Practical Lessons from Rob Arnott

[00:00:00] What assumptions do you have to make about future growth to justify today's price? If those assumptions are extravagant and implausible, you might have a bump.

[00:00:10] Market prices are set based on narratives, based on a set of beliefs that is held by the consensus that represents the consensus view. And betting on a narrative is a complete waste of time.

[00:00:27] I spoke with the whole company and I said, not a single person here is at risk of losing your jobs to AI. You're saying there's no risk at all. You might lose your job to somebody who knows how to use AI better than you do.

[00:00:42] Welcome to Two Quants and a Financial Planner, where we bridge the worlds of investing and financial planning to help investors achieve their long-term goals. Join Matt Zeigler, Jack Forehand and me, Justin Carbonneau, as we cover a wide range of investing and planning topics that impact all of us and discuss how we can apply them in the real world to achieve the best outcomes in our financial lives.

[00:00:57] Jack Forehand is a principal at Validia Capital Management. Matt Zeigler is managing director at Sunpoint Investments. The opinions expressed in this podcast do not necessarily reflect the opinions of Validia Capital or Sunpoint Investments. No information on this podcast should be construed as investment advice. Securities discussed in the podcast may be holdings of clients of Validia Capital or Sunpoint Investments.

[00:01:15] So Matt, we've got a great one for me this week because I am both a factor investor and a value investor. And I think we've hit the double play this week because we're going to be talking about Rob Arnott and the lessons from, we've done three interviews with Rob Arnott so far. We've done two regular interviews and we've done a show us your portfolio interview.

[00:01:30] And we've pulled together the biggest lessons we've learned from it. We've pulled together clips from Rob Arnott. And we're going to talk about what we think your average investor can learn from it.

[00:01:38] Rob's just one of those master communicators who you simultaneously feel like you're in school and you go, oh, oh crap. But oh crap in a good way. The teacher is way, way smarter than me.

[00:01:49] But then also he's got a way of explaining things where you're like, holy crap. And not just does this make more sense to me now, but I have 52 follow on questions that occur after I hear him explain something like how index is distorting markets and changing things like that, which we're going to get into.

[00:02:06] So I'm excited that we got to listen back to these three episodes and cut up these clips for today.

[00:02:11] Yeah. And he was a big thing for me because it was like, it was one of the first big investors we got in the podcast. Like when, when I, when we asked him to come on, I'm like, there's no way Rob Arnott's coming on. And it's a funny story. Like the way we got in touch with Rob Arnott is he had read, I had written an article about bubbles and he had read the article. And basically he reached out to me on LinkedIn to like say he thought it was a good article. And like that, that was how we, we got to know him. And then, uh, ended up with him coming on the podcast.

[00:02:36] Well, you never know my forthcoming articles on Michael Bouvale could result in a whole next level of bubble orientation.

[00:02:43] I can only imagine what topic you're going to be covering there. I look forward to reading it, but, uh, but it's appropriate to mention the idea about bubbles. Cause that's where we're going to start. And that was one of the things that drew me to Rob's research.

[00:02:54] Because I think bubbles are so interesting because we talk about them all the time, but when you get into the nuts and bolts, like the practical implementation, it's much, much harder than you think, like in theory.

[00:03:03] So he, here's Rob talking about how to define a bubble.

[00:03:06] I find it interesting. People talk about the tech bubble, the Japan bubble, and it's always in retrospect. And if it's in the present, um, it's more framed as a question.

[00:03:17] I think Tesla might be a bubble. GameStop looks like it might be a bubble. Why not rigorously define the term bubble in a fashion that can be used in real time?

[00:03:27] So we did that in 2018. The definition is really simple. Firstly, start with a valuation model like discounted cashflow.

[00:03:36] What assumptions do you have to make about future growth to justify today's price? If those assumptions are extravagant and implausible, you might have a bubble.

[00:03:47] A check on that is, uh, the second question, does the marginal buyer care about valuation models at all?

[00:03:57] So is Apple a bubble? No, you have to use aggressive assumptions to justify today's price. They aren't extravagant. They aren't implausible. They're just aggressive.

[00:04:06] Um, and there are some marginal buyers of Apple who aren't buying the Apple story. They're buying a valuation model in which they're using aggressive assumptions.

[00:04:16] And they're saying, look, this stock is sensibly priced. Okay. So that's not a bubble. It's expensive, but it's not a bubble. Um, Tesla, uh, if you take last year's sales, 2020 sales,

[00:04:30] if you increase it by 50% per year for the next 10 years, then Tesla in 2030 will be 55 times as large as it was in 2020, 55 times as large.

[00:04:44] By comparison, Amazon growing at 26% a year compounded tremendous growth is 11 times as large as it was in the year 2010. So 11 times versus 55 times.

[00:04:58] Do you think Tesla will have five times as much growth in the next 10 years as, as Amazon had in the last 10? That seems to me implausible. Let's take a further assumption. Let's assume that their, um, net profit margin, uh, uh, gap accounting profits.

[00:05:17] In the year 2030 are as high as any major automaker has had in any year in the last 10 years. Well, that'd be a little over 10% after tax profit margin, um, uh, gross margins, um, before, um, the discretionary expenditures north of 25%.

[00:05:38] Uh, if they achieve that in 2030 and you discount that back to today, you get a value of $430, not 600. Okay. So yes, Tesla's a bubble. If the marginal buyer doesn't care about valuation models, have you met any Tesla investors who say, I'm looking at a discounted cashflow model?

[00:06:04] What's hard about this is basically in retrospect, we always think it's a bubble. Like then the late nineties, obviously that was a bubble, but I was sitting there. Then I was like working for an internet company who obviously had no revenue and no, probably no hopes of profits or anything like that. But we were getting tons of venture capital and stuff. And like, when you're living in that moment, you don't think you're in a bubble. You think the world is changing. You think the internet is going to do things that we've never imagined, which by the way, the internet did do. It just didn't work out that well for the people that were sitting there at the time.

[00:06:34] And maybe particular to you being at an internet startup in the boom era of this. And he makes, he makes the explanation there about if you have a valuation model that's still tied to it, even if you have aggressive assumptions, you're not in a bubble yet. But as soon as the, the marginal buyer does not care about the assumptions and it's a totally different thing.

[00:06:57] So do you think when you were at internet startup phase, Jack, that like at first you have aggressive assumptions about how bright and exciting this future is, is it when like the venture capital that ran out where all of a sudden, like there was no longer a marginal buyer who just didn't care to either update their models or not care at all anymore?

[00:07:17] Well, first of all, I would pretty, I could pretty much tell you the VCs were not using a discounted cashflow models to that view.

[00:07:23] We probably were the definition of that from the beginning, but what really changed was 2000.

[00:07:27] You know, when, when early 2000, when the tech, when the public companies roll over, that's when it carries down.

[00:07:32] And we kind of saw that with the recent one too, like you see the cup, the public companies roll over and then, and it carries down everything.

[00:07:37] So that, that was basically the end when the, when the bubble burst in public markets, then there was obviously no IPO.

[00:07:43] There was, you know, all these ideas about, you don't have to worry about revenue, just get eyeballs, like all that went away.

[00:07:48] So yeah, that would, that was the end of the road.

[00:07:50] Yeah.

[00:07:50] It's, it's a really interesting lesson because I think it's understanding there's, there's a part of the bubble where people are just more and more aggressively updating their models.

[00:07:59] And that's not necessarily the bad part of the bubble.

[00:08:01] The bad part of the bubble is when all the models have completely gone out the window or maybe, you know, eyeballs becomes the determining factor in the valuation that you have to go like, wait a second.

[00:08:11] This isn't reality.

[00:08:12] But he, I think what he had in that clip was great because you want to try to do this in real time and it's really hard to do in real time, but to do it in real time, you need criteria.

[00:08:21] And so what he said is what some, what assumptions do you have to make about future growth to justify today's price?

[00:08:27] And does the marginal buyer care about valuation models, which is what you mentioned.

[00:08:30] So that is something you can apply to any bubble in real time.

[00:08:34] It's not easy to do, but it can be done.

