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Speaker 1: Bloomberg Audio Studios, Podcasts, radio News. This is Masters in

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Speaker 1: Business with Barry Ritholts on Bloomberg Radio.

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Speaker 2: This week on the podcast, I have yet another extra

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Speaker 2: special guest, Miller Value Funds, Bill Miller the fourth. He

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Speaker 2: is the son of Bill Miller, the third, fascinating investor,

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Speaker 2: portfolio manager, and World Series of poker player. They have

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Speaker 2: a very unique approach to value. It's not your traditional

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Speaker 2: just buy him cheap. I thought this conversation was fascinating

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Speaker 2: and I think you will also with no further ado,

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Speaker 2: my conversation with Miller Value Funds.

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Speaker 3: Bill Miller, thanks for having me. It's great to be here.

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Speaker 2: So I want to talk about your investment philosophy, what

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Speaker 2: you're doing at Miller Value today. But let's roll back

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Speaker 2: a little bit. Beforehand. You get a degree in economics

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Speaker 2: from Toughts and then an MBA from Dartmouth Talk School

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Speaker 2: of Business. Was investing the original career plan.

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Speaker 3: No, it wasn't the original career plan. You know. When

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Speaker 3: I was growing up went to a small private boys

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Speaker 3: school in Baltimore, Maryland. Never really knew what I wanted

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Speaker 3: to be when I grew up. But when I pointed

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Speaker 3: out to my parents. They said, we'll just consider school

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Speaker 3: as your job, and the harder you study, the more

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Speaker 3: options you'll have down the line, and it'll help you

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Speaker 3: figure it out.

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Speaker 2: So that sounds like pretty good advice.

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Speaker 3: I followed it. It did well academically in school. So

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Speaker 3: when I went to Toughts, I think the primary concern

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Speaker 3: was somewhere where I could actually play baseball. So growing

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Speaker 3: up with a huge Orioles fan, that was something that

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Speaker 3: my dad and I often did together. He was my

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Speaker 3: coach and little league something I'm doing now today for

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Speaker 3: my son. Sports teach you a lot about being on

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Speaker 3: a team, about how to operate, how to internalize which

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Speaker 3: you can and control what you can and not focus

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Speaker 3: on the rest. So learned a lot from that.

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Speaker 2: Did you play baseball in college?

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Speaker 3: Yeah, but I wasn't very good, so I learned that

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Speaker 3: pretty quickly. I played.

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Speaker 2: Difference between the guys who are good and really good

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Speaker 2: is so tiny, Just like a little wood on the

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Speaker 2: bat once or twice more a week and you're in

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Speaker 2: a different tier exactly, Right's fascinating.

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Speaker 3: Yeah, And you know, I probably deluded myself for a

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Speaker 3: while about how good I could be. But I also

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Speaker 3: probably didn't focus on the right things, and knowing what

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Speaker 3: I know now about how to get better and improve

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Speaker 3: with things, I could have been much more systematic about

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Speaker 3: it than I was.

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Speaker 2: Huh, So you start your career at Mackenzie Why consulting?

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Speaker 2: What led to that?

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Speaker 3: Yeah? Well, so I interned for my dad's group in college,

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Speaker 3: loved it, learned a lot. But then you know, on campus,

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Speaker 3: scrooting came along and McKinsey was one of the names,

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Speaker 3: and I just applied to it, did a little work

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Speaker 3: on it, and made it through that interview process. It's

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Speaker 3: pretty rigorous, and I got an offer from McKenzie and

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Speaker 3: I said, hey, Dad, I love being with your group.

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Speaker 3: Investing is a lot of fun. You know, what would

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Speaker 3: you do if you were me? And he said, well,

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Speaker 3: you can always tell McKenzie you can always come back

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Speaker 3: and work for me. But if you tell Mackenzie no,

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Speaker 3: you'll never have a chance to work there again. So

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Speaker 3: it was this concept of optionality again. And also there

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Speaker 3: was he knew and I didn't know at the time,

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Speaker 3: but they placed an immense amount of focus on professional development,

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Speaker 3: and so that was a really valuable place to spend

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Speaker 3: the first three years of my career. So I was

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Speaker 3: working on a huge variety of consulting projects, mainly Actually

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Speaker 3: the job I had there now I don't know if

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Speaker 3: it exists because of AI. So what I was doing

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Speaker 3: was remotely supporting teams on research efforts and deep dives

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Speaker 3: on stuff which now you just ask chat GBT about

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Speaker 3: and he probably does a better job summarizing everything I

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Speaker 3: could possibly do.

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Speaker 2: And you know, assuming it's accurate, which is always a

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Speaker 2: little bit of an ef.

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Speaker 3: Right, that is a big if for sure. Yeah, focusing

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Speaker 3: on primary sources is still a critical skill that I

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Speaker 3: think a lot of people under emphasis.

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Speaker 2: What you take from your years consulting that showed up

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Speaker 2: and as helpful as an investor.

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Speaker 3: You know. One of the things this might surprise you

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Speaker 3: less so about the data driven nature, because my dad's

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Speaker 3: a data driven thinker and thinking quantitatively has always been

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Speaker 3: in my wheelhouse. But the thing that I learned in

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Speaker 3: McKenzie more than anywhere else with me to focus on

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Speaker 3: client service and how to interact with people, how to

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Speaker 3: do the subtle things that show you know somebody else

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Speaker 3: as the client. In finance, you know, when you're managing money,

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Speaker 3: it's very hard to differentiate yourself and that you know

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Speaker 3: Ken French, who was a professor of mine at.

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Speaker 2: Famous Farm of French Factor model at Dartmouth.

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Speaker 3: Sure you got exactly. One of the things he imparted

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Speaker 3: on us was how long does it take to know

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Speaker 3: if a money manager is actually any good? And the

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Speaker 3: answer is from us, a statistically significant basis longer than

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Speaker 3: any money manager's career.

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Speaker 2: Right, So I'm going to say ten years, twenty.

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Speaker 3: Years, it's twenty plus for to see if it's statistically significant, right,

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Speaker 3: So you have to be doing other things. It's like

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Speaker 3: we were talking about before we came in here. Content's

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Speaker 3: a big focus, right, That's a way to differentiate yourself,

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Speaker 3: the way you communicate with clients, getting back to them quickly.

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Speaker 3: All of these things are really important. And I learned

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Speaker 3: those at Mackenzie. And I'm not sure I would have

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Speaker 3: learned those to the same extent if I had just

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Speaker 3: directly joined my dad's firm. So that might be a

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Speaker 3: surprising answer, but it is a no.

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Speaker 2: It's really really interesting. So Mackenzie was a solid place

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Speaker 2: to get grounded. What led to the pivot to investing

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Speaker 2: LADO seven?

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Speaker 3: Wait? Yeah, so in Mackenzie we were effectively handing over

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Speaker 3: analyses to clients and then leaving and moving on to

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Speaker 3: the next analysis. And it occurred to me that if

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Speaker 3: you actually wanted to build any equity in your analysis

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Speaker 3: and what you were doing, you had to actually take

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Speaker 3: a real stake in something. And so that made me think, Okay,

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Speaker 3: you know this is it'd be a great time to

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Speaker 3: pivot from what I was doing at Mackenzie to my

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Speaker 3: dad's side of things, where that's exactly what you're doing

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Speaker 3: all day, every day, excuse me. And then I also

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Speaker 3: during college I a liking to poker and so played

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Speaker 3: a lot in no limit hold and back then Poker

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Speaker 3: Stars was kind of an a legal gray area, and

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Speaker 3: so I played a lot online and I saw a

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Speaker 3: lot of similarities between what my dad did poker analytical

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Speaker 3: edge in terms of thinking quantitatively at Mackenzie, and it

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Speaker 3: all kind of came around to moving in that direction.

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Speaker 2: So, speaking of your father, how did growing up in

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Speaker 2: the Bill Miller household influence how you look at risk

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Speaker 2: and reward at investing at how big of an influence

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Speaker 2: was he on your initial philosophy?

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Speaker 3: I think he's most of it. It's hard for me

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Speaker 3: to specifically say A, B and C because it was

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Speaker 3: as much learning from watching him and how he operated.

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Speaker 3: So Number one, he was always always had a stack

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Speaker 3: of research and was always going through content, always looking

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Speaker 3: for new perspectives. He's a relentless truth seeker. And I

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Speaker 3: think that's ultimately what we're doing his investors is trying

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Speaker 3: to separate where the truth is from where the perception

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Speaker 3: is around what's going to happen. And the bigger the gap,

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Speaker 3: the where you want to place a bet.

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Speaker 2: That variant perception is really important, is it exactly, especially

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Speaker 2: when that gap gets bigger and bigger.

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Speaker 3: Yeah, and especially if there's a you know, a margin

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Speaker 3: of safety there to protect you on the downside. So

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Speaker 3: relentless truth seeking. And the other thing is, you know,

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Speaker 3: there were no shortcuts for him. There's no there's no

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Speaker 3: substitute for actually putting in the time to going through

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Speaker 3: that content all the time and being in front of

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Speaker 3: your machine all day and just time is the ultimate

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Speaker 3: resource and constraint for everyone. And so thinking in blocks

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Speaker 3: of time and thinking how to maximize your productivity per

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Speaker 3: unit of time, I think is something that I took

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Speaker 3: away from.

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Speaker 2: Him really really interesting. So going back to the family business,

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Speaker 2: that's a pretty loaded concept for a lot of people.

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Speaker 2: What was it like first going back to work with

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Speaker 2: your father and then becoming the controlling owner of Miller

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Speaker 2: Value Partners.

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Speaker 3: It was fantastic because we were a small group at

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Speaker 3: LEG for a good period of time, probably from twenty

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Speaker 3: thirteen or twenty fourteen until we split off and went independent,

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Speaker 3: and I think it was twenty nineteen or so. So

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Speaker 3: got to work with my dad very closely a lot,

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Speaker 3: you know. But at the same time, one of the

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Speaker 3: things I love about it is the market doesn't really

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Speaker 3: care what he did or didn't do, and ultimately, now

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Speaker 3: that I'm in charge of the portfolios, it'll hinge upon

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Speaker 3: my decision making more so than what he did, and

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Speaker 3: so it's on me to now take everything I've learned

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Speaker 3: and run with it and do what we can do.

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Speaker 2: Was your father a poker player? How did you find

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Speaker 2: your way into that?

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Speaker 3: No, he wasn't a poker player. It was when Chris

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Speaker 3: Moneymaker won the World Series. I don't know if you remember, sure,

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Speaker 3: I think it was maybe two or.

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Speaker 2: Three big funny glasses.

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Speaker 3: And he was an accountant actually, and so you know,

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Speaker 3: he stressed a lot of quantitative decision making and the

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Speaker 3: other thing I actually looked at coming out of tuck

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Speaker 3: was baseball operation stuff, because moneyball was a you know,

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Speaker 3: the whole analytical side was just coming around then. And

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Speaker 3: you know, I know you like to talk about mistakes,

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Speaker 3: but I think of specifically that recruiting process, my attitude

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Speaker 3: towards it, and just some mistakes I made there.

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Speaker 2: So well, we seem to learn more from our failures

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Speaker 2: than we do from our successes because we don't know

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Speaker 2: if our successes were the result of good fortune or skill.

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Speaker 2: If it takes twenty years to figure out which it is,

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Speaker 2: you're going to obviously learn more from the errors. Hey,

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Speaker 2: we know this was a bad choice, that's right, Or

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Speaker 2: was it a good choice with a bad outcome?

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Speaker 3: Well, I think in this case it was a you know,

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Speaker 3: the outcome was good because it was ultimately where I

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Speaker 3: was probably looking to wind up. But at that time

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Speaker 3: I was thinking, I want to do baseball. Baseball baseball,

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Speaker 3: you know I mentioned earlier I wasn't good enough to play.

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Speaker 3: I wanted to sort of use my analytical talents to

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Speaker 3: our talents, my analytical background and training to go into

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Speaker 3: the analytical side. And as I went through the recruiting process,

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Speaker 3: it became very clear that I was jumping through hoops

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Speaker 3: waiting for callbacks, and it was a very intense process,

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Speaker 3: and I realized that I was probably gonna be charting

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Speaker 3: pitches in Topeka at the end of it, which to

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Speaker 3: me didn't seem all that exciting. But in retrospect, if

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Speaker 3: you want to be in baseball operations, you should do

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Speaker 3: anything you possibly can to get your foot in the

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Speaker 3: door of these competitive businesses.

