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Speaker 1: This is Masters in Business with Barry Ridholtz on Boomberg Radio.

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Speaker 1: This week on the podcast, I have a special guest

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Speaker 1: and this was so much fun. His name is Jeffrey Sherman.

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Speaker 1: He is the I'm gonna make him see I O

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Speaker 1: of Double Line and uh, one of the people who

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Speaker 1: came over from Trust Company of the West with Jeff

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Speaker 1: Gunlock to help set up. He actually is Deputy c

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Speaker 1: i O as well as sitting on a number of

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Speaker 1: different executive management committees UM fixed Income Financial Allocation Committee.

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Speaker 1: He runs a number of farm funds as well as

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Speaker 1: co runs some funds with Jeff Gunlock UH, and is

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Speaker 1: as about as knowledgeable a quants working in the fixed

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Speaker 1: income and equity and commodity space uh as as you'll

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Speaker 1: ever want to meet. UM. We really don't go too

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Speaker 1: deep into the weeds on the wonky quant stuff, but

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Speaker 1: it's really a fascinating, roll up your sleeve sort of conversation.

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Speaker 1: He understands this as well as anybody out in finance.

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Speaker 1: He also hosts his own podcast, which we talked a

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Speaker 1: little bit about. So I found the conversation to be

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Speaker 1: absolutely uh fascinating and intriguing, and I think you will too,

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Speaker 1: so with no further ado, my conversation with Double Lines

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Speaker 1: Other Jeff Jeffrey Sherman. My special guest today is Jeff

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Speaker 1: Sherman of Double Line Capital, where he serves as Deputy

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Speaker 1: Chief Investment Officer UH. The c i O of Double

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Speaker 1: Line is Jeff Gunlock, who coincidentally was the very first

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Speaker 1: broadcast guest on Masters and Business UM. Jeff Sherman, previous

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Speaker 1: to Double Line, worked as a senior VP at Trust

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Speaker 1: Company of the West, where he was a portfolio manager

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Speaker 1: and quant analysts focused on fixed income and real asset portfolios.

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Speaker 1: He has a b s and applied mathematics from the

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Speaker 1: University of Pacific and a master's degree in financial engineering

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Speaker 1: from Claremont Graduate University. He is also a c f

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Speaker 1: A charter holder as well as a financial podcaster. Jeff Sherman,

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Speaker 1: Welcome to Bloomberg. Thanks for having me, Barry. So I

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Speaker 1: have to start with the the education applied mathematics and

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Speaker 1: financial engineering. Did you know you wanted to go into

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Speaker 1: asset management earlier in your life? Not at all, not whatsoever, really,

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Speaker 1: because that would suggest, oh, here's the path to Wall Street.

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Speaker 1: That's right, and um, what happened is is Um. Naturally,

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Speaker 1: I guess I was. I was more inclined towards mathematics

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Speaker 1: along the way. I started off actually as a pure mathematician,

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Speaker 1: which is a lot of abstract math and just trying

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Speaker 1: to prove concepts, a lot of logic. Really, um and uh,

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Speaker 1: although it was okay to me, it just didn't really

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Speaker 1: seem to have a long term path. Obviously, you can

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Speaker 1: be a professor. I mean talking about ring theory and groups.

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Speaker 1: I mean you're already falling asleep. No, I love them. Okay, good,

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Speaker 1: so um, so let's talk deeper about that. Everybody else, Oh,

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Speaker 1: there we go, so we'll transition them. But the idea

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Speaker 1: was the applications of of mathematics. It typically it's applied

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Speaker 1: to a lot of physics, right, and engineering concepts, And um,

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Speaker 1: I was always kind of curious by statistics, and for

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Speaker 1: some reason, I like the probabilition statistics course is a

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Speaker 1: little more and so I'd actually changed my major around

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Speaker 1: the middle of my junior year to become an applied mathematician.

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Speaker 1: But unlike the traditional folks, I didn't use the engineering

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Speaker 1: and physics physics as the application actually used its stats

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Speaker 1: and probability. So, um, you know, I forgot to really

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Speaker 1: apply for a job as I was going through my Yeah, well,

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Speaker 1: you know, you kind of get stuck in that academic

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Speaker 1: lifestyle and so decided to take the g r S

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Speaker 1: and just try to keep going to school. So ended

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Speaker 1: up applying to grad school UM, and ended up down

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Speaker 1: in Florida State, down in Tallahassee and uh, interesting place.

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Speaker 1: UM didn't really have a lot of application towards statistics

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Speaker 1: and probability as you might think of them. They're they're

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Speaker 1: pretty well honed on a meteorological tilt. Uh. There's these

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Speaker 1: things called hurricanes that they study, and they're well known

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Speaker 1: for that. So my application got thrown out the window

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Speaker 1: of statistics, not my application for grad school. But they

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Speaker 1: said everybody learns fluid mechanics here. Um and by the way,

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Speaker 1: here's fifth semester physics. Figure it out, and so um

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Speaker 1: it was doing that along the way. It's kind of late.

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Speaker 1: This was like late ninety nine early two thousand. Realized

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Speaker 1: there are this quand jobs on Wall Street, and there's

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Speaker 1: these programs that actually had a financial tilt and so

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Speaker 1: similar types of equations like um, uh kind of like

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Speaker 1: think in those areas and started taking simulation and things

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Speaker 1: like that, and UH ended up transferring back to Claremont,

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Speaker 1: closer to home, back in California, and UM went from

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Speaker 1: there financial engineering. Speaking of another mathematician, You're working at

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Speaker 1: the Trust Company of the West with a gentleman named

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Speaker 1: Jeff Gunlock. UM, what was that like when you were there?

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Speaker 1: Tell us about about your relationship. Well, Um, it was

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Speaker 1: non existent when I started. UM, it's worked in a

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Speaker 1: different department. And I remember at the time. It's probably

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Speaker 1: a story a lot of people haven't heard. Is Mr

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Speaker 1: Gunlock would go around and put out puzzles of the

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Speaker 1: month and they were always some quirky, very deep in

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Speaker 1: thought puzzle and it was always the rumor was if

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Speaker 1: you could solve it within the month and turned into him,

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Speaker 1: you could get a job in his department. I'm not

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Speaker 1: here to tell you I solved one of those, by

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Speaker 1: the way, UM, but it was always curious to me. UM.

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Speaker 1: You know someone that's kind of challenging folks in the workplace.

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Speaker 1: And obviously as I was, I was working in the

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Speaker 1: risk type of group and kind of the middle office

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Speaker 1: type analyzing things and just seeing kind of tracker of

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Speaker 1: the team and and how the team had some autonomy.

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Speaker 1: It's always something that I wanted to do. Um, and

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Speaker 1: so UM just kind of started hanging around the oaks

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Speaker 1: on the team trying to, uh, you know, get my

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Speaker 1: name known or something that, to try to get in

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Speaker 1: the group. So you never solve one of his puzzles.

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Speaker 1: Negative and then he I don't know if he actually

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Speaker 1: for fairness, I'm not sure if anyone ever did. I

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Speaker 1: believe he probably did, but I'm not sure if anyone

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Speaker 1: ever did and actually got rewarded with that. It could

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Speaker 1: have just been a rumor. But the puzzles were available.

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Speaker 1: I do know that it's an interesting crowdsourcing. They could

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Speaker 1: be puzzles he couldn't solve and say, let's see if

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Speaker 1: we can find someone else who can. Uh. Again, I

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Speaker 1: don't know the answer to that, but you know, again

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Speaker 1: you have to ask him next time you see. I

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Speaker 1: will so so he leaves to launch double line on

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Speaker 1: his own. How did you go about saying, hey, Jeff,

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Speaker 1: I think you need another Jeff in the shop right? Well, Um,

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Speaker 1: you know I was on the team at that point

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Speaker 1: in time. I've been with the team probably at least

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Speaker 1: around five years, four to five years at the time,

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Speaker 1: and Um, it was. It was a very quick kind

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Speaker 1: of movement and a bunch of people on the desk

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Speaker 1: we're talking about, you know, what should we do? And

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Speaker 1: it was a pretty easy decision. I was in my

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Speaker 1: early thirties, Um, and I said, you know, if there's

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Speaker 1: a risk to take, this is the time to do it.

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Speaker 1: One and you know, one of the most respected investors

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Speaker 1: in the world. Why wouldn't you take a risk to

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Speaker 1: join this person on a new venture? And so from

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Speaker 1: that perspective, it's it's almost one of those things people

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Speaker 1: call a no brainer. Obviously there's a little bit of

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Speaker 1: you know, strife and turmoil and internally and again look

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Speaker 1: back and the rest is history. You have a lot

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Speaker 1: of different subject areas you cover your deputy c I, oh,

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Speaker 1: you're on the executive committee. Uh, you're a fund manager.

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Speaker 1: What takes the most of your time? What do you

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Speaker 1: focus on the most? Well, I'll clarify that I don't

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Speaker 1: run the executive Did I say it sounded like tend

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Speaker 1: to give people promotion? You know, Hey, it's good to

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Speaker 1: be here. But that said, um, most of my day,

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Speaker 1: you know, is spent between you know, facing clients, you know,

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Speaker 1: portfolio review, strategy, reviews UM, giving outlooks and forecasts of

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Speaker 1: how we're thinking about the markets UM and obviously you know,

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Speaker 1: coming up with ideas for implementation. So UM our team

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Speaker 1: works on the astilication side, So we're trying to kind

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Speaker 1: of find relative valuation across various sectors of the bond market. UM. Additionally,

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Speaker 1: you know, we run our commodity strategy all quantitatively. Orned

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Speaker 1: my team also helps run the equity products that we

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Speaker 1: have on the UH. It's kind of a blend of

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Speaker 1: an index with some active fixed income management. And so

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Speaker 1: again it's it's UM. It's every day is different, but

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Speaker 1: that's what makes it interesting, right, It's UM. You don't

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Speaker 1: come in and do the same thing day and day out. UM.

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Speaker 1: And it's I always viewed as a problem solving exercise, right, UH.

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Speaker 1: The ideas you're trying to find, you know, inefficiencies in

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Speaker 1: the markets, something that looks attractive, perhaps something that people

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Speaker 1: are missing in the puzzle, and more importantly, trying to

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Speaker 1: poke holes in what we own today. Right. So that's

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Speaker 1: a that's a big part of it, is that are

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Speaker 1: we missing some risk out there? Obviously the exogenous ones

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Speaker 1: you can ever figure out to after the fact, but

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Speaker 1: It's also are we are we getting lulled into, you know,

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Speaker 1: an environment like today which is complacent, low volatility, not

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Speaker 1: much going on? UM, Are we being lulled to sleep

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Speaker 1: as well? And is there something we can do in

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Speaker 1: our portfolios to help kind of offset that, or you know,

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Speaker 1: try to think about something that's UM again, somewhat exogenous

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Speaker 1: to the process today. Here's a rumor that I just

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Speaker 1: love Bob Schiller visits Double Lines Los Angeles office and

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Speaker 1: more or less starts pitching Cape as a way to

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Speaker 1: manage equities more safely, and then somehow this becomes a

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Speaker 1: portfolio How how exaggerated? Is that there's some truth in it? Um?

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Speaker 1: The facts are that we don't want fake news right,

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Speaker 1: want facts right. The facts are that Professor Schiller was

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Speaker 1: in our office and Professor Schiller was talking about his

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Speaker 1: Cape Index family of the products he had partnered with

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Speaker 1: Barclays to work on UM. And I don't know if

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Speaker 1: he pitched as a more safe way or that he

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Speaker 1: was actually there truly pitching the product, because that's not

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Speaker 1: that's not really Professor Schiller's style. You know. Yeah, he's

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Speaker 1: he's very humble and he likes to talk about ideas,

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Speaker 1: But I don't believe it was a full blown pitch.

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Speaker 1: The bankers with them, well, I think perhaps they were

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Speaker 1: pitching um. And the question became, okay, this is great.

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Speaker 1: We run a lot of fixed income assets, we have

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Speaker 1: a macro fund, we have a hedge fund that we

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Speaker 1: do things where we could body these types of products.

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Speaker 1: But so do you want us to just trade this

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Speaker 1: or what's the idea here? So from there what we

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Speaker 1: ended up doing was taking a look at the at

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Speaker 1: the family in disease and thinking about is there a

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Speaker 1: merit here? And at first, looking at it cursory glance, think,

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Speaker 1: you know, just another value product, you know, So okay, great,

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Speaker 1: good job, you know, yeah, using like a cape cape ratio,

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Speaker 1: which is a tenure price. Duran's racist And because the

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Speaker 1: longer time you got inflation adjust of course, full cycle

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Speaker 1: blah blah blah. Well, who knows if it's a full

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Speaker 1: cycle anymore? Here? Where are you're eight? You know? Will

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Speaker 1: we uh? You know the low? I know, I know

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Speaker 1: you're about that right the bull market starts with the

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Speaker 1: new high. I get it, um, But that being said,

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Speaker 1: I've read, I've I've read enough and heard enough about it.

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Speaker 1: But what we did is started to do some kind

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Speaker 1: of statistical work on it, look at kind of factory

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Speaker 1: decomposition and things, and I gotta The story I like

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Speaker 1: to tell is that the first blush through, I just said,

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Speaker 1: this is wrong. These these results make no sense. You

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Speaker 1: still have like residual return of alpha in there after

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Speaker 1: this process of adjusting for factors. So in ways I'm

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Speaker 1: saying there's something to this another when you say it's wrong, Hey,

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Speaker 1: this is identifying an inefficiency that you hadn't previously considered. However,

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Speaker 1: you don't know me well enough, Barry the first thing,

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Speaker 1: I say, that's gonna be wrong, Right, it's gotta be wrong,

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Speaker 1: um and so um. So crank through it again. And

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Speaker 1: then the next step, after we see it again, go

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Speaker 1: for monthly to daily, start looking at different time periods

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Speaker 1: like go, now, give me the data set. I want

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Speaker 1: to make sure. Let me look through how you're doing it,

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Speaker 1: and yeah, you're absolutely correct. It's that there seems to

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Speaker 1: be something beyond what's in the factors. And there's nothing

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Speaker 1: wrong with factory decomposition or factory portflows. They're great. But

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Speaker 1: if everybody can deliver to you and it's commoditized, what's

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Speaker 1: my edge, right. So well, we ended up finding out

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Speaker 1: there is that this this excess return seemed to exist,

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Speaker 1: and we started going through regime changes and look at

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Speaker 1: different rate environments and different growth and recessionary areas. What

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Speaker 1: we found is it seems to be relatively robust. And

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Speaker 1: so now the big question becomes, we have this equity

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Speaker 1: inducts that we've seen that appears to deliver something different

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Speaker 1: in the value space or even just in core large

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Speaker 1: cap equity in the US. What do you do with it? Right?

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Speaker 1: Double Line historically have been known for being more fixed

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Speaker 1: income oriented, So what do we do with him? And

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Speaker 1: so first thing I think about is why not do

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Speaker 1: it as an overlay? Right? So, an overlay means that

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Speaker 1: you can get this exposure through a derivative like a swap,

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Speaker 1: and you can put that on top of let's say

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Speaker 1: a treasure report foil that will replicate the total return

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Speaker 1: um and you can deliver that. But that's no fun,

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Speaker 1: that's just an index business um. And if you're not familiar,

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Speaker 1: we run about a hundred and seventeen billion dollars of

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Speaker 1: actively managed product. So from the standpoint of what to

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Speaker 1: do with it, why not be a little active with

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Speaker 1: that treasury PORTFOLIL, and why not run things beyond treasuries.

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Speaker 1: Why not do what we do well and try to

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Speaker 1: build a diversified kind of lower risk fixed income probably

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Speaker 1: don't look like the traditional intermediate term bond funds, but

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Speaker 1: run something that'll will take a little bit of interest risk,

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Speaker 1: take a little bit of credit risk, and use our

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Speaker 1: macro forecasting to blend that together for the right environment.

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Speaker 1: And if you do it right, you can add let's

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Speaker 1: call it, a couple hundred basis points a year over

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Speaker 1: the index. So if you have a good product in

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Speaker 1: a process that you believe in from the equity side,

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Speaker 1: which UM really resonated with us, so you buy the

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Speaker 1: four cheapest s and P five hundred sectors as measured

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Speaker 1: by the ten year cape not precisely. So there's a

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Speaker 1: couple of things different there. One is UM. Instead of

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Speaker 1: using just the cap ratio to identify the value, think

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Speaker 1: about like for instance, tech, the technology sector, and think

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Speaker 1: about utilities. Historically, utilities have always really traded a lower

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Speaker 1: multiple than technology, right, and then there's reasons for that.

