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- [00:00]
Rob Arnott
Una silla de masajes puede pares er extravagante ocho configuraciones differentes intensidada justable ademases calefacionado y se siente tambien si una sille pares extravagante y dos bueno a un mas Peru se vuelben bastante practicas.
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Walmart Advertiser
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Rob Arnott
Hacientos de lanteros con masaje dispon ibles solo parese extravagante.
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- [00:58]
Podcast Co-host (Justin)
Savor Respons what would define a bubble?
- [01:02]
Rob Arnott
You have to make implausible, not impossible, but implausible growth assumptions to justify today's price. That's part one and part two. The marginal buyer doesn't care about discounted cash flow models. They care about the narrative. The story. Never short sell a bubble. Bubbles can go further and can last longer than you can possibly imagine. If you go back historically and you sort companies based on R and D expenditure that's positively correlated with subsequent success as a stock. Capex tends to be negatively correlated with future stock market performance. If you look at Nvidia, they have very happy customers. People are lining up for the privilege of getting on a waiting list to spend vast sums on the most expensive chips in the history of computing. Nvidia's customers have yet to find any way to transform that Capex into revenues and profits.
- [02:09]
Podcast Host
Hi Rob, welcome back to Excess Returns.
- [02:12]
Rob Arnott
Happy to be here.
- [02:14]
Podcast Host
It's always a privilege to have you on. You always bring your A game and that is a mix of data, evidence, historical, historical perspective on markets and the economy and a lot of times, you know, a non consensus but heavily weighted sort of view on the markets and sort of what we're sort of seeing in the market today relative to like its historical context. And so we always sort of get a lot of value and our audience does too by sort of having these, you know, longer discussions with you. And today we wanted to talk to you about get Your views on the market. Talk about whether or not we may be in a bubble or if there's bubble like areas of the market that investors should be paying attention to and sort of a whole host of things around that. And then also get into some of the research that Research Affiliates has put out recently because I think there's some very interesting stuff that you and your team over there have been working on. So hopefully people, you know, stay with us and hear about that research because it's going to, it's. It's important to be thinking about as investors. So, so to start, I mean, let's start on the bubble conversation a little bit. And you know, it's always hard to know. It's always easy to look back, but it's sort of can be hard to know when you're in it, whether or not you're, you know, we're in a bubble or nearing bubble, like territory or whatever. So just. Can you kind of walk us through how you think about looking at bubbles and assessing whether or not, you know, the market or areas of the market might be in a. In a bubble?
- [03:49]
Rob Arnott
Sure, sure. Well, firstly, I just. As the dot com bubble, lots of people identified it as a bubble while it was happening. A lot of folks are starting to identify this as a bubble while it's happening now. That doesn't guarantee that we're right about it. But if you stick to objective facts, you're less likely to be wrong. One cautionary note. Never short sell a bubble. Bubbles can go further and can last longer than you can possibly imagine. So be very careful about betting too aggressively against a bubble. That said, bubbles do happen. Back in 2018, we wrote a paper in which we offered a definition for the term bubble. The bubble. Term bubble is too often used and too rarely defined. And we offered a definition that can be used in real time. And I think that's important. What is that definition? Well, the price of any asset is supposed to be the market's best guess at the discounted net present value of all future profits distributed to the investors. All right, that makes sense. So what would define a bubble? You have to make implausible, not impossible, but implausible growth assumptions to justify today's price. That's part one and part two. The marginal buyer doesn't care about discounted cash flow models. They care about the narrative, the story. The bubbles also don't permeate entire markets. Bubbles are asset by asset. And there's a lot of froth in this market that I think would qualify as bubbles. Examples Palantir recently hit a market value of over half a trillion dollars. Trailing twelve month revenues. Three billion. Okay, now what's, what's the plausibility that a company with 3 billion in revenues could deliver net present value, future profits to shareholders of $500 billion? You'd have to see the sales, the revenues grow from 3 billion to 10 billion to 20 billion to 50 billion to 100 billion and then some over the course of the coming years. So if revenues aren't likely to reach 100 billion within 10 years, then you have an implausible pricing for Palantir. Second part of the definition. Does the marginal buyer of Palantir care about discounted cash flow models? Of course not. That's not why they're buying. They're not buying based on. I analyze the revenues and I analyze the future profits and here's my projections. No, they're buying because they buy into the story. So yes, we have bubbles galore today. We had bubbles galore in the year 2000. I think there are many lessons to be learned from the dot com bubble that are very applicable today and very useful to the long term investor.
- [07:21]
Podcast Host
Let's, let's just talk about some of those lessons because I think it's, you know, a lot of times these things rhyme but they're not exactly the same. So like what similarities are here, which people that you talk to? But are there also some differences as well in your opinion?
