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Speaker 1: This is Master's in Business with Barry Ridholds on Bloomberg Radio.

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Speaker 2: This week on the podcast, once again, I am fortunate

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Speaker 2: to have another extra special guest. Ted Side's has a

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Speaker 2: fascinating career in allocating capital, both on an institutional basis

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Speaker 2: and as an academic theoretical philosophical approach. Perhaps he is

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Speaker 2: best known for a bet he made on a lark

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Speaker 2: with this guy named Warren Buffett, which we spend a

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Speaker 2: lot of time talking about. Really a hilarious and amazing

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Speaker 2: conversation about this delightful experience he had. But he spent

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Speaker 2: most of his career allocating capital to various hedge funds,

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Speaker 2: private equity, venture etc. First working for David Twentzon at

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Speaker 2: Yale and then later at Protege Partners, and now talks

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Speaker 2: about the philosophy and art and science of allocation at

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Speaker 2: Capital Allocators. I found our discussion to be an absolute joy,

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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 Ted Side's of Capital Allocators.

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Speaker 1: Thanks Barry, great to be here with you.

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Speaker 2: That is quite a CV I stumbled through. Let's talk

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Speaker 2: a little bit about your alternative investments career. How did

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Speaker 2: you get started in this space.

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Speaker 1: I got lucky in a sense that when I was

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Speaker 1: an undergraduate at Yale, I took a class with David Swinson.

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Speaker 2: God, I'm just so jealous at that sentence right then

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Speaker 2: and there.

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Speaker 1: Yeah, I didn't know a whole lot about markets or stocks.

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Speaker 1: I had a mild passing interest in it. But he

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Speaker 1: mentioned in this class that they hired one person a year,

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Speaker 1: and so, alongside of Wall Street recruiting, in my senior year,

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Speaker 1: I interviewed at the Ye Investment's office. Was fortunate to

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Speaker 1: get that job and violated the two principles I had

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Speaker 1: at the time, which was I wanted to be in

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Speaker 1: a training program and I wanted to leave New Haven.

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Speaker 2: And so you stayed in New Haven and did not

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Speaker 2: enter a training program, although arguably working on just Onson

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Speaker 2: is its own sort of training program, isn't it.

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Speaker 1: Of course it was, but who knew at the time.

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Speaker 1: This was back in nineteen ninety two. So that was

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Speaker 1: my initial foray into the investment business.

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Speaker 2: So you graduate cum LAUDI from Yale, you end up

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Speaker 2: going to Harvard Business School. Tell us a little bit

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Speaker 2: about how that led you to working with some of

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Speaker 2: the managers that worked with the Yale Endowment.

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Speaker 1: Sure, well, I spent five years working for David and

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Speaker 1: learned just to a tremendous amount.

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Speaker 2: That was really your MBA right there.

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Speaker 1: That was my true investment MBA. David didn't want me

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Speaker 1: to go to Busins school. He said, you're not going

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Speaker 1: to learn anything about investing. You just stay here for

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Speaker 1: a couple more years. But I really had an interest

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Speaker 1: in trying to work directly at markets, and so my

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Speaker 1: summer job at business school, I worked for a hedge

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Speaker 1: fund that Yale had money with, and that was the

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Speaker 1: summer of ninety eight. They were value long growth short.

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Speaker 1: When Amazon went from forty dollars to two hundred and

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Speaker 1: sixty dollars the same summer, phenomenal firm.

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Speaker 2: Did long term capital management impact them at all?

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Speaker 1: No, I mean not while I was there. I was

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Speaker 1: there during the summer so that a few months later,

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Speaker 1: two months later, it did. And then when I came out,

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Speaker 1: I felt like I wanted to learn more about business

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Speaker 1: analysis compared to stocks, even though that was my passion

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Speaker 1: for stocks. So I worked at a private equity firm,

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Speaker 1: that middle market private equity firm Yell had money with,

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Speaker 1: and then I got wooed by a friend from business

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Speaker 1: school to a larger one. And those were my kind

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Speaker 1: of three formative experiences in direct investing.

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Speaker 2: Hedge fund, private equity, and Yelle endowment. Right now, that's

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Speaker 2: a that's a hell of a list. Are you still

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Speaker 2: working with any of the managers Yale or is that

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Speaker 2: along the disc.

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Speaker 1: I mean that I left Yale twenty five years ago,

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Speaker 1: so it's a little bit in the distant past.

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Speaker 2: So it's funny because for a while what we were

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Speaker 2: calling the Yale model. Really the genius of David Swinson

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Speaker 2: was that he was so early to alternatives when they

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Speaker 2: were small, they were mostly outperformers. There was a lot

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Speaker 2: of alpha generation, not a giant pond to fish in,

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Speaker 2: and the Yale model did spectacularly. What's the driver for

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Speaker 2: endowment if not under performance? Well, certainly worse performance than

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Speaker 2: we saw in the eighties, nineties and early two thousands.

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Speaker 1: Yeah, I mean, the only caveat I would give to

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Speaker 1: what you said is, I'm not sure if you measured

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Speaker 1: it properly, the performance is worse.

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Speaker 2: Oh no, it's much was it's lower. May it's lower.

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Speaker 2: That's fair.

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Speaker 1: But market returns the.

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Speaker 2: Past decade twenty ten to twenty twenty, we were what

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Speaker 2: fourteen fifteen.

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Speaker 1: Percent your benchmark, which it isn't. For these pools of capital,

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Speaker 1: what should.

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Speaker 2: Be their benchmark? That's a that's a very by the way,

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Speaker 2: very fair point your global investor. Maybe the SMP isn't

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Speaker 2: the best manage that's right.

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Speaker 1: I mean the one of the early innovative beliefs that

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Speaker 1: David Swinson had was that if you're managing a pool

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Speaker 1: of capital for what's effectively a perpetual time horizon infinite, right,

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Speaker 1: you want thoughtful diversification. So if you start with the

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Speaker 1: S and P five hundred, or in this case, stocks

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Speaker 1: and bonds, you only have two asset classes. And the

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Speaker 1: question was, if you can find other areas of investment

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Speaker 1: that can generate the types of returns you need for

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Speaker 1: your liability stream, diversification becomes the free launch. So the

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Speaker 1: proper benchmark for those pools has to look a little

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Speaker 1: bit like the underlying assets they're investing in.

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Speaker 2: Fair enough, what so what what do you use for

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Speaker 2: a benchmark? Now keep in mind, let's let's talk about

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Speaker 2: what David invested in as an example. So of course

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Speaker 2: there was stocks and bonds, but there was real estate,

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Speaker 2: There were commodities before anybody had any idea, Wait, timber,

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Speaker 2: why are we investing in timber? And then there was

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Speaker 2: venture capital and private credit and hedge funds. So how

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Speaker 2: do you create a benchmark for an allocation that looks

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Speaker 2: nothing like a sixty forty allocation?

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Speaker 1: Well you have to think about what you're trying to measure.

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Speaker 1: So one reasonable benchmark, as you said, could be a

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Speaker 1: sixty forty or seventy thirty. That's a really easy portfolio

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Speaker 1: to create, and for sure, over the last ten fifteen

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Speaker 1: years it's been hard to beat. Over a longer period

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Speaker 1: of time, maybe not so much. If you look at

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Speaker 1: the types of assets that you'll invests, and you can

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Speaker 1: create a benchmark for each pool, and that allows you

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Speaker 1: to do two things. It allows you to understand, generally speaking,

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Speaker 1: what is a reasonable beta for that whole portfolio. And

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Speaker 1: the other thing it allows you to do is to

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Speaker 1: benchmark your ability to select managers that outperform both in

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Speaker 1: each areas and across the sleeve. So you can imagine

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Speaker 1: in real estate, there's a net Creef real estate index

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Speaker 1: you could use. You could also use it read index,

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Speaker 1: though it's not the same. In private markets, there are

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Speaker 1: pure benchmarks in venture capital and private equity that you

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Speaker 1: can use, and then you can aggregate those across the

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Speaker 1: asset classes to get a benchmark for the pool as

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Speaker 1: a hole. Huh.

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Speaker 2: Really intriguing. So the two issues that have changed since

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Speaker 2: the heyday of the Yale model. One is everybody's imitating

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Speaker 2: the Yale model. So the first question is does that

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Speaker 2: create challenges for an allocator that wants to follow the

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Speaker 2: Yale model. It's no longer Hey, I got this whole

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Speaker 2: field to myself. I got five hundred other endowment's foundations

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Speaker 2: institutions trying to play in, trying to fish in this pond.

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Speaker 1: Yeah, it absolutely does. And I think when you think

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Speaker 1: through the Yale model, it helps to understand what David

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Speaker 1: was thinking as opposed to what you put a label

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Speaker 1: on the Yale model on what that means. David's brilliance

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Speaker 1: was he started everything with first principles, you know, what

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Speaker 1: makes sense? What set of beliefs do you have about

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Speaker 1: the world in investing? And then how do you go

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Speaker 1: about and applying that with extreme discipline. He kind of

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Speaker 1: wrote about that in his book, and people look at

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Speaker 1: that and say, oh, I can replicate that, But most

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Speaker 1: people have trouble having their own beliefs and then sticking

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Speaker 1: to them when the rubber meets the road. In terms

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Speaker 1: of execution. The other piece of it that David had

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Speaker 1: that no one really could replicate is this deep belief

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Speaker 1: in continuous improvement and incredible vision to see both, you know,

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Speaker 1: big opportunities like you could think about hedge funds way

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Speaker 1: back when, and then also small opportunities. So he thought

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Speaker 1: about fees thirty five forty years ago before anyone else,

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Speaker 1: and when you could do something about.

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Speaker 2: It, it was him and Jack Bogel. That was pretty

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Speaker 2: much it. Yeah, thinking about fees. So the other side

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Speaker 2: of this is, and I'm gonna channel Jim Chenos who

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Speaker 2: said of Kinnico's associates famous shorts, he said, you know,

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Speaker 2: in the eighties there was five hundred hedge funds. They

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Speaker 2: all generated alpha. Now there's eleven thousand hedge funds and

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Speaker 2: five hundred generating alpha. So the other challenge is how

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Speaker 2: do you choose from the pool of eleven thousand hedge

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Speaker 2: funds and ten thousand venture funds and god knows how

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Speaker 2: many private equity funds and private credit funds. Making the

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Speaker 2: choice within the allocation seems to have become a whole

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Speaker 2: lot more difficult, more complex, and even if you find

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Speaker 2: a fund manager you really like, you're now competing with

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Speaker 2: other LPs to put your billion dollars there.

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Speaker 1: Yeah, that's absolutely right, And depending on the asset class,

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Speaker 1: there are a different set of lenses. But just to

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Speaker 1: use that example, in long short equity investing, the first

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Speaker 1: question you have to ask is is that a place

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Speaker 1: you want to be anymore?

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Speaker 2: Right?

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Speaker 1: Because it is a much tougher game, particularly adding value

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Speaker 1: on the short side.

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Speaker 2: Than shorting has always been hard. There's this there's this

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Speaker 2: myth that people put out a short position and then

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Speaker 2: talk it down and just count the money. It's much

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Speaker 2: harder than that.

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Speaker 1: Yeah, So I think selecting managers in any asset class

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Speaker 1: has that two pieces right. So one is going back

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Speaker 1: to David's first principles. What do you believe about what

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Speaker 1: type of manager should outperform it. There's some people who

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Speaker 1: think fundamental discretionary investing with people who know their business

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Speaker 1: is better than anyone else is the right way to

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Speaker 1: do it. There are other people that think, no, you

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Speaker 1: need to be large and systematic, like Citadel or Millennium.

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Speaker 1: There's no right or wrong, but you have to follow

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Speaker 1: your own set of beliefs for what you think will

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Speaker 1: work for your pool. The other piece of it, say,

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Speaker 1: in something like venture capital, which you mentioned, access really matters,

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Speaker 1: and that's where you could look at a Yale and

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Speaker 1: say they had a first mover advantage thirty years ago.

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Speaker 1: They are already in the top tier venture managers who

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Speaker 1: don't take money from anybody else. And there are a

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Speaker 1: lot of investors say that I have on the podcast

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Speaker 1: to say, if we can't get into those top venture

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Speaker 1: you don't have an allocation to venture. You have a

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Speaker 1: group of managers and you take what you can get,

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Speaker 1: but you don't extend beyond what you believe or the

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Speaker 1: very top tier, because the dispersion of returns in that

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Speaker 1: asset class is really wide, and you only want to

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Speaker 1: be intay that top quarte.

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Speaker 2: So we'll circle back to this podcast thing you referenced

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Speaker 2: later because I'm interested in that. But I love the

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Speaker 2: idea of the first move advantage. When you think about

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Speaker 2: the Yale model. When Swanson was first allocating to these

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Speaker 2: other asset types, commodities, lands, alternatives, it was the wild West,

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Speaker 2: it was wide open. How much of an advantage did

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Speaker 2: he have being a pioneer in those spaces. The old

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Speaker 2: joke is yeah, yeah, the second mouse gets the cheese.

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Speaker 2: In this case, it looks like the first mouse got

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Speaker 2: the jets.

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Speaker 1: It was shooting fish in a barrow. Really, when I

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Speaker 1: worked at Yale, the hardest part of the game was

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Speaker 1: understanding that the game was getting played, knowing where to

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Speaker 1: go to access it, and then on top of that,

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Speaker 1: having your board approval to let you do it. So

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Speaker 1: to give you some examples of that, I joined Yale

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Speaker 1: in ninety two. David was there in eighty five. There

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Speaker 1: were some venture investments. When they got there. It wasn't

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Speaker 1: a full thing, but they loved it. They quickly understood

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Speaker 1: the potential for that. Oh the board, no yell David

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Speaker 1: and Dean Takashi the team at Yale.

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Speaker 2: But did the oversight. The governance was already in place.

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Speaker 1: They really did.

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Speaker 2: That's a huge aspect of Yale's success, no doubt the success.

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Speaker 1: Of that governance. So they then had time to go

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Speaker 1: to Silicon Valley to meet with the people, to see

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Speaker 1: over a decade who was good and who wasn't, to

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Speaker 1: ask questions and to make mistakes. That's a huge first

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Speaker 1: move advantage. By the time I got there in ninety two,

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Speaker 1: they had a great venture portfolio and almost nobody else

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Speaker 1: even understood what venture.

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Speaker 2: Capital was just starting to run up up ninety three,

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Speaker 2: ninety four, ninety five, and by late nineties everyone had

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Speaker 2: been piling in. If you're there a decade before, talk

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Speaker 2: about first movie, Oh my goodness.

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Speaker 1: And hedge funds were the same way. To give you

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Speaker 1: a fun story. We launched Protege Partners in two thousand

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Speaker 1: and two. In that period of time ninety two to two,

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Speaker 1: you really had a golden era of hedge funds in

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Speaker 1: terms of returns.

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Speaker 2: Now, the whole pre financial crisis decade or two, hedge

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Speaker 2: funds crushed crushed it, or at least the top pick

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Speaker 2: a number thirty forty percent less twenty thirty percent.

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Speaker 1: I know. Back then the premier job in asset management

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Speaker 1: was to run Fidelity Magellan. There was no reason to

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Speaker 1: think people would make billions of dollars running hedge funds.

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Speaker 1: It was such a boutique industry. I used to say

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Speaker 1: that the guys who ran hedgehunds were the one who

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Speaker 1: woke up on the wrong side of the bed in

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Speaker 1: the morning and felt like they just had to short

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Speaker 1: because things were going wrong. So when we launched Protege,

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Speaker 1: we had we had a classification of hedge funds and

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Speaker 1: said we're going to not invest in the large ones.

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Speaker 1: In two thousand and two, the bucket of the largest

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Speaker 1: hedge funds was those north of one billion dollars. And

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Speaker 1: then I started reaching out to some of the managers

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Speaker 1: I knew for my time at Yale, and one of

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Speaker 1: them said to me, we're closed. We have a weight list,

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Speaker 1: and I said, what what is that? He said, I

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Speaker 1: don't know. But all of a sudden people have said,

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Speaker 1: why don't you start a wait list?

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Speaker 2: We're at a capacity And that's that.

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Speaker 1: Before two thousand and two, there were no capacity issues

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Speaker 1: with whoever you thought the best hedge funds were.

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Speaker 2: And subsequently there's been some academic research that has implied,

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Speaker 2: I don't want to say you found, but strongly implied

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Speaker 2: that much and again much not most of the alpha

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Speaker 2: is coming from the emerging managers, you know.

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Speaker 1: So that was the premise of the business we started

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Speaker 1: at Protege, and I would tell you that whow true

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Speaker 1: in that academic research, it's all deeply flawed.

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Speaker 2: Well, there's a little hindsight bias built in.

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Speaker 1: Right, there's hindsight bias. The data of the managers you

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Speaker 1: really want to measure isn't included, and.

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Speaker 2: It's all self reported, right.

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Speaker 1: And then I've never seen a study who said that

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Speaker 1: the large managers were anything north of fifty million in

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Speaker 1: assets the large managers. So you look at those studies,

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Speaker 1: they see these small ones are less than five million.

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Speaker 2: Million or billion. Are we talking like that's a typo?

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Speaker 2: It sounds like because do you look at Millennium and

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Speaker 2: Citadel and oak Tree and correct AQR which just had

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Speaker 2: a fantastic year, and Bridgewater We're talking fifty one hundred,

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Speaker 2: one hundred and fifty billion dollars. These are massive pols.

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Speaker 1: The promise the academics should do the research don't have

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Speaker 1: access to the performance data of the funds that matter.

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Speaker 1: None of them are call it asset weighted. And so

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Speaker 1: those studies, while true and while they seem to have

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Speaker 1: an intellectual vigor to them in thought process, they're really

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Speaker 1: not based on anything in the real world of the

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Speaker 1: investment market.

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Speaker 2: So all of this tease up the obvious question, was

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Speaker 2: Warren Buffett right or most people better off in an

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Speaker 2: index fund than playing with an active manager, be it

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Speaker 2: a mutual fund or high fee hedge funds.

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Speaker 1: Yeah, I said back then the bets started in two

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Speaker 1: thousand and seven, and I say today, being in the

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Speaker 1: market and investing in hedge funds is completely apples and oranges.

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Speaker 1: So for a taxable investor, hedge funds generally aren't tax efficient.

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Speaker 1: And when you look at the assets that are invested

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Speaker 1: the three trillion in hedge funds, I would guess that

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Speaker 1: north of ninety percent of that are in institutions that

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Speaker 1: don't pay.

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Speaker 2: Tax, so foundations, endowments.

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Speaker 1: So as an individual it probably doesn't make sense generally speaking.

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Speaker 1: As an institution, it has a very different risk return

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Speaker 1: profile that, when done well, fits in really well with

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Speaker 1: the diversified portfolio that we talked about earlier.