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Speaker 1: Vall Um. You know, highly regulated industries versus high flying

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Speaker 1: growthy stocks. David, Yeah, all the traditional kind of metrics

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Speaker 1: you would think for that. So if you just used

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Speaker 1: the cap ratio, you would always buy utilities, for instance, right,

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Speaker 1: because it would be one of those lower valuation sectors

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Speaker 1: as at least in a historical context, and that would

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Speaker 1: introduce bias to the portfolio. So to normalize this, or

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Speaker 1: to try to standardize it, what you do is you

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Speaker 1: compare each sector's cap ratio to its own historical average.

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Speaker 1: So think about it's normalizing it for its own trading range.

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Speaker 1: Now you have a basis to compare them. So in

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Speaker 1: other words, you're picking the four least expensive sectors relative

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Speaker 1: to their own history. You're almost there getting and thus far,

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Speaker 1: that's all the information you have that is correct um.

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Speaker 1: So you rank these each month, and you're gonna pick

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Speaker 1: the bottom five. And then of those five, which is

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Speaker 1: the cheapest Because it's valuation, you want to avoid value traps,

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Speaker 1: cheap getting cheaper, right, falling knife, all those you know,

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Speaker 1: sexy adages we put to the to the to that

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Speaker 1: process which you do is apply momentum. So the five sectors,

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Speaker 1: whicheveryone is the worst performer, you throw it away. So

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Speaker 1: think about you're sitting in two thousand fourteen energy is

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Speaker 1: extremely cheap on a on a multiple basis, especially real

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Speaker 1: to its own history on this CAPE basis. And all

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Speaker 1: of a sudden, oil starts declining in the middle of

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Speaker 1: the second half of fourteen and by a couple of

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Speaker 1: months because of such negative performance in the equities, it

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Speaker 1: kicks it out of the index. So you're left with

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Speaker 1: the other four. Well, this actually would have saved you

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Speaker 1: if you if you just only focus on the five,

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Speaker 1: it saves you approximately six hundred basis points PERU over

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Speaker 1: the next couple of years. Right, So that's just when

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Speaker 1: those CAPE plus a factor plus plus a factor. But

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Speaker 1: you're not trying to emphasize the factor, right, So I

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Speaker 1: like to say that we're not factor investors. The factors

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Speaker 1: are a result of the process. And who came up

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Speaker 1: with this really interesting way to use CAPE as a

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Speaker 1: basis of creating an equity like product. Not me. First

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Speaker 1: of all, I'm not going to take credit for that,

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Speaker 1: even though you want to give me a promotion on No, no, no,

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Speaker 1: not gonna do that. But this was a joint effort

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Speaker 1: between Professor Schiller and the folks at Barclays. So after

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Speaker 1: I think it was in early two thousand and ten,

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Speaker 1: they started getting together working on this project to try

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Speaker 1: to use the CAPE ratio to do something investable. You know,

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Speaker 1: there's all these critics out there about the KPE ratio. Oh,

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Speaker 1: it doesn't work right, Uh, it's been above average for

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Speaker 1: a long period. Well, you can't just use it as

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Speaker 1: a buy or cell decision at face value. That's why

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Speaker 1: people say it doesn't work, but they're really not looking

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Speaker 1: at it correctly. I would agree with that, and I

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Speaker 1: would agree that what what is KPE? It is a

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Speaker 1: valuation metric? What do evaluation metrics to They don't tell

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Speaker 1: you when to time the market, They tell you how

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Speaker 1: to think about prospective returns, right, And that's exactly what

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Speaker 1: the cap ratio does. When it's above average, it says

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Speaker 1: you should expect below average returns. Wow, that's not very hard.

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Speaker 1: But people want to say, oh, it's at this level,

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Speaker 1: the market hasn't crashed. It's stupid, right, Um, But if

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Speaker 1: you look at any valuation metric today, they are and

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Speaker 1: apply it to the US equity market, at least as

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Speaker 1: many as I'm aware of, They all say the market

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Speaker 1: is overvalued, But it doesn't say it's gonna crash. But

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Speaker 1: for some reason people get uh fascinated by this cape

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Speaker 1: ratio and just want to attack it. And again it

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Speaker 1: does have, um, some good credibility of of of talking

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Speaker 1: about forward looking returns. In fact, it has one of

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Speaker 1: the highest our squares of the metrics out there. However,

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Speaker 1: it doesn't say when to get out of the market.

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Speaker 1: I'm fond of reminding people that stocks were cheap in

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Speaker 1: the seventies and they did poorly, and they were expensive

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Speaker 1: in the nineties and they did really well. Right well, Um,

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Speaker 1: And you know the level we see on the KP

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Speaker 1: ratio at the US equity market day large cap U

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Speaker 1: has had. This is the third time we've been here,

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Speaker 1: and both times, once it's hit this level, at some

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Speaker 1: point it collapsed. You you had the great depression which

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Speaker 1: you lost about between friends. Yeah, especially if you compounded

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Speaker 1: how it doesn't take it doesn't take much but five

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Speaker 1: to get back to break even, that is, and then

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Speaker 1: getting your bowl market as you'd like to say, right, um.

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Speaker 1: But then the second time was in the technology kind

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Speaker 1: of boom and it went up like another before it

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Speaker 1: ultimately did crash. Putting us all together, there's nothing that said,

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Speaker 1: you know, we have two data points not very robust

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Speaker 1: statistically set right, but it does, you know, it does

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Speaker 1: strike some fear. But you know, if you want to

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Speaker 1: get bullish, I just think of the Japanese stocks in

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Speaker 1: the late eighties. I mean they traded with a high

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Speaker 1: ninety cape multiple. So I mean, look, we've got in

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Speaker 1: a couple percent to run without even earnings growing if

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Speaker 1: you believe in the Japanese model. Let's talk a little

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Speaker 1: bit about the two Jeff's, which is how you and

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Speaker 1: the other Jeff. Jeff Gunlock is known. Uh, he has

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Speaker 1: a pretty wild origin story. He's a board drummer in

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Speaker 1: hair bands, watching the television show Lifestyles are the Rich

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Speaker 1: and Famous. When he decides he's tired of being broke

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Speaker 1: and takes a phone book and just literally starts reaching

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Speaker 1: out to finance companies. More or less, he looked at

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Speaker 1: the word investment banker. That's right, And it wasn't in

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Speaker 1: the Yellow Pages. It was not in the Yellow Pages. Um,

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Speaker 1: what was your origin story like? Uh? Nothing dramatic like that. Um.

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Speaker 1: After I was in grad school and obviously one of

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Speaker 1: the things you have to do as an internship, you know,

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Speaker 1: to get some hands on experience. And I did my

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Speaker 1: internship at a place called Trust Company in the West

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Speaker 1: and so as an intern there. UM I accepted a

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Speaker 1: full time position. Why I finished up the last piece

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Speaker 1: of my graduate work. So unfortunately, nothing really sexy like

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Speaker 1: using the phone book at the time. I guess the

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Speaker 1: if you could, if you want to get nostalgic the

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Speaker 1: way I got the internship. UM, I actually accepted an

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Speaker 1: internship back at Florida Power and Light down in West

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Speaker 1: Palm Beach. I knew some people there from my Florida

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Speaker 1: State days, and so looking for an internship, I tried

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Speaker 1: some local companies and then getting calls back, and I

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Speaker 1: drove my Ford Ranger pick up you know, the two

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Speaker 1: seat or not the extended cat and you can see

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Speaker 1: I'm you know, I'm about six three, not the most

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Speaker 1: comfortable ride cross country, UM in that four cylinder beasts

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Speaker 1: that I had there, and drove to West Palm Beach

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Speaker 1: from California. From California, I was because like a week

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Speaker 1: driving four days, four days. I mean, look, there's not

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Speaker 1: a lot of money to go around internships. You get

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Speaker 1: there as soon as you can. What those motels are

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Speaker 1: expensive across the country at like thirty bucks a night.

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Speaker 1: So anyway, I get there and why I say it's

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Speaker 1: a little nostalgic. Is I get a call from my

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Speaker 1: roommate back in l A who says, Hey, it's this

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Speaker 1: guy from tc W who left you a voicemail, you know,

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Speaker 1: on the answering machine, right, this isn't cell phone days. Um,

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Speaker 1: and so, UM, they're talking about interviewing you for internships.

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Speaker 1: I said, great, I'll call them. So I ended up

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Speaker 1: actually calling them. UH, did the interview, and at the

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Speaker 1: end of it, I was like, you know, kind of

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Speaker 1: what's your time frame, A couple of weeks or something

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Speaker 1: like that, I said, I started, I started a job

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Speaker 1: in like four days. Um, but if you guys can

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Speaker 1: offer me the internship, I'll come back. So I had

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Speaker 1: to meet with someone else and um, fortunately they did,

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Speaker 1: and I made the trek back three days this time, uh,

404
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Speaker 1: because again no funds are coming into so those are

405
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Speaker 1: like fourteen fifteen hour days. But that's how I came

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Speaker 1: back to start my internship. That's a pretty good origin story,

407
00:21:37,119 --> 00:21:39,760
Speaker 1: that one. That's not terrible. That's that's an interesting Uh.

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Speaker 1: Cross country and back in a week essentially, I mean

409
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Speaker 1: essentially like five thousand miles over the course of a week,

410
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Speaker 1: week and a half. Um, not the most pleasant experience.

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Speaker 1: There was a lot of pit stops along the way.

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Speaker 1: I think I was doing, you know, because of my

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Speaker 1: legs aching no more than like ninety minutes. I was

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Speaker 1: getting getting up in a corner tank at gas each

415
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Speaker 1: time just to do something. Um that's uh. You know,

416
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Speaker 1: you gotta have a good playlist on your CDs. So

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Speaker 1: the other Jeff, which is what people used to call you,

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Speaker 1: the primary Jeff, is Gunlock. What'sh it like working with

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Speaker 1: a guy who is a force of nature like him? Um,

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Speaker 1: it's what I know. You know, Um, this this is

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Speaker 1: the team I've worked with the majority of my career.

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Speaker 1: I've been around this team, you know, in my entire

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Speaker 1: formidable years of an as being an investor, and so

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Speaker 1: you know, he's human like anybody else. Um, you know,

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Speaker 1: we we collaborate, we all work together. Um. He fosters

426
00:22:32,960 --> 00:22:35,720
Speaker 1: a very great environment. Um you think about you know,

427
00:22:35,720 --> 00:22:39,439
Speaker 1: the amount of talent we have surrounding from our emerging markets.

428
00:22:39,440 --> 00:22:42,920
Speaker 1: Team are loan team are high yield folks are mortgage people.

429
00:22:43,200 --> 00:22:45,000
Speaker 1: You know a BS we I mean we we span

430
00:22:45,160 --> 00:22:48,199
Speaker 1: the entire universe and he provides folks with a lot

431
00:22:48,240 --> 00:22:52,600
Speaker 1: of autonomy you know, UM foster growth, UM constructive criticism

432
00:22:52,600 --> 00:22:55,919
Speaker 1: when necessary. But I think one thing that should be

433
00:22:55,960 --> 00:22:58,240
Speaker 1: noted is he he is very a very good listener.

434
00:22:58,520 --> 00:23:00,879
Speaker 1: You know, if there's ideas, there's different ways to do something,

435
00:23:00,920 --> 00:23:03,320
Speaker 1: he's always open to them. But if they're wrong, he'll

436
00:23:03,320 --> 00:23:06,040
Speaker 1: tell you. You know. So it's it's a fair relationship.

437
00:23:06,080 --> 00:23:09,040
Speaker 1: And I think that's why you see very limited turnover

438
00:23:09,119 --> 00:23:11,639
Speaker 1: the investment staff is it's it's a good environment. What

439
00:23:11,680 --> 00:23:14,040
Speaker 1: do you think when he goes on TV and says

440
00:23:14,280 --> 00:23:16,960
Speaker 1: sell everything? How how do you guys respond to that

441
00:23:17,400 --> 00:23:20,480
Speaker 1: school or what happens? Well, my team's office, we don't

442
00:23:20,520 --> 00:23:22,439
Speaker 1: sit on the trading desk with everybody else. We're kind

443
00:23:22,440 --> 00:23:25,080
Speaker 1: of removed. I kind of like that low close knit

444
00:23:25,119 --> 00:23:27,240
Speaker 1: with my team. But our team is right outside the

445
00:23:27,240 --> 00:23:30,960
Speaker 1: media room. So we're going, that's happening right there, right now, now,

446
00:23:31,160 --> 00:23:34,320
Speaker 1: sell everything. You know. I'm not gonna say that he's

447
00:23:34,320 --> 00:23:36,600
Speaker 1: always hyperbolic, but I think he's trying to get a

448
00:23:36,640 --> 00:23:39,280
Speaker 1: point across. And what he's saying is that at the time,

449
00:23:39,359 --> 00:23:42,520
Speaker 1: this was right around Brexit, where everyone is telling you

450
00:23:42,560 --> 00:23:45,480
Speaker 1: that this is right prior to Brexit, that disinflation is

451
00:23:45,520 --> 00:23:48,760
Speaker 1: taking over GDPs collapsing, we're gonna be stuck in this

452
00:23:49,200 --> 00:23:52,159
Speaker 1: highly levered economy with no growth. I mean, it was

453
00:23:52,160 --> 00:23:55,239
Speaker 1: just very negative time. And the idea is that we

454
00:23:55,280 --> 00:23:58,159
Speaker 1: can't break really new lows on the tenure. These markets

455
00:23:58,200 --> 00:24:00,359
Speaker 1: aren't responding in a way that's consisting it with the

456
00:24:00,440 --> 00:24:03,400
Speaker 1: message and to sell everything is that if you feel

457
00:24:03,440 --> 00:24:05,440
Speaker 1: that you have too much risk on and you're nervous

458
00:24:05,800 --> 00:24:08,479
Speaker 1: by the phrase sell everything, Barry, what that means is

459
00:24:08,520 --> 00:24:10,960
Speaker 1: you probably own too much risk. And that was really

460
00:24:11,000 --> 00:24:14,119
Speaker 1: the message behind it. Um. Again, clients don't take it

461
00:24:14,160 --> 00:24:17,919
Speaker 1: as well as that. They're like, should I just sell everything? Um?

462
00:24:17,960 --> 00:24:20,520
Speaker 1: But it's like you tell people when you have a

463
00:24:20,560 --> 00:24:22,639
Speaker 1: great market going on, like we have an the equity market,

464
00:24:22,800 --> 00:24:25,560
Speaker 1: people get extremely nervous and they want to sell everything,

465
00:24:25,800 --> 00:24:28,920
Speaker 1: sell a piece, monetize something. Um. But you gotta be

466
00:24:28,960 --> 00:24:30,840
Speaker 1: able to get back in the game too, So let's

467
00:24:30,840 --> 00:24:34,520
Speaker 1: sell everything mantra. I think I'm not gonna call it hyperbolic,

468
00:24:34,600 --> 00:24:36,840
Speaker 1: but it's meant to be there to try to drive

469
00:24:36,880 --> 00:24:38,879
Speaker 1: a message home is that, look, there's a lot of

470
00:24:38,960 --> 00:24:41,800
Speaker 1: risk out there you're not seeing reduce your risk levels,

471
00:24:42,080 --> 00:24:44,080
Speaker 1: and anytime you sell something, you have to have a

472
00:24:44,160 --> 00:24:46,679
Speaker 1: line in the sands to get back in. I assume

473
00:24:46,720 --> 00:24:49,720
Speaker 1: it's exactly right. And we were really focused on the

474
00:24:49,720 --> 00:24:53,520
Speaker 1: bond market, and the thing wasn't just sell everything, you know,

475
00:24:53,840 --> 00:24:56,600
Speaker 1: it was really related to an art piece too, where

476
00:24:56,600 --> 00:24:59,440
Speaker 1: it was sell the house, sell the wife, sell the kids.