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Speaker 2: Let me point out a little over a decade ago

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Speaker 2: a kid became an intern in the NFL and he

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Speaker 2: just won the Super Bowl as head coach. So if

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Speaker 2: you really love it that much and you that committed,

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Speaker 2: I'm with you. I can't count pitches in Topeka.

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Speaker 3: I just right.

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Speaker 2: I mean yes, especially because you have how many other

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Speaker 2: people were in turns and they didn't head coach the

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Speaker 2: Super Bowl winner.

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Speaker 3: But it's funny because now I see that on the

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Speaker 3: other side, right, So I get LinkedIn's and messages all

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Speaker 3: the time. Hey, I'm a really good software analyst. I

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Speaker 3: want to come and work for you and be a

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Speaker 3: software analyst. And I'm like, we don't need a software

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Speaker 3: analyst right now. We need somebody that can go get

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Speaker 3: me a sandwich at lunchtime, you know, like so, But

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Speaker 3: I understand the perspective too. It's just that I think

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Speaker 3: if you want to become a member of a team,

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Speaker 3: you have to understand what the team needs and where

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Speaker 3: you can genuinely help, and it may not always necessarily

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Speaker 3: align with what you want to do. And I think

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Speaker 3: that's important to keep in mind.

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Speaker 2: Huh really really very interesting. So as long as we're

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Speaker 2: talking about all these career choices, if you were starting

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Speaker 2: out today, would you follow this a similar path to

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Speaker 2: what you did previously? Would you go a different rap?

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Speaker 3: I really like what I'm doing now, and I want

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Speaker 3: to do it indefinitely, so it's hard for me to

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Speaker 3: go back and say I would do something differently because

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Speaker 3: I'm where I want to be for the long term.

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Speaker 3: I do think one of the lesser considered paths that

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Speaker 3: a lot of undergrads don't think about would be actually

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Speaker 3: going into something entrepreneurial. H And I don't mean like

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Speaker 3: starting a startup that you're trying to scale from zero

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Speaker 3: to gajillion dollars over the next year, right, But that's

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Speaker 3: what people tend to think of because that's where all

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Speaker 3: the returns look like they are In reality, I think

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Speaker 3: potentially scaling a small services business, you know, whether that's powerwashing,

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Speaker 3: home cleaning, just things that where you can get your

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Speaker 3: arm around the fundamental service and scale that and make

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Speaker 3: it bigger is potentially a more a safer risk adjusted

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Speaker 3: way to a big outcome than people consider.

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Speaker 2: Just because you're learning a business from the ground up

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Speaker 2: and customer relations and all those other things.

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Speaker 3: Yeah. Well, you know, even in our business, it takes

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Speaker 3: time to build a track record, it takes time to

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Speaker 3: build the assets, and so anything you do where you're

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Speaker 3: gonna have a good outcome in the long run just

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Speaker 3: takes repetitive effort and the right focus. And so sometimes

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Speaker 3: the learning around something that you can get your arms

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Speaker 3: around can be easier than the learning around to software

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Speaker 3: development or you know, scaling a big fund or things

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Speaker 3: like that.

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Speaker 2: So really really interesting. Coming up, we continue our conversation

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Speaker 2: with Bill Miller, the Fourth Miller Value Fund's chief investment officer,

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Speaker 2: talking about his investment philosophy.

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Speaker 3: I'm Barry Dults.

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Speaker 2: You're listening to Masters in Business on Bloomberg Radio. I'm

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Speaker 2: Barry Ridults. You're listening to Masters in Business on Bloomberg Radio.

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Speaker 2: My extra special guest today is Bill Miller. He is

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Speaker 2: the chief investment officer and portfolio manager of Miller Value Fund,

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Speaker 2: where he works with his famous father, Bill Miller the Third.

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Speaker 2: So let's talk about your investment philosophy separate from your dad's,

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Speaker 2: starting with how do you defe f value in a

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Speaker 2: world where a lot of the traditional metrics like price

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Speaker 2: to earnings or price to book seem to have been

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Speaker 2: downgraded somewhat, perhaps they don't fully capture modern intellectual property

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Speaker 2: based business models. How do you think about those?

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Speaker 3: Yeah, I think you have to have a flexible definition

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Speaker 3: of value and that if it's just based on accounting figures,

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Speaker 3: you're probably not going to do very well over the

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Speaker 3: long run. Because if you look at some of the

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Speaker 3: best performing assets stocks of all time, they never look

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Speaker 3: cheap just because they have such a right tail and

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Speaker 3: they compound with very you know, they're investing all their

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Speaker 3: earnings and they're constantly seeking to grow that edge, and

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Speaker 3: so solely focusing on accounting factors is not a great

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Speaker 3: way to capture long term value or outperformers, although it

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Speaker 3: can be. You know, we have a strategy where whereby

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Speaker 3: by business partner Dan Leisac has this collection of ten

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Speaker 3: or twelve names that look insanely cheap on these metrics,

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Speaker 3: So you can do there's a lot of different ways

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Speaker 3: to skin the cat.

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Speaker 2: So what are the different thought processs around defining value?

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Speaker 2: So cheap but not broken is obviously what your partner

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Speaker 2: is focusing on. How do you contextualize things like Amazon

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Speaker 2: or in Video or Google which have looked expensive for

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Speaker 2: ten years and have just shot the lights out.

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Speaker 3: Yeah. Well, in the case of Amazon, they started with

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Speaker 3: a very small idea around just selling books online and

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Speaker 3: it was you know, it ended up being this retail

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Speaker 3: juggernaut just because if you look at now that the

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Speaker 3: distribution logistics networks that they've used to fulfill their orders,

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Speaker 3: it's just a it's a network that can't be touched, right,

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Speaker 3: and it's everything store And it depends on the actual scenario. So,

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Speaker 3: you know, one of the things that I've been vocal

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Speaker 3: about now for probably ten years is our view the

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Speaker 3: bitcoin is still a massively undervalue technology. And so that

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Speaker 3: would be one where you probably say, well, it has

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Speaker 3: no cash flows, it's you know, speculative, it's based upon

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Speaker 3: other people's beliefs, and I'd say that's exactly right. It

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Speaker 3: is based upon other people's beliefs, but other people don't

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Speaker 3: haven't yet come around to the view that it is

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Speaker 3: a functionally superior technology to gold. It's a form of

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Speaker 3: capital governance. I think it requires a lot of different lenses.

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Speaker 3: Right when we say we have flexible definition of value,

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Speaker 3: you have to approach things from a variety of different perspectives.

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Speaker 3: In this case, one of the reasons I think bitcoin

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Speaker 3: is so interesting and compelling seventeen years in you know,

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Speaker 3: it's gone from this weird technology on the Internet that

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Speaker 3: only criminals used to now it's collateral for loans in

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Speaker 3: our modern day financial system, right, And so what explains that, well,

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Speaker 3: markets explained it to an extent, and that people are

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Speaker 3: increasingly coming around to view it as an interesting place

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Speaker 3: to put money in, an interesting capital governance system. It's

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Speaker 3: totally separate from the fiat systems that everyone has known

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Speaker 3: for their entire lifetimes in multiple centuries before us. It

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Speaker 3: wasn't possible prior to nine or twenty ten when the

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Speaker 3: White Paper came out, And so now you've got this

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Speaker 3: new emerging system of capital governance that I think it's

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Speaker 3: one of the most dynamic areas of finance in general,

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Speaker 3: as a matter of fact. So it's an area I'm

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Speaker 3: very optimistic about over the long term bounce around. It'll

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Speaker 3: be volatile, but I think it's headed to much bigger places.

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Speaker 2: So we're recording this the day after it briefly broke

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Speaker 2: sixty thousand. Are you a buyer of bitcoin at these prices.

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Speaker 3: Yes, So it's a big part of my personal financial situation.

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Speaker 3: In one of our MVPA it's roughly or digital assets

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Speaker 3: collectively are about ten percent of that fund.

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Speaker 2: So we'll talk more about state of markets in a

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Speaker 2: little bit. Let's stay with the concept of Philosophically, this

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Speaker 2: is an interesting technology. I've described this as stop thinking

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Speaker 2: as a unique asset class. I think of it as hey,

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Speaker 2: it's somewhere between Facebook and Google, between Meta and Alphabet

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Speaker 2: as a technology company, which gives it a little more perspective.

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Speaker 2: But at the same time, it came out around the

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Speaker 2: same time as an iPhone, and I would never give

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Speaker 2: up my iPhone. I don't know how I would my

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Speaker 2: train tickets, my plane tickets, my communication, my portfolio, everything

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Speaker 2: I do I do on this. If bitcoin were to

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Speaker 2: disappear tomorrow, it wouldn't affect my life in the least

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Speaker 2: why is it that seventeen years in we're still waiting

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Speaker 2: for this to gain broad usefulness. I'm still waiting for

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Speaker 2: smart tickets that cut out stub hub and those guys,

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Speaker 2: and all sorts of technological uses that I heard about

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Speaker 2: five ten years ago but still haven't happened. What's the

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Speaker 2: response to the skeptics?

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Speaker 3: Well, so, if you look at the introduction of running

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Speaker 3: water in households, it took one hundred years for it

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Speaker 3: to go from possibility to ubiquitous, okay, and that was

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Speaker 3: a clearly better technology than using an out house or

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Speaker 3: boiling water to put it on unite or whatever. So

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Speaker 3: this this is an entirely new idea. And again from

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Speaker 3: my perspective, it's a capital denominator. It's not a numerator,

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Speaker 3: it's a capital denominator. So it's Bitcoin is a denominator

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Speaker 3: for capital. And the reason I think it's so superior

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Speaker 3: to what we've known before is that money the way

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Speaker 3: it works right now, it's ultimately backed by this the

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Speaker 3: threat of state ordered.

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Speaker 2: Violence, standing army and a set of laws.

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Speaker 3: Right, that's right, you know you don't pay your taxes,

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Speaker 3: We'll throw it in a box and lock the key away.

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Speaker 3: I'll throw the key away. But this and if you

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Speaker 3: think about actually around the world, the countries you want

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Speaker 3: to visit, most of them are going to have stability

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Speaker 3: of process and rule of law, right, And the places

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Speaker 3: where that's not the case, there's a much there's a

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Speaker 3: much less distinct, much less a distinction between who controls

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Speaker 3: the ledger and who controls the guns. So the farther

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Speaker 3: apart those two things are the better. So in this case,

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Speaker 3: we now have a distinct ledger entirely apart from any state,

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Speaker 3: and its units can't be controlled by anyone, right in

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Speaker 3: that they're controlled by actual energy. So you need to

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Speaker 3: have energy to crank out a new bitcoin, because that's

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Speaker 3: what the whole mining process is about, right, You verify

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Speaker 3: a transaction. Takes a lot of energy to do that,

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Speaker 3: and in exchange for expending that energy, you get more bitcoin.

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Speaker 3: That's a minor reward, right right. So this is a

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Speaker 3: capital denominator whereby energy input is actually required to create

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Speaker 3: new units. What happens now. What happens now is somebody,

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Speaker 3: you know, a bunch of congress people sign something fed

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Speaker 3: goes and prints money to keep roughly rates roughly in

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Speaker 3: line prices roughly stable, employment, roughly full, and so it's

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Speaker 3: it's there's still some issues with that from a process perspective, right,

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Speaker 3: so they're trying to control the money supply to come,

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Speaker 3: engineer outcomes as opposed to having a fair set of

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Speaker 3: value that we all agree upon. Right, this is a

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Speaker 3: valuable thing because it takes energy to produce and having

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Speaker 3: that be the arbiter of value. And so if you

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Speaker 3: look at the political process today, it's a process issue

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Speaker 3: more than anything else, and that oftentimes the least accountable

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Speaker 3: party ends up winning an office because of all the

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Speaker 3: promises they make and what happens then, well more units

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Speaker 3: get printed, right, and they just get printed and printed

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Speaker 3: over time, and that's what ultimately causes inflation. And it's

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Speaker 3: you know, it's not a red issue or blue issue.

