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

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

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Speaker 1: His name is Jeremy Schwartz. He essentially runs the research

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Speaker 1: division at Wisdom Tree Investments. I was kind of surprised

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Speaker 1: to learn his nickname is Junior Jeremy. He has been

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Speaker 1: working with Professor Jeremy Siegel at Wharton for almost twenty years.

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Speaker 1: Uh and he is a really knowledgeable and up to

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Speaker 1: his elbows in all of the specifics of creating ETFs

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Speaker 1: focusing on valuation, dividends, earnings. They have carved out a

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Speaker 1: niche in the world of investing in ETFs um that

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Speaker 1: kind of bypassed the question I was gonna ask, Hey,

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Speaker 1: what makes you guys different from filling the blank, Black Rock, Vanguard,

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Speaker 1: Dimensional funds, whatever. But Jeremy does a great job explaining

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Speaker 1: what they do, what it's like to work in a

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Speaker 1: fund where you have legends of finance like Michael Steinhardt

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Speaker 1: as chairman and Jeremy Siegel as as one of the

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Speaker 1: chief advisers, and Jonathan uh Stein putting this together. Really

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Speaker 1: a fascinating conversation for anybody who is at all interested

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Speaker 1: in indexing factor based investing valuation e t f S.

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Speaker 1: I think you're gonna find this to be an absolutely

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Speaker 1: fascinating conversation. It's something I've been trying to do for

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Speaker 1: a long time. We we Jeremy and I just keep

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Speaker 1: ships in the night. Our schedules just didn't work out,

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Speaker 1: and I'm glad I finally got him into the studio

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Speaker 1: with no further ado. My conversation with Jeremy Schwartz. My

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Speaker 1: special guest today is Jeremy Schwartz. He is the Director

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Speaker 1: of Research at Wisdom Tree Investments, where he has been

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Speaker 1: asconce since two thousand and five, having risen through the

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Speaker 1: ranks from senior analyst to deputy director to essentially head

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Speaker 1: of research at the firm. He is responsible for the

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Speaker 1: construction process and oversees all of research across the wisdom

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Speaker 1: Tree equity family. Jeremy Schwartz, Welcome to Bloomberg Berry. Thanks

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Speaker 1: for having me. Let's begin with the fun stuff. You

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Speaker 1: were um an early higher at wisdom Tree. You started

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Speaker 1: in oh five, is that right? That's right, and you

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Speaker 1: had around two thousand and eight, recently received a promotion

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Speaker 1: right into the midst of the financial collapse. What was

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Speaker 1: that collapse like while you were working at wisdom Tree

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Speaker 1: and since also a startup asset management firm going into

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Speaker 1: the biggest financial crisis. It's the Great Depression, pastic time

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Speaker 1: and you have value oing to investment philosophies, dividend based

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Speaker 1: investment strategies. Financials were big parts that dividend paying universe, right,

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Speaker 1: So it was a tough environment. Also, you know, wisdom

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Speaker 1: Tree was really trying to establish yourself as a pioneer

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Speaker 1: in e t s. It was early days in ets

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Speaker 1: when we started, oh six, there was three t s

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Speaker 1: maybe three billion under management, so we were trying to

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Speaker 1: novel indexing approach and so we were built not for

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Speaker 1: small success. We really had bigger ambitions in mind. So

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Speaker 1: we had high break events um and really trying to

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Speaker 1: have a big team to to put us on the map.

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Speaker 1: So it was certainly a challenging moment going through the

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Speaker 1: financial crisis UM. But we bottomed around three billions of

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Speaker 1: assets in two thousand nine, a little bit below three billion.

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Speaker 1: Today were forty five billions. We've seen mammoth growth over

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Speaker 1: last ten years. But yeah, it was very trying times

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Speaker 1: and you didn't know could you survive, could you get

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Speaker 1: past that crisis point. Everybody has a story about what

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Speaker 1: was going on in their shop in the midst of

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Speaker 1: the crisis, from from Vanguard to Morgan Stanley to Dave

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Speaker 1: Rosenberg tells the story of his first day at work

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Speaker 1: in the private sector was the day of the eighty

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Speaker 1: seven crash. Tell us what was going on behind the

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Speaker 1: scenes at Wisdom Tree when it felt like the world

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Speaker 1: was coming to an end. I mean, what's amazing is

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Speaker 1: I was on vacation in the first week of October.

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Speaker 1: We had a family vacation plan. We were on a

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Speaker 1: cruise in two thousand and eight, October two thousand and eight,

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Speaker 1: leaving from Asia and Asia cruise. You know, we're in

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Speaker 1: starting in Japan, going to Hong Kong, China, and I

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Speaker 1: looking at the screens on TVA, Am I gonna have

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Speaker 1: a job when I get back? I mean, it was

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Speaker 1: really unbelievable. You see the market falling ten percent um

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Speaker 1: and I didn't know, you know, where we were just

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Speaker 1: as a firm wise, like how close we were to

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Speaker 1: just not surviving during the depths of the crisis, Like

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Speaker 1: we were weeks away from not being able to make payroll?

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Speaker 1: Is that true? You were actually that close in March

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Speaker 1: of O nine. Yeah, I mean we were definitely bleeding losses.

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Speaker 1: We definitely had you know, a capital raising in March

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Speaker 1: of O nine. Um, and that put us on. The

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Speaker 1: markets turned around and we were sort of off to

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Speaker 1: the races after that. But yeah, we were we were

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Speaker 1: close in March of O nine. Did you guys have

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Speaker 1: a white night? Or was it the existing funders and

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Speaker 1: founders basically reached a little deeper into their pocket. It's

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Speaker 1: a combination. Um. So A I G came in during

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Speaker 1: two thousand nine. Uh, and there was a you know,

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Speaker 1: that's hilarious, isn't it. A I G said it's a

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Speaker 1: Wisdom Tree. Hey, let us help you out. You guys

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Speaker 1: look like you can need a little assistance. They were

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Speaker 1: investing in the investment management side. They saw the growth

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Speaker 1: potential of ETS as part of ASID management and they

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Speaker 1: did make an investment that that's that's fascinating and the

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Speaker 1: structure currently of Wisdom Trade, it's been a publicly traded company.

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Speaker 1: And one of the background is we had Jonathan Steinberger CEO,

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Speaker 1: had a media company in nineties and two thousand's and

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Speaker 1: he saw INDEXI and ETS when he was doing publishing.

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Speaker 1: Was called Individual Investor Group, and so he was. He

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Speaker 1: saw McGraw hill, he saw indexes, he saw ETS and

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Speaker 1: he's trying to create his own indexes, license him to

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Speaker 1: become ETS. Well. During the tech bubble, he sold the magazine,

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Speaker 1: kept the indexes and was trying to relaunch the firm

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Speaker 1: UM and it was really he had this shell company

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Speaker 1: is really literally a penny stock trading and then he

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Speaker 1: re raised capital and No. Four to real waunch the

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Speaker 1: business UM with Michael Steinhardt, Professor Siegell, Jim Robinson from

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Speaker 1: American Express funding the business and OH four and relaunching UM.

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Speaker 1: But that was that was the history back back then.

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Speaker 1: So it's always been publicly traded because of Johano's previous

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Speaker 1: magazine days. So that's some trinity behind behind the company.

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Speaker 1: That's quite a list of heavy hitters. Yeah, I mean,

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Speaker 1: you think going from trading at a few pennies right

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Speaker 1: before the funding, Michael funded it in oh for at

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Speaker 1: sixteen cents and the day they announced, just these these

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Speaker 1: people coming together, I think it closed at a dollar

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Speaker 1: dollar dollar fifty something like that. That Steinhardt guy is

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Speaker 1: an up and comic. Keep an eye on, Keep an

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Speaker 1: eye on him. The other thing that I find kind

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Speaker 1: of fascinating, And I think I kind of knew this

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Speaker 1: about you, but forgot about it. You were Jeremy Siegell's

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Speaker 1: assistant at Wharton. You helped him edit subsequent editions of

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Speaker 1: Stops for the Long Run. You practically co authored a

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Speaker 1: book with him. What on earth was it like being

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Speaker 1: next to Jeremy Seagal during all the unbelievable um? And

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Speaker 1: he was he was a fountain hose of knowledge. I

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Speaker 1: was just trying to soak it all in. Um. I mean,

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Speaker 1: I got so lucky of when I got to Warrant.

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Speaker 1: It was so the bubble um. That's when I first

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Speaker 1: got to warr And I've done internships at Prudential, you know,

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Speaker 1: sort of caught up in the tech craze. You know,

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Speaker 1: he wrote our Internet socks that were valued in April,

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Speaker 1: then big cap tech socks or suckers bet in March

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Speaker 1: of two thousand. I meet him right after that article

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Speaker 1: comes out. He's, you know, reevaluating his own portfolio from

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Speaker 1: being just vanguardists and fire from the nineteen seventies and

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Speaker 1: all of his researches around. Okay, I'm telling people to

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Speaker 1: sell tech stocks, yet my own portfolios vanguardist be five hundred.

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Speaker 1: What should I be doing? And so I helped him

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Speaker 1: do a lot of that research. I met him in

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Speaker 1: two thousand one. I took well, I met him through

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Speaker 1: a bunch of programs. I took his class in oh one.

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Speaker 1: I needed something to do for a few months before

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Speaker 1: I supposed to go to Australia from a semester abroad,

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Speaker 1: ended up working for him. Never went to Australia. Took

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Speaker 1: off like two years of school to work for him

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Speaker 1: full time on his books. You know, obviously set my

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Speaker 1: future path. I just dedicated really my life after that

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Speaker 1: towards working with him, and I sort of knew it

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Speaker 1: could be more than books. One day, because I sat

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Speaker 1: in his office, I heard every conversation he had, and

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Speaker 1: I knew what people wanted to do with him, and

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Speaker 1: he just you know, he was very much in low

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Speaker 1: fee I Vanguard, I buy the market, but he really

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Speaker 1: was struggling with what is the best way to index?

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Speaker 1: And so I saw there could be a potential to

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Speaker 1: do more with him. Um and wisdom Tree came along

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Speaker 1: with the perfect fit. But it was you know, he

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Speaker 1: wasn't just unbelievable mentor and teacher and still is something

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Speaker 1: I still interact with him all the time today. How

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Speaker 1: has the company changed over the past decade since the

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Speaker 1: financial crisis? You know, when we started out that the

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Speaker 1: idea was very simple, is everything's market cap weighted. You

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Speaker 1: need some relative discipline to rebounce back to value, help

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Speaker 1: try to protect investors from bubbles and things get it

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Speaker 1: really expensive. So the original conception was these value based

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Speaker 1: rebalancing dividend earnings waited type portfolios and in other words,

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Speaker 1: moving away from the heavy market cap waiting towards something

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Speaker 1: with a different flavor. Yes, the idea was to be simple,

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Speaker 1: rules based, transparent but managed valuation risk for the market.

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Speaker 1: And that was the original conception, and that just applied

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Speaker 1: in every region around the world, and we blanketed the

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Speaker 1: world with equities for that. UM. We've certainly branched out

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Speaker 1: and continue to develop products UM currency hedging became a

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Speaker 1: very major focus of the firm. UM that's one things

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Speaker 1: that's really taken off. It's one thing that I'm very

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Speaker 1: passionate about, where I think we have some really unique

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Speaker 1: ideas that are different than the way people traditionally allocated

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Speaker 1: or nationally and let's talk about that because d x

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Speaker 1: J was essentially your baby. That's the wisdom Tree Japan

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Speaker 1: Yen currency, hedged e t F and full disclosure. I

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Speaker 1: own it, clients of my firm own it when we

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Speaker 1: want a Japan exposure, and recognized that uh Abonomics and

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Speaker 1: their version of QWI was gonna really put a little

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Speaker 1: pain on the end as the dollar was getting stronger.

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Speaker 1: It was the perfect product. Thank you well, we appreciate

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Speaker 1: your support, UH And I think, listen, I think currency

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Speaker 1: is one of these very misunderstood phenomenas, and I you know,

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Speaker 1: I think so it's great to see Japan take off.

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Speaker 1: It was the first currency GT have to really illustrate

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Speaker 1: how currencies and stocks can work together. That often a

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Speaker 1: declining currency can be very good for the stocks in

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Speaker 1: that market and they move in such big directions. I mean. So,

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Speaker 1: so let me interrupt you there because there's a really

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Speaker 1: interesting story about d x J. It's been trading for

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Speaker 1: how long now. It was one of our original et

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Speaker 1: s and O six now it was unhedged when we

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Speaker 1: launched it. It was given way to Japan and it

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Speaker 1: was going it was doing better than the MSCI capway

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Speaker 1: of Japan by points a year, but it was you know,

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Speaker 1: nobody cared enough. And as we were looking at it,

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Speaker 1: and we're saying, and at the time, the end was

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Speaker 1: super strong and the stocks were super weak. Dollar was weak,

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Speaker 1: The end was strong, and things were about to reverse,

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Speaker 1: and we kept saying, this may not go on forever,

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Speaker 1: this might turn around. And you could say, everybody else

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Speaker 1: has these two bets. They have the stock bet and

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Speaker 1: the currency additional risk, and the currency moving ten to

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Speaker 1: fifteen percent a year. So while our our our value

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Speaker 1: added on the stocks that might have been a hundred

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Speaker 1: basis points, if the currency goes against you ten percentage

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Speaker 1: points a year, good luck, right, So we said, just

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Speaker 1: he'ld be so different by just focusing on the stock

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Speaker 1: alone and not take this second So when did the

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Speaker 1: currency hedge enter that particular holding? Ap All? Right, now,

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Speaker 1: I remember I haven't seen that holding, and your a

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Speaker 1: u M was fairly low, the inflows were fairly low.

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Speaker 1: It was doing okay, and then suddenly, you know, suddenly

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Speaker 1: it was like a fuse was lit and off to

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Speaker 1: the races. How did that come about? And what was

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Speaker 1: it like watching these giant inflows on a product you

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Speaker 1: essentially created? So we were the first firm to do

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Speaker 1: currency hedging in e t F FORMA. It's not a

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Speaker 1: new concept. People have been doing charging and they've been

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Speaker 1: teaching on the c f A text books for years,

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Speaker 1: but we're the first one to do it in ETS.

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Speaker 1: We've done our first one on a broader national basis

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Speaker 1: a few months before d x J, which was what

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Speaker 1: was the which is now h E d J, which

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Speaker 1: was we start off with just broad EFA hedging. And

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Speaker 1: what's interesting is we then made the second for listeners

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Speaker 1: who are IFA is your is your core international index

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Speaker 1: that people follow? It's all the twenty one developed markets

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Speaker 1: of the x US without the emerging markets Europe, Australasia, Asia,

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Speaker 1: so Hong Kong, Australia, it's it's Europe, Australia, Far East.

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Speaker 1: Is that essentially the shorthand? Yes? And so now how

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Speaker 1: do you do a currency hedge on a broad region

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Speaker 1: that has a dozen different currencies. It's really the same

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Speaker 1: way as d x J, just with multiple currencies, as

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Speaker 1: you have the underlying stock exposures, and then you add

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Speaker 1: a currency forward on top that's designed to neutralize and

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Speaker 1: get you back to just the underlying stock exposure. So

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Speaker 1: you're rolling these currency forwards on a monthly basis. But

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Speaker 1: it's pretty plain vanilla, simple um. Which is the ironic

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Speaker 1: thing is people think of hedging as the more exotic play,

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Speaker 1: and I say, it's actually more plane vanilla. So it's expensive.

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Speaker 1: You're dealing with a lot of different it's complicated, and

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Speaker 1: make the counter argument, so it's really not expensive. So

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Speaker 1: it's expensive in Brazil. Brazil costs you ten percent a

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Speaker 1: year in Ifa, you're being paid to hedge is actually

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Speaker 1: a better than free proposition, and it's been better than

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Speaker 1: free probably for the last thirty years. So the idea

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Speaker 1: that it's expensive is one of these myths that I

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Speaker 1: keep trying to come back on. And I actually feel

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Speaker 1: like we have this branding problem in hedging, which is

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Speaker 1: you can't go back and change history. But if I

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Speaker 1: if you call your international stock fund, your international double

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Speaker 1: decker fund, which is your international stock plus currency fund,

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Speaker 1: who would buy that? I don't know. They wouldn't. They

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Speaker 1: would say, I just want the stocks. I don't want

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Speaker 1: a double decker fund. And the problem is people think

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Speaker 1: of the hedge is a double decker. No, the hedges

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Speaker 1: plane vanilla stock exposure, not stock plust current. So let

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Speaker 1: me push back a little bit on the European hedge fund.

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Speaker 1: You have a eurohedged e t f UM, but not

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Speaker 1: every country in Europe is on the euro so you're

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Speaker 1: ex Switzerland, your excellent, a lot of the Nordic countries,

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Speaker 1: your Xenland. How European is the European fund. So HD

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Speaker 1: d J, which we start off as our broad EF proxy.

