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[00:00:00] Rob Campbell: Hi everyone. Manar Hassan-Agha is back to discuss Mower's global equity strategy today. We start with what's behind the benchmark relative underperformance year to date. We talk through a couple of the new additions to the portfolio so far this year. And, yeah, we talk artificial intelligence (AI), and the quote that has lingered with me since: “We tend to overestimate the effect of a technology in the short run and underestimate its effect in the long run.”
[00:00:35] Disclaimer: This podcast is for informational purposes only. Information related to investment approaches or individual investments should not be construed as advice or endorsement. Any views expressed in this podcast are based upon the information available at the time and are subject to change.
[00:00:43] Rob Campbell: Manar, welcome back.
[00:00:44] Manar Hassan-Agha: Thanks Rob. Thanks for having me again. We took a little break there. I think it's good for the folk listening.
[00:00:49] Rob Campbell: It feels like we've been on a regular cadence of getting together. And on this occasion, here's where I want to start. I want to imagine that I'm a Mawer client – which isn't very difficult, by the way, because I am a client of the global equity strategy – opening my June statement and seeing that, hey, my return over the past year is up double digits. So I feel pretty happy. But then I look at the benchmark and realize that it is up considerably more.
Can we start there? Why is it that we are lagging our benchmarks in this type of environment?
[00:01:20] Manar Hassan-Agha: I think that's important. We think about that a lot. The first point, obviously, is the concentration in the index is a bit crazy. So we're underweight the Magnificent Seven. I hate to support the acronym, but we're underweight the Magnificent Seven by 10%, roughly the same for semiconductor companies and the like. Another reason is some boring is out of favour versus if you think of artificial intelligence. So we think of consumer staples and healthcare a little bit out of favour in terms of boring industries.
How we've historically created value, Rob, over the long term is our downside captures outperforms. I think over the last 10 years, its something like 85%; we only capture 85% of the downside versus our upside capture typically lags or just barely keeps up. The math is intuitive about how that creates value for clients over a long period of time. Just to exaggerate the point, if you're down 50%, you need to be up 100% to recover, but if you're down 40%, then you only need to be up 67%.
So over a long period of time, that tends to compound wealth. And honestly, Rob, just to inject humility here, we probably have some errors in our portfolio that we haven't yet realized. But we're not resting on our laurels here; we're trying to uncover those errors as quickly as possible. I think in the same breath, we likely have some winners in there that are unrealized today.
[00:02:41] Rob Campbell: I think clients know that typically in exuberant markets, our boring style, it doesn't tend to keep up as much. But I want to continue on something that you just mentioned, which are the potential errors of omission. So less about stuff that we don't own but more about what's in the global equity portfolio.
I'm wondering if there are a couple of stocks that you can touch on that perhaps haven't done as well over the past year – maybe they've been flat or down slightly and just what our updated thinking is on those securities.
[00:03:10] Manar Hassan-Agha: Yeah, absolutely. And maybe I'll do a quick aside on errors of omission because I think our perspective on that is important. We think of it as a balancing act between learning and improvement and then being careful not to learn the wrong things. When we're assessing our errors of omission, any due causes resulting, which the idea is you look at the result and you try to learn from that only, but really we think of it as a matrix of good-bad decisions and good-bad outcomes. So sometimes you can make good decisions and have bad outcomes.
When we're looking in the short term, there's a lot of statistical noise that becomes more apparent over a long period of time. Our average hold period is something like eight to 10 years, so we try to look at the track record over that period of time. In our view, it's quite a weak form of error if you can't relate it back to what you would change in your process. I'm reminded of Deming's funnel problem. So he drops a marble through a funnel onto a sheet of paper that has a target. The goal is to get the marble to stop as close to the target as possible.