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Speaker 3: Most of the time, Republicans are cutting taxes in a

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Speaker 3: way that probably doesn't make sense from a systemic perspective.

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Speaker 3: At the other side of the equation, oftentimes the blue

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Speaker 3: side of the aisle increases in titlements right without an offset,

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Speaker 3: and so both of those are bad things for the

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Speaker 3: for the overall medium through which we transact over time.

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Speaker 3: And so now you've got a system that offers a

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Speaker 3: promise of effectively cutting that whole. The clown show is

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Speaker 3: like sometimes out entirely, so you look like you're not

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Speaker 3: believing it.

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Speaker 2: Well, you know, I don't care about deficits. Since the

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Speaker 2: past fifty years, I've been hearing about the problem with

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Speaker 2: printing money, and everything that we were warned against didn't happen.

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Speaker 2: The dollar hasn't devalued, we haven't had hyperinflation, we haven't

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Speaker 2: crowded out private capital, and you could still lend money

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Speaker 2: to Uncle Sam at historically low rates if you want

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Speaker 2: three and a half four percent as a yield. So

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Speaker 2: all the warnings about printing money and deficits have been

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Speaker 2: you know, the boy who crolled cried wolf for half

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Speaker 2: a century. So there's that, and then there's okay, So

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Speaker 2: here's an idea that we can what do we limit

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Speaker 2: it to twenty four million twenty one million coins?

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Speaker 1: And that.

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Speaker 2: Scarcity creates value. I understand it's virtual. I understand the

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Speaker 2: advantages of having things be purely digital from conception forward.

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Speaker 2: I have a hard time getting past the criminality and

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Speaker 2: the pig butchering and the blackmail. That that's a little

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Speaker 2: problematic and it's sort of like democracy, all the other

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Speaker 2: you know, it's the worst system except all the others. Well,

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Speaker 2: a central bank and a government that make sure we're

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Speaker 2: doing something within reason is better than just opening it

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00:23:34,359 --> 00:23:37,280
Speaker 2: up to the wild west, which is what this seems

438
00:23:37,320 --> 00:23:40,640
Speaker 2: to have been for a long time. The US did

439
00:23:41,200 --> 00:23:46,520
Speaker 2: was pretty aggressive in embracing it, especially this administration, and

440
00:23:46,640 --> 00:23:50,400
Speaker 2: it seems to have speculatively run up in anticipation from that.

441
00:23:51,000 --> 00:23:53,439
Speaker 2: And you know, once it was all in the price,

442
00:23:54,440 --> 00:23:57,640
Speaker 2: you know, we got cut in half. It's when you're

443
00:23:57,640 --> 00:24:01,200
Speaker 2: talking about stability. Yeah, the US dollar was down nine

444
00:24:01,240 --> 00:24:04,600
Speaker 2: percent in twenty twenty five, not cut in half. This

445
00:24:04,680 --> 00:24:08,760
Speaker 2: is a giant whack in you know, less than six months.

446
00:24:09,240 --> 00:24:12,400
Speaker 2: So I have a hard time just wrapping my head around, Oh,

447
00:24:12,480 --> 00:24:16,760
Speaker 2: the source of stability is something with no fundamental value

448
00:24:16,840 --> 00:24:22,359
Speaker 2: but swinging wildly up and down. So I'm I'm not

449
00:24:22,440 --> 00:24:24,880
Speaker 2: as negative about it as a lot of people are.

450
00:24:24,920 --> 00:24:29,760
Speaker 2: I was really negative about the NFTs and Mike, which, wait,

451
00:24:29,800 --> 00:24:33,080
Speaker 2: you want to take something with literally no value and

452
00:24:33,160 --> 00:24:37,440
Speaker 2: totally reproducible, and like I understood the idea of hey,

453
00:24:37,440 --> 00:24:40,399
Speaker 2: you're gonna buy a ten thousand dollars burken bag, and

454
00:24:40,480 --> 00:24:43,439
Speaker 2: here's a unique identifier on the blockchain. All right, that

455
00:24:43,600 --> 00:24:48,960
Speaker 2: made some sense, but not sixty eight million dollars. This

456
00:24:49,080 --> 00:24:52,120
Speaker 2: is sort of crazy prices he's traded at. So there

457
00:24:52,160 --> 00:24:56,000
Speaker 2: seems to be a lot of speculative excess that get

458
00:24:56,000 --> 00:25:00,879
Speaker 2: in the way of the technological story underneath.

459
00:25:01,920 --> 00:25:03,760
Speaker 3: Yeah, and you think you bring up a good point

460
00:25:03,760 --> 00:25:05,560
Speaker 3: with regard to the United States and the depths. It's

461
00:25:05,600 --> 00:25:08,160
Speaker 3: not making a big impact, and that's because we are

462
00:25:08,200 --> 00:25:11,280
Speaker 3: the best house in a bad neighborhood. From a fiat perspective,

463
00:25:11,280 --> 00:25:13,959
Speaker 3: I mean, we have the reason that America is the

464
00:25:14,000 --> 00:25:17,639
Speaker 3: most desire place to be. From an immigration perspective, I

465
00:25:17,640 --> 00:25:21,040
Speaker 3: think we have four time multiples the number of immigrants

466
00:25:21,680 --> 00:25:24,640
Speaker 3: as the next fore closest countries combined. Again, that comes

467
00:25:24,680 --> 00:25:28,200
Speaker 3: down to stability of process, rule of law, and property rights.

468
00:25:28,680 --> 00:25:31,000
Speaker 3: And so if there's now a form of currency that

469
00:25:31,119 --> 00:25:35,040
Speaker 3: wasn't possible fifty twenty years ago, call it that has

470
00:25:35,359 --> 00:25:38,640
Speaker 3: more stability a process and more certainty around property rights

471
00:25:38,640 --> 00:25:42,200
Speaker 3: over the long term. I think it's an education issue

472
00:25:42,280 --> 00:25:46,760
Speaker 3: as much as anything else interesting, and people may not

473
00:25:46,800 --> 00:25:49,240
Speaker 3: come around to that view, But from my perspective, the

474
00:25:49,320 --> 00:25:53,679
Speaker 3: quantitative inevitability of the technology is pretty compelling when you

475
00:25:53,720 --> 00:25:56,920
Speaker 3: look at just the Bitcoin versus gold. Right, Gold's done

476
00:25:56,960 --> 00:25:58,639
Speaker 3: amazing in the past year. I get it, it's a

477
00:25:58,720 --> 00:26:01,959
Speaker 3: deep part of the debasement, tit. Bitcoin hasn't. But when

478
00:26:02,000 --> 00:26:05,800
Speaker 3: you think about you know, if gold is the predominant

479
00:26:05,880 --> 00:26:10,119
Speaker 3: check and balance on Fiat, fiat's a lack of accountability.

480
00:26:10,640 --> 00:26:14,680
Speaker 3: And then you look at the functional attributes of bitcoin,

481
00:26:14,760 --> 00:26:16,119
Speaker 3: it's so far superior to gold.

482
00:26:16,240 --> 00:26:19,280
Speaker 2: So you join, like Mason in eight, pretty much right

483
00:26:19,320 --> 00:26:22,399
Speaker 2: in the middle of the financial crisis. How did that

484
00:26:22,440 --> 00:26:29,320
Speaker 2: experience shape your perspective on investing and in particular on value.

485
00:26:30,440 --> 00:26:33,520
Speaker 3: Wow's start with a hard hitting question here. So that

486
00:26:33,640 --> 00:26:35,760
Speaker 3: was a as you point out, I joined right at

487
00:26:35,800 --> 00:26:39,080
Speaker 3: the top. I think when I joined Capital Management there

488
00:26:39,119 --> 00:26:42,600
Speaker 3: were roughly one hundred and fifty people working there, and

489
00:26:42,640 --> 00:26:50,200
Speaker 3: then by the time you know, Capital Management merged with Clearbridge,

490
00:26:50,359 --> 00:26:53,200
Speaker 3: there were a substantially fewer number of people working there,

491
00:26:53,240 --> 00:26:58,399
Speaker 3: just because assets flew out the door, performance struggled, and

492
00:26:59,080 --> 00:27:01,960
Speaker 3: you know, it could be a pretty ugly compounding effect

493
00:27:02,000 --> 00:27:02,879
Speaker 3: on an asset manager.

494
00:27:02,920 --> 00:27:06,679
Speaker 2: So for sure, by the way, that story was pretty

495
00:27:06,720 --> 00:27:08,520
Speaker 2: much ubiquitous throughout finance.

496
00:27:09,440 --> 00:27:11,760
Speaker 3: Yeah, and so I think that taught me you know,

497
00:27:12,080 --> 00:27:14,880
Speaker 3: you to run one of these businesses, you obviously want

498
00:27:14,920 --> 00:27:18,800
Speaker 3: to have some extra gas in the tank. You know,

499
00:27:18,880 --> 00:27:21,520
Speaker 3: at all times you want to you don't want to

500
00:27:21,600 --> 00:27:25,479
Speaker 3: run it too thin from an operating capital perspective, if

501
00:27:25,520 --> 00:27:29,080
Speaker 3: you want to build it for the long term. And

502
00:27:29,160 --> 00:27:31,919
Speaker 3: so it's a good idea to keep those fixed costs

503
00:27:31,920 --> 00:27:33,760
Speaker 3: lower than you might even anticipate.

504
00:27:34,320 --> 00:27:37,280
Speaker 2: So let's talk about building on that. You come out

505
00:27:37,320 --> 00:27:41,600
Speaker 2: of the financial crisis, you get your CFA soon after

506
00:27:41,680 --> 00:27:44,360
Speaker 2: twenty eleven, something like that, that sounds right, and then

507
00:27:45,000 --> 00:27:50,240
Speaker 2: become a Chartered market technician in twenty eighteen. Unusual combination.

508
00:27:50,960 --> 00:27:52,960
Speaker 2: Tell us why you went that route.

509
00:27:53,560 --> 00:27:57,400
Speaker 3: Yeah, So the analogy I make is if the CFA

510
00:27:57,560 --> 00:27:59,840
Speaker 3: teaches you to play your cards on the poker table,

511
00:28:00,160 --> 00:28:02,199
Speaker 3: CMT teaches you to play the other players at the

512
00:28:02,200 --> 00:28:06,480
Speaker 3: poker table, and that one of the interesting things about

513
00:28:06,480 --> 00:28:08,640
Speaker 3: the CMT is number one, it takes a lot less

514
00:28:08,640 --> 00:28:12,280
Speaker 3: time than the CFA. But number two, I use that

515
00:28:12,119 --> 00:28:14,399
Speaker 3: in that some of the teachings from that more often

516
00:28:14,440 --> 00:28:15,600
Speaker 3: now than I use the CFA.

517
00:28:16,080 --> 00:28:19,399
Speaker 2: It's funny the way you described it. I always thought

518
00:28:19,400 --> 00:28:24,280
Speaker 2: the difference was financial analysts tell you what to buy.

519
00:28:24,560 --> 00:28:26,120
Speaker 2: Technicians tell you when to buy.

520
00:28:26,480 --> 00:28:29,199
Speaker 3: Well, I think that's accurate as well. Yeah, and so

521
00:28:29,359 --> 00:28:31,159
Speaker 3: one of the things that it's very easy to do

522
00:28:31,160 --> 00:28:33,879
Speaker 3: as a value investor to see multiples coming down and

523
00:28:33,880 --> 00:28:35,480
Speaker 3: a stock going down, you go, why this is way

524
00:28:35,480 --> 00:28:38,840
Speaker 3: too cheap, and reality is that it could just keep

525
00:28:38,840 --> 00:28:40,840
Speaker 3: going down because it's going down and people are selling it,

526
00:28:40,880 --> 00:28:42,640
Speaker 3: and you have to be able to read that on

527
00:28:42,680 --> 00:28:45,240
Speaker 3: the chart and when the volumes change and when the

528
00:28:45,960 --> 00:28:48,400
Speaker 3: investor behavior changes. So it teaches you to look at

529
00:28:48,400 --> 00:28:50,960
Speaker 3: investor behavior. It teaches you how to figure out what

530
00:28:51,000 --> 00:28:55,440
Speaker 3: other investors are thinking based upon price trends, in action,

531
00:28:55,880 --> 00:28:59,360
Speaker 3: and volume, and it's been a really valuable skill set

532
00:28:59,400 --> 00:29:00,960
Speaker 3: and compliment the CFA.