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Speaker 1: We saw the success in d x J. The japan

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Speaker 1: in you know, went from a hundred million. The earthquake

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Speaker 1: happened and people really started training it after literally the

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Speaker 1: earthquake to tsunami, everything that took place there that whacked

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Speaker 1: the end and suddenly you had some well the end

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Speaker 1: went up a lot, but people were starting to say

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Speaker 1: it might not continue. And that's when it really started.

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Speaker 1: That was trading five years six years ago, and so

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Speaker 1: that's when I started training and started seeing some interest UM.

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Speaker 1: And that's when we had the idea to make the

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Speaker 1: broad h E d J, which was at the start

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Speaker 1: just the whole international basket. We focused it on the

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Speaker 1: single currency, the Euro because we saw, hey, people can

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Speaker 1: grasp the idea that a single currency the end. They

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Speaker 1: started training d x J. We made the hedge h

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Speaker 1: e d J just the euro Zone only, so it

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Speaker 1: is just zero specific um. Euro is the biggest currency

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Speaker 1: in the IFA international complex. It's a third called a

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Speaker 1: third of IFA's Euro traded stocks. So we did focus

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Speaker 1: on the single currency so we can make it easier

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Speaker 1: for people to make that decision. One currency Germany, France, Spain,

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Speaker 1: all those Euro only countries. So yes, each e J

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Speaker 1: is Euro only, but you could you could have a

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Speaker 1: broader Europe fund that you hedge the euro the pound.

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Speaker 1: This was frank the Norway. You could do that too.

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Speaker 1: We've focused on Euro only. That that's what I I

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Speaker 1: think d x J is unique because you have one

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Speaker 1: country with one currency, with a fairly uniform population and

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Speaker 1: a behavior set that is very very similar. I'm not

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Speaker 1: saying everybody acts and things alike in Japan, but it

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Speaker 1: is unique in that there is no other sizeable country

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Speaker 1: other than the United States that that has that same

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Speaker 1: sort of Japan is also unique in the currency market

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Speaker 1: where you actually need a week end for the stocks

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Speaker 1: to do well. So it is correlated, right, There is

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Speaker 1: a real economic linkage between the currency and the stocks,

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Speaker 1: and you do see profits the last five years as

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Speaker 1: the currency is weaken profits have soared, so there is

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Speaker 1: a real direct economic benefit. But even for small cab

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Speaker 1: companies which are more local to Japan, even they trade

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Speaker 1: inversely correlated to the end. So Japan just the way

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Speaker 1: people trade it, you need a week end to really

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Speaker 1: be bullish Japan today. Um So it's one where when

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Speaker 1: you hedge, you actually increase the volatility for the broader

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Speaker 1: international basket where I'm talking about. That's where the opportunity

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Speaker 1: really is. You know, for the going forward basis Europe

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Speaker 1: and Japan. Maybe there's a hundred billions of assets between

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Speaker 1: Europe and Japan. Mutual funds, there's one point a trillion

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Speaker 1: dollars in IFA that are basically unhedged, but thirty percent

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Speaker 1: of Japan's now hedged, of Europe's hedged. The big opportunity

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Speaker 1: and that I'm focused on, or we had with some

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Speaker 1: tree really focused on our the EFA complex. We're adding

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Speaker 1: currency adds your expected risk profile, not your expected return profile,

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Speaker 1: you're did risk profile. That's pretty fascinating. Let's talk a

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Speaker 1: little bit about what's happening in the world of asset management.

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Speaker 1: We've heard that indexing is worse than Marxism, that this

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Speaker 1: is an American. It's the end of the world. I

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Speaker 1: think that everybody who is making those arguments are sort

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Speaker 1: of self interested in talking their own books. But let's

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Speaker 1: at least discuss how indexing might be affecting, uh, the

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Speaker 1: price discovery mechanism. What what are your views on this? Yeah,

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Speaker 1: I don't think it's worse than Marxism. It's actually the

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Speaker 1: definition of what people need. They want lower fees. Right,

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Speaker 1: Amazon is bringing down fees for retail customers, and essentially

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Speaker 1: indexing is bringing down fees for active or asset management generally. Um. Now,

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Speaker 1: there's this idea that our et s to story of

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Speaker 1: the market is that flows to passive causing this quote

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Speaker 1: unquote bubble in the markets or pushing up prices. For

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Speaker 1: every buyer there's a seller. So I just see fees

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Speaker 1: coming out of the system. Investors are being better off

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Speaker 1: with fees not going to the active managers are keeping

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Speaker 1: it in investors pockets. For you to say that the

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Speaker 1: flows too passive over the last decade, and passive is

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Speaker 1: taking a large amount of money or last decade for

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Speaker 1: them to be driving up the market prices. There people

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Speaker 1: are buying the passive, who are they selling? Are they

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Speaker 1: selling value managers? Are they selling the people who's who

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Speaker 1: buy cheaply and just buying the more expensive stuff? And

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Speaker 1: it has been a growth led market over the last

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Speaker 1: ten years. But when I look at the flows to

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Speaker 1: the styles, let's say us large cap, I don't see

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Speaker 1: the flows dramatically leaving value if anything. Or the last

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Speaker 1: ten years you've seen flows leaving growth. You're seeing active growth,

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Speaker 1: seeing out flows, and you're seeing just general trends towards indexing,

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Speaker 1: which makes you question, are the flows to passive really

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Speaker 1: driving up the prices of these sort of quote unquote

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Speaker 1: expensive parts of the market. So I see it as

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Speaker 1: a big win for investors are keeping the fees. I

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Speaker 1: don't see them as dramatically changing. And I think Vanguard

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Speaker 1: did a study saying that feed compression saved investors over

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Speaker 1: forty billion dollars over the past twenty year. That's a

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Speaker 1: lot of money, and that's going to continue. I mean

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Speaker 1: that's people people worry. You know, what percentage of the

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Speaker 1: market can be indexed. It could be a lot higher

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Speaker 1: than where we are today, and it should be a

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Speaker 1: lot higher. There's a lot of active managers who aren't

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Speaker 1: adding value, and so in the future are not adding

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Speaker 1: value active managers that Bill Miller calls them the closet index. Yeah.

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Speaker 1: I love that conversation, and it's it's I see more

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Speaker 1: and more of what we're trying to do at Wisdom

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Speaker 1: Trees is you know, we started off ten years ago

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Speaker 1: trying to provide low tracking indexes so get you very

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Speaker 1: broad exposure. Are broad diven weighted portfolios have fifteen hundred stocks,

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Speaker 1: are broad earnings waited portfolios have two thousand stocks, And

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Speaker 1: there we're tilting towards value and quality factors that we

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Speaker 1: think can add value over the market. So maybe we

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Speaker 1: add a hundred bases points over long periods of time

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Speaker 1: with two percent tracking error in the earnings indexes. That's

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Speaker 1: low tracking air portfolios. Those are the closet index trackers

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Speaker 1: Miller is talking about, and we're doing it in sort

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Speaker 1: of low fee index type format. Increasingly, where I think

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Speaker 1: the future is that we're going to be going for

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Speaker 1: the higher active share, higher alpha strategies and trying to

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Speaker 1: get more activeness into the portfolios as well. So so

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Speaker 1: let's touch on that because that's a fascinating subject. First,

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Speaker 1: I noticed you have I don't want to say a

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Speaker 1: dividend way across everything. But but dear lord, dividends are

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Speaker 1: really the mother's milk of wisdom tree? Is it? Is

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Speaker 1: it profitability and valuation? Or what is it about dividends

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Speaker 1: that are special? And the past decade is seen a

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Speaker 1: cheat money allowed a ton of buy backs? What does

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Speaker 1: what do all those buy backs due to dividends? I

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Speaker 1: personally would rather see dividends as an investor than buy backs.

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Speaker 1: But tell me your perspective. Yeah, finance one oh one,

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Speaker 1: assets are president value of cash flows for stocks? Cash

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Speaker 1: flows are dividends. Where do we do is come from?

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Speaker 1: They come from earnings. So when we started ten years

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Speaker 1: ago dividends and earnings, where the two families we created

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Speaker 1: dividends and earnings? Okay, two separate families. We launch the

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Speaker 1: US Earnings Family Global dividen. How many different funds were

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Speaker 1: in that group in in earnings? We have today approximately

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Speaker 1: six across different regions and different that's in the US.

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Speaker 1: So what are the six in the US? Total market? Large, mid, small,

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Speaker 1: And then we have some specific um sort of domestic

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Speaker 1: economy and exporter strategies. And then and what about dividends?

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Speaker 1: There's a the exact number I'm gonna lose because it's

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Speaker 1: like it's a large number. UM. So we do cover

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Speaker 1: the world with dividend focused strategies. UM. We do India.

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Speaker 1: We have an earning fund because diven end earnings fund.

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Speaker 1: India is earnings because they don't pay a lot of dividends,

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Speaker 1: and so we're the first firm to do India local

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Speaker 1: shares in two thousand eight. So we have the broadest

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Speaker 1: India Index or India Earnings Wait Index, and that's the

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Speaker 1: country we're super bullshot over. The I couldn't agree more.

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Speaker 1: But it's valuation sensitive and we wanted to own the

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Speaker 1: broadest cross sections. So the tradial Eta sixty seventy stocks,

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Speaker 1: we have two D plus stocks, so that's one where

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Speaker 1: earnings waited. We did do UM, but the idea was

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Speaker 1: dividends are the subjective measure around the world, and every

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Speaker 1: region outside the US N plus to the market pays

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Speaker 1: a divon. It's really the U S where we do

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Speaker 1: a lot of buy backs because of stock options. If

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Speaker 1: you have a stock option, you don't like to pay

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Speaker 1: a DIVD because your stock goes down by the amount

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Speaker 1: of the dividend. Because we have literally penny for penny

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Speaker 1: and so that's what when we started doing stock options.

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Speaker 1: Two is when we started paying divids less. I mean

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Speaker 1: the power issue used to be seventy in the old days.

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Speaker 1: It's been you know, thirty to pent in the last

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00:22:27,240 --> 00:22:30,800
Speaker 1: twenty thirty years. UM. But so clearly buy backs are

430
00:22:30,840 --> 00:22:33,760
Speaker 1: impacting the available cast for dividends. People are doing as

431
00:22:33,840 --> 00:22:36,359
Speaker 1: much buybacks as dividends today. So when people look at

432
00:22:36,359 --> 00:22:38,399
Speaker 1: the two percent diven yield and say we used have

433
00:22:38,400 --> 00:22:40,720
Speaker 1: a four percent diven yield, will net buy backs have

434
00:22:40,800 --> 00:22:42,679
Speaker 1: been one and a half to two percent? And so

435
00:22:42,760 --> 00:22:44,639
Speaker 1: that what that means is and they're actually net buy

436
00:22:44,680 --> 00:22:46,760
Speaker 1: back So there who docing shares out standing, which means

437
00:22:46,800 --> 00:22:49,800
Speaker 1: future dealing growth will be higher. Um. And so i've

438
00:22:49,920 --> 00:22:52,199
Speaker 1: you know, we've focused when people say, do you have

439
00:22:52,200 --> 00:22:55,240
Speaker 1: a dividend plus net buy back index, we've often set

440
00:22:55,240 --> 00:22:58,600
Speaker 1: our earnings indexes represent that because you would basically add

441
00:22:58,720 --> 00:23:01,159
Speaker 1: at historically would more technic alogy companies, which is what

442
00:23:01,560 --> 00:23:04,240
Speaker 1: had earnings and buybacks but no dividends. Now in our

443
00:23:04,320 --> 00:23:09,240
Speaker 1: large cat doing next you have more tech companies financial So, UM,

444
00:23:09,280 --> 00:23:12,119
Speaker 1: I gotta ask you the question that always has been

445
00:23:12,160 --> 00:23:16,919
Speaker 1: scratching my head on an earnings based set of holdings.

446
00:23:18,000 --> 00:23:22,560
Speaker 1: The US, we have completely wacky accounting rules and regulations.

447
00:23:23,400 --> 00:23:27,280
Speaker 1: How do you manage to square the circle of every

448
00:23:27,320 --> 00:23:30,120
Speaker 1: region of the world. Every country in the world has

449
00:23:30,160 --> 00:23:34,000
Speaker 1: our own set of accounting standards and and rules, and

450
00:23:34,040 --> 00:23:37,439
Speaker 1: you end up with, Hey, a pe of ten in

451
00:23:37,480 --> 00:23:40,359
Speaker 1: this country maybe nothing like a pe in ten of

452
00:23:40,440 --> 00:23:43,200
Speaker 1: ten in a different country. You just made my case

453
00:23:43,240 --> 00:23:45,840
Speaker 1: for divin waiting around the world. That's exactly why we

454
00:23:45,880 --> 00:23:48,640
Speaker 1: did dividends around the world was it's an objective measure.

455
00:23:48,800 --> 00:23:50,320
Speaker 1: When we started ten years ago, you didn't have to

456
00:23:50,320 --> 00:23:53,160
Speaker 1: worry about different accounting centers. Now we really don't have

457
00:23:53,240 --> 00:23:56,119
Speaker 1: any cross country earnings waited funds. I mean, we have

458
00:23:56,240 --> 00:23:59,960
Speaker 1: the India Fund. Um we do have any that's not exact.

459
00:24:00,160 --> 00:24:03,879
Speaker 1: You are emerging market consumer fund has an earnings model,

460
00:24:04,920 --> 00:24:06,440
Speaker 1: but that's you know, it's like a one off fund

461
00:24:06,440 --> 00:24:08,280
Speaker 1: for US. So so in other words, when you go

462
00:24:08,320 --> 00:24:11,320
Speaker 1: in country by country, you're really doing the valuation screen

463
00:24:11,760 --> 00:24:14,959
Speaker 1: specific to that country, and the top ten percent across

464
00:24:15,000 --> 00:24:17,600
Speaker 1: every country. What does it make a difference how their

465
00:24:17,640 --> 00:24:20,239
Speaker 1: math is. It's still the cream of the crop in

466
00:24:20,280 --> 00:24:22,760
Speaker 1: each country. And that is why dividen just cut across

467
00:24:22,760 --> 00:24:24,840
Speaker 1: all the countries, and so I think that's the that's

468
00:24:24,880 --> 00:24:27,800
Speaker 1: the key there. Um, you can fake earnings, you can't

469
00:24:27,800 --> 00:24:30,760
Speaker 1: fake dividends. For only so long can you fake the dividends.

470
00:24:31,119 --> 00:24:35,920
Speaker 1: Let's talk a little bit about the future of asset management. Um,

471
00:24:35,960 --> 00:24:39,679
Speaker 1: there's a sense that the Vanguard effect, the compression of

472
00:24:39,720 --> 00:24:44,399
Speaker 1: fees everywhere, is not just a brief phenomena or a

473
00:24:44,520 --> 00:24:48,359
Speaker 1: shallow phenomena. But hey, it's all going to zero eventually,

474
00:24:49,000 --> 00:24:52,360
Speaker 1: discuss Listen to the drive for fees lower puts more

475
00:24:52,440 --> 00:24:56,080
Speaker 1: money back in investors pockets. I think it's generally the

476
00:24:56,119 --> 00:24:58,600
Speaker 1: trend it's going in. It's across all segments, from asset

477
00:24:58,640 --> 00:25:02,920
Speaker 1: management to advisors to everywhere. Is that's where it's going.

478
00:25:03,600 --> 00:25:06,879
Speaker 1: How low can it go? It's getting close to zero.

479
00:25:06,960 --> 00:25:09,160
Speaker 1: I mean it's at a few basis points for pure beta.

480
00:25:09,200 --> 00:25:11,400
Speaker 1: I mean wisdom Tree was set up living in a

481
00:25:11,480 --> 00:25:14,639
Speaker 1: Vanguard world, and we were saying, we have our mission

482
00:25:14,640 --> 00:25:17,000
Speaker 1: in life only mission life was can we do better

483
00:25:17,080 --> 00:25:19,879
Speaker 1: than Vanguard after fees, after taxes? You got improved on

484
00:25:19,920 --> 00:25:21,919
Speaker 1: the Vanguard experience because you know they're gonna always have

485
00:25:21,960 --> 00:25:25,879
Speaker 1: the lowest fees. Nobody can compete, So they're built for

486
00:25:25,920 --> 00:25:28,680
Speaker 1: that for forty years, there's nobody even close to them,

487
00:25:29,000 --> 00:25:31,560
Speaker 1: So dimensional funds maybe, so it's no, I mean, they're

488
00:25:31,600 --> 00:25:34,560
Speaker 1: they're they're well, they're a little more expensive, they have

489
00:25:34,560 --> 00:25:38,439
Speaker 1: a little deeper research bench, but you know, they're considered

490
00:25:38,720 --> 00:25:41,960
Speaker 1: factor slash active. So it's there's a there's a little

491
00:25:42,000 --> 00:25:44,960
Speaker 1: more on it, pure beta, zero cost beta. You're going

492
00:25:45,000 --> 00:25:47,320
Speaker 1: to have that out there. But so the question is

493
00:25:47,359 --> 00:25:49,080
Speaker 1: how can you add value on top of that? So

494
00:25:49,119 --> 00:25:51,280
Speaker 1: we think of that as an investment firm. Can our

495
00:25:51,280 --> 00:25:55,960
Speaker 1: individual products add value after fees, after taxes? But then

496
00:25:56,000 --> 00:25:59,119
Speaker 1: also then how when you deliver advice, can you try

497
00:25:59,119 --> 00:26:01,880
Speaker 1: to package it in a way that adds value as well?