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Speaker 2: You have to tell us how where did the idea

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Speaker 2: come from? How did you reach out to Buffet? And

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Speaker 2: what was his response?

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Speaker 1: Yeah, well, in you have to go back. This is

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Speaker 1: the summer of two thousand and.

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Speaker 2: Seven seven, So let me set the table a little bit. Yeah,

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Speaker 2: the run up in the dot COM's to two thousand,

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Speaker 2: I have a vivid recollection of people saying, ah, Buffet's

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Speaker 2: all these lustes touch right. Then everything implodes and again

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Speaker 2: Buffett is outperforming for a while posts October Lows and

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Speaker 2: two March double bottom, O three the invasion of Iraq.

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Speaker 2: By the time you get to seven, market's up eighty

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Speaker 2: ninety percent from the lows, and housing is just about

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Speaker 2: peaking and things are starting to come apart around then

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Speaker 2: by seven it's pretty clear that the housing bears are

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Speaker 2: are gonna be right.

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Speaker 1: That's right. So I had seen that Warren had made

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Speaker 1: a comment to a bunch of students. So a year

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Speaker 1: or two before that he had written about fees, the

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Speaker 1: head rocks, and the gut rocks, and I guess he

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Speaker 1: had made some throwwake that hedge funds could never beat

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Speaker 1: the market. A student asked him about it, and his

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Speaker 1: response was, well, no one's taken me up on it,

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Speaker 1: so I must be right.

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Speaker 2: Meaning no one's taking me up on his statement. Or

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Speaker 2: did he lay out a challenge.

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Speaker 1: I'm not quite sure because I didn't hear what he

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Speaker 1: originally said, but it came off as it was a

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Speaker 1: form of a challenge. And at the time I was

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Speaker 1: managing proj Partners with a hedge fund of funds. We

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Speaker 1: were short subprime mortgages with John.

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Speaker 2: You were crushing it. Let me say what Your compliance

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Speaker 2: wouldn't allow you to say. You guys were killing it

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Speaker 2: in the mid two thousands.

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Speaker 1: We had a great run. And I read a statement

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Speaker 1: and my thought was, look, he's Warren Buffett, but he

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Speaker 1: just made a really bad bet because for all the

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Speaker 1: reasons you just said, the S and P was trading

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Speaker 1: it all time highs. And let's keep mind interest rates

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Speaker 1: were normalized then and.

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Speaker 2: What mid they had just started going up.

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Speaker 1: Well rates short term rates were four or five six.

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Speaker 2: Pers Okay, so reasonable, right?

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Speaker 1: And I looked at that and said, well, you know

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Speaker 1: you wouldn't want to bet on the market over ten

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Speaker 1: years starting at that point in time. And meanwhile, hedge

364
00:19:09,760 --> 00:19:13,080
Speaker 1: funds had been cranking along, generating market like returns with

365
00:19:13,119 --> 00:19:16,720
Speaker 1: a lot less volatility. And so I wrote him a

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Speaker 1: one page letter and mail or hard C. I didn't

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Speaker 1: have his email, so I sent it snail mail, and

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00:19:23,800 --> 00:19:28,320
Speaker 1: he sent back through his assistant a PDF with a

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00:19:28,359 --> 00:19:31,359
Speaker 1: little chicken scratch response, and I made the letter. I

370
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Speaker 1: actually put the letter in my first book to describe

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Speaker 1: how you get somebody's attention. And he said, well, it

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Speaker 1: has to be this and that and has to be

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Speaker 1: clatteralized with a letter of credit. And I was like what,

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Speaker 1: And so I sent me another.

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Speaker 2: Specifically the bet. He wanted cash up front credit It's unclear,

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Speaker 2: but he didn't want anybody just sort of, you know,

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Speaker 2: fooling around. He wanted serious.

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Speaker 1: Correct. It felt a little dismissive. So I sent him

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Speaker 1: another one. I said, Okay, fine of you say, and

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Speaker 1: then he's warm Buffett.

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Speaker 2: Why are you gonna argue with him about it? Right?

382
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Speaker 2: Started the terms great, I'm in Yeah. It started a back.

383
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Speaker 1: And forth series of letters. It was all written out

384
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Speaker 1: that was hysterical.

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Speaker 2: But by the way, I just picture I just I

386
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Speaker 2: just picture this as a sort of sort of a

387
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Speaker 2: Civil War soldier writing home dearest Martha. I am considering

388
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Speaker 2: it like in the two thousands, you guys are sending

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Speaker 2: letters back and forth.

390
00:20:33,359 --> 00:20:37,320
Speaker 1: Yeah, that's right. And it got to the point where

391
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Speaker 1: there was the potential to do this nonprofit like charitable bet.

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Speaker 2: By the way, I don't even have to ask, but

393
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Speaker 2: I'm gonna ask. You have all these letters saved framed somewhere,

394
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Speaker 2: like please tell me you kept ev.

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Speaker 1: It's in a PDF.

396
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Speaker 2: But I mean the originals, the original so three, four,

397
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Speaker 2: five times, how many times back.

398
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Speaker 1: And forth something like that. Yeah, don't remember the exact amount.

399
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Speaker 1: And I had originally said, hey, let's bet dinner at

400
00:21:03,960 --> 00:21:07,239
Speaker 1: Gorat's his favorite place. Maybe one hundred thousand dollars your

401
00:21:07,240 --> 00:21:09,200
Speaker 1: annual salary all that kind of stuff.

402
00:21:09,200 --> 00:21:10,679
Speaker 2: Oh, no, he wants to step it up.

403
00:21:11,000 --> 00:21:13,600
Speaker 1: He said that his estate planners would be thought he

404
00:21:13,640 --> 00:21:16,639
Speaker 1: was nuts anyway for doing something so small. But yeah,

405
00:21:16,720 --> 00:21:20,359
Speaker 1: So I went and talked to my partners at Protege,

406
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Speaker 1: Scott Besseno, who now runs a macro hedge fund ransros

407
00:21:23,440 --> 00:21:25,760
Speaker 1: after for a year my original partner passed by a

408
00:21:25,760 --> 00:21:27,800
Speaker 1: couple of years ago and said, hey, by the way,

409
00:21:27,840 --> 00:21:31,200
Speaker 1: I've been corresponding with Warren about there, like what And

410
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Speaker 1: Scott read the letters and he said, I'll never forget this.

411
00:21:34,160 --> 00:21:38,919
Speaker 1: He said, huh, it looks like Warren recognizes he's the

412
00:21:38,960 --> 00:21:42,560
Speaker 1: patsy at the poker table, but he has the most chips, right,

413
00:21:43,000 --> 00:21:45,440
Speaker 1: Because every time I'd say okay, let's do it this way,

414
00:21:45,480 --> 00:21:47,359
Speaker 1: there was something back that said, well, it has to

415
00:21:47,400 --> 00:21:48,840
Speaker 1: be like this, And it got to the point where

416
00:21:48,840 --> 00:21:50,239
Speaker 1: he said, okay, do we want to do this or not?

417
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Speaker 1: And then it's actually hard to make a legal bet.

418
00:21:54,160 --> 00:21:57,400
Speaker 1: It's probably easier now right there, Some betting is legal loss.

419
00:21:57,480 --> 00:22:00,840
Speaker 1: But then it wasn't. And he found through his lawyer

420
00:22:00,960 --> 00:22:04,879
Speaker 1: a foundation called the Long Bets. They've been around for

421
00:22:04,920 --> 00:22:08,240
Speaker 1: a long time that allows you to make charitable bets

422
00:22:08,280 --> 00:22:12,280
Speaker 1: based on long term educational beliefs. And so that's what

423
00:22:12,320 --> 00:22:14,600
Speaker 1: we did, and we we find we made it for

424
00:22:14,640 --> 00:22:18,680
Speaker 1: a million dollars. We split the value, we split the

425
00:22:18,720 --> 00:22:21,560
Speaker 1: amount and bought a zero coupon bond of the present

426
00:22:21,640 --> 00:22:24,320
Speaker 1: value upfront, so back in.

427
00:22:24,359 --> 00:22:26,560
Speaker 2: So ten years in advance with a four or five

428
00:22:26,640 --> 00:22:28,280
Speaker 2: so ourse like four hundred it.

429
00:22:28,359 --> 00:22:31,520
Speaker 1: Was six hundred and fifty is put in three twenty

430
00:22:31,560 --> 00:22:34,680
Speaker 1: five something. Oh really, and then the money would go

431
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Speaker 1: to the winner's charity at the end of ten.

432
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Speaker 2: That's a very reasonable bet. That's a very honorable bet

433
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Speaker 2: because it's not a matter of taking money from one

434
00:22:44,000 --> 00:22:48,360
Speaker 2: person or another. Both people are kicking money in so technically,

435
00:22:49,000 --> 00:22:51,960
Speaker 2: and that's probably why it was legal. There's no gambling.

436
00:22:52,119 --> 00:22:54,159
Speaker 1: And I'll tell you a story that's fun about the

437
00:22:54,160 --> 00:22:57,920
Speaker 1: communication of it too. So Warren wanted to announce this

438
00:22:58,760 --> 00:23:02,560
Speaker 1: at his annual meeting every year here and originally I

439
00:23:02,640 --> 00:23:04,280
Speaker 1: wanted to make it anonymous. So there's a bunch of

440
00:23:04,320 --> 00:23:06,160
Speaker 1: reasons why it didn't end up being that way.

441
00:23:06,280 --> 00:23:08,520
Speaker 2: Did he Was he going to have you at the

442
00:23:08,560 --> 00:23:10,639
Speaker 2: annual meeting? Was that the plan? Or was he just

443
00:23:10,680 --> 00:23:12,000
Speaker 2: going to announce that was independent.

444
00:23:12,520 --> 00:23:14,080
Speaker 1: I did go a bunch of years.

445
00:23:14,119 --> 00:23:16,120
Speaker 2: But I mean on stage to the audience.

446
00:23:16,119 --> 00:23:19,040
Speaker 1: Oh no, let everybody boo and no, no, no, that

447
00:23:19,080 --> 00:23:20,880
Speaker 1: was never a part of the plan. Didn't happen. What

448
00:23:20,960 --> 00:23:22,720
Speaker 1: was interesting was I had said to him, well, let's

449
00:23:22,720 --> 00:23:25,879
Speaker 1: make this really educational. I'm happy to have you announce

450
00:23:25,960 --> 00:23:29,159
Speaker 1: the results, but let's only announce the result after a

451
00:23:29,200 --> 00:23:31,879
Speaker 1: period of time when the markets dropped ten percent, because

452
00:23:31,920 --> 00:23:34,560
Speaker 1: I think that'll show the value of a hedgemomp portfolio.

453
00:23:34,680 --> 00:23:35,600
Speaker 2: And what did he say?

454
00:23:35,880 --> 00:23:37,720
Speaker 1: He said, no, no, this is part of the cat

455
00:23:37,720 --> 00:23:39,359
Speaker 1: and mouse. No, no, no, I think we need it.

456
00:23:39,560 --> 00:23:41,040
Speaker 1: Right from the beginning, I was like, yeah, but this

457
00:23:41,080 --> 00:23:43,240
Speaker 1: isn't a horse race. This is about investing. He said, no, no,

458
00:23:43,280 --> 00:23:44,080
Speaker 1: I think we needed.

459
00:23:43,840 --> 00:23:46,119
Speaker 2: It is a horse race because there's a start and

460
00:23:46,160 --> 00:23:47,440
Speaker 2: a finish.

461
00:23:47,720 --> 00:23:52,199
Speaker 1: So that's how it came about. It started on January

462
00:23:52,320 --> 00:23:53,760
Speaker 1: one of two thousand and eight.

463
00:23:54,080 --> 00:23:57,040
Speaker 2: Great timing for hedge funds. Right, you would.

464
00:23:56,800 --> 00:24:01,200
Speaker 1: Think, and it played out that way. It took about

465
00:24:01,640 --> 00:24:04,800
Speaker 1: five years for the market to catch up from that

466
00:24:04,880 --> 00:24:07,879
Speaker 1: one year of pain, and it wasn't glory days for

467
00:24:07,920 --> 00:24:09,960
Speaker 1: hedge funds, right. Once Lehman went under, that caused a

468
00:24:10,000 --> 00:24:11,360
Speaker 1: lot of pain for hedge funds as well.

469
00:24:12,600 --> 00:24:15,840
Speaker 2: One would have thought they would have seen that writing

470
00:24:15,880 --> 00:24:18,320
Speaker 2: on the wall. But let's that's that's a topic for

471
00:24:18,359 --> 00:24:21,080
Speaker 2: another conversation. If you're a long short fund at the

472
00:24:21,160 --> 00:24:24,760
Speaker 2: very least, and David Einhorn and others very famously was

473
00:24:24,800 --> 00:24:26,160
Speaker 2: short Lehman Brothers.

474
00:24:26,200 --> 00:24:29,000
Speaker 1: Yeah, no, you're right about the securities that the challenge is.

475
00:24:29,160 --> 00:24:32,040
Speaker 1: Unlike the S and P five hundred, hedge funds sit

476
00:24:32,160 --> 00:24:36,159
Speaker 1: in a box that has underlying credit risk from prime brokers.

477
00:24:36,160 --> 00:24:39,119
Speaker 1: So the credit markets froze, and that wasn't a question

478
00:24:39,160 --> 00:24:41,720
Speaker 1: of security prices going down. It's a question of like

479
00:24:41,760 --> 00:24:43,199
Speaker 1: can you transact? And what is that?

480
00:24:43,560 --> 00:24:47,320
Speaker 2: My colleague Ben Carlson calls that organizational alpha, and it's

481
00:24:47,320 --> 00:24:53,000
Speaker 2: a great phrase because suddenly the infrastructure gets creaky and

482
00:24:53,080 --> 00:24:57,720
Speaker 2: you can't do anything that's right. So fascinating to hear

483
00:24:57,760 --> 00:25:03,560
Speaker 2: that Buffett is so coy about this, right, tell everybody

484
00:25:03,640 --> 00:25:05,160
Speaker 2: what the result was ten years later.

485
00:25:05,160 --> 00:25:08,160
Speaker 1: So after ten years, FED comes in, the market probably

486
00:25:08,240 --> 00:25:10,160
Speaker 1: generates seventeen to eighteen percent a year for the last

487
00:25:10,240 --> 00:25:12,480
Speaker 1: nine years, and the SMP five hundred beats the hedge

488
00:25:12,480 --> 00:25:13,880
Speaker 1: funds by a wide margin.

489
00:25:13,760 --> 00:25:18,960
Speaker 2: Right, crushes it. And you basically preempted my question, which

490
00:25:19,000 --> 00:25:20,520
Speaker 2: was why do you think that was?

491
00:25:20,520 --> 00:25:20,639
Speaker 1: So?

492
00:25:20,800 --> 00:25:24,240
Speaker 2: Was it the financial crisis? Was it QE, was it ZERP?

493
00:25:24,440 --> 00:25:27,720
Speaker 2: What was the real reason that the hedge funds just

494
00:25:27,840 --> 00:25:30,240
Speaker 2: never caught up after a great start.

495
00:25:30,520 --> 00:25:33,320
Speaker 1: Yeah, well again I would look at it differently. So

496
00:25:33,520 --> 00:25:36,920
Speaker 1: you have the market which got crushed and then FED

497
00:25:36,960 --> 00:25:39,000
Speaker 1: comes in, and you end up with seven or eight

498
00:25:39,040 --> 00:25:42,359
Speaker 1: percent a year, which is a historical average, right, including

499
00:25:42,400 --> 00:25:45,199
Speaker 1: the biggest crisis since nineteen twenty nine, So you wouldn't

500
00:25:45,240 --> 00:25:47,399
Speaker 1: expect that ten year period to have a historical average

501
00:25:47,400 --> 00:25:50,679
Speaker 1: return on the hedge fund side. A couple things happened. First,

502
00:25:50,680 --> 00:25:54,000
Speaker 1: as you talked about earlier, you had in that decade

503
00:25:54,040 --> 00:25:57,040
Speaker 1: a lot more competition, You had a lot more money

504
00:25:57,080 --> 00:26:00,359
Speaker 1: coming in, and I think it's reasonable to think that

505
00:26:00,400 --> 00:26:05,119
Speaker 1: the alpha pool shrunk, So that's one. The second is structural,

506
00:26:05,440 --> 00:26:08,159
Speaker 1: which we haven't seen in fifteen years, but we're starting

507
00:26:08,200 --> 00:26:11,000
Speaker 1: to see now, which is hedge from returns are a

508
00:26:11,040 --> 00:26:15,040
Speaker 1: direct function of the level of interest rates. Huh, Because

509
00:26:15,080 --> 00:26:17,520
Speaker 1: when you put out a short position, you get a

510
00:26:17,520 --> 00:26:20,600
Speaker 1: short rebate, and when the FED brought rates to zero,

511
00:26:20,760 --> 00:26:22,920
Speaker 1: not only were you not getting a rebate, you were

512
00:26:22,960 --> 00:26:23,680
Speaker 1: paying to short.

513
00:26:23,880 --> 00:26:25,880
Speaker 2: You always have to pay to borrow. But usually there's

514
00:26:25,880 --> 00:26:26,800
Speaker 2: an offset at zero.

515
00:26:26,920 --> 00:26:29,960
Speaker 1: There's no offset right at five percent. Where we are today,

516
00:26:30,040 --> 00:26:32,080
Speaker 1: you're probably making three and a half percent a year

517
00:26:32,160 --> 00:26:35,160
Speaker 1: just for showing up. So there was a structural piece.

518
00:26:35,200 --> 00:26:37,600
Speaker 1: You think about the difference between zero and three and

519
00:26:37,640 --> 00:26:40,360
Speaker 1: a half percent, it's actually pretty similar to the difference

520
00:26:40,480 --> 00:26:42,439
Speaker 1: in what the S and P generated during that period

521
00:26:42,440 --> 00:26:43,520
Speaker 1: and what hedge fund's generated.

522
00:26:44,119 --> 00:26:46,480
Speaker 2: So here's the pushback to that. And I think you

523
00:26:47,000 --> 00:26:51,200
Speaker 2: said it before. You said you wouldn't have expected that

524
00:26:51,240 --> 00:26:56,520
Speaker 2: there would have been this outsized return following the financial crisis.