- [07:38]
Rob Arnott
Well, starting with the differences, I think AI is a bigger deal than the Internet. I think it will change our world more radically in the coming generation than the Internet has in the past generation. But the similarities also abound. If you look at the dot com bubble, I love looking at the top stocks in the dot com bubble. What were they? At the start of the year 2000, Microsoft was number one most valuable company on the planet. It's still in the top three. It pogos around 1, 2 or 3, but it's still in the top three. However, you had to wait 18 years for Microsoft to beat the S P500. That's a long time to wait. Now what happened? The decade of the 2000s was terrible for the company. Then under the new CEO they regained their footing, regained their vision and regained their momentum and lofted past the S and p in year 18. That's a long time to wait. Number two on the list, GE cresting on its way to irrelevance, lending money to its customers to buy its products. Ouch. Next was Cisco Chambers. The CEO was on TV in March of 2000 saying I don't see why we can't grow at 40% a year. As far as the eye can see. 40% a year after six years means. After five years means that you're six times as as valuable, six times as much sales, profits, whatever. Where are they today? They're six times as big as they were 25 years ago. That's 8% growth, not 40. They were also lending money to their customers to buy their product. Next on the list was Intel. It had a moat. It was building along with Cisco. It was building the infrastructure for the Internet and it had a moat. Nobody could dislodge it in the foreseeable future. Well, except for amd, aslm, excuse me, sml, Taiwan Semiconductor, AMD and now Nvidia. Okay, that means that it's been disrupted four times over in the last quarter century and it's now the fifth biggest chip manufacturer in the world. That's daunting. And that's after a $50 billion cash infusion from the Chips Act. Last two on the top six list would be Lucent doesn't exist anymore. And Nokia. Nokia still makes cell phones. You imagine Nokia was sixth most valuable company in the world in the year 2000. World straddling Colossi, destined for greatness. And only one has had a positive return. One out of the six has had a positive return in the last quarter century. Only one has beat the S&P. The other five have had negative returns for a quarter century. Yikes. So when we look at today's world straddling Colossi, wonderful companies, visionary leadership, a moat that can protect them from the competition. Except when it can't. And the simple reality is disruptors get disrupted. So one of the lessons of the dot com bubble is disruptors get disrupted. Another lesson is narratives shape prices. So don't bet on the narrative. That's going to do you no good. It's already in the price. Look for where the narrative might be off target. The narrative in the dot com bubble is off target in two ways. One, the narrative said the Internet's going to change everything, everything and it's going to happen fast. The narrative was correct on the first part. It changed everything, but it didn't happen fast. And the second, the second place the narrative was wrong is these companies have moats. They, they're not going to be disrupted. Most of them were. So be careful about bubbles because they can burst. They don't necessarily take take down everything around them with them. The bubble burst in March of 2000. Roll the clock forward two years. Nasdaq was down 50% on its way to an 80% drop. Meanwhile, the median stock is in the Russell. Russell 3000 was up 20%. The Russell 2000 value small cap value was up 53%. So the bull market of the 1990s for the average stock didn't end until two years later. The bull market ended for the cap weighted indexes because the dot com companies were so dominant in those cap weighted indexes. So many lessons from the dot com bubble.
- [13:09]
Podcast Host
So would one of the practical takeaways be, you know, for investors? I would imagine, you know, a lot of investors portfolios are heavily tilted towards many of the tech darlings large cap growth stocks today. So would one of the important lessons be, you know, let's get some diversification in. Let's buy, be buying other stocks in other categories like the value. I mean what else trying to get like what practically can investors do here if they have these concerns?
- [13:38]
Rob Arnott
Well, we're probably best known for having invented Rafi, the fundamental index 20 years ago. And Rafi takes, let's say the 500 largest companies in the United States, not 500 largest market cap, 500 largest businesses, and then weights them by the size of their business. So the growth stocks are going to be reweighted down. The Magnificent Seven are 34% of the S&P. They're 18% of Rafi. They're big businesses, they've been highly successful, they are magnificent. But we downweight them to their economic footprint. They aren't a third of the U.S. economy. Then we also have a rebalancing alpha. If the stock soars and its underlying fundamentals don't validate that price move, then Rafi will say, thanks for the nice gain. I'm trimming you back. If a stock tanks and its fundamentals don't, Rafi will say, thanks for the big discount. I'm topping it up. In so doing, you're concentrating against the market's constantly changing views of what a company is worth and you're turning volatility into alpha. So Rafi has a deep value tilt. It's every bit as value tilted as Russell value, but it has a rebalancing alpha. So globally, rafi has beat MSCI's equity value index by about 2 and a half percent a year for the last 20 years. 2 and a half percent a year is a lot. Compounds nicely over time with only about 2% tracking error. So it's 1, it's beat ACU value in 15 out of 20 years. That's wonderful. So one thing you can do is to the extent you want value as part of your portfolio and you should Value is really cheap now Rafi is a fantastic way to do it. Another thing that you can do is to look to broader diversification to liquid alternatives away from mainstream. US stocks are expensive. I love using the Shiller PE ratio price relative to 10 year smooth earnings. Shiller PE ratio for the US is 40 times 40 times the 10 year average earnings. That sounds expensive because it is. It's been higher than that once. Top of the dot com bubble it reached 44 times. So 40 times is in the 1% most expensive in history. Value is in the bottom 2 or 3%. In terms of relative cheapness in history, it's as cheap as it was at the peak of the dot com bubble. It's almost as cheap as it was after the COVID induced value meltdown in the summer of 2020. And so value represents an extraordinary opportunity. Non US stocks are priced at roughly half the US valuation multiples. Emerging markets are about 55, 60% off. Emerging markets value is priced at a Shiller P ratio of about 12. That's 70% off from U.S. s P500. RAFI fundamental index in emerging markets is priced at single digit Shiller PE ratio. You can buy half the world's GDP for less than 10 times the sustainable 10 year average earnings. That's cool. Now can I tell you that Rafi and emerging markets will beat the S and P over the coming year? No, of course not. But on a 10 year look ahead basis I would bet long odds that emerging markets Rafi and emerging markets value will soundly beat the S and P and especially will soundly beat U.S. growth stocks. It's not that the growth narrative is wrong. These companies are rocking our world. They are changing our world. They are changing the way we live in more ways than we can possibly imagine. But they're priced for perfection. They're priced as if they won't be disrupted by other newcomers with even better ideas.
