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Speaker 1: This is Masters in Business with Barry Ridholts on Bloomberg Radio.

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

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Speaker 1: Matt Hogan is a friend who I know through his

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Speaker 1: work at inside e t F S as well as

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Speaker 1: the inside et F H Big Conference. I also know

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Speaker 1: him from his days running e t F dot com

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Speaker 1: and he more recently joined a crypto fund where they

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Speaker 1: are producing the very first index of crypto coins, which

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Speaker 1: is quite fascinating. If you're at all interested in anything

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Speaker 1: from the gamut of e t f S to Bitcoin

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Speaker 1: and quite bluntly bitcoins held in e t f S

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Speaker 1: and everything in between, then this is the conversation that's

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Speaker 1: gonna be for you. There are few people who are

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Speaker 1: more knowledgeable about the entire process of creating, managing, mark

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Speaker 1: ing UH, and administrating e t fs UH than Matt.

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Speaker 1: And taking that skill set and bringing it to a

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Speaker 1: crypto firm where he's basically going to try and do

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Speaker 1: for various crypto coins and crypto assets what he helped

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Speaker 1: do with E t F S UH is really quite

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Speaker 1: a fascinating conversation. I think those folks who are interested

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Speaker 1: in this space will find it endlessly informative and entertaining,

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Speaker 1: So with no further ado, my conversation with Matt Hogan.

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Speaker 1: My special guest this week is Matt Hogan. He is

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Speaker 1: the global head of research at bit Wise Asset Management.

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Speaker 1: Prior to that, he was the chairman and pretty much

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Speaker 1: chief cook and bottle washer at u e t F

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Speaker 1: dot Com that was purchased by Informa and the Inside

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Speaker 1: et F conference is the biggest ETF conference in the world.

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Speaker 1: You're you're still chairman of that event. I'm still chairman

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Speaker 1: of that event. Yeah, I love it very much. Bit

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Speaker 1: Wise Asset Management is the creator of the world's first

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Speaker 1: cryptocurrency index fund. Matt Hogan, Welcome to Bloomberg. Thanks for

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Speaker 1: having me, Barry. I've been looking forward to this. I

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Speaker 1: am a little bit of a bitcoin skeptic, but I'm

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Speaker 1: open minded because I'm somewhat fascinated by the underlying blockchain technology,

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Speaker 1: and you know, I'm interested in anything related to either

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Speaker 1: E t F or indexes. So let's let's jump right

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Speaker 1: into this. And why don't we start with your work

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Speaker 1: at et F dot com right? What did you do there? So?

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Speaker 1: I I started as a freelance reporter for its predecessor,

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Speaker 1: which was index universe and over that we left the

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Speaker 1: worst u r O in the world with Index Universe

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Speaker 1: and not a winner. No. E t F dot Com

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Speaker 1: is just marginally better. Oh really, I would think that's

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Speaker 1: a no brainer. I think it was a no brain.

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Speaker 1: So we switched to et F dot Com. I eventually

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Speaker 1: became the CEO of the business. Some of the things

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Speaker 1: I'm most proud of that we did there. We built

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Speaker 1: the largest et F conference in the world. Inside e

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Speaker 1: t F s we built the first e t F

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Speaker 1: classification and ratings system. It's hard to imagine an e

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Speaker 1: t F land that eight or nine years ago, things

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Speaker 1: like tracking error were not available to most. That's just

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Speaker 1: that's just entry level stuff. Is entry level stuff, but

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Speaker 1: it didn't exist. No one had even gone through the

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Speaker 1: perspectus is to make sure that they were actually tracking

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Speaker 1: total return indexes. Uh. It was a mess. So we

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Speaker 1: built the first classification and rating system, which we subsequently sold.

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Speaker 1: The fact sets now powers And that's how our mutual

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Speaker 1: friend David Neated previously ended up at a fact set

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Speaker 1: and then didn't they get bought by was it c Bolt?

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Speaker 1: So so we sold our business in three separate sales.

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Speaker 1: We sold our data business to fact Set, our events

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Speaker 1: business to inform A, and our media business. E t

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Speaker 1: F dot Com the property to CBOE which is now

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Speaker 1: BATS where we sold it to BATS which is now

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Speaker 1: cbo E. To confuse matters more, we sold Dave with

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Speaker 1: the data business to facts Set, and then he left

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Speaker 1: facts Set to go to e t F dot Com

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Speaker 1: at cbo E BATS. So it's it's virtually impossible to

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Speaker 1: keep straight here. Now, Well, that explains my my lack

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Speaker 1: of understanding. So so your CEO of e t F

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Speaker 1: dot Com at the start of the I guess, for

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Speaker 1: lack of a better word, the e t F era,

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Speaker 1: what was the industry like you mentioned some of the

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Speaker 1: real basic metrics that everybody takes for granted with mutual

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Speaker 1: funds that didn't exist. For people have to remember that

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Speaker 1: early in the days of e TF no one believed

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Speaker 1: in them, no one trusted them, and no one understood them.