525
00:26:57,119 --> 00:27:00,280
Speaker 2: But that's the whole point of the bet. Managers didn't

526
00:27:00,280 --> 00:27:03,720
Speaker 2: expect it, and the SMP doesn't care. The SMP rides that,

527
00:27:04,280 --> 00:27:09,880
Speaker 2: and so the winner was the lack of human judgment

528
00:27:09,960 --> 00:27:13,639
Speaker 2: by a dumb index as opposed to managers. So I

529
00:27:13,680 --> 00:27:17,600
Speaker 2: have a very vivid recollection of the financial crisis not

530
00:27:17,760 --> 00:27:20,240
Speaker 2: just because I was trading around it and more or

531
00:27:20,320 --> 00:27:22,840
Speaker 2: less got it right, but I was writing a book

532
00:27:23,080 --> 00:27:26,879
Speaker 2: and publishing it online as I was writing it, researching

533
00:27:26,880 --> 00:27:30,800
Speaker 2: it online, and the pushback in nine and ten and

534
00:27:30,840 --> 00:27:36,120
Speaker 2: eleven and twelve to the bullmarket. My philosophy has always been, hey,

535
00:27:36,200 --> 00:27:39,080
Speaker 2: take a US index, cut it in half. I'm a

536
00:27:39,119 --> 00:27:40,919
Speaker 2: buyer right there. I don't care what's going on the

537
00:27:40,920 --> 00:27:46,359
Speaker 2: rest of the world twenty nine, eighty seven, seventy four.

538
00:27:47,160 --> 00:27:50,800
Speaker 2: Just pick any fifty plus percent number, and certainly two

539
00:27:50,880 --> 00:27:54,760
Speaker 2: thousand and eight oh nine, a major index gets cut

540
00:27:54,760 --> 00:27:57,240
Speaker 2: in half, you want to at least put a toe

541
00:27:57,240 --> 00:28:00,840
Speaker 2: in the water, if not not go large. So that

542
00:28:00,920 --> 00:28:04,080
Speaker 2: was what was so shocking to me that no one

543
00:28:04,840 --> 00:28:06,840
Speaker 2: or I shouldn't say that. What was so shocking to

544
00:28:06,840 --> 00:28:11,119
Speaker 2: me was how much pushback people gave in the early

545
00:28:11,200 --> 00:28:16,720
Speaker 2: part of the twenty tens following a giant reset, free money,

546
00:28:16,920 --> 00:28:19,879
Speaker 2: zero cost of capital, some but not a lot of

547
00:28:19,880 --> 00:28:25,680
Speaker 2: fiscal stimulus. I think a lot of fund managers had

548
00:28:26,040 --> 00:28:28,680
Speaker 2: I like to call it zero edge. You know that

549
00:28:29,320 --> 00:28:32,280
Speaker 2: they had a narrative they believed in and no amount

550
00:28:32,320 --> 00:28:35,200
Speaker 2: of data would change their mind. Is that a fair

551
00:28:35,400 --> 00:28:37,680
Speaker 2: pushback to this is why the S and P five

552
00:28:37,760 --> 00:28:40,440
Speaker 2: hundred beat a bunch of hedge fund managers.

553
00:28:40,720 --> 00:28:44,800
Speaker 1: I think it's always fair to say you believe arry

554
00:28:44,880 --> 00:28:47,080
Speaker 1: part of your belief systems that a hedge fund is

555
00:28:47,120 --> 00:28:49,520
Speaker 1: supposed to capture these moves in markets.

556
00:28:49,360 --> 00:28:51,120
Speaker 2: Some of them, one would think, right.

557
00:28:51,080 --> 00:28:52,960
Speaker 1: I'm sure some of them did and some of them didn't.

558
00:28:53,000 --> 00:28:55,560
Speaker 1: So you're talking about an average of a large number.

559
00:28:56,400 --> 00:28:59,280
Speaker 1: I would say, that's not really part of my belief

560
00:28:59,320 --> 00:29:02,200
Speaker 1: system of what hedge funds trying to deliver. It's much

561
00:29:02,280 --> 00:29:06,080
Speaker 1: more about security selection and a relatively static portfolio construction.

562
00:29:06,640 --> 00:29:09,600
Speaker 1: So I think that argument is very valid. In those

563
00:29:09,680 --> 00:29:13,000
Speaker 1: couple of years two thousand and nine, twenty ten, probably

564
00:29:13,280 --> 00:29:15,720
Speaker 1: maybe twenty eleven, which was a tough year for hedgehunts,

565
00:29:16,400 --> 00:29:19,560
Speaker 1: you still had twenty twelve to two thousand and seventeen

566
00:29:19,640 --> 00:29:23,000
Speaker 1: to finish the bet, and that was just the market

567
00:29:23,040 --> 00:29:25,040
Speaker 1: what we've seen in tech stocks. It was just a

568
00:29:25,160 --> 00:29:27,920
Speaker 1: very very hard index to beat, no matter what you

569
00:29:27,960 --> 00:29:28,360
Speaker 1: were doing.

570
00:29:28,640 --> 00:29:31,800
Speaker 2: So here's the lesson I learned from your bet. Because

571
00:29:31,840 --> 00:29:36,480
Speaker 2: I was very alternatives are too expensive. Everything is pricedy.

572
00:29:36,520 --> 00:29:40,120
Speaker 2: These guys all eventually underperform. But I've evolved that view

573
00:29:40,160 --> 00:29:43,880
Speaker 2: over time to hey, if you could get into the top.

574
00:29:44,000 --> 00:29:48,440
Speaker 2: Deccyle right. I once was speaking somewhere and trashing hedge

575
00:29:48,480 --> 00:29:51,480
Speaker 2: funds and someone said, I have an allocation that I

576
00:29:51,560 --> 00:29:53,960
Speaker 2: inherited from my father in d E Shaw. Are you

577
00:29:54,040 --> 00:29:55,840
Speaker 2: telling me I should sell that? And my answer was

578
00:29:55,960 --> 00:29:59,800
Speaker 2: absolutely not. If you're in go down the list of

579
00:29:59,840 --> 00:30:02,280
Speaker 2: the top. I don't know one hundred hedge funds out

580
00:30:02,280 --> 00:30:06,840
Speaker 2: of eleven thousand. There the alpha generators. The challenge is

581
00:30:06,880 --> 00:30:11,000
Speaker 2: the median is very different than the experience you had

582
00:30:11,160 --> 00:30:14,440
Speaker 2: at Yale when there were five hundred hedge funds and

583
00:30:14,840 --> 00:30:16,240
Speaker 2: five hundred alpha generators.

584
00:30:16,520 --> 00:30:19,640
Speaker 1: It's much harder with more capital there. But you have

585
00:30:19,720 --> 00:30:21,920
Speaker 1: to keep in mind that what you see in an

586
00:30:21,960 --> 00:30:26,160
Speaker 1: index tends to be equal weighted, and the experience of

587
00:30:26,200 --> 00:30:31,200
Speaker 1: investors is asset weighted by definition. So where institutional investors

588
00:30:31,240 --> 00:30:34,080
Speaker 1: have their money in hedge funds is with d Shaw,

589
00:30:34,240 --> 00:30:37,040
Speaker 1: it is with Millennium, it is with Citadel, and these

590
00:30:37,080 --> 00:30:41,120
Speaker 1: firms have continued to generate call it alpha excess returns,

591
00:30:41,600 --> 00:30:45,320
Speaker 1: and that's why the assets have stayed in call it

592
00:30:45,360 --> 00:30:47,920
Speaker 1: the asset class or the strategies. When there's so much

593
00:30:47,960 --> 00:30:51,120
Speaker 1: scrutiny about oh, the hedge fund index did this. Every

594
00:30:51,120 --> 00:30:53,800
Speaker 1: hedge fund index is equal weighted, and that is not

595
00:30:53,920 --> 00:30:55,040
Speaker 1: the experience of investments.

596
00:30:55,240 --> 00:31:01,480
Speaker 2: I've evolved towards your position because my criticism of the

597
00:31:01,560 --> 00:31:05,720
Speaker 2: industry turns out to be somebody said to me, you know,

598
00:31:05,800 --> 00:31:09,000
Speaker 2: you're really criticizing the bottom ninety percent of the industry.

599
00:31:09,360 --> 00:31:13,440
Speaker 2: I'm like, okay, that's a fair critique of my criticism.

600
00:31:13,960 --> 00:31:16,840
Speaker 2: If you're in the top ten percent of anything, well,

601
00:31:16,920 --> 00:31:18,240
Speaker 2: God blessed, stay there.

602
00:31:18,320 --> 00:31:18,520
Speaker 1: Yeah.

603
00:31:18,640 --> 00:31:22,640
Speaker 2: But if you're not in one of the better alternatives,

604
00:31:23,320 --> 00:31:25,640
Speaker 2: what are you paying for? Is really the question. And

605
00:31:25,680 --> 00:31:30,400
Speaker 2: I think that's the underlying side of the buffet bet.

606
00:31:30,560 --> 00:31:35,280
Speaker 2: With all the coyness and all his gamesmanship, he wasn't

607
00:31:35,280 --> 00:31:38,440
Speaker 2: the patsy at the poker table. I think he was

608
00:31:38,480 --> 00:31:42,560
Speaker 2: just playing a different game and nobody realized it until

609
00:31:42,560 --> 00:31:47,280
Speaker 2: way afterwards. Think about heading into the financial crisis, the

610
00:31:47,360 --> 00:31:49,680
Speaker 2: hedge funds should have crushed the S and P five

611
00:31:49,760 --> 00:31:53,160
Speaker 2: hundred and did for a couple of years, which leads

612
00:31:53,200 --> 00:31:55,800
Speaker 2: me to this question, at what point were you feeling

613
00:31:55,800 --> 00:31:59,080
Speaker 2: a little cocky, Hey, I'm gonna eat warm buffet at

614
00:31:59,120 --> 00:32:01,720
Speaker 2: this like two years, three years in And at what

615
00:32:01,920 --> 00:32:05,600
Speaker 2: point did you get that sinking feeling his stomach. Son

616
00:32:05,680 --> 00:32:07,600
Speaker 2: of a bitch, The old man's gonna kick my button,

617
00:32:07,640 --> 00:32:08,120
Speaker 2: This isn't he?

618
00:32:08,440 --> 00:32:13,560
Speaker 1: So fourteen months in fourteen months deep into nine where

619
00:32:13,640 --> 00:32:16,240
Speaker 1: everything hit the fan January February of oh nine, markets

620
00:32:16,280 --> 00:32:18,560
Speaker 1: down another twenty percent. So fourteen months in the hedgehuns

621
00:32:18,560 --> 00:32:19,880
Speaker 1: were up by fifty percent.

622
00:32:20,040 --> 00:32:20,920
Speaker 2: Oh my goodness.

623
00:32:21,000 --> 00:32:24,360
Speaker 1: And if you would look to historically at hedgephung returns

624
00:32:24,440 --> 00:32:26,800
Speaker 1: versus the market, there was only a difference of one

625
00:32:26,880 --> 00:32:29,160
Speaker 1: or two or three percent. Right, this is just giant.

626
00:32:30,040 --> 00:32:34,760
Speaker 1: In Warren's two thousand and eight annual letter I think

627
00:32:34,760 --> 00:32:36,280
Speaker 1: it was two thousand and eight, he.

628
00:32:36,280 --> 00:32:38,800
Speaker 2: Made a statement, meaning the one that came out in

629
00:32:38,960 --> 00:32:40,840
Speaker 2: early nine, about the previous year.

630
00:32:40,880 --> 00:32:44,480
Speaker 1: Correct. He made a statement in that letter, really referring

631
00:32:44,520 --> 00:32:47,680
Speaker 1: to Berkshire having underperformed for the first period of time,

632
00:32:47,960 --> 00:32:50,479
Speaker 1: that even in periods as long as ten years, your

633
00:32:50,520 --> 00:32:52,680
Speaker 1: results can be heavily influenced by the starting point or

634
00:32:52,720 --> 00:32:53,240
Speaker 1: the ending point.

635
00:32:53,360 --> 00:32:53,560
Speaker 2: Right.

636
00:32:53,800 --> 00:32:56,360
Speaker 1: And I put that in a presentation I had as

637
00:32:56,840 --> 00:32:59,920
Speaker 1: he had just given his reason for losing the bet.

638
00:33:00,760 --> 00:33:04,000
Speaker 2: That the irony is he was hedging the bet. Perhaps

639
00:33:04,000 --> 00:33:05,120
Speaker 2: that stay perhaps right?

640
00:33:05,320 --> 00:33:10,520
Speaker 1: So, But even then you know it took five, I

641
00:33:10,560 --> 00:33:13,240
Speaker 1: don't remember, five or six years for that market to

642
00:33:13,280 --> 00:33:13,800
Speaker 1: catch up.

643
00:33:13,960 --> 00:33:18,680
Speaker 2: Wow, one, Well, fifty is a giant head start. Here's

644
00:33:18,680 --> 00:33:20,960
Speaker 2: a fifty percent head start. You got seven years go.

645
00:33:21,200 --> 00:33:23,920
Speaker 1: Yeah, Warren used to. He did announce it every year,

646
00:33:24,160 --> 00:33:25,480
Speaker 1: and what he would do is he would put the

647
00:33:25,520 --> 00:33:27,960
Speaker 1: results up right before lunch and say, as you can see,

648
00:33:28,000 --> 00:33:31,920
Speaker 1: I'm losing, let's go to lunch right, wouldn't say anything else.

649
00:33:32,280 --> 00:33:36,720
Speaker 1: Then the first year the market had tumunably beaten headghrounds,

650
00:33:36,720 --> 00:33:38,080
Speaker 1: there was like two pages about it in the.

651
00:33:38,120 --> 00:33:42,800
Speaker 2: Annual Letterious, but that's that's so funny. I had no idea.

652
00:33:43,200 --> 00:33:46,080
Speaker 2: I followed the bet from a distance, but I had

653
00:33:46,120 --> 00:33:48,080
Speaker 2: no idea he was doing that at the annual meetings.

654
00:33:48,120 --> 00:33:48,640
Speaker 2: That's brilliant.

655
00:33:48,640 --> 00:33:50,440
Speaker 1: The other thing he did that was sort of brilliant

656
00:33:50,520 --> 00:33:54,000
Speaker 1: was he wrote like two or three pages nine years in.

657
00:33:54,120 --> 00:33:55,440
Speaker 1: So the bet wasn't over.

658
00:33:55,400 --> 00:33:57,600
Speaker 2: But it was, for all intents and purposes done.

659
00:33:57,680 --> 00:34:01,120
Speaker 1: It was with one interesting exception. Yeah, so the name

660
00:34:01,160 --> 00:34:03,800
Speaker 1: of the five fund of funds we picked has never

661
00:34:03,840 --> 00:34:06,160
Speaker 1: been won't be disclosed. It doesn't matter did you pick

662
00:34:06,240 --> 00:34:08,240
Speaker 1: five funds or a fund of funds?

663
00:34:08,239 --> 00:34:11,360
Speaker 2: So really like twenty funds, twenty five funds, a tall.

664
00:34:11,360 --> 00:34:15,040
Speaker 1: Many more than that. Right, one of those five was

665
00:34:15,080 --> 00:34:18,200
Speaker 1: still outperforming the S and P five hundred through eight years.

666
00:34:18,600 --> 00:34:20,719
Speaker 1: At the end of the ninth year was the very

667
00:34:20,760 --> 00:34:23,600
Speaker 1: first year that the market had been outperforming all five.

668
00:34:23,800 --> 00:34:25,440
Speaker 1: But there was still one year left where that one

669
00:34:25,440 --> 00:34:28,800
Speaker 1: could have caught up. My premise is that Warren caught

670
00:34:28,840 --> 00:34:31,560
Speaker 1: that one period of time to deliver this whole message

671
00:34:31,560 --> 00:34:34,239
Speaker 1: about see the market even outperformed every single one of

672
00:34:34,239 --> 00:34:35,279
Speaker 1: these five fund funds.

673
00:34:35,320 --> 00:34:38,279
Speaker 2: So this raises an obvious question, and let me throw

674
00:34:38,320 --> 00:34:42,400
Speaker 2: out a doctoral thesis for anybody who who is looking

675
00:34:42,440 --> 00:34:46,120
Speaker 2: for one. What would happen if you, with the benefit

676
00:34:46,120 --> 00:34:49,120
Speaker 2: of hindsight, picked a different time period and a different

677
00:34:49,160 --> 00:34:52,760
Speaker 2: group of funds. You know, is there an era where

678
00:34:53,760 --> 00:34:54,920
Speaker 2: you would have won the bet?

679
00:34:55,080 --> 00:34:58,799
Speaker 1: So every era that you had data, which started in

680
00:34:58,840 --> 00:35:03,120
Speaker 1: the early nineties until that ten year period, hedge fronts

681
00:35:03,120 --> 00:35:05,400
Speaker 1: it out perform the market over ten years. I was

682
00:35:05,440 --> 00:35:07,920
Speaker 1: happy to do it in that ten year period solely

683
00:35:07,960 --> 00:35:10,000
Speaker 1: because of my view of the market.

684
00:35:10,280 --> 00:35:13,000
Speaker 2: Plus it was the only ten year period you had

685
00:35:13,080 --> 00:35:15,600
Speaker 2: at that moment in time. Right, We're going to make

686
00:35:15,600 --> 00:35:17,919
Speaker 2: a bet saying let's start this ten years from now.

687
00:35:18,000 --> 00:35:19,799
Speaker 1: That's right. But I didn't have to call him on it,

688
00:35:19,880 --> 00:35:20,440
Speaker 1: right you just.

689
00:35:20,840 --> 00:35:24,080
Speaker 2: So that will know you you had to call him

690
00:35:24,080 --> 00:35:26,959
Speaker 2: on it was. I have to tell you, I think

691
00:35:27,040 --> 00:35:30,000
Speaker 2: the whole idea is brilliant, not just of him tossing

692
00:35:30,000 --> 00:35:33,040
Speaker 2: it out there, but you saying, what the hell, let's

693
00:35:33,040 --> 00:35:37,640
Speaker 2: take warm Buffett up on this bed. At the very least.

694
00:35:38,000 --> 00:35:39,600
Speaker 2: It's going to be a fascinating decade.

695
00:35:39,920 --> 00:35:42,640
Speaker 1: And the best part about it is that we used

696
00:35:42,640 --> 00:35:44,040
Speaker 1: to go out and have dinner with them every year.

697
00:35:44,239 --> 00:35:46,600
Speaker 2: Come on, so that's worth a million dollars.

698
00:35:46,640 --> 00:35:48,200
Speaker 1: Yeah, I would go with my partners and I we

699
00:35:48,280 --> 00:35:50,160
Speaker 1: might bring one of our managers or close three in

700
00:35:50,200 --> 00:35:50,600
Speaker 1: a quarter.

701
00:35:50,640 --> 00:35:52,680
Speaker 2: That's worth three and a quarter. Oh my, talk about

702
00:35:52,680 --> 00:35:53,200
Speaker 2: a bargain.

703
00:35:53,680 --> 00:35:56,360
Speaker 1: And so all kinds of things came from that. So,

704
00:35:56,440 --> 00:35:59,279
Speaker 1: for example, one of the people I brought out this

705
00:35:59,320 --> 00:36:02,560
Speaker 1: guy named Steve. He used to be the strategist Morgan Stanley.