[00:08:36] So we can look at where we are now.

[00:08:38] And, you know, he had some examples in his, you know, this is, this is introduced from a little while back.

[00:08:40] So he's talking about Apple and Tesla, but he's talking about them in a different world than we sit in today.

[00:08:44] Although one could argue maybe we're in the same world.

[00:08:46] But so if we apply that to say the Mag 7 today, like it's hard to argue like NVIDIA is in a bubble.

[00:08:54] Because is NVIDIA very potentially overvalued?

[00:08:58] It is potentially overvalued, but we've talked about in previous episodes.

[00:09:01] And when you model the free cash flow NVIDIA against its stock price, it carries through pretty well.

[00:09:06] So you don't need ridiculous assumptions about the future of NVIDIA's growth.

[00:09:11] I don't think at least to justify the current price doesn't mean it's overvalued, not overvalued, but potentially not a bubble.

[00:09:17] And does the marginal buyer care about valuation models?

[00:09:20] I mean, maybe some don't with NVIDIA, but it is possible to create an evaluation model with the growth NVIDIA is showing right now.

[00:09:26] And with the future at AI, it's possible to create a valuation model that justifies today's price.

[00:09:31] So to me, NVIDIA is an example of something that's probably not in a bubble.

[00:09:35] And I think this is the value of the criteria is you can apply it in real time.

[00:09:39] You can look at where we are now.

[00:09:41] It doesn't tell you anything about what's going to happen with NVIDIA's stock, but it does tell you maybe we're not in bubble-like conditions.

[00:09:47] And I think that's an important point, especially for those of us who deal with clients, who field client questions about this stuff, who have sometimes purposeful and other times accidental exposure to these things that may or may not be a bubble.

[00:09:59] But just understanding how hard we want to pump the brakes on that type of stuff or have really hard conversations with clients about it.

[00:10:07] Because if you find a number of things that have evidence that at least don't say, warning, warning, this is clearly a bubble.

[00:10:13] Nobody cares about financial models anywhere.

[00:10:15] It's just all cults of behavior.

[00:10:17] Then you can go, here's where I'm cautioning you.

[00:10:20] But if you find stuff like a bunch of thoughtful, articulate comments on this, I'm right there with you.

[00:10:25] There's lots of reasons to go like, okay, if there's evidence that still supports this, even if the assumptions are aggressive, maybe just don't press panic.

[00:10:34] So I think the only logical thing to do now is to allow you to apply this model to Dogecoin.

[00:10:38] So how would you break it down when you use Rob's model?

[00:10:43] Well, when I discount the cash flows back from each Dogecoin to...

[00:10:48] Yeah, exactly.

[00:10:50] So the point being, there probably are some bubbles out there today, but it might not be the Mag7 stuff that a lot of people are thinking about.

[00:10:57] So we did this clip in two parts because I want to talk about, it's great to identify a bubble, but then the next problem is, what do I do?

[00:11:03] So here's Rob talking about that idea.

[00:11:05] Now, the third part of your question is, what can investors do about bubbles?

[00:11:10] That is trickier.

[00:11:12] Bubbles can last longer and go further than anyone could possibly imagine.

[00:11:19] So be very careful about shorting bubbles.

[00:11:23] You don't have to own them, but shorting them is very dangerous.

[00:11:28] My favorite example is the Zimbabwe stock market during the early stages of their hyperinflation in 2008.

[00:11:35] In the summer of 2008, if you said, this country's experiencing hyperinflation, it looks like it's about to get out of control.

[00:11:43] The last thing I want to do is own stocks in this country.

[00:11:47] I'm going to actually short them.

[00:11:49] I'm going to short the Zimbabwe stock market, but I'm going to do it prudently, just 2% of my portfolio.

[00:11:55] Well, the first six weeks of summer, the Zimbabwe stock market, the currency fell tenfold in six weeks.

[00:12:02] So people didn't want to have any Zim dollars that they could possibly avoid holding.

[00:12:09] And so they put money into the stock market and it went up 500 fold in Zim dollar terms.

[00:12:17] 50 fold in U.S. dollar terms in six weeks.

[00:12:21] By the end of the summer, the currency had fallen another hundredfold.

[00:12:26] The stock market essentially fell to zero and stopped trading.

[00:12:30] So I think there's two things to understand here.

[00:12:32] First of all, obviously, I think you were probably shorting the Zimbabwe market back at that time.

[00:12:37] So you probably felt the pain of the Zim dollar and everything else that went on.

[00:12:41] But he had a nickel for every time I was short in Zimbabwe at a hyperinflation scenario.

[00:12:46] Yeah, I'd be original.

[00:12:49] But it's important what he said because you can't short these things.

[00:12:52] Like the reality is, all right, I've identified there's a bubble here.

[00:12:55] There's not much you can do about it because if you think about going back to our own example, the late 90s, like when did people start thinking that was a bubble?

[00:13:01] They started thinking it was a bubble way before it finally burst.

[00:13:04] And if you like thinking about what the year 99 was in terms of the performance of Internet stocks was a ridiculous, ridiculous year.

[00:13:11] Like if you would come out of 98 thinking like this can't go anymore and you had shorted some basket of Internet stocks in 99, you were you were completely blown.

[00:13:19] And so from that perspective, there's there's nothing you can do in terms of shorting these things using any conceivable system that'll help you make money.

[00:13:30] So you have to kind of put that aside and say, all right, I know it's in a bubble, but there's really not much I can do about it.

[00:13:36] So this aspect of and I know you said the Dogecoin thing like ingest before, but this this question of what's the market?

[00:13:43] Who are the active buyers and sellers of this thing?

[00:13:46] And kind of I think of it as not who am I in bed with?

[00:13:49] That sounds dirty.

[00:13:50] But like who who else is playing in this marketplace?

[00:13:53] Because I think that becomes a really important question, too.

[00:13:56] And we can pick on like, you know, some of the.

[00:14:00] Crypto stuff are like weird, you know, crappy coins and all that wonderful stuff where you basically say, like, who is buying and selling this thing in the marketplace that if I come in and I join this market system, who am I buying from?

[00:14:13] Who am I selling to?

[00:14:14] And if all that happens is when you look around, as you see, like freaks, weirdos and people with no financial models and just banking on cultish prayers, you probably want to go to yourself like, wait, this is more bubble like behavior than if I'm in a public market stock and pick any of the S&P 500 names.

[00:14:32] And no matter what you think of their valuations, you just go like, who am I buying, selling from to against in this scenario?

[00:14:39] And do I think there's at least some rational players, even semi-rational players in this market or passive, too?

[00:14:45] We'll get to that.

[00:14:45] And how does that inform just who I'm exchanging with?

[00:14:48] I think that's a critical aspect to understanding these things, because we can see them out of sample in the Zimbabwe stuff, but we can also see them like in real time with how do we think through how does this fit into the broader context of who I'm buying and selling from?

[00:15:01] Which seems somehow strangely useful here.

[00:15:05] And that there is potentially some stuff you could do about a bubble, like not on the short side, but potentially on the long side.

[00:15:09] And, you know, Rob made this point in the interview is if you're a big believer that, you know, there's a bubble in the market.

[00:15:14] But like thinking back to the late 90s, there wasn't a bubble in value stocks in the late 90s.

[00:15:18] They were they were getting killed.

[00:15:19] Like they were they were not going up along with everything else in the late 90s.

[00:15:23] So you could say, well, I'm going to tilt my portfolio towards value stocks.

[00:15:26] And that's a perfectly reasonable thing to do.

[00:15:28] And it worked out really well.

[00:15:29] But again, we have to realize, like the timing of it's going to be impossible.

[00:15:33] Behaviorally, it's going to be really, really challenging.

[00:15:35] Obviously, if I was tilting towards value stocks as 96, 97, 98, as those came by, if I kept tilting and tilting and tilting more to value stocks, I was just getting angrier and angrier and angrier.

[00:15:44] It wasn't working.

[00:15:45] And eventually, yes, I did well.

[00:15:47] But it's very behaviorally difficult to go into these areas where you might have higher expected returns when a bubble is going on because you're sitting there watching the bubble happen and everything else just go up and up and up.