533
00:29:01,040 --> 00:29:04,800
Speaker 2: So walk us through your process from I DEA generation

534
00:29:05,000 --> 00:29:09,080
Speaker 2: to execution and position sizing. What sort of steps do

535
00:29:09,080 --> 00:29:10,400
Speaker 2: you have to work your way through?

536
00:29:11,280 --> 00:29:12,920
Speaker 3: Well, I think a lot of it starts with the

537
00:29:13,000 --> 00:29:16,760
Speaker 3: appreciation that most assets are efficiently priced. Right, so we

538
00:29:16,840 --> 00:29:19,560
Speaker 3: have a portfolio of things that we believe are undervalued,

539
00:29:20,720 --> 00:29:24,560
Speaker 3: and so all day, every day, we're constantly running through screens.

540
00:29:24,640 --> 00:29:28,120
Speaker 3: We're reading research, we're looking at price movements, we're looking

541
00:29:28,120 --> 00:29:31,880
Speaker 3: at insider action. A lot of the time, whether insiders

542
00:29:31,880 --> 00:29:36,080
Speaker 3: are buying or selling to potentially point something out to us,

543
00:29:37,120 --> 00:29:39,520
Speaker 3: But then we have to then once we identify something

544
00:29:39,520 --> 00:29:42,160
Speaker 3: that looks interesting, it has to then be better than

545
00:29:42,200 --> 00:29:45,720
Speaker 3: what else we have in the portfolio. So we have

546
00:29:46,280 --> 00:29:48,640
Speaker 3: a group of things that we own and like, but

547
00:29:48,720 --> 00:29:51,640
Speaker 3: at the same time, we're constantly comparing new ideas to

548
00:29:51,640 --> 00:29:53,840
Speaker 3: see if it can be a fit coming to the portfolio.

549
00:29:54,320 --> 00:29:56,920
Speaker 3: And so how we make changes is going to be

550
00:29:57,080 --> 00:30:01,000
Speaker 3: obviously directly relevant to that thesis. In some cases, we'll

551
00:30:01,000 --> 00:30:04,480
Speaker 3: have a name that the investment these has completely changed

552
00:30:04,480 --> 00:30:07,320
Speaker 3: with the latest earnings report or something went out the window,

553
00:30:07,320 --> 00:30:09,440
Speaker 3: and then we'll have an ability to either add something

554
00:30:09,480 --> 00:30:13,000
Speaker 3: new or bump something up. But it's always about constantly

555
00:30:13,000 --> 00:30:15,440
Speaker 3: looking for new ideas that could be undervalued and then

556
00:30:15,480 --> 00:30:17,680
Speaker 3: trying to figure out the right way to wait them.

557
00:30:17,760 --> 00:30:20,800
Speaker 3: Because there's unconstrained investors. All of our torque isn't a

558
00:30:20,840 --> 00:30:25,640
Speaker 3: position sizing in the weights. So you know, we made

559
00:30:25,640 --> 00:30:28,600
Speaker 3: a lot of mistakes, and oftentimes the answer to those

560
00:30:28,600 --> 00:30:30,719
Speaker 3: mistakes is sitting right in our portfolio. You know, it

561
00:30:30,760 --> 00:30:32,720
Speaker 3: almost always is we should done more of that and

562
00:30:32,800 --> 00:30:34,840
Speaker 3: less of that, And so I spent a lot of

563
00:30:34,880 --> 00:30:37,080
Speaker 3: time just going through the portfolio and figuring out where

564
00:30:37,080 --> 00:30:39,440
Speaker 3: the relative weights should be. But I would say at

565
00:30:39,440 --> 00:30:43,200
Speaker 3: a high level, probabilistic fundamental value.

566
00:30:44,320 --> 00:30:48,080
Speaker 2: Probabilistic fundamental value, all right, I like that phrase. When

567
00:30:48,120 --> 00:30:52,280
Speaker 2: you're looking at fundamental values, how do you distinguish between

568
00:30:52,320 --> 00:30:58,160
Speaker 2: something that's only temporarily out of favor, temporarily hated to Oh,

569
00:30:58,200 --> 00:31:01,640
Speaker 2: this business model is structurally broken. How do you avoid

570
00:31:01,680 --> 00:31:03,080
Speaker 2: the classic value traps?

571
00:31:03,920 --> 00:31:09,560
Speaker 3: Well, we don't always unfortunately, you know, and just because

572
00:31:09,560 --> 00:31:12,400
Speaker 3: something is undervalue doesn't mean that other people are going

573
00:31:12,440 --> 00:31:14,120
Speaker 3: to agree that it's undervalue. So I think that's an

574
00:31:14,120 --> 00:31:17,880
Speaker 3: important thing to keep in mind too. And it's important

575
00:31:17,920 --> 00:31:20,760
Speaker 3: to use the markets to help you figure out how

576
00:31:20,760 --> 00:31:23,480
Speaker 3: to change your position sizes. Sometimes you start legging into

577
00:31:23,520 --> 00:31:26,160
Speaker 3: something and it just keeps going down. You should probably

578
00:31:27,040 --> 00:31:30,160
Speaker 3: heed the markets feedback a lot of the time relative

579
00:31:30,200 --> 00:31:33,880
Speaker 3: to your own positions in their sizes. So one of

580
00:31:33,960 --> 00:31:36,320
Speaker 3: the key reports that my dad looked at every day

581
00:31:36,840 --> 00:31:39,240
Speaker 3: I still look at every day is our daily Performance report,

582
00:31:39,320 --> 00:31:43,080
Speaker 3: And basically it just has the entire portfolio ranked by weight,

583
00:31:43,560 --> 00:31:46,320
Speaker 3: and then how it's done over the past day, how

584
00:31:46,360 --> 00:31:50,640
Speaker 3: each name has done over the past day, week, month, quarter,

585
00:31:51,080 --> 00:31:51,880
Speaker 3: six months a year.

586
00:31:52,320 --> 00:31:55,000
Speaker 2: What about the reverse? When something's working out, do you

587
00:31:55,080 --> 00:31:57,440
Speaker 2: pyramid and add to the position as it runs?

588
00:31:58,160 --> 00:32:00,480
Speaker 3: It depends? So I mean we just you know, I

589
00:32:00,560 --> 00:32:02,800
Speaker 3: know you don't like to talk about short term stuff

590
00:32:02,840 --> 00:32:04,880
Speaker 3: and market related things, but we just eliminated our Google

591
00:32:04,920 --> 00:32:06,840
Speaker 3: position a few days ago, right, So.

592
00:32:06,800 --> 00:32:09,080
Speaker 2: We mean that had a great twenty twenty five.

593
00:32:09,320 --> 00:32:11,120
Speaker 3: It did, and we actually got the I think the

594
00:32:11,120 --> 00:32:14,680
Speaker 3: investment thesis right. Hopefully we got the exit right, but

595
00:32:15,440 --> 00:32:18,600
Speaker 3: you know, the thesis there was, Okay, here's Google, this

596
00:32:18,680 --> 00:32:22,040
Speaker 3: is this should be a huge AI winner. Everyone was

597
00:32:22,040 --> 00:32:24,040
Speaker 3: concerned about their search business at the time and AI

598
00:32:24,120 --> 00:32:26,920
Speaker 3: replacing search. And you know our position was hold on

599
00:32:27,240 --> 00:32:29,240
Speaker 3: This trades at a massive discount to the mag seven.

600
00:32:29,280 --> 00:32:31,160
Speaker 3: It trades at a discount to the market on an

601
00:32:31,160 --> 00:32:34,320
Speaker 3: earnings and cash flow basis. Yet it has all the

602
00:32:34,400 --> 00:32:36,960
Speaker 3: distribution mechanisms for AI. You know, they're in seven out

603
00:32:36,960 --> 00:32:38,520
Speaker 3: of ten phones globally.

604
00:32:39,080 --> 00:32:44,120
Speaker 2: And all the technology capability to implement AI. I mean,

605
00:32:44,480 --> 00:32:46,640
Speaker 2: they're a giant tech brain trust.

606
00:32:46,400 --> 00:32:48,640
Speaker 3: Right exactly. And they had a ton of funding to

607
00:32:48,640 --> 00:32:51,600
Speaker 3: build it with, so and you know Waymo and all

608
00:32:51,640 --> 00:32:54,360
Speaker 3: these other you know, YouTube, all these other insane businesses

609
00:32:54,400 --> 00:32:56,080
Speaker 3: and was trading at a discount to the market. It

610
00:32:56,120 --> 00:32:58,360
Speaker 3: just didn't make any sense, so we bought that. That's

611
00:32:58,480 --> 00:33:01,560
Speaker 3: probably fairly valued today, I think, you know, and obviously

612
00:33:01,600 --> 00:33:04,920
Speaker 3: one of the classic mistakes is selling things too early.

613
00:33:05,360 --> 00:33:08,120
Speaker 3: Could it continue to compound? Yes, But if you look

614
00:33:08,160 --> 00:33:11,320
Speaker 3: at why the whole mag seven hyper scalers have done

615
00:33:11,400 --> 00:33:13,760
Speaker 3: so well over the past two to three years, the

616
00:33:13,800 --> 00:33:16,840
Speaker 3: answer has been, well, they're number one, growing faster than

617
00:33:16,840 --> 00:33:19,360
Speaker 3: everything else, and number two, they've got these huge incremental

618
00:33:19,440 --> 00:33:23,200
Speaker 3: free cash flow margins. But what's been going on recently

619
00:33:23,240 --> 00:33:25,600
Speaker 3: they don't really have big incremental free cash flow margins

620
00:33:25,600 --> 00:33:28,440
Speaker 3: anymore because they're dumping so much money into the AI

621
00:33:29,400 --> 00:33:32,160
Speaker 3: space that there really is no free cash flow and

622
00:33:32,160 --> 00:33:34,600
Speaker 3: now you're betting on it materializing down the line. So

623
00:33:35,080 --> 00:33:37,280
Speaker 3: where we take the other side on the AI situation

624
00:33:37,480 --> 00:33:41,320
Speaker 3: is if you actually look at the dollars required to

625
00:33:41,400 --> 00:33:45,440
Speaker 3: be found in revenues five years out, they're so substantial.

626
00:33:46,280 --> 00:33:48,360
Speaker 3: The number one, they're bigger than the entire software as

627
00:33:48,400 --> 00:33:52,640
Speaker 3: a service business right now globally around the world. Okay,

628
00:33:52,840 --> 00:33:55,800
Speaker 3: and number one number two, the total revenues that are

629
00:33:55,880 --> 00:33:58,080
Speaker 3: required to justify all the investment that's gone in is

630
00:33:58,160 --> 00:34:01,880
Speaker 3: bigger than the combined of mag seven today. And those

631
00:34:01,880 --> 00:34:04,520
Speaker 3: companies have been scaling for thirty to forty fifty years

632
00:34:04,560 --> 00:34:06,600
Speaker 3: in some cases, and so you've got to find that

633
00:34:06,640 --> 00:34:08,600
Speaker 3: in five years to make all this investment worth it.

634
00:34:09,080 --> 00:34:11,960
Speaker 3: And if you think about the structural the way it works,

635
00:34:12,000 --> 00:34:15,080
Speaker 3: it's all this capex investment upfront and then it's very

636
00:34:15,080 --> 00:34:17,839
Speaker 3: little marginal costs. Right, So you potentially have a race

637
00:34:17,880 --> 00:34:20,480
Speaker 3: to the bottom on pricing on the top line in

638
00:34:20,480 --> 00:34:22,520
Speaker 3: a few years as well. So that gives us a

639
00:34:22,520 --> 00:34:25,479
Speaker 3: little bit of pause whether or not it's right, Who knows, huh.

640
00:34:25,640 --> 00:34:31,560
Speaker 2: So what I'm hearing is that there's a probabilistic quantitative discipline.

