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The Biggest AI Investment Mistakes Investors Could Make · Merryn Talks Money

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Speaker 1: Bloomberg Audio Studios, Podcasts, Radio News.
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Speaker 2: Welcome to Marin Talks Money. In the podcast in which
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Speaker 2: people who know the markets explain the markets. I am
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Speaker 2: Maren Somerset Web and this week I am speaking with
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Speaker 2: Sarah Catterer. Sarah is the CEO of Causeway Capital Management
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Speaker 2: affirm and she co founded in two thousand and one.
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Speaker 2: Today we speak about how AI is going to impact
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Speaker 2: and is impacting the fund management industry. We talk about
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Speaker 2: bargains in the UK and whether anyone is ever going
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Speaker 2: to pick them up, what's going on in biotech and pharma,
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Speaker 2: and why you may need more medical devices than you think. Sarah,
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Speaker 2: Welcome to Marin Talks Money.
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Speaker 3: Thank you for inviting me right now. Why don't we start?
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Speaker 2: Can I just ask you to tell me what it
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Speaker 2: is the Causeway actually does. You've been on the podcast before.
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Speaker 2: We've got piles and you listen, it'll rundown of what
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Speaker 2: is your business actually do.
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Speaker 3: Cosway is a fund manager. We manage approximately eighty billion
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Speaker 3: dollars of client assets and our clients are largely institutional
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Speaker 3: and our business is global equity. So we have both
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Speaker 3: fundamental research and quantitative research, and we have strategies that
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Speaker 3: deploy primarily fundamental with quantitative risk control and then primarily
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Speaker 3: quantitative with fundamental risk control. So that's what distinguishes us.
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Speaker 3: It's the it's the convergence of both fundamental quant.
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Speaker 2: Yeah, the combination of the two, which is not something
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Speaker 2: you find that often. Okay, So following directly on from that,
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Speaker 2: I wanted to ask you about AI because I know
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Speaker 2: you've been thinking about a lot. I know you've been
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Speaker 2: talking about it, but the key question is how are
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Speaker 2: you using it in your own business. You know, hearing
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Speaker 2: a lot about the businesses that are being disrupted by
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Speaker 2: AI and how they're being disrupted, and I'm beginning to
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Speaker 2: hear a lot from people saying, well, what do we
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Speaker 2: need fund managers for because AI can do this?
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Speaker 3: Yes, if only I know. Well, I believe that the
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Speaker 3: initial applications of AI for us at Causeway has been
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Speaker 3: that we've had a similar experience to other enterprises and
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Speaker 3: that we've got tremendous efficiency gains from coding so that
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Speaker 3: our software engineers could do so much more in the
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Speaker 3: same amount of time. And I've noticed this based on
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Speaker 3: our head of investment, technology has been able to do
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Speaker 3: much more for our quant effort and the people who
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Speaker 3: work for him that the quant software infrastructure has become
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Speaker 3: much more developed more quickly. That means that our quant
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Speaker 3: researchers can test more ideas more and do so not
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Speaker 3: just more quickly with more accuracy. The head of our
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Speaker 3: digital services just our whole it effort. He's been able
2:54
Speaker 3: to help us produce tax optimizer. He did in about
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Speaker 3: two weeks and normally would have taken months. This was all,
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Speaker 3: I guess in part. Vibe coded using AI models to
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Speaker 3: accelerate the software development. But the output has been really good,
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Speaker 3: and the interaction with our team to make sure that
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Speaker 3: it does what it's supposed to do for our mutual
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Speaker 3: funds has been great. But I'm going to just step
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Speaker 3: back and say that from a coding perspective fantastic. From
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Speaker 3: an investment perspective, the answer is mixed, and it's that
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Speaker 3: AI has been made us, each of us as research
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Speaker 3: analysts able to read everything. We have an assistant now
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Speaker 3: our AI agents who read everything, every company transcript, earning transcript,
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Speaker 3: every government agency filing, every every trade journal, every bit
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Speaker 3: of news.
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Speaker 2: Every actually the annual report. Someone's reading the report.
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Speaker 3: Finally, it reads them all it can do all of that,
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Speaker 3: but what it can't do is make decisions with the information.
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Speaker 3: I don't know how AI will replicate the fundamental portfolio
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Speaker 3: manager who relies on his or her experience, has a
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Speaker 3: level of intuition that's probably thirty to forty percent of
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Speaker 3: the investment decision comes from something that you can't even quantify.
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Speaker 3: It's this instinct honed after decades of doing this, and
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Speaker 3: from a quanm perspective, with AI, the ability to find
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Speaker 3: signals that aren't actually explainable to clients as quite a temptation.
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Speaker 3: We'd be really careful not to go and use the tool,
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Speaker 3: i'd say ineffectively. So in short, AI is an accelerant
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Speaker 3: to productivity improvement, but it hasn't yet developed where it
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Speaker 3: can replace that human judgment. And I think that's true
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Speaker 3: across many of the companies that we research. They have
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Speaker 3: some of the similar experiences. So it doesn't confine to finding.