[00:15:56] I think about this a lot in terms of just because typically most of my client work, there's not a short book.

[00:16:04] We're not dealing with that unless it's like through a specific manager with short exposure.

[00:16:08] So most of the time, the version of shorting we discuss is just like what flavor or what level of avoidance is it?

[00:16:15] And if it's a valuation driven thing, it might be just a case of just not owning a stock or owning less of a sector than the market or whatever it is.

[00:16:23] And then you're basically saying, do I want to be completely away from this?

[00:16:26] Do I want to be partially away from this?

[00:16:28] How do I want to do this in and til?

[00:16:30] I think that's really like what you're talking about there before.

[00:16:33] If all through the late 90s, you just start going increasingly into value.

[00:16:37] It was probably OK to keep tilting into value as opposed to going like full on get short with all the gross stocks and try to get the long book and value up and running.

[00:16:47] So this next one is a quote I remember.

[00:16:48] And I don't know if he was the person who originated this, but I've heard him say it a lot of times, like from early in my career.

[00:16:53] There obviously are pure value strategies where I'm using some value metric and I'm trying to find the cheapest stocks.

[00:16:59] But there's a lot of other strategies that are value strategies that maybe people don't think are value strategies.

[00:17:04] So here's Rob talking about indexing and breaking the link with price.

[00:17:07] Think about stocks that are priced too high relative to their future fundamentals.

[00:17:14] Now, we don't know what their future fundamentals are.

[00:17:16] But if the company is destined to perform worse than the market expects, it will underperform.

[00:17:23] If it's destined to perform better than the market expects, it will outperform.

[00:17:28] Now, if you had a crystal ball and could create a fair value weighted portfolio, cap weighting will assuredly overweight all the overvalued and underweight all the undervalued stocks.

[00:17:40] OK, that's a given.

[00:17:43] Indexers have faced that criticism ever since the S&P was launched in 1957.

[00:17:48] And they've had a very ready retort to that.

[00:17:51] And that is, that's true.

[00:17:54] So what?

[00:17:55] You can't tell me which stock is which.

[00:17:57] Well, you don't have to know which stock is which.

[00:17:59] If you break the link between the weight in a portfolio and its price and the price of an asset, then an overvalued stock might be overweight or it might be underweight.

[00:18:10] An undervalued stock might be overweight or it might be underweight.

[00:18:14] Now the errors cancel.

[00:18:15] So roughly half of the portfolio is underweight.

[00:18:18] Roughly half is overweight.

[00:18:19] That gives you a structural alpha that is directly proportional to whatever errors the market is making in pricing assets.

[00:18:31] If it's a mean reverting error, you will get an alpha by breaking that link.

[00:18:36] So that much we know and can prove.

[00:18:45] The issue becomes pretty straightforward when it comes to what do you do about it?

[00:18:52] Anything you do that doesn't tie the weight to the price is going to give you a value tilt because growth stocks priced at premium multiples are likely to be downweighted.

[00:19:02] Value stocks trading at deep discounts are likely to be overweighted.

[00:19:06] And this ironically holds true whether you're using fundamental index or a minimum variance strategy or equal weight.

[00:19:14] They all have the same alpha engine.

[00:19:17] This is something that none of the practitioners offering these products will talk about, but their alpha engine has nothing to do with equal weight or minimum variance or anything else.

[00:19:25] It has to do with breaking the link with price.

[00:19:27] The point he made here is really, really important because a lot of people think, you know, if you're running a value strategy, you know,

[00:19:33] you're the cheapest EV to EBITDA stocks or the cheapest price to book stocks.

[00:19:37] But the reality is that you start with your market cap index.

[00:19:40] A lot of the other things you see out there are technically value strategies.

[00:19:43] So one example is the S&P equal weight.

[00:19:46] You know, the S&P equal weight is a value strategy relative to the S&P 500 or like what Rob runs fundamental index,

[00:19:53] which is instead of weighting stuff by their market cap, I'll weight it by some sort of fundamental thing.

[00:19:57] You know, whether it be sales or EPS, or I think they use a composite of a bunch of that stuff.

[00:20:00] But those are value strategies because they're caring more about fundamentals.

[00:20:04] They're breaking that leak with price.

[00:20:06] And I think that's an important way to look at things as you look at a variety of strategies that you have access to.

[00:20:11] Like value strategies or strategies that have a value tilt are not necessarily strategies that just start with these value ratios.

[00:20:16] It's funny to think because it's, you know, value is in one or the price in one sense is the only thing that matters.

[00:20:25] But in another sense, just thinking about what you care about and why for the exposure helps solve a lot of the long-term problems.

[00:20:33] And there's the surface level argument of breaking the link with price in these index design and constituents.

[00:20:39] There is a second and there's a way more behavioral element in people who are either buying the products, like buying the Equalway S&P 500,

[00:20:47] or thinking about building portfolios for themselves and whatever else and just going, what strategy I can stick to?

[00:20:54] And for some people, especially with any type of valuation concern or overlay,

[00:20:58] just this idea of breaking the link with price and putting the way that you think about stuff into the mix can go just a long way for still maintaining exposure.

[00:21:08] Because we're not talking about this other scenario of if you only buy stocks that start with the letter C and you don't care what the price.

[00:21:14] There was that old survey years ago where like that, even that outperformed the price weighted index from like 2000, 2010 or something.

[00:21:20] And it's like these types of ideas are just, it's okay to break the link with price.

[00:21:25] Know what you're getting into, but it's okay to do.

[00:21:27] And a lot of times the results still work.

[00:21:30] And what you said, know what you're getting into is important because even with these strategies,

[00:21:33] because what these things end up being like an equal weighted strategy or fundamental index,

[00:21:37] they end up being value strategies that are easier to stick with to some degree because they're less different than the index.

[00:21:44] You know, if you go in, if I'm buying the top 20, you know, cheapest price to book stocks for you,

[00:21:47] that thing is going to be a catastrophe in terms of your ability to hold on to it.

[00:21:50] So these are really good from that perspective, but you also have to keep in mind, there still are the behavioral issues.

[00:21:56] Anytime you break the link with price, you're also breaking the link with the S&P 500.

[00:21:59] And when you break the link with the S&P 500, you're going to look different than the S&P 500.

[00:22:03] And you're going to have periods of time where it doesn't work.

[00:22:05] And if you're not a believer in whatever you use to break that link,

[00:22:08] you're going to have problems where you're not going to stick with the strategy at a certain point.

[00:22:11] I think that's the most profound here is break the link at your own peril, go into it, eyes wide open,

[00:22:17] and just make sure if you're choosing to break that link,

[00:22:20] you're not also choosing to measure yourself exclusively against the prior connection.

[00:22:26] I'll take you using profound to say something I said, Matt, and I don't know if anybody's ever said that before.

[00:22:32] You are a wealth of profundity, Jack.

[00:22:34] I see, now you've gotten into words I don't understand.

[00:22:40] But some of this next split, we asked Rob about the rise of passive,

[00:22:43] but I think there's a couple interesting things in here too in terms of mean reversion.

[00:22:46] So here's Rob talking about the rise of passive.

[00:22:49] I think there's definitely truth in that.

[00:22:51] I think one of the main forces at work here is the move towards indexation,

[00:22:57] which is a very powerful force in the markets these days.

[00:23:04] If money goes from non-indexed portfolios to index portfolios,

[00:23:10] much of the money doesn't move because the index owns the market.

[00:23:17] But it really doesn't.

[00:23:18] It owns most of the market.

[00:23:20] So what happens is that the non-members in the index get sold and the members in the index get bought.

[00:23:30] So every $100 that goes into an index fund,

[00:23:34] about $80 stays more or less where it is

[00:23:39] because the index spans 80% of the market

[00:23:42] and about 20% of the portfolio moves from non-members to members.

[00:23:46] Well, that pushes up the relative valuation for members.

[00:23:50] And we saw that just two weeks ago.

[00:23:56] S&P made a blunder.

[00:24:00] They reported a list of holdings for a narrow niche dividend index that they maintain

[00:24:10] that didn't include one of the stocks that's supposed to be in the index.