477
00:25:00,040 --> 00:25:01,720
Speaker 1: And so I think he used that and he said

478
00:25:01,720 --> 00:25:03,840
Speaker 1: just sell everything. Uh. And I think he used it

479
00:25:03,840 --> 00:25:07,000
Speaker 1: on a webcast a few few days earlier. And you know,

480
00:25:07,040 --> 00:25:09,240
Speaker 1: we we heard him staying it around the office. Didn't

481
00:25:09,280 --> 00:25:11,359
Speaker 1: think it'd really go on TV and say it, but

482
00:25:11,400 --> 00:25:13,720
Speaker 1: he did. Um. And you know, look he was right

483
00:25:13,800 --> 00:25:15,159
Speaker 1: at the time. I mean there was a lot of

484
00:25:15,240 --> 00:25:18,240
Speaker 1: risk brewing, specifically in the blonde market and you'll shut

485
00:25:18,280 --> 00:25:21,000
Speaker 1: up pretty quickly post Brexit, and so um there was

486
00:25:21,000 --> 00:25:23,240
Speaker 1: the entry point to you know, we weren't really doing

487
00:25:23,240 --> 00:25:24,720
Speaker 1: a lot of trains that time. We just hated the

488
00:25:24,720 --> 00:25:26,960
Speaker 1: price levels and so it was time to start putting

489
00:25:27,000 --> 00:25:29,879
Speaker 1: things back to work. So it's being patient to making

490
00:25:29,880 --> 00:25:32,800
Speaker 1: sure that you don't stray, don't let the central bankers

491
00:25:32,840 --> 00:25:34,919
Speaker 1: force you into the box in the positions you're not

492
00:25:34,960 --> 00:25:37,880
Speaker 1: comfortable with. UM, don't don't have the fomo, the fear

493
00:25:37,920 --> 00:25:40,520
Speaker 1: of missing out with everybody else, and you know, make

494
00:25:40,520 --> 00:25:43,640
Speaker 1: sure you're you're investing for your philosophy and what you're

495
00:25:43,640 --> 00:25:46,119
Speaker 1: trying to achieve. And that's really what it is, is

496
00:25:46,160 --> 00:25:48,600
Speaker 1: that people have gotten accustomed to taking a lot of

497
00:25:48,720 --> 00:25:51,760
Speaker 1: risk UM that's really not in their normal zones. I

498
00:25:51,760 --> 00:25:54,719
Speaker 1: would say, let's talk a little bit about stocks and

499
00:25:54,720 --> 00:25:59,120
Speaker 1: bonds and commodities, which is telling us where we are

500
00:25:59,119 --> 00:26:02,080
Speaker 1: in the financials now. Well, I think each of those

501
00:26:02,119 --> 00:26:05,240
Speaker 1: three sectors of the market, those asset classes have a

502
00:26:05,240 --> 00:26:08,600
Speaker 1: different time perspective UM. And I think of the bond

503
00:26:08,600 --> 00:26:12,280
Speaker 1: market as being more contemporaneous. It's digesting macro day as

504
00:26:12,280 --> 00:26:16,280
Speaker 1: it comes through. It tells us essentially where we are currently. Uh.

505
00:26:16,320 --> 00:26:20,160
Speaker 1: The equity market, obviously, the forward discounting mechanism you think

506
00:26:20,160 --> 00:26:23,400
Speaker 1: about when we're in the midst of a recession, Equity

507
00:26:23,400 --> 00:26:26,359
Speaker 1: prices tend to be rising somewhat um when you're in

508
00:26:26,400 --> 00:26:28,640
Speaker 1: the middle to the back end of the recession, as

509
00:26:28,640 --> 00:26:31,600
Speaker 1: it's thinking about the prospects looking forward um. And then

510
00:26:32,240 --> 00:26:34,399
Speaker 1: we call commodities the more of the laggard. They actually

511
00:26:34,400 --> 00:26:36,879
Speaker 1: tell you what has happened, uh. And the reason for

512
00:26:36,960 --> 00:26:39,679
Speaker 1: that commodity is being on that kind of backward looking

513
00:26:39,720 --> 00:26:43,320
Speaker 1: thing is because you're talking about already have consuming, already

514
00:26:43,320 --> 00:26:46,960
Speaker 1: have consumed uh, the commodity of itself, and so you

515
00:26:46,960 --> 00:26:48,399
Speaker 1: you kind of see this forward looking to it, the

516
00:26:48,400 --> 00:26:52,000
Speaker 1: supply demanding balance gets out of whack and so UM,

517
00:26:52,040 --> 00:26:54,840
Speaker 1: they all tell you different things, except or they have

518
00:26:54,880 --> 00:26:58,119
Speaker 1: different time horizons. Except right now you're getting a little

519
00:26:58,160 --> 00:27:03,080
Speaker 1: contradictory efference between UM these markets. And in fact, with

520
00:27:03,280 --> 00:27:06,280
Speaker 1: the commodity story, what you've seen is it's been based

521
00:27:06,320 --> 00:27:09,680
Speaker 1: on a lot of growth, uh specifically industrial metals very

522
00:27:09,880 --> 00:27:12,119
Speaker 1: very strong this year. So let me push back on

523
00:27:12,160 --> 00:27:15,360
Speaker 1: you the immediate response on commodities. I hear from traders

524
00:27:15,400 --> 00:27:18,000
Speaker 1: all the time, Oh, it's a weak dollar story. Well,

525
00:27:18,080 --> 00:27:20,360
Speaker 1: you know the dollar has been weak, but if eight

526
00:27:20,359 --> 00:27:22,920
Speaker 1: percent is going to spike, you know, industrial mother's prices,

527
00:27:24,200 --> 00:27:26,600
Speaker 1: I think there's a little disconnect the UM. So the

528
00:27:26,600 --> 00:27:28,840
Speaker 1: strength of the dollar is not gonna pull if we

529
00:27:28,840 --> 00:27:31,359
Speaker 1: we rallied back to you know, the early two thousand

530
00:27:31,400 --> 00:27:33,800
Speaker 1: seventeen levels, I don't think it's gonna pull down. UM.

531
00:27:34,040 --> 00:27:37,440
Speaker 1: You know industrial metal prices, copper nickels specifically UM and

532
00:27:37,480 --> 00:27:40,360
Speaker 1: in that manner to to reset those prices. So UM,

533
00:27:40,400 --> 00:27:42,760
Speaker 1: it's a good story, um, but we'll keep it as

534
00:27:42,760 --> 00:27:46,320
Speaker 1: a narrative that's not necessarily factually correct. What about the

535
00:27:46,320 --> 00:27:49,159
Speaker 1: flattening yield curve. I keep hearing people say, you know,

536
00:27:49,240 --> 00:27:51,639
Speaker 1: this yield curve is flattening, and that's a just a

537
00:27:51,720 --> 00:27:54,560
Speaker 1: recession is not that far off, that's right. But they

538
00:27:54,640 --> 00:27:56,720
Speaker 1: when they pull you the chart out, they start either

539
00:27:56,760 --> 00:28:00,280
Speaker 1: in two thousand seventeen or they go back to really

540
00:28:00,320 --> 00:28:02,360
Speaker 1: December of thirteen, at the end of the Taper tantrum,

541
00:28:02,480 --> 00:28:05,199
Speaker 1: remember the Taper tantrum, although not December. If you go

542
00:28:05,280 --> 00:28:07,720
Speaker 1: back time, the peak what the tenure kind of close

543
00:28:07,800 --> 00:28:09,879
Speaker 1: at three oh two, and what we're two is at

544
00:28:09,880 --> 00:28:12,480
Speaker 1: that time like thirty basis points, right, I mean massively

545
00:28:12,520 --> 00:28:15,120
Speaker 1: steep curve. Um. But if you actually pull the data

546
00:28:15,160 --> 00:28:18,600
Speaker 1: set back respect history, um, what you see is the

547
00:28:18,640 --> 00:28:21,040
Speaker 1: average experiences and you know kind of the high ninety

548
00:28:21,040 --> 00:28:24,560
Speaker 1: basis points, like nineties seven basis points average, kind of

549
00:28:24,600 --> 00:28:27,760
Speaker 1: using monthly data. The shape between two twos and tens. Yeah,

550
00:28:27,760 --> 00:28:29,879
Speaker 1: it's actually a differential between ten and the tube. We

551
00:28:29,960 --> 00:28:32,880
Speaker 1: call it two s tens um. But today yeah, yeah,

552
00:28:32,920 --> 00:28:35,439
Speaker 1: you're sitting in the mid seventies. UM. But that's not

553
00:28:35,480 --> 00:28:38,760
Speaker 1: a recession indicator. In fact, we have some charts we

554
00:28:38,880 --> 00:28:41,360
Speaker 1: use in a lot of our webcast UM that we

555
00:28:41,480 --> 00:28:44,880
Speaker 1: show that this is an endemic of a FED tightening cycle,

556
00:28:45,200 --> 00:28:47,720
Speaker 1: and so when the FED tightens, the yield curve tends

557
00:28:47,800 --> 00:28:51,200
Speaker 1: to flatten. UM. Where people get fearful is that if

558
00:28:51,240 --> 00:28:53,760
Speaker 1: the yield curve inverts at the end of that Right,

559
00:28:53,760 --> 00:28:56,440
Speaker 1: and so I hear I read a lot about oh,

560
00:28:56,520 --> 00:29:00,520
Speaker 1: this is portending recession, recession, but it's barely below average

561
00:29:01,000 --> 00:29:02,840
Speaker 1: to see a little bit this flatting could take place.

562
00:29:02,840 --> 00:29:05,720
Speaker 1: But what about the gross story, Barry? What about the

563
00:29:05,760 --> 00:29:08,320
Speaker 1: idea that you know we're growing on a nominal basis

564
00:29:08,360 --> 00:29:11,440
Speaker 1: in the four handles, right, I real GDP is about

565
00:29:11,440 --> 00:29:13,920
Speaker 1: two point three percent on a year over year basis.

566
00:29:14,120 --> 00:29:18,400
Speaker 1: We've been growing in the low two since the financial crisis. UM,

567
00:29:18,440 --> 00:29:20,920
Speaker 1: And you have this inflation print. And if Camani has

568
00:29:20,920 --> 00:29:22,800
Speaker 1: actually put you on the verge of getting a little

569
00:29:22,800 --> 00:29:26,280
Speaker 1: more inflation system, perhaps the yeld curve actually does steep

570
00:29:26,280 --> 00:29:28,280
Speaker 1: in a little bit. So we'll have to see kind

571
00:29:28,320 --> 00:29:30,640
Speaker 1: of the inflation side, because the back end of the

572
00:29:30,640 --> 00:29:33,360
Speaker 1: curve is gonna be priced closer to nominal GDP and

573
00:29:33,400 --> 00:29:35,880
Speaker 1: we haven't been talked about the FEDS unwinding of their

574
00:29:35,880 --> 00:29:38,120
Speaker 1: balance So let's talk a little bit about the FED

575
00:29:38,240 --> 00:29:41,320
Speaker 1: unwanting their balance sheet. I keep, by the way, every

576
00:29:41,320 --> 00:29:43,960
Speaker 1: time I reference they said, I hear trading and say,

577
00:29:44,280 --> 00:29:47,320
Speaker 1: you know the rumors that bounce around desks. One of

578
00:29:47,320 --> 00:29:50,120
Speaker 1: the things we hear is, hey, you know, the Fed

579
00:29:50,240 --> 00:29:53,600
Speaker 1: is behind the curve. They should have tightened much further already.

580
00:29:53,680 --> 00:29:55,680
Speaker 1: What what are your thoughts on that? Well, if you

581
00:29:55,720 --> 00:29:58,120
Speaker 1: want a recession, yes they shouldn't. They should have tightened

582
00:29:58,160 --> 00:30:01,320
Speaker 1: sooner um. But the behind the curve is garbage. I mean,

583
00:30:01,800 --> 00:30:05,560
Speaker 1: the fact that we can't print a two handle inflation consistently.

584
00:30:05,960 --> 00:30:08,200
Speaker 1: The fact that we can't print a to handle inflation

585
00:30:08,280 --> 00:30:12,760
Speaker 1: print consistently. It really just destroys that thesis. Yes, unemployment

586
00:30:12,800 --> 00:30:15,560
Speaker 1: is low, but there's no wage inflation behind it. Um.

587
00:30:15,600 --> 00:30:18,040
Speaker 1: People use the hurricane spike at the you know, the

588
00:30:18,120 --> 00:30:20,440
Speaker 1: two point nine percent average hourly growth a couple of

589
00:30:20,480 --> 00:30:24,560
Speaker 1: months back, the month post hurrican, the hurricanes that it was,

590
00:30:24,720 --> 00:30:26,520
Speaker 1: Oh my gosh, here it comes, here, it comes. It's

591
00:30:26,520 --> 00:30:28,760
Speaker 1: revised down a little bit. The next print to five.

592
00:30:29,080 --> 00:30:30,760
Speaker 1: We're back in the in the middle of the range.

593
00:30:31,160 --> 00:30:34,120
Speaker 1: And so the idea that the Feds behind the curve,

594
00:30:34,440 --> 00:30:36,880
Speaker 1: I think once again it's just a myth. The Fed

595
00:30:37,000 --> 00:30:39,400
Speaker 1: is pushed this year. I mean they've they've raised race twice.

596
00:30:39,440 --> 00:30:42,480
Speaker 1: They're on their path to third the third hike. And

597
00:30:42,760 --> 00:30:45,200
Speaker 1: you know what you've seen though, is because it's put

598
00:30:45,200 --> 00:30:47,120
Speaker 1: pressure on the front of the curve, which you know,

599
00:30:47,240 --> 00:30:50,000
Speaker 1: the FED funds ties into live or prime all those rates,

600
00:30:50,320 --> 00:30:53,560
Speaker 1: which you've actually done is constrict some parts of the consumer.

601
00:30:53,840 --> 00:30:56,320
Speaker 1: When they talk about credit cards, loans that are tied

602
00:30:56,360 --> 00:30:58,640
Speaker 1: on the front end of the curve. Almost everything outside

603
00:30:58,640 --> 00:31:01,680
Speaker 1: of housing is tied to war right or some derivative

604
00:31:01,720 --> 00:31:05,160
Speaker 1: of via prime rate. So you've actually seen some constriction

605
00:31:05,240 --> 00:31:07,600
Speaker 1: and consumer spending. Um. So it's a it's a little

606
00:31:07,640 --> 00:31:10,280
Speaker 1: bit strange the bond market. You know, if you talk

607
00:31:10,280 --> 00:31:13,920
Speaker 1: about term financing through Corporate America, yields are lower today

608
00:31:14,000 --> 00:31:15,960
Speaker 1: than they were at the beginning here, but the consumer

609
00:31:16,160 --> 00:31:18,680
Speaker 1: is paying you know, fifty plus basis points higher. So

610
00:31:19,440 --> 00:31:21,960
Speaker 1: for consumer driven economy, they have to be very careful.

611
00:31:22,160 --> 00:31:25,320
Speaker 1: If it's sevent GDPs coming from the consumer, we've got

612
00:31:25,320 --> 00:31:28,160
Speaker 1: to be careful of of like tightening net spigot too quickly.

613
00:31:28,520 --> 00:31:30,640
Speaker 1: And so I don't buy the idea that the fits

614
00:31:30,680 --> 00:31:33,080
Speaker 1: behind the curve. In fact, they're doing a double dose

615
00:31:33,120 --> 00:31:35,440
Speaker 1: of tightening for the fact that they're going to raise

616
00:31:35,520 --> 00:31:38,680
Speaker 1: rates there in the process of a hiking regime that's undeniable,

617
00:31:39,200 --> 00:31:42,560
Speaker 1: and they're reducing their balance sheet. They've already started last

618
00:31:42,600 --> 00:31:46,120
Speaker 1: month in October, they started taking off ten billion dollars

619
00:31:46,120 --> 00:31:48,760
Speaker 1: a month out of the balance sheet by lack of reinvestment.

620
00:31:49,280 --> 00:31:52,080
Speaker 1: But stop there, because I've been discussing this with people,

621
00:31:52,120 --> 00:31:55,480
Speaker 1: and you get that thousand yard stare when it starts.

622
00:31:56,040 --> 00:32:00,520
Speaker 1: Explain what it means for them not to roll over paper.

623
00:32:00,600 --> 00:32:04,040
Speaker 1: They have, how their balance sheet shrined by them doing

624
00:32:04,120 --> 00:32:08,080
Speaker 1: nothing right. So they have there's there's a maturity wall

625
00:32:08,200 --> 00:32:12,920
Speaker 1: each month, there's securities that mature prior to October of seventeen.