- [18:03]
Commercial Narrator
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- [18:33]
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- [19:02]
Podcast Co-host (Justin)
What are your thoughts on the AI Capex spend? I wanted to get your thoughts because you're really good at putting things in a historical context and we're seeing massive, massive amounts of money spent. We're seeing companies that were effectively capital light companies become asset heavy companies very, very quickly. Like do you have any thoughts or historical context? You put this in in terms of what they're doing and the possibility that that's going to produce revenues and profits eventually that will justify that spend.
- [19:26]
Rob Arnott
One very simple, very powerful message is that if you go back historically and you sort companies based on R and D expenditure, that's positively correlated with subsequent success as a stock, not just as a business. If you do the same with Capex, it's negatively correlated. Capex tends to be negatively correlated with future stock market performance. And so CapEx is dangerous. It's seductive. You feel like you've got to do it, you've got to play along to, to. It's like the Red Queen, gotta run twice as fast as you possibly can just to stay in the same place. That's the nature of Capex. So it's dangerous not because it won't produce the changes that we're expecting it will, but because it won't necessarily do so profitably. One of the beauties of a well functioning capitalist system is creative destruction. Spend money carelessly and you could be making your way making way for another company to displace you. One of the key elements of a healthy capitalist system is that for a business to succeed it has to have happy customers. If you don't have happy customers you will be a victim of creative destruction. And justly so. The simple fact is if you look at Nvidia, they have very happy customers. People are lining up for the privilege of getting on a waiting list to spend vast sums on the most expensive chips in the history of computing. Very cool. And a money machine. Until they're disrupted by somebody else or by other chip makers that catch up. Now what about Nvidia's customers? Nvidia's customers have yet to find any way to transform that Capex into revenues and profits. So the the Capex spend is dozens of times the magnitude of the revenues that are being produced by by that capex spend. So that's not to say that there won't be revenues from AI. There will be. This puzzle will be solved in the years ahead. But for now, the companies doing the capex spending are having a dickens of a time trying to find a way to earn profits on that expenditure. That's a dangerous situation and that's very symptomatic of or very emblematic of what we already saw in the dot com.
- [22:24]
Podcast Co-host (Justin)
Yeah, I have like a value nature like you do. So one of the things I've been trying to challenge myself on is like, is there something different about AI? Like we had Kai Wu on, who wrote a really good paper about this. And you know, if you look back at the railroads or if you look back at the Internet, like all this money that went into infrastructure, to your point before, resulted in great things for society, but bad things for the people who built the infrastructure. And I'm just wondering, is there something about this technology that's just different than other technologies? Because you talked about before, you expect bigger things in the next decade, even in the Internet. Is there something we're missing in terms of how great this technology is, that maybe it's different this time? It's just something I think about. I don't know if you have any thoughts on that.
- [23:01]
Rob Arnott
Firstly, this technological revolution is very real. It's one of many. You go back to the steam engine, it changed everything. You go back to. Go back to 1825. 1825. The fastest way to get a message from New York to Washington D.C. was on horseback. And it took three days. And that's with fast horses and changing them and riding a series of horses 20 hours a day. Then came the railroad. Now you could do it in two days. Then came the telegraph. Now you could do it like that. Talk about a technological revolution. It was staggering. And the people who created those revolutions became wealthy. But the big beneficiaries were the users, the end customers. So when I'm asked who are the big beneficiaries of AI? My answer is you, me, everybody. We're all big beneficiaries, even those of us who have zero knowledge or interest in technology. It's going to rock our lives because it'll be made part of our lives in ways that we don't even notice. On the drive to this office here, I had a conversation with somebody about autonomous vehicles. AI is going to make autonomous vehicles able to drive without any traffic lights or stop signs, Just know where each other is and zoom. And on city streets, bumper to bumper Traffic flowing at 40 miles an hour on freeways, bumper to bumper traffic flowing at 80 miles an hour. And all of that made possible by AI without any of us even knowing how it's done. So the big beneficiaries will be everybody. An ordinary retailer will figure out how to use AI without even realizing they're using AI to broaden their reach to their customers. So it's going to change everything. But the big beneficiaries aren't necessarily the obvious ones. It'll be the less obvious ones that are currently priced as if they're headed for oblivion, when in point of fact most of them are going to be more prosperous in the future because of AI than they are today.