706
00:36:02,960 --> 00:36:07,080
Speaker 1: He was best friends professionally with Jack Bogle. I bring

707
00:36:07,120 --> 00:36:10,120
Speaker 1: out Steve, Steve's sister, Warren. Would you ever want to

708
00:36:10,160 --> 00:36:12,719
Speaker 1: have Jack at your annual meeting? And Warren lit up,

709
00:36:13,200 --> 00:36:16,600
Speaker 1: He's one of my idols. And that led to Jack

710
00:36:16,719 --> 00:36:20,239
Speaker 1: being there when Warren announced that Bet was the first

711
00:36:20,239 --> 00:36:21,480
Speaker 1: time he had ever been at the annual meeting. It

712
00:36:21,520 --> 00:36:23,319
Speaker 1: was a year or two before he passed away, and

713
00:36:23,360 --> 00:36:25,520
Speaker 1: Steve brought him there. All came from having dinner with

714
00:36:25,600 --> 00:36:26,680
Speaker 1: Warren that that one night.

715
00:36:26,719 --> 00:36:28,959
Speaker 2: When did he pass by? I think it was twenty fifteen, right,

716
00:36:29,160 --> 00:36:33,360
Speaker 2: so he announced he So when did Warren? Was that

717
00:36:33,440 --> 00:36:36,000
Speaker 2: an eight or ninety at him at or was it

718
00:36:36,080 --> 00:36:36,520
Speaker 2: much later?

719
00:36:36,600 --> 00:36:38,359
Speaker 1: No, it was much later. Yeah, that's much later.

720
00:36:38,520 --> 00:36:39,800
Speaker 2: Oh so, yeah, it had to be after.

721
00:36:40,000 --> 00:36:42,040
Speaker 1: Was like right around his ninetieth birthday, I think.

722
00:36:42,200 --> 00:36:45,200
Speaker 2: Right, And he was still an amazing voice, a little

723
00:36:45,239 --> 00:36:48,840
Speaker 2: launched over, but powerful and full wits about him. We

724
00:36:48,880 --> 00:36:51,760
Speaker 2: should all we should all be that shark at his age.

725
00:36:52,040 --> 00:36:56,040
Speaker 2: So dumb question, but I got to ask. So, of

726
00:36:56,080 --> 00:37:00,000
Speaker 2: course the firm three hundred and twenty thousand dollars well

727
00:37:00,120 --> 00:37:04,120
Speaker 2: worth every penny? Or was this like to me? It

728
00:37:04,200 --> 00:37:06,360
Speaker 2: sounds like the whole thing was spectacular.

729
00:37:06,600 --> 00:37:09,000
Speaker 1: Yeah. I wouldn't measure it in terms of economic returns

730
00:37:09,000 --> 00:37:09,480
Speaker 1: like I don't.

731
00:37:09,400 --> 00:37:10,879
Speaker 2: Know, No, I mean just across the board.

732
00:37:11,120 --> 00:37:14,960
Speaker 1: Yeah, as an experience and relationships, it was just extraordinary.

733
00:37:15,000 --> 00:37:15,879
Speaker 1: And Warren is.

734
00:37:17,440 --> 00:37:20,160
Speaker 2: One of a coun He's just the real deal. Yeah.

735
00:37:20,280 --> 00:37:22,759
Speaker 1: I mean, he didn't need to have dinner with us ever,

736
00:37:24,560 --> 00:37:27,640
Speaker 1: and it was just so fun. And the stories that

737
00:37:27,719 --> 00:37:30,520
Speaker 1: he tells, we hear lots of them, but to hear

738
00:37:30,600 --> 00:37:34,080
Speaker 1: different ones over and over, investment stories, non investment stories.

739
00:37:34,120 --> 00:37:36,240
Speaker 1: He really is so extraordinary.

740
00:37:36,320 --> 00:37:39,240
Speaker 2: So here's a crazy question that again I feel compelled

741
00:37:39,280 --> 00:37:43,279
Speaker 2: to ask. Is it possible that the guy known as

742
00:37:43,320 --> 00:37:46,359
Speaker 2: the world's greatest investor? Whether that title is accurate or not,

743
00:37:46,680 --> 00:37:50,240
Speaker 2: it doesn't matter. Is it possible that he's still underestimated?

744
00:37:50,440 --> 00:37:54,640
Speaker 2: Because every couple of years people start to come out

745
00:37:54,640 --> 00:37:57,480
Speaker 2: and say, ah, he's lost his touch. They are not outperforming.

746
00:37:57,560 --> 00:38:01,760
Speaker 2: But and then he surprises people every decade. This seems

747
00:38:01,800 --> 00:38:02,240
Speaker 2: to happen.

748
00:38:02,600 --> 00:38:04,799
Speaker 1: I mean, for him to be underestimated, you'd have to

749
00:38:04,800 --> 00:38:08,640
Speaker 1: have an assessment of him that is a certain level, right,

750
00:38:08,840 --> 00:38:11,680
Speaker 1: I think people see him in such high esteem.

751
00:38:11,920 --> 00:38:15,560
Speaker 2: Some people do. But what I've heard from some folks,

752
00:38:16,040 --> 00:38:19,200
Speaker 2: some younger quants, well, when you look at the sequence

753
00:38:19,239 --> 00:38:21,600
Speaker 2: of returns, Buffett did so well in the late sixties

754
00:38:21,600 --> 00:38:24,839
Speaker 2: and seventies, that's the fourth source of out performance. And

755
00:38:25,000 --> 00:38:27,200
Speaker 2: what have you done for me lately? And I think

756
00:38:27,280 --> 00:38:29,200
Speaker 2: they're kind of missing the bigger picture.

757
00:38:29,320 --> 00:38:31,279
Speaker 1: I agree with you, and you could say the same thing.

758
00:38:31,280 --> 00:38:33,680
Speaker 1: When we were talking about the Yale model with David Swinston, right,

759
00:38:33,719 --> 00:38:35,840
Speaker 1: Cliff asked us wrote a piece that said, all Warren

760
00:38:35,880 --> 00:38:37,839
Speaker 1: did was buy these quality stocks, and if you had

761
00:38:37,840 --> 00:38:39,960
Speaker 1: replicated that strategy, you could replicate the results, which is

762
00:38:39,960 --> 00:38:43,520
Speaker 1: absolutely true, except fifty years ago more you had to

763
00:38:43,640 --> 00:38:45,240
Speaker 1: know to buy the quality.

764
00:38:44,840 --> 00:38:49,200
Speaker 3: Stock almost sixty years ago. Right, that's crazy. No, I mean,

765
00:38:49,280 --> 00:38:55,840
Speaker 3: I think that he is that extraordinary and when you know,

766
00:38:56,040 --> 00:38:58,120
Speaker 3: so fortunate to get to spend a bunch of time

767
00:38:58,160 --> 00:39:01,240
Speaker 3: with him, he uses wizdo him in everything he says.

768
00:39:01,360 --> 00:39:04,000
Speaker 3: David Swinson was exactly the same way. And I've only

769
00:39:04,040 --> 00:39:06,200
Speaker 3: known maybe a handful of people in this in my life.

770
00:39:06,360 --> 00:39:08,240
Speaker 2: Charlie Munger, I assume is another.

771
00:39:08,000 --> 00:39:10,280
Speaker 1: One, Charlie. I don't know, Charlie, but of the people

772
00:39:10,320 --> 00:39:14,359
Speaker 1: that I've known, every word that comes out of Warren's mouth,

773
00:39:14,440 --> 00:39:16,800
Speaker 1: no matter what subject I talked to him about a

774
00:39:17,000 --> 00:39:20,279
Speaker 1: Rod signing with the Yankees, everything that comes out of

775
00:39:20,320 --> 00:39:23,200
Speaker 1: his mouth is just oozing wisdom.

776
00:39:23,360 --> 00:39:27,160
Speaker 2: That's interesting. You know, there's this wonderful chart on compounding

777
00:39:27,880 --> 00:39:31,000
Speaker 2: that shows you know, the average person, you're start accumulating

778
00:39:31,000 --> 00:39:33,719
Speaker 2: a little money in your thirties, your investment window is

779
00:39:33,800 --> 00:39:37,400
Speaker 2: like forty to sixty eight, So you got, if you're lucky,

780
00:39:37,560 --> 00:39:41,160
Speaker 2: twenty five thirty years. Buffett has nearly sixty years. And

781
00:39:41,239 --> 00:39:44,600
Speaker 2: when you see the hockey stick of the compounding effect,

782
00:39:45,200 --> 00:39:48,640
Speaker 2: it's the last twenty five years that most people don't

783
00:39:48,719 --> 00:39:51,600
Speaker 2: leave their money working for them. Where he's gone from

784
00:39:51,640 --> 00:39:54,600
Speaker 2: a billionaire to a deck of billionaire to a multi

785
00:39:54,600 --> 00:39:59,000
Speaker 2: decad billionaire. That people just don't realize the impact of compounding.

786
00:39:59,280 --> 00:40:03,600
Speaker 2: And it's not us cash, it's those insight and wisdom

787
00:40:03,719 --> 00:40:04,880
Speaker 2: seems to just multiply.

788
00:40:05,160 --> 00:40:08,040
Speaker 1: Yeah, our friend Morgan Housel has written about that in

789
00:40:08,120 --> 00:40:12,399
Speaker 1: just a beautiful way telling that story, and it's it's time, right,

790
00:40:12,440 --> 00:40:17,000
Speaker 1: It's both brilliant investing and time.

791
00:40:17,640 --> 00:40:21,920
Speaker 2: So let's bring this back to the day job, which

792
00:40:21,960 --> 00:40:27,960
Speaker 2: is allocators. What's the takeaway from the bet for allocators?

793
00:40:28,160 --> 00:40:29,719
Speaker 1: I don't know if there are many paks.

794
00:40:30,040 --> 00:40:33,240
Speaker 2: I have my own takeaways, Rich so you're here, which

795
00:40:33,360 --> 00:40:35,279
Speaker 2: I'll tell you mine you tell me sure.

796
00:40:35,840 --> 00:40:40,080
Speaker 1: One of them is that time periods really matter for sure, not.

797
00:40:40,560 --> 00:40:44,920
Speaker 2: Just the specific length of time, but that specific chunk of.

798
00:40:44,880 --> 00:40:48,839
Speaker 1: It, absolutely right. The other is it was a fascinating

799
00:40:48,920 --> 00:40:54,920
Speaker 1: exercise to see how the media works. So I'll give

800
00:40:54,920 --> 00:40:58,319
Speaker 1: you two little stories of that. Carol Loomis wrote a

801
00:40:58,400 --> 00:41:00,400
Speaker 1: piece about the bet when we launched.

802
00:41:00,440 --> 00:41:05,320
Speaker 2: It was she eventually writes the biography of Buffett correct

803
00:41:05,400 --> 00:41:06,920
Speaker 2: Dancing to work or something.

804
00:41:06,719 --> 00:41:08,920
Speaker 1: Correct, and she wrote about the bet in that as well.

805
00:41:09,480 --> 00:41:11,719
Speaker 1: Her piece was two pages. I had said to her,

806
00:41:12,000 --> 00:41:13,840
Speaker 1: how are you you're gonna write an article about this

807
00:41:13,880 --> 00:41:15,720
Speaker 1: little bet? And it was just so well done.

808
00:41:15,760 --> 00:41:18,239
Speaker 2: Oh it wasn't a little bet, but go on.

809
00:41:18,320 --> 00:41:20,759
Speaker 1: At the time it felt that way. Really sure, you.

810
00:41:20,880 --> 00:41:23,480
Speaker 2: Make it a million dollar bet with Warren Buffett. How

811
00:41:23,520 --> 00:41:25,600
Speaker 2: on God's green Earth is that a little bet?

812
00:41:25,800 --> 00:41:28,000
Speaker 1: Well, it might not be a little bet, but I

813
00:41:28,040 --> 00:41:30,400
Speaker 1: didn't think there was a story of it other than

814
00:41:30,560 --> 00:41:31,200
Speaker 1: here's the bet.

815
00:41:31,800 --> 00:41:35,000
Speaker 2: Again. My hindsight bias is like this is this is

816
00:41:35,200 --> 00:41:39,040
Speaker 2: like the defining moment in your career that colors everything

817
00:41:39,080 --> 00:41:41,239
Speaker 2: else you do the rest of your life. You're the

818
00:41:41,280 --> 00:41:43,280
Speaker 2: guy that made the bet with Warren Buffett.

819
00:41:43,440 --> 00:41:45,319
Speaker 1: I get that that might go on my tombstone, but

820
00:41:45,400 --> 00:41:47,800
Speaker 1: it certainly didn't feel like it was a defining moment.

821
00:41:48,160 --> 00:41:51,120
Speaker 2: There's no false humility here, because I could see in

822
00:41:51,160 --> 00:41:54,960
Speaker 2: your face you're not exaggerating. At the time you felt, Oh,

823
00:41:55,000 --> 00:41:57,120
Speaker 2: this just a fun little side thing.

824
00:41:57,760 --> 00:41:59,839
Speaker 1: Yeah, I got a chance to do this thing with Warren.

825
00:41:59,840 --> 00:42:01,600
Speaker 1: How cool is that it?

826
00:42:01,880 --> 00:42:05,760
Speaker 2: Okay, I get I guess, I guess history has blown

827
00:42:05,840 --> 00:42:08,239
Speaker 2: it up into something more than it felt like at

828
00:42:08,239 --> 00:42:08,880
Speaker 2: the time.

829
00:42:09,000 --> 00:42:12,239
Speaker 1: Not to me but to others for sure. Okay, So

830
00:42:12,320 --> 00:42:15,840
Speaker 1: Carol writes this piece and it's brilliantly done, as everything

831
00:42:15,880 --> 00:42:19,600
Speaker 1: she did was, and then massive amounts of media attached

832
00:42:19,600 --> 00:42:19,839
Speaker 1: to it.

833
00:42:19,920 --> 00:42:23,440
Speaker 2: Right, I I vividly remember that what was she forbes?

834
00:42:23,480 --> 00:42:24,080
Speaker 2: A fortune?

835
00:42:24,400 --> 00:42:24,840
Speaker 1: Fortune?

836
00:42:24,880 --> 00:42:25,320
Speaker 2: Fortune?

837
00:42:25,719 --> 00:42:28,480
Speaker 1: So keep in mind the only definitive information about the

838
00:42:28,520 --> 00:42:31,880
Speaker 1: bet was in Carol's two page piece, and then every

839
00:42:31,920 --> 00:42:34,160
Speaker 1: other piece that got riden had factual inaccuracy.

840
00:42:34,239 --> 00:42:38,520
Speaker 2: Right, it's multiplicity, every copy is that's so that was

841
00:42:38,600 --> 00:42:39,560
Speaker 2: that was eye opening.

842
00:42:39,600 --> 00:42:42,720
Speaker 1: The other was there are a whole bunch of different

843
00:42:42,760 --> 00:42:45,680
Speaker 1: ways you could interpret a stream of returns, so you

844
00:42:45,680 --> 00:42:48,520
Speaker 1: can say about the bet about any investment manager. And

845
00:42:49,800 --> 00:42:53,279
Speaker 1: I dissected what had happened in a way that I

846
00:42:53,320 --> 00:42:56,040
Speaker 1: thought had a lot of merit, things like short rebates,

847
00:42:56,160 --> 00:42:58,800
Speaker 1: things like choosing the s and p versus a global

848
00:42:58,840 --> 00:43:01,680
Speaker 1: index all the kinds of things, and I put that.

849
00:43:01,719 --> 00:43:05,240
Speaker 1: Actually it was in Bloomberg. So here's my first lesson

850
00:43:05,480 --> 00:43:07,880
Speaker 1: was I didn't know at the time that when you

851
00:43:07,920 --> 00:43:10,600
Speaker 1: write a piece, you don't control the title of the piece.

852
00:43:11,120 --> 00:43:15,360
Speaker 2: FYI, editors write the title, the writer writes the body

853
00:43:15,400 --> 00:43:16,000
Speaker 2: of the work.

854
00:43:16,040 --> 00:43:19,960
Speaker 1: Correct. So I had written a piece something about nine

855
00:43:20,040 --> 00:43:22,680
Speaker 1: years in whatever the title came, Why I lost my

856
00:43:22,760 --> 00:43:24,320
Speaker 1: bet with Warren Buffett.

857
00:43:24,239 --> 00:43:27,399
Speaker 2: Well, that's clickbait that clickworthy people are.

858
00:43:27,280 --> 00:43:29,600
Speaker 1: Going to use. The bet wasn't over yet, so it

859
00:43:29,920 --> 00:43:33,640
Speaker 1: became an interesting, interesting thing, and it also completely changed

860
00:43:33,640 --> 00:43:36,120
Speaker 1: the tone of what I had written, sure, because it

861
00:43:36,160 --> 00:43:38,400
Speaker 1: made it look like a series of excuses as opposed

862
00:43:38,440 --> 00:43:39,239
Speaker 1: to an analysis.

863
00:43:39,400 --> 00:43:41,759
Speaker 2: There are worse people to lose a bet to than

864
00:43:41,800 --> 00:43:45,960
Speaker 2: Warren Buffett. What's been the takeaway? What's been the impact

865
00:43:46,040 --> 00:43:50,640
Speaker 2: on you from that whole delightful sounding experience.

866
00:43:50,760 --> 00:43:53,719
Speaker 1: Yeah, I haven't really thought about it that much. I mean,

867
00:43:53,920 --> 00:43:57,200
Speaker 1: for me, the biggest takeaway is the value of relationships

868
00:43:58,040 --> 00:44:02,399
Speaker 1: and how what a wonderful, full fortunate experience I had

869
00:44:02,480 --> 00:44:04,800
Speaker 1: to just be able to spend the time with Warren

870
00:44:04,840 --> 00:44:07,439
Speaker 1: that I did, and to get to know what Todd

871
00:44:07,480 --> 00:44:10,480
Speaker 1: Combs I had known, and Ted Wessler and Tracy Brick

872
00:44:10,520 --> 00:44:13,440
Speaker 1: cool when she was there, all coming to these dinners

873
00:44:13,480 --> 00:44:15,920
Speaker 1: and just having fun talking about investing in markets, and

874
00:44:15,960 --> 00:44:19,520
Speaker 1: so that for me, that was priceless. We say, what

875
00:44:19,640 --> 00:44:21,400
Speaker 1: was the price of the bet? Well, it was priceless

876
00:44:21,400 --> 00:44:24,080
Speaker 1: town to have that time and had a couple of

877
00:44:24,120 --> 00:44:26,359
Speaker 1: things that Warren and I did together when he was

878
00:44:26,560 --> 00:44:29,040
Speaker 1: when he was first starting the Giving Pledge, at one

879
00:44:29,080 --> 00:44:31,319
Speaker 1: point in time, no one was signing up, and he

880
00:44:31,400 --> 00:44:33,040
Speaker 1: called and said, hey, you know some of these hedge

881
00:44:33,040 --> 00:44:34,839
Speaker 1: fun guys, is there anyway we can.