[00:24:15] And so the index trackers for that strategy,

[00:24:18] and these aren't big index trackers because it's a niche index.

[00:24:24] Actually, it was the other way around.

[00:24:27] They added a stock to the list that wasn't supposed to be there.

[00:24:30] And then a couple of days later, they realized their mistake and they took it out.

[00:24:34] Well, the stock went from 84 to 90 and then back down to 84.

[00:24:39] That's a 7% move for a little niche index strictly because the stock was added and then dropped.

[00:24:49] And that's a big turnaround.

[00:24:52] So the spread in valuation for members versus non-members of the big indexes,

[00:24:57] like the S&P and the Russell, is much bigger.

[00:25:00] By our measure, it's in the 30% to 50% range.

[00:25:04] Membership has its privileges.

[00:25:06] You're worth more if you're a member.

[00:25:09] And that in turn, with the flow of money into index funds, can push the valuation of these companies up.

[00:25:18] Higher valuation means lower future long-term returns.

[00:25:22] You're more front-end loading the return in the run-up in price.

[00:25:26] And so non-members ought to have higher long-term forward returns than members of the index.

[00:25:36] But that's more than offset by the flow of money into indexes,

[00:25:41] as long as that flow is enough to push the prices higher and higher and higher.

[00:25:45] So that's a long-winded way of saying this value cycle, this anti-value cycle from 2007 to 2020,

[00:25:55] was undoubtedly augmented by the flow of money into index funds and augmented in a big way.

[00:26:01] We had had this discussion as part of, like, we were talking to him about expected returns.

[00:26:06] And, you know, one of the things I think that I think about a lot is,

[00:26:08] as you look at expected returns, and, you know, you do a lot more with expected returns than I do

[00:26:12] in the financial planning world, but you've got this idea of mean reversion.

[00:26:16] And what do I do about mean reversion?

[00:26:18] Because the challenge is, if I look at, like, the valuation of the S&P 500 over 100 years,

[00:26:23] these are wrong numbers, but I'm just going to throw something out.

[00:26:25] Let's say it's 15 or something is the PE.

[00:26:26] And let's say it now is 35 or something.

[00:26:29] But in the past 30 years, it's been, you know, in the 20s.

[00:26:33] So that we've been above that long-term average for a really, really long period of time.

[00:26:38] And when I'm thinking about expected returns, I've got to think about mean reversion back to something.

[00:26:42] And what do I mean revert back to?

[00:26:44] Like, do I think, you know, well, the 100-year thing is going to happen.

[00:26:46] This is what the bears think.

[00:26:47] You know, the huge bears, at least, is we're going back to 15.

[00:26:50] Like, you've got to put a lot of mean reversion in your models.

[00:26:52] But then you could say, well, you know, a lot of things have improved in the market in the past 30 years,

[00:26:56] and we'd probably have a lot of things that would justify a higher PE ratio.

[00:26:59] So maybe something in the 20s is more reasonable.

[00:27:01] So how do you think about that idea of mean reversion and what we're going back to?

[00:27:05] This is a big internal discussion on the investment committee I sit on for Sunpoint often.

[00:27:11] And I think a big part of this, and this is something I learned mostly in the Rob Arnott thing,

[00:27:16] but, you know, Mike Green and some others have definitely played into this thinking.

[00:27:21] Passive becoming dominant in this more recent window means stuff just comes into the S&P 500.

[00:27:27] One of the points Rob makes somewhere in one of these interviews is this whole idea of, like,

[00:27:31] when the active strategy got flipped or switched to the passive strategy,

[00:27:36] not every single stock in that portfolio changed.

[00:27:38] There were changes at the margin.

[00:27:39] It's not like 500 stocks went out and 500 new stocks came in.

[00:27:43] And even if it was only a, if it was a 50 stock strategy, maybe 40 or 45 of those are the same

[00:27:51] stocks when, like, the conversion happens.

[00:27:53] Meaning, like, the client sells the crappy active mutual fund we all love to make fun of,

[00:27:57] and they buy the super cheap S&P 500 index fund, and yay.

[00:28:01] But there's not that much change at the margin.

[00:28:03] What really is different is that in the marketplace, whether it's 50% passive or whatever the number

[00:28:07] is these days, anything that's in those benchmarks has this automatic flow lift that we've now been

[00:28:15] experiencing for a couple of decades.

[00:28:17] And when we look back at the data, we go all the way back to 1928 or wherever the hell the

[00:28:22] data starts.

[00:28:23] When we look all the way back at that data, it's kind of like, in this most recent period,

[00:28:26] it makes a lot of sense.

[00:28:28] And Rob has a quote about this where he says, you know, at the big level, it's like, what does

[00:28:33] he say, like, markets are 30 to 50%, you know, overvalued pretty much, like, systemically

[00:28:37] at this point?

[00:28:39] I think that's about right, yeah.

[00:28:41] So if you think about it, if, like, 15 was your number, 19 and a half or 20 or whatever

[00:28:46] the 30% markup is probably the new mean.

[00:28:49] And so we have to think about that while we're building into our assumptions and whatever

[00:28:52] else and not expect maybe the mean reversion all the way down before we say something

[00:28:56] is statistically cheap.

[00:28:57] But look at a narrower window of time, amend the models in some way, and just say, when we

[00:29:02] talk about this data pre-2010, let alone pre-2000, there's a lot more passive flows in this market

[00:29:09] and they're probably disrupting these things.

[00:29:12] Now, the perk of that too is meaning if you're looking for stuff that is intentionally different

[00:29:17] from those things, you almost have to correct in the other way as well.

[00:29:21] So I don't even know if I answered this question, but these expected return assumptions in planning

[00:29:26] and your time horizon, they're so intricately late, and this is so interesting to have somebody

[00:29:30] explain it the way that Rob and I just explained it.

[00:29:33] And the other place this plays in is in my world of value investing, because we rely on mean

[00:29:37] reversion.

[00:29:37] We think, you know, these stocks are going to mean revert back to fundamentals.

[00:29:40] And, you know, if you look at Mike Green's work, that's an argument that we may have to either,

[00:29:44] I mean, Mike may argue it's not going to happen, but it's at least an argument we have to wait

[00:29:47] longer for it to happen.

[00:29:48] Because if we've got these flows coming into these companies that don't care about fundamentals,

[00:29:52] it becomes harder for us to mean revert back to those fundamentals as more and more

[00:29:56] people do that.

[00:29:57] So I think that's just also something, you know, we should keep in mind as we look at this.

[00:30:01] And the distribution of those things too.

[00:30:04] So you might have to A, wait longer for your value thing to do whatever the value thing is

[00:30:10] supposed to do.

[00:30:10] But the other piece of this is those returns might come really fast and furious.

[00:30:16] So you might have to wait a longer period, but instead of just being anchored on reverting

[00:30:20] to your fundamental, have something that's anchored to, you know, the amount of the performance,

[00:30:25] the amount of the change, whatever it is.

[00:30:27] And I think as we identify places to make that tilt or be structurally overweight or take

[00:30:33] an idea that's not just a pure passive idea and put it into a portfolio, one of the other

[00:30:38] things that has to come into it is how long do we just want to let this ride and do nothing?

[00:30:41] But then what is also our strategy when all of a sudden this thing wakes up and goes to

[00:30:47] the moon in a very short amount of time?

[00:30:49] How do we deal with that?

[00:30:51] That that's more like owning a tail risk strategy or something that only performs in rare incidents.

[00:30:56] It's a very different way of thinking about stuff when you look at either specialty managers

[00:31:00] or specialty strategies where mean reversion ain't working the way it used to.

[00:31:05] So this next one is something that everyone in the world thinks, but may not be as accurate

[00:31:09] as people think.

[00:31:10] So everyone thinks value strategies are going to perform better in periods of high interest

[00:31:16] rates.

[00:31:16] And I'll let Rob explain why, but the data may not support that.

[00:31:20] So here's Rob talking about the relationship between interest rates and the performance

[00:31:23] of value versus growth.