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Speaker 2: When we're talking about it reading everything, every research report,
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Speaker 2: every every company announcement, every everything, and that'll be done
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Speaker 2: and summarized and presumably produced for enos. That's I mean,
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Speaker 2: if you're looking at thousands of companies, which I know
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Speaker 2: you are, that's a massive time saving. But back to
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Speaker 2: the intuition bit. It is the reading of those reports,
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Speaker 2: the reading of the company announcements, followed by the reading
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Speaker 2: of the transcripts of earning calls, et cetera, et cetera,
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Speaker 2: where a good analysts might pick up the bits and
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Speaker 2: bobs and make the connections that create the intuition. So
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Speaker 2: without the without the hard graft bit, yes, can you
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Speaker 2: have the bay.
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Speaker 3: I can make some connections. You can find in the
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Speaker 3: footnotes where there might be counting anomalies. What it can't
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Speaker 3: do is what we're doing. It can't have a meeting
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Speaker 3: with management and observe the body language. You can't say,
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Speaker 3: you know, this doesn't feel right. I don't even know
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Speaker 3: how to put it into words. But I think they're
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Speaker 3: becoming the measure a little more caution, and I'm going
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Speaker 3: to take that back and assimilate that information. We don't
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Speaker 3: record meetings we I think management would find that a
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Speaker 3: little off putting and probably we wouldn't get any meetings.
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Speaker 3: But we're taking notes. But what we're it's what we're
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Speaker 3: hearing and the way we're observing how the message is
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Speaker 3: being delivered. That's so incredibly important. And this is not.
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Speaker 3: Someday when robots are doing the job and it's all visual,
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Speaker 3: I think the other side of the table will be
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Speaker 3: a robot too. It's going to be a pretty grim world.
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Speaker 2: How And I don't normally get into young people early on.
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Speaker 2: We normally save that for the end. But the way
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Speaker 2: you're talking about the fund management business now the fundamental
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Speaker 2: part of it. Yes, what is the young person who
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Speaker 2: wants to be in fund management these days do because
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Speaker 2: all that grunt work that was the training ground.
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Speaker 3: Yeah, yes, the grunt work initially is probably a good idea.
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Speaker 3: We encourage analysts to do everything from scratch to understand
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Speaker 3: what the meaning is of all these documents, where where
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Speaker 3: to go? When you in a prompt, one has to
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Speaker 3: ask the AI to search certain areas, or we have
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Speaker 3: agent builders that link into systems. It links into databases
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Speaker 3: and you have to know which database is to plumb.
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Speaker 3: But once an analysis has done this a few times,
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Speaker 3: they don't necessarily want to do the gruntwork because it
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Speaker 3: displaces in a zero sum day any something more higher
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Speaker 3: level thinking oriented. So I'm okay with the AI doing
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Speaker 3: the grunt work. It's just that if people stop thinking,
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Speaker 3: that's when we're in trouble. It's it's using that time
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Speaker 3: freedom where you're not entering the entering in the quarter's
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Speaker 3: earnings into your spreadsheet, but the AI is doing it
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Speaker 3: your clawed ad in or whatever the tool is. What
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Speaker 3: how else is the analyst using that freedom time? Is
8:01
Speaker 3: he or she thinking about more about the assumptions, really
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Speaker 3: testing the model, going back to the notes and thinking
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Speaker 3: again about where they might have been wrong, taking a
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Speaker 3: step back and thinking more about structural change and how
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Speaker 3: this company what come out of left field being one's
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Speaker 3: own devil's advocate, and the AI can help with that too, interestingly,
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Speaker 3: But that's the higher level thinking that we want and
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Speaker 3: we are promoting.
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Speaker 2: Okay, I'm convinced we still need you. Thanks. When you
8:32
Speaker 2: look at how working in your own company, and then
8:35
Speaker 2: you look at the businesses in which you invest, what
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Speaker 2: are you looking for in the companies you're investing in?
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Speaker 3: Well, I'm glad you asked, because we for every sector globally,
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Speaker 3: have done a deep dive into how we believe they
8:47
Speaker 3: will be impacted by AI. This is quite an endeavor.
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Speaker 3: We did this fundamentally in our quant colleagues observed the
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Speaker 3: process and the output. But what we found is for
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Speaker 3: many there are some structural changes that are going to
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Speaker 3: be quite significant, and then others there's a lot of upside.
9:03
Speaker 3: Let's go to healthcare to start. We have a number
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Speaker 3: of pharmaceutical companies in the portfolio and now we're adding
9:09
Speaker 3: more medical technology because they've been left out in the
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Speaker 3: cold in this huge AI driven rally. But their ability
9:17
Speaker 3: to innovate, their ability to in the case of pharmaceuticals,
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Speaker 3: discovered new molecules advance them through the clinical trial process
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Speaker 3: more quickly, efficiency, lower cost is that could be given
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Speaker 3: that patent lifes remain the same. That means more years
9:35
Speaker 3: out in the marketplace and less in development. That's a
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Speaker 3: profit booster. It's more hard pressed to see how there'll
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Speaker 3: be some sort of mysterious AI entity that will develop drugs.
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Speaker 3: Pharmaceutical business is very laborious and involves a lot of
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Speaker 3: interaction with the health authorities and clinical trials are carefully
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Speaker 3: scripted and then being able to target patients with AI
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Speaker 3: in advance of a doing trials so they are they
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Speaker 3: are the right individuals for that particular drug. That's another
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Speaker 3: way to accelerate the process and get output that can
10:14
Speaker 3: be get that drug into the market more quickly. So
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Speaker 3: for healthcare, we think this is going to be fantastic.