641
00:34:31,920 --> 00:34:34,319
Speaker 2: You're looking at value, you're looking at growth rate, you're

642
00:34:34,360 --> 00:34:39,440
Speaker 2: looking at risk, combined with a qualitative judgment about management

643
00:34:39,600 --> 00:34:44,440
Speaker 2: and sounds like specific industry and whether these moonshots are

644
00:34:44,440 --> 00:34:46,480
Speaker 2: going to pay off or not. How do you balance

645
00:34:46,560 --> 00:34:53,760
Speaker 2: between the squishy qualitative side and the more quantitative mathematical side.

646
00:34:54,040 --> 00:34:55,840
Speaker 3: Well, I think there always has to be a quantitative

647
00:34:55,920 --> 00:35:00,319
Speaker 3: value perspective, and anything we're buying and thinking about often

648
00:35:00,320 --> 00:35:05,840
Speaker 3: from a total addressable market perspectives versus the current valuation.

649
00:35:07,760 --> 00:35:10,719
Speaker 3: One of the big themes for us also is alignment.

650
00:35:10,920 --> 00:35:14,479
Speaker 3: So we want to see managers, you know, actually using

651
00:35:14,480 --> 00:35:17,040
Speaker 3: their capit So it's capital allocation and alignment. So are

652
00:35:17,040 --> 00:35:19,719
Speaker 3: they using their capital in ways that align with our

653
00:35:19,840 --> 00:35:22,520
Speaker 3: view of the stock? You know, are they buying back

654
00:35:22,560 --> 00:35:26,120
Speaker 3: a lot of shares if it's mispriced hopefully yes? Are

655
00:35:26,160 --> 00:35:29,280
Speaker 3: they aligned with you as a manager of the company,

656
00:35:29,280 --> 00:35:31,360
Speaker 3: you know, principal agent conflict is one of the biggest

657
00:35:31,360 --> 00:35:34,279
Speaker 3: sources of value destruction you can possibly imagine, and so

658
00:35:34,480 --> 00:35:38,000
Speaker 3: that's important to us as managers. We are the biggest

659
00:35:38,000 --> 00:35:40,080
Speaker 3: investors in our own funds as well, so it really.

660
00:35:39,960 --> 00:35:40,880
Speaker 2: Is very interesting.

661
00:35:41,000 --> 00:35:45,600
Speaker 3: Yeah, but it's you know, it's a first principles based approach.

662
00:35:45,680 --> 00:35:49,080
Speaker 3: So one of the things we pay special attention to,

663
00:35:49,200 --> 00:35:51,120
Speaker 3: I think more so than most and can be opportunistic

664
00:35:51,200 --> 00:35:53,600
Speaker 3: about moving on, is insider activity. So when you see

665
00:35:53,600 --> 00:35:56,640
Speaker 3: a big insider buy, if you can then reverse engineer

666
00:35:56,680 --> 00:36:01,000
Speaker 3: a quantitative value perspective into that insider buy, that makes

667
00:36:01,040 --> 00:36:04,320
Speaker 3: a lot of sense. That can be a really compelling.

668
00:36:04,160 --> 00:36:07,560
Speaker 2: I just saw a big Wall Street Journal piece on

669
00:36:08,440 --> 00:36:13,200
Speaker 2: to insider buyers indicate future performance, and I saved it.

670
00:36:13,200 --> 00:36:16,480
Speaker 2: I haven't read it yet, what's your take. I mean,

671
00:36:16,480 --> 00:36:20,080
Speaker 2: the assumption is insiders, there's a million reasons to sell

672
00:36:20,080 --> 00:36:22,840
Speaker 2: a stock if you need liquidity, there's only one reason

673
00:36:22,920 --> 00:36:28,520
Speaker 2: to buy a stock. You stay with that conclusion. Insider

674
00:36:28,560 --> 00:36:31,520
Speaker 2: buying is indicative of positive things to come.

675
00:36:32,000 --> 00:36:35,239
Speaker 3: I think it's a potentially high signal source of information.

676
00:36:35,960 --> 00:36:40,360
Speaker 3: So in the aggregate doesn't necessarily guarantee it. No, But

677
00:36:40,440 --> 00:36:43,960
Speaker 3: if you can contextualize and say, Okay, this CEO is

678
00:36:44,040 --> 00:36:47,160
Speaker 3: really smart, He's done this sort of thing in the past.

679
00:36:47,280 --> 00:36:49,399
Speaker 3: He has a plan for this company, here's what it's

680
00:36:49,400 --> 00:36:51,640
Speaker 3: looking like, and you just put a huge amount of

681
00:36:51,640 --> 00:36:55,000
Speaker 3: personal capital in, that can be a really good sis.

682
00:36:55,080 --> 00:36:57,960
Speaker 2: So it's not binary. There are other factors that have

683
00:36:58,040 --> 00:37:00,480
Speaker 2: to be It's a little more nuanced than the way

684
00:37:00,520 --> 00:37:01,719
Speaker 2: we typically think of it.

685
00:37:01,760 --> 00:37:04,040
Speaker 3: Context matters always really interesting.

686
00:37:04,400 --> 00:37:07,400
Speaker 2: Coming up, we continue our conversation with Bill Miller, the

687
00:37:07,440 --> 00:37:12,200
Speaker 2: fourth chief investment officer at Miller Value Fund, talking about

688
00:37:12,239 --> 00:37:16,680
Speaker 2: today's market environment. I'm Barry Ridlts. You're listening to Masters

689
00:37:16,680 --> 00:37:33,439
Speaker 2: your Business on Bloomberg Radio. I'm Barry rid Halts. You're

690
00:37:33,480 --> 00:37:37,240
Speaker 2: listening to Masters in Business on Bloomberg Radio or watching

691
00:37:37,320 --> 00:37:41,360
Speaker 2: us on YouTube television I'm speaking with Bill Miller the fourth.

692
00:37:41,440 --> 00:37:46,080
Speaker 2: He's Miller Value Fund's chief investment officer and portfolio manager.

693
00:37:47,280 --> 00:37:50,440
Speaker 2: He works with his father, Bill Miller the third, the

694
00:37:50,520 --> 00:37:54,719
Speaker 2: famous value investor. So let's talk about what's going on

695
00:37:55,200 --> 00:37:58,920
Speaker 2: in the current environment. If you look at today's markets,

696
00:37:58,960 --> 00:38:02,399
Speaker 2: where do you see things that are very much mispriced,

697
00:38:02,719 --> 00:38:08,000
Speaker 2: either by asset class, sector, geography, factor, whatever. What's out

698
00:38:08,040 --> 00:38:13,240
Speaker 2: there that's not fully priced, or what's out there that's overpriced.

699
00:38:14,120 --> 00:38:17,920
Speaker 3: Yeah, I think aspects of the current environment remind us

700
00:38:17,920 --> 00:38:21,000
Speaker 3: of nineteen ninety nine. Right. So You've had a narrative

701
00:38:21,080 --> 00:38:26,200
Speaker 3: driven performance led by AI. You have a very narrow

702
00:38:26,239 --> 00:38:29,440
Speaker 3: market for the most part, with mag seven leading huge

703
00:38:29,440 --> 00:38:34,120
Speaker 3: returns to momentum momentum factor last year. But then if

704
00:38:34,160 --> 00:38:38,359
Speaker 3: you look at the actual macroeconomic backdrop, you're seeing deregulation,

705
00:38:39,120 --> 00:38:46,160
Speaker 3: you are seeing weaker dollar, and you're seeing economic acceleration

706
00:38:46,280 --> 00:38:50,040
Speaker 3: potentially in the US. And so when you think about

707
00:38:50,040 --> 00:38:53,160
Speaker 3: all those things combined and you look at what happened

708
00:38:53,160 --> 00:38:56,279
Speaker 3: between call it nineteen ninety nine, two thousand, all the

709
00:38:56,280 --> 00:39:00,480
Speaker 3: way until six oh seven, you had the market go

710
00:39:00,520 --> 00:39:02,839
Speaker 3: effectively nowhere for seven years. I mean, it went down

711
00:39:02,880 --> 00:39:05,799
Speaker 3: and bounced around, right, because I think valuation heading into

712
00:39:05,840 --> 00:39:08,080
Speaker 3: that period was very high. But what did really well

713
00:39:08,160 --> 00:39:12,840
Speaker 3: during that period actually small MidCap value. And if you

714
00:39:12,840 --> 00:39:16,840
Speaker 3: look at the relative valuation discrepancies today between smid value

715
00:39:17,680 --> 00:39:21,000
Speaker 3: and large growth, they're right at the same sort of

716
00:39:21,200 --> 00:39:24,400
Speaker 3: extremes that occurred in nineteen ninety nine. And so you

717
00:39:24,480 --> 00:39:29,480
Speaker 3: have same valuation extremes, you have compelling valuations and a

718
00:39:29,520 --> 00:39:33,359
Speaker 3: lot of the small MidCap value space, and you have

719
00:39:33,800 --> 00:39:38,440
Speaker 3: an economic acceleration backdrop. So that means that a lot

720
00:39:38,440 --> 00:39:43,759
Speaker 3: of more cyclically oriented things, value oriented names that are

721
00:39:44,640 --> 00:39:47,520
Speaker 3: care more about what's going on in the economy. There's

722
00:39:47,520 --> 00:39:50,040
Speaker 3: a much lower hurdle rate for those guys to exceed

723
00:39:50,080 --> 00:39:53,560
Speaker 3: the expectations embedded in the valuations right over the next

724
00:39:53,600 --> 00:39:55,880
Speaker 3: five to seven years than there are in the massive

725
00:39:55,920 --> 00:39:56,640
Speaker 3: AI space.

726
00:39:57,200 --> 00:40:00,440
Speaker 2: So let's talk a little bit about small and MidCap value.

727
00:40:00,880 --> 00:40:04,200
Speaker 2: Last year we only saw two that's twenty twenty five.

728
00:40:04,600 --> 00:40:08,640
Speaker 2: We only saw two of the seven mag seven outperform

729
00:40:08,680 --> 00:40:12,640
Speaker 2: the S and P five hundred, which tends to suggest, hey,

730
00:40:12,680 --> 00:40:14,719
Speaker 2: maybe this is broadening out. We're going to see more

731
00:40:14,719 --> 00:40:19,640
Speaker 2: mid caps and more small caps. The value skeptics are

732
00:40:19,680 --> 00:40:21,720
Speaker 2: going to say Hey, we've had so many false starts

733
00:40:21,719 --> 00:40:25,719
Speaker 2: in value. It's been fifteen years of growth winning. How

734
00:40:25,760 --> 00:40:26,640
Speaker 2: do you respond to that?

735
00:40:27,520 --> 00:40:30,480
Speaker 3: Yeah, I think that those snapbacks can be violent. Right.

736
00:40:30,600 --> 00:40:33,040
Speaker 3: We actually had one of our research providers recently called

737
00:40:33,280 --> 00:40:36,759
Speaker 3: MidCap value quote unquote inferior asset class. I mean that

738
00:40:36,840 --> 00:40:41,040
Speaker 3: sounds like capitulation to me. There's a lot of underloved

739
00:40:41,040 --> 00:40:45,080
Speaker 3: stuff out there that's really interesting. So energy sectors. Energy

740
00:40:45,120 --> 00:40:47,279
Speaker 3: is interesting right now. You know, if you look at

741
00:40:47,320 --> 00:40:49,560
Speaker 3: its weight in the market, it's three or four percent,

742
00:40:49,960 --> 00:40:51,960
Speaker 3: But if you look at its free cash flow contribution

743
00:40:52,040 --> 00:40:54,000
Speaker 3: over the next year to the market, it's going to

744
00:40:54,040 --> 00:40:55,600
Speaker 3: be ten to twelve percent most likely.

745
00:40:55,920 --> 00:40:58,080
Speaker 2: What's that historic relationship look like.

746
00:40:58,640 --> 00:41:00,880
Speaker 3: I don't know if it's that large, to be honest,

747
00:41:00,920 --> 00:41:04,600
Speaker 3: that gap, and so, you know, energy is under love.

748
00:41:04,600 --> 00:41:08,240
Speaker 3: It's underperformed for so long. It's not the best industry

749
00:41:08,239 --> 00:41:11,640
Speaker 3: from a capital allocation alignment perspective, but it's gotten a

750
00:41:11,640 --> 00:41:14,520
Speaker 3: lot better over the past few years. And I think

751
00:41:14,520 --> 00:41:16,720
Speaker 3: you can see those types of stocks do really well.