[00:31:24] The linkage between interest rates or real interest rates or direction, recent direction of interest

[00:31:31] rates and the growth value cycle is very weak.

[00:31:35] There is no statistically significant evidence.

[00:31:39] The narrative is very strong.

[00:31:41] Low interest rates means a low discount rate.

[00:31:44] Low discount rates are better for companies with long duration, meaning growth companies

[00:31:49] where growth is big for the next 20 years than for value companies, which are front end

[00:31:54] loaded.

[00:31:56] Well, that narrative makes sense.

[00:31:57] That narrative also makes sense for stocks versus other assets that stocks should be more

[00:32:06] expensive in low interest rate environment.

[00:32:08] OK, let's start with the latter one.

[00:32:10] If that's true, then why are Europe and Japan with zero interest rates cheaper than the U.S.

[00:32:17] with 2% rates?

[00:32:19] That doesn't make sense.

[00:32:21] If that's true, why was the U.S. in the 1950s, the last time we had 2% rates, one third as

[00:32:29] expensive as it is today?

[00:32:31] That doesn't make sense.

[00:32:33] So the empirical evidence suggests very little linkage.

[00:32:35] As for the growth value story, low interest rates in the 50s, was it a great environment

[00:32:40] for growth stocks?

[00:32:41] No, it was not.

[00:32:43] It was a good environment for value stocks.

[00:32:46] Now, narratives can be very powerful.

[00:32:50] They can move markets.

[00:32:51] And so growth versus value moved as a consequence in part of that narrative.

[00:33:00] If the narrative is at odds with the empirical evidence, and this one is, then what you have

[00:33:09] is a narrative creating a market inefficiency.

[00:33:12] That's a wonderful thing.

[00:33:14] So I look for narratives that don't match the empirical evidence as a wonderful way of

[00:33:21] identifying sources of possible alpha.

[00:33:23] So, yeah, I mean, this makes so much sense, like, in theory, right?

[00:33:27] I mean, obviously, growth stocks have more of their value in the future.

[00:33:30] So if interest rates are higher, we have to discount that at a higher rate, they should

[00:33:33] be worth less.

[00:33:34] You know, and value, the opposite is true.

[00:33:36] And also, the market itself, you know, you can argue, basically, in periods of lower rates,

[00:33:41] the market itself should be worth, you know, it should trade at a higher PE.

[00:33:43] It should be worth more.

[00:33:44] And he talks about the data here.

[00:33:46] And this is one of those examples.

[00:33:47] And you see these examples all over in investing where the data doesn't necessarily back up what

[00:33:52] people think.

[00:33:52] So that great value growth argument in terms of interest rates, like, if you look at the

[00:33:56] long-term data, there's really nothing there to say value.

[00:34:00] And all the stuff people were talking about, you know, when inflation rose and because of

[00:34:03] that rates were higher, the value should have this huge run.

[00:34:06] It's just unfortunately not backed up in the data.

[00:34:08] I mean, there's other reasons value should have a huge run, but the relationship with

[00:34:11] interest rates isn't it.

[00:34:13] Do you think some of this falls all the way through just to, like, basic cost of capital

[00:34:18] things and the way our economy is adjusted?

[00:34:20] Do interest rates just not matter what they used to, not just as discounted into the future

[00:34:25] and now we compare a company that doesn't need to ever borrow any money because shareholders

[00:34:28] give it to them for free?

[00:34:29] Like, it feels like this is a bigger structural shift that is at play here.

[00:34:34] Yeah, it could be.

[00:34:35] You know, to be honest, I don't have the explanation because I've always been the guy who thinks

[00:34:38] this should be holding up.

[00:34:38] I mean, in terms of what the Fed has been doing and, you know, people are talking about

[00:34:42] how the Fed is influencing the market or, you know, distorting the market in some way.

[00:34:46] I don't really know.

[00:34:47] But one thing I've learned in my career is, like, if I have this logical explanation,

[00:34:51] I got to go to the data.

[00:34:52] And if I go to the data and the logical explanation doesn't work, I unfortunately have to throw

[00:34:57] out the logical explanation.

[00:34:58] And that's very, very hard to do because, like, something like this makes just complete

[00:35:02] sense.

[00:35:02] I mean, you still have people all the time who explain things this way and it makes 100% sense.

[00:35:07] But when you go to the data, it's got to work.

[00:35:09] And if it doesn't work in the data, then you've got to throw it out.

[00:35:12] I think that's a big lesson as a factor investor, but it's also a big lesson for anybody who runs

[00:35:15] any kind of strategy.

[00:35:16] Like, you can't just have your bias and then, you know, ignore the data.

[00:35:19] If the data says what it says, then that's what it says.

[00:35:22] I think that is a super important lesson to not ignore your bias.

[00:35:27] And one of the things that I use for stuff like this to just try to help keep myself intellectually

[00:35:32] honest, also to help clients think through this type of stuff, whether it's portfolio related

[00:35:37] questions or like in a business is you got to take these things and you got to apply them

[00:35:41] to yourselves and then apply to somebody else, you know.

[00:35:44] So if you have your, you know, HVAC company or whatever, like very, you know, not capital

[00:35:50] intensive in the traditional sense of you didn't build a factory, but like you have stuff,

[00:35:53] you have certain costs and you go like, what does it cost for me to borrow?

[00:35:56] What does it cost for me to do this?

[00:35:57] Do I even need to borrow money or any of these things?

[00:35:59] And you compare it to, you know, your, your buddy at his tech startup or whatever, like

[00:36:03] take these things, apply them to the real world.

[00:36:05] It's really hard to, I think it's really hard to scan this out to the entire macro economy

[00:36:09] and have one giant rule to rule them all.

[00:36:12] But it's, you can take a lot of nuance that are just thinking through how much variation

[00:36:17] is inside of these stories when you start to look at them on the, at smaller and smaller

[00:36:20] levels.

[00:36:22] So as we move to his next clip, I mean, there've been a lot of arguments where in a narrative

[00:36:25] driven market, and obviously this is something we've talked with our friend Ben Hunt a

[00:36:28] lot about, but Rob talked about the idea of there's one thing to understand what narratives

[00:36:32] are.

[00:36:33] The other thing is like, how do you implement them or what do they mean for an investment

[00:36:36] portfolio?

[00:36:37] So here's Rob talking about betting on narratives and market prices are set based on narratives

[00:36:42] based on a set of beliefs that is held by the consensus that, that represents the consensus

[00:36:50] view.

[00:36:51] And betting on a narrative is a complete waste of time.

[00:36:56] The reason for that is very simple.

[00:36:59] Narratives are usually largely true, but they're a hundred percent reflected in share prices already.

[00:37:05] So, uh, betting that the narrative will come true is the same thing as, uh, betting on

[00:37:10] nothing.

[00:37:12] Uh, now that actually comes into play on both of the topics you alluded to, uh, inflation and

[00:37:21] the macro economy.

[00:37:22] The narrative on inflation is, whew, thank goodness that's, um, over now.

[00:37:29] We just need to wait for the fed to push us through the last mile and get, get it back under

[00:37:35] control and, uh, the narrative is largely true.

[00:37:41] Inflation is much more subdued.

[00:37:44] It's backed down into sensible territory in the three, three and a half range.

[00:37:51] Okay.

[00:37:52] But, uh, I think it's awfully useful to ask where's the asymmetry now, 10 year break, even

[00:38:01] inflation, the difference between tips yields and treasury yields.

[00:38:05] For, uh, the 10 year bond is currently at 2.3%.

[00:38:09] So how do I think about asymmetry there?

[00:38:13] Is the coming 10 year inflation rate more likely to be 1% below that or 1% above that?

[00:38:22] 1.3 versus 3.3.

[00:38:25] I think if you asked a hundred people knowledgeable about markets and about the economy, you, you'd

[00:38:32] probably get 80 out of a hundred saying, well, 3.3 is more likely than 1.3.

[00:38:39] So that's an asymmetry.

[00:38:40] You can have part of your portfolio positioned to do better in a regime of elevated inflation

[00:38:51] rather than a regime of rapidly subsiding inflation, settling in at 2% in the next couple

[00:38:58] of years.