He basically tells the subjects of the experiment, “Hey, the goal is to adjust the funnel so that the marbles fall more precisely onto the target.” Statistically, the optimal thing to do is to drop a lot of marbles first to get a sufficient sample size through the funnel without making any adjustments. And then find the average position where they fall, and that's the amount of adjustment you need to adjust the funnel. But the human behaviour is we adjust the funnel immediately. We drop only one marble, and we quickly adjust. And that rule of adjusting the funnel after each marble actually produces the greatest variability. So what happens is your process becomes unstable. You have these knee-jerk reactions.
[00:04:53] Rob Campbell: I can get a sense for it. You have to keep an eye on the long term. You want to weigh information in the short term a little bit more lightly. But more specifically, and I'm thinking of a position like XP, which was probably one of the portfolio's top performers last year and yet one of the bottom drivers so far this year, what's going on there?
[00:05:12] Manar Hassan-Agha: So XP, just as a quick refresher, is the number one independent broker-dealer in Brazil. They have roughly 80% of the independent financial advisors in Brazil. And we, for risk management purposes, have a smaller position size in XP due to emerging market risks. It's in Brazil. Obviously, there's a capital market cycle where equities flow and have outflows. But what's happening there is that today, the Brazilian central bank rate is something like 10.5%. If that's your opportunity cost, if you think about, “Do I invest in equities, for example, or do I invest in a daily liquid instrument?” then that's a pretty high bar, right? I can earn 10.5%.
Now, the key in our mind is XP is still seeing net inflows. They've slowed, but they're still seeing net positive inflows into their platform. The second thing is they're plugging other products into their distribution network. When you have something like 14,000 independent financial advisors, you start having this network effect, like insurance products, like credit cards. They're plugging into their network, tapping into higher net-worth clients within Brazil. If we step back, the reason to own this is while it has a small market share of a large and growing market, if we think of the oligopoly in Brazil, the top five banks still have 80% of the assets under custody within Brazil. Tapping into that, disrupting that type of market, they have identifiable competitive advantages.
When we think about the business, it has really high switching costs. If you have your assets on the platform, you have the expense and the tax impact of trying to move your account, the trust and the credibility that you build with your financial provider, and, of course, the distribution moat that they have and the breadth that they have it.
They have engaged owners who understand the value drivers of the business and have roughly 20% economic interest within the business across a group of management members.
And they’re returning excess capital to date. We think of it as having positive convexity to rate cuts as Brazil slowly goes down that path. With all of that, you get a pretty modest valuation. So something like 12 times versus 14 times with double the ROEs (returns on equity). All this is to say that we have a longer-term horizon with this, but we still manage our risk through position sizing under 2% weight.
[00:07:38] Rob Campbell: And specifically, like you said, just given some of the country risks, I know the currency is down pretty considerably relative to the U.S. dollar so far this year, too. What about another position like Robert Half, which I think we added to the portfolio around this time last year?
[00:07:53] Manar Hassan-Agha: Yeah, Robert Half. Maybe a quick refresher. It's a temporary and permanent staffing agency, and it has also the mini big-four accountant consulting business. So the KPMGs and Deloitte’s of the world. They have a mini big-four consulting business, which is sizable today, roughly 30% of operating profit.
We incremented into this from a position size perspective due to the cyclicality. If you think of staffing cycles, it can be pretty brutal. But typically, temporary staffing is a leading indicator of employment cycles. You can think of it as FIFO (first in first out). Companies tend to cut temporary labour early. And then when there is a positive cycle, they come in first. You could think of it as the leading indicator.
When we look at the business, we think it has great fundamental features. The business is asset light. It's a people business, so it doesn't require a lot of capital to grow. And as such, it has really high returns on capital through cycles. We have excellent alignment with the CEO and management team, and despite earnings being more cyclical, the free cash flow of the business is quite stable, relative to the earnings profile because in a downturn, the account receivables turn into cash. So the free-cash-flow profile is more stable. The owners of the business, the management team of the business, understand that it's quite a brutal cycle. So they have net cash on their balance sheet worth 6% of their market capitalization.
[00:09:27] Rob Campbell: It sounds like we were pretty eyes open going into this investment last year, recognizing the cyclicality. Robert Half sort of took a half position maybe at the start (a smaller position to start) and have been adding as the stock has gotten weaker, given the great long-term prospects of the business.
[00:09:45] Manar Hassan-Agha: I think if you have a longer-term horizon, you look through mid-cycle through cycle, we think that there's a modest valuation. It's kind of the old lumpy 15% versus a smooth 7% type of return profile, but we think that there might be some underappreciation of two things that they've done, which is they've improved their mix to higher skill – think more CFO/senior accountant types versus more ground level accounting. And their mini big-four consulting business is now 30% of their profit. So it's a more robust, less cyclical part of the business.
[00:10:22] Rob Campbell: Got it. Can you talk about AI with respect to Robert Half?
[00:10:23] Manar Hassan-Agha: I think there might be some concerns lingering around the staffing business, in particular, like, “Hey, this generative AI is going to replace all the accountants.” We think about it in a few ways.
Obviously, the bands of this, there's some uncertainty, but Robert Half has significant scale advantages. Particularly in their data, with more than 30 million candidates in their database. This is not resumes; this is proprietary data that they have because they're the employer of record.
That means they have your on-job performance data that you wouldn't otherwise be able to get. We think that proprietary data is likely the scarce input into these large language models that may commoditize over time. So everyone's going to have these models. The question is, “How valuable is that data that's going in?” So that proprietary data is critical.
Another thing, Rob, is you don't really want your accountant to hallucinate – although we do see some financial statements from time to time where we think the accountant might be hallucinating. But that's one aspect. That's why we do our own forensic accounting as a sidebar. But the third piece I would say is that historically speaking, there's been no net reduction in the number of jobs in accounting. And that's amazing because --
[00:11:34] Rob Campbell: You're talking going back decades? As we've introduced QuickBooks and other products that help accountants, the level of staffing has stayed pretty consistent?
[00:11:43] Manar Hassan-Agha: Yes. Of course, there have been shifts. If you can't use QuickBooks, you might've lost a job. You need upscaling or up-training. If I think of those shifts, even just manual to spreadsheets and spreadsheets to software type of shifts, these are massive cumulative shifts. Generative AI today is not as big of a shift. A lot of companies have already automated a lot of parts of their accounting, but yet there's been no net reduction in the number of jobs in accounting. In context of the magnitude of the shifts in the past, it's much smaller relative to today.
Of course, Robert Half is not sleeping at the wheel. There are two parts of their AI program; they have AI-recommended clients. So better recruiter productivity, think about LinkedIn coming in, and it hasn't really disrupted their business. What's happened is it's augmented the recruiter's productivity. They use that as a database. Then better candidates; they're getting to AI-recommended talent, but obviously, there are all sorts of pitfalls you've got to be careful of when you're recommending talent that's mission critical to these small businesses.
[00:12:46] Rob Campbell: Shifting to errors of omission, maybe, but very much on the topic of AI. Zooming out, I heard in a recent risk management meeting, somebody say that there are kind of two risks right now. One is that we're in this giant AI bubble. And the other risk is that we're not. That this is legitimate and sustainable, and Nvidia is the most important stock in the world really at the moment.
Where do you fall on this? Where does the global equity team fall? Do you have a view? Presumably, given the way the portfolio is postured, there's a lean potentially a little bit one way, but I'm just curious to get your bigger picture thoughts on that.
[00:13:19] Manar Hassan-Agha: I think that the technology's impact potential is clear. I don't think that's disputed. The more central questions that we ponder today that we're curious about are, “What's the return on this investment? On $200 billion of capex being spent by a lot of hyperscalers and Meta?” Or implied data center AI, I saw Sequoia could say upwards of $300 billion. And then the second point is as investors, “What are the embedded expectations in the current prices relative to the potential for returns?”
So we come back to Moore's law, which is that we tend to overestimate the effects of new technology in the short term but perhaps underestimate them in the long run. We see some dangers of the supply side wave today. This “if they build it, they will come” type of mentality because a lot of the demand side today is mostly characterized as experimental or is quite anecdotal. Klarna comes up and some apocryphal story about cutting a bunch of customer service. Even BP Oil is talking about cutting 70% of third-party coders, but we don't see that in the demand generation in terms of real revenue generation for, ultimately, which is where the rubber meets the road. And keep in mind that ChatGPT has been out for 20 months or more. So, it's not that new, so to speak.
[00:14:36] Rob Campbell: Can I interrupt you for a second just to make sure that I understand? On Moore's law, are you suggesting that there's too much excitement at the moment, less with respect to the long-term implications of the technology but more on how quickly individuals and companies can actually deploy them? Meaning – hey, we may think that this podcast could be done by AI in the future. We've got your likeness, your image, we've got mine. Certainly, we've been on the podcast enough times; there are enough samples of our voices. Could we just plug and play? So excitement around that potential, but realistically, it's going to take a much longer time before we actually deploy that. Is that what you're saying in terms of this delay in terms of timing?
[00:15:20] Manar Hassan-Agha: I think you're spot on. I don't know if we can replace you though, my friend. I think out of the two of us, you're the hardest to replace.
Look at Accenture. Accenture has great visibility into companies and what they're doing. They say only 5-10% of companies are even ready to use generative AI. They have the data and the infrastructure ready to plug in these and be useful and productive to their environment. I read something that the Census Bureau is suggesting only 5% of businesses have even used AI in the past two weeks and that jives with that eccentric idea.
Now a lot of consumers are using it – apparently something like 75% of global knowledge workers, Microsoft and LinkedIn had a stat around that. But a lot of it is in a free capacity. I think about Amazon Prime’s unlimited two-day shipping. Back in 2005 when it first launched, it was $79 a year, so that's less than $7 a month. Today, I struggle to even sometimes fork out $15 for Netflix and think of all the value it's produced for me or the value I get out of it. I think it's just the early days of seeing and that there may be a mismatch between the timing of the investment – the scale and magnitude of that – and the returns.
I think that mismatch can create opportunities down the line for us, where we're headed for some type of a trough of disillusionment or something to that effect. The asymmetry today, in our mind, is still that there's a lot of uncertainty around this, particularly with respect to what's embedded in the prices of stocks. The asymmetry is while still identifying losers versus winners in a longer-term perspective. Just one more stat for you, Rob. The CEO of Microsoft, Satya Nadella, said they “could justify the spend by getting gross domestic product (GDP) growth to double, effectively from 1-2% to 3-4%.” Now it's early days, but we don't see those productivity gains today. Economic data is actually showing it's slowing down. So there is some mismatch between the scale and timing of the investment and the potential returns.
[00:17:25] Rob Campbell: Okay, and valuation being the great equalizer in all that. I want to talk about some other bigger-picture themes that I've heard or read and questions that we've gotten from clients that are more regional in nature.
There's been a lot of excitement around corporate governance improvements in Japan. And the U.S. is a tremendous place to invest. I know the global equity strategy has had longstanding underweights to both of those markets. I suppose my question is about those two markets and how we're seeing opportunities there, but it's more just how process-wise we think about or incorporate some of these big-picture themes, either with respect to idea generation or in terms of the portfolio construction.
[00:18:10] Manar Hassan-Agha: First of all, we think that the lines are blurred, particularly in a more global world. To give you an example, we own Publicis; it's French headquartered, but roughly 70% of its profit is in the U.S. So that is really more of a U.S. risk exposure type of company. Or from a sector perspective, we own Wolters Kluwer, which is listed as an industrial, but if I told you it provides data and software for professionals like accountants or lawyers, I'm not so sure we would both characterize that as industrial.
So some of these lines are blurred or some of them are distorted, but we don't typically think of themes as chasing them. We think of mispricing for our time horizon and our investment process at a security level. Part of it is that chasing a theme is very difficult. We often think about the billiard ball mental model, which is one of the hardest shots is to hit a ball that hits a ball that hits a ball to go into the pocket.
You have to be right on the theme, then right on the securities that win in that theme, then not overpay relative to the expectations already priced into the theme to get the ball into the pocket. That's just not a one-foot order for us. Being right on the theme sometimes is not as easy as you think, particularly relative to the expectations priced into the theme.
We also think about this mental model of narrative versus numbers. So we hear about the Japan narrative about improving capital allocation, and there's some inductive evidence of that in higher payouts, but we own a Japanese company, the number two telecom operator in Japan, KDDI, and they acquired a convenience store. And we've joked before in the past, not sure I want to get my egg sandwich with my mobile data package. KDDI has historically always had pretty high payouts, at least in the last five years. And so there is some narrative violations, so to speak.
So you can't go across the board and paint a broad picture. You have to get to the security level, which is where we look at it. The last thing I'll say on that is we typically do capture themes in our assessment of skew of how the distribution of outcomes can look. For example, Satya Nadella had said in 2020, that 5% of GDP is spent on technology and that it would double to 10% by the end of the decade. It seems logical. Obviously, COVID has accelerated some of that. If you have durable competitive advantages or right to win with a good management team that won't squander that opportunity, then we would say, “Hey, that's positively skewed.”
We had owned Microsoft in part because of the positive skew and its exposure to that fast-growing market and its ability to win in that market. So we would consider those themes in that skew aspect.
[00:20:54] Rob Campbell: This feels like a weird question, given that markets are pretty much at all-time highs, but what's got you most excited looking forward, either about the portfolio, the team, the market environment? What should clients feel really good about at the moment?
[00:21:08] Manar Hassan-Agha: I'm reminded of what Warren Buffett once said, that you should sell all your IQ points above 120 because they're useless. You don't need IQ points above 120. I think the key is temperament but not intelligence. And when I say temperament, I mean, manage the highs and the lows.
So you're asking me what has me encouraged? We try to manage the highs and lows, play the plan, and follow our process, and manage that with the inherent contradiction, which is we need to continuously improve and not be complacent. One thing that has me encouraged is that our temperament is really good, Rob. We're managing the highs and the lows on the team very well. The second thing that has me encouraged is the portfolio appears statistically advantaged. If I use what I call dumb numbers – because we obviously do discounted cashflow and other methods – but on multiples, we have lower or slightly lower valuations and higher returns on capital, better cash back as a shareholder in terms of share buybacks and dividend yield if you combine the two. So that's in the statistics as a portfolio relative to that, but in the intangibles are also important.
We think we have a better alignment, and you can see that as a proxy, we have two times the insider ownership as the benchmark and lower economic sensitivity from an intangible standpoint. We do portfolio reviews so a monkey can't just point at the portfolio and say, “But we think our judgment is reasonable in those two aspects.”
The last thing is I'm encouraged by the rocks we're turning over here. I think the concentration creates more opportunity underneath the hood. Minus seven is 493 just in the S&P 500, but we're a global equity universe. So typically we're quite index agnostic, but underneath the hood, we’re finding a lot of high-quality companies that could be mispriced because the concentration is sucking the air out of the room. And so that creates opportunity that sets up for the next five or 10 years.
[00:23:03] Rob Campbell: Very good. Well Manar, I hope listeners appreciate your perspective. I hope you have a great rest of your summer, and we're probably due to come back together sometime in the fall.
[00:23:13] Manar Hassan-Agha: Sounds good. It'd be my pleasure.
[00:23:16] Rob Campbell: Hi everyone. Rob here again. To subscribe to the Art of Boring Podcast, go to mawer.com. That's M A W E R dot com forward slash podcast or wherever you download your podcasts. If you enjoyed this episode, please leave a review on iTunes, which will help more people discover the “be boring, make money” philosophy. Thanks for listening.