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Speaker 3: Healthcare companies they gather lots and lots of data and
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Speaker 3: their ability to use it in ways they never could
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Speaker 3: before with AI is not that dissimilar from other industries.
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Speaker 3: It's just they have so much intellectual property and their
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Speaker 3: ability to innovate now is improved. And innovation equals pricing power,
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Speaker 3: and pricing power is margin, and margin is profitability, and
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Speaker 3: profitability leads to cash flow, and cash flow gets returned
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Speaker 3: to shareholders.
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Speaker 2: Okay, that makes sense. How does that then interact? I
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Speaker 2: mean one of the one of things about healthcare sector
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Speaker 2: is how regulated. It hugely regulated across the board, regulated
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Speaker 2: in different ways in every country, but the layers of
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Speaker 2: regulation massive.
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Speaker 4: Is that a barrier, It's part of the moat, and
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Speaker 4: regulation and compliance and on the need for audible outcomes
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Speaker 4: are one of the reasons why some industries they will
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Speaker 4: they just won't have this sort of AI competition.
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Speaker 3: The market might be inferring they're going to incur. So
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Speaker 3: a mote is a plus and a minus. A mote
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Speaker 3: can protect the business from competition, but it can also
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Speaker 3: mean that there will be it conhibit growth. You need competition, yes,
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Speaker 3: yes you do. But the working their way for the
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Speaker 3: regulatory maze is what healthcare companies do very well, and
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Speaker 3: the large ones have whole teams for this, and the
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Speaker 3: teams may be able to harness AI to be more
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Speaker 3: efficient doing that, which could be also a cost savings
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Speaker 3: as well as time saving.
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Speaker 2: Interesting, and we've all talked on this podcast about how
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Speaker 2: big companies love regulation because nothing, nothing holds competition back
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Speaker 2: more and a good bit of regulation. And one of
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Speaker 2: the thought was about AI was that it might be
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Speaker 2: one way for new entrance to circumvent We'll find easier
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Speaker 2: ways to deal with large parts of regulation. But it
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Speaker 2: sounds like your case is that that is not.
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Speaker 3: Going to happen. It depends in something that gets put
12:18
Speaker 3: into the human body. The regulations there for a reason. Yeah. Yeah,
12:23
Speaker 3: it's a little different. Say financial services, okay, that necessarily
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Speaker 3: got to create a health outcome.
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Speaker 2: Okay, So what other sectors will have a regulatory remote
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Speaker 2: that will limit the use of AI elsewhere?
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Speaker 3: Well, iound I've been talking about software as a service.
12:42
Speaker 3: This sounds a little silly, but it's tangential. The SaaS
12:46
Speaker 3: companies have all sold off this idea that you're a
12:49
Speaker 3: software business, you had a seventy plus percent gross margin
12:53
Speaker 3: or higher. Now your business is losing its mode and
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Speaker 3: the software will be vibe coded. Anybody can now code,
13:01
Speaker 3: but code isn't the mote. And these software companies that
13:05
Speaker 3: provide like SAP or Oracle very comprehensive for Fortune for
13:11
Speaker 3: five hundred global companies, and SAP in particular this mission
13:14
Speaker 3: critical software where they're dealing with systems of ledger in
13:19
Speaker 3: businesses that are heavily regulated. That means that data is crucial.
13:24
Speaker 3: There can't be errors in the outcome. So software needs
13:28
Speaker 3: to be deterministic. Yet generative AI is non deterministic. We
13:34
Speaker 3: can be a useful tool for users in the enterprise
13:37
Speaker 3: to get access to their data and see it in
13:40
Speaker 3: different ways. But it can't run the business. It can't
13:44
Speaker 3: run HR, can't run account it can't run supply.
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Speaker 2: Chain, can't run relations.
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Speaker 3: Yes, so I think about that as the market has
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Speaker 3: just decided these companies are all to be incurring great competition,
13:59
Speaker 3: and we would disagree. It's the it's regulation and the
14:04
Speaker 3: need for the businesses out everything they do to be
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Speaker 3: fully audible and transparent, auditable that that make it will
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Speaker 3: make it quite hard for new AI native AI startups
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Speaker 3: to undermine them.
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Speaker 2: Okay, so you quite heavily invested in the likes of SAPA.
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Speaker 3: We are. We are fundamentally the good management, incredibly sticky
14:29
Speaker 3: business and all that migration to cloud that's coming up,
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Speaker 3: that's one of the absolute So what we know, there's
14:36
Speaker 3: a lot we don't know. What we do know is
14:38
Speaker 3: that for enterprises to take advantage of AI, they need
14:41
Speaker 3: to move their data to the cloud, they need to
14:44
Speaker 3: have it accessible for the AI, and they need to
14:46
Speaker 3: be able to access that tremendous compute on an as
14:49
Speaker 3: needed basis.
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Speaker 2: And are you on the other side of this, are
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Speaker 2: you and any of the hyperscalars that they don't fit
14:55
Speaker 2: into your your fundamental matrix.