626
00:32:13,240 --> 00:32:16,080
Speaker 1: They reinvested those proceeds at some point along the curve,

627
00:32:16,440 --> 00:32:20,800
Speaker 1: both through treasuries and agency mortgages government guaranteed mortgages, so

628
00:32:21,000 --> 00:32:25,480
Speaker 1: buy them, not reinvesting the securities. That means those securities

629
00:32:25,680 --> 00:32:27,640
Speaker 1: instead of being held in what I would call a

630
00:32:27,720 --> 00:32:31,200
Speaker 1: price taker hands that the Fed buys bindly does not

631
00:32:31,320 --> 00:32:34,080
Speaker 1: care what the yield is. Right, it now gets put

632
00:32:34,120 --> 00:32:36,479
Speaker 1: out in the float of the market. So from an

633
00:32:36,480 --> 00:32:40,320
Speaker 1: equity perspective, if we draw that parallel, imagine insiders putting

634
00:32:40,520 --> 00:32:43,520
Speaker 1: securities out in the marketplace. So those bonds need to

635
00:32:43,520 --> 00:32:47,960
Speaker 1: be digested by price discrimination or people who are priced

636
00:32:47,960 --> 00:32:51,160
Speaker 1: discriminatory when it comes to the price and yield those securities,

637
00:32:51,200 --> 00:32:53,480
Speaker 1: as opposed to the FED that buys it any price. Finally,

638
00:32:53,600 --> 00:32:55,520
Speaker 1: so you can think of the e c B sixty

639
00:32:55,520 --> 00:32:58,040
Speaker 1: billion euros is still a month that they're doing until

640
00:32:58,040 --> 00:33:01,280
Speaker 1: the end of the year. So by the FED putting

641
00:33:01,280 --> 00:33:04,120
Speaker 1: these securities out in supply in the market, it needs

642
00:33:04,120 --> 00:33:07,640
Speaker 1: to be digested by investors, and so that means there's

643
00:33:07,680 --> 00:33:11,040
Speaker 1: a net supply of new bonds in the marketplace. Without

644
00:33:11,520 --> 00:33:15,880
Speaker 1: even discussing the budget, discussing the shortfalls there the the

645
00:33:16,680 --> 00:33:19,880
Speaker 1: deficit neutral one point five trillion dollars that the new

646
00:33:19,920 --> 00:33:22,960
Speaker 1: tax plan is gonna cost every ten years. So at

647
00:33:22,960 --> 00:33:25,320
Speaker 1: the margin, it's not much on their balance sheet. It's

648
00:33:25,360 --> 00:33:27,960
Speaker 1: only ten billion dollars. You know, some firms get that

649
00:33:27,960 --> 00:33:30,280
Speaker 1: in a month in terms of bond flows. So but

650
00:33:30,640 --> 00:33:35,360
Speaker 1: the plan is yeah, right, that that's that's the elephant

651
00:33:35,400 --> 00:33:37,560
Speaker 1: in the room, right. But what we're saying about the

652
00:33:37,600 --> 00:33:40,320
Speaker 1: FED is don't take that money and roll it into

653
00:33:40,360 --> 00:33:43,200
Speaker 1: a new bond, which means that bond is now those

654
00:33:44,440 --> 00:33:47,160
Speaker 1: um what would have been purchased and put back on

655
00:33:47,200 --> 00:33:49,280
Speaker 1: the FED balance sheet is now in the out in

656
00:33:49,320 --> 00:33:51,840
Speaker 1: the market plans out in the market one, so the

657
00:33:51,840 --> 00:33:54,320
Speaker 1: market to digest it. But don't forget it goes from

658
00:33:54,400 --> 00:33:57,360
Speaker 1: ten billion a month, and in January it's on schedule

659
00:33:57,480 --> 00:33:59,480
Speaker 1: to go to twenty billion a month, and then in

660
00:33:59,520 --> 00:34:02,840
Speaker 1: April thirty billion a month, and then July forty billion,

661
00:34:02,920 --> 00:34:05,480
Speaker 1: and in October fifty billions. So this isn't them selling.

662
00:34:05,520 --> 00:34:10,160
Speaker 1: This is simply them not renewing, not rolling over bonds

663
00:34:10,200 --> 00:34:12,880
Speaker 1: that mature in order to strength their balance sheet. That's correct,

664
00:34:12,960 --> 00:34:15,319
Speaker 1: and so that's has stated today. Remember the game plan

665
00:34:15,400 --> 00:34:19,399
Speaker 1: can change, UM. So what that means is is that

666
00:34:19,480 --> 00:34:21,640
Speaker 1: these securities were set to mature anyway. And if you

667
00:34:21,680 --> 00:34:24,120
Speaker 1: actually look at the Fed's balance sheet and the maturity schedule,

668
00:34:24,560 --> 00:34:27,640
Speaker 1: it always is above this threshold. So they will be

669
00:34:28,280 --> 00:34:31,719
Speaker 1: barring any changes in the plan UM putting these securities

670
00:34:31,719 --> 00:34:35,160
Speaker 1: out in the marketplace effectively. However, they do have a

671
00:34:35,200 --> 00:34:38,920
Speaker 1: little thing and they'd say up to doesn't say exactly,

672
00:34:39,360 --> 00:34:42,080
Speaker 1: And there are a few months which I can't recall

673
00:34:42,080 --> 00:34:43,359
Speaker 1: off the top of my head, if there's one month

674
00:34:43,360 --> 00:34:45,880
Speaker 1: in eighteen or it starts a nine team where there's

675
00:34:45,960 --> 00:34:48,560
Speaker 1: not enough to actually dump the fifty billion a month.

676
00:34:48,960 --> 00:34:51,319
Speaker 1: So we'll have to see how that plays out. But

677
00:34:51,440 --> 00:34:54,040
Speaker 1: let's talk about what happens at the FED continues to

678
00:34:54,080 --> 00:34:57,160
Speaker 1: press rates because they're behind the curve and we're putting

679
00:34:57,160 --> 00:35:00,279
Speaker 1: these these more more of these bonds in the marketplace. Um,

680
00:35:00,440 --> 00:35:01,920
Speaker 1: we just feel that it has to be at the

681
00:35:01,960 --> 00:35:04,319
Speaker 1: margin negative for yields me and they should go up

682
00:35:04,920 --> 00:35:08,440
Speaker 1: because there's more float in the market, And yet yields

683
00:35:08,440 --> 00:35:10,440
Speaker 1: have not really ticked up all that much. How do

684
00:35:10,480 --> 00:35:14,080
Speaker 1: you explain that up to this point late in right,

685
00:35:14,080 --> 00:35:17,160
Speaker 1: I think I'm gonna call it super Mario, you know. Um,

686
00:35:17,200 --> 00:35:21,520
Speaker 1: And that's I'm referring to the CCP president And UM,

687
00:35:21,560 --> 00:35:25,640
Speaker 1: you know, Droggy has he's really got himself a conundrum. Um.

688
00:35:25,680 --> 00:35:29,160
Speaker 1: He's got nominal GDP similar to ours. Right, he's got

689
00:35:29,200 --> 00:35:32,719
Speaker 1: German Boone's the tenure trading sub forty basis points. You

690
00:35:32,719 --> 00:35:35,640
Speaker 1: know what, we're sitting closer to HU forty basis points.

691
00:35:36,040 --> 00:35:39,520
Speaker 1: Um so, and he's got overnight lending rates negative forty

692
00:35:39,560 --> 00:35:42,360
Speaker 1: basis points. Um. You know, we're talking today at like

693
00:35:42,400 --> 00:35:45,120
Speaker 1: one in three eights here in the US. UM, So

694
00:35:45,600 --> 00:35:48,239
Speaker 1: what is the disconnect between their economy which is growing,

695
00:35:48,280 --> 00:35:52,359
Speaker 1: they have margins expanding, you know, they never had this recession, um,

696
00:35:52,480 --> 00:35:55,560
Speaker 1: and they're contained to grow similar rates. Why are there yields?

697
00:35:55,560 --> 00:35:58,480
Speaker 1: So why would he say they never had this recession.

698
00:35:58,880 --> 00:36:01,480
Speaker 1: They had a bad up of the years, and they

699
00:36:01,520 --> 00:36:05,160
Speaker 1: certainly suffered during the Great Great Recession. Sure, but also

700
00:36:05,800 --> 00:36:08,799
Speaker 1: we did too, really in profitability in the US. It

701
00:36:08,800 --> 00:36:12,200
Speaker 1: was highly correlated to energy, right, it infected the entire world.

702
00:36:12,480 --> 00:36:14,319
Speaker 1: But I mean we had a profit recession here in

703
00:36:14,360 --> 00:36:17,600
Speaker 1: the US, which I'm defined as declining corporate profits consecutively,

704
00:36:18,000 --> 00:36:22,439
Speaker 1: so I it was proxibly five quarters. We saved that off, right,

705
00:36:22,800 --> 00:36:24,799
Speaker 1: And really they did too. Rite they never had the

706
00:36:24,840 --> 00:36:28,359
Speaker 1: true economic recession that's typically associate with And that's that's

707
00:36:28,400 --> 00:36:30,280
Speaker 1: one of the first times in history you've actually seen,

708
00:36:30,560 --> 00:36:32,920
Speaker 1: even in the US go through the profit recession not

709
00:36:33,000 --> 00:36:36,799
Speaker 1: leading to a true economic recession. So when you when

710
00:36:36,840 --> 00:36:39,080
Speaker 1: you actually look at kind of spreads and everything, I

711
00:36:39,360 --> 00:36:42,120
Speaker 1: do believe if you look at yields, there's been such

712
00:36:42,160 --> 00:36:45,120
Speaker 1: correlation in global bond yields. That the reason you have

713
00:36:45,280 --> 00:36:47,680
Speaker 1: some of this um kind of I won't call it

714
00:36:47,680 --> 00:36:49,920
Speaker 1: a ceiling, but the fact that you have yields in

715
00:36:49,960 --> 00:36:53,000
Speaker 1: the US a little too low relative historical standards as

716
00:36:53,040 --> 00:36:55,480
Speaker 1: measured by g d p UM. I think a lot

717
00:36:55,520 --> 00:36:57,279
Speaker 1: of it stemps in the fact that you had this

718
00:36:57,320 --> 00:37:00,600
Speaker 1: compression because they continue to buy bonds. It's not just

719
00:37:00,640 --> 00:37:03,680
Speaker 1: that they won't hike rates negative forty basis points and

720
00:37:03,760 --> 00:37:08,000
Speaker 1: overnight lending, but they also buying sixty billion euros. So

721
00:37:08,200 --> 00:37:11,200
Speaker 1: Draggy cuts thirty billion of that out in January. That's

722
00:37:11,239 --> 00:37:14,160
Speaker 1: thirty less that thirty billion euros less he's buying, and

723
00:37:14,200 --> 00:37:16,839
Speaker 1: the FEDS dumping more into the market, so we could

724
00:37:16,920 --> 00:37:20,040
Speaker 1: see an increase in rates. And that's that's kind of

725
00:37:20,040 --> 00:37:22,359
Speaker 1: our stance at this point, is that yield should push

726
00:37:22,440 --> 00:37:25,440
Speaker 1: higher from these levels and historically long bonds and you know,

727
00:37:25,680 --> 00:37:28,520
Speaker 1: trade around nominal GDP, so that says, you know, maybe

728
00:37:28,520 --> 00:37:31,400
Speaker 1: they're about a hundred basis points too rich today and

729
00:37:31,520 --> 00:37:34,360
Speaker 1: long bomb being thirty. We have been speaking with Jeff Sherman.

730
00:37:34,440 --> 00:37:37,680
Speaker 1: He is the deputy c i O at Double Line Capital.

731
00:37:38,360 --> 00:37:41,920
Speaker 1: If you enjoy this conversation, we love your comments. Feedback

732
00:37:42,000 --> 00:37:46,359
Speaker 1: end suggestions right to us at m IB podcast at

733
00:37:46,360 --> 00:37:49,480
Speaker 1: Bloomberg dot net. You can check out my daily column

734
00:37:49,520 --> 00:37:52,640
Speaker 1: on Bloomberg View dot com or follow me on Twitter

735
00:37:52,800 --> 00:37:56,080
Speaker 1: at Rid Halts. Be sure and check out our podcast

736
00:37:56,120 --> 00:37:59,400
Speaker 1: extras where we keep the tape rolling and continue discussing

737
00:37:59,440 --> 00:38:03,720
Speaker 1: all things UH, bonds, commodities and equities. You can find

738
00:38:03,760 --> 00:38:10,440
Speaker 1: those podcast extras wherever finer podcasts are sold Apple iTunes, Overcast, SoundCloud,

739
00:38:10,719 --> 00:38:14,280
Speaker 1: and Bloomberg dot com. I'm barrier It Holts. You're listening

740
00:38:14,320 --> 00:38:31,000
Speaker 1: to Masters in Business on Bloomberg Radio. Welcome to the podcast.

741
00:38:31,160 --> 00:38:33,040
Speaker 1: Thank you Jeff for doing this. I had so much

742
00:38:33,080 --> 00:38:36,759
Speaker 1: fun on your podcast earlier this year, and I knew

743
00:38:36,800 --> 00:38:40,920
Speaker 1: I've wanted to have you here for a while. UM,

744
00:38:41,000 --> 00:38:43,680
Speaker 1: let's talk about a few things we didn't get to

745
00:38:43,800 --> 00:38:47,880
Speaker 1: some questions I wanted to ask you, um during the

746
00:38:47,880 --> 00:38:51,120
Speaker 1: regular broadcast portion, and then we'll jump into some more

747
00:38:51,160 --> 00:38:54,399
Speaker 1: fun stuff. So you mentioned super Mario, we were talking

748
00:38:54,400 --> 00:38:57,880
Speaker 1: about the FED. We left out the third player in

749
00:38:58,080 --> 00:39:01,279
Speaker 1: Central Bank Corona Thon. Yes, what what do you think

750
00:39:01,360 --> 00:39:06,600
Speaker 1: about Albanomics and what's going on in Japan? And can

751
00:39:06,680 --> 00:39:10,920
Speaker 1: you ever recall a period where the US Japan and Europe.

752
00:39:11,239 --> 00:39:15,200
Speaker 1: We're so out of phase with their recoveries and or

753
00:39:15,560 --> 00:39:19,319
Speaker 1: economic stimuli. Yeah, that's that's a lot to digest there.

754
00:39:19,680 --> 00:39:23,160
Speaker 1: So um Essentially, I don't know how the bo j

755
00:39:23,400 --> 00:39:26,480
Speaker 1: gets out of their policy. I mean, they own so

756
00:39:26,560 --> 00:39:29,600
Speaker 1: many equities. I mean, the the data we see is

757
00:39:29,600 --> 00:39:32,200
Speaker 1: like sixty percent of the equity market roughly the same

758
00:39:32,200 --> 00:39:34,560
Speaker 1: as their et F market. Like you could let you

759
00:39:34,600 --> 00:39:37,240
Speaker 1: could let bonds just mature and roll off, you can't

760
00:39:37,239 --> 00:39:40,080
Speaker 1: do that with equities, right. And the other thing is

761
00:39:40,080 --> 00:39:42,919
Speaker 1: is that they're supposedly targeting the rate. The rate isn't

762
00:39:42,920 --> 00:39:45,759
Speaker 1: the rate they're targeting. I mean, it's it's flat out

763
00:39:45,880 --> 00:39:49,040
Speaker 1: trying to manipulate the curve. Um. But you know, the

764
00:39:49,040 --> 00:39:51,320
Speaker 1: thing is is that they believe it's working. The ABBE

765
00:39:51,360 --> 00:39:55,520
Speaker 1: got re elected, got the majority, which is the economy

766
00:39:55,560 --> 00:39:57,759
Speaker 1: isn't bad, and you know, they think they're going to

767
00:39:57,800 --> 00:40:01,400
Speaker 1: get their inflation. So we'll have to see, um. But

768
00:40:01,480 --> 00:40:04,040
Speaker 1: I think they're the ones that are on cruise control.

769
00:40:04,080 --> 00:40:06,440
Speaker 1: They're not going to peel this back until they get

770
00:40:06,480 --> 00:40:09,000
Speaker 1: their desire to fact, how do we explain that of

771
00:40:09,040 --> 00:40:13,680
Speaker 1: all the major economies, they're the ones that's the most

772
00:40:13,760 --> 00:40:20,160
Speaker 1: problematic in terms of their balance sheets, their demographics, their

773
00:40:20,200 --> 00:40:26,040
Speaker 1: heavily export dependent economy. And yet what is the ten

774
00:40:26,120 --> 00:40:28,719
Speaker 1: year in Japan? Now it's roughly it's usually in a

775
00:40:28,719 --> 00:40:31,960
Speaker 1: single digit basis point. It's amazing. So so how do

776
00:40:32,000 --> 00:40:35,720
Speaker 1: we explain that. Is Japan more credit worthy than Germany

777
00:40:35,840 --> 00:40:38,319
Speaker 1: or the US or is something else going on? I

778
00:40:38,320 --> 00:40:40,399
Speaker 1: think it's something else going on to I mean, look,

779
00:40:40,440 --> 00:40:42,399
Speaker 1: it's it's the home of the carry trade. It has

780
00:40:42,440 --> 00:40:45,000
Speaker 1: been for so long. Um, it turns into the flight

781
00:40:45,040 --> 00:40:49,600
Speaker 1: to quality asset when there's crisis because as Japanese based investors,

782
00:40:49,920 --> 00:40:52,840
Speaker 1: they have to invest overseas to get any semblance of

783
00:40:52,840 --> 00:40:55,800
Speaker 1: a return right. And so what you find is in

784
00:40:56,040 --> 00:40:58,680
Speaker 1: when things go bad, they repatriate the money back home,

785
00:40:58,800 --> 00:41:01,719
Speaker 1: get the strength in the yam um. So I think

786
00:41:01,760 --> 00:41:04,680
Speaker 1: the dynamics have changed over time, but I think what

787
00:41:04,760 --> 00:41:07,000
Speaker 1: we should learn from it it's a precursor of things

788
00:41:07,040 --> 00:41:10,960
Speaker 1: to come in developed world and Europe is on that track.