498
00:26:01,880 --> 00:26:04,159
Speaker 1: And that's really so our first ten years that was

499
00:26:04,160 --> 00:26:06,840
Speaker 1: in was about building great products, and I think the

500
00:26:06,880 --> 00:26:09,560
Speaker 1: next ten years is really how do we help our

501
00:26:09,600 --> 00:26:12,719
Speaker 1: clients and how do we deliver advice in a cheaper

502
00:26:12,760 --> 00:26:15,439
Speaker 1: format enabled by technology. So we're making a lot of

503
00:26:15,480 --> 00:26:19,400
Speaker 1: investments in that technology side to really help advisors grow

504
00:26:19,480 --> 00:26:22,760
Speaker 1: and and and leverage their businesses and then um, you know,

505
00:26:22,800 --> 00:26:25,399
Speaker 1: just bring costs down there as well. So let's let's

506
00:26:25,720 --> 00:26:30,840
Speaker 1: look at that um advisory firms and advisors are looking

507
00:26:30,880 --> 00:26:35,840
Speaker 1: for more than just asset management. What do you you

508
00:26:36,160 --> 00:26:38,359
Speaker 1: sit in a fairly unique position in the in the

509
00:26:38,359 --> 00:26:41,880
Speaker 1: food chain. What do you think the financial advisors are

510
00:26:41,880 --> 00:26:45,240
Speaker 1: looking for and how do you guys create something unique

511
00:26:45,359 --> 00:26:49,959
Speaker 1: for that audience. Yeah, everybody is talking about the robo world, right,

512
00:26:50,040 --> 00:26:53,080
Speaker 1: the betterments of the wellffronts and and this online direct

513
00:26:53,080 --> 00:26:57,240
Speaker 1: to consumer model. We are very advisor driven, so you

514
00:26:57,280 --> 00:27:00,000
Speaker 1: know we're we have an advisor solutions program. We made

515
00:27:00,040 --> 00:27:03,080
Speaker 1: a big investment in a firm called advisor Engine that

516
00:27:03,240 --> 00:27:06,080
Speaker 1: is really a full technology stack try to help people

517
00:27:06,119 --> 00:27:10,200
Speaker 1: manage from client on boarding, account opening digital. It's a

518
00:27:10,320 --> 00:27:13,720
Speaker 1: very digitizing your investment practice and that's gonna be an

519
00:27:13,760 --> 00:27:15,800
Speaker 1: increasing part of what we do over time. I see

520
00:27:15,840 --> 00:27:17,800
Speaker 1: it from just the conversation we've had in the last

521
00:27:17,800 --> 00:27:20,640
Speaker 1: few months going out with Advisor Engine together. Um, they're

522
00:27:20,680 --> 00:27:23,639
Speaker 1: becoming an increasing partner. But as well as you know

523
00:27:23,760 --> 00:27:27,159
Speaker 1: are we're also we've been investing in technology ourselves for

524
00:27:27,160 --> 00:27:29,919
Speaker 1: the last few years, and so we created some great tools.

525
00:27:30,000 --> 00:27:33,080
Speaker 1: We call it portfolio construction services on our website, just

526
00:27:33,240 --> 00:27:36,840
Speaker 1: digital portfolios, a way to do analytics, institutional caliber stuff

527
00:27:36,880 --> 00:27:39,200
Speaker 1: that people pay very high fees for. We're trying to

528
00:27:39,200 --> 00:27:42,200
Speaker 1: provide for free that will help you look at your portfolio,

529
00:27:42,280 --> 00:27:46,199
Speaker 1: look at different factor exposures, stress test, it creates some mappings,

530
00:27:46,440 --> 00:27:48,600
Speaker 1: edit your own what we spit back out it there

531
00:27:48,640 --> 00:27:52,240
Speaker 1: for you. So it's a really trying to help people

532
00:27:52,280 --> 00:27:55,160
Speaker 1: with their portfolio management side. That's available to any advisor

533
00:27:55,359 --> 00:27:59,520
Speaker 1: or anybody who goes to the wood and financial professionals

534
00:27:59,640 --> 00:28:02,119
Speaker 1: uh through you know, there's you gotta have to log

535
00:28:02,160 --> 00:28:04,000
Speaker 1: in on our website and that's all you need as

536
00:28:04,040 --> 00:28:06,280
Speaker 1: a financial professional and you can get access to the

537
00:28:06,320 --> 00:28:11,200
Speaker 1: portfolio tool. So you mentioned robo advisors. I'm a little

538
00:28:11,200 --> 00:28:14,679
Speaker 1: bit of a contrarian because, hey, you know what, if

539
00:28:14,720 --> 00:28:17,800
Speaker 1: you give me two hundred million dollars in venture capital

540
00:28:17,800 --> 00:28:21,119
Speaker 1: money from marketing, I could raise three or four billion dollars.

541
00:28:21,119 --> 00:28:23,520
Speaker 1: But the better way to think about it is, Wait,

542
00:28:23,880 --> 00:28:26,600
Speaker 1: you've spent a hundred million dollars to generate four or

543
00:28:26,640 --> 00:28:28,959
Speaker 1: five million dollars a year in revenue. How is that

544
00:28:29,000 --> 00:28:30,920
Speaker 1: going to take over the world. Yeah, I don't want

545
00:28:30,920 --> 00:28:34,320
Speaker 1: to comment on valuations there, but it's it's everybody's going

546
00:28:34,359 --> 00:28:36,240
Speaker 1: to have some element of that. I mean, it's that

547
00:28:36,240 --> 00:28:40,920
Speaker 1: that technology all clients are going to access their accounts online.

548
00:28:41,360 --> 00:28:45,560
Speaker 1: I think everything place already now is increasingly I mean,

549
00:28:45,600 --> 00:28:47,920
Speaker 1: if you think about it, everybody who's got a custodian

550
00:28:47,960 --> 00:28:50,640
Speaker 1: be a Schwab or TV, your fidelity, you get a

551
00:28:50,640 --> 00:28:53,280
Speaker 1: full dashboard online. You could see your holdings. You can

552
00:28:53,400 --> 00:28:57,360
Speaker 1: more or less see your performance. What what the robos

553
00:28:57,360 --> 00:28:59,680
Speaker 1: seem to do is come up with an asset allocation

554
00:28:59,760 --> 00:29:03,760
Speaker 1: mob all relative to your risk tolerance. How unique is

555
00:29:03,800 --> 00:29:06,560
Speaker 1: that and and is that gonna spread to the rest

556
00:29:06,560 --> 00:29:10,440
Speaker 1: of the industry. I think, you know, our our firm

557
00:29:10,440 --> 00:29:12,320
Speaker 1: has been investing on the advisors side. We think there

558
00:29:12,440 --> 00:29:14,160
Speaker 1: there will be some people who like to go direct

559
00:29:14,200 --> 00:29:16,800
Speaker 1: to consumer and people manage our own money and do

560
00:29:16,840 --> 00:29:19,480
Speaker 1: that through through what they're offering, and they have very

561
00:29:19,480 --> 00:29:21,960
Speaker 1: good jet you know, generic offerings. Is that Is that

562
00:29:22,000 --> 00:29:24,280
Speaker 1: going to be true for the average high net worth family.

563
00:29:24,360 --> 00:29:27,200
Speaker 1: Someone has three million dollars five million dollars in the market.

564
00:29:27,680 --> 00:29:29,320
Speaker 1: Do they want to pick up the phone and speak

565
00:29:29,360 --> 00:29:31,640
Speaker 1: to somebody or they want to log in? I think

566
00:29:31,680 --> 00:29:34,920
Speaker 1: most people there's a spa is how much of the

567
00:29:34,960 --> 00:29:39,120
Speaker 1: wealth around is is advisor overseeing versus direct? I think

568
00:29:39,160 --> 00:29:42,400
Speaker 1: we're still we've always from the beginning in position for

569
00:29:42,560 --> 00:29:45,360
Speaker 1: working with advisors and financial intermedis. I think that's how

570
00:29:45,400 --> 00:29:47,040
Speaker 1: we continue to see. You know, so all of our

571
00:29:47,080 --> 00:29:50,520
Speaker 1: investments in technology advisor solutions is really trying to help

572
00:29:50,600 --> 00:29:53,880
Speaker 1: advisors build their businesses and it's very tough to find

573
00:29:53,880 --> 00:29:56,920
Speaker 1: that individual client, and that's what we're going to continue

574
00:29:56,960 --> 00:30:00,080
Speaker 1: position for. I'm curious as to how much of a

575
00:30:00,480 --> 00:30:05,520
Speaker 1: fear of robo advisors is a generational thing that the

576
00:30:05,560 --> 00:30:09,440
Speaker 1: older advisors see the new technology and fear it, and

577
00:30:09,480 --> 00:30:11,840
Speaker 1: the younger advisors say, yeah, this is just another tool

578
00:30:11,920 --> 00:30:15,440
Speaker 1: in our another arrow in my quiver. And the research

579
00:30:15,480 --> 00:30:17,959
Speaker 1: we've seen is that even the older generations they've been

580
00:30:17,960 --> 00:30:21,160
Speaker 1: working with technology, you know, the successful people, they've been

581
00:30:21,160 --> 00:30:24,160
Speaker 1: operating with technology. So they even the seventy year olds,

582
00:30:24,200 --> 00:30:27,360
Speaker 1: they need they want your a digital experience. UM So

583
00:30:27,400 --> 00:30:30,840
Speaker 1: if you if you're not on board with upgrading your technology,

584
00:30:30,840 --> 00:30:33,520
Speaker 1: if you're still in the paper world, clients are going

585
00:30:33,560 --> 00:30:36,120
Speaker 1: to go to firms that have the digital offerings. And

586
00:30:36,160 --> 00:30:38,560
Speaker 1: so that's that's the trend that we see just continuing

587
00:30:38,560 --> 00:30:40,840
Speaker 1: and we want to help on the clients that we

588
00:30:40,920 --> 00:30:43,480
Speaker 1: work with do that and do it do it well.

589
00:30:43,840 --> 00:30:46,760
Speaker 1: So you mentioned fees earlier, we've been talking about that

590
00:30:46,840 --> 00:30:52,840
Speaker 1: for for forever. UM Very recently Fidelity introduced the concept

591
00:30:52,920 --> 00:30:56,440
Speaker 1: of the Falcrum fee, which is a reduced fee if

592
00:30:56,480 --> 00:31:00,040
Speaker 1: they're not out not out performing a particular benchmark. Is

593
00:31:00,080 --> 00:31:02,520
Speaker 1: that's something that potentially can catch on. What are your

594
00:31:02,520 --> 00:31:05,640
Speaker 1: thoughts on these fulk room fees. Conceptually, it's a very

595
00:31:05,680 --> 00:31:08,000
Speaker 1: interesting I mean, it's a it's what you would think

596
00:31:08,040 --> 00:31:10,640
Speaker 1: you want as a consumer products. If you're manager, you're

597
00:31:10,640 --> 00:31:13,560
Speaker 1: trying to outperform. Your manager doesn't outperform, you should pay less.

598
00:31:13,680 --> 00:31:16,960
Speaker 1: And so conceptually I'm I'm aligned with it. The incentives

599
00:31:17,000 --> 00:31:19,800
Speaker 1: are very hard to align it in sort of a

600
00:31:19,840 --> 00:31:23,160
Speaker 1: public vehicle like in ETFU. There are some people who

601
00:31:23,160 --> 00:31:25,600
Speaker 1: are starting to experiment with that, so we're definitely watching

602
00:31:25,640 --> 00:31:28,720
Speaker 1: that closely, UM, and and you just you want to

603
00:31:28,720 --> 00:31:30,920
Speaker 1: make sure if you're doing it, you've got align when

604
00:31:31,200 --> 00:31:34,280
Speaker 1: people are invested in the fund, you know, time periods,

605
00:31:34,360 --> 00:31:37,760
Speaker 1: the incentives for both the investors in the fund. Properly

606
00:31:37,880 --> 00:31:41,960
Speaker 1: timing up who's paying what when is not a straightforward

607
00:31:42,000 --> 00:31:45,239
Speaker 1: proposition in the public vehicle like ETFs, I mean, as

608
00:31:45,280 --> 00:31:47,680
Speaker 1: a doing a one on one, separate account where you

609
00:31:47,680 --> 00:31:50,160
Speaker 1: can manage your time horizon with your performance in the

610
00:31:50,160 --> 00:31:54,240
Speaker 1: fund super easy to think about. But as a ute

611
00:31:54,240 --> 00:31:57,160
Speaker 1: et f rapper, that's a challenge that seems challenging me.

612
00:31:57,200 --> 00:31:58,880
Speaker 1: But you know, I'm sure there's gonna be ways of

613
00:31:58,880 --> 00:32:00,800
Speaker 1: looking at that and we'll we'll study that and see

614
00:32:01,240 --> 00:32:04,400
Speaker 1: think about it. So you guys are are pretty heavy

615
00:32:04,480 --> 00:32:09,440
Speaker 1: value oriented, you're pretty heavy divinend oriented. These are part

616
00:32:09,800 --> 00:32:13,959
Speaker 1: not that dividends are. But it's the same traditional FAMA

617
00:32:14,000 --> 00:32:17,360
Speaker 1: fringe factor models. What do you think of the rise

618
00:32:17,400 --> 00:32:21,080
Speaker 1: of so called smart beta, which really is factor investing

619
00:32:21,600 --> 00:32:24,719
Speaker 1: with a little bit of a different marketing twist, and

620
00:32:24,840 --> 00:32:29,000
Speaker 1: you guys get painted with that same brush. What you

621
00:32:29,080 --> 00:32:31,160
Speaker 1: call things is always an interesting term, and we used

622
00:32:31,200 --> 00:32:35,200
Speaker 1: to call things passive alpha when we first started passive alpha,

623
00:32:35,360 --> 00:32:38,800
Speaker 1: trying to get rules based ways of generating alpha in

624
00:32:38,840 --> 00:32:41,000
Speaker 1: a lot of ways. I think what we're trying to

625
00:32:41,040 --> 00:32:43,640
Speaker 1: provide is lo fi alpha, or you could say modern alpha.

626
00:32:43,720 --> 00:32:46,560
Speaker 1: You know the idea I like that modern alpha in

627
00:32:46,560 --> 00:32:53,280
Speaker 1: other words, low fie passive technology twist. And so you're

628
00:32:53,320 --> 00:32:56,320
Speaker 1: using technology algorithms to add value. It's going to be

629
00:32:56,400 --> 00:33:01,080
Speaker 1: increasingly you're you're using smart technology, which is its century

630
00:33:01,160 --> 00:33:04,880
Speaker 1: technologies to try to add value UM and so increasingly,

631
00:33:04,960 --> 00:33:08,440
Speaker 1: where we might have been low tracking error alpha, we're

632
00:33:08,480 --> 00:33:10,760
Speaker 1: increasingly going to be going after the higher tracking air

633
00:33:10,840 --> 00:33:14,400
Speaker 1: real value added defined tracking a sort of how much

634
00:33:14,520 --> 00:33:17,000
Speaker 1: risk versus the benchmark you're taking. So we're not talking

635
00:33:17,040 --> 00:33:20,920
Speaker 1: about active share, we're talking about risk adjusted returns. Yeah,

636
00:33:21,040 --> 00:33:22,960
Speaker 1: we active share is a component of that. So the

637
00:33:23,000 --> 00:33:25,320
Speaker 1: more active share you are, the higher tracking AIR is

638
00:33:25,400 --> 00:33:27,920
Speaker 1: likely to be because the more mismatch you are from

639
00:33:27,920 --> 00:33:32,640
Speaker 1: the front. So UM, I think about it as the

640
00:33:32,680 --> 00:33:34,719
Speaker 1: closer you are to the benchmark, the lowrier tracking AIR

641
00:33:34,760 --> 00:33:37,520
Speaker 1: will be. And that's what just a total market, if

642
00:33:37,520 --> 00:33:39,120
Speaker 1: you have two thousand stocks, you're gonna have a pretty

643
00:33:39,120 --> 00:33:41,840
Speaker 1: low tracking air. Let's talk about a little bit about bonds.