14:58
Speaker 3: Some of them do, some of them do. For example,
15:02
Speaker 3: the two great digital advertising leviathans, Meta and Alphabet generate
15:08
Speaker 3: enough free cash flow to where they can fund their
15:12
Speaker 3: foundational model ambitions and so they can fund their own
15:16
Speaker 3: cap X, which is very different from some of these
15:20
Speaker 3: massive new AI companies where it's all about finding more
15:26
Speaker 3: investors who believe in the dream.
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Speaker 2: They're going to be voyant with the opena ipo.
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Speaker 3: I cannot say.
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Speaker 2: I'm kind of guessing where else are you finding value
15:38
Speaker 2: in the market?
15:39
Speaker 3: Well, I did mention in passing medical technology. I just
15:43
Speaker 3: think it's fascinating that you could find companies like Boston
15:46
Speaker 3: Scientific and heart valves and very complex, important cardiovascular devices
15:53
Speaker 3: that you cannot get anywhere else. They used to trade
15:56
Speaker 3: twenty five or thirty times earnings and now they're multiples.
15:59
Speaker 3: Are half that. Uh, Companies like Striker or zimmer BioMed.
16:05
Speaker 3: They're fantastic medical devices as long as human bodies break
16:12
Speaker 3: down are going to be needed. And the very research
16:17
Speaker 3: intensive business. And to the degree they keep innovating and
16:22
Speaker 3: they're not in commodity products, they should do quite well.
16:26
Speaker 3: Part of what's weight on them has been concerns about
16:30
Speaker 3: the g LP one trends and consumer and individuals will
16:34
Speaker 3: no longer need new body parts, and we think that's unlikely.
16:40
Speaker 3: In fact, the longer they live, the more part replacements
16:44
Speaker 3: they'll need.
16:45
Speaker 2: Okay, so people will get thin, they'll still need the
16:48
Speaker 2: replacement polsitives. I quite need them until later.
16:50
Speaker 3: Yes, and they won't.
16:51
Speaker 2: They won't.
16:52
Speaker 3: They won't all get thin, sadly, wun't they? No, Some
16:57
Speaker 3: people will neither want an injection or where they wanted
17:00
Speaker 3: they will take a pill, they won't, they won't do it,
17:03
Speaker 3: and compliance will well, as always with drugs, they're not necessary.
17:08
Speaker 3: People aren't necessarily willing to comply.
17:10
Speaker 2: Sure, it has been fascinating seeing the obesity rate in
17:13
Speaker 2: the US drop. It has for the first time.
17:15
Speaker 3: Yes, it has change, and that should lead to better
17:20
Speaker 3: healthcare outcomes and lower cost healthcare.
17:25
Speaker 2: Two new hips each whenevery one's ninety, yes one at sixty,
17:29
Speaker 2: I'll take two, please, and a couple of knees. Or
17:56
Speaker 2: when I look at your at your your main vehicles
17:59
Speaker 2: ugly global, global, international, two different words for it. But
18:04
Speaker 2: you also have some emergen markets exposure. The Global fundkind
18:07
Speaker 2: of twenty percent in emerging markets, and there's also one
18:10
Speaker 2: Emerging Markets fund, right what's interesting there, And we've talked
18:13
Speaker 2: about this quite a lot recently about how the difficulty
18:15
Speaker 2: of emerging markets being now so defined by career in
18:18
Speaker 2: Taiwan and that market concentration making a nonsense of the
18:21
Speaker 2: idea that you can get diversified exposure within index has
18:24
Speaker 2: been one of the things we've been I'm afraid going
18:26
Speaker 2: on about for rather too long. But then the question
18:29
Speaker 2: is if you're not going to have index index style
18:32
Speaker 2: exposure to those two countries. Of course, to China, what
18:35
Speaker 2: are you going to have?
18:36
Speaker 3: Well, I would argue vociferously against indexing emerging markets, and
18:41
Speaker 3: I don't just give recent examples. Maybe twenty twenty two
18:44
Speaker 3: isn't that recent, but Russia, like, why would you even
18:47
Speaker 3: wanted an index weight in that market? We were underweight
18:52
Speaker 3: and very underweight, and that was extremely helpful. Sometimes emerging
18:55
Speaker 3: markets go to zero, and that one did. That's why
19:01
Speaker 3: they're emerging. They have much higher levels of risk because
19:04
Speaker 3: they're growth markets, and they interestingly, they're not all demographically
19:10
Speaker 3: in that growth phase. China, we didn't. It's been the
19:15
Speaker 3: largest of the emerging markets, and now it's number three
19:17
Speaker 3: behind South Korea and Taiwan, which is also fascinating, but
19:21
Speaker 3: it's within China, and that.
19:22
Speaker 2: All three of them have shrinking populations.
19:25
Speaker 3: They do, but at least South Korea and Taiwan have
19:30
Speaker 3: semiconductor giants in memory, and Taiwan has TSMC in chip production,
19:37
Speaker 3: and there are no substitutes at present, there won't be
19:40
Speaker 3: for a couple of years. No matter how many fabs
19:43
Speaker 3: are built or semiconductor facilities, it's going to take some
19:49
Speaker 3: time for supply to catch up with the demand. If
19:52
Speaker 3: demand may sag, and there may be technological reasons why
19:57
Speaker 3: we don't, you know, memories and quite hot as hotly
20:01
Speaker 3: demand as it is now. But that's very clear, and
20:05
Speaker 3: I can see those markets of those are highly highly concentrated,
20:08
Speaker 3: and the stocks they're those big three stocks are very
20:12
Speaker 3: large in the benchmark. It's beginning to look a little
20:15
Speaker 3: bit more like the US, oddly than anywhere else. What's
20:20
Speaker 3: interesting in emerging markets. I think in China there are
20:23
Speaker 3: all kinds of companies that have been left behind. We
20:25
Speaker 3: were talking about US hyperscalers. You could have the Chinese version,
20:29
Speaker 3: effectively the operating system of China through we chatter wishin
20:34
Speaker 3: which is Tencent. They're the largest publisher of music.