789
00:41:11,440 --> 00:41:13,880
Speaker 1: The US is on that track. When you look at

790
00:41:13,960 --> 00:41:16,759
Speaker 1: birth rates were barely at replacement rates here in the US,

791
00:41:17,040 --> 00:41:19,800
Speaker 1: way ahead of Japan, though, I mean the US maybe

792
00:41:19,960 --> 00:41:24,000
Speaker 1: the best birth rate of industrialize that that's why I

793
00:41:24,040 --> 00:41:27,080
Speaker 1: say Europe is going to have the problem next, right,

794
00:41:27,160 --> 00:41:31,960
Speaker 1: And there's one way to hear the birth rate, have kids. Um.

795
00:41:32,560 --> 00:41:35,640
Speaker 1: Immigration is another thing that you need workers. It's not

796
00:41:35,680 --> 00:41:39,320
Speaker 1: necessarily you know, having children, because that takes a while.

797
00:41:39,600 --> 00:41:41,799
Speaker 1: If we start tonight, Barry, it's gonna take you know,

798
00:41:42,040 --> 00:41:45,520
Speaker 1: eighteen twenty years to get that thing going. So immigration

799
00:41:45,640 --> 00:41:47,840
Speaker 1: is a is a good stop gap too for that time.

800
00:41:48,160 --> 00:41:50,279
Speaker 1: But you look at things like Saudi Arabia, I mean

801
00:41:50,400 --> 00:41:53,960
Speaker 1: their workforce in prime working age. It's like of their

802
00:41:54,040 --> 00:41:57,200
Speaker 1: area has in prime working age. So I think what

803
00:41:57,280 --> 00:42:00,200
Speaker 1: you see in the Japan, it goes to Europe next, um,

804
00:42:00,239 --> 00:42:02,800
Speaker 1: and then the US without changing its ways. Ultimately we

805
00:42:02,960 --> 00:42:06,520
Speaker 1: go that direction. But you're talking decades, many decades down

806
00:42:06,560 --> 00:42:09,400
Speaker 1: the road. But again we we shouldn't just turn a

807
00:42:09,400 --> 00:42:11,560
Speaker 1: blind eye to what's going on in Japan. And that's

808
00:42:11,560 --> 00:42:14,200
Speaker 1: what happens when you have a closed off immigration system

809
00:42:14,480 --> 00:42:17,400
Speaker 1: and you don't have the birthrate, and again the demography

810
00:42:17,480 --> 00:42:21,600
Speaker 1: is horrible, you know, and yet they continue just puttering along.

811
00:42:21,640 --> 00:42:25,279
Speaker 1: It's it's it's good to control your own printing press well,

812
00:42:25,360 --> 00:42:27,320
Speaker 1: to say, to say the least I have to push

813
00:42:27,360 --> 00:42:29,799
Speaker 1: back against something you said or or I may have

814
00:42:29,920 --> 00:42:35,040
Speaker 1: misheard previously you had said this is the only profit

815
00:42:35,080 --> 00:42:40,400
Speaker 1: recession we've seen where there wasn't a subsequent economic recession.

816
00:42:41,120 --> 00:42:46,640
Speaker 1: I believe that to be true. But so US unemployment

817
00:42:46,640 --> 00:42:49,440
Speaker 1: doubled from five to ten percent, GDP dropped to zero.

818
00:42:49,520 --> 00:42:54,600
Speaker 1: How is that not a I'm talking and I'm talking recently,

819
00:42:55,280 --> 00:42:59,360
Speaker 1: so you're not to the financial forever. Come on, Barry, alright,

820
00:42:59,600 --> 00:43:05,040
Speaker 1: so it I've been around at least that low, right,

821
00:43:05,120 --> 00:43:08,440
Speaker 1: So that's really when you had a drop in residing,

822
00:43:08,680 --> 00:43:11,040
Speaker 1: drop in profits throughout most of the fifteen, at least sixteen,

823
00:43:11,040 --> 00:43:13,000
Speaker 1: and then you start to see the recovery. So those

824
00:43:13,000 --> 00:43:16,279
Speaker 1: are the five quarters I'm referring to. Got it so

825
00:43:16,320 --> 00:43:19,360
Speaker 1: you can fact check it later too, But a number

826
00:43:19,360 --> 00:43:22,240
Speaker 1: of I think it was Um, I'm trying to remember

827
00:43:22,280 --> 00:43:26,520
Speaker 1: who Eckery was forecasting that as a recession, and it

828
00:43:26,640 --> 00:43:28,799
Speaker 1: never showed up, never materialized. And if you look at

829
00:43:28,800 --> 00:43:32,239
Speaker 1: the conference Board leading Indicator, which is a great indicator recession,

830
00:43:32,680 --> 00:43:35,440
Speaker 1: what you had in fifteen is we got close when

831
00:43:35,440 --> 00:43:38,160
Speaker 1: it rolled over at least six team. We got almost

832
00:43:38,160 --> 00:43:41,000
Speaker 1: to zero on that. And the negative area tends to

833
00:43:41,000 --> 00:43:44,000
Speaker 1: be recessionary, not always, but again it's one point and

834
00:43:44,040 --> 00:43:46,759
Speaker 1: that rebound there, so that indicator still looks pretty good.

835
00:43:46,920 --> 00:43:50,000
Speaker 1: That UM. That is the Ryan Hart and rogue Off

836
00:43:50,680 --> 00:43:55,000
Speaker 1: um explanation is following financial crises, you get a very

837
00:43:55,040 --> 00:43:59,040
Speaker 1: subpart GDP, very subpart employment and wage gains, and it

838
00:43:59,040 --> 00:44:01,640
Speaker 1: looks like you're parent lee on the verge of a recession,

839
00:44:02,040 --> 00:44:04,960
Speaker 1: but you're just slowly recovering and and there is no

840
00:44:05,120 --> 00:44:08,960
Speaker 1: credit available to push you away from that, and there's

841
00:44:09,000 --> 00:44:12,480
Speaker 1: sub one percent GDP, very little credit. I should say,

842
00:44:12,680 --> 00:44:15,200
Speaker 1: then there's two things that I kind of um gleamed

843
00:44:15,239 --> 00:44:18,920
Speaker 1: from that UM. One is is that, um, you you

844
00:44:19,000 --> 00:44:21,759
Speaker 1: also have this high debt burden, right, And that's the

845
00:44:21,800 --> 00:44:25,240
Speaker 1: other part of the Reinhardt Rogoff study is that essentially

846
00:44:25,239 --> 00:44:27,879
Speaker 1: when you hit certain debt to GDP ratios, you can

847
00:44:27,920 --> 00:44:30,759
Speaker 1: just never recover. So and the second point I was

848
00:44:30,800 --> 00:44:35,480
Speaker 1: trying to make too, is that ultimately or historically should say,

849
00:44:35,600 --> 00:44:38,440
Speaker 1: when you had a nominal GDP sub five in the

850
00:44:38,560 --> 00:44:42,080
Speaker 1: US that led to a recession and we've been perennial there,

851
00:44:42,600 --> 00:44:45,799
Speaker 1: sub five percent nominal not real? Okay, yeah, sorry I

852
00:44:45,840 --> 00:44:48,759
Speaker 1: wasn't clear there, so including inflation, but that has to

853
00:44:48,800 --> 00:44:50,600
Speaker 1: be tossed out. We've we've been sub five for a

854
00:44:50,640 --> 00:44:53,200
Speaker 1: long time time, so I think it's consistent with the

855
00:44:53,280 --> 00:44:55,839
Speaker 1: Rhino Rugoff study as well. And then the other thing

856
00:44:55,920 --> 00:44:58,359
Speaker 1: I wanted to ask you about that I didn't get

857
00:44:58,400 --> 00:45:02,480
Speaker 1: too while we were doing the broadcast portion was on

858
00:45:02,560 --> 00:45:07,520
Speaker 1: the Schiller cap portfolio. There are a handful of questions. Um, First,

859
00:45:08,080 --> 00:45:11,120
Speaker 1: this model, you guys at double one and now running

860
00:45:11,239 --> 00:45:13,520
Speaker 1: a billion dollars or so? Is that right? It's a

861
00:45:13,520 --> 00:45:15,680
Speaker 1: little more than that's about six billion today six billion?

862
00:45:16,040 --> 00:45:20,200
Speaker 1: So and who is the fun manager of that? Myself?

863
00:45:20,200 --> 00:45:22,719
Speaker 1: All right? So the two jeffs are running this as

864
00:45:22,760 --> 00:45:26,800
Speaker 1: a six billion dollar portfolio. You have the original version?

865
00:45:26,840 --> 00:45:29,879
Speaker 1: Was us? I understand there's a European version of Yes,

866
00:45:29,960 --> 00:45:33,359
Speaker 1: that's correct. Um, So the same basic models, same model.

867
00:45:33,360 --> 00:45:36,879
Speaker 1: Instead of using the SMP five decomposing its sectors, take

868
00:45:36,960 --> 00:45:40,879
Speaker 1: the MSCI Europe and decomposion did sectors. So if you're

869
00:45:40,880 --> 00:45:43,840
Speaker 1: taking ms A your ms C I Europe, could you

870
00:45:43,880 --> 00:45:46,680
Speaker 1: do the same thing for ms CI Emerging Markets or

871
00:45:46,719 --> 00:45:48,719
Speaker 1: Asia or what have you. You are correct? And there

872
00:45:48,760 --> 00:45:51,680
Speaker 1: are other versions there is, um there's a Japanese version.

873
00:45:51,719 --> 00:45:54,080
Speaker 1: We do not have a product on that today. Um.

874
00:45:54,080 --> 00:45:57,799
Speaker 1: There is the Asia x Japan version as well. Um,

875
00:45:57,880 --> 00:46:01,120
Speaker 1: and most people the first question is what about emerging markets?

876
00:46:01,560 --> 00:46:05,800
Speaker 1: And so remember we're using earnings data to build a ratio.

877
00:46:06,239 --> 00:46:08,600
Speaker 1: So how do you think earnings ten years ago looked

878
00:46:08,600 --> 00:46:11,720
Speaker 1: in the emerging market? Where the credibility of it? And so,

879
00:46:11,880 --> 00:46:15,399
Speaker 1: although we've tried to gravitate to these international standards, um,

880
00:46:15,480 --> 00:46:18,640
Speaker 1: the you know, I'm I'm skeptical of the data set

881
00:46:19,160 --> 00:46:22,439
Speaker 1: and the actually how good the data is? So um,

882
00:46:22,480 --> 00:46:25,200
Speaker 1: perhaps at sometimes someone will be able to create a

883
00:46:25,320 --> 00:46:29,000
Speaker 1: standard methodology for that, but again it's I think it's

884
00:46:29,000 --> 00:46:32,040
Speaker 1: too early to apply this in its form as it

885
00:46:32,040 --> 00:46:36,719
Speaker 1: exists today. So that's a really interesting product that that

886
00:46:36,800 --> 00:46:41,120
Speaker 1: you helped to to create based on Bob Schiller's work.

887
00:46:41,840 --> 00:46:45,919
Speaker 1: What is the process like for thinking about developing and

888
00:46:46,080 --> 00:46:50,600
Speaker 1: rolling out new models, new funds? Knew? What have you? Yeah,

889
00:46:50,680 --> 00:46:53,640
Speaker 1: I have a whiteboard in the office. Um, you know

890
00:46:54,080 --> 00:46:56,959
Speaker 1: typically you know, when people have ideas, our team looks

891
00:46:57,000 --> 00:46:59,640
Speaker 1: at it. You know. Um, you know, you know, what's

892
00:46:59,680 --> 00:47:02,640
Speaker 1: the tar going to market? What's our edge? How do

893
00:47:02,680 --> 00:47:05,400
Speaker 1: we what what's what differentiates this from other things? And

894
00:47:05,520 --> 00:47:09,279
Speaker 1: so um, although you know, we have probably seventeen strategies

895
00:47:09,280 --> 00:47:11,959
Speaker 1: that we offer out to the public today. Um, when

896
00:47:12,080 --> 00:47:14,480
Speaker 1: you look across them, they are different, but they're all

897
00:47:14,520 --> 00:47:17,680
Speaker 1: consistent their macro consistent. There same thinkers, are the same

898
00:47:17,719 --> 00:47:20,960
Speaker 1: portfolio managers, and it's different risk profiles. And so what

899
00:47:21,000 --> 00:47:23,280
Speaker 1: I like to say is that it answers the question

900
00:47:23,360 --> 00:47:25,000
Speaker 1: I get whenever I give a talk in front of

901
00:47:25,040 --> 00:47:27,959
Speaker 1: an audience. You know, if you had a hundred dollars, Barry,

902
00:47:28,480 --> 00:47:31,240
Speaker 1: how would you allocate across your funds? And so instead

903
00:47:31,280 --> 00:47:33,240
Speaker 1: of doing a good question, it is a great question.

904
00:47:33,440 --> 00:47:35,800
Speaker 1: And so my response now is tell me a risk profile,

905
00:47:36,239 --> 00:47:38,040
Speaker 1: what what kind of draw down do you like? What's

906
00:47:38,040 --> 00:47:41,120
Speaker 1: your objective here? And we can give you probably a strategy.

907
00:47:41,120 --> 00:47:44,280
Speaker 1: It's a one stop shop for it, right and so, Um,

908
00:47:44,480 --> 00:47:47,840
Speaker 1: the idea is that if we find new things, you know,

909
00:47:47,920 --> 00:47:50,680
Speaker 1: we're happy to get involved with them. Um. But again,

910
00:47:50,719 --> 00:47:53,040
Speaker 1: we don't want to saturate the market with products that

911
00:47:53,239 --> 00:47:55,960
Speaker 1: we don't think has some different edge than something that

912
00:47:55,960 --> 00:47:58,560
Speaker 1: currently exists. And so you know, we've rolled out ETFs

913
00:47:58,600 --> 00:48:02,600
Speaker 1: over the years where we sub advise them UM different channels.

914
00:48:02,680 --> 00:48:05,760
Speaker 1: We've built a use of complex starting last year starting

915
00:48:05,760 --> 00:48:07,920
Speaker 1: to take it's trying to take hold of the European

916
00:48:07,960 --> 00:48:10,399
Speaker 1: markets and so um, right now we're looking at kind

917
00:48:10,400 --> 00:48:13,520
Speaker 1: of you know, that horizontal type of distribution where trying

918
00:48:13,560 --> 00:48:16,719
Speaker 1: to bring our services to more people, right and not

919
00:48:16,719 --> 00:48:19,359
Speaker 1: not necessarily got to have new products to do that.

920
00:48:19,640 --> 00:48:22,560
Speaker 1: So the the biggest theme in in the world of

921
00:48:22,600 --> 00:48:26,279
Speaker 1: investing for the past I don't know year decade fill

922
00:48:26,320 --> 00:48:31,360
Speaker 1: in the blank, has been the shift towards passive investing

923
00:48:31,400 --> 00:48:35,080
Speaker 1: on the equity side versus active stock picking. But I

924
00:48:35,120 --> 00:48:38,719
Speaker 1: think a lot of people make the assumption that the

925
00:48:38,760 --> 00:48:42,760
Speaker 1: same is true on the bond side, and from what

926
00:48:43,400 --> 00:48:47,800
Speaker 1: most of the academic data shows is that active investing

927
00:48:47,840 --> 00:48:53,440
Speaker 1: on bonds actually generates alpha. Tell us about um, why

928
00:48:54,080 --> 00:48:57,840
Speaker 1: active on bonds is so much more effective than active

929
00:48:57,880 --> 00:49:04,000
Speaker 1: on equities more a little question tiny topics, yea, how

930
00:49:04,080 --> 00:49:06,040
Speaker 1: much time do you have for the rest of the day.