[00:38:58] This is the challenge with narratives.

[00:39:00] And, you know, we've, we've learned this from Ben's work is when the narrative becomes

[00:39:03] the thing all of us are talking about, that's not the time to battle the narrative because

[00:39:07] the narrative is priced in at that 20.

[00:39:08] And that's what Rob's talking about.

[00:39:10] Like, you know, Ben's work, a lot of it is trying to find these rising narratives that

[00:39:14] are coming up, not the narrative that has already peaked.

[00:39:16] But when your average investor wants to bet on inflation, a great example, because it

[00:39:20] just happened.

[00:39:20] When your average investor wants to bet on inflation, it's a pretty good sign.

[00:39:23] Inflation is probably going to slow down.

[00:39:25] And Rob talked about this idea of asymmetry.

[00:39:27] You want to find a situation where you have a divergent view from what is the popular narrative

[00:39:31] of the time.

[00:39:32] And you think you can make a bet on that divergent view.

[00:39:35] And Rob's talking about inflation and the idea, and this is, this was recorded earlier.

[00:39:39] So these are not his current thoughts, but he's talking about the idea that everybody

[00:39:42] kind of thinks inflation's going to come down now.

[00:39:45] Everybody thinks inflation's over.

[00:39:46] So if you want to make a bet on inflation being over now, you know, you're, you're probably

[00:39:51] just doing what everybody else is doing.

[00:39:52] Whereas if you have a divergent bet, you might have a better opportunity to make a profit

[00:39:56] from it.

[00:39:57] I love the idea of asymmetry here.

[00:39:59] I love the idea, extra Ben Hunt.

[00:40:01] And you know, you're looking for that emperor's new clothes moment.

[00:40:05] You're looking for the things where it's like, okay, everybody's accepted this thing.

[00:40:09] We're all following the parade along.

[00:40:11] But that first inkling of like, did, did the little girl stand up and really say that

[00:40:16] thing?

[00:40:17] And were we all scared to admit it before?

[00:40:19] And this can be a bubble popping moment or just like a transition.

[00:40:22] And if you're going to have narratives as part of your process, you need to also have

[00:40:27] some questions on how you understand those asymmetries.

[00:40:30] Because if you're just chasing the narrative that's already dominant, there's probably

[00:40:34] no edge aside from just following along.

[00:40:37] And sometimes just following along is just fine.

[00:40:39] You can be that index fund investor and just be along for the ride.

[00:40:43] As long as you understand that's the ride you're along for.

[00:40:45] But the reality of understanding the asymmetry and how you're going to be a part of that

[00:40:52] shift, because those shifts are just always changing.

[00:40:55] And I think that's, that's one of the hardest things.

[00:40:57] I think we underappreciate how much these, these things change over time.

[00:41:02] Like how, how few narratives are actually totally static in our lives or just kind of like wiggle

[00:41:07] back and forth without meaning a whole lot.

[00:41:09] You feel that too?

[00:41:11] Yeah, no, I do.

[00:41:12] And you know, and Ben's like, Ben's work on like the life cycle of these narratives is

[00:41:15] so good.

[00:41:16] Like I would, I would definitely encourage anybody to read it because as I mentioned at

[00:41:19] the beginning, we're dealing with a market where most of us think narrative probably

[00:41:23] plays a bigger role than it used to.

[00:41:25] And Ben has, what does he call it?

[00:41:26] Like a strong form of the narrative market hypothesis or where he's kind of come to,

[00:41:30] he's come to like from the idea that like this is a big part of what's going on to

[00:41:34] like the belief that this is everything in terms of.

[00:41:37] So for all of us who are fundamental investors, it's important to at least

[00:41:40] keep this in mind and to understand the role these are playing in markets.

[00:41:43] And, you know, I really like Ben's work from that perspective.

[00:41:45] Yeah.

[00:41:45] And there's, it shows up in lots of different places.

[00:41:49] So I think this is another case of where don't just try to make the one ring to rule them

[00:41:55] all thing about, uh, about broader markets and macro and think you're going to crack

[00:41:59] the entire code.

[00:42:00] Look for smaller places where this shows up.

[00:42:02] There's a great sort of like narrative shift happening right now in there was that whole

[00:42:07] thing.

[00:42:16] So it's this whole thing where Unilever has now come back to the table.

[00:42:19] So first Twitter makes it unsafe for large brands to be on the platform and do it.

[00:42:24] So then a bunch of them left and Twitter counter sues and says, says, Hey, you guys all got

[00:42:28] together behind the scenes and decided against us.

[00:42:31] And now we're slowly starting to see the first big brands start to come back into this thing.

[00:42:35] And it's, you have three kind of like prevailing narratives and counter narratives all fighting

[00:42:41] with each other to see which is the new one where everybody's like, Oh, it's okay.

[00:42:44] Now understanding this logic is one of those.

[00:42:47] It's a, it's unfortunately it's a rabbit hole.

[00:42:49] You read enough Ben Hunt, you start to see this stuff everywhere.

[00:42:52] And, uh, I don't know.

[00:42:53] It's a more interesting way to look at a lot of these smaller stories and not have to come

[00:42:57] up with a grand theory of everything.

[00:42:59] So there's probably not a bigger topic right now that everybody's thinking about than AI, um,

[00:43:03] and how it's going to influence all of us.

[00:43:04] And, you know, I'm hoping since you bring all the personality to the podcast, I can't

[00:43:07] wait for the day where I can just put AI Jack over here.

[00:43:10] Um, and you can just basically talk to AI Jack and I could be having a beer while this

[00:43:14] is going on.

[00:43:14] I mean, I can hallucinate with the best AIs for you, Jack.

[00:43:20] Don't worry.

[00:43:21] I'll give AI a run for each moment.

[00:43:23] It could be AI Jack right now, by the way.

[00:43:24] Um, you will.

[00:43:24] You know it.

[00:43:25] Um, this, this could just be a, yeah, I may be like sitting on the sofa right now and this

[00:43:28] might be AI Jack that you're talking to, but, uh, I don't think the technology is

[00:43:32] there yet, but I can't wait till it does.

[00:43:33] But, but on a more serious level, like thinking about this, you know, there, there's two levels.

[00:43:37] All of us are thinking about this on like, one is what is this going to mean for the

[00:43:40] markets?

[00:43:41] And two is what is this going to mean for our everyday lives?

[00:43:43] So we asked Rob, what do you think about the future?

[00:43:45] It's breakthrough for sure.

[00:43:46] It's going to change the world as we know it big time.

[00:43:52] Um, but the narrative is these are the players that are dominant in this industry.

[00:43:59] They'll still be dominant in 10 years.

[00:44:02] The disruptors won't get disrupted.

[00:44:04] And this change is going to come shockingly fast.

[00:44:09] So the parts of that narrative that are dubious are the rate of change of adoption of AI and

[00:44:18] the, um, uh, possibility of disruptors getting disrupted.

[00:44:23] So as we look, uh, as, as we look at this whole landscape, is AI going to change everything?

[00:44:31] Yes, it will.

[00:44:32] It's going to displace millions of jobs.

[00:44:36] Um, you guys aren't needed.

[00:44:39] I'm not needed if AI takes over our work.

[00:44:43] But I, I did tell our, uh, uh, uh, our old hands meeting about a year ago.

[00:44:49] Um, I, I spoke with, um, the whole company and I said, not a single person here is at risk

[00:44:56] of losing your jobs to AI.

[00:44:59] You're saying there's no risk at all.

[00:45:01] You might lose your job to somebody who knows how to use AI better than you do.

[00:45:05] So get on it, learn how to use it and learn how to have it leverage your time and efforts.

[00:45:12] And, uh, it was, um, an interesting reaction, but, um, uh, AI is going to change everything.

[00:45:20] Um, a couple of interesting examples, uh, early days of chat GPT.

[00:45:26] I tasked it to write a children's bedtime story with, um, uh, uh, brave knights and unicorns.

[00:45:34] And it wrote a little 500 word bedtime story that any child's book author would have been

[00:45:39] proud to put their name on.

[00:45:41] It was beautiful.