20:39
Speaker 2: Video or.
20:41
Speaker 3: Video games globally, and they have a music business, they
20:43
Speaker 3: have a messaging business, they have the most amazing flywheels.
20:48
Speaker 3: So they're massively cash generative like US hyper scalers, and
20:53
Speaker 3: they're developing through HY three their own foundational models. They
20:58
Speaker 3: got they were a little behind in a but it's
21:00
Speaker 3: when you have that kind of that that sort of
21:03
Speaker 3: financial resource, their net cash, it's not too hard to
21:06
Speaker 3: catch up, and they will. They'll find a way to
21:09
Speaker 3: get AI infused throughout their consumer products, that all the
21:15
Speaker 3: social media they do, and they'll keep their customers and
21:19
Speaker 3: that what is it one point three billion monthly average users?
21:25
Speaker 3: Like they're just this doc just keeps falling and we
21:31
Speaker 3: just look at it and we wonder, why, what an
21:34
Speaker 3: amazing company. It shouldn't trade at mid teens multiples of earnings.
21:38
Speaker 3: It should be much And part of this is just China.
21:41
Speaker 3: No one's interested right now. It's so there's this love
21:44
Speaker 3: hate relationship with China. Only if three or four years
21:46
Speaker 3: ago it was uninvestible, that's probably the time we all
21:50
Speaker 3: should have bought a lot of it. But now all
21:52
Speaker 3: eyes are in one area and not there. And especially
21:57
Speaker 3: for these Chinese companies that aren't necessarily at the considered
22:04
Speaker 3: at the absolute forefront of AI, they've been discarded. And
22:08
Speaker 3: this is where taking a two year view is really
22:11
Speaker 3: useful as opposed to just thinking out the next three
22:13
Speaker 3: to six months, because it gives us a chance to
22:16
Speaker 3: accumulate what maybe one of I think the I think
22:19
Speaker 3: my colleagues would agree with me, probably one of the
22:21
Speaker 3: best companies in China overall for a very attractive valuation.
22:27
Speaker 2: Yeah, and the lack of interest in it is just fashioned,
22:30
Speaker 2: just people coming slowly back to being in the Chinese market. Again,
22:33
Speaker 2: the fact that it's impossible to draw your eyes away
22:35
Speaker 2: from the stars and the etector in the US. And
22:39
Speaker 2: as they said, these few as you market.
22:41
Speaker 3: Yes, I think so. I think so that there's a
22:45
Speaker 3: certain amount of short term ism baked into that. It
22:48
Speaker 3: may or I mean, we could be we cause we
22:50
Speaker 3: could be wrong and ten Cent doesn't develop out their
22:53
Speaker 3: AI features fast enough and and part of their business
22:57
Speaker 3: gets competed away. But it's very unlikely that's going to happen,
23:02
Speaker 3: given their track record, given what they've already built, and
23:05
Speaker 3: given the marketplaces where they dominate. They you know, they've
23:09
Speaker 3: got infrastructure as a service, their platforms a service, and
23:13
Speaker 3: software as a service, and they will they have this
23:16
Speaker 3: cloud business and that gives them a lot of compute
23:19
Speaker 3: and a lot of flexibility. And again that balance sheet,
23:23
Speaker 3: it's like they have all the raw materials and they
23:26
Speaker 3: have the history of doing it, and that usually convinces
23:29
Speaker 3: us as fundamental investors. And given how low the valuation is,
23:34
Speaker 3: this isn't the risk is very modest. Versus I mean
23:38
Speaker 3: you mentioned semiconductors we started. Given where they trade, they're
23:44
Speaker 3: very risky right now.
23:46
Speaker 2: Well, because they're cychnical businesses. Right, this is exactly the
23:49
Speaker 2: wrong point of the cycle historically, if you were looking
23:52
Speaker 2: at this is a normal cycle, exactly the.
23:54
Speaker 3: Wrong cycle exactly. You don't believe in a cycle if
23:57
Speaker 3: you think that they the demand goes on prepared actually
24:00
Speaker 3: like this, and the supply will be will not meet
24:03
Speaker 3: demand indefinitely. But that's I think physically impossible.
24:08
Speaker 2: Yeah, normally at this point you would stop to see
24:10
Speaker 2: a shot rise and supply and the fool of and
24:12
Speaker 2: demand at the same time.
24:13
Speaker 3: Or all the market needs to perceive is that their
24:18
Speaker 3: supply is planned. That's all. That's all it'll take to
24:21
Speaker 3: tip them back the other direction.
24:23
Speaker 2: Well, the always us to say, I remember someone telling
24:25
Speaker 2: me when I was a very very junior broker that
24:28
Speaker 2: the chip makers you seld them when they were very cheap,
24:31
Speaker 2: and you bought them when they were very expensive, because
24:33
Speaker 2: that's how the cycle looks.