- [25:33]
Podcast Co-host (Justin)
I was thinking about that because I was thinking it'd be ironic if obviously the average stock has underperformed these tech stocks by a lot. But what if ultimately those companies end up being the biggest beneficiary of AI? And maybe some of the things we've been seeing in terms of value underperforming and the average stock underperforming, the AI carries down and that helps to change that in the other direction.
- [25:51]
Rob Arnott
And the beauty of it is just like, just like the Internet. Everybody uses the Internet whether they think about it that way or not. And Everybody's already using AI even if they're unaware of it. I mean, OpenAI disrupted Google's core business model this year. Google's core business model is sponsored links and pop up ads. That's where most of its profits come from. Well, you could use ChatGPT or Claude or Perplexity or whatever you want as your search engine. And you get no pop up ads and no sponsored links. You just get a verbal answer to your question and three, four, five useful links. Well, that's what you wanted from Google. So what's Google's answer? They realize, okay, we're being disrupted. This is existential for us. We'd better have AI as part of our default response. And so that's what they have now. Meanwhile, OpenAI itself has been disrupted also this year by Deep Seek coming out of nowhere. Back In January, Chinese AI ostensibly measured to be as powerful as ChatGPT 4.5 and ostensibly built with 1/100 the resources of OpenAI. Well, that rocks the world of AI. And now there's competing AI tools. Will OpenAI be the dominant player in 10 years? I have no idea. In three years? I have no idea. And yet you have Sam Altman telling a reporter just about 10 days ago who had the nerve to ask how with 13 billion in revenues. Can you commit to 1.4 trillion in spending an investment alongside your customers? How can you do that? That's 100 times your run rate revenues. And Sam Altman's answer was, well, if you don't like your stock, I'm sure I can find a buyer for it. That's a non answer. Come on, it's a legitimate question. And he later clarified and said, well, our revenues are way better than 13 billion and they're going to be 100 billion, 200 billion in very short order. He's suggested 20, 27 it could cross 100 billion. Maybe he's right. Even if it is 100 billion, can you still, even at that, can you commit to 1.4 trillion in spending? So you have huge expectations and huge promises for future growth. That again, back to my definition for the term bubble, are implausible. Discounted cash flow model would require implausible growth for OpenAI to be able to spend 1.4 trillion alongside its customers. So there's a lot of fluff. That's not to say that AI is any less consequential. I think it's the biggest revolution of the last half century. It may turn out to be the biggest revolution in technological history, but you know, the railroad was big, telegraph was big, automobiles and planes were big, medical innovations were big. The invention of the computer, my career, I've been really lucky. I started my career early days of computing. First computer I worked on when I was in high school was a digital equipment PDP8 that had 4k of storage and could handle 2 to 3,000 instructions per second. Wow. And now you've got an iPhone that does, I think 5 or 10 trillion calculations per second. I don't know the number, but something breathtakingly large. And that's all happened in my lifetime. And the advent of AI is happening sort of towards the end of my career. I hope to still be around in another 10, 20 years.
- [30:33]
Podcast Co-host (Justin)
Are you using it a lot personally though?
- [30:35]
Rob Arnott
Oh yeah, yeah. I did a little demographics research last night. I'd. I'd heard someone say that 80% of all 80 year olds who've ever lived are alive today. And I was curious whether that was true. So I did work using AI to scour databases to find out what was the world's population and what percentage of the population made it to age 80. And I came up with no, it's not quite true, there's been about 200. No, it was 1.3 billion people have made it to 80 years old out of 100 billion who've ever lived and that's about six times as many as are alive today. So what I heard was not true. But it took me 20 minutes on the Internet to using AI to assemble a spreadsheet to manipulate the spreadsheet and bingo, get an answer to my question. I was curious. Five years ago I would have thought, that's an interesting thing. I don't have access to that data and don't know where to find it. And it would be a, a whole weekend of work to answer a stupid little question. Well, I was willing to spend a half hour to answer a stupid little question, but. And I use it for, for work. We, we write about 20, 25 research papers a year and we self publish them on our website. And each time we put an image, I've got a picture here behind me, it might be an image like that or whatever, where the image is supposed to capture the essence of the paper. Three years ago we would hire three graphic artists and say, here's our paper, show us a picture that you think captures the essence of the paper. And whoever came up with the best picture that we chose to use, we'd pay them double. Okay, so that worked out really nicely. We got a lot of nice little images that were a fun way to kick off a paper starting early 2023, where we started using Dolly and Chat GPT to create these images. And within two or three months we found in 10 minutes it comes up with a half dozen images. And one of them is almost always better than anything that the graphic artists came up with. So I realized one of the careers that is most vulnerable to AI is graphic artist. And so we stopped using graphic artists and AI comes out with these clever little images that are just wonderful as a way to kick off the start of a paper. So we use it in all sorts of ways that would, would have been unpredicted just a year before ChatGPT was launched.