[00:45:42] It was sweet.

[00:45:43] It was elegant.

[00:45:44] And, uh, it captivated the attention.

[00:45:47] This was done in the space of about five seconds by a computer.

[00:45:53] Cool.

[00:45:53] I then asked it to do a short bio of me.

[00:45:58] And I didn't know that I graduated with an MBA from university of Chicago and started my

[00:46:03] career at Goldman Sachs, but I guess I must care.

[00:46:06] Um, so it's, um, it makes things up.

[00:46:10] Um, I was recently reflecting back on Sun Tzu's famous book, the art of war.

[00:46:17] Uh, and I hadn't read it in decades.

[00:46:22] And so I asked chat GPT, write me a summary, uh, um, 2000 words or less of Sun Tzu's art of

[00:46:31] war.

[00:46:31] And it wrote less than a thousand words and it was succinct and it was thorough and it mirrored,

[00:46:39] perfectly mirrored my recollections.

[00:46:42] And it was so good that I circulated it to my whole management team and said, I know you

[00:46:48] haven't, most of you haven't had time to read art of war, but it's useful.

[00:46:55] Um, here's a synopsis that I think is just brilliant.

[00:46:58] And it was written by Chad G.

[00:46:59] So my, my big takeaway from this, and he mentions like the meeting of research affiliates that

[00:47:03] they had.

[00:47:04] And my big takeaway from him is, is what I think I've learned myself.

[00:47:07] Like I'm using AI a lot.

[00:47:09] There, there's certain things it does really, really well.

[00:47:11] I mean, there's certain things it does better than I ever thought it could do it.

[00:47:14] But I think this connection of like humans and AI is going to be the key here.

[00:47:19] I think like the people, he mentioned this in the interview, like the people who he,

[00:47:22] you're not going to lose your job to AI, or you're at least not likely to lose your job

[00:47:26] to AI, but you are likely to lose it to someone who learns how to use it.

[00:47:30] And so I just think like with all the stuff I do, every process I have, I always ask myself,

[00:47:34] like, how could AI aid me in this?

[00:47:36] And it is great if it's a process that AI could just take over completely.

[00:47:39] But more and more, I'm finding it's something where AI could just make the process a lot

[00:47:43] better or like accentuate what I can do as a person.

[00:47:47] So I think he's very right about that.

[00:47:49] I mean, I think that's where we're headed is where the people who should figure out the

[00:47:52] right way to use AI are the people that are going to be successful.

[00:47:55] There was a point in the, we've done a couple of different things with Brent Donnelly in

[00:48:00] the last couple of months.

[00:48:01] It was in the intentional investor interview where he talks about as the, uh, the foreign

[00:48:06] exchange markets really got upset in the early to mid two thousands by just the advent of

[00:48:11] all the algos and all the other things coming to it.

[00:48:14] And he had stepped away from FX trading and then decided to come back into it in the early

[00:48:19] to mid two thousands.

[00:48:20] And one of his big realizations were he's like, everybody kind of hated the bots.

[00:48:24] They hated the algos.

[00:48:25] They hated all these system, uh, systematic traders that were coming into the fold.

[00:48:29] And he was like, but then he realized that kind of took a lot of the drudgery out a lot

[00:48:34] of the stuff he had been burning out on in the nineties where you're just basically a glorified

[00:48:38] blackjack dealer or something.

[00:48:40] I think that's the way he put it.

[00:48:41] He was like, Oh wait, if you can take the drudgery out, then it creates all this room and openness

[00:48:47] for other stuff you can go and do.

[00:48:49] And I keep thinking about that from, it goes back to this too.

[00:48:53] It's that mix of not just people like you.

[00:48:57] And I love that I can work with you and you can tell me, this is how we put these queries

[00:49:00] and questions into Claude or whatever and get this stuff back.

[00:49:03] That's amazing.

[00:49:04] But I'm also not that guy.

[00:49:06] But what's fascinating to me is that I have people like you who understand how we're doing

[00:49:10] it with like YouTube and the podcast and all this other stuff.

[00:49:13] I have people like my, my colleague Ben Tusk guy and how we're doing it with like tax

[00:49:17] planning and forecasting and legal stuff and all these other things for my work work.

[00:49:22] And it's, it's pretty amazing.

[00:49:24] If you can have the right people who understand AI around you and become enough of that person

[00:49:29] yourself, holy crap.

[00:49:31] Can you take a lot of drudgery out of life and, and actually do stuff that creates value

[00:49:37] because just removing that drudgery is just holy crap.

[00:49:41] Amazing.

[00:49:42] So here's a good example.

[00:49:43] Like we, with these podcasts and with YouTube in general, it's not the way you'd love it

[00:49:47] to be in the world, but it is the way it is.

[00:49:48] Like how much these get watched is very much a function of what the title we use for the

[00:49:52] interview is and what we put on the thumbnail.

[00:49:55] And, you know, we're not the types of people, like I'm not going to put a picture of Matt

[00:49:58] with like burning fire and like the world, the coming apocalypse or whatever.

[00:50:02] Like some of the stuff people do, or we're not going to do Mr. Beast's face.

[00:50:04] Like we're trying to run a professional show here.

[00:50:06] I mean, people could argue whether we're actually doing that or not, but we're attempting to do

[00:50:09] it.

[00:50:09] So, but this is an example of where AI can help me a lot because I have to figure out

[00:50:14] like the right thing within the standards we want to apply here.

[00:50:17] I want to find, I have to find the right thing to put on that cover.

[00:50:19] And if it makes an, it makes a huge difference in terms of how these things are watched.

[00:50:22] And so what I can do is I can take the transcript of this interview.

[00:50:25] I can put it in there and I can say, suggest to me, here's exactly what I'm trying to accomplish

[00:50:30] with the title and with the cover.

[00:50:32] Give me a bunch of examples of things I could potentially use.

[00:50:35] And then what I can do, if you just allow it to do it for you, what it's going to do right

[00:50:39] now, at least is give you the most over the top thing that you don't want to do.

[00:50:43] It's going to give you something that it thinks would create the most engagement, but it's

[00:50:45] typically something that's beyond what we want to do.

[00:50:48] But what it can do is when it gives me these 10 different options, I can say, oh, from that

[00:50:52] one, you know, that's a great idea.

[00:50:53] And then this other one, they said, I can build on that and change that a little bit and that

[00:50:56] will work really well.

[00:50:58] And so it's reduced the time of that a lot.

[00:51:00] Not only is it giving me a better outcome, but it's reduced the time of that a lot.

[00:51:03] But if I wasn't coupling it with myself, we would have the over the top fire and all

[00:51:07] that stuff on the covers because that's what it's telling me to do.

[00:51:10] So that's an example of it's making me come up with a better outcome myself.

[00:51:14] But if I left it on its own, it wouldn't be as good of an outcome.

[00:51:17] And it's interesting as that shows up on your YouTube home screens and whatever else, everybody

[00:51:22] out there watching this, where nobody's actually made it this long in the show, right?

[00:51:26] No, probably not.

[00:51:28] For the one of you who's left, I've been about to leave some bizarro YouTube comment below

[00:51:32] this thing.

[00:51:34] There's a range of this happening.

[00:51:36] So there's a marketplace of this happening too, where all these content creators and

[00:51:39] other people are using AI to create different layers of this stuff.

[00:51:42] So there's going to be a preponderance of people using the Mr. Beast face, everything's

[00:51:47] on fire, doomerism stuff.

[00:51:48] And then there's also going to be a bunch of people who aren't doing any of this, who

[00:51:51] have like crappy titles and subjects or whatever else, basically see the Culture's Creative

[00:51:55] YouTube channel for my attempts at these things.

[00:51:57] And it's somewhere in the middle is people who are becoming that hybrid.

[00:52:02] And I have to believe over time that it's going to be some of the people from the bottom

[00:52:06] migrating up and some of the people from the top just kind of flaming themselves out.

[00:52:10] Because this is the stuff that's, that stuff is trendy right now.

[00:52:14] Some of it will work forever.

[00:52:17] Big air quotes around that.