882
00:44:34,800 --> 00:44:36,560
Speaker 2: Round up some round the up. Let's get a few

883
00:44:36,600 --> 00:44:38,000
Speaker 2: billion dollars in trying to do that.

884
00:44:38,080 --> 00:44:39,520
Speaker 1: And there were one or two that signed up from

885
00:44:39,560 --> 00:44:39,839
Speaker 1: that act.

886
00:44:39,960 --> 00:44:41,680
Speaker 2: Can I Can I tell you something? You make a

887
00:44:41,680 --> 00:44:44,239
Speaker 2: phone call to someone and say, hey, Warren Buffett asked

888
00:44:44,239 --> 00:44:46,480
Speaker 2: me to call you. He signed up for the Giving Pledge.

889
00:44:46,640 --> 00:44:49,120
Speaker 2: You want to make a commitment to donating money. By

890
00:44:49,120 --> 00:44:52,080
Speaker 2: the way, Leon Cooperman tells a story about going to

891
00:44:52,160 --> 00:44:55,560
Speaker 2: dinner when he signs up for the Giving Pledge, and

892
00:44:55,600 --> 00:44:59,000
Speaker 2: it's Buffett, and it's Bill Gates, and it's on and on,

893
00:44:59,360 --> 00:45:01,680
Speaker 2: and he doesn't at the end of this dinner with

894
00:45:01,719 --> 00:45:05,480
Speaker 2: twelve people, the newest guy picks up the check and

895
00:45:06,360 --> 00:45:09,000
Speaker 2: he tells the story. He's like, I'm looking around. Everybody

896
00:45:09,080 --> 00:45:11,960
Speaker 2: is five, ten, twenty times wealthier than me. I get

897
00:45:12,000 --> 00:45:14,920
Speaker 2: stuck with the bill and those guys order expensive wine

898
00:45:15,239 --> 00:45:18,960
Speaker 2: and he tells the story. It's hilarious. Did you manage

899
00:45:18,960 --> 00:45:20,960
Speaker 2: to intro warrant to a bunch of hedge fun guys?

900
00:45:21,040 --> 00:45:24,000
Speaker 1: Yeah, there were two that signed on from that, just wonderful.

901
00:45:24,320 --> 00:45:27,399
Speaker 2: I would think you drop Warren's name. Doors just open

902
00:45:27,520 --> 00:45:28,560
Speaker 2: up on stuff like that.

903
00:45:29,400 --> 00:45:31,600
Speaker 1: You know, if you're sitting with the billion dollars, I'm

904
00:45:31,600 --> 00:45:33,560
Speaker 1: not sure you're giving away half of it just because

905
00:45:33,600 --> 00:45:34,160
Speaker 1: of warrantony.

906
00:45:34,239 --> 00:45:36,360
Speaker 2: But some of these guys are given are sitting with

907
00:45:36,400 --> 00:45:38,680
Speaker 2: a lot more than a billion dollars, and why not?

908
00:45:38,760 --> 00:45:42,000
Speaker 2: Who cares unless they have their own foundation. I give

909
00:45:42,000 --> 00:45:44,960
Speaker 2: you a list of thirty billionaires. They all set up

910
00:45:44,960 --> 00:45:48,280
Speaker 2: their own foundations. It's part of their own tax planning.

911
00:45:48,520 --> 00:45:52,319
Speaker 2: I like Buffett's idea. I don't need to duplicate all

912
00:45:52,360 --> 00:45:56,239
Speaker 2: that effort and administrative headache. Let Bill worry about it here, Bill,

913
00:45:56,239 --> 00:45:59,759
Speaker 2: I'm in for half, so that the two of the

914
00:45:59,760 --> 00:46:02,520
Speaker 2: well these guys in the world'll turn the Gates Foundation,

915
00:46:02,760 --> 00:46:05,920
Speaker 2: which really should be called the Gates Buffet Foundation, into

916
00:46:05,960 --> 00:46:09,760
Speaker 2: this giant what is it, one hundred plus billion dollars

917
00:46:09,760 --> 00:46:13,120
Speaker 2: now maybe more than that. Just tremendous. So all in all,

918
00:46:13,520 --> 00:46:15,000
Speaker 2: good experience with Warm Buffett.

919
00:46:15,000 --> 00:46:18,160
Speaker 1: Everybody wins, especially the charity. I think it was Girls

920
00:46:18,239 --> 00:46:21,480
Speaker 1: Inc of Omaha. Who there's a side thing which we'll

921
00:46:21,600 --> 00:46:23,600
Speaker 1: talk about another time, but it ended up being north

922
00:46:23,680 --> 00:46:25,640
Speaker 1: of two million dollars that went.

923
00:46:25,600 --> 00:46:28,319
Speaker 2: And what's their budget? Like fraction though, right, it just

924
00:46:28,440 --> 00:46:32,920
Speaker 2: overwhelmed them. I'm sure that's great. So let's talk about

925
00:46:32,920 --> 00:46:36,400
Speaker 2: some of your philosophy and your writings. One of my

926
00:46:36,480 --> 00:46:41,200
Speaker 2: favorite things you wrote in you have a podcast. We'll

927
00:46:41,200 --> 00:46:43,359
Speaker 2: talk about that in a little bit. You ask all

928
00:46:43,400 --> 00:46:47,520
Speaker 2: your guests one question about a pet peeve. I love

929
00:46:47,719 --> 00:46:50,319
Speaker 2: your peeve I don't know, which is one of my

930
00:46:50,440 --> 00:46:54,439
Speaker 2: favorite peeves. Tell us a little bit about investors who

931
00:46:54,480 --> 00:46:59,720
Speaker 2: express absolutes in a world of probabilities. Tell us about

932
00:47:00,920 --> 00:47:01,440
Speaker 2: I don't know.

933
00:47:01,640 --> 00:47:05,280
Speaker 1: Yeah, Well, I've always viewed investing, as I think everyone

934
00:47:05,320 --> 00:47:09,120
Speaker 1: properly should is as a probabilistic game. And one of

935
00:47:09,200 --> 00:47:12,800
Speaker 1: the things that happens when you're a money manager telling

936
00:47:12,880 --> 00:47:16,520
Speaker 1: stories to raise capital is you need to show conviction.

937
00:47:17,680 --> 00:47:20,799
Speaker 1: The best ones can blend that conviction with humility. But

938
00:47:20,920 --> 00:47:24,680
Speaker 1: sometimes you find people that say things it's not just

939
00:47:24,760 --> 00:47:28,399
Speaker 1: investing in life too, where they're just sure what will

940
00:47:28,400 --> 00:47:31,160
Speaker 1: happen the outcome of this, that or the other thing,

941
00:47:31,160 --> 00:47:34,840
Speaker 1: and it just doesn't work that way. And so particularly now,

942
00:47:35,640 --> 00:47:38,719
Speaker 1: there are so many things that are either common wisdom

943
00:47:39,320 --> 00:47:43,040
Speaker 1: or that the consensus believes that have nuance to them

944
00:47:43,200 --> 00:47:46,120
Speaker 1: right where I look at it and say I don't

945
00:47:46,160 --> 00:47:48,680
Speaker 1: know what the answer is. Now you could put probability

946
00:47:48,680 --> 00:47:51,680
Speaker 1: weights to it. But I walk through in this piece

947
00:47:51,840 --> 00:47:54,520
Speaker 1: a couple of different things where I just said, look,

948
00:47:54,840 --> 00:47:55,319
Speaker 1: I don't know.

949
00:47:55,880 --> 00:47:57,680
Speaker 2: I love that. By the way, if you're ever on

950
00:47:57,760 --> 00:48:01,040
Speaker 2: TV and want to make the hosts headach blowed, have

951
00:48:01,160 --> 00:48:03,439
Speaker 2: them ask you a question. Just say I don't know. Yeah,

952
00:48:03,680 --> 00:48:05,279
Speaker 2: it doesn't work very They don't know what to do.

953
00:48:05,320 --> 00:48:06,520
Speaker 2: They look at you like, what do you mean you

954
00:48:06,520 --> 00:48:06,799
Speaker 2: don't know?

955
00:48:06,880 --> 00:48:08,120
Speaker 1: It doesn't make for very good TV.

956
00:48:09,160 --> 00:48:12,239
Speaker 2: It makes for honest TV. But that's a whole other conversation.

957
00:48:12,640 --> 00:48:15,280
Speaker 2: Since we've been talking about David Swinson, let's talk about

958
00:48:15,800 --> 00:48:19,160
Speaker 2: don't be so short term. How big a problem is

959
00:48:19,200 --> 00:48:23,200
Speaker 2: short term ism in investing, be it institutional or individual.

960
00:48:23,320 --> 00:48:27,400
Speaker 1: Yeah, well, it's a huge problem, and it's an intractable

961
00:48:27,440 --> 00:48:30,840
Speaker 1: problem because of the way incentive systems work. In the

962
00:48:30,880 --> 00:48:35,080
Speaker 1: asset management industry, everyone across the food chain of capital

963
00:48:35,120 --> 00:48:38,520
Speaker 1: is reporting to somebody else, and through that reporting people

964
00:48:38,560 --> 00:48:42,560
Speaker 1: have to generate performance. And so what's happened over decades

965
00:48:43,320 --> 00:48:46,160
Speaker 1: is that the holding periods of every type of investment

966
00:48:46,200 --> 00:48:50,040
Speaker 1: have just gotten shorter and shorter. And the problem with

967
00:48:50,120 --> 00:48:53,080
Speaker 1: that is there's a cost to it. So there are

968
00:48:53,080 --> 00:48:57,239
Speaker 1: a lot of situations where investing with a shorter time

969
00:48:57,280 --> 00:48:59,880
Speaker 1: horizon costs long term returns.

970
00:49:01,040 --> 00:49:05,520
Speaker 2: Really interesting. There's another quote that I'm fascinated by. Limiting

971
00:49:05,640 --> 00:49:09,759
Speaker 2: an assessment of returns only to market conditions in the

972
00:49:09,840 --> 00:49:14,120
Speaker 2: moment fails to consider the wide range of possibilities of

973
00:49:14,160 --> 00:49:16,960
Speaker 2: what might happen in the future. So that's a very

974
00:49:17,000 --> 00:49:21,520
Speaker 2: loaded statement. Not only is it filled with concerns of

975
00:49:21,560 --> 00:49:25,560
Speaker 2: the recency effect, but you're also talking about probabilities of

976
00:49:25,640 --> 00:49:30,080
Speaker 2: all the range of possible outcomes that there is no

977
00:49:30,280 --> 00:49:32,480
Speaker 2: yes or no. It's this might happen, that might happen,

978
00:49:32,520 --> 00:49:35,239
Speaker 2: this might happen. Tell us a little bit about how

979
00:49:35,239 --> 00:49:38,560
Speaker 2: you came to that, and while being stuck in the

980
00:49:38,600 --> 00:49:42,000
Speaker 2: moment is so problematic for long term returns.

981
00:49:42,080 --> 00:49:45,279
Speaker 1: Well, if you look at what happened with SVB, a

982
00:49:45,320 --> 00:49:48,560
Speaker 1: mismanagement of the balance sheet. So you go back a

983
00:49:48,560 --> 00:49:51,840
Speaker 1: couple of years and you could say, well, what return

984
00:49:51,960 --> 00:49:57,279
Speaker 1: is available buying a treasury? And it turned out if

985
00:49:57,280 --> 00:50:00,759
Speaker 1: you looked at the market at that time, i'll call

986
00:50:00,800 --> 00:50:03,400
Speaker 1: it one percent five year treasure or ten year treasure.

987
00:50:03,680 --> 00:50:06,640
Speaker 1: And so you say, well, we need to invest. You know,

988
00:50:06,719 --> 00:50:08,960
Speaker 1: we are deposits cost less than that, we're going to

989
00:50:09,000 --> 00:50:11,240
Speaker 1: earn a spread, so we're going to invest at one percent.

990
00:50:11,920 --> 00:50:13,880
Speaker 1: The problem with that, of course, is that if you

991
00:50:13,960 --> 00:50:16,600
Speaker 1: said what return is available, let's say over the next

992
00:50:16,600 --> 00:50:18,719
Speaker 1: ten years, and it was one percent, it turns out

993
00:50:18,760 --> 00:50:21,120
Speaker 1: you were wrong, because the right thing to do was

994
00:50:21,160 --> 00:50:24,280
Speaker 1: to sit on cash and wait till rates moved to five.

995
00:50:24,080 --> 00:50:27,400
Speaker 2: Percent, Especially when the Fed said we're taking rates up

996
00:50:27,440 --> 00:50:31,879
Speaker 2: aggressively posts you know, late twenty one, early twenty two.

997
00:50:32,360 --> 00:50:35,040
Speaker 2: It wasn't that they didn't communicate that, correct.

998
00:50:35,880 --> 00:50:37,719
Speaker 1: So if you look at that over a longer period

999
00:50:37,760 --> 00:50:39,920
Speaker 1: of time and say, well, my opportunity said, isn't just

1000
00:50:40,000 --> 00:50:43,239
Speaker 1: what's available today. It's what's available today and might be

1001
00:50:43,280 --> 00:50:46,200
Speaker 1: available tomorrow. And I can forego a tiny bit of

1002
00:50:46,239 --> 00:50:49,040
Speaker 1: return in the near term to earn a much higher

1003
00:50:49,040 --> 00:50:52,520
Speaker 1: return at some unknowable time in the future. That could

1004
00:50:52,560 --> 00:50:55,840
Speaker 1: have saved SVB, It could have saved First Republic.

1005
00:50:55,920 --> 00:50:58,759
Speaker 2: So hold the duration risk aside with those two. But

1006
00:50:59,200 --> 00:51:02,839
Speaker 2: just for an investor in treasuries, I know you've done

1007
00:51:02,840 --> 00:51:05,759
Speaker 2: the math before. If you're getting if you're giving up

1008
00:51:05,800 --> 00:51:11,000
Speaker 2: that one percent, big fat yield in twenty nineteen, twenty

1009
00:51:11,080 --> 00:51:13,800
Speaker 2: twenty one, Let's say you give up three years of

1010
00:51:14,600 --> 00:51:17,439
Speaker 2: one percent and get zero, how does the math work

1011
00:51:17,480 --> 00:51:20,520
Speaker 2: over ten over the subsequent couple of years, how would

1012
00:51:20,520 --> 00:51:22,040
Speaker 2: you have done well, You've.

1013
00:51:21,920 --> 00:51:23,839
Speaker 1: Done a lot better. Right to even take a five

1014
00:51:23,920 --> 00:51:27,600
Speaker 1: year period, you go one one one one one or

1015
00:51:27,760 --> 00:51:28,920
Speaker 1: zero zero zero.

1016
00:51:28,960 --> 00:51:34,319
Speaker 2: Five five ahead, they get more way ahead. And so

1017
00:51:34,360 --> 00:51:37,000
Speaker 2: people tend to get stuck in the moment and not

1018
00:51:37,200 --> 00:51:42,200
Speaker 2: think so. My description for that is everybody is dealing

1019
00:51:42,200 --> 00:51:45,120
Speaker 2: with photographs when they should be dealing with a moving

1020
00:51:45,320 --> 00:51:48,760
Speaker 2: a movie or a film. It's hard to pull yourself

1021
00:51:48,800 --> 00:51:51,880
Speaker 2: out of the moment, which is a snapshot, and instead

1022
00:51:51,880 --> 00:51:54,960
Speaker 2: of think over the arc of time, that's a foible

1023
00:51:55,160 --> 00:52:00,000
Speaker 2: of just how human's brains operate, and it infects even

1024
00:52:00,120 --> 00:52:01,120
Speaker 2: professional investors.

1025
00:52:02,080 --> 00:52:08,680
Speaker 1: That's a great analogy. It's also compounded by competition. Oh really,

1026
00:52:08,840 --> 00:52:11,520
Speaker 1: So if you're a money manager and you're sitting on

1027
00:52:11,640 --> 00:52:14,960
Speaker 1: cash and earning zero, let's just simplify the example, and

1028
00:52:15,000 --> 00:52:17,799
Speaker 1: the guy across the street is earning one. For those

1029
00:52:17,800 --> 00:52:19,719
Speaker 1: three years, you're underperforming.

1030
00:52:19,840 --> 00:52:24,560
Speaker 2: Yeah, you're losing. That's where the idea of perpetual capital,

1031
00:52:25,040 --> 00:52:28,919
Speaker 2: which you talked about having a perpetual time horizon, sometimes

1032
00:52:29,000 --> 00:52:32,400
Speaker 2: is more theoretical than realistic because you may not have

1033
00:52:32,440 --> 00:52:36,719
Speaker 2: liabilities for ten twenty years and an ongoing perpetual endowment

1034
00:52:36,800 --> 00:52:40,800
Speaker 2: that never vests, but people still live in the month

1035
00:52:40,880 --> 00:52:45,200
Speaker 2: and the quarter, and who cares about one percent? Well,

1036
00:52:45,280 --> 00:52:47,200
Speaker 2: allocators are going to look at you when you're thinking

1037
00:52:47,200 --> 00:52:49,520
Speaker 2: to joint up for those three years.

1038
00:52:50,960 --> 00:52:53,840
Speaker 1: There are real challenges in the profession of money management.

1039
00:52:53,880 --> 00:52:56,240
Speaker 1: So just take that concept. There's a lot of interest

1040
00:52:56,280 --> 00:52:59,400
Speaker 1: in permanent capital vehicles, and it turns out the permanent

1041
00:52:59,400 --> 00:53:04,480
Speaker 1: capitol vehicle themselves are impermanent. You have closed end funds

1042
00:53:04,520 --> 00:53:07,360
Speaker 1: that trade a discounts that sometimes have shareholder pressure to

1043
00:53:07,400 --> 00:53:11,960
Speaker 1: open end. You have holding company structures that have management changes.

1044
00:53:12,239 --> 00:53:17,080
Speaker 1: And then in the allocator community, these perpetual pools of capital,

1045
00:53:17,160 --> 00:53:20,320
Speaker 1: generally speaking, are run by chief investment officers whose average

1046
00:53:20,360 --> 00:53:22,080
Speaker 1: tenure in the seat is only six years.

1047
00:53:23,120 --> 00:53:24,200
Speaker 2: So not so permanent.

1048
00:53:24,320 --> 00:53:25,720
Speaker 1: Not so permanent after all.