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Speaker 1: There were huge myths about e t F liquidity. People

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Speaker 1: didn't know what a creation redemption was, and people have

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Speaker 1: no way to even answer basic questions like what are

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Speaker 1: all the emerging market ETFs that didn't exist? Uh, no

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Speaker 1: way to answer how well does this et F track

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Speaker 1: it's index. So we spend a huge amount of time.

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Speaker 1: I must have explained creation redemption. That's the thing that

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Speaker 1: I think most of the investing public understands. The least Yes,

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Speaker 1: give us a thirty second version. What is creation and

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Speaker 1: redemption of the underlying in an et sure? So let

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Speaker 1: me start with mutual funds, because people understand them better.

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Speaker 1: When you invest money in a mutual fund, you send

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Speaker 1: them cash, and then the mutual fund managers sits on

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Speaker 1: that cash overnight. Then they come into work and they

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Speaker 1: pick which stocks to buy, and they buy stocks with

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Speaker 1: that cash, and usually they're buying their existing model. Here's

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Speaker 1: what our core holdings look like. Oh we've gotten this

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Speaker 1: much inflow. Great, go out and buy pro rata everything

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Speaker 1: we already own in proportion. And then when you want

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Speaker 1: your money back, the exact same thing happens in reverse.

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Speaker 1: You say I want my hundred thousand dollars back, They

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Speaker 1: sell a hundred thousand dollars of whatever stocks are out

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Speaker 1: of favor, and they send you your ash. And that's

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Speaker 1: that's a creation and a redemption in the mutual fund.

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Speaker 1: But you're doing it in an e t F. When

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Speaker 1: you buy an e t F, you just buy it

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Speaker 1: like you buy shares of IBM. I buy my shares

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Speaker 1: like a closed funds, just on the exchange, right. I

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Speaker 1: might buy a hundred shares of SPY and you might

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Speaker 1: be selling it, and we'll get matched at the exchange level.

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Speaker 1: What happens with an e t F is instead of

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Speaker 1: the e t F going out and buying the securities,

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Speaker 1: it publishes a list of what securities it wants to buy,

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Speaker 1: and a big institutional investor called an authorized participant goes

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Speaker 1: out and acquires that list of securities. Say it's the

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Speaker 1: SMP five hundred. They buy all five hundred securities, and

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Speaker 1: then they send all five hundred securities to the e

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Speaker 1: t F company in exchange for the same value of

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Speaker 1: shares in the e t F, which they can just

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Speaker 1: send sell on the broke on the on the markets.

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Speaker 1: Same thing happens in reverse. When these aps want to

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Speaker 1: redeem shares, they say, we want to we have fifty

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Speaker 1: thousand shares of the e t F. They send the

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Speaker 1: fifty thou shares to the e t F company, and

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Speaker 1: the e t F company sends them the equivalent dollar

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Speaker 1: amount in stocks, which they can then out that You

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Speaker 1: may wonder why does that matter? And it matters for

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Speaker 1: a bunch of different reasons. I'll give you two. So first,

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Speaker 1: think about when you send money to a mutual fund company.

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Speaker 1: They have to hire people who go into the market,

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Speaker 1: decide what to buy, trade. It costs money that raises

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Speaker 1: the fees. Uh. The other reason it matters is when

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Speaker 1: you redeem from a mutual fund, they have to sell

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Speaker 1: actual stocks. If those stocks have appreciated in value, they

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Speaker 1: realize capital gains and the fund. The horrible thing about

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Speaker 1: the mutual fund industry is at the end of the year,

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Speaker 1: everyone who still owns those funds has to pay taxes

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Speaker 1: based on the fact that you left. Someone else sold

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Speaker 1: generated a capital gain tax event, and the people who

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Speaker 1: didn't sell are on the hook are left holding the bag.

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Speaker 1: So I always look at ETFs as having to really

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Speaker 1: um attractive qualities. One is there if you decide to

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Speaker 1: sell your ETF and I don't, I don't get stuck

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Speaker 1: with your capital gains. And second that whole um create

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Speaker 1: and redemption process means as long as the underlying holdings

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Speaker 1: have liquidly there's never a liquidly problem with the broader

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Speaker 1: SMP like E t F or Am I wrong? No,

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Speaker 1: you are absolutely right. I actually think if the e

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Speaker 1: t F came first, the SEC would never approved a

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Speaker 1: mutual fund structure. Right, you're gonna make people share in

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Speaker 1: the tax event. That's insane socialism for the tax for investors. Yeah,

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Speaker 1: it's totally It's totally right. And you're absolutely right about

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Speaker 1: the liquidity as long as the underlying as liquid. The

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Speaker 1: e t F is liquid, which is why and people

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Speaker 1: get this wrong. Uh, the only bond funds that have

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Speaker 1: blown up have been bond mutual funds because they have

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Speaker 1: to redeem out and so liquid. Very often it's only

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Speaker 1: the top third or top half of the bonds, and

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Speaker 1: a lot of big indexes trade regularly. Are are deep

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Speaker 1: and wide and have a lot, but by the time

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Speaker 1: you get to the thousandth holding, it trades every Tuesday

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Speaker 1: by appointment. Not a lot of liquid. Good luck. People

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Speaker 1: worry about bond e t f s blowing up. What

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Speaker 1: they should be worried about is in a bond market crisis,

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Speaker 1: corporate bond mutual funds blowing up and having real issues.