[00:52:18] But a lot of it is just like, if you're chasing just the thing the algorithm wants right now

[00:52:23] and here, these platforms shift their thinking all the time.

[00:52:27] So if you can get just enough of a shortcut to make something that's authentic to you

[00:52:30] and explains your, uh, what you're trying to do, run a professional operation, as you

[00:52:34] said, I think there's a lot of durability and staying power in that.

[00:52:37] And again, who are you competing with?

[00:52:39] The people who put their full faith and trust into this thing, doing all the work for them

[00:52:44] so they don't have to do anything.

[00:52:45] And like the people who don't want to do this at all.

[00:52:47] I think this is true in a lot of careers right now.

[00:52:49] If you're just touching AI, you won't lose your job to AI, but, uh, you know, you will

[00:52:55] potentially lose a job to some reason, not at least engaging with this to understand how

[00:52:59] it can take the drudgery out and make them better at their work.

[00:53:02] Yeah.

[00:53:02] It's funny.

[00:53:02] Like YouTube covers may become like what markets were, which is markets where people competing

[00:53:06] as people, and then it became like computers completing its computers.

[00:53:09] Like it might be the same thing.

[00:53:10] It might be AI competed against AI, but like we mentioned this idea Gavin Baker had had a while

[00:53:14] back where he, he kind of thinks in the world of value investing, like one, what, who's going

[00:53:19] to win here are going to be like the traditional, the value managers again, the people, because

[00:53:23] they're going to figure out how to use the AI.

[00:53:25] And so they're going to kind of have an edge over the people that are just purely operating

[00:53:29] on AI.

[00:53:29] And I think that's probably, that's true.

[00:53:30] And that's basically how I'm conducting, you know, what I'm doing is, is based on that

[00:53:33] belief.

[00:53:34] I think eventually like, yeah, we're going to, the AI is going to take over and it's going

[00:53:37] to do all this stuff.

[00:53:38] But I think human assisted AI is going to be the way to go.

[00:53:41] And I think it's going to be an edge for people who figure out how to use this and use

[00:53:44] themselves as well to compete against just the pure AI.

[00:53:48] Couldn't agree more.

[00:53:49] And I think it dovetails right in the search as well.

[00:53:51] And that's part of like the insanity of all this is it's a matter of, it's, it's a two

[00:53:56] way street with AI because you're using it to go out and play in markets and play in a

[00:54:00] world against people who are using AI.

[00:54:03] And then AI is being trained back on you to watch your behaviors and whatever else down

[00:54:07] to the point where I wrote a, I wrote a post the other weekend about the history of an

[00:54:12] MOP song that I really love.

[00:54:14] And like, oh, days after I released the post, but I'd gone through YouTube finding all

[00:54:20] these like, um, snippets of the song and whatever else it, it served me up this video from at

[00:54:26] least two years ago that I had never found, never heard of, couldn't have found on search

[00:54:30] on my own.

[00:54:31] But YouTube knew to present it to me.

[00:54:33] And it was actually like the story about the person in the remix of the song that I was

[00:54:37] writing about.

[00:54:37] I was like, where are you when I was writing my piece with this incredible story, but it's,

[00:54:43] it's impacting our lives at all the levels.

[00:54:45] And it's, it's not all bad.

[00:54:46] It's not all bad.

[00:54:47] It was pretty cool.

[00:54:48] Really happy.

[00:54:49] I found that Remy Ma interview.

[00:54:51] And just before we wrap up, we should talk about the other part I mentioned at the beginning,

[00:54:53] which is the impact on the market.

[00:54:54] And this is, this is what's tough about these new technologies is they're really,

[00:54:57] really hard to invest in.

[00:54:58] I mean, we certainly know it's going to change the world.

[00:55:00] We certainly know a ton of money is going to be made.

[00:55:02] We certainly know there's going to be companies.

[00:55:04] We're going to look back and be like, wow, how did I not invest in that company?

[00:55:06] Like, like the Amazons from the previous era.

[00:55:08] The problem is identifying them in real time is tough.

[00:55:11] Like if we think about AI right now, I mean, you can make a very strong case.

[00:55:14] The Mag 7 are going to be the winners here because they just require so much investment.

[00:55:19] They're the ones getting the stuff from NVIDIA.

[00:55:20] NVIDIA itself is getting this stuff.

[00:55:22] You could argue like those are going to be your winners.

[00:55:24] You could also argue, you know, some companies that come out of nowhere and figure out because

[00:55:28] you need a lot less people with AI.

[00:55:30] Some companies are going to come out of nowhere and figure something out.

[00:55:32] And that's going to be the next winner.

[00:55:33] And I always remember Amazon.

[00:55:35] I remember pets.com when I think about this, because in real time they were doing different

[00:55:39] things.

[00:55:39] But the point is in real time, both of them might've looked like they could potentially

[00:55:44] be big winners long time from the long term from the internet.

[00:55:47] And there were a lot of other companies that were like pets.com and the Amazons were the

[00:55:51] exception.

[00:55:52] The pets.com were the rule.

[00:55:53] And so it's very far, you know, other than buying like a basket of these and hoping you

[00:55:57] have the right stocks in the basket.

[00:55:59] As much as we know this is going to change the world, it's very hard to invest in it.

[00:56:02] And you can't forget another Rob Arnett point from these interviews.

[00:56:05] You can't forget that the people doing the disrupting now that are getting the increasingly

[00:56:11] aggressive assumptions will also be disrupted at some point in time.

[00:56:16] So no matter what, even if you get the Amazon right and the pets.com wrong or whatever, whatever

[00:56:21] the right mix is on these things, the disrupt, this is the nature of disruption.

[00:56:25] This is the nature of capitalism.

[00:56:27] This is the nature of markets.

[00:56:28] Like something else is coming for those things and it's coming for the assumptions.

[00:56:31] The more aggressive the assumptions are, the higher the chance that if there's something

[00:56:37] real there, it's going to get disrupted over time.

[00:56:39] That's just, I mean, it's just frigging humbly.

[00:56:41] It's just humbly.

[00:56:43] What's interesting to me is we've been in a world for a long time where all these different

[00:56:45] industries are getting disrupted from technology.

[00:56:48] What we're going to be in now is a world where technology is getting disrupted by other

[00:56:51] technology.

[00:56:52] And so like eventually everything becomes like these tech companies and then they have to

[00:56:56] worry about other tech companies coming from behind them.

[00:56:57] It's not like they're taking over these industries and, you know, finding these traditional businesses

[00:57:00] that are not using technology and overtaking that.

[00:57:03] Now it's going to be somebody is going to come from behind the Airbnb or whoever it is

[00:57:06] of the world and they're going to find a way to disrupt them.

[00:57:09] And Hey, listen, after watching a evil dead and evil dead to the other night, I can test, you

[00:57:14] know, Airbnb coming along and making sure that those log cabins in the woods aren't quite

[00:57:18] the murder holes that they once were.

[00:57:21] Like the world is evolving in fascinating ways, Jack.

[00:57:24] That's all I'm saying.

[00:57:25] I'm not a log cabin in the woods type of guy and you're not going to find me in one of

[00:57:28] those things.

[00:57:28] Ah, but what if it has a fun, you know, Necronavicon hiding in the basement with some haunted old

[00:57:33] people?

[00:57:34] It'll be good.

[00:57:35] Well, on that note, Matt, it's a good time to wrap up.

[00:57:37] Thank you for joining us and we'll see you next time.

[00:57:39] Hi guys.

[00:57:40] This is Justin again.

[00:57:41] Thanks so much for tuning into this episode.

[00:57:44] You can follow Jack on Twitter at practical quant.

[00:57:47] You can follow me on Twitter at JJ carbon and follow Matt on Twitter at cultish creative.

[00:57:53] If you found this discussion interesting and valuable, please subscribe in either iTunes

[00:57:57] or on YouTube or leave a review or a comment.

[00:58:01] Also, if you have any ideas for topics you'd like us to cover in the future, please email

[00:58:05] us at excess returns pod at gmail.com.

[00:58:07] We would like this to be a listener driven podcast and would appreciate any suggestions.

[00:58:12] Thank you.