- [33:41]
Podcast Co-host (Justin)
Yeah, it's interesting. You can never, you can never predict who's going to be disrupted by these things either. Like, I remember when this first stuff first came on, everybody was worried about truck drivers. And I'm sure eventually truck drivers will be disrupted by this, but they're not going to be the first ones to be disrupted by this. It was professional lawyers and, you know, things that no one, no one guessed. So it's just hard to predict what these things are going to be.
- [33:59]
Rob Arnott
Yeah, that's exactly right. Tax preparers, the list goes on and on and on. There will be millions of white Collar jobs lost. There will also be millions of jobs created. And that's the other element of technological revolutions. The Luddites were destroying mechanical looms because they were worried about the millions of jobs lost to mechanical looms. It used to be that people would use looms that were not run mechanically, were run using human hands to create cloth. And millions of people, a lot of them 10 and 12 year old kids, losing fingers to their loans that were out of work and not bringing in income that helped feed the family. Was it horrible and disruptive to the families of these kids? Yeah. Although there were a lot less lost fingers. And did anyone, one generation after those jobs were lost, did anyone regret those lost jobs? No. Computers. Advent of computers was 50 60s, 70s. Before that a computer was a job description. It was a person who was very fast with math. It was a job, a job. You could be a computer. Computers put computers out of work. Does anyone regret a person who's very fast with math not being able to do fast math to calculate something that can be done on a calculator in a split second? Of course not. Not even the person who had that job would be read it at this stage. So technological revolutions kill millions of jobs. Media loves bad news. So all of these jobs lost, but millions of jobs created, that's not newsworthy. And efficiency improved. That's not newsworthy until long after it happens. The other thing is people think this is going to radically change the rate of growth of productivity. That I think is a dangerous oversimplification because every technological revolution does that. So you need a technological revolution, a big one, every generation, to create the productivity growth that we've enjoyed for the last 250 years. And if you don't have a technological revolution in any particular decade, you're going to have a stagnant economy for a generation. Well, we haven't had a stagnant economy for a generation in a long, long time because we keep having these technological revolutions that are just wonderful.
- [37:08]
Podcast Co-host (Justin)
I want to switch to index construction because one of the cool things you guys do, like if you looked at my portfolio or if you looked at your portfolio, they're going to look very, very different than an index. But for a lot of your average people, they don't want to look that different from an index. And you guys have done a lot of work around, you mentioned fundamental index before. You guys done a lot of work around, how can we make these indexes better? And you, some of your colleagues wrote a paper recently which I thought was really interesting because everybody wants to Sort of classify the index into. You've got the value section, you've got the growth section. And they sort of made the point, well, there's companies that maybe aren't both or maybe aren't either of those, and maybe you don't want to own those companies that are either of those. So can you talk about that work?
- [37:44]
Rob Arnott
We have done some work that just to tip you off and your viewers off on something that's coming. We, we've created what I think is a trifecta. Rafi introduced 20 years ago is a better way to do value investing. I mean, relentlessly better. We beat value indexes three years out of four over the last 20 years and beat it by a wide margin. T statistic on the global Rafi relative to cap weight value is now over five. I've, I've been in the quant community for my entire career. I've seen back tests with t statistics of 4 or 5. I've never seen a live strategy with a T statistic of 5 except this one. Well, that's cool. Second leg of the trifecta RAC we Research Affiliates Cap Weighted Index. We introduced four years ago, the US RAC WE has beat Live, has beat the S and P by 81 basis points a year with 99.96% correlation with 95% overlap. If you only have 5% known overlap and you're adding 81 basis points, that means that the stocks that we have and they don't are beating the stocks they have and we don't by 16% per year. That's huge. So ETF Architect launched an ETF based on that index just nine weeks ago. We're already, as of Friday, 29 basis points ahead of the spider. That's three basis points a week. That is so cool. And the third leg of the trifecta is a better way to do growth. So what about growth growth indexes? We've had this stupid myth that a stock is growth or value. If it's cheap, it's value. If it's expensive, it's growth. No, if it's expensive, it's expensive. That doesn't mean it's growth. It means it better be growth or you're overpaying. But if it's expensive, the market clearly thinks there will be growth and it's already in the price. If there isn't growth, you're in trouble. Now, we've gone back historically and we've said, are there lessons we can learn from Rassie? Yes, there are. Instead of choosing companies for an index based on its market value. Why don't we choose companies based on its size? Well, if you're building a growth portfolio, why don't we choose companies for an index based on their observed growth rates? Wow, what a