752
00:41:17,000 --> 00:41:18,799
Speaker 3: You know, sadly, I do think it's a really cheap

753
00:41:18,840 --> 00:41:22,600
Speaker 3: coll option on global strife. Right now, Energy prices, you know,

754
00:41:22,640 --> 00:41:26,880
Speaker 3: they're pretty bouncing pretty close to the marginal cost of production, which.

755
00:41:26,680 --> 00:41:30,359
Speaker 2: Is shocking when you think about Russia and Ukraine and

756
00:41:30,520 --> 00:41:34,360
Speaker 2: Gaza and Israel and what's going on in Venezuela and

757
00:41:34,520 --> 00:41:37,359
Speaker 2: who knows what's going to happen. By the time this

758
00:41:37,400 --> 00:41:41,200
Speaker 2: comes out, we can own Greenland. So given given all

759
00:41:41,239 --> 00:41:45,719
Speaker 2: of that, what does it What does it mean to

760
00:41:45,760 --> 00:41:52,400
Speaker 2: see despite all this geopolitical turmoil, energy prices are almost reasonable.

761
00:41:52,960 --> 00:41:55,640
Speaker 3: Yeah they are. They've started to turn up, and energy

762
00:41:55,640 --> 00:41:57,959
Speaker 3: has done well over the past few weeks. It could

763
00:41:57,960 --> 00:42:01,640
Speaker 3: continue to do really well. So that's why we're overweight energy.

764
00:42:01,920 --> 00:42:03,279
Speaker 2: What other sectors do you like?

765
00:42:04,800 --> 00:42:06,960
Speaker 3: You know, financials, we're still overweight. I think you're going

766
00:42:07,000 --> 00:42:10,840
Speaker 3: to continue to see curve steeping and that should be

767
00:42:10,840 --> 00:42:14,520
Speaker 3: a decent earnings growth in those. I think utilities are

768
00:42:14,600 --> 00:42:18,720
Speaker 3: finally attractively valued again at you know, ten to thirteen

769
00:42:18,760 --> 00:42:20,800
Speaker 3: times earnings in a lot of cases with very clear

770
00:42:21,719 --> 00:42:24,360
Speaker 3: growth pathways, and I'd say little risk. You know, we

771
00:42:24,360 --> 00:42:26,960
Speaker 3: don't have enough energy in the country, and utilities are

772
00:42:27,000 --> 00:42:28,120
Speaker 3: pretty attractive.

773
00:42:27,680 --> 00:42:32,719
Speaker 2: Here, especially as AI and data centers continue to come online.

774
00:42:33,000 --> 00:42:38,200
Speaker 2: You take very concentrated position, at least compared to traditional

775
00:42:39,239 --> 00:42:41,879
Speaker 2: value managers. How do you what's the framework for thinking

776
00:42:41,960 --> 00:42:45,200
Speaker 2: about this? How do you position size these? Is this

777
00:42:45,400 --> 00:42:49,560
Speaker 2: just strictly a function of Hey, we're not closet indexers.

778
00:42:49,560 --> 00:42:52,520
Speaker 2: We have a high active share, and when we have

779
00:42:52,600 --> 00:42:56,400
Speaker 2: high conviction, we really we go all in to follow

780
00:42:56,440 --> 00:42:57,600
Speaker 2: the poker analogy.

781
00:42:58,120 --> 00:43:00,319
Speaker 3: Yeah, that's a good way of putting it. I mean,

782
00:43:00,360 --> 00:43:05,400
Speaker 3: if you consider that most stocks underperformed the index for

783
00:43:05,440 --> 00:43:11,239
Speaker 3: their lifetime in it, it's an interesting exercise to come

784
00:43:11,239 --> 00:43:13,200
Speaker 3: at it from the entire other side and just say, okay,

785
00:43:13,239 --> 00:43:16,239
Speaker 3: what are the ten to fifteen names that you think

786
00:43:16,960 --> 00:43:21,400
Speaker 3: have the highest probability of actually outperforming instead of effectively.

787
00:43:21,400 --> 00:43:23,799
Speaker 3: What most active managers do is they have these risk

788
00:43:23,840 --> 00:43:26,719
Speaker 3: constraints and they can only overweight certain sectors a little

789
00:43:26,719 --> 00:43:31,239
Speaker 3: bit or so. You know, the closer you are to

790
00:43:31,280 --> 00:43:34,040
Speaker 3: the benchmark, the more likely you are to underperforming, right,

791
00:43:34,080 --> 00:43:36,480
Speaker 3: because you're just layering higher fees on something that looks

792
00:43:36,520 --> 00:43:40,040
Speaker 3: more like the benchmark. So, you know, we're very comfortable

793
00:43:40,880 --> 00:43:45,000
Speaker 3: taking bets entirely outside of the index, with the obvious

794
00:43:46,080 --> 00:43:47,839
Speaker 3: caveat that there are going to be period when we're

795
00:43:47,840 --> 00:43:51,720
Speaker 3: going to underperform meaningfully just because we're taking entirely different

796
00:43:51,760 --> 00:43:53,879
Speaker 3: risks and there'll be some periods to reoutperform by a lot.

797
00:43:53,960 --> 00:43:55,960
Speaker 3: So I think that's really the only way to.

798
00:43:55,880 --> 00:44:01,080
Speaker 2: Do it is to not be a closet in essentially.

799
00:44:01,280 --> 00:44:03,719
Speaker 3: Yeah, and you have to match the investment process to

800
00:44:03,800 --> 00:44:07,680
Speaker 3: your IP. So you know, for us, thinking that the

801
00:44:08,000 --> 00:44:10,040
Speaker 3: edge is on the thirty seventh page of the Excel

802
00:44:10,080 --> 00:44:13,360
Speaker 3: spreadsheets just not realistic, right. Or if your fidelity and

803
00:44:13,360 --> 00:44:15,480
Speaker 3: you've got a guy that's been following a certain industry

804
00:44:15,520 --> 00:44:17,840
Speaker 3: for a long period of time and really understands the

805
00:44:17,920 --> 00:44:21,400
Speaker 3: nuances of every single company and what could change, you know,

806
00:44:21,440 --> 00:44:23,239
Speaker 3: that might make sense. But it just depends on what

807
00:44:23,280 --> 00:44:24,600
Speaker 3: you're trying to do, and you have to match up

808
00:44:24,640 --> 00:44:25,320
Speaker 3: those two things.

809
00:44:25,640 --> 00:44:29,960
Speaker 2: So we've been kind of dancing around AI throughout this conversation,

810
00:44:30,040 --> 00:44:33,640
Speaker 2: So let's let's talk about that a little bit. Are

811
00:44:33,680 --> 00:44:38,160
Speaker 2: you thinking of AI as its own investment entity? Are

812
00:44:38,200 --> 00:44:42,680
Speaker 2: you thinking of it as disrupting traditional business models? Are

813
00:44:42,719 --> 00:44:46,120
Speaker 2: you thinking of other businesses forget the Max seven, the

814
00:44:46,800 --> 00:44:50,080
Speaker 2: mag four ninety three as being the beneficiaries of AI

815
00:44:50,200 --> 00:44:54,160
Speaker 2: to be more productive, efficient, profitable? How are you thinking

816
00:44:54,200 --> 00:44:55,920
Speaker 2: about AI as an investor?

817
00:44:56,360 --> 00:45:01,600
Speaker 3: I think it's all of those things. Yeah, it's it's

818
00:45:01,640 --> 00:45:03,479
Speaker 3: all those things. So I use it all day every day.

819
00:45:03,640 --> 00:45:06,080
Speaker 2: Man, how do you that was really my next question,

820
00:45:06,440 --> 00:45:09,680
Speaker 2: how do you use AI throughout the day for your process,

821
00:45:10,320 --> 00:45:16,320
Speaker 2: both for selecting investments and just managing a large investment.

822
00:45:15,840 --> 00:45:19,680
Speaker 3: From Well, it's an enormous time saver, and it's not

823
00:45:19,719 --> 00:45:22,440
Speaker 3: necessarily always a time saver on the investment front, although

824
00:45:22,480 --> 00:45:25,600
Speaker 3: it often is. It can just be a timesaver personally,

825
00:45:25,719 --> 00:45:28,040
Speaker 3: Like if you have an interpersonal issue that is weighing

826
00:45:28,080 --> 00:45:30,239
Speaker 3: on you, sometimes you throw it into AI and you

827
00:45:30,239 --> 00:45:31,799
Speaker 3: get a better answer than you could have gotten from

828
00:45:31,800 --> 00:45:35,359
Speaker 3: asking your three closest friends and move on. So if

829
00:45:35,400 --> 00:45:37,160
Speaker 3: you're thinking in units of time, it's a huge time

830
00:45:37,200 --> 00:45:39,040
Speaker 3: saver for me personally. I think a lot of life

831
00:45:39,080 --> 00:45:41,799
Speaker 3: is about asking the right questions, and you got a

832
00:45:41,840 --> 00:45:45,280
Speaker 3: pretty good set of answers there, or method for answering

833
00:45:45,360 --> 00:45:48,080
Speaker 3: questions you point out earlier. It can be wrong often

834
00:45:48,160 --> 00:45:50,759
Speaker 3: and you have to consider that, but it's got a

835
00:45:50,800 --> 00:45:52,719
Speaker 3: lot of good perspectives in there that can bring to

836
00:45:52,719 --> 00:45:53,879
Speaker 3: bear on a lot of different things.

837
00:45:53,880 --> 00:45:57,520
Speaker 2: So what tools do you use? What's your favorite AI?

838
00:45:57,719 --> 00:46:01,200
Speaker 3: At the moment? We have Chat, GPT and Gemini going

839
00:46:01,560 --> 00:46:04,120
Speaker 3: for business, both for business, and then we're also adding

840
00:46:04,760 --> 00:46:05,960
Speaker 3: Claude here soon.

841
00:46:06,080 --> 00:46:08,759
Speaker 2: I just I just put Claude on a couple of

842
00:46:08,760 --> 00:46:13,359
Speaker 2: desktops and a laptop, and the coding side of it

843
00:46:13,400 --> 00:46:19,520
Speaker 2: is really fascinating, And I can see why people are

844
00:46:19,560 --> 00:46:25,960
Speaker 2: concerned that this could replace certain at least menial kind

845
00:46:26,000 --> 00:46:28,759
Speaker 2: of work, grinding work, Like, oh, it does this so

846
00:46:28,880 --> 00:46:31,279
Speaker 2: much faster and better than I could ever grind down

847
00:46:31,320 --> 00:46:35,600
Speaker 2: on my own. Yeah, Claud's kind especially Claude pro. It's

848
00:46:35,680 --> 00:46:38,680
Speaker 2: really kind of impressive. And the question is, is two

849
00:46:38,760 --> 00:46:40,840
Speaker 2: hundred a month a lot? Is that not a lot?

850
00:46:41,320 --> 00:46:44,239
Speaker 2: Is that a fair price? I think it sounds like

851
00:46:44,280 --> 00:46:47,480
Speaker 2: a lot of money compared to what is perplexity twenty

852
00:46:47,480 --> 00:46:50,960
Speaker 2: bucks a month. That seems like free practically for that

853
00:46:51,120 --> 00:46:55,319
Speaker 2: much power. So you're using it everywhere? Yeah, what are

854
00:46:55,360 --> 00:46:57,239
Speaker 2: you hearing from your peers? Is this the sort of

855
00:46:57,239 --> 00:47:01,759
Speaker 2: thing that everybody has gone all in on? Is the fear? Hey,

856
00:47:01,760 --> 00:47:03,759
Speaker 2: if we don't do this, our competitors are, so we

857
00:47:03,800 --> 00:47:04,600
Speaker 2: better step up.

858
00:47:06,520 --> 00:47:08,440
Speaker 3: I don't know if it's fear just as much as

859
00:47:08,680 --> 00:47:11,239
Speaker 3: the ability to cover so much more ground in the

860
00:47:11,239 --> 00:47:15,560
Speaker 3: same amount of time or less. You know, it's just

861
00:47:15,560 --> 00:47:18,239
Speaker 3: a super powerful technology. And we use it a lot.