24:35
Speaker 3: Yes, yes, exactly. The multiples tend to be low. This
24:39
Speaker 3: is where people often get confused. They think very low
24:42
Speaker 3: multiple stocks are value stocks, so they're cheap, but it
24:46
Speaker 3: could be. You have to look carefully. If they're in
24:48
Speaker 3: cyclical industries, their earnings are at a peak, and conversely,
24:52
Speaker 3: when their earnings are at a trough, their multiples.
24:55
Speaker 2: Are look very expensive. But that's exactly the time is
24:58
Speaker 2: their earning start to go up gun.
25:00
Speaker 3: And it's really helpful from an investor perspective to be
25:04
Speaker 3: in a cyclical business because at least you have history
25:07
Speaker 3: as a guide. If you're in a business that has
25:11
Speaker 3: no history or everything has changed, you can't use the
25:15
Speaker 3: past as a predictor of the future. And in my view,
25:19
Speaker 3: it makes cyclical investing, assuming there isn't some massive change
25:23
Speaker 3: in the business, lower risks than appears at first glance.
25:28
Speaker 2: Let's go back to the US. We've talked briefly about
25:31
Speaker 2: the intense concentration in the US indices, and we've talked
25:35
Speaker 2: a little bit about biotech and pharma, other other sectors
25:38
Speaker 2: in the US that you are finding very interesting at
25:39
Speaker 2: the moment that outside these hugely expensive tech companies and
25:43
Speaker 2: outside what we've READI discussed that.
25:46
Speaker 3: Well, because tech is so massive. Technology communications services and
25:50
Speaker 3: another stock that's come out of our research is in
25:55
Speaker 3: the IT services area, and this is a major contract
26:00
Speaker 3: of the US government Booze Allen and again in the
26:03
Speaker 3: category if we didn't used to be able to buy
26:05
Speaker 3: these stocks because the growth rates were high and the
26:08
Speaker 3: multiples were even higher. The concern about reduced use government spending,
26:15
Speaker 3: especially in civil but seventy three to seventy five percent
26:19
Speaker 3: of booz Allen's revenues come from military defense. So the
26:24
Speaker 3: US government needs to modernize its systems and it needs better,
26:30
Speaker 3: much better cybersecurity. This was all common sense, Like nobody's
26:35
Speaker 3: ever said to me, Oh, that's not true.
26:37
Speaker 2: Yes, in any cybersecurity they'll be fine.
26:39
Speaker 3: Exactly. So, this is an eighty five year old company
26:42
Speaker 3: and ninety percent of the revenues come from US agencies.
26:47
Speaker 3: They've they've had somewhat of a partially rocky relationship, and
26:51
Speaker 3: yet nobody else can do what they do. They they're
26:54
Speaker 3: partly they collaborate as well as compete with Palenteer can
27:00
Speaker 3: take all the business. There's you know, there's military cryptography needed,
27:05
Speaker 3: there's I mean, there's just so many different areas where
27:08
Speaker 3: Booze has has that dominant expertise, and it's a it's
27:13
Speaker 3: just eight billion dollar market cap now and it trades
27:16
Speaker 3: at high single digit earnings. You can then market has
27:21
Speaker 3: said it's going out of business or it slowly surely
27:24
Speaker 3: will melts like an ice cube in the sun, and
27:27
Speaker 3: we disagree. And valuations, yeah, well, evaluation they're very attractive,
27:32
Speaker 3: probably should be at least fifteen times next year's earnings.
27:35
Speaker 3: And then you get a three point six percent dividend yield,
27:38
Speaker 3: which is something a lot of these tech stocks don't
27:41
Speaker 3: give you much in dividend. They may do share of
27:44
Speaker 3: purchases like SAP does big buybacks. I think they've been
27:48
Speaker 3: out something like ten billion euros over the next couple
27:51
Speaker 3: of years.
27:52
Speaker 2: It's extraordinary, isn't it. We've talked about this quite a
27:55
Speaker 2: few times recently as well, the way that ever the
27:56
Speaker 2: last decados the stock market has become at an extra
28:00
Speaker 2: machine for investors, where you take out your dividends, you
28:02
Speaker 2: take out your special dividends, you get your money back
28:04
Speaker 2: and buy backs, et cetera. Whereas originally the whole idea
28:07
Speaker 2: was that individuals gave money to companies, then the other
28:11
Speaker 2: way around. Well, there's still plenty of that happening too, well,
28:13
Speaker 2: there is now, But if you have to think about.
28:16
Speaker 3: How in the in the idea of gaining a return
28:20
Speaker 3: if you were expecting let's just say ten percent annually
28:24
Speaker 3: from your global equities, which I think is a very
28:27
Speaker 3: punchy number, but let's just throw that out there so
28:29
Speaker 3: we can all smile and love the fact that our
28:33
Speaker 3: money is doubling every seven years. What if you can
28:37
Speaker 3: get a third or forty percent of that in dividends,
28:42
Speaker 3: that's phenomenal. Then you don't have to rely so much
28:44
Speaker 3: on capital gains. Is this sort of dividend one oh one?
28:49
Speaker 3: But the dividends are a signal management saying we're so
28:53
Speaker 3: confident in our business. We're sending money back to you
28:55
Speaker 3: shareholders and that's great. We want them to be confident
28:59
Speaker 3: if they once dividends are paused or eliminated, that's a
29:04
Speaker 3: time to be a little nervous.
29:06
Speaker 2: It's not like an add for the UK market.
29:09
Speaker 3: Well, the UK given that we passed these great dividends,
29:11
Speaker 3: hits the bargains in the UK market, there's no doubt
29:14
Speaker 3: about it. And it's just a question of when the
29:18
Speaker 3: global spotlight turns to it. Somebody say this week they
29:22
Speaker 3: thought that your private equity was galloping over here to
29:25
Speaker 3: take a good look.
29:26
Speaker 2: Oh, yes they are. And then we find ourselves in
29:29
Speaker 2: this ridiculous situation where you can investors won't buy UK companies,
29:33
Speaker 2: private equity arrives here, buy them up, and then we
29:37
Speaker 2: buy the private equity companies or the private equity funds
29:40
Speaker 2: and just have the same stuff in them and pay
29:41
Speaker 2: five times the fee. Yes, yes, not ideal.
29:44
Speaker 3: Not ideal. There's so many things in the world that
29:46
Speaker 3: aren't ideal.
29:47
Speaker 2: What might make global spotlight move here in a good way,
29:50
Speaker 2: because it quite often moves here in a bad way
29:52
Speaker 2: these days. Still make stable government, stable government, good luck.
29:57
Speaker 3: Hand yields remaining stable, if not dropping slightly, which would
30:03
Speaker 3: mean getting inflation under control and having a fiscal stability. Yes,
30:09
Speaker 3: well I didn't. I don'ty it was gonna be easy.
30:11
Speaker 3: I just said that would.
30:12
Speaker 2: Be I was just for those of you who are listening,
30:15
Speaker 2: not watching. I'm just looking there going well. I mean,
30:17
Speaker 2: I don't even know what to say to that, because
30:19
Speaker 2: these things sound quite unlikely for world you get about it.
30:22
Speaker 3: Globally competitive companies. I think about astrozenic and pharmaceuticals. What
30:27
Speaker 3: a what a what an incredible innovator they're based here,
30:31
Speaker 3: but they don't. I mean, I don't know what percentage
30:34
Speaker 3: of revenue I guess is less than ten in this country.
30:37
Speaker 3: But to have a company like that listed here is
30:40
Speaker 3: tremendous or in life insurance and Prudential Plc. They're an
30:45
Speaker 3: Asian life insurance giant.
30:49
Speaker 2: Well, I mean, we always say that a very small
30:51
Speaker 2: percentage of forty one hundred revenues actually come from the UK,
30:54
Speaker 2: well under forty percent.
30:55
Speaker 3: Yes, yeah, but that's okay. The fact they've chosen to
30:59
Speaker 3: domin style here and use UK jurisdiction is an endorsement
31:04
Speaker 3: of the UK legal system and they like the weather.
31:12
Speaker 2: When you look at your portfolios, Sarah, all the many
31:14
Speaker 2: portfolios across the board, look at them, and is there
31:16
Speaker 2: anything that you worry about?
31:19
Speaker 1: What?
31:19
Speaker 2: You look at them and you think, oh god, if
31:20
Speaker 2: this thing happens around a whole part of dropt And
31:22
Speaker 2: one things that one of our most recent guests was
31:25
Speaker 2: talking about was if AI works as suggested, and perhaps
31:29
Speaker 2: is in the way that you've suggested taking away a
31:31
Speaker 2: lot of the grunt work, and we see a lot
31:34
Speaker 2: of highly paid jobs disappear. And this guest was saying, well,
31:38
Speaker 2: maybe fifteen percent of of high income jobs will disappear.
31:40
Speaker 2: I might call high income jobs. Then that has an
31:43
Speaker 2: immediate knock on effect into the flows into four to
31:46
Speaker 2: one case, which again has not gone effect into the
31:49
Speaker 2: flows into passive funds, and then we might see a
31:52
Speaker 2: massive market collapse of GFC style collapse. That was his worry.
31:57
Speaker 3: I don't share that. I'm more in the mark and
32:00
Speaker 3: in camp that the day. I think there are some
32:03
Speaker 3: industries or even sectors that we're going to struggle a
32:06
Speaker 3: little bit, are gonna have to find new ways of
32:08
Speaker 3: proving their value to consumers. But as for employment, I
32:14
Speaker 3: would have more software engineers because they're doing so much
32:17
Speaker 3: like there is revolutionary. And as for analysts, our analysts
32:23
Speaker 3: will be even more productive. We'll be able to cover
32:25
Speaker 3: more stocks. There's seven thousand stocks and we only can
32:29
Speaker 3: cover about ten to twelve per person pretty well, and
32:32
Speaker 3: in quant we can cover quite a lot, but it's
32:35
Speaker 3: a breadth strategy, so we don't have any depth there,
32:38
Speaker 3: and we'd like to have more depth. I mean, why not.
32:40
Speaker 3: It would make our models even more informed. So I
32:45
Speaker 3: would happily take on more analysts if the AI tools
32:48
Speaker 3: make them even more productive, because then they sort of
32:51
Speaker 3: pay for themselves. So I think it really depends on
32:54
Speaker 3: the industry you're talking about. First, I thought it would
32:57
Speaker 3: put lawyers out of business, and of course I should
32:59
Speaker 3: never have thought that.
33:00
Speaker 2: Nothing everything is that, of course not but whatever it is,
33:04
Speaker 2: But there is why they didn't train enough people at
33:06
Speaker 2: the boatman And then there aren't enough experienced people in
33:08
Speaker 2: the middle to check the mistakes of the LLLM.
33:11
Speaker 3: Yes, well, so that's Look the LM's that right now.
33:15
Speaker 3: The AI coding agents do the coding and then check
33:19
Speaker 3: the coating, and but somebody has to be there across
33:24
Speaker 3: the table from the client. Somebody has to supervise it all.
33:28
Speaker 3: And then the amount of legal work is just urgin.
33:31
Speaker 5: Look at radiologists, we thought maybe they would go out
33:34
Speaker 5: a bit with all the scans in the AI, and
33:37
Speaker 5: when you get a scan, it's compared to thousands, maybe
33:40
Speaker 5: hundreds of thousands of different and you have the benefit
33:42
Speaker 5: of all these different radiologists' opinions.
33:46
Speaker 3: But you still want the radiologists in fact now too.
33:50
Speaker 2: You want one to do well.
33:51
Speaker 3: Not just that, but if it brings down the cost
33:54
Speaker 3: of the radiology process, then more people who heretofore wouldn't
33:59
Speaker 3: have been scanned because it was too expensive, can afford it,
34:02
Speaker 3: Like the marketplace, the tam the total dress ball market
34:05
Speaker 3: gets bigger, so you need more radiologists.
34:07
Speaker 2: It's like a hypochondria extreme.
34:11
Speaker 3: Well, yes, one can find things if one goes to look.
34:15
Speaker 3: It's so true. But every once in a while it's
34:17
Speaker 3: saved somebody's life, so why not.
34:19
Speaker 2: Yeah? Absolutely, all right. Last question, last question. You said
34:24
Speaker 2: that people come to London for the weather, when at
34:26
Speaker 2: the moment we are talking, it is very, very hot
34:29
Speaker 2: in London. Well, hope for us anyway, hold for us
34:31
Speaker 2: over thirty degrees, So a lot of people heading to beach.
34:34
Speaker 2: When you go, what are you going to take to read?
34:37
Speaker 2: Be reading at the moment.
34:41
Speaker 3: I really like sci fi, so I will read as
34:50
Speaker 3: much science fiction as I can get my hands on.
34:54
Speaker 3: I don't know what it is. I've never really been
34:56
Speaker 3: that interested in history. I've forced myself to. Thank God,
35:00
Speaker 3: my husband is a great historian, so he helps full
35:03
Speaker 3: need offense for me. Yeah, but when I have one
35:05
Speaker 3: of those husbands, taos great. Thinking about the future is
35:09
Speaker 3: fascinating going back and reading some of the great sci
35:12
Speaker 3: fi of the past and anything that's been written in
35:14
Speaker 3: the last ten years. But when when an author who
35:18
Speaker 3: has a great mind divines the future, and it turns
35:22
Speaker 3: out that's sort of where we're heading today. And they
35:24
Speaker 3: wrote it forty or fifty years ago or more. I
35:27
Speaker 3: just find that thrilling. Yeah, I ask you.
35:30
Speaker 2: And I think I might even have mentioned this on
35:32
Speaker 2: another book case. My son was reading something called The
35:34
Speaker 2: Invasion of the Aliens Wells and that fascinating because a
35:38
Speaker 2: lot of it is like, how did you think of
35:40
Speaker 2: that back when in horsing garriage days? How do you
35:43
Speaker 2: think of this? Yes? Exactly the extraordinary? Do you prefer
35:45
Speaker 2: utopia or a dysktype? Yeah, and your satisfaction where you're
35:49
Speaker 2: not quite.
35:50
Speaker 3: Sure where the word ends, where it could go either way,
35:53
Speaker 3: because dystopian is depressing.
35:56
Speaker 2: Yeah, yeah, a lot of that about a lot of
35:58
Speaker 2: depressing about an invest Sorry, you have to ultimately be
36:01
Speaker 2: an optimist otherwise you're not going to hold anything. Oh well,
36:03
Speaker 2: we'll leave it there, Darah, thank you so much for
36:05
Speaker 2: joining us today.
36:06
Speaker 6: Thank you, Mary, thanks for listening to this week's Marryn
36:17
Speaker 6: Talks Money.
36:17
Speaker 2: If you like our show, rate review and subscribe wherever
36:20
Speaker 2: you listen to your podcasts, and keep sending questions or
36:23
Speaker 2: comments to Marryn Money at Bloomberg dot net You can
36:26
Speaker 2: also follow me and John on Twitter or x I'm
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Speaker 2: at Marinus w and John is John Underscore Stepic. This
36:32
Speaker 2: episode was hosted by Me Marrin's UNSEP Web was produced
36:35
Speaker 2: by Someersadi Moses Andam and Jennifer Seely. Sound designed by
36:39
Speaker 2: Blake Maples and Aaron Kaspers and special thanks of course
36:41
Speaker 2: to Sarah and Kett