direction of the way you're educating kids is getting more bimodal in terms of what you're looking for. Let me step way back. What is the benefit of intelligence? Personal intelligence, like your own intelligence, in a world where there's infinite intelligence for models. You might say, oh, it's useless. Doesn't matter. Someone with a 50 IQ can navigate the world just as well as someone with a one fifty IQ. And I don't think that's quite right. And intuitively, doesn't feel right. But I think to nail down where it is, is that the more intelligence you have, and the more crystallized intelligence you have, which would be sort of education, the better you are at communicating with a model and telling a model what you want. I would have a very tough time having a deep conversation with a model to create leading quantum physics experiments because I don't know anything about quantum physics. And the model could try very hard to explain things to me, but in the end, it would be explaining things in crayon and NERF, and it would just be very hard to get the leading edge and get the best out of what the model has to offer. Whereas in an area where I do have some expertise, the model and I can communicate effectively, and I can direct the model to my will much better. And so to direct the model to do your will, which I think is gonna be an important skill in the future, you do have to understand something about the world. And smarts help for that. And education helps for that. You can't ask it to assume this is a stochastic process unless you know what a stochastic process is. It could teach you what one is, but that's a lot of friction in figuring this all out. You don't have to work out the math, but you have to know what it is. And so when I've been thinking about education, there's this idea that you're teaching your kids a bunch of foundational skills that build on one another, where I think in the end, the sum total of those, they have to be able to them without models, not because they're going to do them without models in the future, but because if they don't know how to do multiplication, it's gonna be really hard to understand matrix multiplication.