1049
00:53:26,000 --> 00:53:28,600
Speaker 2: I love this quote from a piece you wrote about

1050
00:53:28,719 --> 00:53:33,600
Speaker 2: risk in nineteen ninety eight. You asked fame value investor

1051
00:53:33,680 --> 00:53:39,080
Speaker 2: Michael Price what he learned from investing in Sunbeam Corporation,

1052
00:53:39,560 --> 00:53:43,560
Speaker 2: which was run by chainsaw Al Dunlop and was just

1053
00:53:43,880 --> 00:53:47,879
Speaker 2: rife with accounting fraud the whole thing ultimately collapses. He

1054
00:53:48,000 --> 00:53:53,120
Speaker 2: responds absolutely nothing. So for those of you who are

1055
00:53:53,239 --> 00:53:56,839
Speaker 2: listening on the air, he responds absolutely nothing, with an

1056
00:53:56,880 --> 00:54:00,760
Speaker 2: explot of in the middle, how could you learn nothing

1057
00:54:00,800 --> 00:54:02,440
Speaker 2: from that experience? Tell us about that.

1058
00:54:02,840 --> 00:54:07,400
Speaker 1: The challenge with that is that fraud is fraud. So

1059
00:54:07,560 --> 00:54:11,040
Speaker 1: you're underwriting risks when you invest, and one of those

1060
00:54:11,360 --> 00:54:15,000
Speaker 1: is all the analysis you do isn't real and the

1061
00:54:15,120 --> 00:54:17,759
Speaker 1: problem with it, and you could use it made off

1062
00:54:17,800 --> 00:54:21,719
Speaker 1: as an example, You could use FTX as a recent example,

1063
00:54:22,280 --> 00:54:24,920
Speaker 1: is that for every you know, one or two percent

1064
00:54:24,960 --> 00:54:27,560
Speaker 1: of your analytical time that you're trying to figure out

1065
00:54:27,960 --> 00:54:31,080
Speaker 1: if what you see is real the person committing the

1066
00:54:31,080 --> 00:54:33,279
Speaker 1: fraud of spending one hundred percent of their time staying

1067
00:54:33,320 --> 00:54:33,879
Speaker 1: ahead of you.

1068
00:54:34,000 --> 00:54:36,840
Speaker 2: Right, so you had written you spend ninety nine percent

1069
00:54:36,880 --> 00:54:39,359
Speaker 2: of the time assessing the merits of the deal. What's

1070
00:54:39,400 --> 00:54:41,480
Speaker 2: the valuation? How likely is this going to get all

1071
00:54:41,480 --> 00:54:45,120
Speaker 2: the fundamentals? And maybe you throw one percent at hey,

1072
00:54:46,280 --> 00:54:49,040
Speaker 2: it is what I'm seeing actual? Is there any chance

1073
00:54:49,040 --> 00:54:51,239
Speaker 2: of fraud? And most of the time you're going to

1074
00:54:51,320 --> 00:54:54,440
Speaker 2: say no, of course not burning made off as president

1075
00:54:54,480 --> 00:54:57,360
Speaker 2: of NASDAK. How could this be a fraud? Right that?

1076
00:54:57,360 --> 00:55:01,680
Speaker 2: That's an astonishing admission by price. What's the takeaway for

1077
00:55:01,760 --> 00:55:04,600
Speaker 2: the average investor? Is there something you can do to

1078
00:55:04,680 --> 00:55:08,440
Speaker 2: avoid fraud or is it just forever and always out there.

1079
00:55:09,400 --> 00:55:11,680
Speaker 1: There are lots of risks that are forever and always

1080
00:55:11,719 --> 00:55:15,640
Speaker 1: out there. Fraud is one of them, but you can

1081
00:55:15,680 --> 00:55:19,800
Speaker 1: diversify away from it. So that comes out in position

1082
00:55:19,920 --> 00:55:24,040
Speaker 1: sizing and conviction and just making sure that you're thinking

1083
00:55:24,040 --> 00:55:27,080
Speaker 1: about all the things that could go wrong if you're

1084
00:55:27,120 --> 00:55:29,240
Speaker 1: taking a more concentrated position in something.

1085
00:55:29,600 --> 00:55:34,120
Speaker 2: Huh really interesting. Here's another quote I love. You can't

1086
00:55:34,200 --> 00:55:40,120
Speaker 2: have investment success with a bad governance structure by Karl Sheer,

1087
00:55:40,760 --> 00:55:43,480
Speaker 2: explain what you mean by that? What mean?

1088
00:55:44,000 --> 00:55:46,520
Speaker 1: Yeah, Carl is the chief investment officer or the University

1089
00:55:46,520 --> 00:55:52,000
Speaker 1: of Cincinnati. The allocator pools that have chief investment officers

1090
00:55:52,440 --> 00:55:55,160
Speaker 1: have on top of them a board, maybe it's an

1091
00:55:55,200 --> 00:55:59,279
Speaker 1: investment committee, and that committee often is ultimately responsible for

1092
00:55:59,320 --> 00:56:00,520
Speaker 1: making investment decisions.

1093
00:56:01,040 --> 00:56:03,600
Speaker 2: And these boards they're all filled with humans.

1094
00:56:04,040 --> 00:56:05,120
Speaker 1: Yes, exactly.

1095
00:56:05,120 --> 00:56:07,359
Speaker 2: And that seems to be the underlying problem, isn't it?

1096
00:56:07,760 --> 00:56:11,240
Speaker 1: So everything that any duke talks about in decision making theory.

1097
00:56:11,320 --> 00:56:13,840
Speaker 1: If you can't make a good decision as a board,

1098
00:56:14,480 --> 00:56:18,240
Speaker 1: we'll call that the governance structure. How do actual investment

1099
00:56:18,239 --> 00:56:21,000
Speaker 1: decisions get made? You can't have a good investment process.

1100
00:56:21,040 --> 00:56:24,479
Speaker 2: And she focuses on process over outcomes. You make certain

1101
00:56:24,520 --> 00:56:27,040
Speaker 2: decisions even if it doesn't work out. You got to

1102
00:56:27,080 --> 00:56:30,600
Speaker 2: stay with the high probability. Back to what you said earlier,

1103
00:56:30,840 --> 00:56:34,880
Speaker 2: The high probability decision, even if it's a loser, is

1104
00:56:35,320 --> 00:56:38,719
Speaker 2: better process over the long haul than dumb luck.

1105
00:56:38,800 --> 00:56:40,200
Speaker 1: That wins absolutely right.

1106
00:56:40,960 --> 00:56:45,360
Speaker 2: So the story was that, I think was the Hertford

1107
00:56:45,520 --> 00:56:50,440
Speaker 2: investment Hartford Insurance. Everybody resigns. When they hired Bully and

1108
00:56:50,480 --> 00:56:53,319
Speaker 2: Stanley as the outside advisor. The whole thing was just

1109
00:56:53,360 --> 00:56:55,160
Speaker 2: a debacle what happened there.

1110
00:56:55,680 --> 00:56:59,279
Speaker 1: So it's Hartford Healthcare. David Holgrim is the CIO. I

1111
00:56:59,280 --> 00:57:01,759
Speaker 1: can't say I know exactly what happened on the inside,

1112
00:57:01,920 --> 00:57:04,040
Speaker 1: but they had a team that had delivered a good

1113
00:57:04,080 --> 00:57:07,720
Speaker 1: track record. H I'm assuming there was some friction between

1114
00:57:07,719 --> 00:57:11,000
Speaker 1: that team and the board, and the board hired Morgan

1115
00:57:11,040 --> 00:57:16,240
Speaker 1: Stanley as an OCIO, not only without ever consulting the team,

1116
00:57:16,840 --> 00:57:20,560
Speaker 1: but they had an investment committee of knowledgeable experts other

1117
00:57:20,720 --> 00:57:25,080
Speaker 1: endowment chief investment officers. That investment committee never knew that

1118
00:57:25,200 --> 00:57:27,560
Speaker 1: the board had done a search to replace the investment team.

1119
00:57:27,640 --> 00:57:31,800
Speaker 2: Wow, that seems pretty egregious. Sounds like a bunch of

1120
00:57:31,840 --> 00:57:38,040
Speaker 2: personality conflicts and no organizational alpha. I'm curious, how has

1121
00:57:38,360 --> 00:57:43,360
Speaker 2: that investment pool done since this palace coup.

1122
00:57:44,600 --> 00:57:46,920
Speaker 1: I don't know the answer. It's way too short of

1123
00:57:46,920 --> 00:57:49,160
Speaker 1: a period of time to actually have any assessment. And

1124
00:57:49,200 --> 00:57:52,880
Speaker 1: on top of that, chances are the underlying investments were

1125
00:57:52,920 --> 00:57:55,000
Speaker 1: mostly the same as what they were before on this.

1126
00:57:55,120 --> 00:57:57,720
Speaker 2: So they were inheriting what happened, you know. I'm reminded

1127
00:57:57,760 --> 00:58:00,720
Speaker 2: of what took place at Harvard with Iris Summers. I

1128
00:58:00,760 --> 00:58:03,680
Speaker 2: don't know what was that fifteen years ago, twenty years ago,

1129
00:58:04,000 --> 00:58:09,960
Speaker 2: and they went from an absolute bone crusher, outperformer alpha

1130
00:58:10,040 --> 00:58:13,720
Speaker 2: generator to just stinking up the joint for decades. It's

1131
00:58:14,360 --> 00:58:17,960
Speaker 2: it's hard to look at those changes, which, by the way,

1132
00:58:18,000 --> 00:58:21,640
Speaker 2: didn't come from Summers. It came from an alumni who said,

1133
00:58:21,680 --> 00:58:24,240
Speaker 2: why are we spending all this money? Even though they

1134
00:58:24,240 --> 00:58:27,840
Speaker 2: really were spending not a lot, especially once you looked

1135
00:58:27,880 --> 00:58:33,720
Speaker 2: at the returns. Talk about terrible governance destroying a beautiful, fragile,

1136
00:58:34,680 --> 00:58:36,240
Speaker 2: winning investment team.

1137
00:58:36,360 --> 00:58:40,880
Speaker 1: Yeah, the compensation structures of the largest, most influential pools

1138
00:58:40,880 --> 00:58:43,120
Speaker 1: of the capitol in the United States in particular, are

1139
00:58:43,240 --> 00:58:47,960
Speaker 1: really challenged. Public pension funds that manage hundreds of billion

1140
00:58:48,000 --> 00:58:51,160
Speaker 1: dollars can be manned by professionals that make eighty to

1141
00:58:51,160 --> 00:58:53,720
Speaker 1: one hundred and fifty thousand dollars a year. And you

1142
00:58:53,840 --> 00:58:57,600
Speaker 1: compare that with models that we've seen in Canada and Australia,

1143
00:58:58,120 --> 00:59:03,880
Speaker 1: where the investment professionals on those teams are market competitively compensated,

1144
00:59:03,960 --> 00:59:06,560
Speaker 1: maybe a slight discount to the market.

1145
00:59:06,280 --> 00:59:09,160
Speaker 2: But not like ten percent, not giant exactly right.

1146
00:59:09,960 --> 00:59:13,200
Speaker 1: And in the US, these largest pools of capital might

1147
00:59:13,240 --> 00:59:15,080
Speaker 1: have ninety percent discounts to the market.

1148
00:59:15,160 --> 00:59:19,160
Speaker 2: Really, that's that's unbelievable. Listen, just paying up for something

1149
00:59:19,240 --> 00:59:22,680
Speaker 2: doesn't guarantee that you're going to get the best, But

1150
00:59:22,840 --> 00:59:26,320
Speaker 2: paying a ninety percent discount pretty much guarantees that you're

1151
00:59:26,360 --> 00:59:29,400
Speaker 2: in the bottom let's call it half, I'm being generous,

1152
00:59:29,400 --> 00:59:33,840
Speaker 2: probably quartile that there's you know, it's a market bay system.

1153
00:59:33,960 --> 00:59:37,080
Speaker 2: Don't you want the best people steering your forty two

1154
00:59:37,200 --> 00:59:41,520
Speaker 2: billion dollar endownmen? It just so short sighted. Just goes

1155
00:59:41,560 --> 00:59:46,439
Speaker 2: to show you how important governance is. And since we're

1156
00:59:46,480 --> 00:59:49,080
Speaker 2: talking about governance, let's talk about another thing you had

1157
00:59:49,080 --> 00:59:52,000
Speaker 2: written that I was intrigued by. What's in a name?

1158
00:59:52,120 --> 00:59:56,520
Speaker 2: The problem with ESG. Now we're not talking about wokeism

1159
00:59:56,600 --> 01:00:01,800
Speaker 2: or the political backlash, which is really a partisan political debate.

1160
01:00:02,640 --> 01:00:08,200
Speaker 2: What's the problem with ESG as a approach to value

1161
01:00:08,240 --> 01:00:09,040
Speaker 2: based investing?

1162
01:00:09,240 --> 01:00:15,040
Speaker 1: Yeah, well let's start with the name itself. So EESG became.

1163
01:00:14,760 --> 01:00:18,000
Speaker 2: A thing, environmental, social, and governance.

1164
01:00:17,840 --> 01:00:20,720
Speaker 1: Three things which may or may not have anything to

1165
01:00:20,760 --> 01:00:23,680
Speaker 1: do with each other. Clearly, you can go back and say,

1166
01:00:23,720 --> 01:00:27,480
Speaker 1: remember fang and then Fang had two a's and then

1167
01:00:27,480 --> 01:00:31,240
Speaker 1: it turned into fan mag. So these names have a

1168
01:00:31,280 --> 01:00:35,520
Speaker 1: way of taking off right back in the day brick

1169
01:00:35,560 --> 01:00:41,040
Speaker 1: and emerging markets Zil, Russia, India, China. So the problem

1170
01:00:41,080 --> 01:00:43,600
Speaker 1: with the SG in its first iteration was that the

1171
01:00:43,720 --> 01:00:48,040
Speaker 1: label that everyone ascribed to it wasn't anything anyone could understand.

1172
01:00:48,240 --> 01:00:53,160
Speaker 2: So let's track that evolution. This all started with divesting

1173
01:00:53,280 --> 01:00:57,120
Speaker 2: South African investments with I think it was Harvard actually

1174
01:00:57,640 --> 01:00:59,920
Speaker 2: or Yale was one of the ivys that the student

1175
01:01:00,600 --> 01:01:04,160
Speaker 2: population wanted the endowment out of that, which led to

1176
01:01:04,400 --> 01:01:08,720
Speaker 2: socially responsible investing, which led to impact investing. Like there

1177
01:01:08,720 --> 01:01:11,880
Speaker 2: have been a ton of names, ESG just seems to

1178
01:01:11,880 --> 01:01:15,680
Speaker 2: be a catchual umbrella. Yeah, what should it be called?

1179
01:01:15,760 --> 01:01:16,920
Speaker 2: Or should it be called anything?

1180
01:01:17,480 --> 01:01:19,760
Speaker 1: Well? I think it goes back to what we talked about,

1181
01:01:19,760 --> 01:01:24,520
Speaker 1: the onset about beliefs. Each institution has to decide how

1182
01:01:24,520 --> 01:01:29,200
Speaker 1: do they want to align their investing with the purpose

1183
01:01:29,280 --> 01:01:31,360
Speaker 1: of the institution. What are they trying to solve for?

1184
01:01:31,480 --> 01:01:34,200
Speaker 1: So lots of people want to solve for call it

1185
01:01:34,280 --> 01:01:37,040
Speaker 1: sustainable investing. What does that mean? I don't know, but

1186
01:01:37,760 --> 01:01:43,080
Speaker 1: the idea of an environment that humans can habit for

1187
01:01:43,200 --> 01:01:46,480
Speaker 1: centuries seems like that resonates with people, so that that

1188
01:01:46,640 --> 01:01:50,240
Speaker 1: leads to one set of sort of investment criteria that

1189
01:01:50,280 --> 01:01:54,120
Speaker 1: you can filter into your whole portfolio. The s is

1190
01:01:54,160 --> 01:01:58,120
Speaker 1: really about diversity, and that's important to a lot of people.

1191
01:01:58,360 --> 01:02:01,120
Speaker 1: It's certainly in financial services recognized now that there are

1192
01:02:01,120 --> 01:02:03,400
Speaker 1: all these microaggressions that have been in place for decades.

1193
01:02:03,560 --> 01:02:05,720
Speaker 1: I'm not sure how that turned into an investment strategy.

1194
01:02:05,720 --> 01:02:07,320
Speaker 2: See, I don't even think of it in those terms.

1195
01:02:07,320 --> 01:02:09,760
Speaker 2: I think of it as you want to avoid group think.

1196
01:02:10,240 --> 01:02:12,840
Speaker 2: And if everybody went to the same undergrad went to

1197
01:02:12,880 --> 01:02:15,400
Speaker 2: the same grad went to the same training program, well

1198
01:02:15,440 --> 01:02:19,360
Speaker 2: you're cranking out these automatons that are gonna think, speak,

1199
01:02:19,400 --> 01:02:23,280
Speaker 2: and act similarle and so the investment results will be similar,

1200
01:02:23,400 --> 01:02:29,600
Speaker 2: therefore subpar. So let's bring in different people from different backgrounds,

1201
01:02:29,600 --> 01:02:34,000
Speaker 2: different thought processes, different education, so that there is some

1202
01:02:34,160 --> 01:02:39,600
Speaker 2: robust diversity of thought. I just don't like the microaggression thing.

1203
01:02:39,640 --> 01:02:40,640
Speaker 2: I could care less about.

1204
01:02:40,720 --> 01:02:43,560
Speaker 1: So the challenge is that the academic research shows that

1205
01:02:43,600 --> 01:02:46,440
Speaker 1: what you're trying to solve for is cognitive diversity. Yes,

1206
01:02:47,240 --> 01:02:50,920
Speaker 1: social diversity is a proxy for cognitive diversity.

1207
01:02:50,560 --> 01:02:51,600
Speaker 2: Not a great one, by the way.

1208
01:02:51,600 --> 01:02:54,080
Speaker 1: I know. You could have people from all different races

1209
01:02:54,080 --> 01:02:56,240
Speaker 1: that think exactly the same way because they were educated

1210
01:02:56,280 --> 01:02:59,120
Speaker 1: at the same places. So the question is if you

1211
01:02:59,280 --> 01:03:03,280
Speaker 1: care about improving your investment results from cognitive diversity, which

1212
01:03:03,280 --> 01:03:06,480
Speaker 1: we can all agree the research shows make sense. Is

1213
01:03:06,480 --> 01:03:09,000
Speaker 1: that a thing that you measure, Is that a thing

1214
01:03:09,080 --> 01:03:11,920
Speaker 1: that you evaluate? How do you do that? So nobody

1215
01:03:11,920 --> 01:03:15,680
Speaker 1: really knows. And then governance, like, I'm not sure I

1216
01:03:15,720 --> 01:03:20,160
Speaker 1: know of anyone except for occasionally an activist investor as

1217
01:03:20,200 --> 01:03:23,400
Speaker 1: an opportunity set that is pro poor governance.

