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Speaker 1: M. This is Mesters in Business with Very Results on

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Speaker 1: Bluebird Radio. This week on the podcast, I have an

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Speaker 1: extra special guest. His name is Dave Nodded. And if

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Speaker 1: this sounds like to all friends just yammering about all

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Speaker 1: sorts of market eso ica, well that's because it is.

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Speaker 1: I know Dave for a long time, and we kinda

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Speaker 1: fell in love with each other's books, music, film, and

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Speaker 1: financial history when we first met a hundred years ago.

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Speaker 1: And so if it sounds like just too idiots talking

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Speaker 1: about really interesting stuff in great detail, and me probably

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Speaker 1: speaking more than I usually do during the podcast, well

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Speaker 1: that's probably because it is. Um. Dave is really a

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Speaker 1: fascinating person with an incredible depth of knowledge about well.

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Speaker 1: He's probably best known as the E T F guy,

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Speaker 1: and we literally talk about during the show. I got

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Speaker 1: tagged to present to the SEC about their new single

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Speaker 1: stock product, and my answer was, well, I get all

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Speaker 1: my information about this from nating. Why don't you speak

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Speaker 1: to him? And they said, we already do. But he

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Speaker 1: also has an incredible death of knowledge about market structures,

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Speaker 1: about what people get wrong about thinking about systems, about

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Speaker 1: what we get wrong about humans and capitalism and finance,

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Speaker 1: and I find Dave to be really just an intriguing,

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Speaker 1: fascinating guy, full of great humility and insights. And I

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Speaker 1: think you'll find this conversation to be really fascinating. With

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Speaker 1: no further ado, my interview with vertifies Dave noting, let's

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Speaker 1: start in thees when you were at Barclays, which eventually

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Speaker 1: becomes black Rock, I shares tell us about what you

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Speaker 1: did at Barclays. Oh, I mean mostly I got coffee

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Speaker 1: at the beginning, you know, and I joined, Uh, they

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Speaker 1: gave me the hypho leading title of Managing Director of

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Speaker 1: Corporate Strategy. What it really meant was I was picking

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Speaker 1: up little businesses nobody else wanted to pay any attention

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Speaker 1: to through all the acquisitions they were doing so. For

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Speaker 1: a while I ran Wells Fargo's four O win K

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Speaker 1: business because they had acquired that as part of Wells

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Speaker 1: Fargo Nico Investment Advisors when we did the Barkley's acquisition.

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Speaker 1: When Barkley's acquired Wells Fargo Nico, I then spent most

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Speaker 1: of my time in Asia shutting down Barkley's Dessert Wed businesses,

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Speaker 1: which were brokerage shops in Australia and Singapore Hong Kong, Japan. UM.

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Speaker 1: So I went around and sort of did some rationalization.

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Speaker 1: They basically sent the young kid out to get his

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Speaker 1: you know, you know what, handed go go go fire

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Speaker 1: a bunch of you know, Japanese salaryman that that had

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Speaker 1: to be a crazy experience being in Australia and Japan

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Speaker 1: in the nineties. It was. It was bonkers, and I

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Speaker 1: was very To be clear, I was young and incredibly stupid.

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Speaker 1: Now I'm just older and slightly less. Isn't that a

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Speaker 1: little redundant I say this. I say this not to

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Speaker 1: mock the young, but to reflect on my own youthful

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Speaker 1: indiscretions and stupidity. The story of growing a career is

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Speaker 1: recognizing how little you knew every previous five years, Yes exactly,

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Speaker 1: that five year review was like, wow, I had no

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Speaker 1: idea what the hell I was doing? Now I know,

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Speaker 1: and then you find out you really don't. So I started.

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Speaker 1: I started there. I was lucky enough to be on

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Speaker 1: the edges of a product which became webs, which became

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Speaker 1: I shares Um. I was absolutely not somebody driving the

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Speaker 1: train on that. I was the one reviewing, marketing copy

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Speaker 1: and you know, doing presentations to groups of institutions about

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Speaker 1: how to use the darn things. Who was driving the

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Speaker 1: train on that Oh my gosh, there were so many,

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Speaker 1: I mean, you know, success as a thousand fall others

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Speaker 1: at this point. And the folks that I mean, so

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Speaker 1: the people I was working with on the Wells Fai

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Speaker 1: Niko side because this was a joint project with Stanley

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Speaker 1: and other folks like that. UM, I was working with

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Speaker 1: Don Lusk and Patty Donne Fred Grower were sort of

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Speaker 1: the main group. Blake Grossman was the chief investment. He

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Speaker 1: stuck around at you know, post into b g I

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Speaker 1: for the rest of his career. Um. And so that

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Speaker 1: was that was the crew that was really doing the

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Speaker 1: hard work there. And then you know the Morgan Stanley side.

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Speaker 1: I was working with folks like Joe and Hill who

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Speaker 1: you know, um, Marian Stanley one of the quants there.

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Speaker 1: UM and then of course all the folks who were

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Speaker 1: coming in from the Amex like Nate Most. I mean,

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Speaker 1: it was it was a pretty big group of Jim

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Speaker 1: was he there at State Street? Um? After that was

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Speaker 1: that was Jim Ross was at State Street a little

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Speaker 1: bit after that when that was but that was you know,

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Speaker 1: when the Spiders build out this was very much counter

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Speaker 1: to to spy having been launched. So we were the

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Speaker 1: other side of the fence from that. Even though AMX

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Speaker 1: was the key, you know, AMEX was the glue holding

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Speaker 1: it together because they figured out a lot of the

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Speaker 1: how to do creation, redemption, and how to handle book.

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Speaker 1: So let me fast forward a couple of years. You

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Speaker 1: end up at et F dot com, which clearly is

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Speaker 1: a or at least at the time was a dominant

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Speaker 1: force in the E t F space when a lot

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Speaker 1: of the world of finance looked at ETFs a little scans,

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Speaker 1: a little skeptical like yeah, And that was really Jim Wyant.

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Speaker 1: He started something called the Index Universe with Stephen Showen

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Speaker 1: Fell somebody else you know in the industry UM who's

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Speaker 1: now working for I believe Market Beckers in Texas UM.

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Speaker 1: And you know, they they had this vision of understanding

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Speaker 1: that E T S which at that point we're still

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Speaker 1: largely institutional vehicles early two thousand's right. I mean there

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Speaker 1: were some advisor pick up, but you had to be

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Speaker 1: kind of on the front edge of finance or a

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Speaker 1: quant or running your own models, which in two thousand

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Speaker 1: three was not that common. Um they had the vision

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Speaker 1: there that oh no, this is where all the wealth

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Speaker 1: management is going to head um and built a business

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Speaker 1: which eventually, through you know, acquiring the right names in

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Speaker 1: you or else, became et F dot com. And then we,

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Speaker 1: you know, we myself, Matt Hogan, Jim Wyant, a bunch

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Speaker 1: of other folks built that business up into a you know,

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Speaker 1: pretty respectable, chunky business that had a big conference and

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Speaker 1: a huge data but I was focused almost exclusively on

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Speaker 1: the data side. Um. And then we broke that into

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Speaker 1: pieces so that that was solved though, wasn't it broken?

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Speaker 1: So when you say broke into pieces, acquires in a

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Speaker 1: positive way. Yeah, Like the pieces ended up being worth

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Speaker 1: more than the part, which is not uncom not uncommon

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Speaker 1: at all, especially when you're bolting together businesses that do

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Speaker 1: in fact have silos themselves. So the data business was

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Speaker 1: a natural fit for facts that which needed usc t

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Speaker 1: F data. So Elizabeth K Facts is a is a big,

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Speaker 1: big operator on that. And now they're now there. I

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Speaker 1: think that that we re license the data that I

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Speaker 1: helped build over a verify right, I mean they are

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Speaker 1: now I still think the go to source for primary

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Speaker 1: et F data, So that business continues to run over

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Speaker 1: there and and you know, and now here I am

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Speaker 1: at Vertifi doing largely a lot of the same work,

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Speaker 1: also pushing a big conference that we're excited about Exchange

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Speaker 1: in Miami and Florida. We're gonna talk about Vertifi. We're

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Speaker 1: gonna talk about Exchange, which is one of my favorite

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Speaker 1: events every year. It's always a blast. Um when you

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Speaker 1: were running the conference beforehand. The old conference, this was

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Speaker 1: at the Diplomat Hotel in Hollywood, Florida, was always late

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Speaker 1: January early February, which occasionally went interview with my vacation schedule.

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Speaker 1: But you know, to get out of New York in

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Speaker 1: February and spend time with three thousand people and just

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Speaker 1: absolutely a list speakers. Um, you know, Derek Jeter and

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Speaker 1: Go Go I remember, um Joe Montana. Like the sports

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Speaker 1: figures were always fascinating, but so too were the finance figures.

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Speaker 1: You would people that were very much rock stars in

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Speaker 1: that space. Yeah, and that was that was an interesting time.

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Speaker 1: I think that's sort of the ten years pre prandemics

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Speaker 1: are between GFC and pandemic whatever we're gonna call that window.

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Speaker 1: It's not a lost decade. It was a great decade,

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Speaker 1: but in that window, like the I mean you were

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Speaker 1: on it to the conference circuit was lit. There was

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Speaker 1: there was a really interesting finance relevant event every other

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Speaker 1: week at least all year long. Well, keep in mind

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Speaker 1: what was going on back then. So first you had

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Speaker 1: the rise of ETFs. You had a radical expansion of passive.

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Speaker 1: My my theory is post Great Financial Crisis, mom and

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Speaker 1: pop said, you know, we're done playing this game. We're

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Speaker 1: just gonna put the money, let Mr Market do his thing,

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Speaker 1: and we'll find out how we did when we get

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Speaker 1: ready to retire. Um. But you had that, you had

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Speaker 1: e t F you rise a passive, but you also

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Speaker 1: had this incredible I'm reluctant to call it PTSD, but

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Speaker 1: following the financial crisis, there was this pervasive negativity that

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Speaker 1: lasted years and years and years. And to run around

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Speaker 1: and say, hey, markets are positive here, you need to

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Speaker 1: be more constructive because down fifty is a fantastic reset.

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Speaker 1: That was kind of a lonely voice for a few years.

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Speaker 1: I think that's a big part of why you had

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Speaker 1: the hard metals people doing a lot of stuff. You

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Speaker 1: had the rise of crypto. I mean, think about that crypto.

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Speaker 1: Crypto is where that enthusiasm went everybody who was finance adjacent,

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Speaker 1: tech positive, growth oriented, all of them went into crypto

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Speaker 1: in that window, in that to GFC two pandemic window. Huh.

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Speaker 1: That that makes a whole lot of sense. So there's

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Speaker 1: a lot of other things I want to get to

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Speaker 1: with you, but before we do, there's a quote of

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Speaker 1: yours that I think is a great leaping off point

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Speaker 1: for more discussion. Finance is a problem that has been solved. Yeah,

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Speaker 1: so you know, when we think about finance, particularly when

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Speaker 1: we think about investing, which is what we spend most

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Speaker 1: of our time talking about, right, how to how to

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Speaker 1: take your wealth and turn it into more wealth through

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Speaker 1: all of these tools out there from you know, I,

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Speaker 1: P O S two derivatives. Um, how those pieces fit

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Speaker 1: together is no longer a mystery. I mean that's really

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Speaker 1: the core of it. Um, the academic side of how

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Speaker 1: to build a portfolio. We can argue about the details, right,

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Speaker 1: and certainly we could have a whole conversation about you know, Okay, well,

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Speaker 1: this combination of interest rates and inflation and expected returns

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Speaker 1: on equities is different, and so maybe we need to adjust.

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Speaker 1: But the tools to do that are largely baked Anybody

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Speaker 1: who has the curiosity and the basic intellectual capacity to

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Speaker 1: learn about the markets can become a fairly sophisticated investor. So,

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Speaker 1: if you're an advisor, and I spend most of my

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Speaker 1: time talking to the wealth management institutional business, if you're

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Speaker 1: an advisor, you should not be spending a lot of

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Speaker 1: your time trying to add alpha through understanding investing better

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Speaker 1: than the rest of the market. That is a mug's game, right,

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Speaker 1: So don't try to solve that problem. It's largely solved.

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Speaker 1: You can go get some turnkey asset management program as

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Speaker 1: an advisor, you could get somebody's model portfolio, or you

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Speaker 1: could hire some you know, three c f a s

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Speaker 1: and do it yourself. But it shouldn't be your primary focus.

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Speaker 1: Your primary focus should be solving the much harder problem,

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Speaker 1: which is actually working with human beings. Right. The advice

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Speaker 1: part of being a financial advisor is the hard part.

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Speaker 1: That's the part where you should earn the money. We're

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Speaker 1: kind of upside down and how we compensate and how

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Speaker 1: we think about markets. Right, some advisor that's out there

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Speaker 1: and can say, oh, I've generated one percent alpha for

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Speaker 1: the last three years in my model portfolio, everybody's going

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Speaker 1: to talk about that. But when you talk to that

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Speaker 1: same advisor and they say, yeah, you know, they are

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Speaker 1: these five families I've worked with for ten years, and

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Speaker 1: because I've worked with them, generations of wealth are going

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Speaker 1: to be preserved and these feel philanthropical exercises are going

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Speaker 1: to be put forth like that's the real success story.

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Speaker 1: I don't need to tell you that that's your business, right,

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Speaker 1: that's the real success story. And that's much harder than investing,

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Speaker 1: really really quite quite interesting. You have to explain to

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Speaker 1: me the name of this firm. I've given you grief

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Speaker 1: about this. What is edify? Alright? So well, the shortest

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Speaker 1: answer about how to think about that, if I is

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Speaker 1: where morning start without a ratings business? Right, So like

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Speaker 1: a financial think tank. Yeah, we're in the business of

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Speaker 1: sitting in between asset owners, financial advisors, institutions, retail and

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Speaker 1: asset managers right the black Rocks, State Streets, Pimco's of

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Speaker 1: the world, and helping them understand each other. What I

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Speaker 1: spend most of my time doing is helping advisors understand

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Speaker 1: the thousands of crazy ideas the asset management comes up

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Speaker 1: with every year. And then I work with the asset

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Speaker 1: management community to help them understand the hundreds of thousands

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Speaker 1: of financial advisors and institutions who may or may not

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Speaker 1: be interested in any of those products whatsoever. And so

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Speaker 1: what that entails is a lot of good data understanding

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Speaker 1: what both sides want of each other. It understands. It

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Speaker 1: means having to understand markets, because if you're gonna understand

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Speaker 1: the asset management industry, you need to understand well why

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Speaker 1: you're managed. Future is part of the conversation here today

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Speaker 1: but not six months ago, and it means spending a

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Speaker 1: lot of time talking to individual advisors and investors who

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Speaker 1: are out there trying to do the real work. So

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Speaker 1: that's where vertify sits the company, like the meet and

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Speaker 1: the bones underneath it brands folks know on et F

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Speaker 1: trans et F database. We recently emerged with Advisor Perspectives,

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Speaker 1: which is the largest advisor newsletter in the country. So

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Speaker 1: we've sort of cornered a market on this dialogue between

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Speaker 1: asset managers and financial advisors, and it goes both ways.

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Speaker 1: We also do a lot of polling with financial advisors.

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Speaker 1: We meet them at conferences, we do surveys of them,

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Speaker 1: We track their behavior as they're doing research using our

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Speaker 1: data and analytics tools, and that lets us really get

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Speaker 1: an interesting picture of Hey, what are advisors thinking this week? Well,

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Speaker 1: we can kind of tell you because we know what

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Speaker 1: they're researching. We know you know how they answered pole

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Speaker 1: questions last week, we know how they answered a survey

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Speaker 1: two weeks ago, and then we write about that. We

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Speaker 1: produce fifty odd pieces of content today. So here's the question.

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Speaker 1: Are your clients the advisors or are your clients the

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Speaker 1: institutional asset managers? Or both? Both? Is the real answer?

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Speaker 1: I think the way to think about this is we're

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Speaker 1: a business to business organization in terms of where you know,

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Speaker 1: if you're gonna look at the revenue lines, but with

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Speaker 1: b TWOC responsibilities, right, we take our relationship with the

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Speaker 1: financial advisor very very seriously. In my position, that's really

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Speaker 1: almost exclusively what I focus on, all right, And this

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Speaker 1: leads me to a question that I never in a

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Speaker 1: million years thought I would get to ask on this show.

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Speaker 1: But what the hell is the financial futurist? Your title

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Speaker 1: is a financial futurist? Yes, who came up with that? Who?

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Speaker 1: What are the responsibilities? What does a financial futurist do?

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Speaker 1: Like I expect you to be in one of little

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Speaker 1: storefronts with the red light people to win financial and

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Speaker 1: I hand you a card to the glass Madame Zolof

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Speaker 1: with the turban on in the whole night Year, it's

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Speaker 1: like big thank you here and I think it's actually

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Speaker 1: a dude in the movie, but it is neither here

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Speaker 1: nor there. Um. So look about a year ago. I

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Speaker 1: had a conversation with the senior management of the company

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Speaker 1: as we were putting Verified together, right, and we would

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Speaker 1: you know, one of the things we use as a

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Speaker 1: hook when we talk about the company is we're trying

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Speaker 1: to turn it from an industry to a community. What

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Speaker 1: we mean by that is that we focus on finance

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Speaker 1: a lot on rules, regulations, process operations, none of which

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Speaker 1: matter at all, and we've often just ignore the fact

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Speaker 1: that they're human beings at the end of this equation.

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Speaker 1: Now that's changed because of a lot of what's going

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Speaker 1: in behavioral finance, and I think that's great. I don't

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Speaker 1: think it goes nearly far enough. I think human centered

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Speaker 1: organizations are always going to win, So we really tried

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Speaker 1: to skew the organization towards that. So with that context,

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Speaker 1: I said, here's a bunch of stuff I want to

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Speaker 1: write about, which is the stuff we've been talking about,

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Speaker 1: how the markets work, how people it into them. And

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Speaker 1: I literally just started putting adjectives and nouns on piece

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Speaker 1: of paper, trying to figure out, like, well, how do

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Speaker 1: I describe the work that I think I should be

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Speaker 1: doing and that hopefully people find at least entertaining, if

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Speaker 1: not valuable. Uh and a little from column A little

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Speaker 1: column B. You know, I've spent most of my career

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Speaker 1: writing and thinking about finance. Most of what I've done

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Speaker 1: has been taking an understanding of the status quo, which

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Speaker 1: is very brief because next tomorrow it's gone, and trying

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Speaker 1: to help people understand what that means for next week,

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Speaker 1: in the next year, and the next decade, to position

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Speaker 1: products underneath it, like a t S in two or

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Speaker 1: model portfolios in two thousand, or direct indexing in two right,

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Speaker 1: really trying to focus on that. Now it would be

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Speaker 1: tokenized asset management. It's like, you can see these things

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Speaker 1: if you're paying attention, but it's super easy to get

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Speaker 1: really excited and spend lots of money chasing them. Having

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Speaker 1: some context is important. So you mentioned direct indexing. Let's

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Speaker 1: go there because I always disliked the broad context of

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Speaker 1: direct indexing as how it was done previously. I couldn't

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Speaker 1: stand the fifty pages of stockholdings every month or every quarter.

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Speaker 1: But I give you credit for the person who kind

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Speaker 1: of turned me around on that. I don't want to

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Speaker 1: say it was ten years ago, but it was probably

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Speaker 1: like five years ago, maybe a little longer that you

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Speaker 1: pointed out there are a lot of things you can

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Speaker 1: do with direct indexing in terms of and you were

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Speaker 1: way ahead of the software. You had talked about things

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Speaker 1: before it was available, that you could tilt towards a

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Speaker 1: variety of e s g. Things, Hey show me companies

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Speaker 1: where the board has at least two women on it,

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Speaker 1: or you could tilt towards value where you could tilt

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Speaker 1: towards small cap, or you could use it for tax

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Speaker 1: lost harvesting or philanthropy. And you kind of opened my

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Speaker 1: eyes up. Full disclosure. We work with O'shanna Sees Canvas,

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Speaker 1: which was recently purchased by Franklin Templeton, and we're the

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Speaker 1: largest client to that about a billion of three billions

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Speaker 1: in at But I give you credit because if you

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Speaker 1: hadn't opened my eyes to the advantages of what you

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Speaker 1: can do with that. Um, we might not have stepped

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Speaker 1: as aggressively into it as we did. I was primed

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Speaker 1: two and receptive to see the things that were possible.

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Speaker 1: So full credit to you. Now tell us about what

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Speaker 1: is tokenized financial investments? Well, so you know, if you

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Speaker 1: think about right now, I have a million dollars I

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Speaker 1: want to put the work I wish I have a

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Speaker 1: hundred thousand dollars I want to put to work. I

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Speaker 1: have lots of different ways I can get that number

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Speaker 1: to go up, and ultimately, let's be honest, that's what

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Speaker 1: you care about. As an individual investor, I have a

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Speaker 1: hundred thousand dollars, I would like to have a hundred

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Speaker 1: and ten thousand dollars? How do I get there? And

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Speaker 1: right now we throw it into the stock market, and

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Speaker 1: we effectively use a tokenized system, right, I mean, nobody

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Speaker 1: really carries shares around anymore. You want, you gotta led

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Speaker 1: your entry at seeding company down on Water Street, right like,

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Speaker 1: It's it's all just this fiction that we've created to

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Speaker 1: keep track of notional ownership, and then we built this

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Speaker 1: enormous infrastructure around it. So now we have payment for

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Speaker 1: order flow and seventeen market centers and you know, reagaan

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Speaker 1: MS judging who what has to get broadcast to who.

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Speaker 1: When we made all this up, I think it's really

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Speaker 1: important to remember this is fiction. We just created the

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Speaker 1: system out of whole cloth. You can trace why, and

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Speaker 1: there's lots of reasons, but you could invent another one.

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Speaker 1: Inventing another one is what crypto has done. If you're

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Speaker 1: in Europe right now, for instance, and you open up

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Speaker 1: an account at ft X dot d E, which is

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Speaker 1: you know f t X is European business in Germany,

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Speaker 1: you can trade Tesla, but not as a stock. You

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Speaker 1: can trade what is effectively a fungible token, right, a

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Speaker 1: unit of Tesla. You and I can trade that in

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Speaker 1: the ft X closed ecosystem all day long, with no

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Speaker 1: trading costs, no settlement, no slippage, no nothing. It's a

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Speaker 1: bearer instrument. It's like me handing you a pencil. You

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Speaker 1: just now have the pencil and I don't, and the

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Speaker 1: legal claim is the fact that you've got it and

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Speaker 1: I don't. That's scary for all sorts of reasons, but

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Speaker 1: it's also incredibly powerful because if you imagine that world

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Speaker 1: where instead of it being this closed ecosystem in Germany.

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Speaker 1: It's just sort of how global markets work, all of

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Speaker 1: a sudden, almost any beta, any risk, any ownership stake

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Speaker 1: that you want, as long as you can get two

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Speaker 1: people to agree on what the tokens mean and how

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Speaker 1: they unwind, to unlock some sort of underlying value, we

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Speaker 1: can do all sorts of crazy stuff through the crypto

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Speaker 1: rails that we could never have done before. You want

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Speaker 1: to put together a portfolio, Great, here's a smart contract.

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Speaker 1: It owns these fifteen other tokens that happened to be

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Speaker 1: stocks that can be managed in real time by the

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Speaker 1: contract itself. Creation redemption literally just becomes buying the thing

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Speaker 1: redemption of right. You can create the TF on the blockchain.

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Speaker 1: People have already done this. This is not news. Um.

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Speaker 1: There's a thing called the set product all call. You

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Speaker 1: can create a portfolio with a set of rules, and

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Speaker 1: you can even put in a fee of how much

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Speaker 1: you want to get paid because you came up with

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Speaker 1: a smart contract. And there's hundreds of thousands of these

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Speaker 1: things out there already, so the rails for doing it.

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Speaker 1: The smart to the people talking about ethere and being

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Speaker 1: the world computer, right, there's real truth to that. There's

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Speaker 1: work being done by a computer there to keep track

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Speaker 1: of ledger entries and to move those ledger entries around,

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Speaker 1: which is the entire stock market. It's moving ledger entries around.

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Speaker 1: So we're recording this on the same day that Matt

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Speaker 1: Levine's Business Week Right dropped, like this is the second

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Speaker 1: time in Business Week's history where one writer has written

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Speaker 1: the entire book issue right. It's like fifty words, and

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Speaker 1: it begins by saying, everything in the world these days

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Speaker 1: that reflects ownership is a data database. You remind me

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Speaker 1: of that in what you were talking about UM at FTX,

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Speaker 1: which really raises the question if everything is a database

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Speaker 1: and the blockchain is a public and verifiable, transparent database.

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Speaker 1: The pushback to crypto continues to be, hey, it's been

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Speaker 1: around for fifteen years, how come it isn't doing anything

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Speaker 1: yet substantially? Why is it still so experimental and so small?

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Speaker 1: And I honestly don't know how to answer that. It's regulatory,

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Speaker 1: That's the literally the one word answer is it's regulators. Um.

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Speaker 1: The thing that is keeping the entirety of normal markets

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Speaker 1: from collapsing and being replaced by free crypto software is

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Speaker 1: that their rules that won't let that happen um and

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Speaker 1: their rules that are there for a very good reason, right.

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Speaker 1: I mean, we have a lot of security laws in

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Speaker 1: this country, not because we're obsessed with lawmaking, but because

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Speaker 1: some bad stuff happened and we fixed it by breaking

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Speaker 1: rules about it, right that, you know, going back to

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Speaker 1: the twenties, actually going back to the fourteen hundreds, we

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Speaker 1: have rules about how we engage in these transactions. And

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Speaker 1: the rule of law is a big deal. How that

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Speaker 1: interacts with this sort of bear bond instrument world where

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Speaker 1: literally ownership is the entirety of the law is unknown territory. Right,

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Speaker 1: we have to rewrite how we think about intellectual property,

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Speaker 1: how we think about property rights themselves, how we think

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Speaker 1: about ownership and scrow and security is a huge one.

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Speaker 1: Knowing your customers a big one. Anti money laundring. Those

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Speaker 1: are real issues. So I don't want to I don't

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Speaker 1: want to pretend that those aren't real issues, and they're

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Speaker 1: going to take years to solve. This is not something

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Speaker 1: we're not gonna flip a switch tomorrow. But what I

430
00:22:15,440 --> 00:22:18,159
Speaker 1: fear is going to happen is because the block is

431
00:22:18,240 --> 00:22:21,119
Speaker 1: now regulatory, we're gonna end up in the world's biggest

432
00:22:21,160 --> 00:22:24,679
Speaker 1: regulatory arbitrage race where you're gonna and we've already seen this.

433
00:22:24,720 --> 00:22:26,800
Speaker 1: Their jurisdictions where you can kind of get away with

434
00:22:26,800 --> 00:22:29,400
Speaker 1: doing anything to do in crypto and hey, I'm sorry,

435
00:22:29,400 --> 00:22:31,720
Speaker 1: if you lost a million dollars, call interpoll, maybe they'll

436
00:22:31,720 --> 00:22:34,280
Speaker 1: figure it out for you. Right, And then there's jurisdictions

437
00:22:34,320 --> 00:22:37,760
Speaker 1: like the United States, which are quite locked down. The

438
00:22:38,000 --> 00:22:40,840
Speaker 1: problem is that if I'm right, if the world does

439
00:22:40,920 --> 00:22:43,960
Speaker 1: move more quickly towards this and you start seeing capital

440
00:22:44,040 --> 00:22:47,040
Speaker 1: follow it more than it even has already, you end

441
00:22:47,119 --> 00:22:49,240
Speaker 1: up with this weird haves and have nots world where

442
00:22:49,280 --> 00:22:51,199
Speaker 1: the United States actually ends up on the sort of

443
00:22:51,280 --> 00:22:54,240
Speaker 1: butt end of innovation UM and plays catch up for

444
00:22:54,280 --> 00:22:57,720
Speaker 1: the next twenty years, and another financial center will emerge

445
00:22:58,240 --> 00:23:00,720
Speaker 1: where the I p O s are happening, where private

446
00:23:00,720 --> 00:23:04,560
Speaker 1: equity is is really congealing um, where interesting M and

447
00:23:04,640 --> 00:23:06,800
Speaker 1: A activity is happening, and it ain't gonna be New York.

448
00:23:06,880 --> 00:23:08,560
Speaker 1: I'd like to push against that. I'm kind of a

449
00:23:08,560 --> 00:23:11,440
Speaker 1: fan of the United States. I wouldn't mind us leading here.

450
00:23:11,480 --> 00:23:13,919
Speaker 1: I think you live here rules I I believe I do, yes,

451
00:23:14,000 --> 00:23:15,719
Speaker 1: So you would like to see leadership from the U

452
00:23:15,840 --> 00:23:18,719
Speaker 1: S and it. It just there. There's seems to be

453
00:23:18,760 --> 00:23:22,960
Speaker 1: no interest in a crypto et F. What's that about? Well,

454
00:23:23,040 --> 00:23:26,119
Speaker 1: just Gary ginstlur, is that more institutional? Um? So the

455
00:23:26,119 --> 00:23:28,919
Speaker 1: bitcoin ETF debate right, and gray scale is now suing

456
00:23:28,920 --> 00:23:31,640
Speaker 1: the sec always a great move. Suing your regulators always work.

457
00:23:32,800 --> 00:23:35,960
Speaker 1: They love it. They just say yes after you sue them.

458
00:23:36,359 --> 00:23:38,359
Speaker 1: But here and there there. Yeah, So people have been

459
00:23:38,359 --> 00:23:40,840
Speaker 1: trying to put bitcoin in e T F rapper frankly

460
00:23:40,880 --> 00:23:44,199
Speaker 1: since bitcoin was invented um And the problem is it

461
00:23:44,240 --> 00:23:46,520
Speaker 1: makes you have to define what bitcoin is because there's

462
00:23:46,560 --> 00:23:48,560
Speaker 1: certain things you can put into a mutual fund or

463
00:23:48,600 --> 00:23:50,560
Speaker 1: et F rapper and certain things you can't write. You

464
00:23:50,600 --> 00:23:53,080
Speaker 1: can't put a stake dinner in an e T F rapper.

465
00:23:53,200 --> 00:23:56,400
Speaker 1: Their rules about it, and uh, nobody has been able

466
00:23:56,400 --> 00:23:59,679
Speaker 1: to agree yet whether or not bitcoin belongs in those rappers.

467
00:23:59,680 --> 00:24:02,560
Speaker 1: So we've ended up with these weird edge cases where

468
00:24:02,600 --> 00:24:06,000
Speaker 1: the futures based products get approved, but the species based product,

469
00:24:06,040 --> 00:24:08,760
Speaker 1: I mean, the specie products can't be and it's it's

470
00:24:08,880 --> 00:24:11,639
Speaker 1: an absolute mess. It's the front end of the problem

471
00:24:11,640 --> 00:24:15,320
Speaker 1: we're talking about where crypt where cryptoregulation is actually the

472
00:24:15,400 --> 00:24:17,640
Speaker 1: largest problem in the space. So let me push back

473
00:24:17,680 --> 00:24:22,840
Speaker 1: a bit, because I became dramatically enamored of an idea

474
00:24:22,960 --> 00:24:26,480
Speaker 1: of smart contracts and using them. Let me preface this

475
00:24:26,560 --> 00:24:29,160
Speaker 1: by saying, I'm not a big fan of ticket Master

476
00:24:29,280 --> 00:24:32,680
Speaker 1: and Live Nation, which is now monopoly. There are some

477
00:24:32,800 --> 00:24:36,680
Speaker 1: just ridiculous fees and the whole thing is just an

478
00:24:36,680 --> 00:24:41,000
Speaker 1: egregious affront to free market capitalism. Hold that aside, but

479
00:24:41,119 --> 00:24:47,680
Speaker 1: the idea behind smart tickets that if Taylor Swift says,

480
00:24:48,040 --> 00:24:52,240
Speaker 1: I'm gonna put all of my concert seats on a blockchain,

481
00:24:52,760 --> 00:24:56,000
Speaker 1: and so therefore I'm going to offer the first round

482
00:24:56,040 --> 00:24:58,879
Speaker 1: to my hardcore fans who have been newsletter subscribers for years,

483
00:24:59,200 --> 00:25:01,639
Speaker 1: and the next going to give to my junior fans,

484
00:25:01,680 --> 00:25:04,240
Speaker 1: and then the last one I'll open to the public.

485
00:25:04,440 --> 00:25:06,919
Speaker 1: And by the way, built into this is if you

486
00:25:07,080 --> 00:25:09,360
Speaker 1: decide to sell it at a markup, I get half

487
00:25:09,359 --> 00:25:12,119
Speaker 1: of that markup, but in no cases canna be higher

488
00:25:12,160 --> 00:25:14,600
Speaker 1: than X, and so you stop the you know, you

489
00:25:14,680 --> 00:25:22,280
Speaker 1: basically demolish the entire um. Stub hub seek geek, absolutely egregious.

490
00:25:22,320 --> 00:25:24,280
Speaker 1: How do we use bots? You know, if they were

491
00:25:24,320 --> 00:25:27,119
Speaker 1: just reselling tickets, it's one thing, But they seem to

492
00:25:27,160 --> 00:25:29,840
Speaker 1: have gained the citizens, they buy all the tickets, buy

493
00:25:29,840 --> 00:25:32,720
Speaker 1: the tickets first, and you know, there's a reason why

494
00:25:32,880 --> 00:25:36,920
Speaker 1: artists offer their tickets at affordable prices to their fans,

495
00:25:37,160 --> 00:25:42,199
Speaker 1: and these um rentiers in the middle are abusive. So

496
00:25:42,240 --> 00:25:45,320
Speaker 1: all this comes back to, if the technology exists for that,

497
00:25:45,560 --> 00:25:48,479
Speaker 1: why haven't we seen a major artist who was it?

498
00:25:48,560 --> 00:25:53,879
Speaker 1: Was it Pearl jam tried to buy Nobody seems to

499
00:25:53,880 --> 00:25:55,239
Speaker 1: be able to come up with a way to do this.

500
00:25:55,480 --> 00:25:58,280
Speaker 1: So the reason is because you know, when we look

501
00:25:58,320 --> 00:26:01,919
Speaker 1: at how the corporate economy were works their investments that

502
00:26:01,960 --> 00:26:03,840
Speaker 1: you have to make like the ticketmaster wins a great

503
00:26:03,840 --> 00:26:06,600
Speaker 1: example because the technology to do that is trivial. We

504
00:26:06,600 --> 00:26:08,320
Speaker 1: can stand them up on three of the computers here

505
00:26:08,359 --> 00:26:11,080
Speaker 1: in this control room right now. That's the easy part.

506
00:26:11,320 --> 00:26:14,560
Speaker 1: The hard part is it's Madison Square Garden Friday night

507
00:26:14,640 --> 00:26:17,720
Speaker 1: at seven o'clock and you have twenty five thousand people

508
00:26:17,760 --> 00:26:19,639
Speaker 1: you have to get through the gate in the next

509
00:26:19,640 --> 00:26:22,040
Speaker 1: hour to get to the Taylor Swift concert that's about

510
00:26:22,040 --> 00:26:26,399
Speaker 1: to go live. That infrastructure having forty five guys standing

511
00:26:26,440 --> 00:26:29,119
Speaker 1: there with the scanners going to the network confirming your

512
00:26:29,119 --> 00:26:31,159
Speaker 1: ownership that this is the tip it has already been

513
00:26:31,200 --> 00:26:34,200
Speaker 1: used once, it hasn't been used twice. That and used

514
00:26:34,240 --> 00:26:36,679
Speaker 1: that right now, every time I saw Hades Town and

515
00:26:36,720 --> 00:26:39,399
Speaker 1: they don't even scan the ticket, you put your phone

516
00:26:39,440 --> 00:26:42,760
Speaker 1: on it just it's not you're not even looking at that.

517
00:26:42,960 --> 00:26:45,119
Speaker 1: If you are, find all of that is a whole

518
00:26:45,119 --> 00:26:49,720
Speaker 1: bunch of trust. Infrastructure that says the digital signature coming

519
00:26:49,720 --> 00:26:53,160
Speaker 1: off Barry Ridholt's wallet is the thing that says they

520
00:26:53,160 --> 00:26:56,480
Speaker 1: can go see Haydes Town. Right. That infrastructure is actually

521
00:26:56,520 --> 00:26:59,760
Speaker 1: the hard part because implied in that is a whole

522
00:26:59,760 --> 00:27:02,760
Speaker 1: lot rule of loss stuff like wait a minute, Barry

523
00:27:02,800 --> 00:27:04,439
Speaker 1: and I show up at the same time with the

524
00:27:04,480 --> 00:27:06,919
Speaker 1: same ticket, how do we determine which one of us

525
00:27:07,000 --> 00:27:08,399
Speaker 1: is the one that actually got to go in? How

526
00:27:08,440 --> 00:27:10,440
Speaker 1: do we determine which one of us owns it? What's

527
00:27:10,480 --> 00:27:13,200
Speaker 1: the recourse if you stole it from me? In other words,

528
00:27:13,200 --> 00:27:15,840
Speaker 1: if someone took a scan of that QR. That's the

529
00:27:15,840 --> 00:27:19,880
Speaker 1: problem with enforcement and and the last mile of all

530
00:27:19,880 --> 00:27:22,040
Speaker 1: of these things. Right, This is the part that I

531
00:27:22,040 --> 00:27:24,960
Speaker 1: always I sort of compare to blockchain solve that I've

532
00:27:25,000 --> 00:27:27,959
Speaker 1: been told over and over again. Oh, bitcoin fixes bitcoin

533
00:27:28,000 --> 00:27:31,160
Speaker 1: solves everything, Except it's not molecular, right, It's still digital.

534
00:27:31,200 --> 00:27:33,200
Speaker 1: At the end of the day, most of the things

535
00:27:33,200 --> 00:27:35,680
Speaker 1: we actually give a you know what about our molecular

536
00:27:36,040 --> 00:27:38,760
Speaker 1: We want the coffee cup, we want to go to

537
00:27:38,800 --> 00:27:42,240
Speaker 1: the space to see the event where sound waves propagate

538
00:27:42,280 --> 00:27:45,000
Speaker 1: through the air from another human being on stage. At

539
00:27:45,000 --> 00:27:46,800
Speaker 1: the end of the day, you've got to have that

540
00:27:46,840 --> 00:27:51,119
Speaker 1: interface between the virtual and the real. Otherwise none of

541
00:27:51,119 --> 00:27:54,199
Speaker 1: this matters at all. And it's precisely that boundary that

542
00:27:54,320 --> 00:27:57,359
Speaker 1: is the problem right now. So let's talk a little

543
00:27:57,400 --> 00:28:01,280
Speaker 1: bit about a conference. I have participated in the t

544
00:28:01,400 --> 00:28:05,320
Speaker 1: F Exchange over the years. Vitified just purchased this from

545
00:28:05,359 --> 00:28:09,760
Speaker 1: Advisor Circles. I'm an investor in Advisor Circle, so I

546
00:28:09,760 --> 00:28:12,080
Speaker 1: don't know any of all that, right, So full disclosure.

547
00:28:12,440 --> 00:28:14,800
Speaker 1: We're talking about something that I kind of have an

548
00:28:14,800 --> 00:28:16,600
Speaker 1: interest in, or I used to have an interest in,

549
00:28:17,080 --> 00:28:20,280
Speaker 1: but I'm still a participant in the event. Well, we'll

550
00:28:20,320 --> 00:28:22,879
Speaker 1: see whether we get you an that's right, Listen. I

551
00:28:23,440 --> 00:28:27,080
Speaker 1: always feel like more disclosure is better than less, So

552
00:28:27,200 --> 00:28:29,080
Speaker 1: I'll let the lawyers sort that part, the part I

553
00:28:29,119 --> 00:28:31,320
Speaker 1: pay attention to with the content. So let's talk a

554
00:28:31,320 --> 00:28:34,640
Speaker 1: little bit about e t F Exchange. This has always

555
00:28:34,680 --> 00:28:38,440
Speaker 1: been just a massive event you mentioned earlier in the

556
00:28:38,680 --> 00:28:43,080
Speaker 1: heyday of financial conferences. This I think was one of

557
00:28:43,120 --> 00:28:45,480
Speaker 1: the biggest events I went to each year. Yeah, we

558
00:28:45,560 --> 00:28:47,760
Speaker 1: probably need to point out that like this is in

559
00:28:47,840 --> 00:28:50,600
Speaker 1: some ways the spiritual successor to the old inside et

560
00:28:50,840 --> 00:28:53,080
Speaker 1: S event. That event is still going on, and I

561
00:28:53,080 --> 00:28:55,800
Speaker 1: don't want to pretend that it doesn't exist. It is

562
00:28:55,800 --> 00:28:58,480
Speaker 1: now owned by a big conference company named Informa, and

563
00:28:58,520 --> 00:29:01,080
Speaker 1: they still put on those events. Wealth Stack was an

564
00:29:01,120 --> 00:29:02,840
Speaker 1: event that you all used to do with them. That's

565
00:29:02,840 --> 00:29:06,080
Speaker 1: now part of that event. Again more disclosures. So Informa

566
00:29:06,440 --> 00:29:10,440
Speaker 1: ran uh wealth Stack. We were partners with them for

567
00:29:10,560 --> 00:29:13,280
Speaker 1: Wealth Stack, which ran one year and we were ready

568
00:29:13,320 --> 00:29:16,040
Speaker 1: to do the next one when the pandemic hit. That's

569
00:29:16,080 --> 00:29:18,600
Speaker 1: the only reason that everything got juggled. Everything got juggled,

570
00:29:18,640 --> 00:29:22,040
Speaker 1: and then after everything reopened, their staff had left. It

571
00:29:22,200 --> 00:29:25,600
Speaker 1: was a whole craziness. The whole world sort of reset

572
00:29:25,880 --> 00:29:30,280
Speaker 1: and so um we worked with Advisor Circle on future Proof,

573
00:29:30,400 --> 00:29:33,080
Speaker 1: not with Informer because they were kind of they're in

574
00:29:33,120 --> 00:29:36,360
Speaker 1: Europe and they were a little skittish when the US

575
00:29:36,440 --> 00:29:39,320
Speaker 1: was reopening. But hold all that nonsense aside. Tell us

576
00:29:39,320 --> 00:29:43,320
Speaker 1: a little bit about why have UH an E t

577
00:29:43,480 --> 00:29:45,880
Speaker 1: F conference. You know is an E t F to

578
00:29:45,960 --> 00:29:48,480
Speaker 1: settled area. Tell us a little bit about this event. Well, no,

579
00:29:48,720 --> 00:29:50,720
Speaker 1: because E t F are where everything interesting in the

580
00:29:50,720 --> 00:29:52,880
Speaker 1: world is still happening. I think that's part of the

581
00:29:53,000 --> 00:29:54,480
Speaker 1: part of the reason I'm still in the E t

582
00:29:54,640 --> 00:29:56,960
Speaker 1: F business, although I don't have it in my title anymore,

583
00:29:57,480 --> 00:30:00,720
Speaker 1: is that regardless of what you're trying to get done

584
00:30:00,800 --> 00:30:03,120
Speaker 1: with that hundred thousand dollars you're trying to make go up,

585
00:30:03,480 --> 00:30:06,200
Speaker 1: ETFs are probably the right answer under the hood in

586
00:30:06,360 --> 00:30:08,960
Speaker 1: terms of the structure. So whether you're trying to get

587
00:30:09,120 --> 00:30:12,880
Speaker 1: managed futures from an active manager or you know, two

588
00:30:12,960 --> 00:30:17,000
Speaker 1: month treasuries T bills, like the whole spectrum is now

589
00:30:17,040 --> 00:30:19,920
Speaker 1: available in the close to three thousand et F s

590
00:30:20,000 --> 00:30:21,800
Speaker 1: we have trading here in the US. It's like the

591
00:30:21,880 --> 00:30:23,800
Speaker 1: mutual pun business back in the eighties, and so we

592
00:30:23,880 --> 00:30:27,160
Speaker 1: have more ETFs. There are stocks just about getting close

593
00:30:27,320 --> 00:30:32,840
Speaker 1: getting close well in in the world. It's like thirty

594
00:30:32,920 --> 00:30:35,280
Speaker 1: thousand actual tickers out there in the world. But the

595
00:30:35,360 --> 00:30:37,520
Speaker 1: point is they're more E t F than you could

596
00:30:37,560 --> 00:30:40,560
Speaker 1: ever possibly use in one portfolio. Most people probably only

597
00:30:40,640 --> 00:30:43,520
Speaker 1: need a handful to accomplish whatever objectives they're going to do.

598
00:30:44,120 --> 00:30:46,320
Speaker 1: But the reason why we have an event around it

599
00:30:46,480 --> 00:30:50,280
Speaker 1: is because so much of the interesting innovation and finance

600
00:30:50,400 --> 00:30:53,720
Speaker 1: happens through that structure. Because the et F structure lends

601
00:30:53,760 --> 00:30:56,760
Speaker 1: itself naturally to this sort of movement of risk from

602
00:30:56,840 --> 00:31:00,520
Speaker 1: bucket to bucket in a very retail friendly package. It's

603
00:31:00,520 --> 00:31:02,120
Speaker 1: sort of like the best thing we've come up with.

604
00:31:02,160 --> 00:31:04,120
Speaker 1: It's like people ask, like, well, why are trains a

605
00:31:04,200 --> 00:31:07,200
Speaker 1: certain width? Well, because history just sort of got us

606
00:31:07,280 --> 00:31:10,560
Speaker 1: to this configuration where now everything runs that way and

607
00:31:10,600 --> 00:31:13,760
Speaker 1: nobody's going to invent a new gage of train track. Uh.

608
00:31:13,880 --> 00:31:15,920
Speaker 1: This of the rails that we have at the moment

609
00:31:16,080 --> 00:31:18,200
Speaker 1: and probably for the rest of my career, the e

610
00:31:18,320 --> 00:31:20,920
Speaker 1: t F still looks like the most efficient set of

611
00:31:21,040 --> 00:31:23,520
Speaker 1: rails anybody's figured out how to put down. So why

612
00:31:23,600 --> 00:31:26,680
Speaker 1: have a conference about it? Well, Uh, largely because we

613
00:31:26,760 --> 00:31:31,080
Speaker 1: want to get those interesting conversations going. My perspective on exchanges,

614
00:31:31,560 --> 00:31:34,960
Speaker 1: I'm there to have interesting conversations, and when I'm talking

615
00:31:35,000 --> 00:31:37,040
Speaker 1: to a bunch of financial advisors and a bunch of

616
00:31:37,120 --> 00:31:40,480
Speaker 1: finance investment management types, that tends to be the most

617
00:31:40,520 --> 00:31:43,520
Speaker 1: interesting conversation because you get the real human use in

618
00:31:43,600 --> 00:31:46,360
Speaker 1: the room and you get the real human smarts in

619
00:31:46,440 --> 00:31:49,600
Speaker 1: the room, and that's when the magic happens. So, whether

620
00:31:49,640 --> 00:31:51,600
Speaker 1: it's getting a bunch of folks on stage to have

621
00:31:51,680 --> 00:31:55,480
Speaker 1: a really interesting conversation about you know, geopolitical concerns in Ukraine,

622
00:31:56,240 --> 00:31:58,920
Speaker 1: or whether it's just being able to have a small

623
00:31:59,240 --> 00:32:02,840
Speaker 1: breakfast with four five advisors and some academic where we

624
00:32:02,920 --> 00:32:06,320
Speaker 1: talk about behavioral finance, those are the interesting conversations. So

625
00:32:06,440 --> 00:32:09,600
Speaker 1: exchange is really all about creating that sense of community

626
00:32:10,120 --> 00:32:13,360
Speaker 1: between groups of folks, and some of that content that's

627
00:32:13,360 --> 00:32:14,880
Speaker 1: on the stage and a lot of it isn't we

628
00:32:14,960 --> 00:32:16,720
Speaker 1: learned that. I think at future Proof this is a

629
00:32:16,800 --> 00:32:20,560
Speaker 1: community event. This is about people getting together and exchanging ideas,

630
00:32:20,880 --> 00:32:23,440
Speaker 1: and I think that's a lesson we've learned from the pandemic,

631
00:32:23,560 --> 00:32:25,480
Speaker 1: not just from that conference. People want to get together

632
00:32:25,560 --> 00:32:29,480
Speaker 1: and talk. You know. It's funny because financial conferences and

633
00:32:29,560 --> 00:32:33,360
Speaker 1: maybe conferences in general, everything is based on an academic model,

634
00:32:33,920 --> 00:32:37,120
Speaker 1: and people took the big lecture halls out as their

635
00:32:37,360 --> 00:32:39,720
Speaker 1: frame of reference. Hey, a bunch of people on stage

636
00:32:39,760 --> 00:32:41,840
Speaker 1: talking to a bunch of people in the audience taking notes.

637
00:32:42,360 --> 00:32:45,800
Speaker 1: But the most interesting part of college wasn't necessarily the

638
00:32:45,840 --> 00:32:48,480
Speaker 1: big lecture halls. It was the class let's out and

639
00:32:48,520 --> 00:32:50,600
Speaker 1: you start to talk to people about, hey, could you

640
00:32:50,680 --> 00:32:52,440
Speaker 1: explain this. I don't understand what's going on? And then

641
00:32:52,480 --> 00:32:57,720
Speaker 1: the subsequent conversations that's the really exciting driver, not you know,

642
00:32:57,880 --> 00:33:00,360
Speaker 1: the panel of people telling you here's why interest rate

643
00:33:00,440 --> 00:33:02,640
Speaker 1: is going to go up or down and what's wrong

644
00:33:02,680 --> 00:33:06,200
Speaker 1: with inflation today. So based on that, let's dive a

645
00:33:06,280 --> 00:33:10,120
Speaker 1: little bit into some of the innovations in finance and

646
00:33:10,160 --> 00:33:14,640
Speaker 1: ETFs you reference. Let's start with active ETFs. Uh. They

647
00:33:14,680 --> 00:33:17,760
Speaker 1: were looked at kind of skeptically a few years ago. Hey,

648
00:33:17,880 --> 00:33:20,680
Speaker 1: e t f s are all that low cost passive indexing.

649
00:33:21,080 --> 00:33:23,440
Speaker 1: Why do I want an active ETF? Well, the short

650
00:33:23,480 --> 00:33:25,320
Speaker 1: answer is because if you're an active manager, it's the

651
00:33:25,320 --> 00:33:27,560
Speaker 1: only way you're gonna get any customers. Right. So right,

652
00:33:27,720 --> 00:33:29,160
Speaker 1: there's a bit of a there's just a bit of

653
00:33:29,240 --> 00:33:31,680
Speaker 1: reality in that. I mean, at this point we're still

654
00:33:31,960 --> 00:33:34,880
Speaker 1: something like ten twelve percent of the flows the assets

655
00:33:34,920 --> 00:33:37,560
Speaker 1: are are inactive. It's still a fairly small number. How

656
00:33:37,640 --> 00:33:40,040
Speaker 1: much of that is just arc and Cathy Woods versus

657
00:33:40,080 --> 00:33:42,520
Speaker 1: everybody a decent chunk. But remember a lot of the

658
00:33:42,560 --> 00:33:45,200
Speaker 1: fixed income complex is actually managed right, most of the

659
00:33:45,240 --> 00:33:47,640
Speaker 1: product I want to say most of the vast majority

660
00:33:47,680 --> 00:33:49,440
Speaker 1: of this. Well, I mean there's like t LT you

661
00:33:49,520 --> 00:33:52,520
Speaker 1: at the big treasury funds l q D and h

662
00:33:52,640 --> 00:33:54,920
Speaker 1: y G, and those are sort of big betas and

663
00:33:55,040 --> 00:33:57,680
Speaker 1: fixed income, and that's where the biggest funds are. But

664
00:33:57,800 --> 00:33:59,560
Speaker 1: if you get below that tier, you know all the

665
00:33:59,600 --> 00:34:01,840
Speaker 1: Pimco of funds, anything sort of interesting being done at

666
00:34:01,880 --> 00:34:03,800
Speaker 1: the short end, even like a lot of the short

667
00:34:03,880 --> 00:34:07,160
Speaker 1: treasury stuff is technically actively managed because it moves so

668
00:34:07,240 --> 00:34:09,160
Speaker 1: fast you couldn't possibly want to try to trade down

669
00:34:09,160 --> 00:34:13,120
Speaker 1: an index. And the academics have demonstrated that active actually

670
00:34:13,200 --> 00:34:17,279
Speaker 1: creates worthwhile returns in bonds where it's certainly at least

671
00:34:17,320 --> 00:34:19,759
Speaker 1: the evidence is a little stronger, a lot stronger than

672
00:34:19,920 --> 00:34:22,480
Speaker 1: versus equities, where there's really no argument left. Yeah, So

673
00:34:22,640 --> 00:34:24,720
Speaker 1: this is one of those things where my personal belief

674
00:34:24,800 --> 00:34:27,319
Speaker 1: system tends to I have to check that at the door.

675
00:34:27,680 --> 00:34:31,120
Speaker 1: The reality of the market right now is active management

676
00:34:31,280 --> 00:34:33,600
Speaker 1: is a thing in the E t F space. While

677
00:34:33,640 --> 00:34:35,879
Speaker 1: it is still a fairly small part of flows, call

678
00:34:35,920 --> 00:34:38,799
Speaker 1: it between ten and and a given period um, it's

679
00:34:38,800 --> 00:34:41,160
Speaker 1: an enormous part of revenue because most of these funds

680
00:34:41,320 --> 00:34:45,319
Speaker 1: charge more not judging five judge, so you know, they

681
00:34:45,360 --> 00:34:47,239
Speaker 1: may only be ten percent of the assets, but they're

682
00:34:47,280 --> 00:34:51,160
Speaker 1: more like of the revenue. And active managers are a

683
00:34:51,239 --> 00:34:53,279
Speaker 1: big deal in the E t F space now. And

684
00:34:53,640 --> 00:34:55,439
Speaker 1: I would also point out a lot of the ones

685
00:34:55,480 --> 00:34:58,840
Speaker 1: that have been successful um and are continuing to gain assets,

686
00:34:59,640 --> 00:35:01,839
Speaker 1: whether not they're putting up alpha or not. I think

687
00:35:01,840 --> 00:35:04,359
Speaker 1: it's always a tricky question. It seems like an easy one,

688
00:35:04,440 --> 00:35:06,719
Speaker 1: but there's a lot of miss benchmarking that goes on this. Yeah,

689
00:35:06,760 --> 00:35:09,360
Speaker 1: that's a great cheat, like we're gonna make a benchmark

690
00:35:09,480 --> 00:35:12,080
Speaker 1: much easier, and and and fixed income. This is really

691
00:35:12,120 --> 00:35:14,200
Speaker 1: an issue because a lot of people just default to

692
00:35:14,280 --> 00:35:19,920
Speaker 1: benching against the agg when they have no And you know,

693
00:35:20,040 --> 00:35:23,000
Speaker 1: most people who are an active bond manager, like they're

694
00:35:23,040 --> 00:35:26,000
Speaker 1: focused on credit, right, They're focused on a niche they've got,

695
00:35:26,200 --> 00:35:29,080
Speaker 1: I am working on securitized stuff whatever. They're not trying

696
00:35:29,120 --> 00:35:32,759
Speaker 1: to eek out fifty basics right right, They're not even

697
00:35:32,880 --> 00:35:35,840
Speaker 1: owning the long Treasury attorney of that stuff. So the

698
00:35:35,880 --> 00:35:38,560
Speaker 1: Apple's Apples thing is a real issue. Putting that to

699
00:35:38,680 --> 00:35:41,440
Speaker 1: the side. If you look at what Cathy Wood has

700
00:35:41,480 --> 00:35:44,719
Speaker 1: done at the ARC team, right, they're they're interesting. Their

701
00:35:44,760 --> 00:35:47,640
Speaker 1: performance has been awful, and their flows have been solid,

702
00:35:47,800 --> 00:35:50,920
Speaker 1: meaning money is not leaving. Let me let me annotate

703
00:35:51,040 --> 00:35:57,840
Speaker 1: that slightly, since their performance has been so I'm leading

704
00:35:57,920 --> 00:36:01,840
Speaker 1: up to do went No one even came in second

705
00:36:02,000 --> 00:36:07,600
Speaker 1: they I think she was plus one six when the

706
00:36:07,719 --> 00:36:10,800
Speaker 1: market from the lows. From the lows, the market was

707
00:36:10,880 --> 00:36:13,440
Speaker 1: up six and I think it was up eighteen percent

708
00:36:13,520 --> 00:36:16,480
Speaker 1: for the year. That just astonishing pattern of sort of

709
00:36:16,640 --> 00:36:20,040
Speaker 1: high innovation growth managers. We've seen this several times, not

710
00:36:20,200 --> 00:36:22,239
Speaker 1: just in the dot com era, though we played plenty

711
00:36:22,280 --> 00:36:25,680
Speaker 1: of it. Then look you look over a long cycle

712
00:36:25,719 --> 00:36:27,040
Speaker 1: and it's like, well they kind of did with the

713
00:36:27,120 --> 00:36:31,680
Speaker 1: spire over ten years, but eve and with crazy up

714
00:36:31,719 --> 00:36:33,600
Speaker 1: and down lone. Right, But if you look at that,

715
00:36:34,120 --> 00:36:36,319
Speaker 1: they've managed to hang onto investors. You look at things

716
00:36:36,440 --> 00:36:41,160
Speaker 1: like um Andrew Beers DBMF, which is the pulling a

717
00:36:41,280 --> 00:36:44,600
Speaker 1: billion dollars this year. Really, yeah, good for him. It's

718
00:36:44,640 --> 00:36:47,480
Speaker 1: up three. I mean, that's why. But I also think

719
00:36:47,520 --> 00:36:49,759
Speaker 1: it's a solid strategy. You know, it's effectively a quant

720
00:36:49,800 --> 00:36:52,480
Speaker 1: model that's duplicating that sort of ct A style of

721
00:36:52,560 --> 00:36:55,840
Speaker 1: management has done very well. There are a lot of

722
00:36:55,880 --> 00:36:58,040
Speaker 1: little pockets like that where you can say, oh, here's

723
00:36:58,040 --> 00:37:01,759
Speaker 1: an active manager who's providing interesting beta that other people

724
00:37:01,800 --> 00:37:04,320
Speaker 1: aren't really getting access to, and they're doing it in

725
00:37:04,400 --> 00:37:07,120
Speaker 1: a in a you know, more useful and interesting way

726
00:37:07,200 --> 00:37:09,759
Speaker 1: that there's also some story behind. You understand why you're

727
00:37:09,760 --> 00:37:12,080
Speaker 1: doing it. Now, you understand what it means when rates

728
00:37:12,120 --> 00:37:15,000
Speaker 1: go up another seventy bps um. That I think has

729
00:37:15,040 --> 00:37:18,319
Speaker 1: become pretty important. So as much as I'm personally still

730
00:37:18,560 --> 00:37:21,400
Speaker 1: a pretty strong skeptic of active management, I mean, I

731
00:37:21,520 --> 00:37:24,480
Speaker 1: understand the math and the odds are not in your

732
00:37:24,520 --> 00:37:26,320
Speaker 1: favor as an active manager, but you have to be

733
00:37:26,440 --> 00:37:30,600
Speaker 1: doing something both incredibly disciplined and incredibly well to have

734
00:37:30,719 --> 00:37:33,399
Speaker 1: any success there. I think we're now in a market

735
00:37:33,480 --> 00:37:35,480
Speaker 1: where we'll be able to pick those people out now.

736
00:37:35,520 --> 00:37:38,640
Speaker 1: Whether they're coin flippers who just happened to get heads

737
00:37:38,680 --> 00:37:41,520
Speaker 1: twenty times in a row or not, history will judge.

738
00:37:42,040 --> 00:37:45,279
Speaker 1: But there's demand from advisors, there's demand from institutions, there's

739
00:37:45,280 --> 00:37:48,160
Speaker 1: definitely demand from retail, and there's plenty of supply and

740
00:37:48,200 --> 00:37:51,160
Speaker 1: the asset management business side. So I remember, first of all,

741
00:37:51,239 --> 00:37:53,279
Speaker 1: Andrew Beau was a previous guest. I find him to

742
00:37:53,320 --> 00:37:57,680
Speaker 1: be really fascinating guy. If I recall correctly, he started

743
00:37:57,760 --> 00:38:00,920
Speaker 1: doing hedge fund replications in an at I don't know

744
00:38:01,000 --> 00:38:03,719
Speaker 1: how well those have done, but it wouldn't surprise me

745
00:38:04,280 --> 00:38:08,279
Speaker 1: that managed futures replication given how much commodities have run

746
00:38:08,400 --> 00:38:12,120
Speaker 1: up and run down. If you're doing a trend following model,

747
00:38:12,200 --> 00:38:14,480
Speaker 1: which a lot of the managed futures do, and I'm

748
00:38:14,480 --> 00:38:17,160
Speaker 1: assuming he found a way to create that could be

749
00:38:17,239 --> 00:38:19,719
Speaker 1: a giant winner. Yeah, and it has been right So

750
00:38:19,880 --> 00:38:21,359
Speaker 1: that is, you know, a little bit of a lightning

751
00:38:21,400 --> 00:38:22,920
Speaker 1: in a bottle of right place, right time. Maybe that

752
00:38:23,000 --> 00:38:24,719
Speaker 1: fund was around for year or two before people paid

753
00:38:24,719 --> 00:38:26,960
Speaker 1: any attention. How did the hedge fund replication work out?

754
00:38:27,040 --> 00:38:28,960
Speaker 1: So most of the hedge fund replication products have not

755
00:38:29,080 --> 00:38:31,440
Speaker 1: done particularly well. Index i Q launched a bunch of

756
00:38:31,480 --> 00:38:34,840
Speaker 1: those about a decade. The price you to execute, I meant,

757
00:38:35,000 --> 00:38:37,640
Speaker 1: but the price you to run. But they're also there's

758
00:38:37,680 --> 00:38:41,040
Speaker 1: there's also a mismatch. And anytime somebody says I'm going

759
00:38:41,080 --> 00:38:45,160
Speaker 1: to replicate this unobtainable pattern of returns with this obtainable

760
00:38:45,200 --> 00:38:48,520
Speaker 1: pattern of returns, because I can watch in the mirror

761
00:38:48,600 --> 00:38:50,680
Speaker 1: and see what they're doing, and then replicated over here,

762
00:38:51,239 --> 00:38:53,880
Speaker 1: I read all those academic papers. I understand where the

763
00:38:53,920 --> 00:38:56,799
Speaker 1: math comes from. I'm very skeptical about them. Not because

764
00:38:56,840 --> 00:38:58,600
Speaker 1: I think people get the math wrong, because I think

765
00:38:58,640 --> 00:39:01,279
Speaker 1: the world changes the leg the lag is deadly. You

766
00:39:01,360 --> 00:39:04,160
Speaker 1: and I have talked about the world changes constantly. Right.

767
00:39:04,280 --> 00:39:06,520
Speaker 1: In fact, you and I had a conversation that when

768
00:39:06,600 --> 00:39:09,880
Speaker 1: you perceive the world, you're already perceiving it on a

769
00:39:10,080 --> 00:39:12,759
Speaker 1: leg because of how long it takes for life. Yeah,

770
00:39:12,760 --> 00:39:15,120
Speaker 1: I mean, this is there the foundation of how I view, like,

771
00:39:15,200 --> 00:39:18,839
Speaker 1: my financial futurist model starts with the premise that our

772
00:39:18,960 --> 00:39:21,480
Speaker 1: understanding of how humans work is wrong to start with, Like,

773
00:39:21,640 --> 00:39:24,680
Speaker 1: so just the nature of human existence we've all got wrong.

774
00:39:25,239 --> 00:39:28,440
Speaker 1: So therefore any certainty you apply to anything else in

775
00:39:28,480 --> 00:39:30,560
Speaker 1: the universe you've got to put with a huge grandness.

776
00:39:30,560 --> 00:39:32,080
Speaker 1: We're gonna talk more about that in the bit. I

777
00:39:32,160 --> 00:39:34,680
Speaker 1: want to stick with each other. We no, no, I

778
00:39:34,760 --> 00:39:37,600
Speaker 1: brought it up, but because it's so fascinating, So we

779
00:39:37,680 --> 00:39:42,839
Speaker 1: haven't talked about thematic ets, biblical partisan. Our friend Perth

780
00:39:42,960 --> 00:39:47,600
Speaker 1: Tolls Economic and then there's another one that does emerging markets.

781
00:39:47,760 --> 00:39:51,319
Speaker 1: Dm c Y does emerging and developed market. I think

782
00:39:51,360 --> 00:39:52,880
Speaker 1: that's the one, right, and that's got sort of a

783
00:39:52,960 --> 00:39:55,920
Speaker 1: broader methodology. Per tolls, f R d M is just

784
00:39:56,080 --> 00:39:59,480
Speaker 1: emerging markets ex. China, you know which is It's not

785
00:39:59,560 --> 00:40:03,719
Speaker 1: just ex it's ex dictating you know which has worked out?

786
00:40:03,760 --> 00:40:07,080
Speaker 1: Really another one phenomen another example of an idea that

787
00:40:07,360 --> 00:40:09,839
Speaker 1: right time, right place. This year has been another big

788
00:40:10,080 --> 00:40:12,040
Speaker 1: But we we both know she spent you know, five

789
00:40:12,120 --> 00:40:14,160
Speaker 1: to ten years in the trenches getting to the point

790
00:40:14,200 --> 00:40:16,600
Speaker 1: for the overnight success. That's how it always takes ten

791
00:40:16,680 --> 00:40:20,120
Speaker 1: years to be overnight. So the thematic stuff definitely interesting.

792
00:40:20,239 --> 00:40:24,080
Speaker 1: I think mostly driven by advisors need to have stories

793
00:40:24,120 --> 00:40:27,759
Speaker 1: to talk to their clients about. That's not preservative. Well

794
00:40:27,960 --> 00:40:31,400
Speaker 1: that's that's some of the stories though, and and my

795
00:40:31,560 --> 00:40:34,680
Speaker 1: pushback on the thematics are all right, I can understand

796
00:40:34,719 --> 00:40:38,120
Speaker 1: the concept behind what hims. If we invest in emerging

797
00:40:38,200 --> 00:40:42,680
Speaker 1: markets but leave out the worst players like Russia and

798
00:40:42,840 --> 00:40:46,000
Speaker 1: China that has worked out well this year, the ones

799
00:40:46,080 --> 00:40:50,200
Speaker 1: where I only want to invest in republican or democratic companies,

800
00:40:50,680 --> 00:40:53,719
Speaker 1: or I want to do these sort of biblical based investing.

801
00:40:54,200 --> 00:40:57,000
Speaker 1: They seem to be more emotional, and history has told

802
00:40:57,080 --> 00:41:00,520
Speaker 1: us emotions or the enemy of good investing. Yeah, I'm

803
00:41:00,600 --> 00:41:03,000
Speaker 1: not a super fan of most of that stuff. I

804
00:41:03,400 --> 00:41:07,319
Speaker 1: do think that there's a place for thinking about stewardship,

805
00:41:07,680 --> 00:41:09,800
Speaker 1: and again, part of my longer thesis on how the

806
00:41:09,840 --> 00:41:13,560
Speaker 1: world works um corporate ownership. Who controls what companies do

807
00:41:14,360 --> 00:41:17,080
Speaker 1: is probably a lot more important than who's elected in office.

808
00:41:17,160 --> 00:41:20,359
Speaker 1: We'll talk a bit about in the next But that's

809
00:41:20,560 --> 00:41:23,680
Speaker 1: all that is, all that woke anti woke investing stuff

810
00:41:24,040 --> 00:41:27,240
Speaker 1: that's applying these sort of emotional labels about the world

811
00:41:27,760 --> 00:41:30,040
Speaker 1: to our investments. And I'm with you, I don't think

812
00:41:30,120 --> 00:41:32,000
Speaker 1: that that makes a ton of sense. I think there's

813
00:41:32,040 --> 00:41:34,920
Speaker 1: some threads there around voting that makes some sense, But

814
00:41:35,080 --> 00:41:37,160
Speaker 1: most of that stuff I don't like how it's sold

815
00:41:37,360 --> 00:41:39,719
Speaker 1: more than I don't like how it's built. Where I

816
00:41:39,800 --> 00:41:41,719
Speaker 1: think things get a little tricky is when it's like

817
00:41:42,200 --> 00:41:46,360
Speaker 1: what I call headline funds, you know, electric cars, future food,

818
00:41:46,840 --> 00:41:51,719
Speaker 1: work from home, valid approaches, but they're really so targeted

819
00:41:51,719 --> 00:41:53,560
Speaker 1: towards well, is there going to be a big headline

820
00:41:53,600 --> 00:41:57,040
Speaker 1: like work from home pandemic go right. They're really just

821
00:41:57,320 --> 00:42:01,080
Speaker 1: headline bait. And I think those are interesting speculative plays

822
00:42:01,160 --> 00:42:02,800
Speaker 1: for folks that do that for a living, but I

823
00:42:02,880 --> 00:42:05,239
Speaker 1: don't think they really belonging people's long term portfolio. I

824
00:42:05,239 --> 00:42:07,400
Speaker 1: don't recall a whole lot of work from home ETFs.

825
00:42:08,960 --> 00:42:12,000
Speaker 1: That's that's what is it now, it's already coming gone.

826
00:42:12,239 --> 00:42:16,000
Speaker 1: So last e t F question, why on earth does

827
00:42:16,080 --> 00:42:20,480
Speaker 1: anyone need a single stock e t F. So we've

828
00:42:20,480 --> 00:42:22,040
Speaker 1: got a raft of these things that have come out.

829
00:42:22,280 --> 00:42:24,520
Speaker 1: The SEC is I think going to clamp weight down

830
00:42:24,640 --> 00:42:28,080
Speaker 1: on them. The short answer is they don't. The use

831
00:42:28,160 --> 00:42:31,439
Speaker 1: case for a single stock et is you either it's

832
00:42:31,600 --> 00:42:34,440
Speaker 1: an access to leverage that you couldn't get otherwise two

833
00:42:34,520 --> 00:42:37,600
Speaker 1: to one plus two to one is four to one, right,

834
00:42:38,160 --> 00:42:40,120
Speaker 1: works right? Well, well you could you can own a

835
00:42:40,160 --> 00:42:42,759
Speaker 1: two to one or three to one single stock et F.

836
00:42:43,239 --> 00:42:45,600
Speaker 1: You could buy it on margin, so you could go

837
00:42:45,680 --> 00:42:48,440
Speaker 1: four or six to one, which is kind of against

838
00:42:48,760 --> 00:42:51,719
Speaker 1: It's funny because I got invited to speak at the

839
00:42:52,560 --> 00:42:54,880
Speaker 1: SEC thing and I'm like, you should speak today's nodding,

840
00:42:55,160 --> 00:42:56,960
Speaker 1: and they said, yeah, yeah, we we already have him

841
00:42:57,000 --> 00:42:59,600
Speaker 1: on his artist. I'm like, I swear I get my answers,

842
00:42:59,640 --> 00:43:02,640
Speaker 1: so let cut out the middleman. Go talk to him. Yeah,

843
00:43:02,680 --> 00:43:04,640
Speaker 1: I'll be talking to them about that. So like they

844
00:43:04,719 --> 00:43:06,480
Speaker 1: have a use case if you want to be get

845
00:43:06,600 --> 00:43:08,520
Speaker 1: leverage and you don't want to use your margin account

846
00:43:08,600 --> 00:43:11,279
Speaker 1: or you ran out of margin your margin account. That yeah,

847
00:43:11,360 --> 00:43:14,160
Speaker 1: that's a narrow use case. More importantly, if you want

848
00:43:14,200 --> 00:43:17,520
Speaker 1: to short something, right, so Testla Tesla Q is the

849
00:43:17,560 --> 00:43:19,440
Speaker 1: one that's I caught, the only one that has any

850
00:43:19,480 --> 00:43:21,879
Speaker 1: of the assets right now, and it's the short Tesla fund.

851
00:43:22,400 --> 00:43:25,120
Speaker 1: The biggest benefit of those and I can't believe I'm

852
00:43:25,120 --> 00:43:27,040
Speaker 1: saying this out loud, is you can only lose all

853
00:43:27,080 --> 00:43:30,000
Speaker 1: your money like that can only lose You can only

854
00:43:30,040 --> 00:43:32,040
Speaker 1: lose all your money. That way do I sign up

855
00:43:32,080 --> 00:43:35,320
Speaker 1: for that? That sounds fair as opposed to futures that

856
00:43:35,640 --> 00:43:38,480
Speaker 1: theoretically you put up direct short and you can lose

857
00:43:38,560 --> 00:43:41,360
Speaker 1: a direct shorting finding getting a locate and getting short

858
00:43:41,840 --> 00:43:44,400
Speaker 1: theoretically you know, you have one really bad day and

859
00:43:44,480 --> 00:43:48,000
Speaker 1: you can be out more than your account. Right, that's fair,

860
00:43:48,960 --> 00:43:52,040
Speaker 1: But we are splitting hairs. The short answer, Berry is

861
00:43:52,400 --> 00:43:55,040
Speaker 1: they don't really have much of a use case for

862
00:43:55,200 --> 00:43:58,520
Speaker 1: most investors. The fake a d rs like Roundhill it

863
00:43:58,600 --> 00:44:00,879
Speaker 1: filed for like you know, get am Sung which doesn't

864
00:44:00,920 --> 00:44:02,360
Speaker 1: have an a d R and you can trade it

865
00:44:02,400 --> 00:44:04,880
Speaker 1: like it's an a d R. That one actually that

866
00:44:04,880 --> 00:44:11,719
Speaker 1: would have some utility and I can't buy Why why not?

867
00:44:12,200 --> 00:44:14,400
Speaker 1: Because there are reasons we have a d R rules, right,

868
00:44:14,480 --> 00:44:16,440
Speaker 1: That's part of the reason that you have to go

869
00:44:16,560 --> 00:44:19,480
Speaker 1: through the process of getting a depository receipt listed is

870
00:44:19,560 --> 00:44:22,040
Speaker 1: that the then rules about what that means in terms

871
00:44:22,040 --> 00:44:24,600
Speaker 1: of voting and ownership and reporting and all that jazz.

872
00:44:24,920 --> 00:44:27,920
Speaker 1: Why doesn't Samsung trade as an a d R on

873
00:44:28,000 --> 00:44:30,040
Speaker 1: the New York Stock Exchange. I don't understand that because

874
00:44:30,040 --> 00:44:31,680
Speaker 1: they don't want to go through the process because they

875
00:44:31,760 --> 00:44:33,759
Speaker 1: just don't care. Well, yeah, I mean they'd have to

876
00:44:33,800 --> 00:44:35,879
Speaker 1: do reporting that they don't mean. I'm guessing a little

877
00:44:35,880 --> 00:44:37,719
Speaker 1: bit because I don't live in their boardroom, but you know,

878
00:44:37,920 --> 00:44:40,000
Speaker 1: they have reporting that they'd have to do they don't

879
00:44:40,040 --> 00:44:42,440
Speaker 1: want to do. They've got American investors they don't want

880
00:44:42,440 --> 00:44:44,920
Speaker 1: to have to talk to. You know, they've got requirements

881
00:44:44,960 --> 00:44:48,160
Speaker 1: that the Nisy would put on them. Why would you bother?

882
00:44:48,400 --> 00:44:50,360
Speaker 1: And and also you end up in the situation we

883
00:44:50,440 --> 00:44:52,400
Speaker 1: have right now with Baba, where you end up with

884
00:44:52,480 --> 00:44:53,840
Speaker 1: the I mean, Bob is not an a d R,

885
00:44:53,920 --> 00:44:55,840
Speaker 1: it's a it's a it's a direct list. But you

886
00:44:56,000 --> 00:44:58,480
Speaker 1: end up with this issue where you've got multiple jurisdictions

887
00:44:58,719 --> 00:45:02,640
Speaker 1: governing a country and comes right, especially anything out of

888
00:45:02,719 --> 00:45:06,360
Speaker 1: China these days are really problematic. Alright, I said, no

889
00:45:06,440 --> 00:45:08,480
Speaker 1: more E t F questions. I got to ask you

890
00:45:08,560 --> 00:45:11,560
Speaker 1: the mutual fund question. And you and I again have

891
00:45:11,680 --> 00:45:14,880
Speaker 1: talked about this in the past. If mutual funds were

892
00:45:14,920 --> 00:45:19,080
Speaker 1: a brand new product, would they be approved in Absolutely

893
00:45:20,080 --> 00:45:23,320
Speaker 1: they would not tell us because the E t F

894
00:45:23,400 --> 00:45:26,480
Speaker 1: structure is inherently more tax fair, and that sounds like

895
00:45:26,560 --> 00:45:30,360
Speaker 1: a weird no. The problem with mutual funds, if you

896
00:45:30,400 --> 00:45:32,920
Speaker 1: want them today is that the pitch would be, Hey,

897
00:45:33,040 --> 00:45:36,879
Speaker 1: we're gonna pool our investors, but for tax purposes. If

898
00:45:37,000 --> 00:45:39,880
Speaker 1: you sell out, you can take care of your own stuff,

899
00:45:39,920 --> 00:45:42,239
Speaker 1: but we're gonna book that gain over here with all

900
00:45:42,280 --> 00:45:44,879
Speaker 1: of these other investors, send them all of a check,

901
00:45:44,960 --> 00:45:47,280
Speaker 1: and make all of them restate your base at their basis.

902
00:45:47,360 --> 00:45:49,600
Speaker 1: Because you decided you want out on a Tuesday and

903
00:45:50,080 --> 00:45:53,560
Speaker 1: tax exactly. That's that would be a nonstarter today, end

904
00:45:53,600 --> 00:45:56,640
Speaker 1: of day price, which by the way, works great in

905
00:45:56,680 --> 00:45:59,320
Speaker 1: a four oh one K. Yeah. So it's like I

906
00:45:59,520 --> 00:46:02,360
Speaker 1: I try not to spend a lot of time imagining

907
00:46:02,400 --> 00:46:04,919
Speaker 1: how I think the world should be today and spend

908
00:46:04,960 --> 00:46:06,320
Speaker 1: more of it trying to focus on the word the

909
00:46:06,360 --> 00:46:09,560
Speaker 1: world is today and might end up. We have mutual

910
00:46:09,640 --> 00:46:12,560
Speaker 1: funds now. They're not going to go anywhere because they're

911
00:46:12,600 --> 00:46:15,840
Speaker 1: baked into our retirement system. They're a better fit for

912
00:46:16,040 --> 00:46:18,560
Speaker 1: that specific purpose than E t f s because of

913
00:46:18,640 --> 00:46:22,520
Speaker 1: fractional shares. There's no economic innsenter for anybody to change

914
00:46:22,560 --> 00:46:25,239
Speaker 1: any of that. So I'm gonna die and my four

915
00:46:25,280 --> 00:46:27,520
Speaker 1: ownk is going to be in mutual funds. That's probably

916
00:46:27,560 --> 00:46:30,800
Speaker 1: what's going to happen right whenever, whether that's tomorrow or

917
00:46:30,920 --> 00:46:33,160
Speaker 1: forty years from now. I don't think mutual funds are

918
00:46:33,160 --> 00:46:36,200
Speaker 1: going away because there's no reason for anybody to usurp it.

919
00:46:36,520 --> 00:46:39,360
Speaker 1: Unless we literally throw out the forty Act and rewrite

920
00:46:39,360 --> 00:46:41,640
Speaker 1: the securities laws of this country, the mutual funds going

921
00:46:41,719 --> 00:46:44,840
Speaker 1: to exist. Channeling Ray Dalio's quote, it's the role of

922
00:46:44,920 --> 00:46:47,440
Speaker 1: the investor to deal with the world as it is.

923
00:46:49,400 --> 00:46:52,799
Speaker 1: I'm a huge fan of that quote. Fascinating. So let's

924
00:46:52,840 --> 00:46:56,080
Speaker 1: talk a little bit about a quote from you that

925
00:46:56,280 --> 00:47:00,279
Speaker 1: I'm perplexed about, and that is the ants here to

926
00:47:00,440 --> 00:47:04,120
Speaker 1: every question starts at the beginning and gets just as

927
00:47:04,239 --> 00:47:07,880
Speaker 1: detailed as you need it to be until you've satisfied

928
00:47:07,960 --> 00:47:12,200
Speaker 1: the need. What does that have to do with finance? Well, look,

929
00:47:12,520 --> 00:47:15,279
Speaker 1: the world is infinitely complex, right that I think we

930
00:47:15,320 --> 00:47:18,000
Speaker 1: can get down that it's not black and white. It's

931
00:47:18,000 --> 00:47:20,840
Speaker 1: not black and there bumper stickers on the answers to

932
00:47:20,920 --> 00:47:23,640
Speaker 1: our problem to get like, to get really like neurophil

933
00:47:23,880 --> 00:47:27,360
Speaker 1: philosophical about it. As human beings, we walk around looking

934
00:47:27,440 --> 00:47:30,120
Speaker 1: for affordances. And what that word means is like we

935
00:47:30,239 --> 00:47:32,960
Speaker 1: look for the handle on the cup, and we said,

936
00:47:32,960 --> 00:47:34,800
Speaker 1: when we see a cup and there's a handle on it,

937
00:47:35,280 --> 00:47:37,560
Speaker 1: we can say, oh, I've seen this before. I understand

938
00:47:37,680 --> 00:47:39,799
Speaker 1: that's a thing I can grasp, and I understand how

939
00:47:39,880 --> 00:47:41,440
Speaker 1: my hand works, and so now I can get the

940
00:47:41,480 --> 00:47:43,759
Speaker 1: cup of coffee. If all we're trying to do is

941
00:47:43,840 --> 00:47:46,880
Speaker 1: drink the coffee, that's as far as we need to go, right,

942
00:47:46,960 --> 00:47:49,400
Speaker 1: we get the affordance that allows us to work in

943
00:47:49,480 --> 00:47:51,840
Speaker 1: the environment that we're in. Our model of the universe

944
00:47:51,920 --> 00:47:53,840
Speaker 1: doesn't have to be perfect. It just needs to be

945
00:47:54,000 --> 00:47:56,160
Speaker 1: good enough to get us through the day. And it's

946
00:47:56,239 --> 00:47:58,440
Speaker 1: going to be imperfect. That's the other thing I think

947
00:47:58,480 --> 00:48:00,719
Speaker 1: that is an important thing for anybody who's in the

948
00:48:00,760 --> 00:48:03,400
Speaker 1: business of dealing with human beings for a living around

949
00:48:03,440 --> 00:48:08,560
Speaker 1: emotional subjects, which is the job of financial advisor understanding that, Oh,

950
00:48:09,040 --> 00:48:12,400
Speaker 1: everybody lives in their own little interpreted reality where some

951
00:48:12,560 --> 00:48:16,160
Speaker 1: people understand the molecular structure of the cup and some

952
00:48:16,320 --> 00:48:19,800
Speaker 1: people literally just having their head. Oh handle coffee, drink,

953
00:48:20,440 --> 00:48:23,520
Speaker 1: and both of those are okay, depending on what your purposes.

954
00:48:23,719 --> 00:48:25,920
Speaker 1: What does that have to do with finance. Well, in

955
00:48:26,040 --> 00:48:30,319
Speaker 1: finance we approach that constantly. The markets. Just think about

956
00:48:30,440 --> 00:48:34,120
Speaker 1: we talk about the markets. Okay, do you understand the

957
00:48:34,239 --> 00:48:37,680
Speaker 1: markets well? Yes and no, right, yes, you understand the

958
00:48:37,719 --> 00:48:39,800
Speaker 1: basics of like what's going across the ticker and what

959
00:48:39,880 --> 00:48:42,960
Speaker 1: your clients need to do. Do you really understand at

960
00:48:43,000 --> 00:48:46,520
Speaker 1: a really detailed level exactly how payment for order flow

961
00:48:46,600 --> 00:48:50,520
Speaker 1: impacts capital requirements at the dtc C. No, you don't

962
00:48:50,640 --> 00:48:53,480
Speaker 1: need to. It's not important to what your job is

963
00:48:53,960 --> 00:48:57,120
Speaker 1: until something breaks right, and so part of my job

964
00:48:57,160 --> 00:48:59,920
Speaker 1: as a financial futurist is to go down a lot

965
00:49:00,000 --> 00:49:02,279
Speaker 1: of those rabbit holes so that when when the world

966
00:49:02,320 --> 00:49:04,400
Speaker 1: blows up and everybody's like, payment for workflow is the

967
00:49:04,440 --> 00:49:07,000
Speaker 1: worst thing in the world, I'm not starting from square

968
00:49:07,040 --> 00:49:11,440
Speaker 1: one saying what does pfo F stand for? I've already understood. Okay,

969
00:49:11,560 --> 00:49:14,160
Speaker 1: here's the mechanics of how this go. What am I missing?

970
00:49:14,239 --> 00:49:16,080
Speaker 1: I haven't looked at it in eight weeks. Maybe the

971
00:49:16,160 --> 00:49:18,920
Speaker 1: world change, so I can do the update to get current.

972
00:49:19,640 --> 00:49:21,800
Speaker 1: But I'm not starting from scratch every day, and I

973
00:49:22,000 --> 00:49:24,560
Speaker 1: hopefully that's some of the value. So funny you mentioned

974
00:49:25,040 --> 00:49:28,560
Speaker 1: understanding what's going on when the world breaks. The book

975
00:49:28,640 --> 00:49:32,000
Speaker 1: I love to give to younger people who are getting

976
00:49:32,040 --> 00:49:36,520
Speaker 1: started in markets is tim Mets is Black Monday, because

977
00:49:37,400 --> 00:49:40,839
Speaker 1: even today, most people have no idea what happened during

978
00:49:40,880 --> 00:49:44,600
Speaker 1: the eighty seven crash. And it's exactly as you've described.

979
00:49:45,120 --> 00:49:49,560
Speaker 1: It is the logistics, the plumbing, the day to day

980
00:49:49,680 --> 00:49:53,600
Speaker 1: operations that you don't realize that every decision that's made

981
00:49:54,000 --> 00:49:58,080
Speaker 1: has ramifications deep into the future for how markets operate.

982
00:49:58,160 --> 00:49:59,759
Speaker 1: I'll give you one little weird side note on that.

983
00:49:59,840 --> 00:50:03,520
Speaker 1: So seven, I was twenty one years old or something

984
00:50:03,600 --> 00:50:07,359
Speaker 1: like that. I was living in Hollywood, California. I had

985
00:50:07,400 --> 00:50:10,000
Speaker 1: a little tiny bit of money invested, maybe five grand

986
00:50:10,080 --> 00:50:12,080
Speaker 1: that my grandfather had given me in a Smith Barney

987
00:50:12,080 --> 00:50:16,080
Speaker 1: account or something like that. You know, seven happened, pretty

988
00:50:16,160 --> 00:50:19,120
Speaker 1: much lost most of it whatever, But I became fascinated

989
00:50:19,239 --> 00:50:23,160
Speaker 1: at that moment by what the hell just happened. Years later,

990
00:50:23,320 --> 00:50:25,200
Speaker 1: literally four or five years later, I've gone and gotten

991
00:50:25,239 --> 00:50:27,719
Speaker 1: an m b A. I'm studying investment finance in the

992
00:50:27,800 --> 00:50:29,800
Speaker 1: back of my head constantly, I'm like, I want to

993
00:50:29,880 --> 00:50:31,600
Speaker 1: understand what that, So I read everything about it. I

994
00:50:31,680 --> 00:50:34,719
Speaker 1: end up working for Well's far Unico in the very

995
00:50:34,760 --> 00:50:38,040
Speaker 1: early or something like that, Low and Behol. I started

996
00:50:38,080 --> 00:50:41,040
Speaker 1: going through stacks of stuff on portfolio insurance because they

997
00:50:41,080 --> 00:50:44,560
Speaker 1: were a huge writer that at the time and index provider.

998
00:50:44,760 --> 00:50:46,600
Speaker 1: So it's like, and I had never at that point,

999
00:50:46,680 --> 00:50:48,279
Speaker 1: I had not been down that rabbit hole. There was

1000
00:50:48,320 --> 00:50:50,680
Speaker 1: no Internet to go search on that. Now I had

1001
00:50:50,719 --> 00:50:53,120
Speaker 1: access to all of these internal documents about like what

1002
00:50:53,280 --> 00:50:54,760
Speaker 1: was actually going and the ne of it was hidden.

1003
00:50:54,760 --> 00:50:58,520
Speaker 1: It was all part of congression, the giant SEC report

1004
00:50:58,600 --> 00:51:02,160
Speaker 1: that came out afterwards, and and it was just anyway.

1005
00:51:02,280 --> 00:51:06,440
Speaker 1: My point is, it's fascinating to understand. To me, it's

1006
00:51:06,440 --> 00:51:09,719
Speaker 1: fascining to understand how the pieces actually work versus how

1007
00:51:09,800 --> 00:51:12,000
Speaker 1: we think they work, because they're never the same. One

1008
00:51:12,040 --> 00:51:13,800
Speaker 1: of the things in the book that was always so

1009
00:51:13,920 --> 00:51:16,759
Speaker 1: vivid to me, and I'm sure I'm gonna misquote this,

1010
00:51:17,000 --> 00:51:21,440
Speaker 1: But they used to run the prints from the Chicago

1011
00:51:21,719 --> 00:51:25,839
Speaker 1: futures pits into the floor of the New York Stocks Change,

1012
00:51:25,840 --> 00:51:28,200
Speaker 1: so you could see how the futures were trading, and

1013
00:51:28,840 --> 00:51:33,160
Speaker 1: marry that with portfolio insurance, and suddenly it's a vicious

1014
00:51:33,200 --> 00:51:36,520
Speaker 1: cycle downwards as it just be. There is no bottom

1015
00:51:36,560 --> 00:51:37,719
Speaker 1: and that, and that's how you end up with a

1016
00:51:37,840 --> 00:51:42,120
Speaker 1: down day on on the Dow when it should have

1017
00:51:42,200 --> 00:51:45,320
Speaker 1: been you know, a run of the mill correction. But

1018
00:51:45,440 --> 00:51:47,560
Speaker 1: part of the reason that's so interesting is that the

1019
00:51:47,640 --> 00:51:50,759
Speaker 1: mechanics of that are now gone. The world doesn't work

1020
00:51:50,880 --> 00:51:54,200
Speaker 1: that way anymore. But people are the same, right, They

1021
00:51:54,360 --> 00:51:57,920
Speaker 1: like Neanderthals are pretty much doing the exact same emotional

1022
00:51:58,320 --> 00:52:02,160
Speaker 1: by sell you know, green fear trade off in that cycle.

1023
00:52:02,280 --> 00:52:04,920
Speaker 1: And so what happened in eight seven was a cycle

1024
00:52:05,000 --> 00:52:06,480
Speaker 1: that was had you know, I don't know, had had

1025
00:52:06,480 --> 00:52:08,920
Speaker 1: a cycle time of twenty minutes. Now it has a

1026
00:52:08,960 --> 00:52:11,320
Speaker 1: cycle time of twenty milliseconds. But at the end of

1027
00:52:11,360 --> 00:52:13,960
Speaker 1: the day, you still have people making those decisions. So

1028
00:52:14,080 --> 00:52:17,400
Speaker 1: another quote of yours is history tells us mostly about

1029
00:52:17,480 --> 00:52:21,239
Speaker 1: what people did when faced with a specific set of

1030
00:52:21,360 --> 00:52:25,280
Speaker 1: constraints and inputs. How does that affect traders and investors

1031
00:52:25,360 --> 00:52:28,279
Speaker 1: in market. Well, so you know you do this on

1032
00:52:28,360 --> 00:52:31,360
Speaker 1: your podcast, right, you talked to a lot of very professional,

1033
00:52:31,680 --> 00:52:35,080
Speaker 1: very successful people. That's why it's called Masters in Business. Right.

1034
00:52:35,680 --> 00:52:38,200
Speaker 1: The challenge with that is, I think it's very easy

1035
00:52:38,280 --> 00:52:41,239
Speaker 1: to get hung up on the thing that they did,

1036
00:52:41,680 --> 00:52:43,719
Speaker 1: not why they did it, and what they needed to

1037
00:52:43,760 --> 00:52:46,200
Speaker 1: be able to do it. So we look back at assignments, right,

1038
00:52:46,239 --> 00:52:50,480
Speaker 1: people who were wizards of Wall Street, and we were so,

1039
00:52:50,760 --> 00:52:53,120
Speaker 1: you know, we Revere Warren Buffett, right, and we said, like,

1040
00:52:53,280 --> 00:52:55,920
Speaker 1: you know, and people write books about them and all

1041
00:52:55,960 --> 00:52:58,200
Speaker 1: these things, and often what they end up looking like

1042
00:52:58,360 --> 00:53:01,600
Speaker 1: is hero worship. The more interesting question is that, Okay,

1043
00:53:01,680 --> 00:53:04,560
Speaker 1: Buffet's been really successful. Instead of trying to figure out

1044
00:53:04,640 --> 00:53:06,719
Speaker 1: what is it about Buffett that was better, I think

1045
00:53:06,760 --> 00:53:08,960
Speaker 1: it's much more interesting to look at, well, okay, what

1046
00:53:09,200 --> 00:53:10,920
Speaker 1: was the pond that he was fishing in, who were

1047
00:53:11,040 --> 00:53:14,080
Speaker 1: his who were his colleagues, what were his information sources,

1048
00:53:14,400 --> 00:53:16,600
Speaker 1: What kind of capital constraints did he have or what

1049
00:53:16,800 --> 00:53:20,240
Speaker 1: lack of capital constraints did he have versus competitors. That's

1050
00:53:20,280 --> 00:53:22,759
Speaker 1: what makes him an interesting story. Now, of course he

1051
00:53:22,760 --> 00:53:25,759
Speaker 1: wouldn't be successful. He wasn't also sharp and brilliant and

1052
00:53:25,800 --> 00:53:28,400
Speaker 1: good at his job and good with people. But I

1053
00:53:28,520 --> 00:53:30,880
Speaker 1: think it's much more interesting to look at those decisions

1054
00:53:31,080 --> 00:53:35,440
Speaker 1: as sort of contextual reactions to their environment, as opposed

1055
00:53:35,480 --> 00:53:37,720
Speaker 1: to revering them as like what we should all invest

1056
00:53:37,800 --> 00:53:41,440
Speaker 1: like Warren Buffett. No, we should all have the perspicacity

1057
00:53:41,640 --> 00:53:44,960
Speaker 1: to invest like Warren Buffett when presented with that exact

1058
00:53:45,000 --> 00:53:48,279
Speaker 1: set of situation. It's about process. And one of the

1059
00:53:48,320 --> 00:53:51,360
Speaker 1: things I really go out of my way to avoid

1060
00:53:51,760 --> 00:53:56,120
Speaker 1: is the classic survivorship bias, because that's why one of

1061
00:53:56,200 --> 00:53:58,320
Speaker 1: my favorite questions is always what do you know today

1062
00:53:58,400 --> 00:54:00,840
Speaker 1: that you wish you knew to only five years or

1063
00:54:00,840 --> 00:54:03,239
Speaker 1: so ago when you started, Because I want to give

1064
00:54:03,280 --> 00:54:05,759
Speaker 1: people an opportunity to say, oh, I mess this up

1065
00:54:05,920 --> 00:54:09,319
Speaker 1: or I didn't know this otherwise. It's that's the criticism

1066
00:54:09,480 --> 00:54:12,440
Speaker 1: of you know good too great. Here are twelve companies

1067
00:54:12,480 --> 00:54:15,080
Speaker 1: that did fantastic in the eighties and nineties, and then

1068
00:54:15,120 --> 00:54:17,239
Speaker 1: you look forward a decade and half of them are

1069
00:54:17,320 --> 00:54:20,440
Speaker 1: either out of business or gone or wildly under performing

1070
00:54:20,480 --> 00:54:22,880
Speaker 1: the market. Yeah. I think that's exactly the point. Um,

1071
00:54:22,960 --> 00:54:25,839
Speaker 1: So I I get very skeptical of hero worship I'm

1072
00:54:25,960 --> 00:54:29,759
Speaker 1: much more interested in understanding decision making. So, like you know,

1073
00:54:30,120 --> 00:54:33,040
Speaker 1: in terms of like great business books, I'd rather focus

1074
00:54:33,120 --> 00:54:36,560
Speaker 1: on like Choices, values and frames by Ken min Tversky

1075
00:54:37,320 --> 00:54:39,920
Speaker 1: versus anything Mountain Gladwell has ever written. I thought you're

1076
00:54:39,920 --> 00:54:43,600
Speaker 1: gonna go with money Ball? Well no, but like, actually

1077
00:54:43,640 --> 00:54:46,320
Speaker 1: money Ball is a great counter example where that's a

1078
00:54:46,440 --> 00:54:49,080
Speaker 1: great narrative, it's a great story. But I think that

1079
00:54:49,200 --> 00:54:51,440
Speaker 1: the lesson some people get out of money Ball is, Oh,

1080
00:54:51,480 --> 00:54:52,920
Speaker 1: there was this one sharp kid in the right place

1081
00:54:52,920 --> 00:54:54,760
Speaker 1: at the right time, and he really did something amazing

1082
00:54:55,040 --> 00:54:57,120
Speaker 1: and got just enough people to pay attention and got

1083
00:54:57,160 --> 00:54:59,920
Speaker 1: really lucky. And isn't that a great story? Where they're

1084
00:55:00,080 --> 00:55:03,600
Speaker 1: real thing is okay, what is it about that environment

1085
00:55:03,640 --> 00:55:05,800
Speaker 1: that made a difference. This was somebody who focused on

1086
00:55:06,040 --> 00:55:08,680
Speaker 1: data when other people thought data was irrelevant. They got

1087
00:55:08,840 --> 00:55:12,000
Speaker 1: nerdy when people were thinking it was hunch. The same

1088
00:55:12,040 --> 00:55:14,600
Speaker 1: thing happens in markets all the time. Right when people

1089
00:55:14,640 --> 00:55:17,040
Speaker 1: get nerdy but other people are focused on the emotions,

1090
00:55:17,440 --> 00:55:20,239
Speaker 1: there's often a real opportunity there, right, because now you're

1091
00:55:20,280 --> 00:55:23,160
Speaker 1: dealing with the system, not with the people. You've mentioned

1092
00:55:23,239 --> 00:55:27,480
Speaker 1: another book that I think is fascinating as history the

1093
00:55:27,640 --> 00:55:30,680
Speaker 1: right stuff tell us about what the right stuff has

1094
00:55:30,719 --> 00:55:33,600
Speaker 1: to do with Yeah. So well again, So I'm glad

1095
00:55:33,640 --> 00:55:35,840
Speaker 1: you made that bridge because because I think Moneyball is

1096
00:55:35,840 --> 00:55:38,640
Speaker 1: an interesting example there. To me, Moneyball is interesting not

1097
00:55:39,080 --> 00:55:42,200
Speaker 1: for the like act like this dude, but as a

1098
00:55:42,400 --> 00:55:45,920
Speaker 1: character study to understand how human beings reacted there. So like,

1099
00:55:46,440 --> 00:55:48,120
Speaker 1: um in the right stuff, which was the example I

1100
00:55:48,239 --> 00:55:50,640
Speaker 1: was using in the email I sent you. I'm like

1101
00:55:50,760 --> 00:55:52,840
Speaker 1: a lot of people my age and gen X fascinated

1102
00:55:52,880 --> 00:55:55,520
Speaker 1: by the Apollo Program and read everything and seeing every

1103
00:55:55,600 --> 00:55:58,040
Speaker 1: documentary and built all the models when I was a kid, right,

1104
00:55:58,040 --> 00:56:00,879
Speaker 1: I mean it was the Wild West. You're too young

1105
00:56:00,960 --> 00:56:04,480
Speaker 1: to have been called down to the assembly when one

1106
00:56:04,560 --> 00:56:07,320
Speaker 1: of theo I think the first Apollo landed on the

1107
00:56:07,400 --> 00:56:09,480
Speaker 1: Moon or c. Yeah, but I remember watching on TV

1108
00:56:09,600 --> 00:56:11,440
Speaker 1: as a kid, sitting on the couch, right, So like

1109
00:56:11,960 --> 00:56:14,600
Speaker 1: very very real to me. Um, And so I felt

1110
00:56:14,640 --> 00:56:16,759
Speaker 1: like by the time I was sixteen, I felt like

1111
00:56:16,800 --> 00:56:19,560
Speaker 1: I had a pretty nerdy understanding of the Apollo Program.

1112
00:56:19,920 --> 00:56:21,880
Speaker 1: But then you start reading stuff like Tom Wolf and

1113
00:56:21,960 --> 00:56:24,080
Speaker 1: the Great Stuff. Did you read it or did you?

1114
00:56:24,280 --> 00:56:26,600
Speaker 1: Full disclosure, I watched the movie, I never know, I

1115
00:56:26,640 --> 00:56:28,200
Speaker 1: read the book. I read the book when it came out,

1116
00:56:28,440 --> 00:56:30,680
Speaker 1: and the reason I loved it again was not because

1117
00:56:30,719 --> 00:56:33,640
Speaker 1: it told me anything about how they made the landers.

1118
00:56:34,160 --> 00:56:37,160
Speaker 1: It was because it was like, holy crap, this was

1119
00:56:37,280 --> 00:56:41,040
Speaker 1: an ego farm, Like this was a whole like that.

1120
00:56:41,200 --> 00:56:43,600
Speaker 1: It felt like Wall Street. Okay, here a bunch of

1121
00:56:43,880 --> 00:56:50,399
Speaker 1: extremely high performance, almost exclusively dudes with enormous egos who

1122
00:56:50,560 --> 00:56:54,319
Speaker 1: are going to work collectively to do something nearly impossible.

1123
00:56:54,760 --> 00:56:57,480
Speaker 1: That's why that's an interesting story. It could be about,

1124
00:56:58,000 --> 00:57:01,320
Speaker 1: you know, the Dream Team hockey, right. The fact that

1125
00:57:01,400 --> 00:57:05,000
Speaker 1: it was about these like super high performance people interacting

1126
00:57:05,000 --> 00:57:07,160
Speaker 1: with each other for a common goal. That's what I

1127
00:57:07,239 --> 00:57:08,880
Speaker 1: think was interesting about it. And I think if you

1128
00:57:09,000 --> 00:57:12,000
Speaker 1: learned something from the Apollo program, it should be about that,

1129
00:57:12,360 --> 00:57:14,759
Speaker 1: not about like, well, government spending did this and we

1130
00:57:14,920 --> 00:57:17,600
Speaker 1: invested in No, no, no. This was about creating a

1131
00:57:17,720 --> 00:57:21,000
Speaker 1: community of people around a common goal. So you mentioned

1132
00:57:21,080 --> 00:57:23,720
Speaker 1: what we get wrong about markets. What else do we

1133
00:57:23,800 --> 00:57:27,400
Speaker 1: get wrong about the state of the world. Well, so

1134
00:57:27,600 --> 00:57:30,640
Speaker 1: much so. The most interesting thing I think that's markets

1135
00:57:30,680 --> 00:57:32,840
Speaker 1: related is probably what's going on in economics. I'm a

1136
00:57:32,880 --> 00:57:36,120
Speaker 1: big fan of Oli Peters has run something called ergodicity

1137
00:57:36,200 --> 00:57:39,960
Speaker 1: economics from the Fine good city, because every time I

1138
00:57:40,040 --> 00:57:42,600
Speaker 1: look it up, it seems Google gives me a different,

1139
00:57:43,320 --> 00:57:46,240
Speaker 1: you know, reductionist. And so look with the caveat that

1140
00:57:46,280 --> 00:57:48,880
Speaker 1: I'm neither a mathematician or an economist, and neither are

1141
00:57:48,920 --> 00:57:52,680
Speaker 1: you either of those things. By training, um, fundamentally, we

1142
00:57:52,840 --> 00:57:55,640
Speaker 1: assume certain things about how money and markets work. A

1143
00:57:55,800 --> 00:57:58,960
Speaker 1: big one is that when you average something over time,

1144
00:57:59,120 --> 00:58:00,720
Speaker 1: you end up with similar or answers to when you

1145
00:58:00,760 --> 00:58:07,040
Speaker 1: average things over populations. Right, So if you flip a

1146
00:58:07,080 --> 00:58:09,760
Speaker 1: coin a thousand times, we can come up with similar

1147
00:58:09,800 --> 00:58:12,200
Speaker 1: expected values too, if we have a thousand people flip

1148
00:58:12,240 --> 00:58:15,520
Speaker 1: a coin once. Right. The connection between those is the

1149
00:58:15,680 --> 00:58:18,440
Speaker 1: ergotic assumption, as I understand it, And if I'm wrong,

1150
00:58:18,480 --> 00:58:20,880
Speaker 1: I'm sure people will send me hate mail. A lot

1151
00:58:21,000 --> 00:58:23,800
Speaker 1: of what we do in economics is based on that

1152
00:58:24,000 --> 00:58:26,800
Speaker 1: sort of fundamental mathematical assumption that that you don't have

1153
00:58:26,960 --> 00:58:29,280
Speaker 1: to worry too much about those things. The problem with

1154
00:58:29,440 --> 00:58:32,959
Speaker 1: that is that it's frankly not true. Something as simple

1155
00:58:33,000 --> 00:58:34,840
Speaker 1: as starting conditions. You can do this with just the

1156
00:58:34,880 --> 00:58:37,640
Speaker 1: coin flip experiment. Right. If you and I flip coins,

1157
00:58:37,720 --> 00:58:40,800
Speaker 1: and you flip heads four times in a row top

1158
00:58:40,880 --> 00:58:43,400
Speaker 1: to bottom, and I just know I just randomly, you know,

1159
00:58:43,440 --> 00:58:46,000
Speaker 1: heads tales, heads tails, but we're betting a hundred dollars

1160
00:58:46,040 --> 00:58:48,640
Speaker 1: on each one. I will probably never catch up to

1161
00:58:48,720 --> 00:58:52,720
Speaker 1: you because you are your path dependency on those starting

1162
00:58:52,760 --> 00:58:55,160
Speaker 1: conditions of like you flip that coin heads five times

1163
00:58:55,200 --> 00:58:58,360
Speaker 1: in a row, you now have capital, you have opportunity,

1164
00:58:58,720 --> 00:59:01,240
Speaker 1: you can make smaller bets or lower Kelly number like

1165
00:59:01,360 --> 00:59:05,320
Speaker 1: you get sort of stuff going on. And because I

1166
00:59:05,440 --> 00:59:09,080
Speaker 1: flipped two tails off the beginning, I'm screwed. That is

1167
00:59:09,160 --> 00:59:11,440
Speaker 1: a non or gotic function, right, because that's not the

1168
00:59:11,520 --> 00:59:14,160
Speaker 1: same as saying, well, we're gonna have ten tho people

1169
00:59:14,280 --> 00:59:17,160
Speaker 1: go through that same experiment on average, everybody's gonna flip

1170
00:59:17,200 --> 00:59:19,720
Speaker 1: heads and tails about even so you're saying sequence of

1171
00:59:19,800 --> 00:59:22,880
Speaker 1: returns matters, and you're agreeing with Bill Sharp that that's

1172
00:59:22,920 --> 00:59:26,080
Speaker 1: one of the toughest problems in all of finances, absolutely,

1173
00:59:26,200 --> 00:59:29,200
Speaker 1: is how do you model draw downs and withdrawals in

1174
00:59:29,320 --> 00:59:33,200
Speaker 1: retirement if you get unlucky or lucky in the beginning

1175
00:59:33,240 --> 00:59:36,280
Speaker 1: of your retirement. The implications are actually much more profound

1176
00:59:36,440 --> 00:59:40,400
Speaker 1: than that, however, which is that because we've set up capitalism,

1177
00:59:40,520 --> 00:59:44,880
Speaker 1: not just your portfolio, but global capitalism bakes these assumptions

1178
00:59:44,960 --> 00:59:48,560
Speaker 1: in we end up with things like runaway problems, which

1179
00:59:48,640 --> 00:59:50,480
Speaker 1: we see all over the place right the rise of

1180
00:59:50,520 --> 00:59:53,480
Speaker 1: the billionaire class. It is no longer the case in

1181
00:59:53,680 --> 00:59:58,640
Speaker 1: modern democratic capitalism that the best idea, best executed is

1182
00:59:58,720 --> 01:00:01,680
Speaker 1: the one that will win. It's the best idea that's

1183
01:00:01,720 --> 01:00:04,880
Speaker 1: best executed, that also has very good starting conditions and

1184
01:00:04,960 --> 01:00:07,920
Speaker 1: access to capital, that's the one that wins. So another

1185
01:00:08,000 --> 01:00:10,720
Speaker 1: quote of yours, the here and now is never an accident.

1186
01:00:10,880 --> 01:00:15,520
Speaker 1: It's the result of myriad actions and influences, and understanding

1187
01:00:15,640 --> 01:00:21,040
Speaker 1: those influences provides important context for planning ahead. In other words,

1188
01:00:21,480 --> 01:00:25,200
Speaker 1: path dependency is enormous, and it's not just a function

1189
01:00:25,320 --> 01:00:28,880
Speaker 1: of a single roll of the dice. It's the whole series, absolutely,

1190
01:00:29,040 --> 01:00:32,680
Speaker 1: And also from the advice perspective, part of the reason

1191
01:00:32,720 --> 01:00:35,360
Speaker 1: I put it that way is because boy, I just

1192
01:00:35,520 --> 01:00:38,200
Speaker 1: get this emotional reaction myself, Like I look at the

1193
01:00:38,240 --> 01:00:40,040
Speaker 1: market it's down five per cent, or I look at

1194
01:00:40,080 --> 01:00:42,160
Speaker 1: my portfolio value and it's not what it was six

1195
01:00:42,200 --> 01:00:45,080
Speaker 1: months ago. It's so easy to get caught up in

1196
01:00:45,200 --> 01:00:47,760
Speaker 1: that regret of what happened and I could have done

1197
01:00:47,800 --> 01:00:49,880
Speaker 1: things differently, or if I had put this trade on

1198
01:00:50,000 --> 01:00:52,320
Speaker 1: on Tuesday, I would have made more money and have

1199
01:00:52,600 --> 01:00:56,000
Speaker 1: that dictate what you do today, and that is stupid.

1200
01:00:56,880 --> 01:00:59,800
Speaker 1: What you do today should be based on the markets today,

1201
01:01:00,280 --> 01:01:02,520
Speaker 1: and the markets today are not the markets that were

1202
01:01:02,600 --> 01:01:04,520
Speaker 1: there two weeks ago. When you didn't put on that

1203
01:01:04,600 --> 01:01:07,760
Speaker 1: options trade. That would have been brilliant. So the ability

1204
01:01:07,880 --> 01:01:12,840
Speaker 1: to let did we talk about that option was not

1205
01:01:13,120 --> 01:01:15,880
Speaker 1: going I should have gone bigger. It's killing me and

1206
01:01:15,960 --> 01:01:20,840
Speaker 1: I'm looking at but you're hung up on this and

1207
01:01:20,920 --> 01:01:24,240
Speaker 1: the reality is like, and it's a rounding. A constraint

1208
01:01:24,320 --> 01:01:26,520
Speaker 1: you should have when you're thinking about your money today

1209
01:01:26,680 --> 01:01:28,880
Speaker 1: is what are the transaction costs of not being in

1210
01:01:28,960 --> 01:01:31,600
Speaker 1: what I'm in right now? Because if the answer was zero,

1211
01:01:32,160 --> 01:01:34,640
Speaker 1: then every single morning you should start in cash and

1212
01:01:34,720 --> 01:01:36,560
Speaker 1: make a whole new set of decisions about what you're

1213
01:01:36,560 --> 01:01:40,360
Speaker 1: invested in today. If in a purely frictionless world, I

1214
01:01:40,640 --> 01:01:42,560
Speaker 1: said we were done with ETF, wasn't there a new

1215
01:01:42,600 --> 01:01:45,920
Speaker 1: ETF that wants to invest from the close to the

1216
01:01:46,040 --> 01:01:50,680
Speaker 1: open and spy night chairs. Yeah. See, I'm fascinated by

1217
01:01:51,200 --> 01:01:54,560
Speaker 1: people not understanding, Well, isn't that double or triple the

1218
01:01:54,640 --> 01:01:57,600
Speaker 1: amount of time? Isn't that just time compounded? If we're

1219
01:01:57,640 --> 01:02:00,680
Speaker 1: open from nine thirty to four six and a half hours.

1220
01:02:00,760 --> 01:02:03,120
Speaker 1: The you're closed a lot more. You would think you

1221
01:02:03,120 --> 01:02:05,840
Speaker 1: would be up more over time, right right, Well, they except,

1222
01:02:05,920 --> 01:02:08,560
Speaker 1: of course, liquidity and sorts of other issues like that.

1223
01:02:08,840 --> 01:02:11,760
Speaker 1: But that's kind of interesting, all right. So the biggest

1224
01:02:11,840 --> 01:02:14,720
Speaker 1: question I saved four towards the end here, which is

1225
01:02:15,440 --> 01:02:18,560
Speaker 1: what do we get wrong about human beings? Oh? Boy?

1226
01:02:19,440 --> 01:02:21,080
Speaker 1: I think there are a couple of big ones. And

1227
01:02:21,160 --> 01:02:23,840
Speaker 1: these are fairly recent revelations to me, Um, and some

1228
01:02:23,960 --> 01:02:27,520
Speaker 1: of them are slightly philosophical. I think recognizing the inherent

1229
01:02:27,680 --> 01:02:31,520
Speaker 1: unknowability of reality is an important first step. You know,

1230
01:02:31,640 --> 01:02:35,800
Speaker 1: you mentioned the two millisecond lag on on perception. Um

1231
01:02:35,840 --> 01:02:38,240
Speaker 1: annal Seth has a great book called Being Human or

1232
01:02:38,240 --> 01:02:40,600
Speaker 1: Being You. I always get it wrong. Um. He's the

1233
01:02:40,640 --> 01:02:43,840
Speaker 1: one who put forth the scientific proof that effectively we

1234
01:02:43,960 --> 01:02:47,000
Speaker 1: hallucinate reality. Like what goes on in our heads is

1235
01:02:47,080 --> 01:02:50,680
Speaker 1: a model of the molecular world around us. Do we

1236
01:02:50,760 --> 01:02:52,880
Speaker 1: want to call that a hallucination or is it just

1237
01:02:53,240 --> 01:02:56,520
Speaker 1: our model of the universe? Well, like, if you imagine

1238
01:02:56,560 --> 01:02:59,280
Speaker 1: this coffee cup is here, right, you're already perceiving it

1239
01:02:59,440 --> 01:03:07,040
Speaker 1: delayed from its existence here space etcetera. And that can

1240
01:03:07,080 --> 01:03:09,200
Speaker 1: all get very woo woo and who cares, And so

1241
01:03:09,320 --> 01:03:11,160
Speaker 1: that's fine. It can be woo when he cares, but

1242
01:03:11,360 --> 01:03:13,280
Speaker 1: you have to start from there and build up. And

1243
01:03:13,360 --> 01:03:17,480
Speaker 1: if you accept that fundamentally I cannot prove the table exists,

1244
01:03:17,840 --> 01:03:20,600
Speaker 1: then getting really worked up about Tesla earnings is even

1245
01:03:20,680 --> 01:03:23,840
Speaker 1: more ridiculous, right, because now, when you have an opinion

1246
01:03:23,920 --> 01:03:27,360
Speaker 1: about Tesla earnings, it's based on a set of information

1247
01:03:27,560 --> 01:03:30,680
Speaker 1: that is incredibly incomplete. I don't care whether you're the

1248
01:03:30,800 --> 01:03:33,680
Speaker 1: most storied Tesla analyst in the world. I don't care

1249
01:03:33,720 --> 01:03:36,840
Speaker 1: if you're Elon Musk. Elon Musk on the conference call

1250
01:03:36,960 --> 01:03:40,040
Speaker 1: talking about earnings has no idea what's going on on

1251
01:03:40,120 --> 01:03:42,600
Speaker 1: the floor right now. For all he knows, his factory

1252
01:03:42,760 --> 01:03:46,720
Speaker 1: is burning down while he's talking. Right, So, we're inherently

1253
01:03:46,920 --> 01:03:50,040
Speaker 1: always wrong about the state of anything that we are

1254
01:03:50,080 --> 01:03:54,440
Speaker 1: asserting truth on. So it's about being less wrong when

1255
01:03:54,520 --> 01:03:58,200
Speaker 1: we're trying to make these assessments about I like to

1256
01:03:58,240 --> 01:04:02,000
Speaker 1: say the future is inherently known and unknowable. You're saying

1257
01:04:02,120 --> 01:04:07,360
Speaker 1: the present is inherently inherent Yeah, absolutely unknowable. It's all probabilistic, right,

1258
01:04:07,480 --> 01:04:10,560
Speaker 1: And you know, fundamentally, you start thinking about quantum computing, right,

1259
01:04:10,680 --> 01:04:14,760
Speaker 1: Quantum computing largely ends up being about convincing yourself you're

1260
01:04:14,800 --> 01:04:17,960
Speaker 1: not sure right, because you can't actually measure this state

1261
01:04:18,000 --> 01:04:20,160
Speaker 1: of a cuban in real time because then the wave

1262
01:04:20,400 --> 01:04:24,320
Speaker 1: collapses and it's no longer a quantum computer. So managing

1263
01:04:24,480 --> 01:04:28,240
Speaker 1: uncertainty turns out not just to be a managerial tool

1264
01:04:28,400 --> 01:04:30,800
Speaker 1: for guys who sit around and talk about money. It's

1265
01:04:30,800 --> 01:04:35,440
Speaker 1: actually the fabric of the universe is based on managing probability,

1266
01:04:35,760 --> 01:04:40,640
Speaker 1: not understanding certainty. So if you approach everything from that

1267
01:04:40,800 --> 01:04:43,320
Speaker 1: perspective that, Okay, whether or not I'm going to go

1268
01:04:43,520 --> 01:04:46,760
Speaker 1: on the subway to get down to the hotel, that

1269
01:04:47,040 --> 01:04:50,000
Speaker 1: there's an inherent level of uncertainty in that journey, and

1270
01:04:50,080 --> 01:04:52,440
Speaker 1: that I have to be willing to accept. It's like, okay, well,

1271
01:04:52,680 --> 01:04:55,080
Speaker 1: sixty of the time subway is going to be faster,

1272
01:04:55,640 --> 01:04:57,880
Speaker 1: but here's all the things that could go wrong. Right

1273
01:04:59,000 --> 01:05:01,400
Speaker 1: time it's slower, and two percent of the time I'm

1274
01:05:01,400 --> 01:05:04,640
Speaker 1: going to get or whatever rights. So I think that

1275
01:05:04,800 --> 01:05:07,120
Speaker 1: that is, you know, there's a level of humility that

1276
01:05:07,200 --> 01:05:10,480
Speaker 1: comes from acknowledging the inherent unknowability of whatever is you

1277
01:05:10,520 --> 01:05:13,200
Speaker 1: think you're an expert on um. But at the same time,

1278
01:05:13,280 --> 01:05:16,320
Speaker 1: I think thinking probabilistically. I mean, I think Jim O'Shaughnessy

1279
01:05:16,360 --> 01:05:19,240
Speaker 1: talks about, you know, learning how to think probabilistically and

1280
01:05:19,280 --> 01:05:23,640
Speaker 1: a probabilistic world is opposed to determinalistically, and that I

1281
01:05:23,760 --> 01:05:26,760
Speaker 1: think is very true. So, you know, learning to understand

1282
01:05:26,840 --> 01:05:28,880
Speaker 1: to think in bets. I think it is really Importanti

1283
01:05:28,920 --> 01:05:30,920
Speaker 1: Duke's book on this. I think it's one of the

1284
01:05:31,080 --> 01:05:34,400
Speaker 1: key pieces of reading people should have because it makes

1285
01:05:34,480 --> 01:05:36,840
Speaker 1: it very human. Right, This idea of thinking and bets,

1286
01:05:36,920 --> 01:05:39,800
Speaker 1: thinking and probabilities probably the best thing online poker has

1287
01:05:39,800 --> 01:05:42,320
Speaker 1: ever done to the country. That's interesting, And now I

1288
01:05:42,480 --> 01:05:45,200
Speaker 1: know why you and I get along so well, because

1289
01:05:45,320 --> 01:05:50,120
Speaker 1: we both have the same belief system about how little

1290
01:05:50,280 --> 01:05:55,000
Speaker 1: is actually knowable and why probabilistic thinking is the only

1291
01:05:55,080 --> 01:05:57,440
Speaker 1: way to approach risk assets. Yeah, I mean, at the

1292
01:05:57,640 --> 01:06:01,200
Speaker 1: at the base, all beliefs are wrong right by definition.

1293
01:06:01,240 --> 01:06:03,480
Speaker 1: If I can't prove that I'm in this room, if

1294
01:06:03,520 --> 01:06:06,920
Speaker 1: I can't prove that fundamental reality is phenomenal logically true,

1295
01:06:07,160 --> 01:06:10,440
Speaker 1: I could prove the table is real by just accelerating

1296
01:06:10,520 --> 01:06:13,760
Speaker 1: your skull towards it. Rapidly. Does that disprove it? Or

1297
01:06:14,000 --> 01:06:16,440
Speaker 1: or am I being too literal and I'm not being sarcastic?

1298
01:06:16,520 --> 01:06:19,720
Speaker 1: You know, working with material objects is that where everybody

1299
01:06:19,960 --> 01:06:22,360
Speaker 1: falls down on this? The problem is like, what's actually

1300
01:06:22,440 --> 01:06:25,120
Speaker 1: going on when you're holding onto this table? Is just

1301
01:06:25,280 --> 01:06:28,080
Speaker 1: a set of somatic inputs and visual inputs. So the

1302
01:06:28,120 --> 01:06:31,400
Speaker 1: way we perceive it is sufficient for our purposes, but

1303
01:06:31,640 --> 01:06:36,080
Speaker 1: objectively isn't really as a species, right, we have learned

1304
01:06:36,280 --> 01:06:39,160
Speaker 1: these affordances ways to interact with the environment. I am

1305
01:06:39,200 --> 01:06:41,240
Speaker 1: fairly certain if I hit a table, it will always

1306
01:06:41,320 --> 01:06:44,000
Speaker 1: be there. That is, of course not true when you

1307
01:06:44,040 --> 01:06:46,520
Speaker 1: walk into a really well made illusion. It's not true

1308
01:06:46,520 --> 01:06:49,240
Speaker 1: when you put on a VR headset, right, So we're

1309
01:06:49,320 --> 01:06:54,120
Speaker 1: accepting this version of our perception as somehow phenomenal, logically real.

1310
01:06:54,640 --> 01:06:56,640
Speaker 1: But when we put on the VR headset, we have

1311
01:06:56,760 --> 01:06:58,200
Speaker 1: a brain space where we're like, well, I know the

1312
01:06:58,240 --> 01:07:01,080
Speaker 1: table is not really there. But then again, most people

1313
01:07:01,120 --> 01:07:03,240
Speaker 1: put on that VR headset and they fall down when

1314
01:07:03,280 --> 01:07:04,919
Speaker 1: they go to lean on the table that's not there.

1315
01:07:05,160 --> 01:07:07,800
Speaker 1: Oh is that true? I mean you've seen the video.

1316
01:07:07,840 --> 01:07:10,360
Speaker 1: You've watched millions of these videos of people doing hysterically

1317
01:07:10,400 --> 01:07:12,640
Speaker 1: stupid things with VR helmets on, Well, it's when you

1318
01:07:12,760 --> 01:07:15,640
Speaker 1: look at them when you're not in the same exact

1319
01:07:15,760 --> 01:07:18,720
Speaker 1: and what they're idiots, No, they're not. They're perceiving a

1320
01:07:18,800 --> 01:07:22,960
Speaker 1: different reality than you are. And their model got confused

1321
01:07:23,080 --> 01:07:25,720
Speaker 1: and thought that the table was real because they're so

1322
01:07:25,960 --> 01:07:27,960
Speaker 1: used to seeing a table and thinking the tables really

1323
01:07:28,000 --> 01:07:30,400
Speaker 1: And I still think of VR as kind of blocky

1324
01:07:30,560 --> 01:07:34,280
Speaker 1: and not you know, when the technology accelerates to the

1325
01:07:34,400 --> 01:07:38,120
Speaker 1: whole of deck from Star Trek where the differences and imperceptible,

1326
01:07:38,240 --> 01:07:40,400
Speaker 1: and it's like, then, how do you know what's real

1327
01:07:40,480 --> 01:07:42,120
Speaker 1: and what's not? And I'm not one of these guys

1328
01:07:42,160 --> 01:07:43,880
Speaker 1: who's like, we're all have been a simulation And I

1329
01:07:43,920 --> 01:07:46,280
Speaker 1: don't want to go in that argument. Whatever I think

1330
01:07:46,280 --> 01:07:49,000
Speaker 1: they're entertaining. But my point is from a very practical,

1331
01:07:49,120 --> 01:07:51,920
Speaker 1: real world perspective, let's bring it back to dollars and cents.

1332
01:07:53,080 --> 01:07:55,480
Speaker 1: You have to have the humility of your convictions. Like

1333
01:07:55,560 --> 01:07:58,320
Speaker 1: I look at my Schwab account right now and I say, oh,

1334
01:07:58,400 --> 01:08:00,720
Speaker 1: I get the snapshot of reality what it is. It's

1335
01:08:00,760 --> 01:08:04,200
Speaker 1: in these things right now. For reasons that I had

1336
01:08:04,240 --> 01:08:06,240
Speaker 1: good reasons to put him in the Emerging Markets Fund

1337
01:08:06,320 --> 01:08:09,160
Speaker 1: or whatever, But every day I should be asking myself

1338
01:08:09,200 --> 01:08:12,160
Speaker 1: whether that's still true, because the world changes rather quickly

1339
01:08:12,240 --> 01:08:14,560
Speaker 1: if you haven't noticed. You and I could do this

1340
01:08:15,040 --> 01:08:20,680
Speaker 1: for four hours, and in fact we have um on

1341
01:08:20,800 --> 01:08:24,840
Speaker 1: a canoe on a lake talking about this endlessly, but

1342
01:08:25,120 --> 01:08:28,000
Speaker 1: we only have the studio for another few minutes. So

1343
01:08:28,400 --> 01:08:31,280
Speaker 1: I'm gonna jump to my favorite questions, but I'm gonna

1344
01:08:31,439 --> 01:08:33,479
Speaker 1: mix a few of these up, and they're not going

1345
01:08:33,560 --> 01:08:36,640
Speaker 1: to be the same questions I think, Um, the what

1346
01:08:36,760 --> 01:08:39,200
Speaker 1: are you streaming these days is getting a little long

1347
01:08:39,240 --> 01:08:42,280
Speaker 1: in the tooth if I'm asking about video, So I

1348
01:08:42,400 --> 01:08:45,280
Speaker 1: want to mix it up and ask you what music.

1349
01:08:45,840 --> 01:08:47,800
Speaker 1: I've been on a big music tare lately. One of

1350
01:08:47,840 --> 01:08:49,519
Speaker 1: the it turned out on Twitter one of my most

1351
01:08:49,600 --> 01:08:51,360
Speaker 1: engaged threads I've ever done, is I just heard of

1352
01:08:51,479 --> 01:08:55,000
Speaker 1: post a new song, like every couple of days in there. Um,

1353
01:08:55,160 --> 01:08:57,800
Speaker 1: I'm a big believer that you have to be paying

1354
01:08:57,840 --> 01:08:59,800
Speaker 1: attention to the now if you want to have any

1355
01:09:00,120 --> 01:09:02,960
Speaker 1: of understanding the now. So I try to only listen

1356
01:09:03,040 --> 01:09:05,960
Speaker 1: to new music. Really doesn't mean that I don't occasionally

1357
01:09:06,040 --> 01:09:07,680
Speaker 1: toss on an old Bowie tune that I love or

1358
01:09:07,720 --> 01:09:10,559
Speaker 1: something like that. But four to six hours a day.

1359
01:09:10,840 --> 01:09:13,559
Speaker 1: I'm listening as much as I can to brand new music,

1360
01:09:13,720 --> 01:09:16,719
Speaker 1: and I tend to really listen to basically college radio.

1361
01:09:17,320 --> 01:09:20,320
Speaker 1: Listen to college radio since nine three and I sort

1362
01:09:20,360 --> 01:09:23,360
Speaker 1: of never stopped. Now most of that is intermediated either

1363
01:09:23,520 --> 01:09:27,720
Speaker 1: through sirius xmu on sirius x where find podcasts are

1364
01:09:27,760 --> 01:09:31,479
Speaker 1: held like this one sometimes or various like remember blogs,

1365
01:09:31,720 --> 01:09:34,920
Speaker 1: they're big, big music, big music blogs back in the day,

1366
01:09:35,040 --> 01:09:37,920
Speaker 1: like Gorilla versus Bear Brooklyn Vegan. These guys are all

1367
01:09:37,960 --> 01:09:41,840
Speaker 1: still around um and they're amazing and they're incredible source

1368
01:09:41,920 --> 01:09:43,479
Speaker 1: of new music. And I think that we're in a

1369
01:09:43,640 --> 01:09:46,640
Speaker 1: golden age of independent music. Like in the last two

1370
01:09:46,720 --> 01:09:49,760
Speaker 1: or three years there has been phenomenal There has been

1371
01:09:49,800 --> 01:09:54,960
Speaker 1: a number of articles about streaming has gone classic rock,

1372
01:09:55,520 --> 01:09:59,599
Speaker 1: thirty year old music, and new music has a really

1373
01:09:59,680 --> 01:10:03,839
Speaker 1: different called time being discoverable on all the streaming services.

1374
01:10:04,280 --> 01:10:07,400
Speaker 1: So if you want to discover new music, how do

1375
01:10:07,479 --> 01:10:10,679
Speaker 1: you do that? So Grilla versus Barron brooklyn Vegan dot com,

1376
01:10:10,800 --> 01:10:14,160
Speaker 1: both of them are are blogs where every day, like literally,

1377
01:10:14,240 --> 01:10:16,800
Speaker 1: I think one of them posts here's the twenties six

1378
01:10:16,880 --> 01:10:21,280
Speaker 1: songs that were released today every day, and you can

1379
01:10:21,640 --> 01:10:25,320
Speaker 1: work with new music in the background. It's not terribly distracted. No,

1380
01:10:25,400 --> 01:10:27,160
Speaker 1: I mean I skip stuff I don't like. I don't

1381
01:10:27,160 --> 01:10:29,439
Speaker 1: want to pretend that I just like universally love everything.

1382
01:10:29,760 --> 01:10:32,400
Speaker 1: But you know somebody who's putting up a playlist that's

1383
01:10:32,720 --> 01:10:35,200
Speaker 1: new music every week. You know, there's a top forty

1384
01:10:35,200 --> 01:10:37,760
Speaker 1: alternative charts that I listened to that's new every week

1385
01:10:37,800 --> 01:10:40,559
Speaker 1: based on college radio airplay. And so I'll just put

1386
01:10:40,600 --> 01:10:42,560
Speaker 1: down on repeats the same playlist to just keep it

1387
01:10:42,720 --> 01:10:45,600
Speaker 1: rolling repeat. But it's new stuff every single day. The

1388
01:10:45,640 --> 01:10:48,640
Speaker 1: stuff coming out of particularly like Philadelphia and Chicago in

1389
01:10:48,720 --> 01:10:51,960
Speaker 1: the new music scene, Um, all zoomers, like all kids

1390
01:10:52,000 --> 01:10:55,040
Speaker 1: in their twenties, just amazing stuff. Like a couple bands

1391
01:10:55,200 --> 01:10:57,439
Speaker 1: of note, Um, wet Leg is one that I'm a

1392
01:10:57,520 --> 01:10:59,600
Speaker 1: big fan of, very much a sonic youth kind of

1393
01:10:59,800 --> 01:11:02,679
Speaker 1: ye Horse Squirrel out of Chicago again, a very sonic

1394
01:11:02,760 --> 01:11:06,160
Speaker 1: youth kind of vibe. Philadelphia, there's so many bands down there.

1395
01:11:06,160 --> 01:11:09,559
Speaker 1: Alex G just dropped an incredible album down there. Um

1396
01:11:10,360 --> 01:11:12,720
Speaker 1: you know Dead d e h D and other incredible

1397
01:11:12,760 --> 01:11:16,080
Speaker 1: bands there. Chicago as well. But these little d i

1398
01:11:16,280 --> 01:11:18,880
Speaker 1: y music scenes in in a couple of major cities

1399
01:11:19,439 --> 01:11:23,400
Speaker 1: just unbelievable creative stuff, very a lot of it's very experimental,

1400
01:11:23,560 --> 01:11:27,040
Speaker 1: fourteen minute songs. I'm hearing a lot of alt rock

1401
01:11:27,360 --> 01:11:32,160
Speaker 1: and new synth, but not hip hop that list. I

1402
01:11:32,240 --> 01:11:34,759
Speaker 1: don't listen to a ton of what I would consider

1403
01:11:34,920 --> 01:11:38,280
Speaker 1: mainstream hip hop. Um, it's very distracting if you're trying

1404
01:11:38,320 --> 01:11:41,280
Speaker 1: to read or write exactly. That's that's the big issue.

1405
01:11:41,360 --> 01:11:44,920
Speaker 1: Is that the lyrics, the lyric, that's it's important. Um.

1406
01:11:45,040 --> 01:11:47,320
Speaker 1: I will listen to hip hop generally on headphones, like

1407
01:11:47,720 --> 01:11:50,400
Speaker 1: sitting down in a chair with headphones on to listen,

1408
01:11:50,640 --> 01:11:52,439
Speaker 1: which I don't think that many people do, and I

1409
01:11:52,479 --> 01:11:55,439
Speaker 1: wish more people did. Um. But you know in that

1410
01:11:55,600 --> 01:11:57,479
Speaker 1: space like Run the Jewels, I'm a huge Run the

1411
01:11:57,520 --> 01:11:59,760
Speaker 1: Jewels fan, and that that's more like an indie hip

1412
01:11:59,800 --> 01:12:02,680
Speaker 1: hop artist. UM, so that kind of stuff is a

1413
01:12:02,720 --> 01:12:04,720
Speaker 1: little bit more my jam. I was really into hip

1414
01:12:04,720 --> 01:12:07,880
Speaker 1: hop back in the eighties nineties era, but you know,

1415
01:12:08,040 --> 01:12:09,639
Speaker 1: not not at the level I know some of your

1416
01:12:09,680 --> 01:12:13,280
Speaker 1: boys are at a ridd um yeah, my my hip

1417
01:12:13,360 --> 01:12:16,479
Speaker 1: hop stop with Paul's boutique from the Beat. Yeah, I

1418
01:12:16,520 --> 01:12:19,799
Speaker 1: mean we're both which really which really is the ultimate

1419
01:12:20,080 --> 01:12:23,000
Speaker 1: for you? That's the peace I mean, but the law

1420
01:12:23,200 --> 01:12:25,840
Speaker 1: changed and you couldn't sample the way they I mean

1421
01:12:25,880 --> 01:12:28,320
Speaker 1: they sample beatles and Sergeant pet You couldn't do that

1422
01:12:28,400 --> 01:12:30,800
Speaker 1: today without being sued. Well, the interesting thing is now

1423
01:12:30,920 --> 01:12:32,560
Speaker 1: in the d I Y community, in the in the

1424
01:12:32,600 --> 01:12:36,240
Speaker 1: sort of true indie community, that stuff is really rampant.

1425
01:12:36,360 --> 01:12:39,120
Speaker 1: But it's happening outside of the boundaries of the big

1426
01:12:39,200 --> 01:12:42,160
Speaker 1: record companies. Right. It's literally, you know, one artist in

1427
01:12:42,200 --> 01:12:45,040
Speaker 1: Philadelphia calling up another artist in Chicago saying, Hey, I

1428
01:12:45,120 --> 01:12:46,960
Speaker 1: love the beat you put down on that half made

1429
01:12:47,000 --> 01:12:49,200
Speaker 1: track you dropped on band Camp. Can I sample that

1430
01:12:49,280 --> 01:12:52,240
Speaker 1: in my next thing? And that's happening like crazy, But

1431
01:12:52,320 --> 01:12:54,360
Speaker 1: they're not going back to the old blue note, you know,

1432
01:12:54,760 --> 01:12:56,960
Speaker 1: archives like the Beastie Boys got to not getting too

1433
01:12:57,000 --> 01:12:59,479
Speaker 1: sample a whole lot of love. So it's funny. If

1434
01:12:59,479 --> 01:13:01,679
Speaker 1: I'm writing and I want some music on in the background,

1435
01:13:01,840 --> 01:13:04,519
Speaker 1: I'll go to a weekly show by John Pizzarelli called

1436
01:13:04,600 --> 01:13:09,360
Speaker 1: Radio Deluxe, and it's the classic American songbook from the thirties, forties,

1437
01:13:09,400 --> 01:13:12,640
Speaker 1: fifties and jazz, and I can have that operating in

1438
01:13:12,640 --> 01:13:15,840
Speaker 1: the background and it doesn't interfere with my ability to

1439
01:13:16,280 --> 01:13:21,559
Speaker 1: read or write. The songs are familiar, and it's more music.

1440
01:13:21,760 --> 01:13:25,800
Speaker 1: It's more music than lyrics. So the jazz side of

1441
01:13:25,840 --> 01:13:29,799
Speaker 1: it allows me to function. I think what you're describing

1442
01:13:29,840 --> 01:13:33,040
Speaker 1: would be really hard to work with In terms of

1443
01:13:34,240 --> 01:13:36,760
Speaker 1: writ It totally depends on the kind of work that

1444
01:13:36,840 --> 01:13:39,760
Speaker 1: I'm doing in the moment. If I'm reading academic work,

1445
01:13:39,800 --> 01:13:42,320
Speaker 1: if I'm looking at red legislation, and and you know,

1446
01:13:42,439 --> 01:13:44,800
Speaker 1: reading news and catching up on Twitter, and I can

1447
01:13:44,880 --> 01:13:48,080
Speaker 1: listen to anything. If I'm actively taking the words out

1448
01:13:48,120 --> 01:13:50,040
Speaker 1: of my head and putting them on paper, generally I'm

1449
01:13:50,080 --> 01:13:52,519
Speaker 1: in complete silence. But I tend to compose in my

1450
01:13:52,640 --> 01:13:54,519
Speaker 1: head and then write all at once. So I'll write

1451
01:13:54,560 --> 01:13:56,439
Speaker 1: something in my head for three or four days and

1452
01:13:56,520 --> 01:13:58,759
Speaker 1: then I'll put five thousand words out in thirty minutes.

1453
01:13:58,960 --> 01:14:02,840
Speaker 1: Yeah you me. Morgan Housel says the same thing, that

1454
01:14:03,120 --> 01:14:05,640
Speaker 1: the most important part of writing is the couple of

1455
01:14:05,720 --> 01:14:07,920
Speaker 1: days before you sea. It's usually the most important part

1456
01:14:07,920 --> 01:14:09,599
Speaker 1: of writing to me is the two hour walk at

1457
01:14:09,640 --> 01:14:12,160
Speaker 1: six am. That's the most important part of writing. Then

1458
01:14:12,200 --> 01:14:14,040
Speaker 1: I sit down at eight start writing, and then that's

1459
01:14:14,080 --> 01:14:16,000
Speaker 1: the easy part. My wife makes fun of me. But

1460
01:14:16,200 --> 01:14:18,720
Speaker 1: if I'm giving a presentation that gets written in the

1461
01:14:18,800 --> 01:14:22,240
Speaker 1: shower and she's like, what are you saying in the shower.

1462
01:14:22,280 --> 01:14:24,160
Speaker 1: I'm like, I'm just rehearsing. I have to be moving.

1463
01:14:24,280 --> 01:14:28,560
Speaker 1: For me. It's there's there's a somatic company and that

1464
01:14:28,680 --> 01:14:34,719
Speaker 1: really helps the get the articular. So I normally ask

1465
01:14:34,800 --> 01:14:38,920
Speaker 1: about My second question is about mentors. So I want

1466
01:14:38,920 --> 01:14:41,760
Speaker 1: to ask this question because from Barclays to eat f

1467
01:14:41,880 --> 01:14:46,800
Speaker 1: dot com to vitify, who helped shape your career? Oh

1468
01:14:46,880 --> 01:14:50,680
Speaker 1: my gosh, a million people you know, probably you know,

1469
01:14:50,840 --> 01:14:52,840
Speaker 1: not necessarily people who will know, but like, there was

1470
01:14:53,240 --> 01:14:55,559
Speaker 1: a a guy who was sort of my uncle growing up,

1471
01:14:55,640 --> 01:14:59,680
Speaker 1: who was a Vietnam being on VET mortar surgeon and

1472
01:15:00,320 --> 01:15:01,920
Speaker 1: blown off his hand and he was just sort of

1473
01:15:01,960 --> 01:15:04,040
Speaker 1: growing up in Lenox. He was an uncle of a

1474
01:15:04,120 --> 01:15:08,200
Speaker 1: friend of mine, and he was probably the model that

1475
01:15:08,360 --> 01:15:09,960
Speaker 1: I put in my head when I'm sort of like,

1476
01:15:10,040 --> 01:15:12,040
Speaker 1: what would so and so do you know? It would

1477
01:15:12,080 --> 01:15:15,360
Speaker 1: definitely be Al robertson Um, who was a businessman of

1478
01:15:15,439 --> 01:15:18,439
Speaker 1: some note. But in terms of my direct career, you know,

1479
01:15:18,479 --> 01:15:21,960
Speaker 1: I look back at those early days at UM Wells Fargo, Nico,

1480
01:15:22,240 --> 01:15:25,840
Speaker 1: and for sure I needed to be taught stuff back then.

1481
01:15:26,400 --> 01:15:29,200
Speaker 1: UM and I give Patty Dunn and Fred grauer Um

1482
01:15:29,280 --> 01:15:31,719
Speaker 1: and Blake Grossman a lot of a lot of credit

1483
01:15:32,040 --> 01:15:34,439
Speaker 1: for that because I was very young, and they're all

1484
01:15:34,439 --> 01:15:37,200
Speaker 1: probably ten fifteen years my senior at the time, and

1485
01:15:37,479 --> 01:15:40,439
Speaker 1: they were they were incredibly important. But um, Honestly, if

1486
01:15:40,479 --> 01:15:43,320
Speaker 1: I picked one person, probably Matt Hogan, who's ten years

1487
01:15:43,400 --> 01:15:46,519
Speaker 1: my junior. I've been working with him since nineties six

1488
01:15:46,680 --> 01:15:48,519
Speaker 1: or seven. He was a biotech analyst when I was

1489
01:15:48,600 --> 01:15:51,960
Speaker 1: running money. He and I just have stayed incredibly close

1490
01:15:52,040 --> 01:15:53,840
Speaker 1: over the years. And if there's like one person who

1491
01:15:53,880 --> 01:15:55,680
Speaker 1: I was like, if I had a business decision, like

1492
01:15:56,200 --> 01:16:00,320
Speaker 1: career choice, ethical quandary, something like that is a question,

1493
01:16:00,360 --> 01:16:02,040
Speaker 1: would be the first person in call. He seems to

1494
01:16:02,080 --> 01:16:06,479
Speaker 1: be a very sensible, thoughtful person and not given to

1495
01:16:07,040 --> 01:16:09,479
Speaker 1: you know, he's a main guide. I mean, that's that's

1496
01:16:09,520 --> 01:16:11,719
Speaker 1: what that's how he started in life. He was literally

1497
01:16:11,800 --> 01:16:13,960
Speaker 1: in college, got his guiding certificate in Maine. And we

1498
01:16:14,040 --> 01:16:17,840
Speaker 1: know what those guys are, right, that's the most practical people.

1499
01:16:18,200 --> 01:16:20,639
Speaker 1: God dang planet. How do you survive and not get

1500
01:16:20,720 --> 01:16:23,800
Speaker 1: trampled by an elk exactly or attacked by a bear

1501
01:16:23,920 --> 01:16:27,240
Speaker 1: when you're out hunting moose or bear. It's all about

1502
01:16:27,760 --> 01:16:32,360
Speaker 1: reality there talk about recognizing reality. The penalty there for

1503
01:16:32,479 --> 01:16:35,479
Speaker 1: being wrong is death, right, it's not. My account is

1504
01:16:35,520 --> 01:16:39,439
Speaker 1: down six percent. It's a bunch of bears disembedstment. That's

1505
01:16:39,439 --> 01:16:41,839
Speaker 1: why I'm such a fan of being outside in general, honestly,

1506
01:16:42,040 --> 01:16:43,920
Speaker 1: is because like, if you're three miles in on the

1507
01:16:43,960 --> 01:16:46,639
Speaker 1: Appalachian Trail in the middle of the woods and storm

1508
01:16:46,720 --> 01:16:48,840
Speaker 1: comes up, that's as real as the world guests. Right

1509
01:16:48,880 --> 01:16:50,800
Speaker 1: when you're at a cell phone coverage, standing in your

1510
01:16:50,840 --> 01:16:52,960
Speaker 1: sneakers in the middle of the woods, that's as real

1511
01:16:53,040 --> 01:16:55,719
Speaker 1: as the world gets. There's no bodies, there's no people,

1512
01:16:56,080 --> 01:16:59,599
Speaker 1: there's no stuff, there's no man made anything. That's base

1513
01:16:59,640 --> 01:17:03,000
Speaker 1: state reality. I've had this conversation with people who out

1514
01:17:03,040 --> 01:17:05,400
Speaker 1: on the water on boats. It's like, listen, you can't

1515
01:17:05,400 --> 01:17:07,760
Speaker 1: flip on channel two and get the weather forecast. You

1516
01:17:07,960 --> 01:17:10,679
Speaker 1: need the marine forecast because if it's six ft swells

1517
01:17:11,000 --> 01:17:14,120
Speaker 1: and forty mile on our winds coming up, you need

1518
01:17:14,240 --> 01:17:17,640
Speaker 1: to know that and basically stay in the marina, not

1519
01:17:17,800 --> 01:17:20,240
Speaker 1: go out. Not oh, it's gonna be sunny out today.

1520
01:17:20,400 --> 01:17:23,120
Speaker 1: That's sort of Donning Krueger. Hey, you need to really

1521
01:17:23,240 --> 01:17:26,040
Speaker 1: know what you don't know and not assume you're good

1522
01:17:26,080 --> 01:17:30,880
Speaker 1: at this outdoors. Mother nature is a cruel mistress. There

1523
01:17:31,040 --> 01:17:33,720
Speaker 1: is no fooling around well. And I've run into this

1524
01:17:33,800 --> 01:17:35,160
Speaker 1: all the time. I live in the woods up in

1525
01:17:35,200 --> 01:17:37,760
Speaker 1: the Berkshires in Massachusetts. I run into New Yorkers who

1526
01:17:37,800 --> 01:17:39,599
Speaker 1: come up to go hiking all the time, who were

1527
01:17:39,640 --> 01:17:42,880
Speaker 1: heading off cliffs, like I mean, it's just almost every

1528
01:17:43,000 --> 01:17:45,120
Speaker 1: hike that I go out, and particularly this time of year,

1529
01:17:45,320 --> 01:17:46,880
Speaker 1: it's so easy to get lost if you're not used

1530
01:17:46,880 --> 01:17:49,080
Speaker 1: to walking around in the leaves in the woods. And

1531
01:17:49,400 --> 01:17:51,360
Speaker 1: just just this last weekend, I was walking around just

1532
01:17:51,479 --> 01:17:53,200
Speaker 1: on a trail and I was just like, what the

1533
01:17:53,400 --> 01:17:55,880
Speaker 1: heck are these people doing going over that ridge line.

1534
01:17:55,880 --> 01:17:59,080
Speaker 1: I'm like, hello, don't go that, don't go there. One

1535
01:17:59,120 --> 01:18:01,200
Speaker 1: more step is that do Yeah, they'll figure it out.

1536
01:18:01,320 --> 01:18:04,040
Speaker 1: Let's talk about books. We've mentioned a lot. Give us

1537
01:18:04,080 --> 01:18:06,559
Speaker 1: some of your favorites and what you're reading currently. Oh boy,

1538
01:18:07,280 --> 01:18:09,120
Speaker 1: the most impressive book I've read in the last couple

1539
01:18:09,120 --> 01:18:12,640
Speaker 1: of years is The Matter with Things by Ian McGilchrist,

1540
01:18:12,840 --> 01:18:17,240
Speaker 1: which is fIF pages. It's fifteen under pages of neuroscience

1541
01:18:17,520 --> 01:18:20,599
Speaker 1: and psychology, I would say is probably the best way

1542
01:18:20,640 --> 01:18:22,479
Speaker 1: to describe. How do you attack a book? Like that.

1543
01:18:22,600 --> 01:18:24,880
Speaker 1: You don't sit down and start plowing through. Oh no, So,

1544
01:18:25,040 --> 01:18:26,639
Speaker 1: like we haven't talked about this, how to read a book?

1545
01:18:26,640 --> 01:18:28,840
Speaker 1: You know how to read a book? I think I

1546
01:18:29,000 --> 01:18:30,720
Speaker 1: do because I read a lot of books. No, no,

1547
01:18:30,800 --> 01:18:32,800
Speaker 1: there's a book called how do the book? Okay, so

1548
01:18:32,920 --> 01:18:34,800
Speaker 1: let's talk about So how to read a book is

1549
01:18:34,840 --> 01:18:36,800
Speaker 1: something that I was handed when I was You need

1550
01:18:36,880 --> 01:18:39,439
Speaker 1: a pamphlet years old or something like that, and it

1551
01:18:39,520 --> 01:18:42,080
Speaker 1: basically outlines it's written in the thirties or something like that.

1552
01:18:42,320 --> 01:18:45,360
Speaker 1: It's a very straightforward system for breaking down a book.

1553
01:18:45,800 --> 01:18:48,240
Speaker 1: And it starts with like, okay, you have been handed

1554
01:18:48,320 --> 01:18:50,840
Speaker 1: a book. Here's what you do in the first ten minutes.

1555
01:18:51,200 --> 01:18:53,840
Speaker 1: And it's not for fiction where you're worried about spoiling something.

1556
01:18:53,960 --> 01:18:56,439
Speaker 1: This is really for nonfiction. And there's a process they

1557
01:18:56,520 --> 01:18:58,920
Speaker 1: go through of like, okay, you read the first four

1558
01:18:59,000 --> 01:19:01,519
Speaker 1: paragraphs of the entry production. You go through and you

1559
01:19:01,600 --> 01:19:03,840
Speaker 1: read all of the chapter headings, and you know, usually

1560
01:19:03,840 --> 01:19:06,200
Speaker 1: through the table of contents to try to understand the flow.

1561
01:19:06,520 --> 01:19:08,919
Speaker 1: There's something you don't understand, go read the first paragraph

1562
01:19:09,000 --> 01:19:11,280
Speaker 1: of that chapter so that you now understand the flow.

1563
01:19:11,760 --> 01:19:15,040
Speaker 1: Then go read the introduction to the concluding chapter, and

1564
01:19:15,160 --> 01:19:17,560
Speaker 1: by that point you should understand does this book have

1565
01:19:17,720 --> 01:19:20,960
Speaker 1: anything in it for me? Right? And in the in

1566
01:19:21,200 --> 01:19:24,720
Speaker 1: that modality, you probably reject half the books you open, right,

1567
01:19:24,760 --> 01:19:25,920
Speaker 1: you can. You can do that in the in the

1568
01:19:25,960 --> 01:19:29,360
Speaker 1: bookstore literally, right that what you're just it's funny you

1569
01:19:29,400 --> 01:19:31,519
Speaker 1: said that, because what you're describing used to be my

1570
01:19:31,600 --> 01:19:33,960
Speaker 1: bookstore route exactly. So that's at that would be a

1571
01:19:34,080 --> 01:19:38,080
Speaker 1: level one read. A level to read is with whatever

1572
01:19:38,200 --> 01:19:42,160
Speaker 1: speed you want, you consume the available content of the

1573
01:19:42,240 --> 01:19:46,080
Speaker 1: book itself. So that's literally just reading the book. Now.

1574
01:19:46,800 --> 01:19:49,400
Speaker 1: I tend to do that very quickly. That kind of

1575
01:19:49,479 --> 01:19:52,000
Speaker 1: reading I can be very very quick with. And that's

1576
01:19:52,000 --> 01:19:54,680
Speaker 1: a level to read. I don't mean speed reading. I

1577
01:19:54,760 --> 01:19:59,360
Speaker 1: mean just turn pages, understand what, understand what's important. You're

1578
01:19:59,360 --> 01:20:01,400
Speaker 1: not going to read every single word on the page.

1579
01:20:01,439 --> 01:20:03,960
Speaker 1: We're gonna get the gist of every major point made

1580
01:20:04,000 --> 01:20:06,160
Speaker 1: in the book. Right, You're doing your own spot. Unless

1581
01:20:06,240 --> 01:20:09,400
Speaker 1: it's a Bill Bryson or an Ed Chancelor, somebody who's

1582
01:20:09,479 --> 01:20:12,120
Speaker 1: writing is dense and deep and you really need to

1583
01:20:12,880 --> 01:20:16,200
Speaker 1: think about each sentence in each Yeah. Well, so even

1584
01:20:16,360 --> 01:20:18,040
Speaker 1: in the modality of how to read a book, a

1585
01:20:18,160 --> 01:20:20,320
Speaker 1: level to read even that you would let skip through

1586
01:20:20,320 --> 01:20:22,560
Speaker 1: a little bit, because the objective of a level to

1587
01:20:22,760 --> 01:20:26,040
Speaker 1: read is to understand everything that the book has to

1588
01:20:26,160 --> 01:20:29,040
Speaker 1: offer you, right, so like, what are all its key points?

1589
01:20:29,120 --> 01:20:32,160
Speaker 1: Where it's you know, sailing, it's observations, where it's facts

1590
01:20:32,240 --> 01:20:35,160
Speaker 1: that you haven't gotten A level three read, which I

1591
01:20:35,160 --> 01:20:37,400
Speaker 1: can say I've probably done for ten books in my life.

1592
01:20:37,880 --> 01:20:41,080
Speaker 1: Is when you go through and every concept you don't understand,

1593
01:20:41,120 --> 01:20:43,160
Speaker 1: you go down the rabbit hole. They mentioned a book

1594
01:20:43,200 --> 01:20:46,880
Speaker 1: that you haven't read, you go read that book, and

1595
01:20:47,320 --> 01:20:49,800
Speaker 1: that's a very rare thing to do there. So on

1596
01:20:49,880 --> 01:20:53,280
Speaker 1: a book that's this big, the honest truth is you start.

1597
01:20:53,479 --> 01:20:55,759
Speaker 1: I start at level one. Now. My level one read

1598
01:20:55,920 --> 01:20:57,720
Speaker 1: on the matter of Matter with Things probably took me

1599
01:20:57,760 --> 01:21:01,160
Speaker 1: a week because it's so just to go through and

1600
01:21:01,280 --> 01:21:04,600
Speaker 1: read the opening paragraphs of each chapter and read the

1601
01:21:04,640 --> 01:21:06,640
Speaker 1: conclusions and be like, nope, I didn't get that. I

1602
01:21:06,720 --> 01:21:09,040
Speaker 1: have to go back without actually reading the book. It

1603
01:21:09,120 --> 01:21:11,960
Speaker 1: probably took me a week. Then Tom Morrigan from KCP

1604
01:21:12,120 --> 01:21:15,240
Speaker 1: and I spent I want to say, three months. Tom

1605
01:21:15,320 --> 01:21:18,599
Speaker 1: has by the way of fascinating Twitter feed. He's phenomenal. Yeah,

1606
01:21:19,080 --> 01:21:20,800
Speaker 1: and he's way out there on this stuff. He's my

1607
01:21:21,000 --> 01:21:24,360
Speaker 1: my sirpa on this sort of phenomenology and consciousness end

1608
01:21:24,400 --> 01:21:26,880
Speaker 1: of things. But then we we sort of we're going

1609
01:21:26,960 --> 01:21:29,160
Speaker 1: through it together, which helped a lot um and we

1610
01:21:29,200 --> 01:21:31,160
Speaker 1: would bounce ideas back and forth with each other and

1611
01:21:31,240 --> 01:21:33,600
Speaker 1: compare notes with where we were. And I did a

1612
01:21:33,760 --> 01:21:36,200
Speaker 1: full level to read that book over about a three

1613
01:21:36,320 --> 01:21:39,479
Speaker 1: month window, reading it every day. Give me one more book,

1614
01:21:39,479 --> 01:21:43,800
Speaker 1: because we've talked about so many already. Uh, how about this,

1615
01:21:43,880 --> 01:21:46,240
Speaker 1: I'll go with a comic book, trans Metropolitan by Warren

1616
01:21:46,320 --> 01:21:49,080
Speaker 1: ellis my one of my favorite comic books. Could not

1617
01:21:49,200 --> 01:21:52,639
Speaker 1: be more relevant for the modern world right now. About

1618
01:21:52,680 --> 01:21:56,080
Speaker 1: a journalist named Spider Jerusalem covering the apocalypse in a

1619
01:21:56,160 --> 01:21:59,360
Speaker 1: major city, and it feels like it was written about

1620
01:21:59,479 --> 01:22:05,080
Speaker 1: today today. Interesting. Our final two questions, what sort of

1621
01:22:05,120 --> 01:22:07,840
Speaker 1: advice would you give to a college grad who thinks

1622
01:22:07,880 --> 01:22:12,839
Speaker 1: they want to be a financial futurist? We'll probably inventive

1623
01:22:12,880 --> 01:22:14,599
Speaker 1: better title. But to do like the kind of work

1624
01:22:14,640 --> 01:22:16,200
Speaker 1: that I'm doing, the biggest advice I have is to

1625
01:22:16,240 --> 01:22:19,720
Speaker 1: be curious, right, never allow a good rabbit hole to

1626
01:22:19,840 --> 01:22:25,040
Speaker 1: go unexplored. We've had conversations about that phrase has come up.

1627
01:22:25,439 --> 01:22:28,800
Speaker 1: How much time do you spend down various rabbit holes.

1628
01:22:28,880 --> 01:22:31,680
Speaker 1: I mean, I mean pretty much any time that I'm

1629
01:22:31,720 --> 01:22:34,080
Speaker 1: not doing something else, I'm like if I if I

1630
01:22:34,160 --> 01:22:37,800
Speaker 1: have something in front of me and i'm reading the time,

1631
01:22:37,920 --> 01:22:40,519
Speaker 1: it's something that is way deeper than it needs to be,

1632
01:22:40,600 --> 01:22:43,280
Speaker 1: because I really want to understand it at a core level. Okay,

1633
01:22:43,360 --> 01:22:47,160
Speaker 1: so let me fast forward. I actually by the time

1634
01:22:47,240 --> 01:22:49,200
Speaker 1: this comes out, this will be old news. But I

1635
01:22:49,280 --> 01:22:52,760
Speaker 1: did a blog post about how the FED is causing inflation.

1636
01:22:53,520 --> 01:22:58,360
Speaker 1: The FED, by raising rates, is causing the CPI inflation

1637
01:22:58,520 --> 01:23:02,479
Speaker 1: prints to be higher because the crazy way BLS measures

1638
01:23:02,560 --> 01:23:05,600
Speaker 1: the cost of shelter. And the only way I was

1639
01:23:05,680 --> 01:23:07,840
Speaker 1: able to put that together, and I'm bringing this up

1640
01:23:07,840 --> 01:23:11,040
Speaker 1: because I know you'll appreciate it is because I lived

1641
01:23:11,200 --> 01:23:14,160
Speaker 1: in that rabbit hole during the two thousands. But I

1642
01:23:14,360 --> 01:23:19,960
Speaker 1: was arguing BLS is under reporting inflation because of we've

1643
01:23:20,000 --> 01:23:23,000
Speaker 1: had that conversation. But that was in the two thousands,

1644
01:23:23,360 --> 01:23:26,360
Speaker 1: so the FEED had taken rates down too quickly, too low,

1645
01:23:27,040 --> 01:23:29,960
Speaker 1: and that led to a spike in the cost of shelter,

1646
01:23:30,400 --> 01:23:34,759
Speaker 1: which the BLS reports the inverse of. Fast forward twenty

1647
01:23:34,840 --> 01:23:39,320
Speaker 1: years years now, the FT is raising rates and that

1648
01:23:39,600 --> 01:23:42,360
Speaker 1: leads the b L S c P I to over

1649
01:23:42,520 --> 01:23:46,840
Speaker 1: report inflation because the way they measure owners equivalent rent

1650
01:23:46,880 --> 01:23:49,840
Speaker 1: because for many people a home is an asset, but

1651
01:23:49,920 --> 01:23:51,800
Speaker 1: if you're a renter and it's going up, how do

1652
01:23:51,880 --> 01:23:55,000
Speaker 1: you measure that? And it's not this grand conspiracy, it's

1653
01:23:55,080 --> 01:23:59,760
Speaker 1: just a complex modeling problem, which, as you've described, we

1654
01:24:00,000 --> 01:24:02,759
Speaker 1: it wrong. Yeah, and I think that those are endemic.

1655
01:24:02,840 --> 01:24:05,400
Speaker 1: They're everywhere. I mean during the game stop run up,

1656
01:24:05,439 --> 01:24:07,080
Speaker 1: people were talking about, well we had to make cap

1657
01:24:07,280 --> 01:24:09,040
Speaker 1: you know, why did DTC have to have a capital

1658
01:24:09,120 --> 01:24:11,280
Speaker 1: call in Citadel? And this must be somebody buying Ken

1659
01:24:11,320 --> 01:24:15,640
Speaker 1: Griffin's damn. And it's like, again, they're so easy to

1660
01:24:16,160 --> 01:24:19,000
Speaker 1: disprove that, but only if you've already spent a year

1661
01:24:19,080 --> 01:24:22,479
Speaker 1: down the rabbit hole of understanding capital requirements at settlement Bureau.

1662
01:24:22,600 --> 01:24:24,960
Speaker 1: We all we all talk about our priors, but if

1663
01:24:25,000 --> 01:24:27,479
Speaker 1: your priors were down the rabbit hole, then you have

1664
01:24:27,640 --> 01:24:31,519
Speaker 1: a frame of reference to understand these complex endemically with

1665
01:24:31,680 --> 01:24:34,200
Speaker 1: the with the enormous caveat that everything you knew about

1666
01:24:34,240 --> 01:24:40,759
Speaker 1: financial markets now and so first in in the post,

1667
01:24:40,960 --> 01:24:45,680
Speaker 1: I cite something I had quoted from from I think

1668
01:24:45,720 --> 01:24:47,920
Speaker 1: it was a Cleveland Fed or Atlanta Fed. Look at

1669
01:24:47,920 --> 01:24:51,200
Speaker 1: o we are. And then fortunately my my buddy and

1670
01:24:51,320 --> 01:24:54,280
Speaker 1: Victus said, hey, you know that the Federal Reserve and

1671
01:24:54,439 --> 01:24:56,920
Speaker 1: the maybe it was the Cleveland FED just did a

1672
01:24:57,000 --> 01:24:59,479
Speaker 1: piece on this like three days ago. So I was

1673
01:24:59,560 --> 01:25:02,639
Speaker 1: able to site like, oh, and here's the latest change

1674
01:25:03,160 --> 01:25:06,360
Speaker 1: that they're changing the they're the FED. Everybody is aware

1675
01:25:06,400 --> 01:25:09,120
Speaker 1: that this is a problem, that they're changing the way

1676
01:25:09,200 --> 01:25:12,840
Speaker 1: they measure this. But this all goes back to we're wrong,

1677
01:25:12,960 --> 01:25:14,840
Speaker 1: the models are wrong. We have have to get it right,

1678
01:25:14,880 --> 01:25:17,760
Speaker 1: all right. Final question, what is it that you know

1679
01:25:17,880 --> 01:25:21,880
Speaker 1: about the world of investing today or the world today

1680
01:25:22,080 --> 01:25:24,519
Speaker 1: that you wish you knew twenty five years or so

1681
01:25:24,840 --> 01:25:27,600
Speaker 1: ago when you were first starting out. Oh well, I

1682
01:25:27,640 --> 01:25:29,560
Speaker 1: mean it's a beating a dead horse here, but that

1683
01:25:29,800 --> 01:25:32,840
Speaker 1: I was wrong and whatever the question is, the answer

1684
01:25:32,960 --> 01:25:36,080
Speaker 1: is I was wrong, right that that yeah, that that

1685
01:25:36,680 --> 01:25:39,840
Speaker 1: fundamental shift in my perception, which really only happened in

1686
01:25:39,840 --> 01:25:41,800
Speaker 1: the last three or four years. The pandemic helped a

1687
01:25:41,880 --> 01:25:46,760
Speaker 1: lot to recognize the inherent fallibility of human experience and

1688
01:25:46,880 --> 01:25:51,240
Speaker 1: approach every conversation with the humility that that implies. If

1689
01:25:51,280 --> 01:25:53,519
Speaker 1: I could go back and beat that into my year

1690
01:25:53,560 --> 01:25:56,360
Speaker 1: old self I would do in a heartbeat. Fantastic, Dave,

1691
01:25:56,439 --> 01:25:59,120
Speaker 1: Thank you being so generous with your time. We have

1692
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Speaker 1: been speaking with Dave Noddig, financial futurists for Vitify. If

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Speaker 1: you enjoy this conversation, well, be sure and check out

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Speaker 1: any of the previous four hundred and forty we've done

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Speaker 1: over the past eight years. You can find those at iTunes,

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Speaker 1: Spotify and now YouTube, or wherever you feed your podcast fix.

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Speaker 1: We love your comments, feedback in suggestions right to us

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Speaker 1: at m IB podcast at Bloomberg dot net. Follow me

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Speaker 1: on Twitter at rid Halts. You can sign up from

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Speaker 1: my daily reading list at dhults dot com. I would

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Speaker 1: be remiss if I did not thank the crack team

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Speaker 1: who helps put these conversations together each week. Sarah Livesey

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Speaker 1: is my audio engineer. A Tick of val Bron is

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01:26:41,080 --> 01:26:44,920
Speaker 1: my project manager. Paris Wold is our producer. Sean Russo

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01:26:45,320 --> 01:26:48,800
Speaker 1: is my head of research. I'm Barry Rid Halts. You've

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Speaker 1: been listening to Masters in Business on Bloomberg Radio.