revelation. Choose growth stocks based on whether they're growing. Take the 25% of US stocks that have the fastest growth. How do you measure that? Let's take 3 to 5 year growth in sales, 3 to 5 year growth in cash flow, 3 to 5 year growth in R D spending. If they break out R and D spending because R and D is correlated with future growth. Got three different growth rates. Average them and take the 25% with the fastest growth. All right, now you've got a portfolio of fast growing companies. Cool. What other lessons from Rafi? Don't cap weight it. If you cap weight it, you're weighting it in proportion with what the market thinks. The growth will be weighted instead based on the dollar magnitude of the growth. If one company's had sales growth from a billion to 2 billion and another company's had sales growth from 10 billion to 20 billion, they both qualify. That's doubling your growth. Your revenues in five years is a terrific growth rate. They both qualify for the index. But one of them is 10 times as consequential in the economy. 10 times as big. Let's give it 10 times the weight. Let's wait. Choose companies based on percentage growth. Weight companies based on dollar growth. If you do that, go back over the last 30 years and ask how does this perform relative to Russell 1000 growth? 4% per annum incremental return. And oh by the way, during the dot com bubble when frothy companies with no profits were soaring, companies that had were fast growing and had profits were called GARP growth at a reasonable price. And they were outperforming a little bit but lagging way behind the frothy companies. Then the frothy companies crashed. The companies that had real growth continued to outperform. So the aftermath of the dot com bubble, when Russell growth crashes, Rafi growth continues to outperform. So cool. So we think that we've revolutionized value investing, we've revolutionized gap weighted investing, the broad market. And I think we're on the verge of revolutionizing growth investing.
- [43:26]
Podcast Co-host (Justin)
And so when you put that together, when you put the value together with the growth is what you're doing. You're excluding companies that basically don't meet either one of the criteria.
- [43:35]
Rob Arnott
Why do you want to own expensive companies with sluggish growth? In our research Paper. We went back and we asked the question, if you just take the market and break it into above average growth and below average growth and above average book to price ratio and below average book to price ratio, got four quadrants. And book to price, by the way, is a terrible measure. It's just the one that's popular in academia. So why reinvent the wheel? For purposes of research, for purposes of product, we're not going to use that. But if you take expensive, cheap, fast growing, slow growing, the four quadrants go back over the last. We took it all the way back to the late 60s. So you've got 65 years of data or excuse me, 50, 55 years of data. Over the last 55 years, cheap and fast growing performed best. Beat the market by a little over a percent percent and a half per annum. Simple cap weighting of the stocks in it. Cheap and slow growing added about a percentage. Expensive and fast growing added about a percent. The best performing was was cheap and fast growing. It was about a half a percent faster than the others and way behind. Over 2% per annum under the market per annum for 55 years was expensive and slow growing. And this is not using any forward looking expectations. This is just saying objectively, is the stock cheap or expensive relative to the market in today's valuation multiples on book value and is the company's sales or profits growing faster or slower than average? So super simplistic. Why would you want to own expensive companies that haven't demonstrated an ability to grow? What a dumb idea.
- [45:44]
Podcast Co-host (Justin)
Do you have any feel for like how big of a percentage of the universe that is? Like these expensive companies that aren't growing.
- [45:49]
Rob Arnott
Well, by definition it's 1/4, but because they're cheap, it's 1/4. That represents less than a fourth of the market value. An educated guess. I don't know the answer to your question, but an educated guess would be somewhere around 10 or 15% of the market would be excluded. So our growth. Oh, here's a fun factoid. Two of the so called Magnificent Seven don't make the cut for our growth index because their objective measures of growth are not in the top 25%.
- [46:23]
Podcast Co-host (Justin)
I'm trying to think what it would be. Tesla.
- [46:25]
Rob Arnott
Tesla qualifies, but barely.
- [46:27]
Podcast Co-host (Justin)
Any guesses, Justin?
- [46:28]
Podcast Host
I'm trying to think here. So I would think Apple.
- [46:34]
Rob Arnott
Apple qualifies, but barely.
- [46:36]
Podcast Host
Okay, you stump, you stump.
- [46:37]
Podcast Co-host (Justin)
The podcast host here, go through them.
- [46:39]
Podcast Host
I mean you got.
- [46:42]
Rob Arnott
Amazon and Alphabet. Okay, don't quite make the cut. They both have good growth rates, but they're not top quartile so they don't make it into our index. They would have a year or two ago, but not today. I think Tesla probably won't make it into the PAR index in a year. We'll see. So, all right. These are magnificent seven. They are magnificent companies. They've done, they've got visionary leadership, they've done remarkable things, they've rocked our world, they've changed our lives and they're priced for continuing to do so in the future. And yet objectively, their rates of growth over the last three to five years have slowed to a point where they're no longer in the fastest growing quint quartile of all stocks. Really interesting stuff.