862
00:47:18,440 --> 00:47:24,239
Speaker 2: Huh, really really interesting. So I want to get to

863
00:47:24,280 --> 00:47:27,480
Speaker 2: this question, and I forgot about it. So we're talking

864
00:47:27,520 --> 00:47:31,480
Speaker 2: about the current environment. AI is obviously a game changer,

865
00:47:31,600 --> 00:47:36,240
Speaker 2: but we've gone through a few decades of major regime changes.

866
00:47:36,680 --> 00:47:39,400
Speaker 2: We had the era of monetary policy, and then starting

867
00:47:39,440 --> 00:47:43,920
Speaker 2: in twenty twenty, we've had the era of fiscal policy.

868
00:47:44,760 --> 00:47:48,960
Speaker 2: When you're looking at central banks and the government higher

869
00:47:48,960 --> 00:47:53,239
Speaker 2: for longer, zero interest rates, all these different things. How

870
00:47:53,280 --> 00:47:59,160
Speaker 2: do these geopolitical variables affect how you think about putting

871
00:47:59,280 --> 00:48:01,920
Speaker 2: capital work, how you think about risk?

872
00:48:03,040 --> 00:48:07,440
Speaker 3: Well, I think one really big picture change sort of

873
00:48:07,480 --> 00:48:11,440
Speaker 3: going back over the past decade to today is coming

874
00:48:11,440 --> 00:48:16,440
Speaker 3: out of the financial crisis, capital effectively had no cost.

875
00:48:16,480 --> 00:48:18,840
Speaker 3: I mean, you saw the insane amount of money printing

876
00:48:18,880 --> 00:48:21,480
Speaker 3: that occurred, but that's because that was to offset a

877
00:48:21,560 --> 00:48:24,480
Speaker 3: huge hole in capex that had gone into housing that

878
00:48:24,520 --> 00:48:27,680
Speaker 3: wasn't necessarily needed, right, And we had to work that

879
00:48:27,760 --> 00:48:30,120
Speaker 3: out from a demand supply demand perspective. And we've now

880
00:48:30,160 --> 00:48:32,600
Speaker 3: done that. But if you go back and read what

881
00:48:32,600 --> 00:48:35,239
Speaker 3: the FED said, there was a study that came out

882
00:48:35,320 --> 00:48:39,799
Speaker 3: of I think the San Francisco FED where they used

883
00:48:39,840 --> 00:48:42,120
Speaker 3: computers to look at the language that was used in

884
00:48:42,160 --> 00:48:45,359
Speaker 3: meetings right about how to set rates, and what they

885
00:48:45,440 --> 00:48:51,279
Speaker 3: found was that the two percent inflation number, that's kind

886
00:48:51,280 --> 00:48:53,120
Speaker 3: of the bogie. It was supposed to be quote unquote

887
00:48:53,160 --> 00:48:56,719
Speaker 3: symmetrical goal. It wasn't symmetrical at all the way they

888
00:48:56,719 --> 00:48:58,920
Speaker 3: were setting rates for the between twenty ten roughly and

889
00:48:58,960 --> 00:49:01,400
Speaker 3: call it twenty twenty or so. And so that has

890
00:49:01,440 --> 00:49:03,560
Speaker 3: an enormous implication I think for the way all kinds

891
00:49:03,560 --> 00:49:06,400
Speaker 3: of different assets perform. And I think that's why massive

892
00:49:06,440 --> 00:49:09,040
Speaker 3: growth had the run it did over the past decade, right,

893
00:49:09,120 --> 00:49:11,279
Speaker 3: because when capital has no cost, you're willing to look

894
00:49:11,280 --> 00:49:13,200
Speaker 3: out a huge distance.

895
00:49:12,880 --> 00:49:15,440
Speaker 2: To brace more risk because what are you going to

896
00:49:15,480 --> 00:49:17,319
Speaker 2: get one and a half two percent? It doesn't make

897
00:49:17,400 --> 00:49:18,760
Speaker 2: sense otherwise exactly.

898
00:49:18,800 --> 00:49:20,920
Speaker 3: And so that's why huge growth had the run it

899
00:49:20,960 --> 00:49:24,000
Speaker 3: did because capital had no opportunity cost. And now if

900
00:49:24,040 --> 00:49:25,839
Speaker 3: you look at where we are with mortgages at six

901
00:49:25,880 --> 00:49:30,279
Speaker 3: percent and capital actually has a cost, again, it has

902
00:49:30,640 --> 00:49:32,960
Speaker 3: major implications for the kinds of assets that are likely

903
00:49:33,000 --> 00:49:34,839
Speaker 3: to do well in the future. And it comes back

904
00:49:34,880 --> 00:49:37,680
Speaker 3: to the whole theme we talked about earlier around smid

905
00:49:37,800 --> 00:49:41,720
Speaker 3: value more capital intensive things potentially having a better decade

906
00:49:41,800 --> 00:49:43,200
Speaker 3: now that capital has a cost again.

907
00:49:43,880 --> 00:49:48,440
Speaker 2: Let me share a favorite factoid with you. Former FED

908
00:49:48,680 --> 00:49:53,800
Speaker 2: Vice chair Roger Ferguson wrote a white paper on the

909
00:49:53,840 --> 00:49:58,520
Speaker 2: origination of the two percent target, and he traced it

910
00:49:58,560 --> 00:50:02,680
Speaker 2: back to some random time television interview in the nineteen

911
00:50:02,880 --> 00:50:07,000
Speaker 2: eighties in New Zealand where someone threw out two percent

912
00:50:07,560 --> 00:50:10,279
Speaker 2: and that was it. It just magically stuck and you

913
00:50:10,320 --> 00:50:12,680
Speaker 2: can find that. You can find that paper online. It's

914
00:50:12,719 --> 00:50:18,319
Speaker 2: pretty hilarious. It's just such a random number that doesn't like,

915
00:50:18,400 --> 00:50:23,520
Speaker 2: it's not there's no underlying thesis for why it's two

916
00:50:23,560 --> 00:50:27,439
Speaker 2: when not three or one. It's just it just seems like, yeah,

917
00:50:27,440 --> 00:50:28,359
Speaker 2: that sounds about right.

918
00:50:28,400 --> 00:50:30,120
Speaker 3: Well, I think it's got to actually be higher than

919
00:50:30,120 --> 00:50:32,359
Speaker 3: that if you think about it, because generally in an.

920
00:50:32,280 --> 00:50:35,839
Speaker 2: Era of fiscal rather than monetary stimulus, right, you're going

921
00:50:35,880 --> 00:50:38,280
Speaker 2: to just inherently have higher prices.

922
00:50:38,440 --> 00:50:40,080
Speaker 3: Right. Well, I mean if you think about the fact

923
00:50:40,120 --> 00:50:46,680
Speaker 3: that most consumers overwhelming saving vehicle is their home. Okay,

924
00:50:47,280 --> 00:50:50,560
Speaker 3: what's the blended rate on mortgages right now out there?

925
00:50:50,680 --> 00:50:52,560
Speaker 3: That's just in the stuff.

926
00:50:52,840 --> 00:50:56,880
Speaker 2: Yeah, Well, half the individually owned homes there are no mortgages,

927
00:50:57,280 --> 00:51:00,000
Speaker 2: and the remaining half. It's a crazy set of numbers

928
00:51:00,080 --> 00:51:01,640
Speaker 2: of two and a half, three, three and a half four.

929
00:51:02,120 --> 00:51:05,920
Speaker 2: Just everybody was smart locked in a fixed rate before

930
00:51:05,960 --> 00:51:06,640
Speaker 2: the pandemic.

931
00:51:07,120 --> 00:51:10,400
Speaker 3: Well, so if house prices in the aggregate don't appreciate

932
00:51:10,440 --> 00:51:14,359
Speaker 3: by more than that interest rate, right, people are going

933
00:51:14,360 --> 00:51:17,799
Speaker 3: broke in their primary savings vehicle. So housing actually does

934
00:51:17,880 --> 00:51:19,680
Speaker 3: need to increase in value over a long period of

935
00:51:19,760 --> 00:51:21,400
Speaker 3: time where people slowly go broke.

936
00:51:22,000 --> 00:51:23,040
Speaker 2: It makes a lot of sense.

937
00:51:23,160 --> 00:51:25,000
Speaker 3: Yeah, so I think the two percent is I know

938
00:51:25,040 --> 00:51:27,080
Speaker 3: it is thrown out there, but I think it actually

939
00:51:27,120 --> 00:51:28,719
Speaker 3: has to be higher over the long term to kind

940
00:51:28,719 --> 00:51:31,080
Speaker 3: of make the math work for most people.

941
00:51:31,320 --> 00:51:33,440
Speaker 2: I couldn't agree more. All Right, I only have you

942
00:51:33,480 --> 00:51:35,600
Speaker 2: for a limited amount of time. Let's jump to our

943
00:51:35,680 --> 00:51:40,200
Speaker 2: favorite questions, some of which I know the answers to.

944
00:51:41,480 --> 00:51:45,360
Speaker 2: Starting with who were your mentors who helped shape your career?

945
00:51:46,920 --> 00:51:51,640
Speaker 3: Wow? So mister Keeney was my dad's original business partner,

946
00:51:52,360 --> 00:51:55,799
Speaker 3: and he's a fascinating human worked until the day he

947
00:51:55,880 --> 00:52:00,160
Speaker 3: died ninety two. Wow, an incredibly nice human being. I

948
00:52:00,200 --> 00:52:02,320
Speaker 3: don't think I ever said a bad word about anyone.

949
00:52:02,880 --> 00:52:04,200
Speaker 3: One of the things that was so interesting to me

950
00:52:04,239 --> 00:52:07,400
Speaker 3: about mister keene is he didn't start his career at

951
00:52:07,480 --> 00:52:11,680
Speaker 3: leg Mason in research until he was fifty. Wow. So

952
00:52:11,840 --> 00:52:13,920
Speaker 3: you know a lot of people, young people think, oh, here,

953
00:52:13,920 --> 00:52:15,919
Speaker 3: I am unlocked in this career. Now there's always time

954
00:52:15,960 --> 00:52:18,560
Speaker 3: to switch. And then he hopped over at fifty to

955
00:52:18,680 --> 00:52:21,880
Speaker 3: start this role where he had a prolific career and

956
00:52:22,520 --> 00:52:25,120
Speaker 3: influenced a lot of people and did that for forty

957
00:52:25,200 --> 00:52:25,839
Speaker 3: something years.

958
00:52:26,080 --> 00:52:26,279
Speaker 1: Wow.

959
00:52:26,840 --> 00:52:30,240
Speaker 3: So he was a very smart guy, generous to a fault.

960
00:52:31,360 --> 00:52:33,640
Speaker 3: One of my favorite stories about him and him and

961
00:52:33,640 --> 00:52:36,840
Speaker 3: my dad were heading out for lunch one day downtown Baltimore,

962
00:52:36,880 --> 00:52:39,720
Speaker 3: and you know, some homeless person comes up and says,

963
00:52:40,040 --> 00:52:42,120
Speaker 3: starts with the story, you know, I haven't eaten in

964
00:52:42,160 --> 00:52:45,400
Speaker 3: this many days and blah blah blah, and mister Keeney's

965
00:52:45,640 --> 00:52:47,279
Speaker 3: sits there listening to it. He gets out of his

966
00:52:47,320 --> 00:52:49,239
Speaker 3: wallet and he gives her, you know, it was like

967
00:52:49,280 --> 00:52:52,680
Speaker 3: a fifty dollars bill, certainly inflation to justin. He says, oh, man, here,

968
00:52:52,760 --> 00:52:56,640
Speaker 3: just just go get yourself some hot soup. Take care

969
00:52:56,640 --> 00:52:58,839
Speaker 3: of yourself. And she looks to it, she looks back

970
00:52:58,880 --> 00:53:00,879
Speaker 3: at him, she looks at it. She goes to hell

971
00:53:00,960 --> 00:53:05,359
Speaker 3: a soup I'm gonna get me some whiskey. But yeah,

972
00:53:05,480 --> 00:53:08,239
Speaker 3: so he was incredibly generous human being, contributed a lot

973
00:53:08,280 --> 00:53:13,000
Speaker 3: to animal welfare stuff. I'm a big believer in welfare causes,

974
00:53:14,719 --> 00:53:17,560
Speaker 3: so he was an influence on me. I can also

975
00:53:17,600 --> 00:53:19,760
Speaker 3: think of a handful of times just from business school

976
00:53:20,280 --> 00:53:24,840
Speaker 3: that not necessarily an individual mentor, but just one liners

977
00:53:24,880 --> 00:53:27,640
Speaker 3: from business school that I remember over the years. So

978
00:53:27,719 --> 00:53:29,800
Speaker 3: that line I gave you earlier about Ken French and

979
00:53:29,840 --> 00:53:31,799
Speaker 3: how long it takes for a manager to prove whether

980
00:53:31,840 --> 00:53:35,400
Speaker 3: or not his work is statistically valuable or not. The

981
00:53:35,440 --> 00:53:38,120
Speaker 3: other one liner he told us is never pay a

982
00:53:38,160 --> 00:53:39,799
Speaker 3: load for a mutual fund. He said, if there's one

983
00:53:39,800 --> 00:53:41,799
Speaker 3: thing you take away from my classes, never pay a

984
00:53:41,800 --> 00:53:44,560
Speaker 3: load on an investment fund. And that's certainly still true today.