644
00:33:41,880 --> 00:33:44,880
Speaker 1: We haven't gotten to fixed income at all. How are

645
00:33:44,920 --> 00:33:47,960
Speaker 1: you perceiving what's going on in that space? Can you

646
00:33:48,040 --> 00:33:51,120
Speaker 1: create alpha in the fixed income side? What? What do

647
00:33:51,160 --> 00:33:56,400
Speaker 1: you guys? Absolutely so we do. We have enhanced yield

648
00:33:56,560 --> 00:33:58,640
Speaker 1: bond indexes. And actually you know we're here in the

649
00:33:58,640 --> 00:34:01,600
Speaker 1: Bloomberg offices. Were part here with bloom Bloomberg on a

650
00:34:01,760 --> 00:34:06,560
Speaker 1: number of fixing come indexes Yield Enhanced Bloomberg Barclay's Total

651
00:34:06,640 --> 00:34:10,600
Speaker 1: fixing income indexes where you're just you know, historical yields

652
00:34:10,600 --> 00:34:12,960
Speaker 1: are as low as they've been in the US market,

653
00:34:13,239 --> 00:34:15,920
Speaker 1: duration is the highest. But can you sort of rewaight

654
00:34:16,000 --> 00:34:18,960
Speaker 1: the agg away from just treasuries, which have been huge issuance,

655
00:34:19,160 --> 00:34:22,560
Speaker 1: low yield, high duration, reweight towards credit, which is what

656
00:34:22,600 --> 00:34:25,880
Speaker 1: your traditional active corporates tips, what reads. What are you

657
00:34:25,920 --> 00:34:29,319
Speaker 1: adding to. It's the traditional investment grade agg universe, but

658
00:34:29,440 --> 00:34:32,759
Speaker 1: just rebucketing it to have constraints so you don't an

659
00:34:32,760 --> 00:34:35,239
Speaker 1: increase ration too much, You don't tilt to credit too much,

660
00:34:35,840 --> 00:34:38,160
Speaker 1: but it really it tilts to credit in away from

661
00:34:38,200 --> 00:34:40,640
Speaker 1: treasuries and a constrained fashion. So we have a short

662
00:34:40,719 --> 00:34:43,520
Speaker 1: term version the e t F is SHAG s h

663
00:34:43,600 --> 00:34:46,799
Speaker 1: a G. The longer term is AGGIE so AG y

664
00:34:47,200 --> 00:34:49,359
Speaker 1: UM as a way to just yield enhancing the agg

665
00:34:49,400 --> 00:34:52,239
Speaker 1: we're definitely seeing traction there. It's early days um, but

666
00:34:52,360 --> 00:34:54,760
Speaker 1: I think that's our first factor investment in fixed income.

667
00:34:54,960 --> 00:34:58,920
Speaker 1: But we've also done fundamentally screened sort of credit screen

668
00:34:59,000 --> 00:35:01,560
Speaker 1: so looking at in the high old market as an example,

669
00:35:01,719 --> 00:35:04,759
Speaker 1: screening out bonds with negative free cash flow, not just

670
00:35:04,880 --> 00:35:07,600
Speaker 1: issuing market cap, which gives the biggest way to the

671
00:35:07,600 --> 00:35:10,600
Speaker 1: biggest indebted issuer, screen out those bonds with negative free

672
00:35:10,640 --> 00:35:13,719
Speaker 1: cash flow, and that's a quality portfolio on bonds that

673
00:35:13,800 --> 00:35:16,319
Speaker 1: we've we have four different funds screened around that as well.

674
00:35:16,360 --> 00:35:18,880
Speaker 1: Can you stick around a little bit about we'll keep talking.

675
00:35:19,000 --> 00:35:21,319
Speaker 1: We have been speaking with Jeremy Schwartz. He is the

676
00:35:21,360 --> 00:35:25,800
Speaker 1: director of research at Wisdom Tree Investments. If you enjoy

677
00:35:25,880 --> 00:35:29,040
Speaker 1: this conversation, be sure and stick around for the podcast

678
00:35:29,080 --> 00:35:32,200
Speaker 1: extras where we keep the tape rolling and continue chatting

679
00:35:32,200 --> 00:35:37,040
Speaker 1: about all things value, et F and divinend oriented. Be

680
00:35:37,120 --> 00:35:39,319
Speaker 1: sure to check out my daily column. You can see

681
00:35:39,360 --> 00:35:42,600
Speaker 1: that at Bloomberg view dot com. Follow me on Twitter

682
00:35:42,800 --> 00:35:46,719
Speaker 1: at Hults. I'm Barry Riholts. You're listening to Masters in

683
00:35:46,760 --> 00:36:02,680
Speaker 1: Business on Bloomberg Radio. Welcome to the podcast. Jeremy. Thank

684
00:36:02,760 --> 00:36:05,000
Speaker 1: you so much for doing this. We have been talking

685
00:36:05,160 --> 00:36:07,799
Speaker 1: about doing this for like a year and a half.

686
00:36:07,800 --> 00:36:09,200
Speaker 1: I'm like, oh, I have to get you on the

687
00:36:09,200 --> 00:36:12,560
Speaker 1: show for for forever. So I'm so glad we managed

688
00:36:13,120 --> 00:36:16,839
Speaker 1: um to get in to get you in. And by

689
00:36:16,880 --> 00:36:20,080
Speaker 1: the way, Medina and you could keep this in that

690
00:36:20,400 --> 00:36:25,120
Speaker 1: last conversation where he was describing Junior Jeremy in the intro.

691
00:36:25,800 --> 00:36:29,160
Speaker 1: I love that we should keep that on the broadcast portion.

692
00:36:30,760 --> 00:36:33,360
Speaker 1: So just just not or say yes or something, and

693
00:36:33,400 --> 00:36:39,919
Speaker 1: I'm fine. Um So, so anyway, let's talk a little

694
00:36:39,960 --> 00:36:44,239
Speaker 1: more about Siegel, because I'm endlessly amused by him. In

695
00:36:44,320 --> 00:36:47,439
Speaker 1: full disclosure, I used to bust his chops heading into

696
00:36:47,440 --> 00:36:51,680
Speaker 1: O eight o nine about um, just buy and hold

697
00:36:51,719 --> 00:36:54,040
Speaker 1: and kind of forget to me. The O eight o

698
00:36:54,160 --> 00:36:57,759
Speaker 1: nine crisis was You're never gonna call every crisis, but

699
00:36:57,880 --> 00:37:00,560
Speaker 1: dear Lord, you can if you looked. I used to

700
00:37:00,560 --> 00:37:04,759
Speaker 1: call it the leaping dolphin. Remember the three D pictures

701
00:37:04,760 --> 00:37:07,239
Speaker 1: people used to have on the wall, the posters where

702
00:37:07,239 --> 00:37:09,480
Speaker 1: it didn't look like anything, but if you caught it

703
00:37:09,520 --> 00:37:12,400
Speaker 1: at just the right angle, Oh, there's the leaping dolphin.

704
00:37:12,440 --> 00:37:15,400
Speaker 1: That That's kind of how I felt about the last crisis.

705
00:37:15,760 --> 00:37:22,359
Speaker 1: But full full disclosure, I'm endlessly impressed, entertained, amused by

706
00:37:22,400 --> 00:37:27,360
Speaker 1: Siegell for so many reasons. Him and Bob Shiller buddies.

707
00:37:27,400 --> 00:37:30,359
Speaker 1: Are there two more opposite personalities. I've got a great

708
00:37:30,360 --> 00:37:33,399
Speaker 1: story on sea so um in a way of when

709
00:37:33,440 --> 00:37:35,640
Speaker 1: I was courting my wife. So my wife likes to

710
00:37:35,719 --> 00:37:39,040
Speaker 1: joke that, you know, I met her in two thousand one,

711
00:37:39,200 --> 00:37:41,200
Speaker 1: and I met the love of my my true life,

712
00:37:41,200 --> 00:37:42,919
Speaker 1: of my life in two thousand one, which is when

713
00:37:42,960 --> 00:37:45,759
Speaker 1: I started working for Siegel also, but you know that

714
00:37:45,800 --> 00:37:48,480
Speaker 1: first summer I started working for him, she was taking

715
00:37:48,480 --> 00:37:51,600
Speaker 1: a class where she had to do a book report

716
00:37:51,800 --> 00:37:57,359
Speaker 1: reviewing and contrasting Irrational Exuberance with which Bob Schiller's book

717
00:37:57,400 --> 00:38:01,839
Speaker 1: where he had had briefed Um green Span in ninety six,

718
00:38:01,920 --> 00:38:04,120
Speaker 1: and then green Span went out and gave the Irrational

719
00:38:04,239 --> 00:38:08,439
Speaker 1: Zuberan speech based on Schiller's work, and then Schiller named

720
00:38:08,480 --> 00:38:11,000
Speaker 1: the book Irrational Zuberans. Yeah, And so you know, they

721
00:38:11,000 --> 00:38:13,440
Speaker 1: talked about how they vacation together. So on one of

722
00:38:13,440 --> 00:38:16,760
Speaker 1: those two thousand one summer vacations there in Ocean City,

723
00:38:17,000 --> 00:38:19,640
Speaker 1: Segul invited me to a barbecue and stay with them

724
00:38:19,640 --> 00:38:21,879
Speaker 1: for the weekend. In Ocean City. Schiller was coming down,

725
00:38:21,920 --> 00:38:24,080
Speaker 1: The New York Times was coming to profile and they

726
00:38:24,320 --> 00:38:26,040
Speaker 1: did the walks on the beach with the New York

727
00:38:26,080 --> 00:38:29,040
Speaker 1: Times Profile, And so I got to invite my wife

728
00:38:29,080 --> 00:38:31,799
Speaker 1: to the she was my girlfriend obviously at the time,

729
00:38:32,280 --> 00:38:34,880
Speaker 1: just to impress to the barbecue, and she had to

730
00:38:34,920 --> 00:38:37,480
Speaker 1: be she was doing this book report on Irrational zuber

731
00:38:38,320 --> 00:38:41,560
Speaker 1: and she tells the professor, I have to miss class.

732
00:38:41,760 --> 00:38:43,920
Speaker 1: I'm going to this barbecue with siegu and Schiller and

733
00:38:44,480 --> 00:38:47,520
Speaker 1: can I come? But she got to, you know, she

734
00:38:47,560 --> 00:38:50,960
Speaker 1: wrote her paper and she was giving examples of we

735
00:38:51,000 --> 00:38:53,520
Speaker 1: went to Atlantic City and they're playing black jack and

736
00:38:53,560 --> 00:38:56,480
Speaker 1: Siegel was into black jack, playing the cards, best odds

737
00:38:56,520 --> 00:38:59,239
Speaker 1: in the house, and Schiller didn't even you know, didn't

738
00:38:59,239 --> 00:39:01,200
Speaker 1: want to play the black chacked tables. And she put

739
00:39:01,280 --> 00:39:03,400
Speaker 1: that in her paper on the stories of how even

740
00:39:03,440 --> 00:39:07,080
Speaker 1: they're gambling. You know, Siegel embraced the risk of liking

741
00:39:07,120 --> 00:39:09,240
Speaker 1: to play black shack and Chiller was so risk averse

742
00:39:09,280 --> 00:39:11,759
Speaker 1: and didn't want to play blackjack. She gotten you know,

743
00:39:11,800 --> 00:39:14,680
Speaker 1: eight plus on the paper. But that was, you know,

744
00:39:14,760 --> 00:39:16,839
Speaker 1: in an interesting time. So that's those stories of them

745
00:39:16,920 --> 00:39:20,640
Speaker 1: vacation together are real. Um. And actually my first project

746
00:39:20,719 --> 00:39:23,160
Speaker 1: where I got to show Siegel my writing was also

747
00:39:23,160 --> 00:39:26,719
Speaker 1: really to Bob Schiller. So in what way go explain that?

748
00:39:26,840 --> 00:39:30,040
Speaker 1: So Stocks to the Long Run you know, came out,

749
00:39:30,440 --> 00:39:32,399
Speaker 1: he did the second dition. I was working with him

750
00:39:32,400 --> 00:39:34,560
Speaker 1: on the two thousand two edition, and right after I

751
00:39:34,640 --> 00:39:37,000
Speaker 1: spent the weekend or you know that vacation, I said,

752
00:39:37,560 --> 00:39:39,560
Speaker 1: you know, of all the stuff topics you have in

753
00:39:39,600 --> 00:39:42,680
Speaker 1: socks long when you have nothing on behavioral finance. Um,

754
00:39:42,719 --> 00:39:45,799
Speaker 1: and your best friend is Bob Schiller. Come on, and

755
00:39:45,840 --> 00:39:49,400
Speaker 1: you wrote a paper with Richard Taylor, and Faylor just

756
00:39:49,440 --> 00:39:51,439
Speaker 1: won the Nobel Prize for a lot of his work,

757
00:39:51,480 --> 00:39:54,080
Speaker 1: and Siegel and Taylor had collaborated on some work together.

758
00:39:54,320 --> 00:39:56,120
Speaker 1: So I said, let's you should add a chapter. And

759
00:39:56,160 --> 00:39:59,279
Speaker 1: he's always had quantz and math people, but he never

760
00:39:59,320 --> 00:40:01,520
Speaker 1: had a writer. Um, So I said, why don't you

761
00:40:01,600 --> 00:40:03,520
Speaker 1: let me take a stab at it? And so I

762
00:40:03,560 --> 00:40:06,600
Speaker 1: wrote the behavioral finance chapter for a Doctor long Run.

763
00:40:07,040 --> 00:40:08,520
Speaker 1: And you could see if you read it, it's very

764
00:40:08,560 --> 00:40:10,360
Speaker 1: different than any other chapter in the book. Is actually

765
00:40:10,360 --> 00:40:13,279
Speaker 1: written as a conversation between a psychologist. You know, a

766
00:40:13,280 --> 00:40:16,000
Speaker 1: couple goes to their psychologists and having all these behavioral

767
00:40:16,000 --> 00:40:19,400
Speaker 1: issues and the psychologist walks him through all their behavioral

768
00:40:19,440 --> 00:40:21,040
Speaker 1: finance problems. You can see it's very different than the

769
00:40:21,080 --> 00:40:23,480
Speaker 1: rest of the book. That that that's so funny. You know.

770
00:40:24,120 --> 00:40:26,759
Speaker 1: I have a number of Schiller stories, but the only

771
00:40:26,800 --> 00:40:29,800
Speaker 1: one I want to share is after he did the show,

772
00:40:30,400 --> 00:40:33,080
Speaker 1: I wasn't gonna put Bob Schiller on on a subway.

773
00:40:33,120 --> 00:40:34,880
Speaker 1: He had to go somewhere else. So I got a

774
00:40:34,920 --> 00:40:38,759
Speaker 1: car and I took him in a cab pouring rain,

775
00:40:39,719 --> 00:40:41,719
Speaker 1: tons of traffic. I was afraid we're gonna be late,

776
00:40:42,040 --> 00:40:44,040
Speaker 1: but he gets into the back of the cab and

777
00:40:44,120 --> 00:40:47,759
Speaker 1: immediately puts on a seatbelt, and I'm like, Ah, this

778
00:40:47,880 --> 00:40:51,000
Speaker 1: is a person who really understands risk. Yeah, you can

779
00:40:51,040 --> 00:40:53,880
Speaker 1: see carry throughout there all all their lives. So so

780
00:40:54,000 --> 00:40:56,120
Speaker 1: let's talk a little bit about segull. I have a

781
00:40:56,120 --> 00:40:59,640
Speaker 1: couple of seagulls stories. Also, I really enjoy him. When

782
00:40:59,680 --> 00:41:02,160
Speaker 1: he was on the podcast. I think it was the

783
00:41:02,160 --> 00:41:04,840
Speaker 1: first time I met him in person, as opposed to

784
00:41:05,320 --> 00:41:08,839
Speaker 1: a disembodied head on tv um or a voice in

785
00:41:08,840 --> 00:41:11,680
Speaker 1: in an in an earpiece while you're debating him about something.

786
00:41:12,280 --> 00:41:16,000
Speaker 1: And the only way I could really describe him is

787
00:41:16,880 --> 00:41:20,879
Speaker 1: filled with childlike wonders. Am I overstating that at all?

788
00:41:21,040 --> 00:41:24,000
Speaker 1: I mean his passion for teaching, his passion for the markets.