- [47:31]
Podcast Host
Is the reinventing the cap weighting. Have we already talked about that or is that a different.
- [47:35]
Rob Arnott
Well, we, we alluded to it. Reinventing cap weighting rack we research affiliates cap weighted index. I'm going to grossly oversimplify. S and P is selected by a committee but most people think that it's the 500 largest market cap stocks cap weighted. That's actually not true. 400 of the S P 500 would make it into the top 500 by market cap. So it's an approximation. But let's suppose you chose the 500 largest stocks by market cap and you weight them by market cap. That's what most people think is the S P. Why would you do that? It means that if a stock has soared and its market value has come from well under the top 500 into the top 500, now you have to buy it after it soared. And if a company has tanked and fallen off the top 500, you've participated in that horrible drop and now you get out of it after it's fallen. You're buying high and selling low. People think of index index funds and cap weighted indexes as passive. They mostly are, but they trade. Call it 5% turnover roughly. So think of them as 95% passive. Just along for the ride. We don't care if the stocks are up, down or sideways. We don't care if the businesses are flourishing or floundering. Doesn't matter. We're along for the ride. Unless they flourish too little, flounder too much and get kicked out the active sleeve where it's buying and selling is wildly active. I, I like to joke that the active side of indexing is like Cathie Wood on crystal meth. Now she's sweet, she's very religious and she's conservative. So picturing her on crystal meth is A little hard, but if she ever took crystal meth, she would behave like the index committee at S and P. She'd be buying what's newly frothy just because it went up. She'd be selling what's newly hated just because it went down with no further thought going into it. Then it sword enough we got to buy it, it tanked enough we got to sell it. What is the logic in that? Why not wait until the underlying business validates the price move so a company soars? You wait until the business is among the 500 largest businesses in America. Now you add it and that means you're not necessarily. You're adding the next Nvidia or Tesla probably a handful of years after conventional cap weighting. But you're not getting drawn into buying the next Rivian companies that soar and then crash. Who wants that? Flip flops are the Achilles heel of index funds. Stocks that are kicked out of an index, over half of them were added less than 10 years before. Over a third of them were added less than five years before. So if a stock is added and kicked out in less than five years, what's the nature of the performance? On average, their ad, they outperform by 7,500 basis points in the year before they're added, and then they underperform by 7,000 basis points before they're kicked up. If you're outperforming by 75% and underperforming by 70, you're not back where you started, you're down 50%. That's awful. And then after it's kicked out, it outperforms by an average of 5% a year for the next five years. That's the essence of our work on deletions. And so basically what we have is an automated buy high, sell low discipline. If you use company size to choose what stocks to add or which stocks to drop, you're still going to be adding stocks that have outperformed. Because if a company has grown faster than the economy and is in the top 500 companies, yeah, it's probably outperformed, but it's not being bought because it's soared. It's being bought because it's grown. It's not dropped because it's cratered, it's dropped because its business share has eroded. And so what you find is our flip flops do a little bit of damage. Instead of underperforming by 7000 basis points in the years before before being added and dropped, they underperformed by 2000. That's still bad. But it's a third to a fourth as much damage. And that's why RAC we over the last four years live has beat the S&P by 81 basis points a year. And over the last 35 years in historical testing has won by 69 basis points a year. Now the early weeks of the Rouse ETF have been fortuitous. I mean 29 basis points added in nine weeks is pretty cool. But that's above average. That's larger than I would normally expect. I'd expect one to two basis points a week. We've had three basis points a week performance. Yeah.
- [53:09]
Podcast Host
And by the way, on the deletions index there is an ETF based on that as well that is being run. So for people that find that idea appealing, you can go and actually invest in that, which is pretty cool.
- [53:21]
Rob Arnott
That's exactly right. Yeah.
- [53:24]
Podcast Host
Okay, so let's just as we kind of get wrap up here, we wanted to get your perspective on international markets. I mean we've talked a little bit here that you know, I think you're a fan of the possible outperformance of emerging markets and international here as we look out over the next seven to 10 years and we think about long term returns. But when we had you on maybe at the beginning of the year, maybe end of last year, you talked about how most of your personal portfolio was and you weren't advocating this for anyone else but you. Most of it was in emerging markets. And obviously emerging markets have had a really good year this year. So just what's your overall view today on emerging markets?
- [54:09]
Rob Arnott
Well, firstly I'm a long term investor. I never invest because I think something's going to outperform next year. I invest because I think something's going to outperform over the next five to 10 years. And so I tend to be a buy and hold investor, at least by the standards of today's investors. I view emerging markets value and fundamental index Rafi in Emerging Markets as the best single major stock market investment to choose today. Rafi in emerging markets is priced at a at less than 10 times the 10 year average earnings. That's very cool. And so we have a website, Asset Allocation Interactive. If somebody call goes on Google and says Asset Allocation Interactive the first non sponsored website will take you straight to our tool. And our tool gives you forward looking return expectations for 160 different asset classes. The highest return for major markets is emerging markets value at 10% annualized return expectation. Large cap growth for the US is 1 1/2% per year for the next 10 years. 10% versus 1 1/2. I'll take the 10. Does that mean that I have high confidence that that'll be the winner in 2026? No, I think it's 6040 odds that it'll win on a one year basis. I think it's 8020 odds it'll win on a five year basis and 9010 odds that it'll win on a ten year basis. I like looking at things long term and on a 10 year horizon. I love emerging markets. Value. I love IFA value. Just plain old Europe and Japan Value stocks are cheap and within the US the spread in valuation between growth and value in the US is just about the widest in the world. The spread in valuation between small cap value and large cap growth is the widest in the world. So I don't think US large cap value is cheap. I think it's cheap relative to growth. And to the extent I want US large cap in my portfolio, I'll go with value every time. That's where we are today. So I see international markets as underutilized, underappreciated. The narrative is that American exceptionalism is real and therefore don't bother with non US Stocks. That narrative is in the price. US stocks, especially US growth stocks, are very fully priced and all Europe or Japan has to do is exceed bleak expectations and those stocks will turn out to have been bargains.
- [57:17]
Podcast Co-host (Justin)
Yep.
- [57:17]
Podcast Host
That's what I think a lot of investors fail to realize is that, you know, it's usually almost always embedded in the price. And so, you know, these things that are expensive, they're priced to perfection. And maybe the US market is kind of in one of those spots right now.
- [57:32]
Rob Arnott
I think that's exactly right. I think the US is priced for perfection. Again, I say this again and again. Don't short sell a bubble. It can last longer and go further than you can imagine. Fast way to go bust is to short sell a bubble. It doesn't mean you have to own it heavily. It doesn't mean you have to have it as your number one holding. Doesn't mean you have to own it at all actually. But to the extent that you care about how you're doing relative to the market, then use a soaring stock market or a soaring market for US growth stocks to trim your holdings to say thank you for those gains. I'm going to take some gains off the table. I'm going to start playing with house money. And if you do that, average your way into what's cheap, average your Way out of what's expensive. We all hear about averaging in. How about averaging out? Averaging out is just as powerful a discipline and is overlooked. Nobody wants to sell what's given them great joy and profit. And yet if you trim it, don't sell it, trim it. That can be a very prudent and sensible thing to do and average your way into what's unloved.
- [59:01]
Podcast Co-host (Justin)
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- [59:18]
Podcast Host
So just in closing, is there any new areas of research that you're focused on and or are there any new ideas that you're thinking of bringing? Because I mean some of these ETFs are, you know, they're, they're newer. So you're launching actual product off of your research. So is that something that you think the firm will continue to.
- [59:38]
Rob Arnott
I think we'll continue doing that. I love the fundamental growth idea. If somebody says, wow, I hear you're doing great stuff on growth. How do I invest in it? Unfortunately, there's no products available yet. There will be other areas that in my personal portfolio, I love doing long, short work. The, the, the RAC we research affiliates cap weighted index versus S and P. Like I said, it has 95% overlap. Now if over the last four years you've added 81 basis points a year with 95% overlap, that means that what we're overweighting 5% of the portfolio beats what they're overweighting 5% of the Portfolio by 20 times that, which is 1600 basis points per annum, 16% a year. But. So if you build a long short, that's a pretty nice rate of return. But you don't have to stop there. You can leverage it. Let's leverage it two to one. Now you've got 40 times the return difference. You're taking that 80 basis points and turning it into 30 plus percent. I can do that in my personal portfolio. I do that in my personal portfolio. It's very cool. Can we create that as a product? Yes, we can. Is that going to be a product that's available at some point in the coming couple of years? Maybe. We're looking into feasibility and regulatory issues. It sounds wildly reckless, 40 times longer rack we 40x short s p but it's really not. It's just the 5% leveraged up 2 to 1. And I, I've been doing that live in my personal portfolio since May, and it's been a better than average six months. So that's made about 30%, about half of that since the launch of the Rous etf. So, so I'm doing, I'm doing Rouse on a heavily leveraged basis in my personal portfolio. I eat my own cooking.
- [61:55]
Podcast Host
Well, it's, it's, it's great to have you and we kind of have this inside seat, if you will, to the research you guys are doing and maybe, maybe some future products. So it'll be great to see the developments that come out of research affiliates. Thank you, Rob.
- [62:10]
Rob Arnott
Thank you so much. This has been fun as always. Thanks.
- [62:15]
Podcast Host
Thank you for tuning in to this episode. If you found this discussion interesting and valuable, please subscribe on your favorite audio platform or on YouTube. You can also follow all the podcasts in the Excess Returns network@xsreturnspod.com if you have any feedback or questions, you can contact us@xsreturnspodmail.com no information on this podcast.
- [62:35]
Commercial Narrator
Should be construed as investment advice. Securities discussed in the podcast may be holdings of the firms of the hosts or their clients.