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Speaker 1: I think that that could happen. So I have to

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Speaker 1: ask the obvious question. E t f s were the

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Speaker 1: hottest area in the markets what made you decide to

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Speaker 1: say I'm gonna I'm gonna leave this behind and make

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Speaker 1: a leap into the craziness that is crypto because you

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Speaker 1: jumped into it right in the middle of the Mayhem. Yeah. Yeah,

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Speaker 1: although although it was the plan to jump into it

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Speaker 1: started earlier than that, But that's absolutely true. I would

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Speaker 1: say there are three things, Um, you know, when I

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Speaker 1: got into E t F s UH, they weren't well

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Speaker 1: understood UH. And they weren't widely adopted, and they were

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Speaker 1: still a new and emerging industry. And the only skill

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Speaker 1: I have, to the extent I have a skill, is

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Speaker 1: the ability to explain complex things in a simple way. UH.

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Speaker 1: And I felt like a lot of what I wanted

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Speaker 1: to do in E t F S had been accomplished. Right,

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Speaker 1: I had helped create the first e t F rating system,

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Speaker 1: I'd have to create the first et F classification system. UH.

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Speaker 1: I had done some small part to move ETFs into

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Speaker 1: the mainstream, and now they are the dominant UH way

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Speaker 1: people get exposure to the markets. So I felt most

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Speaker 1: of what I had done, what I wanted to do,

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Speaker 1: had been achieved, and I went looking for the next

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Speaker 1: area of UH disruptive opportunity where I thought the quality

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Speaker 1: of information was poor, I actually ended up with two.

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Speaker 1: I ended up with with crypto and with options strategies,

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Speaker 1: both of which I think are potentially very important, and

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Speaker 1: both of which are really poorly understood by most investors.

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Speaker 1: But this unique crypto opportunity to be involved in the

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Speaker 1: first crypto index fund appealed to my inner indexing nerd.

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Speaker 1: So is there are there are you seeing parallels between

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Speaker 1: how crypto is being perceived by the investing public and

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Speaker 1: e T F And said, do you remember when people

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Speaker 1: talked about e t f s as weapons of mass destruction? Sure?

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Speaker 1: Do you remember when people uh wouldn't didn't think e

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Speaker 1: t s would ever? I'm out too much. I think

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Speaker 1: they were the I Shares franchise was sold for a

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Speaker 1: dollar from Morgan Stanley to b G. I right, it's

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Speaker 1: it's um Uh, it's nice, Yeah exactly. I think someone

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Speaker 1: called the Louisiana purchase of Yeah. I hope someone still

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Speaker 1: has that dollar the wall somewhere. And but these were

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Speaker 1: not uh people didn't think e t s would amount

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Speaker 1: too much? Right, They were a last ditch effort to

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Speaker 1: save the AMMAX and create trading volume. There people didn't

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Speaker 1: realize how good they were. And the same thing as

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Speaker 1: crypto people are reflexively dismissive of crypto. H most people

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Speaker 1: have given it about two and a half minutes of thought.

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Speaker 1: If you give it two and a half minutes of thought,

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Speaker 1: you think it's fairy unicorn money on the internet. And

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Speaker 1: it takes it takes hours and days of really analyzing

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Speaker 1: it to see where it might and may have value.

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Speaker 1: So I see a lot of parallels so to me,

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Speaker 1: and I know this is almost a cliche at this point.

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Speaker 1: Blockchain is so obviously useful in so many applications that

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Speaker 1: we've only begun to think about. It's that the bitcoins

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Speaker 1: and the ethereums and go down. There's hundreds of coins.

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Speaker 1: It seems to be that there's a lot of speculative

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Speaker 1: excess in the space. And I think that's what makes

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Speaker 1: it so easy for people to you know, just yeah, okay, bitcoin, bitcoin,

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Speaker 1: Bitcoin is the next you know, dot com. Uh, And

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Speaker 1: it's the parallels of they're also I think those parallels

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Speaker 1: are accurate. Uh. I think it is the next dot com.

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Speaker 1: But remember, um, the dot com bubble created uh pets

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Speaker 1: dot com. But it also created Amazon. So I think

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Speaker 1: there are two thousand cryptocurrencies out there of them are

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Speaker 1: useless and we'll die a painful death. The sooner that happens,

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Speaker 1: the better. There's also a lot of bad activity, bubble

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Speaker 1: related activity that's getting cleared up. But from those ashes,

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Speaker 1: if you call them ashes, I mean cryptos up over

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Speaker 1: the last two years, that's ashes. They're nice ashes. But

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Speaker 1: from those ashes, I think will emerge import and things,

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Speaker 1: just like from the dot com ashes emerge Amazon, Google, Facebook,

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Speaker 1: et cetera. No no doubt about that. I'm gonna throw

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Speaker 1: a quote at you, and I want you to explain it.

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Speaker 1: You you said, you think, um, we need crypto to

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Speaker 1: cut out the rent seeking middleman that creates attacks on society.

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Speaker 1: Now we're all familiar with rentiers, or at least we

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Speaker 1: should be, but give us a little a little details.

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Speaker 1: So crypto is the first time we've been able to

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Speaker 1: engage in financial transactions between people who don't know each

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Speaker 1: other without someone in the middle to verify those transactions.

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Speaker 1: That's all that blockchain technology does. It allows you to

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Speaker 1: replace someone in the middle verifying transactions like visa or

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Speaker 1: like your bank and your friends bank with software that

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Speaker 1: does it automatically. And for free UH and so so

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Speaker 1: much of the financial industry UH is at some level

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Speaker 1: a middleman, like an escrow agent that verifies trust acrosses

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Speaker 1: transact and crypto has shown that you don't need that,

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Speaker 1: and that's a big deal. There's a huge deal. There's

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Speaker 1: a huge deal. Now we're miles away, we're years away.

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Speaker 1: It's an early stage technology. We're years away. But already

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Speaker 1: you can go to IBM and you can wire money

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Speaker 1: using a crypto asset internationally for much cheaper than you

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Speaker 1: can send it through a traditional banking system. So it

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Speaker 1: is going to get here, but it is early, quite

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Speaker 1: quite fascinating. So let's talk about some real world applications

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Speaker 1: for UM. I think we want to separate the coins

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Speaker 1: from the underlying software from blockchain and that technology. But

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Speaker 1: you're focusing on the entire value chain from start to finish.

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Speaker 1: So so let's start with blockchain a little bit. Sure, UM,

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Speaker 1: what are some of the near future, not fifty years

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Speaker 1: future applications of blockchains? Yeah, for what's worth, I'm way

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Speaker 1: more bullish on crypto assets than I am on blockchain. Really,

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Speaker 1: that's the opposite of what so many people. It's almost

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Speaker 1: a cliche to say, yeah, I'm skeptical about bitcoin, but

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Speaker 1: this blockchain is is if you remember the early days

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Speaker 1: of the Internet, the really early days when there were

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Speaker 1: books and you look up a website and type it in,

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Speaker 1: everyone was really excited about corporate intranets. They're like, oh,

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Speaker 1: it would be great to send files to Joe and

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Speaker 1: accounting without having to walk over people thought exactly no,

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Speaker 1: but people thought corporate internets were the thing, the thing.

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Speaker 1: The The analogy between an open internet, which people are like,

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Speaker 1: no one will trust that. Uh, it's the same between

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Speaker 1: private block chains and public blockchains. Public block chains that

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Speaker 1: are open and accessible by anyone need a crypto asset

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Speaker 1: to function, and I think over the long term, public, open,

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Speaker 1: accessible UH technologies tend to win. Now, private block chains

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Speaker 1: are important. I think they could revolutionized settlement. One of

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Speaker 1: the things black chain does really well is settled transactions

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Speaker 1: much faster. I think they could. Uh. They can memorials,

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Speaker 1: morales data. I think they let you trace back transactions.

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Speaker 1: But I think they are actually modest improvements uh. And

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Speaker 1: I think the massive improvement is this displacement of a

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Speaker 1: trusted mentalman that public box chains allow. Huh. So one

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Speaker 1: of one of my favorite examples is during the financial crisis,

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Speaker 1: when we were securitizing mortgages by the millions, slicing and

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Speaker 1: dicing them and then resecuritizing them and then selling them.

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Speaker 1: That undoing that Gordian not became almost impossible, and banks

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Speaker 1: ended up losing track of which bank owned which mortgage

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Speaker 1: that went to which house. And there were actual stories

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Speaker 1: of something that should be illegal impossibility, people without a

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Speaker 1: mortgage going on vacation and coming home to find that

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Speaker 1: they were foreclosed on. All their stuff is out in

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Speaker 1: the street, there's an armed sign on their door. How

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Speaker 1: has I foreclosed on? I bought this house for cash

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Speaker 1: that that should be impossible, and then banks foreclosing that

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Speaker 1: didn't own the mortgage, foreclosing on somebody. And the example

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Speaker 1: I like to use is if blockchain was used as

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Speaker 1: a methodology to track where each of those mortgages went,

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Speaker 1: it wouldn't have been that same impossible to untangle mess.

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Speaker 1: You could have traced exactly who owned which laggage and

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Speaker 1: who own which property. As a fail safe, there would

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Speaker 1: be no headaches at all. It's it's it's it's amazing,

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Speaker 1: and it's amazing that it exists. We all buy something

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Speaker 1: called title insurance UH to guard against the risk that somehow,

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Speaker 1: this this most important asset we've ever bought, it is

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Speaker 1: not actually ours. UM. It is incredible that that still

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Speaker 1: exists in today's society. I think that example is a

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Speaker 1: great one UH, and there are many like that. So

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Speaker 1: let's talk about you're still chairman of inside ETFs. Why

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Speaker 1: did you decide to keep that role. I still love ETFs,

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Speaker 1: and I still think the E t F industry is

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Speaker 1: evolving rapidly, and I still think there are a lot

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Speaker 1: of things that people need to learn, particularly as we

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Speaker 1: enter a different cycle in the market. So the ability

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Speaker 1: to still influence that conference was really appealing. I like

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Speaker 1: to keep my hand in. I'm also on the board

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Speaker 1: of a small et F issuer UM, so I like

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Speaker 1: to stay involved in the E t F space because

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Speaker 1: I still think we have miles to go there. So

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Speaker 1: I speak at a lot of events and conferences, and

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Speaker 1: every now and then there's a couple of you know,

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Speaker 1: there's a good name or two that speak your conference

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Speaker 1: held in Florida in February year. It's mind blowing the

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Speaker 1: list of names that show up. So last year I

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Speaker 1: got to interview Serena Williams as a as a favor

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Speaker 1: to you, so I'll call I'll be calling back, uh

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Speaker 1: that favor. But before I interviewed Serena Williams, I'm in

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Speaker 1: the audience watching Quincy Jones. And then after I'm done

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Speaker 1: with that interview, I went back into the audience and

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Speaker 1: watched was it a General McCrystal. So, I mean it

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Speaker 1: was just like, and this year you have Michael Lewis,

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Speaker 1: while'll be interviewing in February, Paul Tutor, Jones, Joe Montana.

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Speaker 1: I mean you got s. Don't mess around, Bob Schiller.

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Speaker 1: Uh yeah, we don't mess around. Well we you know,

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Speaker 1: one of the great things about running a conference company

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Speaker 1: is that you get to indulge all your intellectual interests.

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Speaker 1: So I love Michael Lewis, So why don't we want

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Speaker 1: to have him there? Right? We love I love sports,

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Speaker 1: so you can get football giants there. You had Alex

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Speaker 1: Rodriguez the year I was one of the keynote presenters,

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Speaker 1: and I wish I would have hung around. He was great,

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Speaker 1: like I heard and I and how you find him?

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Speaker 1: I read a great article where he reflected on sort

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Speaker 1: of the challenges that he had faced. I thought he

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Speaker 1: would be an interesting person to listen to. It's four days,

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Speaker 1: and so you can't do four days of creation, redemption

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Speaker 1: and emerging market debt. You need to give people a

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Speaker 1: chance to to reflect and think about other things. And Uh, yeah,

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Speaker 1: we're really excited. I think having Schiller there this year,

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Speaker 1: at this time in the market is really timely. Uh

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Speaker 1: and looking forward to that. Yeah, he's terrific. The anybody

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Speaker 1: wants to look up the agenda, you just google inside

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Speaker 1: et F Conference Florida and feb worry and it will

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Speaker 1: show up. Um. It's always a great time. So the

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Speaker 1: next question I have to ask is what do you

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Speaker 1: hope to accomplish with this giant event? And and I

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Speaker 1: don't know if I've I've tied this up correctly for people.

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Speaker 1: I'm not just promoting an event. I don't want people

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Speaker 1: to think that I go to a ton of events.

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Speaker 1: This and SALT. I mean, these are the two biggest

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Speaker 1: conferences of the year. These are giant, two thousand, three

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Speaker 1: thousand people events. So SALT in Vegas, the last time

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Speaker 1: I went there was an amazing that had hedge fund

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Speaker 1: managers there and I got to run around and say

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Speaker 1: under perform I got around, I wasn't the most popular

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Speaker 1: there guy there, although that was yeah, that's true and

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Speaker 1: um And then the first time I I went to

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Speaker 1: this event, I was kind of blown away by how

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Speaker 1: giant it actually was, and not just big for the

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Speaker 1: sake of big big with really big names and really

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Speaker 1: interesting things. What do you hope to accomplish with this event? Yeah? So,

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Speaker 1: so the event is focused primarily on financial advisors. Into

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Speaker 1: my mind, it's a success if the people who come

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Speaker 1: and take three days out of their lives to attend

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Speaker 1: that away from their families, find a way to sustain

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Speaker 1: or grow their business. And so to do that, I

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Speaker 1: want them to learn at this particular year's event a

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Speaker 1: few things. I want them to think deeply about where

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Speaker 1: we are in the economic cycle and what that means

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Speaker 1: for clients and what that means for their bond holdings, etcetera.

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Speaker 1: I want them to uh to think deeply about these

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Speaker 1: new areas of the market that are opening up, not

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Speaker 1: just crypto, which we talked about UM, but some of

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Speaker 1: the thematic ETFs and whether those are performance chasing or

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Speaker 1: valuable and interesting. And then one thing we try to

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Speaker 1: do a little bit is asked them to think five

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Speaker 1: years ahead. I think the financial advisory business is going

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Speaker 1: to be fundamentally transformed in the next five years. I

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Speaker 1: think we're on the cusp of an era of mass

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Speaker 1: customization for client exposures. Uh. And just like we talked

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Speaker 1: about robo advisors five years ago when no one cared,

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Speaker 1: I think getting people to think about mass customization, personalized indexing,

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Speaker 1: E s G overlays now will be helpful to their

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Speaker 1: business in the years ahead. So uh, that's those are

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Speaker 1: some of the things I want them to take away.

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Speaker 1: So who attends these events? Is it just our I

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Speaker 1: a s Is it? Because when I was there last year,

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Speaker 1: I saw a lot of et F managers. I saw

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Speaker 1: a lot of active managers. I saw a bunch of

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Speaker 1: economists and strategists. Who's primarily in the audience? Yeah, I think.

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Speaker 1: I think everyone from the traditional asset management industry is there.

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Speaker 1: So every e t F issuhe or every index provider,

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Speaker 1: all the aps and market makers, also all the mutual

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Speaker 1: fund managers who must be thinking about the E t

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Speaker 1: F space are there to see and learn. And on

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Speaker 1: the flip side, there are really two classes of investors. Uh,

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Speaker 1: So they're they're a large number of financial advisors, and

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Speaker 1: there's a rising number of institutional investors because they're increasingly

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Speaker 1: using e t F s at the core or of

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Speaker 1: their portfolio and not just on the edges, so that

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Speaker 1: that mix comes together. So I recall last year you

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Speaker 1: had Tim Buckley the new CEO of Vanguard. There were

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Speaker 1: a number of other you know, black Rock, State Street,

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Speaker 1: Wisdom Tree. It was hard to walk around and not

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Speaker 1: run into some pretty substantial entities. Have you ever sat

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Speaker 1: back and calculated the total assets under management in that room?

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Speaker 1: I have not. That's a good question. I'm gonna I'm

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Speaker 1: gonna guess it somewhere, and there'll be a lot of

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Speaker 1: overlap because when you have the head of black Rock

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Speaker 1: in the head of Vanguard up front, and then two

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Speaker 1: thirds of the audience owns black Rock and Vanguard, there's

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Speaker 1: a little bit of double counting. But I gotta think

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Speaker 1: there's like ten trillion dollars in that board room. There's

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Speaker 1: a huge amount of volume. There's a thing called the

431
00:23:50,480 --> 00:23:53,480
Speaker 1: inside et effect, which E t F volumes tend to

432
00:23:53,520 --> 00:23:56,520
Speaker 1: be down for the three days. Is that is that

433
00:23:56,600 --> 00:23:58,840
Speaker 1: a fact that used at least used to be a fact.

434
00:23:58,960 --> 00:24:00,560
Speaker 1: I don't know. If it continues to be a fact,

435
00:24:00,720 --> 00:24:03,720
Speaker 1: so many people from the E t F industry are

436
00:24:03,880 --> 00:24:07,320
Speaker 1: in Florida for this event, that trading volume falls, Yes

437
00:24:07,440 --> 00:24:12,080
Speaker 1: it's modest, but yes that is at That's hilarious and

438
00:24:12,320 --> 00:24:14,840
Speaker 1: I just have to I just have to give my

439
00:24:15,040 --> 00:24:19,080
Speaker 1: disclosures about this UM because we're all about transparency and

440
00:24:19,160 --> 00:24:22,560
Speaker 1: full disclosure. So I have been a paid speaker at

441
00:24:22,640 --> 00:24:25,760
Speaker 1: the Inside e t F conference and the Inside E

442
00:24:25,880 --> 00:24:29,200
Speaker 1: t F firm is co sponsoring a conference in T

443
00:24:29,600 --> 00:24:33,800
Speaker 1: nineteen in in September in Arizona with my firm UM

444
00:24:34,119 --> 00:24:37,679
Speaker 1: r W M or Heals Wealth Management UM called wealth Stack.

445
00:24:38,280 --> 00:24:41,359
Speaker 1: And I would rather disclose that than have somebody after

446
00:24:41,440 --> 00:24:43,960
Speaker 1: the facts say hey, why don't you tell us about

447
00:24:44,040 --> 00:24:48,200
Speaker 1: that UM. Two years ago I interviewed Serena Williams, which

448
00:24:48,359 --> 00:24:52,159
Speaker 1: was the highlight of of my interview career as a

449
00:24:52,240 --> 00:24:55,359
Speaker 1: tennis player, and we we played a couple of sets.

450
00:24:55,480 --> 00:24:58,399
Speaker 1: She won six two, six four. It was closer than

451
00:24:59,680 --> 00:25:03,080
Speaker 1: she was six months pregnant. Um. Actually this was right

452
00:25:03,160 --> 00:25:06,040
Speaker 1: after she had a baby. And what was really interesting

453
00:25:06,240 --> 00:25:11,359
Speaker 1: is what I'm fascinated by the non finance people that

454
00:25:11,520 --> 00:25:13,560
Speaker 1: speak at events like this, and you guys do a

455
00:25:13,600 --> 00:25:19,399
Speaker 1: really good job programming. This is how many parallel learning

456
00:25:19,440 --> 00:25:26,080
Speaker 1: experiences there are between non finance related businesses and whether

457
00:25:26,160 --> 00:25:30,400
Speaker 1: it's the military or sports music. Uh, there's some really

458
00:25:30,600 --> 00:25:36,120
Speaker 1: fascinating things to learn about process over outcome, about our

459
00:25:36,160 --> 00:25:39,280
Speaker 1: own errors and biases, and how we can do better

460
00:25:39,520 --> 00:25:42,320
Speaker 1: even when we make mistakes, how we can learn from them. Um,

461
00:25:42,600 --> 00:25:45,520
Speaker 1: that sort of that sort of stuff is always really

462
00:25:46,040 --> 00:25:48,600
Speaker 1: really fascinating. Who are you really looking forward to seeing

463
00:25:48,680 --> 00:25:51,639
Speaker 1: speak this year? Yeah, I'm really looking for I mentioned

464
00:25:51,680 --> 00:25:53,919
Speaker 1: this earlier. I'm really looking forward to chill Or speaking.

465
00:25:55,960 --> 00:25:59,160
Speaker 1: He's you've seen him before, I've seen him before. He's fantastic.

466
00:25:59,280 --> 00:26:02,720
Speaker 1: He's fantastic again. And he seems honest and organic. He's

467
00:26:02,760 --> 00:26:05,840
Speaker 1: totally organic, which is which is unique. Not everyone is

468
00:26:05,880 --> 00:26:09,120
Speaker 1: a lot of people speak their book. Uh, and that's

469
00:26:09,160 --> 00:26:12,520
Speaker 1: not true. I'm really excited about Michael Lewis. We've tried

470
00:26:12,560 --> 00:26:14,840
Speaker 1: to get him many years and the schedule has not

471
00:26:14,920 --> 00:26:18,360
Speaker 1: worked out. He's one of my favorite authors. I see

472
00:26:18,440 --> 00:26:21,280
Speaker 1: him around town in Berkeley and always want to like

473
00:26:21,400 --> 00:26:23,399
Speaker 1: stalk him and ask him to come. Now you have

474
00:26:23,480 --> 00:26:26,520
Speaker 1: an excuse. Now he's there, So I'm assuming you read

475
00:26:26,600 --> 00:26:29,800
Speaker 1: The Undoing Project which is his previous book. The Fifth

476
00:26:29,880 --> 00:26:31,920
Speaker 1: Column is the new one. I haven't read the new one,

477
00:26:33,119 --> 00:26:35,680
Speaker 1: so I read it. We went down to Florida over

478
00:26:35,720 --> 00:26:38,880
Speaker 1: the holidays. I read it on the plane and it's

479
00:26:39,440 --> 00:26:43,440
Speaker 1: it's great, but it's infuriated, yea, because it's just why

480
00:26:43,520 --> 00:26:45,720
Speaker 1: are they making this mistake? You know what it is?

481
00:26:45,840 --> 00:26:49,600
Speaker 1: The big short is infuriating, but you feel like the

482
00:26:49,760 --> 00:26:53,920
Speaker 1: people who deserve to some of the people who deserves

483
00:26:54,040 --> 00:26:59,200
Speaker 1: get punished. In the Fifth Column. There is no justice.

484
00:26:59,840 --> 00:27:03,120
Speaker 1: It's like, wait, people are doing what No, that's wrong.

485
00:27:03,240 --> 00:27:06,800
Speaker 1: It's just bad. Yeah, it's it's uh, it's quite fascinating.

486
00:27:07,040 --> 00:27:11,240
Speaker 1: And I read that in anticipation of this interview were

487
00:27:11,320 --> 00:27:13,480
Speaker 1: I'm looking forward to hearing you chat with him. Normally

488
00:27:13,640 --> 00:27:17,119
Speaker 1: I would have held that book for my like February

489
00:27:17,240 --> 00:27:21,480
Speaker 1: March vacation. That's speech reading to me, um, But I'm like, no, no,

490
00:27:21,600 --> 00:27:23,520
Speaker 1: I got a prep and I like to I like

491
00:27:23,680 --> 00:27:26,840
Speaker 1: to read like a month in advance and then kind

492
00:27:26,880 --> 00:27:29,399
Speaker 1: of go through my notes a week beforehand and it

493
00:27:29,520 --> 00:27:31,960
Speaker 1: all comes back, but it's had time to percolate it.

494
00:27:32,760 --> 00:27:35,080
Speaker 1: So Schiller. By the way, Schiller a prior guest, Michael

495
00:27:35,119 --> 00:27:38,119
Speaker 1: Lewis prior guest. Schiller is amazing. You're gonna have a

496
00:27:38,160 --> 00:27:41,400
Speaker 1: great I think he's not doing an interview, he's just presenting.

497
00:27:41,600 --> 00:27:45,960
Speaker 1: He's just presenting his outlook. He's you know, professors at Yale,

498
00:27:46,119 --> 00:27:50,480
Speaker 1: for some reason, have a way to demand a stage

499
00:27:50,960 --> 00:27:53,359
Speaker 1: and an audience. I think people will will love him.

500
00:27:53,560 --> 00:27:55,800
Speaker 1: And he doesn't go too far out into the weeds,

501
00:27:56,520 --> 00:27:59,479
Speaker 1: even though he could at any time he wants to. Definitely,

502
00:28:00,480 --> 00:28:03,480
Speaker 1: you're you're certainly. I assume you're familiar with his friendship

503
00:28:03,760 --> 00:28:06,960
Speaker 1: with Jeremy c which is hilarious. It is Larry and

504
00:28:07,040 --> 00:28:10,000
Speaker 1: Jeremy Siegel is magic on stage. Yeah. I love seeing

505
00:28:10,080 --> 00:28:12,359
Speaker 1: Jeremy Siegel before he goes on stage, where there was

506
00:28:12,400 --> 00:28:16,399
Speaker 1: the old professor sort of me into him, and then

507
00:28:16,440 --> 00:28:19,520
Speaker 1: he goes on stage and he's just supernova. It's amazing

508
00:28:19,640 --> 00:28:23,600
Speaker 1: to watch him. Fantastic. So when he was on the show,

509
00:28:23,800 --> 00:28:27,080
Speaker 1: he was sitting where you were sitting. And for whatever,

510
00:28:27,400 --> 00:28:30,520
Speaker 1: he's in the University of Pennsylvania, so they take the

511
00:28:30,600 --> 00:28:32,680
Speaker 1: train in. They must have him teed up for a

512
00:28:32,800 --> 00:28:35,840
Speaker 1: dozen things. I'm interviewing him towards the end of the day,

513
00:28:35,920 --> 00:28:39,080
Speaker 1: it's like five o'clock and so It's a long day

514
00:28:39,160 --> 00:28:41,840
Speaker 1: for anybody, and for someone who's his age run around,

515
00:28:42,240 --> 00:28:44,960
Speaker 1: it's a long day. And he's sitting there and I

516
00:28:45,080 --> 00:28:48,000
Speaker 1: want to say, in like the last thirty minutes of

517
00:28:48,080 --> 00:28:52,200
Speaker 1: two hours, he just starts swiveling with the chair and

518
00:28:52,320 --> 00:28:55,200
Speaker 1: then before you know it, he just starts doing this.

519
00:28:56,480 --> 00:28:59,560
Speaker 1: And I'm sitting there watching this, and you could literally

520
00:28:59,760 --> 00:29:02,880
Speaker 1: he or him. You could hear the Doppler effected he

521
00:29:03,040 --> 00:29:07,960
Speaker 1: as he says of a long run. It was absolutely

522
00:29:08,040 --> 00:29:10,640
Speaker 1: one of the things that and I just had like

523
00:29:10,800 --> 00:29:14,080
Speaker 1: a grin on my face that you it must have

524
00:29:14,160 --> 00:29:18,080
Speaker 1: taken a week for me to stop laughing. And then

525
00:29:18,600 --> 00:29:22,760
Speaker 1: the amazing thing is he is consistently picked as um

526
00:29:23,280 --> 00:29:27,320
Speaker 1: everybody's favorite professor, of course, and I always I always

527
00:29:27,360 --> 00:29:30,640
Speaker 1: wondered why, and then you realize he's like this impish child,

528
00:29:31,200 --> 00:29:38,360
Speaker 1: this delightful, this delightful leprechaun discussing um long term expected

529
00:29:38,440 --> 00:29:42,400
Speaker 1: returns of equities. Oh, of course, the Wharton students love him.

530
00:29:42,440 --> 00:29:46,040
Speaker 1: He's just like endlessly entertained and the two of them

531
00:29:46,320 --> 00:29:50,560
Speaker 1: couldn't be more different personalities. It's so great. Yeah, no,

532
00:29:50,680 --> 00:29:54,320
Speaker 1: it really is great. I have to mention a quote

533
00:29:54,360 --> 00:29:57,680
Speaker 1: of yours that I'm tickled by and get get a response.

534
00:29:58,040 --> 00:30:02,120
Speaker 1: So for a long time I been saying that all

535
00:30:02,200 --> 00:30:05,080
Speaker 1: the crypto heads are the new gold bugs. But but

536
00:30:05,320 --> 00:30:09,760
Speaker 1: you phrased it a little differently. You said bitcoin was

537
00:30:09,880 --> 00:30:13,960
Speaker 1: the new millennial gold discussed. Yeah, well, it's definitely true.

538
00:30:14,440 --> 00:30:18,080
Speaker 1: Every generation has an asset that they love or a

539
00:30:18,440 --> 00:30:21,600
Speaker 1: way of getting exposure that they love. The greatest generation

540
00:30:21,720 --> 00:30:25,080
Speaker 1: loved gold. Then people loved active mutual funds, gen X

541
00:30:25,160 --> 00:30:29,880
Speaker 1: loved hedge funds. Millennials love crypto. If you ask millennials

542
00:30:30,240 --> 00:30:33,600
Speaker 1: which would they rather hold gold or or bitcoin, it's

543
00:30:33,640 --> 00:30:36,200
Speaker 1: bitcoined by a mile. Which would they rather hold equities

544
00:30:36,280 --> 00:30:39,120
Speaker 1: or bitcoin? It's bitcoin by a mile. And I would

545
00:30:39,160 --> 00:30:42,680
Speaker 1: say there are a lot of analogies between bitcoin and gold.

546
00:30:42,760 --> 00:30:47,440
Speaker 1: They're both non sovereign stores of value. Uh, but bitcoin

547
00:30:47,560 --> 00:30:50,320
Speaker 1: is much more useful in gold. It's it's much more

548
00:30:50,400 --> 00:30:52,959
Speaker 1: easily divisible. It can be spent, it can be stored,

549
00:30:53,000 --> 00:30:55,880
Speaker 1: it's it's it can be transferred easily. