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The Perpetual Hunt for ‘Alpha’ · Merryn Talks Money

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Speaker 1: Bloomberg Audio Studios, Podcasts, Radio News. Welcome to Maren Talks Money,
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Speaker 1: the podcast in which people who know the markets explain
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Speaker 1: the markets.
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Speaker 2: I'm Maren thumset Web.
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Speaker 1: This week I'm speaking with Steve how quantitative researcher at Bloomberg.
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Speaker 2: Now, Steve, thank you very much for joining us.
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Speaker 3: Very good of you, very nice to you are to
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Speaker 3: speak with you marine, and thank you for the invitation.
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Speaker 2: I wanted to talk to you this week because this week.
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Speaker 1: Is macro week, right, everybody else is going to be
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Speaker 1: talking Trump, talking tariffs, talking inflation, all this kind of thing,
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Speaker 1: and so we're just going to leave that for everybody
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Speaker 1: else because, to be honest, no one really knows what's
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Speaker 1: going to happen with the tariffs. No one really knows
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Speaker 1: what the macro effects are going to be. There's a
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Speaker 1: lot written on and we are going to go a
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Speaker 1: little bit more micro and talk about things that directly
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Speaker 1: affect company that we can understand. So in particular, I
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Speaker 1: don't know innovation, how pressing power works, how analysts look
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Speaker 1: at companies, all those kind of things, so all the
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Speaker 1: areas that are specific to your work. So what we're
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Speaker 1: going to try and do is not mentioned tariffs once
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Speaker 1: in the whole forty minutes that we're going to speak.
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Speaker 2: It's going to be like a challenge between us. Okay,
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Speaker 2: no mention of tariffs.
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Speaker 4: Can we try? Yes?
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Speaker 1: Okay, all right, everyone's going to let us know immediately
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Speaker 1: if we fail, of course. And so I want to
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Speaker 1: start by talking about the thing that, of course everyone
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Speaker 1: talked about last week, about innovation discovery, in particular about AI.
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Speaker 1: So everything that's happened over the last couple of years
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Speaker 1: with AI has really been the most extraordinary wave of
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Speaker 1: innovation and change. And then we had the news on
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Speaker 1: Deep Seek of course only hit the market last week.
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Speaker 1: Better of fact, WITH was out there several weeks before that,
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Speaker 1: and that represents massive change as well. So that's exciting.
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Speaker 1: But there's a lot else out there, right, It's not
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Speaker 1: just AI at the moment. We're in the middle of
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Speaker 1: an extraordinary wave of technological change. One of the most
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Speaker 1: interesting parts for you.
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Speaker 3: So first of all, a little bit of background myself.
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Speaker 3: I'm a quiet researcher at Bloomberugh in disease and I
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Speaker 3: create systematic strategies where we use, you know, sort of
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Speaker 3: different signals that are trying to identify stocks systematically to
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Speaker 3: create investment strategies. And one of the recent wides we've
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Speaker 3: created is looking at innovation. How do you identify innovation
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Speaker 3: in the systematic fashion? And what we've found this turns
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Speaker 3: out that you can use R and D expenditures as
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Speaker 3: a signal. And this is not new, right, companies have
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Speaker 3: researchers have looked at R and D spending, you know,
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Speaker 3: for a long time and indeed identifies companies that are
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Speaker 3: exposed innovative. But what we have found is actually the
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Speaker 3: more indicative of research capability, innovative capability. It is not
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Speaker 3: so much the absolute amount of R and D spending,
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Speaker 3: but the persistence. Right when we screen for companies that
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Speaker 3: spend and persistently row, they're earned the expanditure year on
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Speaker 3: year for say three trailing years. Right, without doing just
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Speaker 3: so anything else, right, you autonomously pick up companies that
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Speaker 3: are actually exposed very innovative, and should get into details
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Speaker 3: as to how we actually show that they are indeed innovative,
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Speaker 3: because it's such a you know, sort of abstract thing.
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Speaker 3: And what's really remarkable is that if you say, screened
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Speaker 3: the US large MidCap companies, you know, by this metric
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Speaker 3: right and sort of market cap weave them with some
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Speaker 3: sort of camping and weights, so you get back exactly
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Speaker 3: the cues the Nasdaq Stock Exchange, which of course is
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Speaker 3: just happens to be everything that's listed on the NASTS
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Speaker 3: exchange and not you know, explicitly screening for innovation, which
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Speaker 3: we think thought it was very fascinating. And along the
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Speaker 3: way you also do pick up you know, of course
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Speaker 3: AI technology, but you also pick up things such as
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Speaker 3: pharmaceutical innovations. You know Eli Lilly, you know which invented
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Speaker 3: along with the noval nor disc. You know, the GP
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Speaker 3: one drugs, you know, the more weight loss want Wonder drug.
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Speaker 1: So you look at companies and you can see trailing
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Speaker 1: R and D spend over over three years going up
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Speaker 1: and up and up, and that gives you some sense
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Speaker 1: that there's interesting innovations going on there, but of course
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Speaker 1: that doesn't help you choose between people who are using
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Speaker 1: their innovative abilities successfully with the product that will come
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Speaker 1: to market and those that are not. And it also
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Speaker 1: doesn't help you pick up the companies. So let's go
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Speaker 1: back to AI for example. Well, one of the things
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Speaker 1: that was much discussed last week was the fact that
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Speaker 1: so many companies are spending so much money, possibly on
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Speaker 1: the wrong thing. So it's not helping you distinguish between
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Speaker 1: good R and D and pointless R and D. And
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Speaker 1: particularly when you get, for example, to their bubble situation
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Speaker 1: where you get that massive capex spending over a series
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Speaker 1: of years, but you only get one winner.
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Speaker 3: Well, let's unpack that idea a lot of bits. So
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Speaker 3: first of all, let's get back to the idea of
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Speaker 3: for just simply screen for companies with persistent R and
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Speaker 3: D spending. You will think exactly like, how would I
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Speaker 3: be able to tell whether the company is just throwing
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Speaker 3: a bunch of money after bad right, you know, and
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Speaker 3: there's way one power building and the money is just
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Speaker 3: being set on fire. That indeed, that is possibility. And
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Speaker 3: what is surprising is it comes out when you screen
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Speaker 3: for companies that persistently spend the R and D instead
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Speaker 3: of just sort of you know, one.
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Speaker 4: On and off.
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Speaker 3: Uh, these tend to be companies that actually have the
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Speaker 3: ascertainability or knowledge about innovative success. And that has been
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Speaker 3: well documented in the academic literature that there is actually
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Speaker 3: persistence in skills, whether it's you know, sort of investing
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Speaker 3: skills or innovative skills, right, And it turns out without
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Speaker 3: explicity screening. So if you look at companies that persistently
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Speaker 3: spend R and D, they tend to be companies with
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Speaker 3: strong cash flows, internally generated cash flows, strong profitability, and high.
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Speaker 4: And low leverage.
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Speaker 3: And the reason is it turns out is because R
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Speaker 3: and D is a fundamentally opaque and asymmetric information activity. Right.
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Speaker 3: It is highly uncertain, it's extremely cost costly, So companies
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Speaker 3: are going to struggle to raise external financing, whether it's
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Speaker 3: debt or issue. You know, you should equity definance it.
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Speaker 3: So only companies that are confident in its own ability
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Speaker 3: to innovate to translate that innovatives that R and D
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Speaker 3: into valuable intensible capital that will produce cash flow streams
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Speaker 3: down the road, will actually do it in a persistent fashion.
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Speaker 3: And that's one thing. For example, you see when you
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Speaker 3: take a company, say R ETF for example, right, look
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Speaker 3: at the companies that are in the ETF. You know
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Speaker 3: they actually have very high percentage of R and D
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Speaker 3: expanditures as a share of net sales. Right, that's a
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Speaker 3: typical way people measure R and D. But if you
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Speaker 3: look at the companies that have persistent R and D
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Speaker 3: spending in that profolio is not very high because those
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Speaker 3: companies are not persistently profitable. So the R and D
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Speaker 3: spending is on and off. Right in one year they
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Speaker 3: spend a time and the next year run out of money,
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Speaker 3: they don't spend any And the companies that we do
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Speaker 3: pick up, you know, in our you know, methodology, then
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Speaker 3: is actually the persistence, right there is actually the embedded
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Speaker 3: quality screen. And I think that combine that with the
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Speaker 3: fact that if you're just doing a market cap waiting,
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Speaker 3: which you know sort of people do these days, you know,
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Speaker 3: sort of matter of factly because it's become the convention.
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Speaker 3: But you think about what it really means is that
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Speaker 3: there is a sense of expost market validation, right that
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Speaker 3: having spend all this money exposed you got you're getting
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Speaker 3: the market valuation because you've produced intensible capital that's actually
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Speaker 3: spinning out cash flows, and and and and and and
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Speaker 3: That's what's different about today's stock market compared to say
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Speaker 3: the bubble of two thousand, is that the bubble today
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Speaker 3: is in the quality stocks, right. The bubble today is
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Speaker 3: in the companies that are tremendously profitable, so much so
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Speaker 3: they seem to have escaped velocity, right, they don't. They
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Speaker 3: don't require credit, They don't require financing because they finance themselves.
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Speaker 1: Okay, So we have this link between a company that
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Speaker 1: that has regular R and D spending and quality and
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Speaker 1: that that's that's the important part of the link. That
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Speaker 1: R and D spending as long as it's regular, inconsistent,
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Speaker 1: and rising, is also indicative of a high quality company.
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Speaker 4: M h. Yeah.
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Speaker 2: If we're buying those companies in the US at the moment,
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Speaker 2: we're really paying up for them.
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Speaker 4: Aren't we quite right?
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Speaker 3: Yeah, I mean, valuation has absolutely climbed over the last decade,
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Speaker 3: I think ten years ago, you know, or more, I guess.
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Speaker 3: So when Buffett started buying Apple that you know, tax
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Speaker 3: stocks were really cheap, right, and you know how many
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Speaker 3: years have we heard, you know, the sort of forecasts
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Speaker 3: of EXCA returns for US equities being lower than the
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Speaker 3: rest of the world and keeps being proven wrong. Is
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Speaker 3: because profitability keeps surprising to the upside, and along with it,
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Speaker 3: valuation paid for them because there was this you know,
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Speaker 3: desire for quality assets.
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Speaker 1: And do you think that that rising and persistent R
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Speaker 1: and D is a thing that is driving earnings forward.
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Speaker 2: Oh, just and justifies the valuations.
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Speaker 3: Yeah, absolutely, thing we do in our white paper, which
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Speaker 3: your listeners can look up when they just search a
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Speaker 3: Bloomberok innovation factor and they'll find a blog.
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Speaker 2: In the blog, we'll put a link in the show notes.
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Speaker 2: We don't have to search, no searching required. It will
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Speaker 2: be in the show notes.
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Speaker 3: Perfect for you. So you can take a look at
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Speaker 3: the paper. And what we show is that if you
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Speaker 3: sort of you know, do an experiment where you go
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Speaker 3: back in history and identify companies that were persistently innovative
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Speaker 3: in biomasure right, having spent three consecutive years of growing
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Speaker 3: R and D, and look at that subsequent five year
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Speaker 3: sort of key fundamental performances, you will see that these
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Speaker 3: companies showed our strongest growth in revenue, net income free,
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Speaker 3: cash flow free cash for pressure and you know, just
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Speaker 3: along all the fundamental metrics, and that particularly accelerated over
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Speaker 3: the last ten years. And so, in other words, the
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Speaker 3: selection is not just based on valuation expansion. We actually
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Speaker 3: identified companies that produced intention by capital that translated into
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Speaker 3: our earnings and that is the reason why these companies
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Speaker 3: are being rewarded by the market and This is what
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Speaker 3: is really particularly reassuring is that this is a phenomenon
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Speaker 3: that we've documented across the globe. It's not just in
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Speaker 3: the US. It is in Europe as well, is in
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Speaker 3: Asia as well.
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Speaker 1: Okay, interesting, but when we look at that, presumably, I'm well,
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Speaker 1: presumably you see the majority of the companies that fit
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Speaker 1: these fit these factors in the US. I mean, that's
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Speaker 1: where we all perceive the main innovation in listed markets
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Speaker 1: being let's put China to one side for a moment.
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Speaker 1: If we're looking at the US, the UK, Europe, et cetera.
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Speaker 1: It is in the US that we see that innovation
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Speaker 1: in the main and that's why we've seen that huge
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Speaker 1: valuation expansion there, which has been the main driver of
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Speaker 1: the US exceptionalism in the US outperformance since twenty fifteen
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Speaker 1: or so. It is the perception and possibly the reality
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Speaker 1: that all the innovation is in the US. That is
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Speaker 1: that the case, or are you actually seeing that persistence
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Speaker 1: of R and D spending in companies in say Europe
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Speaker 1: or the UK as well.
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Speaker 4: Well?
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Speaker 3: So you're absolutely right in that the bulk of the
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Speaker 3: dollar you know, activity, innovation activity probably takes place in
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Speaker 3: the US just because of the size of the market.
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Speaker 3: And also I think it was Jeff Bezos who recently
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Speaker 3: made it remark that observation that was really insightful is
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Speaker 3: because of the US risk capital markets that really finances
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Speaker 3: you know, innovative activities. But that being said, there is
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Speaker 3: less innovative activities, aren't the activity in Europe, But where
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Speaker 3: it does exist, markets actually rewarded those activities similarly as well. Right,
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Speaker 3: you saw this dramatic outperformance, and you see, you know,
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Speaker 3: market follows wherever the activity takes place. So whereas you
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Speaker 3: used to take place more in Germany, Switzerland, you know,
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Speaker 3: sort of in a farmer space, now micro it's more
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Speaker 3: northward towards US, you know, the Netherlands because of SML,
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Speaker 3: or because or Denmark because of a novel nor disc
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Speaker 3: and the associate you know, supply chain as well.
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Speaker 1: Okay, so the innovation they you see in Europe is
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Speaker 1: very much in the farmer area.
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Speaker 3: And and AI for that matter, ASML and their suppliers.
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Speaker 2: Right, uh huh uh huh okay. And the UK can
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Speaker 2: you check us a bone here?
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Speaker 3: Well, you know, actually interestingly, you know UK, I recently
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Speaker 3: noticed the company in my research on you know, we
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Speaker 3: will get you. Later on pressing power, I noticed that
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Speaker 3: there was a company called R E l X, and
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Speaker 3: I was very curious what it is because the stock
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Speaker 3: is absolutely ripping, and I realized it's actually a massive
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Speaker 3: AI beneficiary. Because it turns out there, I think you
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Speaker 3: may be familiar with the company, they own about half
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Speaker 3: the world's academic you know, publications, right, journals. And you
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Speaker 3: would have thought before AI that this was a dead
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Speaker 3: wood industry like who reads anymore? Led along academic journals,
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Speaker 3: but it turns out this is basically a vast of
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Speaker 3: extremely valuable data and AI. It's all about the training data.
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Speaker 3: Uh and and and they're definitely benefiting from it.
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Speaker 2: Okay, that's interesting.
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Speaker 3: Oh, I mean beyond that, of course, there is the
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Speaker 3: farmer angle and you know Astrosdenaga and so on. But yeah,
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Speaker 3: but that's more traditional.
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Speaker 1: Okay, let's move on to talk about this pricing power subject.
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Speaker 1: But before we get there, how does one invest in
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Speaker 1: the companies that you've been talking about? Is there something
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Speaker 1: we can do to get access to these persistent R
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Speaker 1: and D spending quality companies across the board.
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Speaker 3: So with respect to innovation, right you're talking about, Yeah,
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Speaker 3: we have a Bloomberg indices launched in the R and
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Speaker 3: D industries.
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Speaker 4: So B R and D is the index.
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Speaker 3: But then we also have a smaller set of companies
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Speaker 3: with a higher convication that's called be invent right, so
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Speaker 3: easy to remember, Monka. And on the back of that,
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Speaker 3: we have actually licensed the indices to ETF features. The
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Speaker 3: First Trust, for example, has licensed being then to create
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Speaker 3: an ETF with a ticket R and D in America.
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Speaker 3: And we're also I personally think that this concept applies
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Speaker 3: equally well to Europe. And part of the reason why
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Speaker 3: I'm in London this week is to try to persuade
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Speaker 3: people that Europe ought to invest in the South and
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Speaker 3: or to invest in innovation, because you know, the race
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Speaker 3: is on and you know, by both necessity and reward,
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Speaker 3: I think this actually presents a very interesting alternative to
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Speaker 3: US innovation.
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Speaker 1: Okay, so if and if that happens, we might actually
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Speaker 1: see the European markets pick up a little, which we
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Speaker 1: already are this year, right, we're already seeing great performance
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Speaker 1: from European markets relative to the US.
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Speaker 4: Oh absolutely abslightly better.
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Speaker 3: Yeah, yeah, German stocks are killing it, right, you know,
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Speaker 3: everyone's talking about Germany going into a procession. But the
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Speaker 3: decks keep hitting a what time highs and you know,
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Speaker 3: and I think that's part of the reason why we're
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Speaker 3: seeing this pivot of AI broaden out right away from
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Speaker 3: the first phase of pigs and shovels to more applications
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Speaker 3: software and you know, with you know AI, last week's
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Speaker 3: news about AI being much cheaper to implement a much
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Speaker 3: more you know, sort of energy efficient, that means that
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Speaker 3: everybody else can start getting into the game. And that's
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Speaker 3: why software you know is actually doing very well.
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Speaker 1: And it's yet another reminder, isn't it, which apparently people
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Speaker 1: do continually need that markets are not economies. Economies are
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Speaker 1: not markets, and markets can move in completely different directions
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Speaker 1: to economies depending on on the starting valuations.
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Speaker 4: Hmm absolutely mm.
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Speaker 1: Okay, right, So let's go back to what you were
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Speaker 1: saying about pricing power. I mean, this is one of
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Speaker 1: the basics of investing is that analysts and investors always
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Speaker 1: say they're looking for companies with modes with monopoly power
15:51
Speaker 1: or agobly power of some kind and with the ability
15:54
Speaker 1: to control their own pricing. So you would think that
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Speaker 1: that would be the kind of thing that we're be
16:00
Speaker 1: very much out there in the market and you wouldn't
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Speaker 1: be able to find any pricing anomalies in that area.
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Speaker 1: But I think you're going to tell me that I'm wrong.
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Speaker 3: Well, we're going to go back to I think you know,
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Speaker 3: eventually we'll always go back to the quality paradox. But indeed,
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Speaker 3: we've been looking at these accounts of pricing power because
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Speaker 3: over the last few years, so we were looking at
16:22
Speaker 3: this two three years ago, inflation was all the rage,
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Speaker 3: and you know, everyone's asking how do we actually capture
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Speaker 3: pricing power?
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Speaker 4: Pricing power?
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Speaker 3: So everyone has their own ideas and there's qualitative ways
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Speaker 3: of you know, capturing it, and people will throw alls
16:35
Speaker 3: of company names out there and claim that those companies
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Speaker 3: have pricing power. I've seen claims of our Tesla Hast
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Speaker 3: pricing power, Apple is pricing power, But does it.
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Speaker 4: Really how do we actually know?
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Speaker 3: So we sort of did a bit of work and
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Speaker 3: found that it turns out it's not so much profitable
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Speaker 3: companies that have pricing power, because high profit margins can
16:56
Speaker 3: be eroded into right if you don't have pricing power.
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Speaker 3: So either if you look at the case of Apple, right,
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Speaker 3: you know, the flagship iPhone price has actually not changed
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Speaker 3: very much all over the last few years, even though
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Speaker 3: I'm sure cost has gone up, you know, tremendously for them.
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Speaker 3: So how do we actually then sort of capture companies
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Speaker 3: that do have pricing powers, in my opinion, in our opinion,
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Speaker 3: you look at not the level, but the stability, in
17:23
Speaker 3: other words, the standard deviation of gross margins over the
17:27
Speaker 3: last five years.
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Speaker 4: Right.
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Speaker 3: So again there's a certain theme to how we sort
17:30
Speaker 3: of look at to our you know, systematic strategies here.
17:34
Speaker 3: And it turns out that the reason we focus on
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Speaker 3: gross margins because it's the least manipulated you know, accounting metric,
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Speaker 3: you know, because it's just the difference between the top
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Speaker 3: line and the subtracting the variable costs, including our wages.
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Speaker 3: So the things that are more sensitive to inflationary shocks. Now,
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Speaker 3: if you have a company that have pricing power, then
17:56
Speaker 3: if there's cost push shock, they can pass on a
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Speaker 3: cost to customers, and if gross margins growing indicative of
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Speaker 3: a demand shock, then they can supply into it and
18:08
Speaker 3: drive down the margin towards their target. So that's why
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Speaker 3: we've constructed a measure where we look at companies with
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Speaker 3: the most stable gross margins.
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Speaker 1: Okay, and so if you're looking at companies like this,
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Speaker 1: you're going to expect them to be in relatively niche
18:22
Speaker 1: areas like the company you were just disgusting being in
18:25
Speaker 1: an academic academic journals. This marcher not in an area
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Speaker 1: that other people are going to break into in a hurry,
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Speaker 1: is it.
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Speaker 4: Indeed?
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Speaker 3: Yeah, That's one An interesting thing that emerges from our
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Speaker 3: systematic you know so of our screen is that you
18:39
Speaker 3: look at the companies that come out of the screen,
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Speaker 3: they look incredibly either boring or you know, not really
18:46
Speaker 3: one you recognize. For example, one company that keeps popping
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Speaker 3: up in the American version of the Oppresing Power Indux
18:51
Speaker 3: is this company called Cadence Design Systems.
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Speaker 4: Have you heard of it?
18:55
Speaker 2: Chugs familiar, But I don't think I can straight up there,
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Speaker 2: I have no So.
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Speaker 3: Caidence Design system they design software for designing microchips.
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Speaker 2: Uh huh that does that boring? Yeah?
19:06
Speaker 4: Right?
19:06
Speaker 3: So in other words, they are not the ones manufacturing
19:09
Speaker 3: the chips. That's a highly cyclical sector, right. Uh, that
19:13
Speaker 3: comes with bone and bars of demand of traditionally consumer electronics.
19:18
Speaker 3: They design the software with which uh, these manifesture these
19:22
Speaker 3: chip designers design chips. In other words, you know, you
19:26
Speaker 3: would even if your business is down a lot at
19:28
Speaker 3: a MD or wherever you are, you're not going to
19:30
Speaker 3: conceive of canceling your subscription to the software with which
19:34
Speaker 3: you do your work. Right, So that's really what gives
19:37
Speaker 3: them the pressing power is that they are supplier in
19:39
Speaker 3: the verified space with which there's maybe a handful of
19:43
Speaker 3: companies and continuing consolidation. Uh So that and it doesn't
19:48
Speaker 3: attract the attention of regulators because it's not the category
19:51
Speaker 3: that people think of because it's not consumer facing or
19:54
Speaker 3: very glamorous, right, And that's how the pressing power is
19:58
Speaker 3: actually maintained.
19:59
Speaker 1: This when you speak about companies like this and in
20:03
Speaker 1: the category we were discussing for R and D equality, etc.
20:06
Speaker 1: It sounds to me like you're making the case for
20:09
Speaker 1: active investment. You're saying this market is it is not
20:11
Speaker 1: particularly efficient. There's all sorts of anomalies out there. There's
20:14
Speaker 1: lots of places where investors can go to find companies
20:18
Speaker 1: that other people aren't looking at. Are you making the
20:22
Speaker 1: case here for a shift back towards active investment or
20:26
Speaker 1: are you really making the case for factor specifical sector
20:30
Speaker 1: specific ETFs.
20:33
Speaker 4: That's a great question.
20:34
Speaker 3: I mean, so I have a somewhat controversial perhaps view
20:38
Speaker 3: on this whole active passive debate. I don't think of
20:42
Speaker 3: it as being I mean, I think the better word
20:46
Speaker 3: is discretionary versus systematic. Right, Like what I just described
20:50
Speaker 3: to you, the methodology, whether it's looking at the stability
20:54
Speaker 3: of growth margins or the persistent R and D growth,
20:58
Speaker 3: that's not particularly passive. As much as you think about
21:03
Speaker 3: the traditional benchmark of just buying everything on the stock
21:06
Speaker 3: market simply market capt weighted, right, this requires a certain
21:11
Speaker 3: I think particular set of rules and actually involves pretty
21:16
Speaker 3: sizeable turnovers in your portfolios, you know, on every rebalanced date,
21:22
Speaker 3: and depending on the signal you're looking at that the
21:24
Speaker 3: channel can be did quite high. So I don't know
21:28
Speaker 3: if that means it's not in that case active in
21:31
Speaker 3: some sense. Right, It's just it's not discretionary, right. The
21:36
Speaker 3: process is rules based and fully systematic, and that gives
21:40
Speaker 3: you the consistency.
21:41
Speaker 2: Yeah, so rules based active investing.
21:45
Speaker 4: I guess you could say so.
21:46
Speaker 3: I mean, you know there are quant funds out there,
21:48
Speaker 3: you know, and would you consider quant funds to be
21:50
Speaker 3: active or passive?
21:52
Speaker 2: Ooh, rules based active?
21:58
Speaker 1: But it's still from what you're saying it sounds like
22:01
Speaker 1: an argument for active ETFs rather than a traditional active fund.
22:06
Speaker 3: I do think there is opportunity to the extand that
22:09
Speaker 3: investors want to, you know, uh, take take a different
22:14
Speaker 3: view on things and try to you know, sort of
22:18
Speaker 3: capture the changing trends in the market, because I mean,
22:21
Speaker 3: let's be frank, it is incredibly difficult, if not outright impossible,
22:25
Speaker 3: to outperformed the S and P five Well, I mean
22:28
Speaker 3: the B five hundred. You know context we're here, and
22:30
Speaker 3: you know we're talking about Bloomberg five hundred index. Uh
22:33
Speaker 3: and you know, for the matter, you know, a systematic
22:36
Speaker 3: you know, R and D index that we have created here.
22:39
Speaker 3: Like if you just simply have that you know, benchmark view,
22:43
Speaker 3: you know, that gives you essentially a core holding that's
22:46
Speaker 3: really hard to outperform. But then if you want to
22:48
Speaker 3: do some things along along that, if you have sort
22:51
Speaker 3: of microviews or micro industrial views, that's how you can
22:55
Speaker 3: express it. In our opinion, you know, you should do
22:58
Speaker 3: it in a systematic fashion.
23:00
Speaker 1: Yeah, fair enough, fair enough, Okay, Well, let's look at
23:03
Speaker 1: one more of the things that you've been writing about recently,
23:06
Speaker 1: which is about turnaround companies and the way that analyst
23:10
Speaker 1: ratings might give clues as to whether those turnarounds. Oh
23:15
Speaker 1: you wrote on that middle of last year.
23:18
Speaker 4: Right I did.
23:18
Speaker 3: Yeah, So yeah, that's that's another interesting idea that we
23:23
Speaker 3: were looking at. So here bloomber of indices, we tried
23:27
Speaker 3: to leverage the various types of data you know on
23:31
Speaker 3: the terminal that I think somewhat unique, and I think
23:35
Speaker 3: one thing is what everyone looks at is analyst ratings
23:39
Speaker 3: and less opinions you know about stocks.
23:42
Speaker 4: Of course, you.
23:43
Speaker 3: Know, a first order intuitive thing when we look at
23:46
Speaker 3: is just to buy all the stocks that analysts are
23:49
Speaker 3: recommending you to buy. And we were thinking, is there
23:52
Speaker 3: maybe a slightly different you know, views or approach to it?
23:57
Speaker 3: In particular, can we think about the you know, companies
24:01
Speaker 3: that the analysts are becoming more polish on And that
24:05
Speaker 3: led us essentially to looking at this idea of looking
24:08
Speaker 3: at analysts rating momentum but ignoring the ones that analysts
24:13
Speaker 3: tell you to buy. So, you know, on the Bloomook terminal,
24:16
Speaker 3: if you look up any stock and you type the
24:18
Speaker 3: function A and R, you see a score going from
24:22
Speaker 3: one to five, one being strong seale and five being
24:24
Speaker 3: strong bys.
24:26
Speaker 4: If you just toss out the.
24:27
Speaker 3: Ones that have a rating of four and above in
24:30
Speaker 3: other words, a buy or strong by and then you
24:32
Speaker 3: look at the stocks whose consensus rating has improved the
24:36
Speaker 3: most between the last six to twelve months, and you
24:39
Speaker 3: buy those stocks. We found that that sets actually tended
24:43
Speaker 3: to capture a set of companies that the way we
24:47
Speaker 3: can think about summarizing them as being basically turn around companies,
24:51
Speaker 3: companies that are sort of have fallen on hard times.
24:55
Speaker 3: They were hated or not so much or not at
24:57
Speaker 3: least not but love by analysts. But analysts are like
25:00
Speaker 3: starting to change their minds on those stocks before converging
25:02
Speaker 3: their consensus.
25:04
Speaker 4: If that makes sense.
25:05
Speaker 1: Yeah, So the general idea being that if you if
25:08
Speaker 1: you're only looking at stocks that everyone already has a
25:10
Speaker 1: buy on it, maybe.
25:11
Speaker 4: Too late indeed, so yes, so all the games are.
25:15
Speaker 1: In there, so you want to be looking for I mean, analysts,
25:17
Speaker 1: they're going to be slightly late to things, aren't they
25:20
Speaker 1: by definition, by the time everyone's caught hold of a story,
25:23
Speaker 1: and so it's already underway.
25:25
Speaker 2: So it's it.
25:28
Speaker 1: Is it contrariant by something where people are beginning to
25:30
Speaker 1: turn their minds. Yeah, because you've found you found the
25:33
Speaker 1: bottom and you've found the catalyst, right.
25:36
Speaker 3: Yeah, I mean the way yeah, we think about is that, Yeah, analysts,
25:41
Speaker 3: you know, over the long run, they're not wrong, they
25:44
Speaker 3: can be late. By the time everybody comes to love
25:47
Speaker 3: a stock, you know, and give it, you know, a
25:49
Speaker 3: strong by rating, it tends to be that the price
25:52
Speaker 3: has already reflected you know, that strong sentiment and good fundamentals.
25:59
Speaker 3: So we are capturing here. You say, essentially that company
26:02
Speaker 3: is just about turning around or from you know being
26:06
Speaker 3: previously you know, having been in a bad fact of
26:10
Speaker 3: fundamentals and that you know, sentiments to just about improving, right,
26:15
Speaker 3: and that gives you that asymmetric risk award.
26:18
Speaker 1: So you've got an improvement score. Have you got any
26:21
Speaker 1: examples in mind of companies that fit that mold right now?
26:24
Speaker 4: Yeah.
26:25
Speaker 3: So there's a few examples that we go into in
26:28
Speaker 3: the white paper, which again we will.
26:30
Speaker 4: Linked to uh one way.
26:32
Speaker 3: Well, one of them is interesting recently is Oracle, Right.
26:36
Speaker 3: Oracle you know was actually you know, having a hard
26:38
Speaker 3: time until the whole AI thing you know, kicked off,
26:41
Speaker 3: and you know, their consensus ratings were in the threes
26:45
Speaker 3: and and then improving a bit. And then we you know,
26:49
Speaker 3: the index sort of identify that company as say, you know,
26:53
Speaker 3: essentially a company who's analysts are changing their minds on right,
26:58
Speaker 3: And indeed, then we pick the stock and the stock
27:01
Speaker 3: sort of goes of a lot because it catches this
27:05
Speaker 3: AI you know, turn around and also generally I think
27:08
Speaker 3: the sector having bottomed. So that's one example. And another
27:14
Speaker 3: example we saw was actually Hershey's, right, Hershey's, uh, you
27:20
Speaker 3: know in the chocolate you know industry, uh and.
27:25
Speaker 2: Terrible, terrible chocolate. Terrible chocolate.
27:28
Speaker 4: Was it? What's your chocolate choice? Milky?
27:32
Speaker 1: Well, they're very very dark chocolate and my kind of
27:34
Speaker 1: lint eighty five person myself, so you know, Hershey's is inedible, inedible.
27:40
Speaker 3: Well, perhaps that's why that's carry on, that's why the
27:43
Speaker 3: stock has fallen the hard times. And the stock did
27:46
Speaker 3: fall on hart that much chocolate A yeah, so and
27:50
Speaker 3: then you know it was getting hammered by the the
27:54
Speaker 3: the chocolate commodity ripping and eating into their margins. And
27:58
Speaker 3: then the stock, you know, was picked up because analyst
28:02
Speaker 3: ratings finally started improving. Right from trailing six to twelve
28:06
Speaker 3: month we take we'd take an average, and then we
28:08
Speaker 3: saw basically the stock, you know, recovering. But then of course,
28:12
Speaker 3: you know, and then maybe this is the point with
28:14
Speaker 3: actively passive, is that because it's a fully passive, systematic
28:17
Speaker 3: rules based you know, signal, you can pick up, we
28:21
Speaker 3: pick up the stock, and then chocri rice, you know,
28:23
Speaker 3: went down and shot up again, and the stock went
28:25
Speaker 3: down again. So the index, the strategy didn't you know,
28:28
Speaker 3: react to it as quickly, you know, as you would
28:31
Speaker 3: if you were in a fully fully discretionary you know, strategy.
28:35
Speaker 3: But but that's sort of the general idea.
28:37
Speaker 2: Okay, And is there an index for that as well?
28:40
Speaker 4: Oh?
28:40
Speaker 3: Yeah, so the indexes again very simple, B, A and R.
28:44
Speaker 3: Is the index blone broke A N R okay?
28:47
Speaker 2: And is there a way to invest in that?
28:49
Speaker 4: Yeah?
28:50
Speaker 2: There is a for the ordinary investor, Yeah, there isn't.
28:53
Speaker 3: There is an ETF in America. That investor has licensed
28:57
Speaker 3: the index and they ticklar upgrade up g.
29:01
Speaker 4: D uh that's upgrade.
29:04
Speaker 2: Very good.
29:07
Speaker 3: Actually, speaking of investment ways of investing, a Passion Pressing
29:13
Speaker 3: Power index in America has also been been licensed. And
29:16
Speaker 3: the ticker is p o.
29:17
Speaker 4: W A p w A.
29:19
Speaker 2: That's not too good. That's not too good.
29:21
Speaker 1: I'm always interested in the in these tickets and the
29:23
Speaker 1: cleverness of some of them. You know, there's somebody out
29:25
Speaker 1: there who does a great job on tickets, isn't it
29:28
Speaker 1: who chooses those?
29:29
Speaker 4: Who chooses those?
29:30
Speaker 1: Maybe you knows that who worked when you when you
29:32
Speaker 1: apply to have your ETF do you think of the
29:34
Speaker 1: ticker and you ask them? Or is this someone clever
29:36
Speaker 1: around the the the creators.
29:39
Speaker 3: You make, I think this typically comes from uh and yes,
29:43
Speaker 3: someone creative on the as a manager issue side, you
29:47
Speaker 3: know that, I think, Yeah, I like you marvel at
29:51
Speaker 3: not just the tremendous creativity but the availability of some
29:55
Speaker 3: of these tickets. You would have thought they'd been picked up.
29:58
Speaker 3: But yes, like I was very pleasantly surprised that R
30:02
Speaker 3: and D, you know, the ticker was actually available.
30:05
Speaker 4: But there you go.
30:07
Speaker 2: Mm hmm mmmmmm. Well interesting.
30:10
Speaker 1: And I suppose that this tells you about the relative
30:12
Speaker 1: newness of the entirety of industry, doesn't it.
30:14
Speaker 3: Yeah, at least you know sort of. Well, I mean
30:19
Speaker 3: in America it's not so new anymore. I mean, it's
30:21
Speaker 3: all the rage. But but we're trying to see if
30:24
Speaker 3: this become you know, the way in Europe as well.
30:27
Speaker 2: Yeah, so what are you working on at the moment, Steven.
30:30
Speaker 3: So right now, we're working on a couple of things.
30:35
Speaker 3: One of them is we're trying to you know, think
30:38
Speaker 3: about shareholder yield as a concept, you know, total shareholder return.
30:44
Speaker 3: I'm writing a white paper on that topic. So I
30:48
Speaker 3: don't know if you're familiar with the concept of shareholder yilding.
30:50
Speaker 3: You know, there was you know, sort of not just
30:52
Speaker 3: looking at dividends, but all forms in which companies can
30:56
Speaker 3: return capital to shareholders, which includes buy back and debt reduction. Right. Uh,
31:02
Speaker 3: this is not a particular new concept and it has
31:07
Speaker 3: done well, but we have had given our own spin
31:10
Speaker 3: as well at bloom Bloomberg Indices, where we not just
31:14
Speaker 3: look at companies with strong total shareholder holder return, but
31:18
Speaker 3: the companies that have the consistent historical fundamentals to be
31:23
Speaker 3: ablity to afford those you know, strong total shareholder return.
31:27
Speaker 3: In other words, we're looking at a long history of
31:29
Speaker 3: free cash flow and capacity as a ship you know,
31:33
Speaker 3: as a ratio to the total shareholder payout. That will
31:37
Speaker 3: allow us to eliminate more false positives that you might
31:41
Speaker 3: pick up, you know, if you just screened naively for
31:44
Speaker 3: companies that happen to have very large total shareholder return.
31:48
Speaker 1: Okay, interesting, So that's the results of that would be
31:51
Speaker 1: something for us to look out for, assuming we can't
31:53
Speaker 1: see them quite yet.
31:55
Speaker 2: Thank you, Steven.
31:57
Speaker 1: Is it anything that you would like to tell our
31:59
Speaker 1: listeners that we have not talked about yet, Any any
32:03
Speaker 1: perfect little insights, any brilliant investment recommendations, anything we haven't
32:07
Speaker 1: discussed that you feel they should know.