789
00:41:24,200 --> 00:41:26,960
Speaker 1: It's just that's what gets people excited. I mean why

790
00:41:27,000 --> 00:41:29,640
Speaker 1: he's the most popular professor at Wharton, And let me

791
00:41:30,040 --> 00:41:33,840
Speaker 1: stop you there. Year after year he is consistently voted

792
00:41:33,880 --> 00:41:37,520
Speaker 1: by Wharton students their favorite professor, and in the NBA

793
00:41:37,680 --> 00:41:40,000
Speaker 1: World you have to pay for your classes, so it's

794
00:41:40,040 --> 00:41:41,879
Speaker 1: a real market based system. If you have a certain

795
00:41:41,920 --> 00:41:44,360
Speaker 1: number of points, you can allocate it. And I remember

796
00:41:44,360 --> 00:41:47,280
Speaker 1: when this was. I haven't kept tracked with the points,

797
00:41:47,280 --> 00:41:49,200
Speaker 1: but when I was there, he was always the most

798
00:41:49,360 --> 00:41:53,160
Speaker 1: highly bid professor. And it's why it's while he starts

799
00:41:53,360 --> 00:41:55,880
Speaker 1: his class, his first half hour of every class is

800
00:41:55,960 --> 00:41:57,960
Speaker 1: essentially just to look at the markets, and he that

801
00:41:58,080 --> 00:42:01,360
Speaker 1: day he has his Bloomberg term know up, He's walking

802
00:42:01,400 --> 00:42:04,880
Speaker 1: through what's going on news wise, and so it's the

803
00:42:04,880 --> 00:42:06,360
Speaker 1: only you go to Wharton and you think this is

804
00:42:06,360 --> 00:42:08,400
Speaker 1: the most practical thing to learn about the markets, but

805
00:42:08,440 --> 00:42:11,560
Speaker 1: it's really the only class that actually does really go

806
00:42:11,640 --> 00:42:14,520
Speaker 1: through what's happy in the real time, actual market. And

807
00:42:14,680 --> 00:42:16,880
Speaker 1: looking at the other thing about him that I found

808
00:42:16,880 --> 00:42:20,239
Speaker 1: so amusing, he look, we go a little long the

809
00:42:20,280 --> 00:42:24,680
Speaker 1: whole ideas. These are deeper dive conversations. He's sitting where

810
00:42:24,719 --> 00:42:28,279
Speaker 1: you were sitting, and about an hour into the conversation

811
00:42:28,320 --> 00:42:31,160
Speaker 1: and I'm doing it now, he starts just you know,

812
00:42:31,200 --> 00:42:33,759
Speaker 1: it's it's swivel chair. He just starts rocking back and

813
00:42:33,800 --> 00:42:38,680
Speaker 1: forth while while gesticulating and and answering the question. And

814
00:42:38,719 --> 00:42:41,920
Speaker 1: then he started and I'm wearing just one earpiece. The

815
00:42:42,000 --> 00:42:44,960
Speaker 1: guest isn't wearing anything. He starts spinning in circles on

816
00:42:45,040 --> 00:42:49,759
Speaker 1: the It was the most amusing, charming and transing thing.

817
00:42:49,840 --> 00:42:54,440
Speaker 1: And if you listen towards the ends of the Seagull podcast,

818
00:42:54,840 --> 00:42:57,560
Speaker 1: you could kind of hear him whipping around the microphone

819
00:42:57,600 --> 00:43:01,800
Speaker 1: as he spins around, because like he really gets into

820
00:43:01,840 --> 00:43:04,360
Speaker 1: it and was he's presenting. He's pacing back and forth,

821
00:43:04,440 --> 00:43:07,799
Speaker 1: and he's like I can see him jumping on a

822
00:43:07,920 --> 00:43:11,200
Speaker 1: desk and waving his arms. He gets animated. That's for sure.

823
00:43:11,480 --> 00:43:14,800
Speaker 1: That that's that's really interesting. Um, So let's talk a

824
00:43:14,840 --> 00:43:17,720
Speaker 1: little b about some of the things we missed during

825
00:43:17,719 --> 00:43:20,759
Speaker 1: the broadcast. There were a couple of questions I had

826
00:43:20,800 --> 00:43:23,600
Speaker 1: to ask you because, uh, we talked about a lot

827
00:43:23,600 --> 00:43:28,320
Speaker 1: of things we hardly mentioned. Some guy named Michael Steinhardt,

828
00:43:29,280 --> 00:43:35,239
Speaker 1: legendary investor, uh, founder of Wisdom Tree. Tell us about

829
00:43:35,400 --> 00:43:38,800
Speaker 1: his role with the creation and development of the country

830
00:43:38,880 --> 00:43:43,200
Speaker 1: of the company and what sort of working relationship you

831
00:43:43,239 --> 00:43:45,080
Speaker 1: have with him. So I would say, he's the chairman

832
00:43:45,120 --> 00:43:47,560
Speaker 1: of the company. He was the original backer and the

833
00:43:47,680 --> 00:43:51,120
Speaker 1: sort of he funded the company. So Jonathan Steinberg was

834
00:43:51,200 --> 00:43:54,600
Speaker 1: in Luciana Sasano was their intellectual property stort, developing the

835
00:43:54,640 --> 00:43:58,840
Speaker 1: firm after the magazine initial investor group. But Michael, you know,

836
00:43:58,880 --> 00:44:01,360
Speaker 1: he hadn't done anything. He had retired, He closed his

837
00:44:01,480 --> 00:44:04,680
Speaker 1: fund after literally starting the hedge fund industry, hadn't the

838
00:44:04,680 --> 00:44:08,200
Speaker 1: best for twenty nine years, I think something like returned

839
00:44:08,520 --> 00:44:11,279
Speaker 1: an incredible track record, and then he closed the fund

840
00:44:11,280 --> 00:44:16,080
Speaker 1: in ninety four, dedicated his life to charity, Like you

841
00:44:16,160 --> 00:44:19,640
Speaker 1: still have seven years of a booming bullmarket. He's like, nope,

842
00:44:19,680 --> 00:44:23,040
Speaker 1: I'm done. Yeah, he just he That's another story for

843
00:44:23,040 --> 00:44:26,040
Speaker 1: another day. But he closed it. He didn't do anything

844
00:44:26,120 --> 00:44:29,200
Speaker 1: finance wise. He was giving back, giving his money to charity,

845
00:44:29,320 --> 00:44:32,040
Speaker 1: and he didn't do anything literally in finance until Wisdom

846
00:44:32,120 --> 00:44:35,279
Speaker 1: Tree uh in decade later, two thousand four year, so

847
00:44:35,280 --> 00:44:37,560
Speaker 1: he met John oh and John O was had the

848
00:44:37,600 --> 00:44:39,880
Speaker 1: idea about the et F structure and and really this

849
00:44:39,920 --> 00:44:43,880
Speaker 1: better way performance based indexing was his concept, and Michael was.

850
00:44:44,360 --> 00:44:45,919
Speaker 1: I mean, there's a story I remember from the early

851
00:44:46,000 --> 00:44:48,520
Speaker 1: days that Michael said, you know, if I was presented

852
00:44:48,520 --> 00:44:51,440
Speaker 1: with the opportunity to fund Vanguard, I would have that

853
00:44:51,560 --> 00:44:53,759
Speaker 1: I would not have. He would not have because he

854
00:44:53,880 --> 00:44:56,440
Speaker 1: was not about tracking the market. He was about beating

855
00:44:56,440 --> 00:44:58,840
Speaker 1: the market and he wanted he saw this idea of

856
00:44:58,880 --> 00:45:02,560
Speaker 1: trying to generate better performance, a very performance oriented culture,

857
00:45:03,040 --> 00:45:05,800
Speaker 1: and so that's what really inspired him to get involved

858
00:45:05,800 --> 00:45:08,239
Speaker 1: with JOHNO and John Oh you know, linked it up

859
00:45:08,280 --> 00:45:10,799
Speaker 1: with Siegel and we helped validate their initial research and

860
00:45:10,840 --> 00:45:13,520
Speaker 1: gave some academic back into why we think this could

861
00:45:13,520 --> 00:45:16,040
Speaker 1: work going forward and that there was something to this.

862
00:45:16,520 --> 00:45:19,040
Speaker 1: And that's how the that sort of trinity came together

863
00:45:19,080 --> 00:45:22,360
Speaker 1: of Steinhardt funding, Professor Siegel joining and also fund to

864
00:45:22,360 --> 00:45:24,600
Speaker 1: get back and back in a four and joining the

865
00:45:24,680 --> 00:45:27,279
Speaker 1: senior advisor, and then they brought me on together. But

866
00:45:27,360 --> 00:45:31,160
Speaker 1: it's it's um, it was that performance oriented mindset that

867
00:45:31,200 --> 00:45:36,279
Speaker 1: Steinhardt really wasn't inspired by. H That's quite fascinating. And

868
00:45:36,440 --> 00:45:40,280
Speaker 1: I don't know Jonathan stein but I know his father

869
00:45:40,960 --> 00:45:44,560
Speaker 1: was Soul Stein, who ran Reliance Insurance. This is back

870
00:45:44,560 --> 00:45:47,279
Speaker 1: in the eighties and nineties, way back when. Yeah, and

871
00:45:47,320 --> 00:45:49,360
Speaker 1: I didn't really get to know Saul, but in the

872
00:45:49,440 --> 00:45:51,239
Speaker 1: in this in this small world, um, you know, I

873
00:45:51,360 --> 00:45:53,240
Speaker 1: used to work in the Steinberg teacher call at Wharton

874
00:45:53,360 --> 00:45:56,840
Speaker 1: and Professor Siegel is the shared by Saul Steinberg. So

875
00:45:56,840 --> 00:46:00,399
Speaker 1: it's a small, interconnected world of how it all comes together. Um,

876
00:46:00,440 --> 00:46:03,160
Speaker 1: but yeah, it's been. It's been a great relationship. And

877
00:46:03,520 --> 00:46:06,720
Speaker 1: he's also one of these passionate about et s, passionate

878
00:46:06,719 --> 00:46:08,560
Speaker 1: about what we're doing, and really is assembled just a

879
00:46:08,600 --> 00:46:12,399
Speaker 1: remarkable team at with some tree. So you guys are

880
00:46:12,400 --> 00:46:16,520
Speaker 1: so valuation oriented, I would be remiss if I did

881
00:46:16,560 --> 00:46:21,960
Speaker 1: not ask you about valuations of stocks and bonds. First,

882
00:46:22,000 --> 00:46:24,680
Speaker 1: since we talked about Chiller, let's talk about the cape ratio.

883
00:46:25,160 --> 00:46:29,160
Speaker 1: Does the cape ratio tell the full story? Um, it's

884
00:46:29,200 --> 00:46:32,400
Speaker 1: a it's a it's a complicated question there. Um you

885
00:46:32,440 --> 00:46:34,120
Speaker 1: know it's Siegel has done a lot of work on this,

886
00:46:34,320 --> 00:46:36,480
Speaker 1: and which I find, by the way, I find hilarious

887
00:46:36,520 --> 00:46:39,360
Speaker 1: that the two of them are arguing in white papers,

888
00:46:39,760 --> 00:46:42,960
Speaker 1: good naturedly about what is the value of the cape?

889
00:46:43,000 --> 00:46:44,919
Speaker 1: Is it worth something? Is it not worth a lot?

890
00:46:45,440 --> 00:46:47,800
Speaker 1: Is it just here you're expected returns? Or does it

891
00:46:47,920 --> 00:46:51,960
Speaker 1: really give us buying cell signals? And Siegel loves the framework.

892
00:46:52,040 --> 00:46:54,399
Speaker 1: He thinks that it has been one of the better

893
00:46:54,440 --> 00:46:57,920
Speaker 1: predictors of long term returns. He thinks the earnings numbers

894
00:46:57,920 --> 00:47:01,680
Speaker 1: are biased and that is creating problems. So counting numbers

895
00:47:01,800 --> 00:47:04,920
Speaker 1: changed the O nine crisis, which is still in the CAPE. Basically,

896
00:47:05,000 --> 00:47:07,719
Speaker 1: three firms wiped out all of the earnings of the spire.

897
00:47:07,800 --> 00:47:10,279
Speaker 1: They were small firms. Wait to say that again? Three

898
00:47:10,360 --> 00:47:13,160
Speaker 1: How is that possible? Three firms wiped out all of

899
00:47:13,200 --> 00:47:16,319
Speaker 1: the earnings of the sp basically Bank of America's City

900
00:47:16,320 --> 00:47:19,160
Speaker 1: Group A I G. The way they do not exactly

901
00:47:19,160 --> 00:47:21,600
Speaker 1: small firms, no, but but at the time they were

902
00:47:21,800 --> 00:47:24,600
Speaker 1: by market value, they were small by market values, almost

903
00:47:24,719 --> 00:47:29,239
Speaker 1: giant companies with the so so go go. We'll go

904
00:47:29,280 --> 00:47:31,920
Speaker 1: through an example here, but by market value they were

905
00:47:31,920 --> 00:47:34,520
Speaker 1: small at the time, and they destroyed all of the earnings.

906
00:47:34,880 --> 00:47:38,680
Speaker 1: So you're investing, and take a simple to stock example

907
00:47:38,719 --> 00:47:42,560
Speaker 1: the city and but take a simple example you have

908
00:47:43,320 --> 00:47:46,880
Speaker 1: of your portfolio. Okay, let's say you have a hundred

909
00:47:47,360 --> 00:47:51,000
Speaker 1: forty billion ten billion dollars. One firm is is ten

910
00:47:51,040 --> 00:47:55,320
Speaker 1: billion of profits, another firm is is negative nine billion, okay,

911
00:47:55,520 --> 00:47:59,000
Speaker 1: and the first one So you have a hundred fifty

912
00:47:59,000 --> 00:48:01,840
Speaker 1: billion market cap set and firm nagative nine billion profits

913
00:48:01,880 --> 00:48:05,000
Speaker 1: called ten billion. So you have one billion of total

914
00:48:05,040 --> 00:48:08,959
Speaker 1: profits for the combined firm hundred sixty billion market cap.

915
00:48:09,200 --> 00:48:13,160
Speaker 1: So is your p D sixty, or is your pe

916
00:48:13,719 --> 00:48:17,600
Speaker 1: of your portfolio at what is the trooper? What is

917
00:48:17,600 --> 00:48:20,000
Speaker 1: the troop or folio P? And the way S and

918
00:48:20,040 --> 00:48:23,640
Speaker 1: P does their earnings is dollar for dollar, and so

919
00:48:23,760 --> 00:48:26,480
Speaker 1: that's makes sense. It's a it's a problem in the

920
00:48:26,520 --> 00:48:29,080
Speaker 1: way of the accounting on the on the P ratios.

921
00:48:29,120 --> 00:48:31,799
Speaker 1: So so here's the pushback on that. When you look

922
00:48:31,840 --> 00:48:37,239
Speaker 1: across the universe of earnings. Let's let's hold McDonald's and

923
00:48:37,320 --> 00:48:41,000
Speaker 1: g e Aside, who absolutely in the recession, so we're

924
00:48:41,000 --> 00:48:43,560
Speaker 1: an earnings crunched, but they still were on the green

925
00:48:43,600 --> 00:48:47,000
Speaker 1: side of the ledger more or less. But you have

926
00:48:47,600 --> 00:48:50,680
Speaker 1: Lehman Brothers going to zero when Bear Sterns earnings you know,

927
00:48:50,800 --> 00:48:54,720
Speaker 1: both of them deeply negative. And then there's a hundred

928
00:48:54,760 --> 00:48:59,560
Speaker 1: other financial related firms who saw their earnings compressed, be

929
00:48:59,640 --> 00:49:03,000
Speaker 1: it Black Rock or U B A U B S

930
00:49:03,120 --> 00:49:04,960
Speaker 1: is a A d oh, so not that, but you

931
00:49:05,000 --> 00:49:08,160
Speaker 1: could look at a ton of different Every bank, the

932
00:49:08,239 --> 00:49:11,560
Speaker 1: home builders totally one of the crapper, The broker dealers

933
00:49:11,920 --> 00:49:16,160
Speaker 1: got slacked, the community banks did really poorly. So while

934
00:49:16,239 --> 00:49:20,920
Speaker 1: those three firms had like a massively negative earnings number,

935
00:49:21,320 --> 00:49:25,840
Speaker 1: everybody else's numbers really came down or we're you know

936
00:49:25,880 --> 00:49:30,560
Speaker 1: what best flat, And that's before we start talking about industrials.

937
00:49:30,600 --> 00:49:33,120
Speaker 1: Auto sales fall off the cliff. I mean, you could

938
00:49:33,200 --> 00:49:37,080
Speaker 1: go down the list of of sectors. So while for

939
00:49:37,120 --> 00:49:40,720
Speaker 1: sure these three companies had an outsized impact, the rest

940
00:49:40,719 --> 00:49:45,560
Speaker 1: of earnings fell. Well that that's the question how much

941
00:49:45,560 --> 00:49:47,480
Speaker 1: did they really fall? And so I think if you

942
00:49:47,480 --> 00:49:51,040
Speaker 1: look at things like the niper profits um National incomproduct

943
00:49:51,080 --> 00:49:53,720
Speaker 1: account profits or their GDP numbers where they count profits,

944
00:49:53,760 --> 00:49:56,319
Speaker 1: they didn't fall anywhere near as much. And so when

945
00:49:56,360 --> 00:49:58,520
Speaker 1: you do these perations, but that's not what we use

946
00:49:58,640 --> 00:50:01,319
Speaker 1: for pe earning, the questions how do you get a

947
00:50:01,360 --> 00:50:04,080
Speaker 1: real earnings number? And what is the real earning series?

948
00:50:04,239 --> 00:50:08,040
Speaker 1: And so there's there's biases in the numbers, and you

949
00:50:08,080 --> 00:50:10,640
Speaker 1: could you could debate on how much the magnitude is.

950
00:50:10,800 --> 00:50:12,919
Speaker 1: But they changed the accounting rules, so now you're forced

951
00:50:12,960 --> 00:50:15,319
Speaker 1: to mark down losses. I mean, Buffett writes about this

952
00:50:15,320 --> 00:50:16,840
Speaker 1: all the time. He says, I can never write up

953
00:50:16,880 --> 00:50:19,040
Speaker 1: the value my assets. You can only mark down the

954
00:50:19,120 --> 00:50:21,200
Speaker 1: value of assets, and so the accounting rules are one

955
00:50:21,280 --> 00:50:24,239
Speaker 1: side of there. But they suspended that for banks right

956
00:50:24,280 --> 00:50:28,600
Speaker 1: after what was it the October o eight debacle, and

957
00:50:28,640 --> 00:50:33,040
Speaker 1: then again in um the first the whole, um, the whole.

958
00:50:33,080 --> 00:50:36,800
Speaker 1: I'm trying to remember with the which accounting rule changed,

959
00:50:37,160 --> 00:50:41,480
Speaker 1: but essentially essentially we allowed banks that you could segment them,

960
00:50:41,520 --> 00:50:43,719
Speaker 1: you don't have to write them down. So for all

961
00:50:43,760 --> 00:50:46,920
Speaker 1: we really know, these banks were insolvent and we're running

962
00:50:46,920 --> 00:50:50,880
Speaker 1: on fumes and government handouts. So I'm pushing back on

963
00:50:51,000 --> 00:50:54,919
Speaker 1: the well, things really weren't that bad, they were got awful. Then,

964
00:50:55,160 --> 00:50:57,560
Speaker 1: Oh no, I get that they're got awful, um, but

965
00:50:57,640 --> 00:51:01,200
Speaker 1: the question is that it's been a poor in the

966
00:51:01,280 --> 00:51:03,840
Speaker 1: last three years. It's certainly been a very poor predictor,

967
00:51:03,880 --> 00:51:05,840
Speaker 1: and so the question about that. So the question is,

968
00:51:05,880 --> 00:51:08,200
Speaker 1: in fact, you're you're better off buying when earnings are

969
00:51:08,200 --> 00:51:10,640
Speaker 1: worth their worst than buying when the earnings are worth

970
00:51:10,680 --> 00:51:13,000
Speaker 1: the better best. And it will kept you out of

971
00:51:13,000 --> 00:51:15,239
Speaker 1: the market for basically all but a few months, I

972
00:51:15,280 --> 00:51:17,319
Speaker 1: mean even O nine, right, a few months after the

973
00:51:17,400 --> 00:51:20,359
Speaker 1: market rebounded, oh nine, it was telling you to stay

974
00:51:20,360 --> 00:51:22,439
Speaker 1: out of the market. And the market's up to two

975
00:51:22,480 --> 00:51:24,520
Speaker 1: to three x since then. So and then the question

976
00:51:24,600 --> 00:51:26,399
Speaker 1: is at least three x in the US, to say

977
00:51:26,440 --> 00:51:29,760
Speaker 1: the least. And so you know, in terms of going forward,

978
00:51:29,800 --> 00:51:32,960
Speaker 1: how do you look at valuations today, I'd say, you know,

979
00:51:33,000 --> 00:51:36,000
Speaker 1: the S and p P s around twenty times earnings.

980
00:51:36,200 --> 00:51:37,600
Speaker 1: And this is going back and forth with Seagull, but

981
00:51:37,640 --> 00:51:39,439
Speaker 1: he would say the earning seal is close to five

982
00:51:39,440 --> 00:51:41,759
Speaker 1: percent today, and so you get a real earning seal

983
00:51:41,880 --> 00:51:46,319
Speaker 1: of five percent versus historical average of what sixteen is

984
00:51:46,360 --> 00:51:48,640
Speaker 1: the average pe. So when he says stocks are long,

985
00:51:48,640 --> 00:51:50,640
Speaker 1: when you had a six seven long term real return,

986
00:51:50,719 --> 00:51:53,279
Speaker 1: that's basically one divided by the six team. So that's

987
00:51:53,280 --> 00:51:56,120
Speaker 1: where you get the sixth six seven real return. Inverting

988
00:51:56,160 --> 00:51:58,680
Speaker 1: it will take out the zeros. It's just the earning sale.

989
00:51:58,680 --> 00:52:01,359
Speaker 1: It's just povere versus EO repeat, and so you get

990
00:52:01,400 --> 00:52:04,440
Speaker 1: six seven um today. If it's the piece twenty, you

991
00:52:04,480 --> 00:52:07,200
Speaker 1: get a five percent earning sield. You know, the historical

992
00:52:07,280 --> 00:52:11,239
Speaker 1: equity premium phrase two years of data was three. Today

993
00:52:11,520 --> 00:52:14,120
Speaker 1: the real equity you could say the real equity premium

994
00:52:14,120 --> 00:52:16,640
Speaker 1: is like four and a half because the tenure tips

995
00:52:16,719 --> 00:52:19,280
Speaker 1: is at fifty and you have a five earning sield.

996
00:52:19,840 --> 00:52:21,640
Speaker 1: And on top of that, and this is a whole

997
00:52:21,680 --> 00:52:24,839
Speaker 1: another conversation, but on top of that, when you look

998
00:52:24,880 --> 00:52:28,160
Speaker 1: at the money being thrown off by companies like Google

999
00:52:28,200 --> 00:52:31,319
Speaker 1: and Amazon and Facebook. It's not like the old days

1000
00:52:31,320 --> 00:52:33,840
Speaker 1: where you're building a railroad, you hire ten thousand people

1001
00:52:34,280 --> 00:52:38,799
Speaker 1: and buy you know, endless tonnage of steel. Look at

1002
00:52:38,880 --> 00:52:41,800
Speaker 1: look at what'sapp or look at Instagram or some of

1003
00:52:41,840 --> 00:52:44,960
Speaker 1: these other things where it's twenty people are worth five

1004
00:52:45,000 --> 00:52:47,759
Speaker 1: billion dollars and their core structure is a handful of

1005
00:52:47,840 --> 00:52:50,759
Speaker 1: laptops and some Internet connectivity. And that's the worry that

1006
00:52:50,840 --> 00:52:53,400
Speaker 1: people say, Well, margins are going to mean revert and

1007
00:52:53,600 --> 00:52:56,759
Speaker 1: they're gonna be the problem that we're at these high

1008
00:52:56,800 --> 00:52:59,480
Speaker 1: valuations and margins are are high and they're gonna head downward.

1009
00:52:59,680 --> 00:53:01,759
Speaker 1: So that the most barrish argument is that margins have

1010
00:53:01,840 --> 00:53:03,400
Speaker 1: to mean reversion, but they may not because of what

1011
00:53:03,440 --> 00:53:08,480
Speaker 1: you're saying, that different return on capital, that you just

1012
00:53:08,520 --> 00:53:10,320
Speaker 1: have a different profile. M You know, the problem with

1013
00:53:10,400 --> 00:53:12,920
Speaker 1: mean reversion is, hey, if you're waiting for mean reversion

1014
00:53:12,960 --> 00:53:16,279
Speaker 1: and the leather belt companies and steam engines, that that

1015
00:53:16,440 --> 00:53:19,960
Speaker 1: isn't happening. And you know, I always I never want

1016
00:53:19,960 --> 00:53:23,279
Speaker 1: to come across as an apologist for expensive stocks. But

1017
00:53:23,760 --> 00:53:26,359
Speaker 1: that's before you even start talking about the frictions of

1018
00:53:27,120 --> 00:53:30,319
Speaker 1: executing a trade. Buying a stock buying an ETF. It

1019
00:53:30,520 --> 00:53:33,239
Speaker 1: used to be immensely expensive to go out and just

1020
00:53:33,360 --> 00:53:35,920
Speaker 1: buy a stock. That isn't the case anymore, right, So

1021
00:53:35,960 --> 00:53:37,440
Speaker 1: if you may have had to pay more than one

1022
00:53:37,480 --> 00:53:39,920
Speaker 1: probably paid more than one to two percent to actually

1023
00:53:39,960 --> 00:53:43,200
Speaker 1: get market like portfolios and get these diversified portfolios where now,

1024
00:53:43,239 --> 00:53:45,360
Speaker 1: like we talked in the first segment, they're basically free

1025
00:53:45,440 --> 00:53:47,840
Speaker 1: to get diversification. And so how much higher should pe

1026
00:53:48,040 --> 00:53:50,560
Speaker 1: ratios be going forward compared to the past, and you

1027
00:53:50,560 --> 00:53:53,200
Speaker 1: don't have that friction, You can say you could justify

1028
00:53:53,280 --> 00:53:57,320
Speaker 1: a compared to a six ten p um And whenever

1029
00:53:57,360 --> 00:53:59,359
Speaker 1: you really did have single digit ps, you had double

1030
00:53:59,400 --> 00:54:02,160
Speaker 1: digit interest rates. So how far are we from double

1031
00:54:02,200 --> 00:54:05,440
Speaker 1: digit interest rates? So the pushback on stocks are expensive?

1032
00:54:05,480 --> 00:54:08,319
Speaker 1: Stocks are cheap? Hey, stocks are cheapest hell throughout the

1033
00:54:08,360 --> 00:54:11,200
Speaker 1: seventies because you can get ten percent in treasury. So

1034
00:54:11,280 --> 00:54:13,520
Speaker 1: why would you be invested in stole if you could

1035
00:54:13,520 --> 00:54:15,960
Speaker 1: get ten percent in treasuries today? And we gladly go

1036
00:54:16,280 --> 00:54:19,400
Speaker 1: all my portfolio bonds. But if you're getting tempercent treasuries,

1037
00:54:19,440 --> 00:54:22,200
Speaker 1: we have an inflation problem which is going to be different,

1038
00:54:22,239 --> 00:54:26,080
Speaker 1: which let's talk about bonds. So there's a huge swath

1039
00:54:26,200 --> 00:54:29,279
Speaker 1: of bond bears who have been declaring the end of

1040
00:54:29,320 --> 00:54:33,640
Speaker 1: the thirty year Paul Volcan induced bond bull market. For

1041
00:54:33,760 --> 00:54:35,839
Speaker 1: I don't know, about ten years we've been hearing this

1042
00:54:35,880 --> 00:54:39,040
Speaker 1: is the end of the bond market our bonds. By

1043
00:54:39,320 --> 00:54:43,440
Speaker 1: the way, you guys value the way Wisdom Tree values

1044
00:54:43,640 --> 00:54:46,919
Speaker 1: fixed income? Are we in a bond bubble? Well, segu

1045
00:54:47,000 --> 00:54:48,319
Speaker 1: and I had did some op eds in the Law

1046
00:54:48,320 --> 00:54:51,960
Speaker 1: Street Journal together. You don't get to choose your title

1047
00:54:52,000 --> 00:54:53,960
Speaker 1: in the Wall Street Journal. So that's true. By the way,

1048
00:54:53,960 --> 00:54:56,560
Speaker 1: for everybody who writes a column. People don't know this.

1049
00:54:57,040 --> 00:55:01,480
Speaker 1: The editors choose the headline and very often it's clicking

1050
00:55:01,520 --> 00:55:04,960
Speaker 1: and catchy, but may not reflect the nuances of what

1051
00:55:05,000 --> 00:55:07,040
Speaker 1: you wrote. And the nuance of the article was by

1052
00:55:07,120 --> 00:55:09,680
Speaker 1: different paint stocks over tips because you had a you know,

1053
00:55:09,840 --> 00:55:12,440
Speaker 1: a one percent ten year tips. The first article in

1054
00:55:13,239 --> 00:55:15,239
Speaker 1: had one percent ten year tips, and we said you

1055
00:55:15,239 --> 00:55:20,080
Speaker 1: could get stocks yielding three and six years ago. That

1056
00:55:20,120 --> 00:55:23,080
Speaker 1: worked out. That was a good, good call. The article

1057
00:55:23,120 --> 00:55:25,919
Speaker 1: is the Great American bond Bubble. So the title was, yes,

1058
00:55:25,960 --> 00:55:28,000
Speaker 1: there's this huge bubble and bonds. Because you had this

1059
00:55:28,000 --> 00:55:30,520
Speaker 1: one percent tips, then you had this negative tips shield

1060
00:55:30,520 --> 00:55:32,640
Speaker 1: you had negative one percent, which was really and which

1061
00:55:33,600 --> 00:55:36,239
Speaker 1: a few years later you had bond yields. In the

1062
00:55:36,280 --> 00:55:37,520
Speaker 1: U S. You would say, I'm going to give the

1063
00:55:37,560 --> 00:55:40,320
Speaker 1: US government a hundred dollars and get back ninety dollars

1064
00:55:40,360 --> 00:55:43,279
Speaker 1: after inflation ten years later on the expectation that it

1065
00:55:43,320 --> 00:55:47,320
Speaker 1: wasn't even disinflation, that there was full blown deflation coming away.

1066
00:55:47,400 --> 00:55:49,839
Speaker 1: It was just massive risk aversion. It's like, why would

1067
00:55:49,840 --> 00:55:52,359
Speaker 1: you give the government and take back You would never

1068
00:55:52,440 --> 00:55:54,640
Speaker 1: think you would have a ten year negative tips shield,

1069
00:55:54,800 --> 00:55:56,800
Speaker 1: but guess where you do have that today? You still

1070
00:55:56,840 --> 00:56:00,880
Speaker 1: have huge negative tips or inflation adjust body was in Europe.

1071
00:56:00,920 --> 00:56:05,920
Speaker 1: I mean Germany's tenure tips are negative, which which is

1072
00:56:05,960 --> 00:56:08,960
Speaker 1: not a surprise when you look at you had a

1073
00:56:09,000 --> 00:56:12,960
Speaker 1: financial crisis hit the whole world. But the order of

1074
00:56:13,040 --> 00:56:15,439
Speaker 1: recovery was the U S was the first and most

1075
00:56:15,480 --> 00:56:19,680
Speaker 1: aggressive responder. As much as people screamed about KWI and Zurup,

1076
00:56:20,280 --> 00:56:23,920
Speaker 1: we were the first there. Then it's arguable that Japan

1077
00:56:24,120 --> 00:56:27,120
Speaker 1: was next and Europe is still the lagger. Is that

1078
00:56:27,280 --> 00:56:29,680
Speaker 1: a fair description? Yeah? And I think even from where

1079
00:56:29,880 --> 00:56:32,080
Speaker 1: quee and monterary policy is going, you have the FED

1080
00:56:32,200 --> 00:56:35,520
Speaker 1: is quote unquote normalizing we're raising rates, we're reducing our

1081
00:56:35,520 --> 00:56:40,080
Speaker 1: balance sheet. You have Japan targeting zero yields on the tenure,

1082
00:56:40,600 --> 00:56:44,120
Speaker 1: so they sort of outsourced their monetary policy to the US.

1083
00:56:44,560 --> 00:56:47,200
Speaker 1: You have the ECB negative rates at the short end,

1084
00:56:47,320 --> 00:56:50,120
Speaker 1: you have them still aggressively expanding the balance sheet. Um,

1085
00:56:50,120 --> 00:56:52,160
Speaker 1: but you could still say, why should somebody have a

1086
00:56:52,320 --> 00:56:57,359
Speaker 1: negative inflation adjusted body for tenure? And that's a pretty

1087
00:56:57,400 --> 00:57:02,200
Speaker 1: aggressive statement that that's rational unless you're you really have

1088
00:57:02,440 --> 00:57:06,560
Speaker 1: an expectation that we're entering a period of deflation and

1089
00:57:06,600 --> 00:57:09,399
Speaker 1: your money is worth more today than tomorrow. I mean,

1090
00:57:09,440 --> 00:57:11,600
Speaker 1: that's the only way I can rationalize it. And these

1091
00:57:11,640 --> 00:57:14,240
Speaker 1: inflation adjusted yields, I mean, it's it's it's hard. It's

1092
00:57:14,280 --> 00:57:16,200
Speaker 1: just a sign of risk aversion that you don't trust

1093
00:57:16,280 --> 00:57:18,520
Speaker 1: money in the banks, that makes sense, and you don't

1094
00:57:18,520 --> 00:57:20,400
Speaker 1: want to get the negative you know, the CBS at

1095
00:57:20,400 --> 00:57:23,280
Speaker 1: negative forty and so they're they're they're sort of taxing

1096
00:57:23,280 --> 00:57:26,000
Speaker 1: your money by keeping them in and cash at the bank.

1097
00:57:27,000 --> 00:57:29,280
Speaker 1: You and I can talk about this stuff forever, but

1098
00:57:29,360 --> 00:57:32,200
Speaker 1: I only have you for a finite amount of time.

1099
00:57:32,320 --> 00:57:35,800
Speaker 1: So what say we jump to my favorite questions that

1100
00:57:35,880 --> 00:57:40,320
Speaker 1: I ask all of my guests. The first one is

1101
00:57:40,440 --> 00:57:43,880
Speaker 1: tell me something about your background that most people don't know.

1102
00:57:44,720 --> 00:57:46,400
Speaker 1: You know. So, and I think about this. I have

1103
00:57:46,480 --> 00:57:49,360
Speaker 1: two young daughters there, two and five, and you think

1104
00:57:49,360 --> 00:57:52,040
Speaker 1: about how much of where what you do at a

1105
00:57:52,040 --> 00:57:54,200
Speaker 1: young age influences You're like, you sort of think back

1106
00:57:54,240 --> 00:57:56,080
Speaker 1: to like where how do I get to where I am?

1107
00:57:56,120 --> 00:57:59,040
Speaker 1: And there's obviously the proximate causes getting linked up with

1108
00:57:59,080 --> 00:58:01,520
Speaker 1: Siegel at at Pen and how did I get hooked

1109
00:58:01,600 --> 00:58:03,040
Speaker 1: up with that and the people you met at Pen?

1110
00:58:03,400 --> 00:58:05,800
Speaker 1: But I actually go back to my dad says it

1111
00:58:05,840 --> 00:58:08,120
Speaker 1: goes back to when I was two and he would

1112
00:58:08,160 --> 00:58:10,080
Speaker 1: read me the you know, the Wall Streetjournal page in

1113
00:58:10,080 --> 00:58:12,080
Speaker 1: stock pages, showing me numbers and getting me interested in

1114
00:58:12,160 --> 00:58:15,560
Speaker 1: stocks from two years old on his knee, you know.

1115
00:58:15,680 --> 00:58:18,480
Speaker 1: So he thinks it was that that early. Um, I

1116
00:58:18,520 --> 00:58:20,840
Speaker 1: think about when did I really get good at math?

1117
00:58:21,040 --> 00:58:24,000
Speaker 1: And so when I was in first grade, Um, my

1118
00:58:24,040 --> 00:58:26,000
Speaker 1: parents moved to Baltimore for six months and I went

1119
00:58:26,040 --> 00:58:28,280
Speaker 1: to this Hebrew day school where they taught half the

1120
00:58:28,360 --> 00:58:31,160
Speaker 1: day in Hebrew and half the day in English Hebrew.

1121
00:58:31,320 --> 00:58:33,320
Speaker 1: So I spoke more Hebrew in first grade than I

1122
00:58:33,400 --> 00:58:35,480
Speaker 1: ever did ever. Again, so we moved down to Florida

1123
00:58:35,640 --> 00:58:38,160
Speaker 1: and that was end of that. But I was you

1124
00:58:38,200 --> 00:58:40,880
Speaker 1: could could have started speaking Yiddish in parts of so

1125
00:58:40,920 --> 00:58:42,840
Speaker 1: Supposedly when I moved back to South Florida, I was

1126
00:58:42,880 --> 00:58:46,720
Speaker 1: teaching people Hebrew in my class. But in first grade

1127
00:58:46,880 --> 00:58:49,560
Speaker 1: I was already in second grade math, so they accelerated me.

1128
00:58:49,560 --> 00:58:51,880
Speaker 1: And then I just always thought of myself as really

1129
00:58:51,880 --> 00:58:54,440
Speaker 1: good in math, sort of advanced from that one. You know,

1130
00:58:54,520 --> 00:58:57,920
Speaker 1: that first grade where you just get this edge from

1131
00:58:57,960 --> 00:58:59,760
Speaker 1: a different school and you transfer back to a different

1132
00:58:59,760 --> 00:59:03,960
Speaker 1: schoo And how much that then to establish my foundation

1133
00:59:04,000 --> 00:59:07,160
Speaker 1: throughout the rest of middle school, high school, college, coming

1134
00:59:07,200 --> 00:59:09,880
Speaker 1: in with a year's worth of credit so I could

1135
00:59:09,880 --> 00:59:11,840
Speaker 1: take off a year to work with Siegel. All these

1136
00:59:11,880 --> 00:59:14,480
Speaker 1: things started from basically when I was in first grade.

1137
00:59:14,800 --> 00:59:16,640
Speaker 1: You had you had an edge in first grade, and

1138
00:59:16,680 --> 00:59:19,040
Speaker 1: you just carried that forward, never let anybody catch up.

1139
00:59:19,360 --> 00:59:21,600
Speaker 1: I mean, it's it's hard to but I think it

1140
00:59:21,640 --> 00:59:24,960
Speaker 1: does carry all the way back there. So here's a

1141
00:59:25,040 --> 00:59:29,480
Speaker 1: silly question for you, but I'm assuming we can expand

1142
00:59:29,520 --> 00:59:32,800
Speaker 1: on it. Who are your early mentors and feel free

1143
00:59:32,800 --> 00:59:36,400
Speaker 1: to talk about Siegel although we've really discussed him a lot.

1144
00:59:36,480 --> 00:59:39,720
Speaker 1: At what you want or or describe other mentors. Yeah,

1145
00:59:39,760 --> 00:59:41,840
Speaker 1: I mean, so he's obviously been the number one that

1146
00:59:41,920 --> 00:59:44,520
Speaker 1: shaped the last twenty years. Um. I think one of

1147
00:59:44,560 --> 00:59:47,600
Speaker 1: the things that I hope to embody UM is he

1148
00:59:47,600 --> 00:59:49,880
Speaker 1: he said to me, you know, despite all he had

1149
00:59:49,920 --> 00:59:52,480
Speaker 1: obviously was successful from the books and the speaking and

1150
00:59:52,480 --> 00:59:55,200
Speaker 1: then wisdom he took it to another level. But he

1151
00:59:55,280 --> 01:00:01,800
Speaker 1: told me once that despite all that success, se um like,

1152
01:00:01,840 --> 01:00:04,400
Speaker 1: the impact he had on me over time was like

1153
01:00:04,480 --> 01:00:07,640
Speaker 1: just more even more rewarding. So I hope to have

1154
01:00:07,760 --> 01:00:10,320
Speaker 1: that influence on people who work with me. And so

1155
01:00:10,880 --> 01:00:13,600
Speaker 1: for I'm sure that my team is listening in when

1156
01:00:13,600 --> 01:00:15,600
Speaker 1: the podcast comes out, I hope to have that influence

1157
01:00:15,640 --> 01:00:18,560
Speaker 1: on them. And uh, you know, you have to embrace

1158
01:00:18,600 --> 01:00:20,000
Speaker 1: it like I embrace it with him, and you gotta

1159
01:00:20,080 --> 01:00:22,360
Speaker 1: push me to hopefully know my team tries to take

1160
01:00:22,360 --> 01:00:24,480
Speaker 1: me up on that. Beyond that, I mean the co

1161
01:00:24,560 --> 01:00:28,760
Speaker 1: founder's Wisdom Tree Jonathan Steinberg, which Channa Circustano gave a

1162
01:00:28,840 --> 01:00:31,240
Speaker 1: trust in me at a young age. I mean I

1163
01:00:31,280 --> 01:00:33,360
Speaker 1: was when I joined them twenty two years old, twenty

1164
01:00:33,400 --> 01:00:35,440
Speaker 1: three years old, and they made me head of research

1165
01:00:35,480 --> 01:00:38,920
Speaker 1: for his twenty seven managing a few billion dollars. So

1166
01:00:39,040 --> 01:00:43,800
Speaker 1: the trust and confidence in just seeing talent and trying

1167
01:00:43,800 --> 01:00:45,760
Speaker 1: to help you put them in a position to do well.

1168
01:00:46,000 --> 01:00:49,120
Speaker 1: Was was unbelievable. So they've mentored me in in unbelievable ways,

1169
01:00:49,800 --> 01:00:52,360
Speaker 1: um and and Seorat of I try to aspire to be.

1170
01:00:52,600 --> 01:00:55,800
Speaker 1: I mean, John O, our CEO, is really unbelievable character

1171
01:00:55,920 --> 01:00:58,800
Speaker 1: and it really leads us in a way that just

1172
01:00:58,840 --> 01:01:01,240
Speaker 1: what he's been able to overcome in terms of building

1173
01:01:01,280 --> 01:01:03,520
Speaker 1: Wisdom Tree, I mean, it's the odds were definitely stacked

1174
01:01:03,520 --> 01:01:07,240
Speaker 1: against him, and he's just built this incredible team and

1175
01:01:07,280 --> 01:01:10,520
Speaker 1: motivated us all to rally around it and keeps us

1176
01:01:10,560 --> 01:01:14,440
Speaker 1: motivated every day. So let's talk about investors. What investors

1177
01:01:14,640 --> 01:01:22,280
Speaker 1: influenced your approach to markets? Valuation, ETFs, etcetera. UM, some

1178
01:01:22,320 --> 01:01:24,600
Speaker 1: of the standards, I mean, it's very value based investing.

1179
01:01:24,640 --> 01:01:27,520
Speaker 1: So it's it's you know, you've read everything Buffets written

1180
01:01:27,600 --> 01:01:30,880
Speaker 1: and so the Behavioral Finance Crew from Failure and all

1181
01:01:30,960 --> 01:01:34,160
Speaker 1: all that he's written on on behavioral finance Schiller and

1182
01:01:34,280 --> 01:01:36,800
Speaker 1: that it's it's it's a it's a standard thing in

1183
01:01:37,120 --> 01:01:41,640
Speaker 1: the value quality type investing is a lot of it. UM.

1184
01:01:41,720 --> 01:01:44,040
Speaker 1: The one of the books I remember and he's they're

1185
01:01:44,040 --> 01:01:46,160
Speaker 1: also getting a great following now. You know, in terms

1186
01:01:46,160 --> 01:01:48,640
Speaker 1: of the quant finance group, you know, you've read things

1187
01:01:48,640 --> 01:01:52,360
Speaker 1: like What Works on Wall Street from the O'shaughnessys. That

1188
01:01:52,400 --> 01:01:54,320
Speaker 1: was one of the first books I read with working

1189
01:01:54,320 --> 01:01:56,520
Speaker 1: with Siegel, So all those, So it's a lot of

1190
01:01:56,560 --> 01:02:00,320
Speaker 1: the standard quant value quality type folks. So let's let's

1191
01:02:00,320 --> 01:02:05,080
Speaker 1: talk about books. This is everybody's favorite, UM question. I'm

1192
01:02:05,080 --> 01:02:08,800
Speaker 1: going to put down O Sam's What Works on Wall Street?

1193
01:02:08,840 --> 01:02:12,240
Speaker 1: What are some of your favorite books? By the way, fiction, nonfiction,

1194
01:02:12,320 --> 01:02:15,520
Speaker 1: investment related, whatever? What? What do you what have you

1195
01:02:15,600 --> 01:02:18,880
Speaker 1: enjoyed reading? What are you reading now? Yeah? And and

1196
01:02:18,520 --> 01:02:21,320
Speaker 1: and there's actually an overlap there from from O. Sam.

1197
01:02:21,400 --> 01:02:23,520
Speaker 1: So Patrick's reading list is probably one of my go

1198
01:02:23,640 --> 01:02:26,680
Speaker 1: to sources. UM. I think on a personal level, one

1199
01:02:26,680 --> 01:02:30,240
Speaker 1: of the books that I read that has influenced me

1200
01:02:30,280 --> 01:02:33,120
Speaker 1: in my thinking is there's a book Mountains Beyond Mountains

1201
01:02:33,200 --> 01:02:38,120
Speaker 1: from from Tracy Kidder who profiled Paul Farmer, and you

1202
01:02:38,120 --> 01:02:40,280
Speaker 1: know he it was a really moving book for me

1203
01:02:40,480 --> 01:02:43,840
Speaker 1: and as I thought about how do I become, you know,

1204
01:02:43,960 --> 01:02:47,080
Speaker 1: is there some charities to embrace? But Farmers started this group,

1205
01:02:47,120 --> 01:02:50,680
Speaker 1: Partners in Health, and it's one that I've embraced personally

1206
01:02:50,880 --> 01:02:54,080
Speaker 1: partners in health. Yeah, so he's just as a one man.

1207
01:02:54,360 --> 01:02:58,040
Speaker 1: He's a Harvard doctor goes to Haiti. That the book

1208
01:02:58,080 --> 01:03:00,120
Speaker 1: was all about his expeditions to Haiti and how is

1209
01:03:00,160 --> 01:03:02,880
Speaker 1: devoting his life to improving the health conditions in Haiti.

1210
01:03:03,320 --> 01:03:06,080
Speaker 1: But it's now expanded to their like in twelve different countries.

1211
01:03:06,120 --> 01:03:09,240
Speaker 1: But it was one that I found an O'Shaughnessy's list,

1212
01:03:09,280 --> 01:03:11,560
Speaker 1: and it's it's one that it definitely touched me and

1213
01:03:11,760 --> 01:03:13,880
Speaker 1: I sort of spread that to my friends who are

1214
01:03:13,920 --> 01:03:16,240
Speaker 1: involved in health and in health policy. It's it's a

1215
01:03:16,240 --> 01:03:19,360
Speaker 1: really fascinating book. What are you reading right now? What's

1216
01:03:19,400 --> 01:03:22,080
Speaker 1: on your nights? Then one that I think is actually

1217
01:03:22,080 --> 01:03:24,520
Speaker 1: for the next decade that I just i'm sort of

1218
01:03:24,520 --> 01:03:28,960
Speaker 1: in finishing is um Destined for War, which I Destined

1219
01:03:29,080 --> 01:03:32,080
Speaker 1: for War Wow, which is some title which I picked

1220
01:03:32,160 --> 01:03:35,120
Speaker 1: up from Kyle Bass on one of the other podcasts

1221
01:03:35,160 --> 01:03:37,800
Speaker 1: I just listened to, and so he it talks about

1222
01:03:38,400 --> 01:03:43,480
Speaker 1: it's a Graham Allison, I think is the author, and

1223
01:03:43,720 --> 01:03:48,000
Speaker 1: it talks about it really the US versus China, and

1224
01:03:48,080 --> 01:03:50,720
Speaker 1: so it's it's as you think about the two rivalries

1225
01:03:51,000 --> 01:03:54,640
Speaker 1: over the next ten years. China is ascending, It's challenging

1226
01:03:54,680 --> 01:03:58,120
Speaker 1: the US, and the book goes through the times in

1227
01:03:58,240 --> 01:04:00,919
Speaker 1: history you had these ascending rival and it's it goes

1228
01:04:00,960 --> 01:04:04,240
Speaker 1: back to Athens and Sparta, and it goes through all

1229
01:04:04,240 --> 01:04:06,480
Speaker 1: these different examples of when you had these up and

1230
01:04:06,520 --> 01:04:09,840
Speaker 1: comers rivaling. You know, the statu the embedded powers and

1231
01:04:10,160 --> 01:04:13,400
Speaker 1: attentions that creates. And I do think China's ascendance is

1232
01:04:13,400 --> 01:04:15,960
Speaker 1: one of the big stories for the next ten years, no,

1233
01:04:16,080 --> 01:04:18,840
Speaker 1: no doubt. And thank you for not using the word frenemies.

1234
01:04:18,880 --> 01:04:23,160
Speaker 1: I I we all really appreciate that. Um. So you've

1235
01:04:23,160 --> 01:04:26,440
Speaker 1: been in the industry for almost twenty years. Is that

1236
01:04:26,520 --> 01:04:29,520
Speaker 1: a fair statements? Since when did you graduate? Warden? So

1237
01:04:29,560 --> 01:04:32,400
Speaker 1: I've been working, I'd say, really I would. I would

1238
01:04:32,400 --> 01:04:34,200
Speaker 1: mark my start date of two thousand one once I

1239
01:04:34,200 --> 01:04:37,160
Speaker 1: started working for Segull, but we graduated three al right,

1240
01:04:37,200 --> 01:04:39,920
Speaker 1: So you're you're fifteen years coming up on on on

1241
01:04:40,040 --> 01:04:43,320
Speaker 1: twenty years. What do you think is the most significant

1242
01:04:43,520 --> 01:04:46,840
Speaker 1: changes that have taken place taken place over the course

1243
01:04:46,880 --> 01:04:51,600
Speaker 1: of that arc of time within the financial industry. Certainly

1244
01:04:51,760 --> 01:04:55,400
Speaker 1: ETFs have exploded, and that's right where trillion now something

1245
01:04:55,640 --> 01:04:58,480
Speaker 1: that we were three billion to ten times that, right,

1246
01:04:58,520 --> 01:05:01,040
Speaker 1: So that's certainly the one of the major trends and

1247
01:05:01,040 --> 01:05:03,760
Speaker 1: we're I'm lucky to be part of it and trying

1248
01:05:03,800 --> 01:05:05,920
Speaker 1: to shape it and try to continue to shape it.

1249
01:05:06,080 --> 01:05:09,360
Speaker 1: And certainly technology has just advanced just such remarkable space

1250
01:05:10,000 --> 01:05:12,240
Speaker 1: that that's the next ten years is gonna be all

1251
01:05:12,240 --> 01:05:18,120
Speaker 1: about how you marry technology increasingly with investments, and that's

1252
01:05:18,400 --> 01:05:20,840
Speaker 1: I hope to be part of that as well. And um,

1253
01:05:20,920 --> 01:05:22,800
Speaker 1: your ears must have been burning last week. I was

1254
01:05:22,840 --> 01:05:25,640
Speaker 1: in an e t F event, um, and your name

1255
01:05:25,680 --> 01:05:28,240
Speaker 1: had come up several times. I believe one of your

1256
01:05:28,280 --> 01:05:32,160
Speaker 1: staff members was was actually there. Um, So let's talk

1257
01:05:32,240 --> 01:05:35,360
Speaker 1: about the next major shifts. It's the rise of etf

1258
01:05:35,440 --> 01:05:38,880
Speaker 1: is is the biggest single factor over the past ten

1259
01:05:39,000 --> 01:05:42,320
Speaker 1: fifteen years. What do you think the next major change

1260
01:05:42,360 --> 01:05:48,720
Speaker 1: is gonna be. Well, everything has been broad based exposure

1261
01:05:48,800 --> 01:05:52,280
Speaker 1: so far, so you really where there's still the highest

1262
01:05:52,280 --> 01:05:54,560
Speaker 1: feet So if you think about this active passive shift,

1263
01:05:56,080 --> 01:05:59,240
Speaker 1: there hasn't been. I mean, the hedge funds is in

1264
01:05:59,320 --> 01:06:02,280
Speaker 1: some ways so the most expensive part of the market.

1265
01:06:02,280 --> 01:06:04,680
Speaker 1: Where you know, our CEO likes to say, John likes

1266
01:06:04,680 --> 01:06:06,640
Speaker 1: to say that the rich get the worst advice, and

1267
01:06:06,680 --> 01:06:09,240
Speaker 1: so they get put in this most expensive advice for sure. Yeah,

1268
01:06:09,280 --> 01:06:13,120
Speaker 1: the most expensive and worst together. Come. Come for the

1269
01:06:13,200 --> 01:06:15,520
Speaker 1: high fees, stay for the under performance and the not

1270
01:06:15,600 --> 01:06:18,760
Speaker 1: ability to get your money back, no transparency, and so

1271
01:06:19,680 --> 01:06:22,600
Speaker 1: it's it's going we're going to increasingly go after that.

1272
01:06:23,200 --> 01:06:25,600
Speaker 1: And and so we start off as very broad based beta.

1273
01:06:25,920 --> 01:06:29,040
Speaker 1: We're doing more along short, more alternatives. We're gonna go

1274
01:06:29,080 --> 01:06:32,640
Speaker 1: after that too. So alternatives being hedge funds, private equity,

1275
01:06:32,720 --> 01:06:37,640
Speaker 1: venture capital. You think that entire UM, well, private equity

1276
01:06:37,680 --> 01:06:39,880
Speaker 1: can't be in ETF al right, that's no doubt about that.

1277
01:06:39,960 --> 01:06:42,960
Speaker 1: But is that sector of the of the investment world

1278
01:06:43,280 --> 01:06:47,120
Speaker 1: ripe for disruption UM We definitely, we definitely think about that.

1279
01:06:47,200 --> 01:06:49,760
Speaker 1: We figured out how do we rope that into things

1280
01:06:49,800 --> 01:06:53,560
Speaker 1: like our advisor engine UM Investment partnership in terms of

1281
01:06:53,600 --> 01:06:57,280
Speaker 1: bringing that technology oriented to the masses. But there's gonna

1282
01:06:57,280 --> 01:06:59,200
Speaker 1: be elements of trying to I think there's more we

1283
01:06:59,200 --> 01:07:02,240
Speaker 1: can do there on the private side. But but in

1284
01:07:02,560 --> 01:07:04,520
Speaker 1: the where the public side where you can where we

1285
01:07:04,640 --> 01:07:06,440
Speaker 1: focus on the et F market, we're definitely gonna think

1286
01:07:06,440 --> 01:07:09,600
Speaker 1: about doing alternatives and long short strategies. Tell us about

1287
01:07:09,600 --> 01:07:13,400
Speaker 1: a time you've failed and what you learned from the experience. UM,

1288
01:07:13,440 --> 01:07:15,080
Speaker 1: I mean I think about our E T s. I

1289
01:07:15,080 --> 01:07:17,080
Speaker 1: mean every E t F is a little startup, and

1290
01:07:17,760 --> 01:07:19,880
Speaker 1: so we have a number of ETFs that fail. You

1291
01:07:19,920 --> 01:07:23,840
Speaker 1: close ets down, UM, you try to examine why your

1292
01:07:23,920 --> 01:07:26,960
Speaker 1: thesis when you start, UM, when you launched it, and

1293
01:07:27,040 --> 01:07:31,400
Speaker 1: it didn't gain assets attraction? What caused that? So we're

1294
01:07:31,440 --> 01:07:34,880
Speaker 1: constantly evaluating our failures and trying to learn from them

1295
01:07:34,880 --> 01:07:38,360
Speaker 1: and figure out can we do things differently over time?

1296
01:07:38,400 --> 01:07:40,520
Speaker 1: And a means of our greatest success stories have come

1297
01:07:40,560 --> 01:07:42,439
Speaker 1: from changing. As we talked about earlier on, you change

1298
01:07:42,480 --> 01:07:45,040
Speaker 1: funds that didn't take off, and you change them UM,

1299
01:07:45,400 --> 01:07:47,120
Speaker 1: and then you say, you know, why did I miss

1300
01:07:47,200 --> 01:07:49,680
Speaker 1: that segment? Things that took off that you could have

1301
01:07:49,720 --> 01:07:52,240
Speaker 1: been their positioned well for and you try to learn

1302
01:07:52,280 --> 01:07:54,800
Speaker 1: from all those things. So let me let me ask

1303
01:07:54,920 --> 01:07:58,400
Speaker 1: the part B to that question. You guys have over

1304
01:07:58,480 --> 01:08:02,480
Speaker 1: fifty different funds, how and some of them have clearly

1305
01:08:03,040 --> 01:08:05,520
Speaker 1: caught a little lightning in a bottle. They've done really well.

1306
01:08:05,880 --> 01:08:10,280
Speaker 1: How do you try and sprinkle that into a fund

1307
01:08:10,360 --> 01:08:12,560
Speaker 1: that might not be doing as well as as you

1308
01:08:12,640 --> 01:08:15,320
Speaker 1: had originally hoped for when it was launched, and I

1309
01:08:15,440 --> 01:08:18,000
Speaker 1: mean doing as well in terms of performance, I mean

1310
01:08:18,479 --> 01:08:21,680
Speaker 1: resonating with investors in attracting assets. Yeah, we close. We

1311
01:08:21,720 --> 01:08:23,559
Speaker 1: have close to a hundred funds in the US today,

1312
01:08:23,920 --> 01:08:27,240
Speaker 1: so we have a very broad menu um and they

1313
01:08:27,280 --> 01:08:29,640
Speaker 1: are all I actually view all of our ets as

1314
01:08:29,680 --> 01:08:31,960
Speaker 1: little options where your paints. You know, you're paying a

1315
01:08:32,000 --> 01:08:34,960
Speaker 1: fixed cost and you've got to figure out until they

1316
01:08:34,960 --> 01:08:37,040
Speaker 1: get to break even, and so you're paying this sort

1317
01:08:37,040 --> 01:08:40,400
Speaker 1: of option premium until they potentially can have big upside.

1318
01:08:40,760 --> 01:08:43,000
Speaker 1: And so at some point you have to say, that's

1319
01:08:43,000 --> 01:08:45,720
Speaker 1: a good way to contextualize that. It's it's right they

1320
01:08:45,720 --> 01:08:48,360
Speaker 1: either you're either willing to pay that option premium because

1321
01:08:48,360 --> 01:08:51,000
Speaker 1: you still think that option might really take off and

1322
01:08:51,000 --> 01:08:54,479
Speaker 1: then it has really big payoffs. It makes sense to me,

1323
01:08:54,840 --> 01:08:56,600
Speaker 1: and so that's really how I think about it. And

1324
01:08:56,600 --> 01:08:59,120
Speaker 1: so as long as we're still convinced there's a market opportunity,

1325
01:08:59,120 --> 01:09:01,639
Speaker 1: we you know, when we started in O six oh seven,

1326
01:09:01,680 --> 01:09:03,680
Speaker 1: we didn't have that kind of runway. We had to

1327
01:09:03,680 --> 01:09:07,320
Speaker 1: be much more careful. We have more runway today. You

1328
01:09:07,320 --> 01:09:10,479
Speaker 1: can afford to nurture things that might be a little

1329
01:09:10,640 --> 01:09:14,080
Speaker 1: pricey while internally to run it while waiting for it

1330
01:09:14,120 --> 01:09:16,880
Speaker 1: to hit break even for better because you believe in

1331
01:09:16,920 --> 01:09:19,080
Speaker 1: the you have a high degree of conviction and in

1332
01:09:19,120 --> 01:09:21,519
Speaker 1: the idea, and we do close things down. You know,

1333
01:09:21,560 --> 01:09:23,160
Speaker 1: of course from time to time when you've just given

1334
01:09:23,240 --> 01:09:24,720
Speaker 1: up and you think you've given it its time and

1335
01:09:24,760 --> 01:09:26,960
Speaker 1: you've let a play out, but you know, we want

1336
01:09:27,000 --> 01:09:29,599
Speaker 1: to try to give things to take three to five

1337
01:09:29,640 --> 01:09:31,840
Speaker 1: years before you evaluate whether or not it's really been

1338
01:09:32,479 --> 01:09:34,599
Speaker 1: why you haven't been successful, and you could still close

1339
01:09:34,640 --> 01:09:36,160
Speaker 1: things down, then you wish you didn't close it down.

1340
01:09:36,800 --> 01:09:40,639
Speaker 1: That's interesting. Alright, we're down to our last few questions. UM,

1341
01:09:40,680 --> 01:09:43,040
Speaker 1: you're a relatively young guy, so I'm going to ask

1342
01:09:43,120 --> 01:09:47,080
Speaker 1: this differently. What do you do to relax outside of

1343
01:09:47,080 --> 01:09:50,920
Speaker 1: the office. Um? And my wife got into yoga, so

1344
01:09:50,960 --> 01:09:53,800
Speaker 1: she she got teacher trained as a yoga teacher. So

1345
01:09:53,880 --> 01:09:56,800
Speaker 1: this summer's she we go down the Jersey Shore by

1346
01:09:56,800 --> 01:09:59,080
Speaker 1: the beach there and that's where we do with the

1347
01:09:59,080 --> 01:10:02,120
Speaker 1: most yoga. Um is our We have a Jersey Shore

1348
01:10:02,240 --> 01:10:06,400
Speaker 1: yoga teacher. That's it's like our guru. UM In in

1349
01:10:06,400 --> 01:10:08,559
Speaker 1: in Philly where we live, we have a pool. And

1350
01:10:08,640 --> 01:10:10,400
Speaker 1: she says, if I ever finance doesn't work out, I

1351
01:10:10,400 --> 01:10:13,360
Speaker 1: should be a swim teacher. So lovelet's spending time in

1352
01:10:13,400 --> 01:10:16,080
Speaker 1: the water with the kids, and but a combination of

1353
01:10:16,160 --> 01:10:19,760
Speaker 1: yoga walking and we did the alf architect mark for

1354
01:10:19,800 --> 01:10:21,400
Speaker 1: the fall and which was that looks fascinating. It was

1355
01:10:21,400 --> 01:10:24,719
Speaker 1: a big New York Times article about that. West is great.

1356
01:10:24,760 --> 01:10:27,200
Speaker 1: I really like everything those guys do. Yeah, so it's

1357
01:10:27,240 --> 01:10:31,760
Speaker 1: a lot of walking as well. Um, you're a relatively

1358
01:10:31,840 --> 01:10:35,400
Speaker 1: young person who graduated school not too long ago. But

1359
01:10:35,520 --> 01:10:38,360
Speaker 1: if a millennial or a recent graduate came up to

1360
01:10:38,400 --> 01:10:41,080
Speaker 1: you and said, hey, I'm interested in the career of finance,

1361
01:10:41,640 --> 01:10:44,600
Speaker 1: what sort of advice would you give them? You know,

1362
01:10:44,600 --> 01:10:46,160
Speaker 1: when I think back to how I got hooked up

1363
01:10:46,160 --> 01:10:48,839
Speaker 1: with Segell, obviously can you find that mentor who can

1364
01:10:48,920 --> 01:10:52,000
Speaker 1: be useful for you? And the keywords I used there

1365
01:10:52,040 --> 01:10:55,639
Speaker 1: when I made my pitch was free work for free.

1366
01:10:55,840 --> 01:10:58,120
Speaker 1: And in reality you should pay people because it's really

1367
01:10:58,200 --> 01:11:00,840
Speaker 1: investment in their time. But I think out interns and

1368
01:11:00,880 --> 01:11:03,760
Speaker 1: even my cost to bring an intern on. If you're

1369
01:11:03,760 --> 01:11:05,360
Speaker 1: gonna have to spend time with things, they're not gonna

1370
01:11:05,360 --> 01:11:07,679
Speaker 1: add a lot of value upfront, and so they're actually

1371
01:11:07,680 --> 01:11:10,720
Speaker 1: a drag on you versus the time. And so you

1372
01:11:10,760 --> 01:11:14,120
Speaker 1: know that's true. Um, so you want to get find

1373
01:11:14,120 --> 01:11:15,600
Speaker 1: the right people who can mentor you and get the

1374
01:11:15,680 --> 01:11:17,920
Speaker 1: right opportunity, and and you got to put in a

1375
01:11:17,920 --> 01:11:20,559
Speaker 1: lot of time and effort early on don't come. You know,

1376
01:11:20,600 --> 01:11:23,880
Speaker 1: the millennials mentalities. They're entitled, So you've got to not

1377
01:11:23,920 --> 01:11:26,640
Speaker 1: feel entitled and work hard and and and a lot

1378
01:11:26,680 --> 01:11:30,120
Speaker 1: of good things will come. And our final question, what

1379
01:11:30,320 --> 01:11:33,800
Speaker 1: is it that you know about investing, indexing E t FS,

1380
01:11:34,200 --> 01:11:38,840
Speaker 1: dividends valuation today that you wish you knew seventeen years

1381
01:11:38,840 --> 01:11:42,880
Speaker 1: ago when you first started UH divid investing. When we

1382
01:11:42,920 --> 01:11:45,439
Speaker 1: looked at history going back fifty sixty years, I mean,

1383
01:11:45,520 --> 01:11:48,720
Speaker 1: dividends did very well during most down markets. Um, the

1384
01:11:48,760 --> 01:11:51,840
Speaker 1: O eight oh nine down market financials paid a lot

1385
01:11:51,840 --> 01:11:54,320
Speaker 1: of dividends, so it was not your typical down market

1386
01:11:54,320 --> 01:11:56,599
Speaker 1: in terms of how much down market protection you've got.

1387
01:11:56,960 --> 01:11:59,519
Speaker 1: So I think I learned more about sector concentration risk

1388
01:12:00,040 --> 01:12:03,320
Speaker 1: and just the risk of overly becoming concentrate in sectors

1389
01:12:03,320 --> 01:12:06,800
Speaker 1: despite what their value signals might say. So it's something

1390
01:12:06,800 --> 01:12:11,080
Speaker 1: on sector concentrations that you know, I've tried to think

1391
01:12:11,080 --> 01:12:13,479
Speaker 1: about more over time as we developed future products, is

1392
01:12:13,520 --> 01:12:16,280
Speaker 1: what what sort of the sector biases or how can

1393
01:12:16,280 --> 01:12:18,920
Speaker 1: you control for sectors in a way that you don't

1394
01:12:18,920 --> 01:12:22,680
Speaker 1: get overloaded in those times of crisis. We have been

1395
01:12:22,720 --> 01:12:25,839
Speaker 1: speaking with Jeremy Schwartz. He is the director of research

1396
01:12:26,280 --> 01:12:30,200
Speaker 1: at Wisdom Tree Investments. Uh, thank you, Jeremy for doing this.

1397
01:12:30,240 --> 01:12:32,840
Speaker 1: I really appreciate you being so generous with your time.

1398
01:12:33,000 --> 01:12:36,160
Speaker 1: Thanks for having me. If you enjoy this conversation, be

1399
01:12:36,240 --> 01:12:38,080
Speaker 1: sure to look up and intro down an Inch on

1400
01:12:38,120 --> 01:12:40,880
Speaker 1: Apple iTunes and you could see any of the other

1401
01:12:41,000 --> 01:12:46,720
Speaker 1: hundred and fifties something previous conversations we've had. We love

1402
01:12:46,800 --> 01:12:51,960
Speaker 1: your comments, feedback, end suggestions right to us at m

1403
01:12:51,960 --> 01:12:56,000
Speaker 1: IB podcast at Bloomberg dot net. I would be remiss

1404
01:12:56,000 --> 01:12:58,920
Speaker 1: if I did not thank my crack staff who helps

1405
01:12:59,000 --> 01:13:03,200
Speaker 1: me put together these podcasts each week. Medina Parwana is

1406
01:13:03,240 --> 01:13:07,559
Speaker 1: our audio producer and engineer par Excellence. Taylor Riggs is

1407
01:13:07,560 --> 01:13:11,560
Speaker 1: in charge of booking. Michael Batnick is our head of research.

1408
01:13:12,400 --> 01:13:15,839
Speaker 1: I'm Barry Retults. You've been listening to Masters in Business

1409
01:13:16,280 --> 01:13:17,519
Speaker 1: on Bloomberg Radio