1218
01:03:24,720 --> 01:03:28,240
Speaker 2: Yeah, I can't really hear that anybody has been agitating

1219
01:03:28,280 --> 01:03:30,360
Speaker 2: for you need to make your governance worse.

1220
01:03:30,520 --> 01:03:32,480
Speaker 1: So what's evolved over the last couple of years is

1221
01:03:32,920 --> 01:03:36,240
Speaker 1: starting with Greta Thunberg and then during COVID when ESG

1222
01:03:36,440 --> 01:03:38,800
Speaker 1: took on this label, people created a whole bunch of

1223
01:03:38,800 --> 01:03:41,840
Speaker 1: products that nobody really understood what they were solving for,

1224
01:03:41,880 --> 01:03:45,520
Speaker 1: and so not that surprising. It hasn't really taken off

1225
01:03:45,640 --> 01:03:47,440
Speaker 1: in the way that a lot of people predicted four

1226
01:03:47,480 --> 01:03:48,200
Speaker 1: or five years.

1227
01:03:48,000 --> 01:03:50,960
Speaker 2: But there's a ton of capital that has been allocated

1228
01:03:51,240 --> 01:03:55,360
Speaker 2: to So let's work away away from ESG. There are

1229
01:03:55,480 --> 01:03:58,320
Speaker 2: impact funds that go out of their way to make

1230
01:03:58,320 --> 01:04:04,640
Speaker 2: sure that half of their investments go to companies that

1231
01:04:04,680 --> 01:04:07,360
Speaker 2: are either managed by women or people of color, or

1232
01:04:07,800 --> 01:04:13,240
Speaker 2: are geographically away from New York, Boston, San Francisco, Silicon

1233
01:04:13,360 --> 01:04:17,200
Speaker 2: Valley because the rest of the country has innovations and

1234
01:04:17,240 --> 01:04:21,200
Speaker 2: we've been ignoring them. And in fact, the competition in

1235
01:04:21,240 --> 01:04:25,919
Speaker 2: San Francisco and Silicon Valley is much more intense than

1236
01:04:26,600 --> 01:04:28,960
Speaker 2: Milwaukee or Orlando.

1237
01:04:30,080 --> 01:04:33,080
Speaker 1: So I think that's right. The question is what does

1238
01:04:33,120 --> 01:04:37,280
Speaker 1: a ton of capital mean, right? And the scheme of things.

1239
01:04:37,800 --> 01:04:39,960
Speaker 1: The point I would make is that the amount of

1240
01:04:40,000 --> 01:04:44,440
Speaker 1: money that's gone into these different called diversifying strategies is

1241
01:04:44,520 --> 01:04:46,360
Speaker 1: much less than people thought it was going to be

1242
01:04:46,360 --> 01:04:48,760
Speaker 1: four or five years ago, because it's all under this

1243
01:04:48,880 --> 01:04:53,440
Speaker 1: umbrella that each individual organization needs to figure out what

1244
01:04:53,480 --> 01:04:55,160
Speaker 1: do they care about and how do they want to

1245
01:04:55,200 --> 01:04:57,160
Speaker 1: deploy capital to meet that objective.

1246
01:04:57,440 --> 01:05:01,200
Speaker 2: Don't some foundations have a sort of a check approach, Hey,

1247
01:05:01,240 --> 01:05:04,640
Speaker 2: we want to give five percent of our alternative assets

1248
01:05:04,680 --> 01:05:08,320
Speaker 2: to funds run by women, or funds run by minorities

1249
01:05:08,440 --> 01:05:12,800
Speaker 2: or LGBT like down the list as a way of

1250
01:05:13,720 --> 01:05:17,520
Speaker 2: providing a little social diversity. But again, the point you

1251
01:05:17,560 --> 01:05:20,760
Speaker 2: make is social diversity the same as cognitive diversity. Is

1252
01:05:20,800 --> 01:05:21,600
Speaker 2: it a good proxy.

1253
01:05:21,760 --> 01:05:24,240
Speaker 1: They absolutely want to do that as long as those

1254
01:05:24,280 --> 01:05:26,560
Speaker 1: funds outperform.

1255
01:05:26,560 --> 01:05:31,960
Speaker 2: That's really interesting. So once the outperformance stops, we be

1256
01:05:31,960 --> 01:05:36,760
Speaker 2: swap managers. Huh, that's really interesting. Last question on ESG,

1257
01:05:37,560 --> 01:05:40,720
Speaker 2: certain folks have been saying, hey, you know, it works

1258
01:05:40,720 --> 01:05:45,200
Speaker 2: as a pretty good risk management filter. Boards that have

1259
01:05:45,400 --> 01:05:48,640
Speaker 2: thirty forty percent women tend not to have the same

1260
01:05:48,760 --> 01:05:52,640
Speaker 2: sort of me too problems as a board that's all

1261
01:05:52,840 --> 01:05:55,360
Speaker 2: a whole bunch of old white guys. How do you

1262
01:05:55,440 --> 01:05:59,440
Speaker 2: respond to this is a risk management filter that allows

1263
01:05:59,480 --> 01:06:03,680
Speaker 2: us to wipeify the worst actors in corporate America.

1264
01:06:03,800 --> 01:06:07,360
Speaker 1: I think that's a very reasonable way of looking at it. Again,

1265
01:06:07,480 --> 01:06:10,440
Speaker 1: depending on your investment strategy. Are we're talking about boards

1266
01:06:10,480 --> 01:06:13,680
Speaker 1: of stocks? What about in private markets? What about an

1267
01:06:13,680 --> 01:06:16,640
Speaker 1: early stage venture and a hedge fund? Like, there's all

1268
01:06:16,760 --> 01:06:19,760
Speaker 1: different ways that you can think about integrating it, And

1269
01:06:20,320 --> 01:06:23,840
Speaker 1: just like the problem with SG, there's no one absolute

1270
01:06:23,880 --> 01:06:25,160
Speaker 1: solution that works for everything.

1271
01:06:25,240 --> 01:06:28,280
Speaker 2: Huh. Really really quite quite fascinating. Let's talk a little

1272
01:06:28,280 --> 01:06:33,840
Speaker 2: bit about capital allocators. What made you decide to play

1273
01:06:33,840 --> 01:06:35,480
Speaker 2: with this whole podcast? Then?

1274
01:06:36,000 --> 01:06:39,040
Speaker 1: Well, I guess I was channeling my inner Bury Ridtholes. Yeah,

1275
01:06:39,360 --> 01:06:43,200
Speaker 1: years ago when I left protege A Partners. I wasn't

1276
01:06:43,280 --> 01:06:45,680
Speaker 1: sure what I would do, and I had picked up

1277
01:06:45,720 --> 01:06:49,000
Speaker 1: a bunch of called it consulting or advisory relationships, and

1278
01:06:49,040 --> 01:06:51,640
Speaker 1: I had written that first book about hedge funds, which led.

1279
01:06:51,480 --> 01:06:52,440
Speaker 2: Me twenty sixteen.

1280
01:06:52,480 --> 01:06:55,400
Speaker 1: In twenty sixteen, which led me to be on a

1281
01:06:55,440 --> 01:06:58,439
Speaker 1: couple of podcasts, and I woke up one day and said,

1282
01:06:58,720 --> 01:07:00,640
Speaker 1: maybe I'll run around and talk to my old friends.

1283
01:07:00,920 --> 01:07:02,000
Speaker 1: I had no idea.

1284
01:07:02,480 --> 01:07:06,160
Speaker 2: Dude, you're ruining my secret asself. Well, what the greatest gig,

1285
01:07:06,240 --> 01:07:09,520
Speaker 2: the easiest thing in the world, and now everybody's doing it.

1286
01:07:09,640 --> 01:07:12,000
Speaker 2: But for a while, you know, it was it was

1287
01:07:12,080 --> 01:07:14,560
Speaker 2: my secret little garden that no one knew about.

1288
01:07:14,920 --> 01:07:18,160
Speaker 1: And so I did that, and I started a podcast

1289
01:07:18,200 --> 01:07:21,440
Speaker 1: called Capital Allocators, and the idea was to be interviewing

1290
01:07:21,600 --> 01:07:24,280
Speaker 1: the people and make it be about the people, and

1291
01:07:24,280 --> 01:07:28,400
Speaker 1: then of course about investment strategies focused on the allocator

1292
01:07:28,480 --> 01:07:31,800
Speaker 1: CIO community and some of their favored money managers.

1293
01:07:32,920 --> 01:07:36,640
Speaker 2: And that's a rich, deep pool. People don't realize you

1294
01:07:36,640 --> 01:07:38,760
Speaker 2: ever get the question, Hey, are you worried you're gonna

1295
01:07:38,800 --> 01:07:40,640
Speaker 2: run out of people? I'm like, no, I got ten

1296
01:07:40,680 --> 01:07:42,560
Speaker 2: million people to go. What are you kidding me.

1297
01:07:42,760 --> 01:07:45,120
Speaker 1: There's never been a shortage of high quality people to

1298
01:07:45,160 --> 01:07:48,720
Speaker 1: have on And so I started that six years ago,

1299
01:07:49,800 --> 01:07:52,120
Speaker 1: not knowing certainly, not thinking it would be a business.

1300
01:07:52,160 --> 01:07:53,840
Speaker 1: I used to joke, Hey, Barry, we're going to have

1301
01:07:53,840 --> 01:07:57,040
Speaker 1: a conversation, share it for free, and just like the

1302
01:07:57,160 --> 01:07:59,240
Speaker 1: change bank from Saturday Night Live, we'll make it up

1303
01:07:59,240 --> 01:08:02,000
Speaker 1: in volume, right, Like was sort of a dot com

1304
01:08:02,000 --> 01:08:05,920
Speaker 1: click business, and I just kept doing it for a

1305
01:08:06,000 --> 01:08:08,680
Speaker 1: number of years alongside of these other projects.

1306
01:08:08,320 --> 01:08:11,000
Speaker 2: Which, by the way, something like ninety percent of the

1307
01:08:11,040 --> 01:08:14,080
Speaker 2: podcasts drop off within a year. They just it's work.

1308
01:08:14,160 --> 01:08:14,840
Speaker 2: It's not easy.

1309
01:08:15,360 --> 01:08:17,200
Speaker 1: Yeah, it was, but it was just so much fun,

1310
01:08:17,320 --> 01:08:19,040
Speaker 1: and it was one of the things that.

1311
01:08:19,120 --> 01:08:23,040
Speaker 2: Again you're ruining my mind secret it's endless fun, right,

1312
01:08:23,120 --> 01:08:26,439
Speaker 2: I mean, think about, think about I went through the

1313
01:08:26,479 --> 01:08:28,479
Speaker 2: list of some of the people you spoke with. You

1314
01:08:28,520 --> 01:08:31,920
Speaker 2: could see there is delight in the conversation you have

1315
01:08:32,040 --> 01:08:35,160
Speaker 2: with b Yeah. It's a version of what I did

1316
01:08:35,200 --> 01:08:38,200
Speaker 2: my whole career, right. I spent time interviewing money managers

1317
01:08:38,880 --> 01:08:42,400
Speaker 2: with a very very different output mechanism. So in the past,

1318
01:08:42,439 --> 01:08:44,519
Speaker 2: i'd have an interview with a manager and I would

1319
01:08:44,520 --> 01:08:47,280
Speaker 2: be evaluating them, and I would mostly say no, but

1320
01:08:47,479 --> 01:08:49,200
Speaker 2: you know, sometimes you'd say, oh, what do I think

1321
01:08:49,280 --> 01:08:52,200
Speaker 2: of them? And this is just you have the same conversation,

1322
01:08:52,439 --> 01:08:54,880
Speaker 2: there's no evaluation. You get to be on everyone's team

1323
01:08:55,360 --> 01:08:57,719
Speaker 2: and then you share it with people. And what's happened

1324
01:08:57,760 --> 01:09:00,680
Speaker 2: over the years is to become the largest podcast institutional

1325
01:09:00,720 --> 01:09:05,720
Speaker 2: investing so that Allocator community listens and people have incredible

1326
01:09:05,760 --> 01:09:08,920
Speaker 2: experiences when they come on, and it's just it's just

1327
01:09:09,000 --> 01:09:11,320
Speaker 2: so rewarding. It's by far the most rewarding thing I've

1328
01:09:11,360 --> 01:09:14,160
Speaker 2: done in my professional career. I say to people, this

1329
01:09:14,200 --> 01:09:16,040
Speaker 2: is the most fun I have all week, and they

1330
01:09:16,040 --> 01:09:18,599
Speaker 2: look at me, like, wait, what you need to get

1331
01:09:18,640 --> 01:09:21,920
Speaker 2: a life? I'm like, no, you don't understand. Is it

1332
01:09:21,960 --> 01:09:23,679
Speaker 2: the most fun you have each week? H you speak

1333
01:09:23,680 --> 01:09:27,320
Speaker 2: to somebodystely first of all, my dirty little secret, and

1334
01:09:27,360 --> 01:09:29,760
Speaker 2: I don't know if this is yours. I don't care

1335
01:09:29,760 --> 01:09:32,360
Speaker 2: who's listening. I invite people that I want to sit

1336
01:09:32,400 --> 01:09:35,480
Speaker 2: down with for an hour or two and have this conversation.

1337
01:09:35,920 --> 01:09:39,920
Speaker 2: If someone listens, great, but I don't care. It's like, no, no,

1338
01:09:39,960 --> 01:09:41,680
Speaker 2: I have an audience A one. It's me. It's my

1339
01:09:42,320 --> 01:09:46,519
Speaker 2: selfish indulgence. Okay, other people have listened. But when you're

1340
01:09:46,800 --> 01:09:49,880
Speaker 2: picking people to invite, how much of it is I

1341
01:09:49,920 --> 01:09:51,479
Speaker 2: really want to sit down and talk to that guy

1342
01:09:51,560 --> 01:09:52,160
Speaker 2: with that girl.

1343
01:09:52,240 --> 01:09:55,920
Speaker 1: That's all of it. I still and always will source

1344
01:09:56,040 --> 01:09:59,600
Speaker 1: all the guests myself. We do get a lot of inbounds,

1345
01:09:59,600 --> 01:10:03,000
Speaker 1: and we figured out ways of getting more people involved

1346
01:10:03,000 --> 01:10:06,320
Speaker 1: that I might not have known about. But it is

1347
01:10:06,920 --> 01:10:09,280
Speaker 1: entirely Hey, what do I think is interesting? Who would

1348
01:10:09,280 --> 01:10:11,559
Speaker 1: I like to talk to? And you go from there.

1349
01:10:11,800 --> 01:10:16,040
Speaker 2: You focus primarily on the institutional side of things. How

1350
01:10:16,080 --> 01:10:20,760
Speaker 2: does that translate into who listens? Do you want a

1351
01:10:20,800 --> 01:10:24,680
Speaker 2: broader audience or do you like this somewhat narrow but

1352
01:10:24,840 --> 01:10:29,760
Speaker 2: incredibly deep and knowledgeable listenership. What led you in that

1353
01:10:29,800 --> 01:10:32,120
Speaker 2: direction other than that's the world you came from.

1354
01:10:32,520 --> 01:10:34,920
Speaker 1: It's mostly that, And it goes to what you said,

1355
01:10:35,000 --> 01:10:39,400
Speaker 1: which is I love having these conversations. And have never

1356
01:10:39,479 --> 01:10:43,720
Speaker 1: advertised on the podcast. I'm sorry, I've never advertised for

1357
01:10:43,840 --> 01:10:46,719
Speaker 1: the podcast other than a meaning a couple of little experience.

1358
01:10:46,800 --> 01:10:49,719
Speaker 2: So do you promote the podcast? How do you other

1359
01:10:49,760 --> 01:10:53,200
Speaker 2: than going on other PS podcasts? How do you get

1360
01:10:53,240 --> 01:10:56,840
Speaker 2: to the point where people are listening other than the

1361
01:10:56,840 --> 01:10:58,479
Speaker 2: circle of institutional allocate?

1362
01:10:58,560 --> 01:11:02,360
Speaker 1: Yes, it's been entirely organ We've done a few little

1363
01:11:02,400 --> 01:11:05,640
Speaker 1: experiments promoting and advertising, none of it to worked, so

1364
01:11:06,000 --> 01:11:08,080
Speaker 1: I've never really cared about it. It's kind of like

1365
01:11:08,120 --> 01:11:10,640
Speaker 1: what you said. I didn't think of it as a

1366
01:11:10,680 --> 01:11:13,920
Speaker 1: business when I started. I barely do now. And people

1367
01:11:13,960 --> 01:11:17,040
Speaker 1: have found it because it added value to their professional careers.

1368
01:11:17,080 --> 01:11:19,599
Speaker 1: So most of that audience, I would say, as far

1369
01:11:19,640 --> 01:11:21,840
Speaker 1: as we can tell, a little less than half is

1370
01:11:21,880 --> 01:11:26,400
Speaker 1: the institutional allocator community, and that spans endowments, foundations where

1371
01:11:26,400 --> 01:11:29,240
Speaker 1: I came from. It spans sovereign wealth funds, pension funds.

1372
01:11:29,240 --> 01:11:33,280
Speaker 1: Incredibly global and that reach, which I'm sure you know,

1373
01:11:33,680 --> 01:11:36,960
Speaker 1: you know it's hilarious. This is so much wider than

1374
01:11:37,000 --> 01:11:38,840
Speaker 1: I ever could have imagined existed.

1375
01:11:38,520 --> 01:11:42,000
Speaker 2: Because it's total. The Internet is totally global, and I've

1376
01:11:42,000 --> 01:11:45,040
Speaker 2: had I'm sure you've had this experience. I've had guests

1377
01:11:45,040 --> 01:11:47,320
Speaker 2: say I heard from a kid I went to camp

1378
01:11:47,360 --> 01:11:50,160
Speaker 2: with who now runs a fund in Hong Kong. I mean,

1379
01:11:50,600 --> 01:11:55,439
Speaker 2: but what, there's nothing local about a podcast. If it's

1380
01:11:55,439 --> 01:12:00,160
Speaker 2: on the Internet, it's totally discoverable. I've also had the

1381
01:12:00,160 --> 01:12:04,920
Speaker 2: same experience with half. If half are institutional allocators, who's

1382
01:12:04,960 --> 01:12:05,559
Speaker 2: the other half.

1383
01:12:06,280 --> 01:12:08,400
Speaker 1: Most of it's money managers, so it's most of the

1384
01:12:08,400 --> 01:12:08,800
Speaker 1: people in the.

1385
01:12:08,840 --> 01:12:10,360
Speaker 2: Care people they're allocating too.