32:10
Speaker 3: One subject we are looking more active now is the
32:14
Speaker 3: idea of more macro aware investments because I think we've
32:20
Speaker 3: exited the age of moderation, you know, the monitor policy,
32:26
Speaker 3: which used to be the only showing in town. I
32:29
Speaker 3: think I taken a back seat, and we are now
32:32
Speaker 3: seeing more and more of these thematic trends, you know,
32:36
Speaker 3: a macro volatility. So I think during this period it's
32:41
Speaker 3: important to be more tactical. And one thing we are
32:46
Speaker 3: looking at increasingly is how do we identify sort of robust,
32:51
Speaker 3: simple signals that will allow us to essentially pivot between
32:58
Speaker 3: different views. Not so much market timing, because now we
33:01
Speaker 3: know it's nearly impossible, but can we find ways in
33:05
Speaker 3: which that allows us to stay risk one and not
33:09
Speaker 3: miss the upside? While key junctures, you know, avoid the
33:13
Speaker 3: big mistakes. So one signal I've found in all of
33:17
Speaker 3: my micro research, it turns out that you know, there
33:21
Speaker 3: is if you look at the change in CPI right, yeah,
33:25
Speaker 3: year inflation, that turns out to be an extremely robust
33:29
Speaker 3: and powerful projector of uh, you know, sort of as
33:34
Speaker 3: a performance. And what I'm talking about, for example, is
33:36
Speaker 3: if you look at today's inflation in Let's say I
33:39
Speaker 3: don't know what what's was the inflation in K today? Actually,
33:41
Speaker 3: because I normally follow the US, let's say it's two percent,
33:45
Speaker 3: some two point two percent. Let's just pick up a number, right,
33:48
Speaker 3: and if it was say four point four percent a
33:50
Speaker 3: year ago, right, inflation would have gone down over the
33:53
Speaker 3: last twelve month. That is actually a very powerful risk
33:57
Speaker 3: on signal because what follows from falling inflation is you
34:01
Speaker 3: tend to get all the good things right Stronger economic growth,
34:05
Speaker 3: stronger job market, higher earnings per share, higher productivity, higher
34:09
Speaker 3: customer confidence, and lower bond yields. All of these things
34:12
Speaker 3: tend to be good for assets. Now, if you flip
34:16
Speaker 3: the picture and you say, over the last traillion twelve months,
34:18
Speaker 3: if inflation had gone up, right, if let's say it
34:20
Speaker 3: was two point five percent and now it's going back
34:23
Speaker 3: to three point two percent. You get the opposite of
34:25
Speaker 3: all of those things previously. So how do we take
34:28
Speaker 3: advantage of this? So we created a index that is
34:31
Speaker 3: called dynamic equity duration where we essentially calculated the implied
34:37
Speaker 3: cash flow distribution of stocks, and if inflation has been
34:41
Speaker 3: coming down, would buy stocks whose cash flows are further
34:45
Speaker 3: out right, they tend to be growth stocks, risk on stocks. Right,
34:48
Speaker 3: our inflation has been going up, then we do the opposite.
34:52
Speaker 3: We lean towards companies whose cash flows are more near term.
34:56
Speaker 3: And that I think that we have shown to be
34:58
Speaker 3: actually a very interesting way to allow investors to remain
35:04
Speaker 3: risk on, ignoring all of the noise, right, you know,
35:08
Speaker 3: whatever you may be what this deep seek where there
35:11
Speaker 3: is terriffs.
35:13
Speaker 2: Whoa, we nearly got to the end. We were so close.
35:20
Speaker 4: Well I couldn't resist.
35:21
Speaker 3: But anyway, but the point is that you know you've
35:24
Speaker 3: had all this well I think retail investors called fut right,
35:27
Speaker 3: all these sort of news that will give you a
35:32
Speaker 3: terrifying narrative. But if you just look at the trailing
35:35
Speaker 3: half months inflation and remain risk going in terms of
35:37
Speaker 3: equity duration, you would have actually done really well and
35:41
Speaker 3: avoided you know, the disares of Tony Hunty too, right
35:44
Speaker 3: when you know that we had an evaluation compression.
35:47
Speaker 1: Yeah, okay, interesting, So that's the signal that everyone can watch.
35:51
Speaker 1: One last question, Davin, is there anything that you are
35:54
Speaker 1: reading at the moment that you are finding very interesting?
35:57
Speaker 3: Yes, this is actually great question. And I'm reading this
36:02
Speaker 3: little white paper, a slash book called Situational Awareness, which
36:07
Speaker 3: I recommend to all of your listeners. Uh. This is
36:10
Speaker 3: a researcher who used to work at open AI and
36:14
Speaker 3: he has written this long essay or slash or you
36:19
Speaker 3: know book talking about the path forward on AI. And
36:24
Speaker 3: there is a one sentence in that intro that really
36:27
Speaker 3: sort of you know, made me curious. He says, everyone
36:33
Speaker 3: is now talking about AI, but few have the faintest
36:36
Speaker 3: glimmer about what is about to hit them. Nvidia analysts
36:41
Speaker 3: still think twenty twenty four maybe close to the peak.
36:43
Speaker 3: Mainstream pundits are stuck on the idea of just predicting
36:47
Speaker 3: the next word. But they actually they think everything is
36:51
Speaker 3: going to be hype and business as usual. But actually
36:53
Speaker 3: we're going to look at another Internet scale technology change.
36:57
Speaker 3: And I think what he talks about in that essay
37:00
Speaker 3: is going to be very illuminating for people who won't
37:03
Speaker 3: understand the implications of all these different news that comes along.
37:07
Speaker 3: That we are actually proceeding exactly according to script in
37:11
Speaker 3: terms of what the scaling law would have predicted. So
37:15
Speaker 3: what happened last Monday should not be surprising to you know,
37:18
Speaker 3: people at all if they actually, you know, read this
37:21
Speaker 3: little book.
37:22
Speaker 1: So anyway, okay, well we will put the link to
37:25
Speaker 1: that in the show notes as well. I found that
37:28
Speaker 1: mildly terrifying, so I will I've got some long claim
37:31
Speaker 1: flights this way, I will make sure that I read
37:33
Speaker 1: it then. Steve, thank you so much for joining us today.
37:37
Speaker 2: We really appreciate it. That was fascinating.
37:39
Speaker 3: Thank you very much for the conversation, Marie.
37:47
Speaker 2: Thanks for listening to this week's Marryn Talks Money.
37:49
Speaker 1: If you like us, share, rate, review, and subscribe wherever
37:51
Speaker 1: you listen to podcasts, and keep sending your questions or
37:54
Speaker 1: comments to Marryn Money at Bloomberg dot net. You can
37:56
Speaker 1: also follow me and John on Twitter or ex I'm
37:58
Speaker 1: at marins w and.
38:00
Speaker 2: John is at john Underscore Staffic.
38:02
Speaker 1: You can follow Steve on at Steve hoe F that
38:05
Speaker 1: is s t e v e h o u F.
38:08
Speaker 1: This episode was hosted by me Maren Sunset Web the
38:11
Speaker 1: shows produced by Someuersadi and Moses and sound designed by
38:14
Speaker 1: Blake Maples.
38:15
Speaker 2: Special thanks to Steve Howe