931
00:49:06,640 --> 00:49:11,040
Speaker 1: I think what's what's amazing about it is the bonds industries,

932
00:49:11,040 --> 00:49:14,239
Speaker 1: first of all, historically have been kind of poorly constructed,

933
00:49:14,680 --> 00:49:18,240
Speaker 1: and what they did is over inclusive, regardless of quality. Regardless,

934
00:49:18,239 --> 00:49:22,239
Speaker 1: it's not necessarily overly inclusive. What I would argue is

935
00:49:22,560 --> 00:49:25,399
Speaker 1: the it's the thesis pointed the fact that they use

936
00:49:25,520 --> 00:49:28,560
Speaker 1: market value of debt to index it. So the more

937
00:49:28,600 --> 00:49:31,280
Speaker 1: you borrow, the larger position you are in the index.

938
00:49:31,520 --> 00:49:34,279
Speaker 1: So trying to bring that market capitalization idea from the

939
00:49:34,280 --> 00:49:37,800
Speaker 1: equity market and turn into market value in fixed income

940
00:49:38,160 --> 00:49:40,799
Speaker 1: and so it doesn't make sense. So very as you

941
00:49:40,840 --> 00:49:44,120
Speaker 1: borrow more money for me, you know, we more investors

942
00:49:44,120 --> 00:49:46,960
Speaker 1: should give you more money and put a higher allocation

943
00:49:47,040 --> 00:49:50,440
Speaker 1: because you're more credit worthy. No, you're absolutely less credit worthy.

944
00:49:50,480 --> 00:49:54,319
Speaker 1: So it's actually inherently incorrect the way that in the

945
00:49:54,320 --> 00:49:57,120
Speaker 1: traditional industries have looked at that. And obviously there's other

946
00:49:57,160 --> 00:50:00,319
Speaker 1: people trying to build new new models behind that. But

947
00:50:00,400 --> 00:50:02,239
Speaker 1: I think if you look across the universe, there's a

948
00:50:02,239 --> 00:50:06,160
Speaker 1: lot of SMP data that shows active fixedment income management

949
00:50:06,200 --> 00:50:10,000
Speaker 1: tends out perform the indices over very long periods of time. Um,

950
00:50:10,040 --> 00:50:14,480
Speaker 1: it just is such a different set of data versus equities.

951
00:50:14,560 --> 00:50:16,880
Speaker 1: We'll look at We'll look at the e t F

952
00:50:16,920 --> 00:50:20,200
Speaker 1: world the passive ETFs um, not the active ones, but

953
00:50:20,280 --> 00:50:23,080
Speaker 1: the passive ones relative to active manage either E t

954
00:50:23,360 --> 00:50:26,239
Speaker 1: s or funds. It's the same things, is true. They're

955
00:50:26,680 --> 00:50:28,360
Speaker 1: I'm not saying that people are picking off the E

956
00:50:28,440 --> 00:50:31,480
Speaker 1: t F investors, but there you know what they're gonna buy.

957
00:50:31,560 --> 00:50:33,799
Speaker 1: When the big new issue comes out, you don't want

958
00:50:33,800 --> 00:50:36,080
Speaker 1: to participate in it because you know they're gonna gobble

959
00:50:36,120 --> 00:50:38,640
Speaker 1: it down and their price takers. Once again just like

960
00:50:38,719 --> 00:50:41,960
Speaker 1: the ft and so UM it's you can move the

961
00:50:42,000 --> 00:50:43,759
Speaker 1: bond price a lot more than you can probably the

962
00:50:43,800 --> 00:50:48,520
Speaker 1: equity prices. That said this, this fervor for indexation on

963
00:50:48,600 --> 00:50:50,920
Speaker 1: the equity side, there's gotta be a limit to it.

964
00:50:51,000 --> 00:50:53,239
Speaker 1: Obviously the whole world can't be in Well, we're at

965
00:50:53,280 --> 00:50:56,759
Speaker 1: thirty in the US, and if you listen to UM

966
00:50:57,000 --> 00:51:01,480
Speaker 1: Bill McNab or Tim Buckley, the Income CEO, they point

967
00:51:01,520 --> 00:51:07,200
Speaker 1: out that globally it's five. So so wherever that limit is,

968
00:51:07,400 --> 00:51:10,839
Speaker 1: we're still fairly early days. He agreed. But I also

969
00:51:10,960 --> 00:51:14,560
Speaker 1: also think back to how the products sold. The product

970
00:51:14,680 --> 00:51:17,399
Speaker 1: isn't sold buy and hold cheap. A lot of people,

971
00:51:17,640 --> 00:51:20,400
Speaker 1: I know you profess that your team people say that,

972
00:51:21,040 --> 00:51:24,560
Speaker 1: but a lot of people are saying active management doesn't work.

973
00:51:24,960 --> 00:51:27,160
Speaker 1: So what the what the corell area is that they're

974
00:51:27,200 --> 00:51:32,600
Speaker 1: telling people that indexing outperforms active management? So what happens

975
00:51:32,640 --> 00:51:36,120
Speaker 1: when it doesn't? Are the people still going to stay there?

976
00:51:36,200 --> 00:51:40,680
Speaker 1: One Secondly, we we take this idea that if you index,

977
00:51:40,760 --> 00:51:43,040
Speaker 1: you're going to be buy and hold, you're going to

978
00:51:43,160 --> 00:51:45,799
Speaker 1: be Now, your job as an advisor is to help

979
00:51:45,880 --> 00:51:49,920
Speaker 1: people stay invested. But let's be honest, a market correction,

980
00:51:50,200 --> 00:51:53,480
Speaker 1: a legit kind of draw down, people are going to

981
00:51:53,600 --> 00:51:56,800
Speaker 1: run for the hills too. Yes, but here's the pushback.

982
00:51:57,200 --> 00:52:00,520
Speaker 1: So first, I don't disagree with anything you're saying. Accept

983
00:52:01,640 --> 00:52:05,320
Speaker 1: The way it's best phrased is hey, active equity stock

984
00:52:05,400 --> 00:52:10,239
Speaker 1: picking and or market timing can beat indexing. However, it's

985
00:52:10,280 --> 00:52:13,800
Speaker 1: expensive and NETTA fees and costs, there's a there's a

986
00:52:13,840 --> 00:52:16,400
Speaker 1: bog you to overcome, and what makes you think that

987
00:52:16,520 --> 00:52:21,200
Speaker 1: you're gonna find Bill Miller in not Bill Miller No. Seven.

988
00:52:21,560 --> 00:52:24,359
Speaker 1: So those are the challenges, right, But I think that's

989
00:52:24,440 --> 00:52:27,200
Speaker 1: that's I think that's also that's a different argument. It is,

990
00:52:27,480 --> 00:52:30,520
Speaker 1: and and the thing about it is maybe what it

991
00:52:30,760 --> 00:52:34,399
Speaker 1: is is maybe there's too many poor managers, maybe there's

992
00:52:34,440 --> 00:52:39,120
Speaker 1: too many people hugging. The index itself actually comes out

993
00:52:39,120 --> 00:52:41,080
Speaker 1: and says, I think that why are you paying up

994
00:52:41,120 --> 00:52:43,440
Speaker 1: for closet index? Right? And I think those people should

995
00:52:43,440 --> 00:52:46,640
Speaker 1: be exposed and they slowly are. You know what people

996
00:52:46,880 --> 00:52:49,000
Speaker 1: got upset about the d o L rule. But maybe

997
00:52:49,000 --> 00:52:51,520
Speaker 1: we have too many bad advisors too that are flipping

998
00:52:51,600 --> 00:52:54,600
Speaker 1: things and doing no doubt, so we're cleaning these all things.

999
00:52:54,719 --> 00:52:56,640
Speaker 1: We're cleaning these things up. And if you're going to

1000
00:52:56,719 --> 00:52:59,640
Speaker 1: get an index product, pay index fees. I'm with you there.

1001
00:53:00,040 --> 00:53:02,719
Speaker 1: But I do think there are good stock pickers. I'm

1002
00:53:02,760 --> 00:53:05,200
Speaker 1: probably not one of them at this stage of the game,

1003
00:53:05,560 --> 00:53:07,800
Speaker 1: but there are people that you should reward there and

1004
00:53:07,840 --> 00:53:11,239
Speaker 1: the activists, and you know, people have targeted niches. Those

1005
00:53:11,320 --> 00:53:13,400
Speaker 1: those people always be able to generate alpha because you

1006
00:53:13,440 --> 00:53:15,920
Speaker 1: have to identify them, yes, in advance, right in advance.

1007
00:53:16,239 --> 00:53:21,359
Speaker 1: The size you know that you have to pay four

1008
00:53:21,400 --> 00:53:23,759
Speaker 1: and forty four to get in, but and they won't

1009
00:53:23,760 --> 00:53:25,640
Speaker 1: even take you. And they won't take you, they'll close down,

1010
00:53:25,680 --> 00:53:28,640
Speaker 1: only run their own money. But not to mention any name.

1011
00:53:28,719 --> 00:53:30,879
Speaker 1: I don't know anyone that's done that, you know, so maybe,

1012
00:53:32,239 --> 00:53:35,120
Speaker 1: but so so let's talk about podcasting a little bit.

1013
00:53:35,120 --> 00:53:38,120
Speaker 1: But active passive. We've beaten the death over the years everywhere.

1014
00:53:38,480 --> 00:53:42,280
Speaker 1: So you by the way, for those of you listening,

1015
00:53:42,520 --> 00:53:46,839
Speaker 1: Jeff has a podcast which is misnamed The Sherman Show.

1016
00:53:47,040 --> 00:53:51,239
Speaker 1: I have internally renamed it Sherman Says, which is what

1017
00:53:51,360 --> 00:53:54,799
Speaker 1: it should be called it and when you do when

1018
00:53:54,840 --> 00:53:58,160
Speaker 1: you when you were privileged to be invited on Jeff's podcast,

1019
00:53:58,960 --> 00:54:03,279
Speaker 1: they he has the word association and that segment is

1020
00:54:03,320 --> 00:54:08,400
Speaker 1: called Sherman says, and your job in word association is

1021
00:54:08,440 --> 00:54:11,239
Speaker 1: to come up with a word one word response, which

1022
00:54:11,239 --> 00:54:14,359
Speaker 1: I actually think I was pretty pretty true too. Um,

1023
00:54:14,680 --> 00:54:16,960
Speaker 1: but you you were one of the successful people and

1024
00:54:17,120 --> 00:54:19,480
Speaker 1: only using one word. But when I've listened to other

1025
00:54:19,560 --> 00:54:23,359
Speaker 1: people's answers, they're like, paragraph long, how is this word

1026
00:54:23,400 --> 00:54:26,920
Speaker 1: association if you're giving me a storyline on it? So

1027
00:54:27,120 --> 00:54:29,719
Speaker 1: I did not want to do word association with you,

1028
00:54:29,800 --> 00:54:32,560
Speaker 1: because that's your thing. But I did something I'm going

1029
00:54:32,600 --> 00:54:35,000
Speaker 1: to name drop here at at a recent conference, I

1030
00:54:35,080 --> 00:54:38,520
Speaker 1: did something with Cliff Astness, who is always amusing and

1031
00:54:38,680 --> 00:54:42,920
Speaker 1: fascinating and in very sharp tongued and witty right not

1032
00:54:43,040 --> 00:54:45,840
Speaker 1: only not only a math guy, but like a really

1033
00:54:46,160 --> 00:54:50,160
Speaker 1: funny um right side of the brain as well, and

1034
00:54:50,360 --> 00:54:54,120
Speaker 1: that his work is phenomenal, absolutely definitely a so, so

1035
00:54:54,719 --> 00:54:57,319
Speaker 1: for for a live Q and A I did with him,

1036
00:54:57,360 --> 00:55:01,040
Speaker 1: I came up with lightning rounds, which was you can

1037
00:55:01,080 --> 00:55:04,040
Speaker 1: answer these longer short, you could do one word, you

1038
00:55:04,080 --> 00:55:07,239
Speaker 1: could do a sentence, but the idea is whatever comes

1039
00:55:07,280 --> 00:55:09,600
Speaker 1: into your head quick answer. All right, all right, you're

1040
00:55:09,600 --> 00:55:12,960
Speaker 1: ready for the for the lightning round with Jeff Sherman.

1041
00:55:13,640 --> 00:55:18,799
Speaker 1: Uh two year or ten for what? For anything? UM

1042
00:55:19,440 --> 00:55:25,360
Speaker 1: two's hires tens higher spread, relatively similar, Star Treker, Star Wars,

1043
00:55:25,719 --> 00:55:31,120
Speaker 1: Star Wars Europe or Emerging markets, emerging market. Still doll

1044
00:55:31,239 --> 00:55:34,239
Speaker 1: dollar will continue some weakness, and I think that's very

1045
00:55:34,280 --> 00:55:39,080
Speaker 1: supportive l A Lakers, Golden State Warriors. I'm a Lakers fan,

1046
00:55:39,239 --> 00:55:41,400
Speaker 1: all right. I just wanted to give you an opportunity

1047
00:55:41,440 --> 00:55:46,240
Speaker 1: to I like everything else. Barry Santrancis good Giants, Samranson's

1048
00:55:46,280 --> 00:55:48,480
Speaker 1: good Niners. But I grew up watching the Lake Show,

1049
00:55:48,960 --> 00:55:51,879
Speaker 1: you know, with the magic and so and so. Look,

1050
00:55:51,920 --> 00:55:54,200
Speaker 1: I do root for Golden State in the playoffs because

1051
00:55:54,200 --> 00:55:57,080
Speaker 1: the Lakers can't ever make it anymore. Um so again,

1052
00:55:57,160 --> 00:55:59,160
Speaker 1: maybe one day with Lonzo we can get to get

1053
00:55:59,200 --> 00:56:03,360
Speaker 1: back together. Smart data or factor investing, Factor investing, you're

1054
00:56:03,360 --> 00:56:07,239
Speaker 1: going to go that way. Taco or burrito taco. I'm

1055
00:56:07,280 --> 00:56:10,480
Speaker 1: a big taco fan, Yes, Bill Miller or Peter Lynch,

1056
00:56:10,960 --> 00:56:16,480
Speaker 1: Peter Lynch, that's interesting, Tesla P one BMW I eight.

1057
00:56:17,040 --> 00:56:21,319
Speaker 1: I'm a beamer guy. Okay, so I didn't know which

1058
00:56:21,400 --> 00:56:24,520
Speaker 1: way you're gonna go. Yeah, yeah, I don't feel it's

1059
00:56:24,520 --> 00:56:28,280
Speaker 1: still that much of pollution in there. So tax reform

1060
00:56:28,520 --> 00:56:32,680
Speaker 1: or infrastructure spending, infrastructure spinning. If you're going to do

1061
00:56:32,880 --> 00:56:35,560
Speaker 1: one point five trillion dollars, at least, let's put it

1062
00:56:35,640 --> 00:56:38,640
Speaker 1: to work. Let's let's get some paved roads. And if

1063
00:56:38,640 --> 00:56:40,719
Speaker 1: you're gonna drive that I eight or that Tesla, you

1064
00:56:40,800 --> 00:56:42,400
Speaker 1: don't want to bounce down this, let me tell you

1065
00:56:42,440 --> 00:56:46,280
Speaker 1: they both have tight suspensions. What is your favorite pet peeve?

1066
00:56:48,719 --> 00:56:52,400
Speaker 1: When people just state things as facts with no evidence

1067
00:56:52,480 --> 00:56:54,680
Speaker 1: behind them. And so I know you do the Evidence

1068
00:56:54,719 --> 00:56:57,080
Speaker 1: based Investing conference and I'm a big fan of that.

1069
00:56:57,480 --> 00:56:59,640
Speaker 1: We hear so many rumors. We talked about the flattening

1070
00:56:59,680 --> 00:57:02,080
Speaker 1: the eel currentlyze things today and people just say it

1071
00:57:02,120 --> 00:57:05,120
Speaker 1: with blatant fact, with a lot of confidence. It's not

1072
00:57:05,640 --> 00:57:07,320
Speaker 1: That's why it's called a con game, right, It's a

1073
00:57:07,360 --> 00:57:10,440
Speaker 1: confidence game. You gotta come across the sharp so um.

1074
00:57:10,760 --> 00:57:14,680
Speaker 1: You know, again, sometimes we misstate facts, but I'm always

1075
00:57:14,719 --> 00:57:17,880
Speaker 1: willing to retract the statement if that's indeed the case.

1076
00:57:18,280 --> 00:57:20,840
Speaker 1: But at least if you're gonna, you know, spread something around.

1077
00:57:21,200 --> 00:57:23,520
Speaker 1: Let's try to make it somewhat factual, and our our

1078
00:57:23,640 --> 00:57:26,760
Speaker 1: last lightning round, um, give us words to live by

1079
00:57:26,960 --> 00:57:31,280
Speaker 1: or your favorite motto. It's out of I mean, you

1080
00:57:31,400 --> 00:57:33,440
Speaker 1: should at least prep me on that one. I will

1081
00:57:33,480 --> 00:57:35,640
Speaker 1: prep I prep you on the next section. This one.

1082
00:57:35,760 --> 00:57:39,040
Speaker 1: I wanted. I wanted this to be surprised as as

1083
00:57:39,080 --> 00:57:42,160
Speaker 1: you do. Yeah, I mean, I think you know, simply

1084
00:57:42,200 --> 00:57:45,160
Speaker 1: as honestly is the best policy. We're in the business

1085
00:57:45,200 --> 00:57:48,040
Speaker 1: of being fiduciaries, and when you we see these things

1086
00:57:48,080 --> 00:57:50,840
Speaker 1: where people are you know, conning clients and things, it

1087
00:57:50,880 --> 00:57:53,280
Speaker 1: makes our jobs harder. We're trying to come out factual.

1088
00:57:53,320 --> 00:57:55,720
Speaker 1: We're trying to give things, so you know, maybe it's

1089
00:57:55,760 --> 00:57:59,640
Speaker 1: the golden rules like do onto others as It sounds

1090
00:57:59,720 --> 00:58:02,560
Speaker 1: kind of of corny, but it's a compliance friendly answer

1091
00:58:02,640 --> 00:58:06,160
Speaker 1: to right, So there we go. Let's jump to our

1092
00:58:06,360 --> 00:58:10,200
Speaker 1: longer form favorite questions that we ask all of our guests.

1093
00:58:10,640 --> 00:58:13,600
Speaker 1: Tell us the most important thing that people don't know

1094
00:58:13,800 --> 00:58:18,720
Speaker 1: about your background, the most important thing about the background.

1095
00:58:19,640 --> 00:58:22,200
Speaker 1: You know that I had no intention of getting this business,

1096
00:58:22,440 --> 00:58:25,120
Speaker 1: you know, I mean I was just a lost um,

1097
00:58:25,360 --> 00:58:29,080
Speaker 1: you know, teenager into a young adult and just looking

1098
00:58:29,200 --> 00:58:32,760
Speaker 1: for something to do. And um, and that was grad school.

1099
00:58:33,240 --> 00:58:35,520
Speaker 1: Grad school, I've found it. And actually at Florida State,

1100
00:58:35,560 --> 00:58:38,840
Speaker 1: I really found it because I started to really, um,

1101
00:58:39,520 --> 00:58:41,240
Speaker 1: kind of all of all the maths really started to

1102
00:58:41,320 --> 00:58:43,800
Speaker 1: click finally. You know, people talk about the aha Eureka

1103
00:58:43,920 --> 00:58:47,320
Speaker 1: moment and I finally had it where these subjects kind

1104
00:58:47,320 --> 00:58:49,600
Speaker 1: of started tying together all of a sudden and I

1105
00:58:49,720 --> 00:58:53,080
Speaker 1: felt like, I, Okay, now it all makes sense. Perhaps

1106
00:58:53,120 --> 00:58:55,000
Speaker 1: I was teaching too right, I was. I was a

1107
00:58:55,200 --> 00:58:58,320
Speaker 1: teaching assistant, which I taught calculus and the likes. And

1108
00:58:58,840 --> 00:59:00,960
Speaker 1: I think that really helped to try and explain to

1109
00:59:01,000 --> 00:59:02,800
Speaker 1: people not just you know, do they have to be

1110
00:59:02,960 --> 00:59:05,480
Speaker 1: visual or the a oral? Um, you know, what kind

1111
00:59:05,520 --> 00:59:08,040
Speaker 1: of learner are you? And trying to get different perspectives

1112
00:59:08,080 --> 00:59:11,200
Speaker 1: so um, you know again, and I think that's what

1113
00:59:11,320 --> 00:59:14,200
Speaker 1: helps with this job is you know, we are narrators

1114
00:59:14,240 --> 00:59:16,280
Speaker 1: at times, right, we're giving out ideas, we're trying to

1115
00:59:16,320 --> 00:59:19,720
Speaker 1: explain why we're thinking what we're thinking. And um, you know,

1116
00:59:19,800 --> 00:59:21,280
Speaker 1: if you want to go back to the Pet Peeves

1117
00:59:21,360 --> 00:59:23,600
Speaker 1: question that you asked earlier, you know, I hate when

1118
00:59:23,640 --> 00:59:26,840
Speaker 1: people say, well, you're just talking your book the answers

1119
00:59:26,960 --> 00:59:30,240
Speaker 1: you're absolutely right talking our book. Why Because we did

1120
00:59:30,280 --> 00:59:33,400
Speaker 1: a lot of analysis to position that book and here's

1121
00:59:33,480 --> 00:59:37,560
Speaker 1: the data. You're absolutely I'm telling you why we it's

1122
00:59:37,600 --> 00:59:39,800
Speaker 1: a chicken and egg thing. You're not talking your book

1123
00:59:39,840 --> 00:59:42,000
Speaker 1: to just go out and sell it. The book exists

1124
00:59:42,040 --> 00:59:45,440
Speaker 1: because of the underlying philosophy and the data behind. Absolutely right,

1125
00:59:45,480 --> 00:59:47,200
Speaker 1: and take it or leave it. If you like the

1126
00:59:47,240 --> 00:59:49,920
Speaker 1: way we think, then maybe you should invest with us.

1127
00:59:50,000 --> 00:59:52,800
Speaker 1: If you don't, it's fine. Um, you know other people

1128
00:59:52,880 --> 00:59:57,120
Speaker 1: may so. Who are some of your early mentors? Yeah,

1129
00:59:57,200 --> 01:00:01,040
Speaker 1: I mean from a financial perspective. Have I had various

1130
01:00:01,120 --> 01:00:05,320
Speaker 1: layers of bosses too over time? Obviously admired Jeffrey Gunlock,

1131
01:00:05,400 --> 01:00:07,600
Speaker 1: you know, being there, I worked for one of his

1132
01:00:07,680 --> 01:00:10,200
Speaker 1: guys named Claude Herb for a while. Um. Taught me

1133
01:00:10,280 --> 01:00:13,320
Speaker 1: how to read a lot of financial literacy. He's written

1134
01:00:13,320 --> 01:00:16,040
Speaker 1: a lot, he's won like a Graham Dat award. Um.

1135
01:00:16,200 --> 01:00:17,880
Speaker 1: You know he's running some scrolls over the years to

1136
01:00:18,040 --> 01:00:20,680
Speaker 1: good researcher and really taught me to think about every

1137
01:00:20,800 --> 01:00:23,280
Speaker 1: single asset class and you know, don't trust the day

1138
01:00:23,360 --> 01:00:26,800
Speaker 1: to keep grinding through it. Um. Good lessons there. Um.

1139
01:00:27,000 --> 01:00:29,080
Speaker 1: And you know there's the people that I've read like

1140
01:00:29,280 --> 01:00:31,400
Speaker 1: I would even say, like one guy I've only met

1141
01:00:31,520 --> 01:00:34,920
Speaker 1: once in person, Cliff Assess, reading materials from UM and

1142
01:00:35,080 --> 01:00:37,440
Speaker 1: so UM. I spent a lot of time on SSR

1143
01:00:37,600 --> 01:00:39,960
Speaker 1: and you know, checking out what's what's the new stuff

1144
01:00:40,000 --> 01:00:42,320
Speaker 1: out there and so UM. There's a lot of people

1145
01:00:42,400 --> 01:00:44,600
Speaker 1: that I'm forgetting right now. But you know again that

1146
01:00:44,680 --> 01:00:46,920
Speaker 1: probably don't even know who the heck I am, but

1147
01:00:47,000 --> 01:00:48,920
Speaker 1: have been big fans of their work and what they

1148
01:00:49,000 --> 01:00:51,600
Speaker 1: put out. So your referenced Cliff Assness, tell me some

1149
01:00:51,720 --> 01:00:55,360
Speaker 1: other investors who influenced your approach to investment. Yeah, I

1150
01:00:55,440 --> 01:00:57,360
Speaker 1: think you know, you gotta pull out Rob or not

1151
01:00:57,520 --> 01:00:59,880
Speaker 1: in there too, with what he's done and kind of valuation,

1152
01:01:00,080 --> 01:01:02,440
Speaker 1: and I'm gonna go before the factor stuff. You know,

1153
01:01:02,920 --> 01:01:05,200
Speaker 1: a lot of his stuff on on valuation I think

1154
01:01:05,400 --> 01:01:09,120
Speaker 1: was very very groundbreaking at the time too. Um you

1155
01:01:09,240 --> 01:01:12,080
Speaker 1: just just pre smart data, smart beta. So if you

1156
01:01:12,120 --> 01:01:13,800
Speaker 1: go back to the eighties, I mean he was always

1157
01:01:13,800 --> 01:01:17,480
Speaker 1: talking about multiples and really how those of driving sorry,

1158
01:01:17,840 --> 01:01:20,479
Speaker 1: how those drove returns over years. A lot of people

1159
01:01:20,480 --> 01:01:23,040
Speaker 1: don't think about it's all divid and discount model. They

1160
01:01:23,040 --> 01:01:25,320
Speaker 1: don't think about the valuation components. And he's tried to

1161
01:01:25,400 --> 01:01:29,400
Speaker 1: apply that to smart beta factors too. There's a you know,

1162
01:01:29,520 --> 01:01:32,120
Speaker 1: there's a big debate between him and Asnes today about

1163
01:01:32,480 --> 01:01:35,200
Speaker 1: you know, well, really if the baskets turnover snifflely, is

1164
01:01:35,240 --> 01:01:39,400
Speaker 1: it really evaluation expands? According to Cliff, the debate is over. Um.

1165
01:01:39,720 --> 01:01:42,200
Speaker 1: I think in the last piece Cliff sent it's over

1166
01:01:42,680 --> 01:01:46,000
Speaker 1: unless you want more, you know. Um. But again, uh,

1167
01:01:46,360 --> 01:01:49,120
Speaker 1: you know, there's been a lot of just kind of

1168
01:01:49,160 --> 01:01:54,560
Speaker 1: academic works like the uh the studies like from Ibbotson

1169
01:01:54,680 --> 01:01:57,680
Speaker 1: and Seeking phil things like that. Um. I'm just kind

1170
01:01:57,720 --> 01:02:00,640
Speaker 1: of a student of history of the financial markets too,

1171
01:02:00,920 --> 01:02:02,800
Speaker 1: because I think there's a lot to be gleamed there.

1172
01:02:02,840 --> 01:02:04,720
Speaker 1: It's not this cutting edge piece that really gives you

1173
01:02:04,800 --> 01:02:09,000
Speaker 1: the most information. It's respecting other periods that have similarities.

1174
01:02:09,400 --> 01:02:12,000
Speaker 1: And no two crises look the same. Uh, so don't

1175
01:02:12,040 --> 01:02:14,280
Speaker 1: expect the last one to hit in the next time. So,

1176
01:02:14,480 --> 01:02:16,920
Speaker 1: speaking of history, let's let's talk about some of your

1177
01:02:16,960 --> 01:02:19,560
Speaker 1: favorite books. What do you read for fun, be it

1178
01:02:19,920 --> 01:02:23,520
Speaker 1: finance or nonfinance, fiction or nonfiction. Yeah, I think one

1179
01:02:23,560 --> 01:02:26,960
Speaker 1: of the best books. Um. Early on in my career,

1180
01:02:27,120 --> 01:02:29,280
Speaker 1: I was trying to read all these financial literature, you know,

1181
01:02:29,280 --> 01:02:31,480
Speaker 1: so you start the Michael Lewis is and you know,

1182
01:02:31,600 --> 01:02:34,360
Speaker 1: like monkey business, all these things, and one of the

1183
01:02:34,440 --> 01:02:36,960
Speaker 1: ones that really got a hold of me was Bernstein,

1184
01:02:37,040 --> 01:02:40,200
Speaker 1: Peter Bernstein's book Against the Gods. Man, is that an

1185
01:02:40,240 --> 01:02:43,560
Speaker 1: amazing book? It is? And the perspectives I think is

1186
01:02:43,640 --> 01:02:46,720
Speaker 1: what is what really struck me within it? And what

1187
01:02:46,920 --> 01:02:50,440
Speaker 1: you're talking about, well, you know, five hundred thousands of

1188
01:02:50,520 --> 01:02:53,960
Speaker 1: years ago, people just blame the gods. There's no risk, right,

1189
01:02:54,080 --> 01:02:56,480
Speaker 1: it's the god's fault. And then man, I kind of

1190
01:02:56,480 --> 01:02:58,880
Speaker 1: think that today almost right, there's some people out there

1191
01:02:59,000 --> 01:03:01,280
Speaker 1: still say it's not me that did something wrong. Gets

1192
01:03:01,320 --> 01:03:04,000
Speaker 1: you know, let's blame someone else. And the evolution of

1193
01:03:04,320 --> 01:03:07,640
Speaker 1: probability theory. And you know, again it's funny how it's

1194
01:03:07,640 --> 01:03:11,520
Speaker 1: always gambling that starts our station and probability theory, but

1195
01:03:11,840 --> 01:03:15,200
Speaker 1: trying to quantify things and understand it, and if you're

1196
01:03:15,280 --> 01:03:17,600
Speaker 1: going to get in the financial business or the investment

1197
01:03:17,640 --> 01:03:21,800
Speaker 1: management business, I mean this is thinking about risk is imperative.

1198
01:03:22,360 --> 01:03:24,920
Speaker 1: And again it leads you to the cliffhanger at the end.

1199
01:03:24,960 --> 01:03:26,840
Speaker 1: It doesn't ever give you the answer. But I think

1200
01:03:27,000 --> 01:03:29,800
Speaker 1: that's the right answer to risk management, is that there

1201
01:03:29,960 --> 01:03:33,120
Speaker 1: is no perfect answer. We have all these models. Everybody

1202
01:03:33,200 --> 01:03:36,200
Speaker 1: has all these great data points and they're overfitted. Right,

1203
01:03:36,280 --> 01:03:38,160
Speaker 1: we don't know what the next thing is. Most people

1204
01:03:38,240 --> 01:03:40,439
Speaker 1: aren't predicting the crash. When it happens, you're always gonna

1205
01:03:40,440 --> 01:03:44,440
Speaker 1: get someone who's been so against the gods. That's by

1206
01:03:44,440 --> 01:03:46,440
Speaker 1: the way, I've never read his other one of his

1207
01:03:46,480 --> 01:03:50,720
Speaker 1: other books called The Power of Gold. That's literally sitting

1208
01:03:50,840 --> 01:03:53,720
Speaker 1: next up. I'll take it as a recommendation. I liked

1209
01:03:53,960 --> 01:03:59,040
Speaker 1: Bookstaber's book on a Demon of Our Own Design Interesting,

1210
01:03:59,080 --> 01:04:01,520
Speaker 1: that was a really good one to um. And again

1211
01:04:01,880 --> 01:04:04,480
Speaker 1: that was trying to quantify things more so the parallels

1212
01:04:04,480 --> 01:04:06,280
Speaker 1: here kind the wrist side to the effect of of

1213
01:04:06,400 --> 01:04:12,160
Speaker 1: derivatives and how completely unanticipated the average investor unaware the

1214
01:04:12,200 --> 01:04:15,320
Speaker 1: average investor was. Yeah, and so um, you know, I

1215
01:04:15,360 --> 01:04:17,360
Speaker 1: don't read a lot of fiction, you know, I spend

1216
01:04:17,400 --> 01:04:19,240
Speaker 1: more time, as I said, kind of the SSR in

1217
01:04:19,320 --> 01:04:21,680
Speaker 1: and things. But those those are kind of two things

1218
01:04:21,760 --> 01:04:26,280
Speaker 1: that really resonated. Well, um, you know the recent financial

1219
01:04:26,320 --> 01:04:28,600
Speaker 1: books I've read recently and have give me one more.

1220
01:04:28,680 --> 01:04:30,080
Speaker 1: We have to have a third book. Oh I didn't

1221
01:04:30,080 --> 01:04:32,920
Speaker 1: know yet, have three? Well, I've just made that rule up. Okay, well,

1222
01:04:33,680 --> 01:04:36,800
Speaker 1: if we're gonna go three, I'll go back to Uh,

1223
01:04:37,000 --> 01:04:40,400
Speaker 1: I'll take Michael Lewis's money Ball though. Yeah yeah, but

1224
01:04:40,600 --> 01:04:43,440
Speaker 1: I'm a baseball guy, so you know, from a standpoint,

1225
01:04:43,480 --> 01:04:46,440
Speaker 1: I liked the stats. Um, there's something about it, so

1226
01:04:47,080 --> 01:04:50,520
Speaker 1: it's fantastic. And then he I, actually, i've never seen

1227
01:04:50,560 --> 01:04:53,640
Speaker 1: the movie. Uh, the movie is great. I should only recommended.

1228
01:04:54,240 --> 01:04:58,760
Speaker 1: Lewis says that he missed the major point of money Ball,

1229
01:04:59,400 --> 01:05:03,800
Speaker 1: which Richard Taylor and Cass Sunstein reminded him, was Hey,

1230
01:05:04,080 --> 01:05:07,720
Speaker 1: using all this work from Amos Tversky and Danny Kahneman,

1231
01:05:07,840 --> 01:05:11,120
Speaker 1: which is what led him to the most, which is

1232
01:05:11,200 --> 01:05:13,600
Speaker 1: really if you haven't read that, I have read that one.

1233
01:05:13,800 --> 01:05:16,800
Speaker 1: It didn't really string. It's very different. It didn't resonate

1234
01:05:16,840 --> 01:05:19,160
Speaker 1: as much with me. Um. But I do like the

1235
01:05:19,200 --> 01:05:21,880
Speaker 1: Taylor school of thought too, you know, talking more and

1236
01:05:21,920 --> 01:05:25,240
Speaker 1: Mortar Professor Schiller love the Behavioral Side too, and did

1237
01:05:25,280 --> 01:05:27,800
Speaker 1: you speak But speaking of Lewis, did you ever read

1238
01:05:27,880 --> 01:05:30,480
Speaker 1: The blind Side? I did? Would you think of it?

1239
01:05:30,560 --> 01:05:32,840
Speaker 1: I did like it, um, except that you know the

1240
01:05:32,920 --> 01:05:35,480
Speaker 1: opening scene you know, didn't resonate well with me as

1241
01:05:35,480 --> 01:05:39,200
Speaker 1: a forty Niners fan. Um, you know, with lt taking

1242
01:05:39,240 --> 01:05:44,000
Speaker 1: out you know, the career of Montana. So I got

1243
01:05:44,080 --> 01:05:46,040
Speaker 1: through that and I thought it was a good book. Again,

1244
01:05:46,240 --> 01:05:48,760
Speaker 1: not a movie. I never watched the movie though, so

1245
01:05:49,320 --> 01:05:51,440
Speaker 1: I only have you for a few more minutes. Let

1246
01:05:51,520 --> 01:05:55,880
Speaker 1: me jump through my last favorite questions. Tell us about

1247
01:05:55,920 --> 01:06:00,760
Speaker 1: a time you failed and what you learned from the experience. Well, um,

1248
01:06:01,720 --> 01:06:03,920
Speaker 1: you know, the failure stuff is hard to recognize. But

1249
01:06:04,640 --> 01:06:07,240
Speaker 1: you know, oh no, no, I mean I think it's

1250
01:06:07,280 --> 01:06:10,080
Speaker 1: the best thing you do to learn. Um. But you know,

1251
01:06:10,240 --> 01:06:13,920
Speaker 1: as an investor to just um you know again starting

1252
01:06:13,920 --> 01:06:16,960
Speaker 1: probably with the personal accounts to just um, you know,

1253
01:06:17,240 --> 01:06:20,200
Speaker 1: getting over confident, you know, as a young young trader,

1254
01:06:20,600 --> 01:06:23,400
Speaker 1: you know, you think you know everything. Um. You know,

1255
01:06:23,560 --> 01:06:25,919
Speaker 1: I love the options market because you don't have much money,

1256
01:06:26,000 --> 01:06:28,280
Speaker 1: so it's a good way to leverage a bat um

1257
01:06:28,520 --> 01:06:31,840
Speaker 1: and you find the undoings of things, and um, how

1258
01:06:32,080 --> 01:06:35,480
Speaker 1: other people can corner you in positions um think about

1259
01:06:35,640 --> 01:06:37,760
Speaker 1: you know, kind of during the financial crisis, people step

1260
01:06:37,840 --> 01:06:40,400
Speaker 1: in and back companies too, and probably should have been

1261
01:06:40,440 --> 01:06:43,120
Speaker 1: playing around with some of those trades too. But you know,

1262
01:06:43,400 --> 01:06:46,600
Speaker 1: um in you know personal life too, you know, I

1263
01:06:46,680 --> 01:06:49,640
Speaker 1: mean I've been moderately successful, never was you know, the

1264
01:06:49,760 --> 01:06:53,520
Speaker 1: top student in in things. And so I guess probably

1265
01:06:53,640 --> 01:06:55,960
Speaker 1: one of the biggest failings too, was when I was

1266
01:06:56,040 --> 01:07:01,240
Speaker 1: in the pure uh abstract math or pure math mathematics. Um,

1267
01:07:01,440 --> 01:07:03,680
Speaker 1: you know, there was some just tough times there where

1268
01:07:03,680 --> 01:07:06,360
Speaker 1: your brain doesn't click. You just don't get it. There's

1269
01:07:06,400 --> 01:07:10,120
Speaker 1: no examples. You're talking about proving these delta epsilon proofs,

1270
01:07:10,160 --> 01:07:13,560
Speaker 1: which everybody's already sleep by now. Um, but just you know,

1271
01:07:13,840 --> 01:07:16,200
Speaker 1: really just getting my teeth kicked in and that stuff

1272
01:07:16,600 --> 01:07:19,000
Speaker 1: and bouncing back, you know, and so you know, some

1273
01:07:19,160 --> 01:07:21,280
Speaker 1: of it is hard work. You know, as all the

1274
01:07:21,320 --> 01:07:24,040
Speaker 1: sports athletes say adversity, I don't think in a game's

1275
01:07:24,040 --> 01:07:26,480
Speaker 1: adversity by the way. I think it's a little overused there.

1276
01:07:27,000 --> 01:07:29,760
Speaker 1: But there is something to be said from from failing

1277
01:07:29,880 --> 01:07:32,120
Speaker 1: and learning from it and picking up and brushing itself

1278
01:07:32,160 --> 01:07:34,120
Speaker 1: off and yeah, and you have to do that and

1279
01:07:34,240 --> 01:07:37,480
Speaker 1: so again, and then just recognizing that, Look, you can't

1280
01:07:37,520 --> 01:07:40,480
Speaker 1: be an expert at everything, right, There's certain things you

1281
01:07:40,520 --> 01:07:42,400
Speaker 1: can only there's only so much time and there's so

1282
01:07:42,520 --> 01:07:45,400
Speaker 1: much brain capacity we have unless maybe our cliff um,

1283
01:07:45,560 --> 01:07:47,920
Speaker 1: you know that you can absorb all these topics and

1284
01:07:48,040 --> 01:07:50,640
Speaker 1: so you know, dedicate yourself to something. And you know,

1285
01:07:50,880 --> 01:07:54,000
Speaker 1: I think I've you know, I've tried sports some I'm

1286
01:07:54,040 --> 01:07:56,080
Speaker 1: not good at, you know, and I'm never gonna try

1287
01:07:56,120 --> 01:07:57,960
Speaker 1: them again. So, so, speaking of that, what do you

1288
01:07:58,040 --> 01:08:01,040
Speaker 1: do to stay mentally and physical really fit outside of

1289
01:08:01,080 --> 01:08:04,720
Speaker 1: the office? What do you you cold right now? Outside

1290
01:08:04,800 --> 01:08:08,640
Speaker 1: of of the bubonic plague? When when you're not typhoid? Mary,

1291
01:08:08,760 --> 01:08:11,200
Speaker 1: what do you do to relax out of the office? Yeah,

1292
01:08:11,240 --> 01:08:13,480
Speaker 1: I just um, you know, I do some reading here

1293
01:08:13,520 --> 01:08:16,720
Speaker 1: and there. Um, you know, I just um, I live

1294
01:08:16,760 --> 01:08:20,160
Speaker 1: in Santa Monica, just kind of kick back, enjoy kind

1295
01:08:20,160 --> 01:08:23,200
Speaker 1: of lifestyle there and signs check out or you know,

1296
01:08:24,000 --> 01:08:26,160
Speaker 1: I don't know how to surf. It's embarrassing. You're right

1297
01:08:26,200 --> 01:08:28,400
Speaker 1: by meb you should have met I know. I he

1298
01:08:28,520 --> 01:08:32,560
Speaker 1: did offer, he did offer the past. Yeah, And I

1299
01:08:32,560 --> 01:08:34,880
Speaker 1: don't know if he wants to see me. I'm the

1300
01:08:34,920 --> 01:08:36,960
Speaker 1: only the only thing I'm really good at sinking. So

1301
01:08:37,160 --> 01:08:40,080
Speaker 1: I have been doing some scuba diving lately. Um, you know.

1302
01:08:40,200 --> 01:08:42,840
Speaker 1: But the thing about the scuba diving is I'm still

1303
01:08:42,960 --> 01:08:46,200
Speaker 1: just getting familiar with the environment. You want to talk about.

1304
01:08:46,240 --> 01:08:49,160
Speaker 1: Something scary is watching those those things just move around

1305
01:08:49,200 --> 01:08:52,760
Speaker 1: in their own environments. So quickly. Which anything, I'll say,

1306
01:08:52,760 --> 01:08:55,519
Speaker 1: even a sea turtle. These big sea turtles probably the

1307
01:08:55,560 --> 01:08:58,080
Speaker 1: most feared I've ever been scuba dives. Not the little sharks.

1308
01:08:58,520 --> 01:09:01,280
Speaker 1: It's the hundred pound a hundred fifty pound sea turtle.

1309
01:09:01,360 --> 01:09:03,400
Speaker 1: Just with the turbo jets go and buy you buzzing

1310
01:09:03,439 --> 01:09:07,559
Speaker 1: the tower. So and I feel helpless. So um, at

1311
01:09:07,640 --> 01:09:09,880
Speaker 1: least I won't call it a failure. Yes, I was

1312
01:09:09,920 --> 01:09:12,240
Speaker 1: a wiss at the time, and UM, I'm better now.

1313
01:09:12,400 --> 01:09:15,400
Speaker 1: You gotta put yourself in someone's environments. So and then um,

1314
01:09:15,479 --> 01:09:17,920
Speaker 1: our last two questions, What sort of advice would you

1315
01:09:17,960 --> 01:09:21,960
Speaker 1: give a millennial who was interested in a career in finance. Yeah,

1316
01:09:22,560 --> 01:09:25,559
Speaker 1: you gotta be good. It's highly competitive now. Um, there's

1317
01:09:25,560 --> 01:09:28,400
Speaker 1: a lot of consolidation in the in the industry. Be

1318
01:09:28,560 --> 01:09:33,240
Speaker 1: well read in history, um, you know, specially political events. Um.

1319
01:09:33,680 --> 01:09:36,960
Speaker 1: Financial history is extremely important. It's one great thing about

1320
01:09:37,080 --> 01:09:38,960
Speaker 1: you know, grad school and thing you learn history of

1321
01:09:39,040 --> 01:09:42,439
Speaker 1: subjects to. I think that's very pertinent. And you know,

1322
01:09:42,600 --> 01:09:45,679
Speaker 1: be open and listen. Um. You know, I think there's

1323
01:09:45,680 --> 01:09:47,640
Speaker 1: a lot of good people in the industry around you.

1324
01:09:48,200 --> 01:09:50,400
Speaker 1: Be the sponge, you know, make sure you you you

1325
01:09:50,560 --> 01:09:54,719
Speaker 1: kind of absorb that and you know, read scholarly articles.

1326
01:09:55,040 --> 01:09:57,920
Speaker 1: You may not understand everything, but just press through. And

1327
01:09:58,320 --> 01:10:00,120
Speaker 1: the best thing to do when you find something you like,

1328
01:10:00,280 --> 01:10:03,120
Speaker 1: you find article like look at the footnotes. Education is

1329
01:10:03,640 --> 01:10:06,160
Speaker 1: the key here. And our final question, what is it

1330
01:10:06,360 --> 01:10:09,640
Speaker 1: that you know about investing today that you wish you

1331
01:10:09,680 --> 01:10:14,360
Speaker 1: knew twenty years ago that you're never gonna know at all? One? Um,

1332
01:10:14,800 --> 01:10:18,160
Speaker 1: mathematical models are not perfect. They are tools. They're not

1333
01:10:18,320 --> 01:10:23,360
Speaker 1: that albeit end game to everything. Um. And there's going

1334
01:10:23,439 --> 01:10:26,920
Speaker 1: to be things that behave outside of your control. Um.

1335
01:10:27,240 --> 01:10:29,479
Speaker 1: You know, so that can be the security you buy

1336
01:10:29,560 --> 01:10:32,640
Speaker 1: that just tanks, it can be you know, um, the

1337
01:10:32,720 --> 01:10:35,400
Speaker 1: thesis you have and you realize all your bets are correlated,

1338
01:10:35,400 --> 01:10:38,639
Speaker 1: they're all the same thesis. Um, that's something very important.

1339
01:10:39,000 --> 01:10:40,719
Speaker 1: I see that a lot on these top ten lists

1340
01:10:40,800 --> 01:10:42,439
Speaker 1: in here. I know you have your what I did

1341
01:10:42,560 --> 01:10:46,800
Speaker 1: right and wrong kind of stuff or yeah right the

1342
01:10:46,840 --> 01:10:50,360
Speaker 1: mayapa and so UM. You know understand that you know

1343
01:10:51,040 --> 01:10:52,680
Speaker 1: you've got to have that diversity in there, and that

1344
01:10:52,800 --> 01:10:56,479
Speaker 1: that's very important too, because sometimes you think you talk

1345
01:10:56,560 --> 01:10:59,200
Speaker 1: yourself and this idea that you have all these trades

1346
01:10:59,240 --> 01:11:01,760
Speaker 1: on but they're all just being long the dollar right

1347
01:11:01,800 --> 01:11:03,479
Speaker 1: when you really break them down or something like that.

1348
01:11:03,600 --> 01:11:07,040
Speaker 1: So make sure that you actually have those um you know,

1349
01:11:07,160 --> 01:11:11,200
Speaker 1: different exposure, your portfolio and m you know again, I

1350
01:11:11,280 --> 01:11:13,639
Speaker 1: think the best thing is, you know you come out cocky.

1351
01:11:13,800 --> 01:11:16,200
Speaker 1: You studied all this math. I got the perfect model

1352
01:11:16,280 --> 01:11:20,000
Speaker 1: for this. No way such no such things. So thank

1353
01:11:20,040 --> 01:11:23,080
Speaker 1: you Jeff for being so generous with your time. Appreciated, Barry. Thanks.

1354
01:11:23,280 --> 01:11:26,160
Speaker 1: We have been speaking with Jeff Sherman. He is the

1355
01:11:26,479 --> 01:11:30,760
Speaker 1: deputy Chief investment officer at Double Aligned Capital. UH. If

1356
01:11:30,880 --> 01:11:33,320
Speaker 1: you like this conversation, be sure to look up an

1357
01:11:33,360 --> 01:11:37,760
Speaker 1: Inch or down an Inch on Apple iTunes, Overcast, SoundCloud, Bloomberg,

1358
01:11:37,840 --> 01:11:41,160
Speaker 1: wherever final podcasts are sold, and you can see any

1359
01:11:41,280 --> 01:11:44,360
Speaker 1: of the other hundred and sixty five or so h

1360
01:11:44,479 --> 01:11:48,000
Speaker 1: such podcasts that we've done previously. We love your comments,

1361
01:11:48,080 --> 01:11:52,240
Speaker 1: feedback and suggestions right to us at m IB podcast

1362
01:11:52,320 --> 01:11:56,120
Speaker 1: at Bloomberg dot net. Medina Partwana is our producer and

1363
01:11:56,240 --> 01:11:59,840
Speaker 1: audio engineer. Taylor Riggs as our booker. Michael bat Nick

1364
01:12:00,400 --> 01:12:04,240
Speaker 1: is our head of research. I'm Barry Ritolts. You've been

1365
01:12:04,280 --> 01:12:07,240
Speaker 1: listening to Masters in Business on Bloomberg Radio.