1386
01:12:10,400 --> 01:12:13,360
Speaker 1: That's correct. And then there's this other right, so you

1387
01:12:13,400 --> 01:12:16,720
Speaker 1: get notes from students from friends who are outside that

1388
01:12:16,840 --> 01:12:18,960
Speaker 1: it's just entertainment NBA professors.

1389
01:12:18,960 --> 01:12:22,719
Speaker 2: You hear from from professors saying, hey, I love this interview.

1390
01:12:22,760 --> 01:12:24,200
Speaker 2: I assigned this to the class.

1391
01:12:24,280 --> 01:12:27,439
Speaker 1: Yeah, it's just just fantastic. So that that's one of

1392
01:12:27,520 --> 01:12:30,519
Speaker 1: the fun things about it is you just anyone can listen.

1393
01:12:30,840 --> 01:12:36,840
Speaker 2: So Curveball question, what's your favorite podcast guest story that

1394
01:12:36,880 --> 01:12:39,800
Speaker 2: you can tell publicly? Because we all have great stories,

1395
01:12:40,360 --> 01:12:45,280
Speaker 2: some of which not really not really FCC.

1396
01:12:45,439 --> 01:12:47,479
Speaker 1: There are one or two of those, but not that many.

1397
01:12:47,840 --> 01:12:50,519
Speaker 1: I think I would even go all the way back

1398
01:12:50,560 --> 01:12:53,479
Speaker 1: to my very first episode. So it was with Steve Galberth,

1399
01:12:53,520 --> 01:12:57,559
Speaker 1: who mentioned earlier with Jack Bogel, and it was just

1400
01:12:57,640 --> 01:12:59,680
Speaker 1: this idea. I knew Steve, I knew he had a

1401
01:12:59,680 --> 01:13:03,519
Speaker 1: great story, and I sat down and recorded it and

1402
01:13:04,240 --> 01:13:08,120
Speaker 1: I couldn't find the recording on the recording device after

1403
01:13:08,160 --> 01:13:10,639
Speaker 1: we finished, and it was so good. I just said,

1404
01:13:10,680 --> 01:13:12,679
Speaker 1: I can't believe this is I can't wait to share

1405
01:13:12,720 --> 01:13:15,120
Speaker 1: this with people. And then I thought that that was

1406
01:13:15,120 --> 01:13:18,759
Speaker 1: the end of my podcast career after the first recording,

1407
01:13:18,760 --> 01:13:21,160
Speaker 1: and it took a good friend of mine who's a

1408
01:13:21,200 --> 01:13:24,679
Speaker 1: technical whiz to figure out which actually wasn't that hard.

1409
01:13:24,720 --> 01:13:26,680
Speaker 1: I just didn't know how to do it to extract

1410
01:13:26,720 --> 01:13:28,559
Speaker 1: the conversation from the recording device.

1411
01:13:28,760 --> 01:13:31,720
Speaker 2: I'm going to share a similar story with you. So

1412
01:13:31,880 --> 01:13:35,479
Speaker 2: normally I'm in the Bloomberg studios. I got an engineer,

1413
01:13:35,560 --> 01:13:38,799
Speaker 2: I got all the latest equipment. I have the easiest

1414
01:13:38,840 --> 01:13:41,559
Speaker 2: gig in podcast. I show up, I said, hey, print

1415
01:13:41,600 --> 01:13:46,080
Speaker 2: this out for me. Off we go one About five

1416
01:13:46,160 --> 01:13:49,640
Speaker 2: years ago, I'm planning a trip to Silicon Valley. I

1417
01:13:49,720 --> 01:13:53,559
Speaker 2: tea up two interviews in a day, Mark Andreason of

1418
01:13:53,680 --> 01:13:58,840
Speaker 2: Andres and Horowitz and Nobel Laureate Bill Sharp. And by coincidence,

1419
01:13:58,840 --> 01:14:00,360
Speaker 2: I couldn't find a place to the rook towards the

1420
01:14:00,400 --> 01:14:03,320
Speaker 2: Bill Sharp interview, and Dreesen said, oh, do it here.

1421
01:14:03,360 --> 01:14:05,920
Speaker 2: You could use our pic podcast studios. They were great.

1422
01:14:06,400 --> 01:14:08,599
Speaker 2: So I sit down with Bill. So I do Andresen

1423
01:14:08,640 --> 01:14:11,840
Speaker 2: in the morning. Right in the afternoon it is Bill Sharp.

1424
01:14:11,880 --> 01:14:14,960
Speaker 2: After lunch, I sit down. I have my device, which

1425
01:14:15,000 --> 01:14:18,559
Speaker 2: the engineer has taught me forty seven times. How to do,

1426
01:14:19,080 --> 01:14:24,639
Speaker 2: and I start the podcast with Bill Sharp, and maybe

1427
01:14:24,960 --> 01:14:29,080
Speaker 2: ninety seconds in, I notice I'm not recording, and I

1428
01:14:29,320 --> 01:14:33,000
Speaker 2: just to have my stomach sinks and I imagine, like,

1429
01:14:33,280 --> 01:14:35,320
Speaker 2: imagine spending an hour and a half with Bill Sharp

1430
01:14:35,560 --> 01:14:38,640
Speaker 2: and not having hit record. So I'm like Bill, I'm

1431
01:14:38,680 --> 01:14:41,160
Speaker 2: I'm not getting a good audio level. Let me let's

1432
01:14:41,160 --> 01:14:43,599
Speaker 2: start this again. So I hit it and now the

1433
01:14:43,640 --> 01:14:46,080
Speaker 2: red lights on the view meet is going crazy and

1434
01:14:46,120 --> 01:14:48,320
Speaker 2: I could see it's recording. I go, let's start over.

1435
01:14:48,560 --> 01:14:50,720
Speaker 2: I think I was you were too soft, and I

1436
01:14:50,880 --> 01:14:53,439
Speaker 2: just adjusted and we do the recording. And to me,

1437
01:14:53,560 --> 01:14:59,240
Speaker 2: that was the nightmare scenario of missing God Nobel Laurion.

1438
01:14:59,320 --> 01:15:01,960
Speaker 2: Imagine that. So you found the gal Brith.

1439
01:15:03,080 --> 01:15:05,439
Speaker 1: Found, the recording went out, and the rest is history.

1440
01:15:05,840 --> 01:15:08,800
Speaker 2: So that's really interesting. So we only have you for

1441
01:15:08,920 --> 01:15:13,160
Speaker 2: so much time, and I appreciate you tolerating my nonsense.

1442
01:15:13,800 --> 01:15:16,680
Speaker 2: Let's jump to my favorite questions that I ask all

1443
01:15:16,720 --> 01:15:19,719
Speaker 2: of my guests, some of which I think I'm ready

1444
01:15:19,720 --> 01:15:23,000
Speaker 2: to retire. Probably the first one I'm ready to retire,

1445
01:15:23,040 --> 01:15:27,160
Speaker 2: which is a post lockdown question. I was asking people, Hey,

1446
01:15:27,160 --> 01:15:30,440
Speaker 2: what are you streaming? What's keeping you entertained? During lockdown?

1447
01:15:31,920 --> 01:15:34,280
Speaker 2: Let's see if you have an answer to that. What

1448
01:15:34,320 --> 01:15:35,799
Speaker 2: have you been watching that's interesting?

1449
01:15:37,080 --> 01:15:40,200
Speaker 1: Well, I'm a ted Lasso guy and I've watched the

1450
01:15:40,200 --> 01:15:42,320
Speaker 1: finale of the last season three times.

1451
01:15:42,840 --> 01:15:46,160
Speaker 2: I thought that was unfairly slagged. It was really good.

1452
01:15:46,200 --> 01:15:50,360
Speaker 1: It was really good. In addition to that, I had

1453
01:15:50,640 --> 01:15:53,400
Speaker 1: on the show last year named Brent Montgomery, and brand's

1454
01:15:53,439 --> 01:15:57,120
Speaker 1: a TV producer. He created Pawn Stars and Duck Dynasty.

1455
01:15:57,560 --> 01:16:01,240
Speaker 1: His latest show is called The King of Colors, right,

1456
01:16:01,320 --> 01:16:05,599
Speaker 1: and it's pawn Stars meet Sports a guy named Ken

1457
01:16:05,640 --> 01:16:09,320
Speaker 1: Golden who's one of the largest sports collectibles dealers, and

1458
01:16:09,360 --> 01:16:11,439
Speaker 1: it is so so good.

1459
01:16:11,760 --> 01:16:16,559
Speaker 2: Do you get into the massive amount of counterfeit crap

1460
01:16:17,000 --> 01:16:19,800
Speaker 2: that's in that space at all? Because I would of

1461
01:16:19,840 --> 01:16:24,320
Speaker 2: all the junk I buy, sports collectibles is the last

1462
01:16:24,320 --> 01:16:27,519
Speaker 2: thing in the world I would ever risk a penny on. Yeah,

1463
01:16:27,560 --> 01:16:30,680
Speaker 2: I'm convinced there's some kid, you know, in some sweatshop

1464
01:16:30,680 --> 01:16:33,479
Speaker 2: in a basement signing Michael Jordan's name over and over again.

1465
01:16:33,600 --> 01:16:38,120
Speaker 1: Yeah, they do show how they go through the authentication process,

1466
01:16:38,240 --> 01:16:41,639
Speaker 1: at least with this one very high quality dealer, right.

1467
01:16:42,040 --> 01:16:44,639
Speaker 2: I mean, I'm sure there are ways to authenticate it,

1468
01:16:44,960 --> 01:16:47,519
Speaker 2: but every time I look at something on eBay, I

1469
01:16:47,920 --> 01:16:49,200
Speaker 2: just kind of like, yeah, getting go.

1470
01:16:49,360 --> 01:16:52,519
Speaker 1: I mean, this has you know, it has Mike Tyson,

1471
01:16:52,800 --> 01:16:56,960
Speaker 1: has all these incredible athletes and entertainers that get involved

1472
01:16:56,960 --> 01:16:58,559
Speaker 1: with this guy. It's a fantastic show.

1473
01:16:58,720 --> 01:17:02,160
Speaker 2: Really. That sounds really really interesting. Let's talk about books.

1474
01:17:02,720 --> 01:17:04,840
Speaker 2: You've written two of them. What are some of the

1475
01:17:04,880 --> 01:17:06,960
Speaker 2: favorite books that you've read, and what are you reading

1476
01:17:07,000 --> 01:17:09,360
Speaker 2: currently this year.

1477
01:17:10,479 --> 01:17:12,760
Speaker 1: The favorite book I've read is Unreasonable Hospitality.

1478
01:17:13,320 --> 01:17:17,720
Speaker 2: I just got that book. Somebody recommended it. It looks fascinating.

1479
01:17:18,040 --> 01:17:20,640
Speaker 1: It's by Will Goadaro, who's one of the founders of

1480
01:17:20,680 --> 01:17:26,640
Speaker 1: eleven Madison, Danny Meyer's partner, and really describes an excruciating,

1481
01:17:27,080 --> 01:17:31,880
Speaker 1: thoughtful detail what it takes to be a creative customer,

1482
01:17:32,640 --> 01:17:35,719
Speaker 1: customer focused organization. It's a phenomenal book.

1483
01:17:35,760 --> 01:17:39,200
Speaker 2: For a long time, eleven Madison was just you know,

1484
01:17:39,439 --> 01:17:42,800
Speaker 2: mission and rated everything else. It was, Yes, it was spectacular.

1485
01:17:42,920 --> 01:17:45,640
Speaker 1: That's my favorite one this year. The one I've been

1486
01:17:45,680 --> 01:17:48,040
Speaker 1: reading most recently, which has been a long project before

1487
01:17:48,040 --> 01:17:49,960
Speaker 1: I go to bed, and it's a ten year old

1488
01:17:49,960 --> 01:17:52,000
Speaker 1: book is Bill Simmons Book of Basketball.

1489
01:17:52,240 --> 01:17:52,519
Speaker 2: Huh.

1490
01:17:53,280 --> 01:17:53,360
Speaker 3: So.

1491
01:17:53,439 --> 01:17:56,519
Speaker 1: Bill Simmons wrote a book that ranked the top one

1492
01:17:56,560 --> 01:18:00,800
Speaker 1: hundred basketball players. It's again ten years ago of all time,

1493
01:18:01,280 --> 01:18:05,120
Speaker 1: using both stats and his incredible knowledge and judgment, and

1494
01:18:05,200 --> 01:18:07,639
Speaker 1: it is addictive and incredibly fun.

1495
01:18:07,680 --> 01:18:10,720
Speaker 2: So spoiler, was it Jordan or Lebron? Who is he?

1496
01:18:10,880 --> 01:18:13,240
Speaker 1: I'm only up to twenty five, which is Bill Walton,

1497
01:18:13,960 --> 01:18:15,320
Speaker 1: so you know, I don't know yet.

1498
01:18:15,560 --> 01:18:20,160
Speaker 2: And you know ten years ago was Curry really on

1499
01:18:20,200 --> 01:18:20,639
Speaker 2: the list?

1500
01:18:20,800 --> 01:18:23,759
Speaker 1: So early on in the book he had this tiered

1501
01:18:23,800 --> 01:18:26,400
Speaker 1: system and he talked about the players that weren't yet

1502
01:18:26,439 --> 01:18:29,240
Speaker 1: on it, and Curry was mentioned as one he didn't

1503
01:18:29,240 --> 01:18:32,080
Speaker 1: think would get onto the list in a future edition.

1504
01:18:32,240 --> 01:18:35,760
Speaker 2: Hilarious, right, and now he's probably top ten. Right for

1505
01:18:36,040 --> 01:18:40,240
Speaker 2: a fair fair statement. Last two questions, what sort of

1506
01:18:40,320 --> 01:18:43,679
Speaker 2: advice would you give to a recent college graduate interested

1507
01:18:43,680 --> 01:18:49,519
Speaker 2: in a career in either alternate investments, allocation, anything finance related?

1508
01:18:49,600 --> 01:18:51,599
Speaker 1: Yeah, well, the general mice I give And I heard

1509
01:18:51,600 --> 01:18:53,639
Speaker 1: it phrase beautifully by a guy named Eric Resnik, who

1510
01:18:53,720 --> 01:18:56,240
Speaker 1: runs the largest private equity firm for travel and leisure,

1511
01:18:56,760 --> 01:18:59,400
Speaker 1: was recently on our show. He was told early on

1512
01:19:00,280 --> 01:19:05,120
Speaker 1: combined your vocation with your avocation, which is just a

1513
01:19:05,160 --> 01:19:08,599
Speaker 1: thoughtful way of saying to what you love. I think

1514
01:19:08,600 --> 01:19:12,560
Speaker 1: that's general the problem with finance and alternative investments is

1515
01:19:12,600 --> 01:19:15,240
Speaker 1: I would give advice that Howard Marks gives, which is,

1516
01:19:15,240 --> 01:19:17,639
Speaker 1: if you want to have a great career in this space,

1517
01:19:18,160 --> 01:19:19,200
Speaker 1: start thirty years ago.

1518
01:19:21,600 --> 01:19:24,519
Speaker 2: That's great. I love Howard And our final question, what

1519
01:19:24,600 --> 01:19:27,040
Speaker 2: do you know about the world of investing today? You

1520
01:19:27,160 --> 01:19:30,040
Speaker 2: wish you knew twenty five thirty years ago when you

1521
01:19:30,120 --> 01:19:31,160
Speaker 2: were first getting started.

1522
01:19:32,280 --> 01:19:36,040
Speaker 1: I think the importance of people. We're talking about governance

1523
01:19:36,080 --> 01:19:39,360
Speaker 1: and decision making, and it was something that David Swinson

1524
01:19:39,439 --> 01:19:42,719
Speaker 1: taught me early on. But you have to go through

1525
01:19:43,320 --> 01:19:47,479
Speaker 1: people in difficult times, experiencing good and bad behavior in

1526
01:19:47,520 --> 01:19:52,200
Speaker 1: those times to really understand that ultimately active management is

1527
01:19:52,240 --> 01:19:55,120
Speaker 1: a people business. H And yes, you have to have

1528
01:19:55,160 --> 01:19:57,240
Speaker 1: all the investment discipline and all the rigor that goes

1529
01:19:57,280 --> 01:19:59,960
Speaker 1: into that, but they are human beings that are making decisions,

1530
01:20:00,640 --> 01:20:05,479
Speaker 1: and that evaluating people as a frame for how you

1531
01:20:05,520 --> 01:20:07,599
Speaker 1: think about where you want to allocate your capitals probably

1532
01:20:07,640 --> 01:20:09,120
Speaker 1: the single most important thing you can do.

1533
01:20:09,479 --> 01:20:12,599
Speaker 2: Really fascinating stuff. Ted, Thank you for being so generous

1534
01:20:12,640 --> 01:20:15,639
Speaker 2: with your time. We have been speaking with Ted Sids.

1535
01:20:15,720 --> 01:20:19,000
Speaker 2: He is the founder of Capital Allocator and the author

1536
01:20:19,400 --> 01:20:22,840
Speaker 2: of Capital Allocators. How the world's lead money managers Lead

1537
01:20:22,920 --> 01:20:26,760
Speaker 2: and Invest and the host of the Capital Allocators podcast.

1538
01:20:27,520 --> 01:20:30,360
Speaker 2: If you enjoy this conversation, well, be sure and check

1539
01:20:30,400 --> 01:20:34,280
Speaker 2: out any of the previous four hundred and ninety eight

1540
01:20:34,400 --> 01:20:37,760
Speaker 2: podcasts we've done over the past eight years. You can

1541
01:20:37,800 --> 01:20:42,559
Speaker 2: find those at iTunes, Spotify, YouTube, wherever you find your

1542
01:20:42,600 --> 01:20:46,040
Speaker 2: favorite podcast. Sign up for my daily reading list at

1543
01:20:46,120 --> 01:20:48,920
Speaker 2: rid Helts dot com. Follow me on What's Left of

1544
01:20:48,960 --> 01:20:52,840
Speaker 2: Twitter at ripaults. Follow all of the Bloomberg Family of

1545
01:20:52,920 --> 01:20:57,200
Speaker 2: podcasts on Twitter at podcasts. I would be remiss if

1546
01:20:57,240 --> 01:20:59,080
Speaker 2: I did not thank the crack team that helps put

1547
01:20:59,120 --> 01:21:04,280
Speaker 2: these conversations together each week. Justin Milner is my audio engineer.

1548
01:21:04,400 --> 01:21:07,880
Speaker 2: Attika of Albron is my project manager. Sean Russo is

1549
01:21:07,920 --> 01:21:12,040
Speaker 2: my head of research. Paris Wald is my producer. I'm

1550
01:21:12,080 --> 01:21:15,640
Speaker 2: Barry Rutults. You've been listening to Masters in Business on

1551
01:21:15,800 --> 01:21:17,200
Speaker 2: Bloomberg Radio.