985
00:53:44,640 --> 00:53:47,680
Speaker 2: Yeah. Absolutely. Let's talk about books. What are some of

986
00:53:47,719 --> 00:53:49,640
Speaker 2: your favorites. What are you reading right now?

987
00:53:49,840 --> 00:53:53,480
Speaker 3: Yeah, right now I'm reading a book called The Mattering Instinct,

988
00:53:54,440 --> 00:53:57,000
Speaker 3: but I think it's Rebecca Goldstein. But it's a fascinating

989
00:53:57,000 --> 00:54:02,280
Speaker 3: book on mattering, the mattering instinct, and it's about people's

990
00:54:02,320 --> 00:54:05,400
Speaker 3: desire to matter and what that means. So there's a

991
00:54:05,400 --> 00:54:07,879
Speaker 3: lot of psychology unit there's a lot of philosophy in it.

992
00:54:08,600 --> 00:54:11,320
Speaker 3: The basic premise is that we're all just trying to

993
00:54:11,360 --> 00:54:16,480
Speaker 3: overcome entropy, so the tendency for disorder and systems to increase,

994
00:54:16,480 --> 00:54:17,560
Speaker 3: and we're all going to die eventually.

995
00:54:17,760 --> 00:54:20,040
Speaker 2: I was going to say it's a losing battle, but well,

996
00:54:20,080 --> 00:54:21,320
Speaker 2: we're here exactly.

997
00:54:21,680 --> 00:54:25,160
Speaker 3: Let's do something interesting, right, So that's what I'm reading now.

998
00:54:25,680 --> 00:54:29,000
Speaker 3: I just read prior to this, Let Them the mil

999
00:54:29,120 --> 00:54:31,200
Speaker 3: Robins book, so it's one of the I think it's

1000
00:54:31,239 --> 00:54:35,160
Speaker 3: the best selling book last year, right, So I can

1001
00:54:35,239 --> 00:54:39,080
Speaker 3: sum that one up pretty succinctly. And it's focus on

1002
00:54:39,160 --> 00:54:41,920
Speaker 3: what you can control and don't let anything else get

1003
00:54:41,920 --> 00:54:42,120
Speaker 3: to you.

1004
00:54:42,640 --> 00:54:43,560
Speaker 2: Sounds like good advice.

1005
00:54:43,600 --> 00:54:45,239
Speaker 3: It's good advice. And I mentioned that to my dad

1006
00:54:45,239 --> 00:54:48,080
Speaker 3: because he sees me reading it, and he's like, haven't

1007
00:54:48,280 --> 00:54:51,120
Speaker 3: you ever read Marcus Aurelius's Meditations? Is this is not

1008
00:54:51,200 --> 00:54:51,640
Speaker 3: a new.

1009
00:54:51,480 --> 00:54:55,600
Speaker 2: Ideaoicism created the idea of controlling what's within your control

1010
00:54:55,880 --> 00:54:57,480
Speaker 2: three thousand and two thousand years.

1011
00:54:57,280 --> 00:54:59,239
Speaker 3: Ago exactly, And I have read that, and that's a

1012
00:54:59,239 --> 00:55:01,359
Speaker 3: phenomenal book as well. It's just good to have more

1013
00:55:01,400 --> 00:55:03,520
Speaker 3: modern stories that you can relate to.

1014
00:55:04,760 --> 00:55:07,200
Speaker 2: What's keeping you entertaining These days. What are you streaming,

1015
00:55:07,280 --> 00:55:10,960
Speaker 2: either podcasts or or you know, Netflix or whatever.

1016
00:55:11,320 --> 00:55:12,879
Speaker 3: That's one of my things. I don't really do.

1017
00:55:15,360 --> 00:55:15,920
Speaker 2: Netflix. No.

1018
00:55:16,400 --> 00:55:19,000
Speaker 3: I'll watch competitive events, I'll watch sports, I'll watch, you know,

1019
00:55:19,080 --> 00:55:21,759
Speaker 3: an occasional stand up comedy show, but I don't watch

1020
00:55:21,760 --> 00:55:22,200
Speaker 3: the series.

1021
00:55:22,239 --> 00:55:24,040
Speaker 2: Did you see the Australian Open this year?

1022
00:55:24,320 --> 00:55:26,280
Speaker 3: I did. I watched some of that. It was pretty awesome.

1023
00:55:26,440 --> 00:55:28,560
Speaker 2: I have the finals d v R and I haven't.

1024
00:55:28,600 --> 00:55:31,200
Speaker 2: I haven't watched it yet, but I know you're a

1025
00:55:31,239 --> 00:55:31,839
Speaker 2: tennis guy.

1026
00:55:32,080 --> 00:55:32,319
Speaker 3: Yep.

1027
00:55:33,680 --> 00:55:37,880
Speaker 2: It's rare to find someone who can take Djokovic and

1028
00:55:37,920 --> 00:55:39,120
Speaker 2: put them back on his heels.

1029
00:55:39,239 --> 00:55:42,240
Speaker 3: Yeah. Well the Djokovic centermat which match was pretty awesome.

1030
00:55:42,360 --> 00:55:42,560
Speaker 1: Yeah.

1031
00:55:42,640 --> 00:55:46,319
Speaker 2: Yeah, I say these. I watched them like months later

1032
00:55:46,400 --> 00:55:47,400
Speaker 2: when I get around to it.

1033
00:55:47,520 --> 00:55:51,120
Speaker 3: Yeah. I do golf, so that's something I've just started taking.

1034
00:55:51,120 --> 00:55:54,040
Speaker 3: I'm terrible, you know. I'm an eighteen handicap high variants

1035
00:55:54,160 --> 00:55:56,040
Speaker 3: eighteen though, so I can have some pretty good days.

1036
00:55:57,480 --> 00:56:00,440
Speaker 3: But it's interesting because there's a similarity to investing in golf,

1037
00:56:00,480 --> 00:56:03,120
Speaker 3: which is golf. So you get better at golf by

1038
00:56:03,200 --> 00:56:04,200
Speaker 3: narrowing your misses.

1039
00:56:04,480 --> 00:56:04,719
Speaker 1: Huh.

1040
00:56:04,719 --> 00:56:06,680
Speaker 3: And I think that's also true with investing. You start

1041
00:56:06,760 --> 00:56:08,160
Speaker 3: narrowing the misses. It's a way to get better.

1042
00:56:08,239 --> 00:56:11,400
Speaker 2: Charlie Allis made the same argument with tennis. Most tennis

1043
00:56:11,400 --> 00:56:15,439
Speaker 2: players lose because they make all these unforced errors. Other

1044
00:56:15,520 --> 00:56:19,160
Speaker 2: than the pros, most of us would be better off

1045
00:56:19,960 --> 00:56:22,959
Speaker 2: being less bad rather than trying to be more good,

1046
00:56:23,040 --> 00:56:24,080
Speaker 2: if that makes any sense.

1047
00:56:24,120 --> 00:56:26,719
Speaker 3: Absolutely, you can shave a lot of strokes doing that.

1048
00:56:26,920 --> 00:56:27,160
Speaker 1: Yeah.

1049
00:56:27,239 --> 00:56:27,479
Speaker 3: Yeah.

1050
00:56:28,000 --> 00:56:31,040
Speaker 2: Final two questions, what sort of advice would you give

1051
00:56:31,080 --> 00:56:34,400
Speaker 2: to a recent college grad interested in a career in

1052
00:56:34,480 --> 00:56:39,480
Speaker 2: either investing or value or what have you?

1053
00:56:39,640 --> 00:56:39,879
Speaker 3: Choose?

1054
00:56:39,920 --> 00:56:44,960
Speaker 2: Your dad, Well, that certainly helps. I love what your

1055
00:56:45,040 --> 00:56:49,440
Speaker 2: father said to you in terms of create future optionality

1056
00:56:49,680 --> 00:56:53,839
Speaker 2: by studying and doing well in school. I've never quite

1057
00:56:53,920 --> 00:56:56,799
Speaker 2: heard it phrase that way, but that really sums up

1058
00:56:57,120 --> 00:57:00,600
Speaker 2: why do I have to study algebra? Because you were

1059
00:57:00,640 --> 00:57:01,920
Speaker 2: just creating optionality.

1060
00:57:02,480 --> 00:57:06,440
Speaker 3: Investing is about optionality and creating more options for yourself

1061
00:57:06,480 --> 00:57:09,200
Speaker 3: down the road, and so anytime you can invest in

1062
00:57:09,239 --> 00:57:12,759
Speaker 3: yourself and create additional options is a good thing to do.

1063
00:57:13,320 --> 00:57:16,280
Speaker 2: Yeah. Say the very least and our final question, what

1064
00:57:16,320 --> 00:57:21,520
Speaker 2: do you know about the world of investing, valuations, portfolio

1065
00:57:21,640 --> 00:57:25,600
Speaker 2: management today that would have been useful when you were

1066
00:57:25,640 --> 00:57:28,000
Speaker 2: first getting started twenty years ago or so.

1067
00:57:28,920 --> 00:57:31,680
Speaker 3: Well, you know, we were talking about books earlier. I

1068
00:57:31,720 --> 00:57:36,080
Speaker 3: personally think that the best book on personal finance is

1069
00:57:36,120 --> 00:57:39,480
Speaker 3: The Psychology of Money by Morgan Housels. So if you

1070
00:57:39,520 --> 00:57:42,240
Speaker 3: haven't read that, anyone that gets a bank accounts should

1071
00:57:42,240 --> 00:57:45,680
Speaker 3: be required to read that and just internalize the concepts.

1072
00:57:47,040 --> 00:57:48,439
Speaker 3: I know, if you've been in the industry a while.

1073
00:57:48,760 --> 00:57:50,480
Speaker 3: Not all of it's new, but it's a lot of

1074
00:57:50,480 --> 00:57:52,720
Speaker 3: It's a really good reminder on how you should behave

1075
00:57:53,720 --> 00:57:55,600
Speaker 3: to create wealth over the long term for yourself.

1076
00:57:55,800 --> 00:57:58,680
Speaker 2: Absolutely, Bill, thank you for coming in and for being

1077
00:57:58,680 --> 00:58:01,560
Speaker 2: so generous with your time. We have been speaking with

1078
00:58:01,640 --> 00:58:04,920
Speaker 2: Bill Miller the fourth. He is the chief investment officer

1079
00:58:04,960 --> 00:58:09,600
Speaker 2: and portfolio manager at Miller Value Funds. If you enjoy

1080
00:58:09,680 --> 00:58:12,480
Speaker 2: this conversation, well check out any of the six hundred

1081
00:58:12,480 --> 00:58:15,880
Speaker 2: we've done over the past twelve years. You can find

1082
00:58:15,920 --> 00:58:22,440
Speaker 2: those wherever you find your favorite podcasts, iTunes, Spotify, Bloomberg YouTube.

1083
00:58:23,320 --> 00:58:25,200
Speaker 2: I would be remiss if I didn't thank the Cracked

1084
00:58:25,200 --> 00:58:29,080
Speaker 2: team that helps put these conversations together each week. I'm

1085
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Speaker 2: Barry Ridults. You've been listening to Master's in Business on

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Speaker 2: Bloomberg Radio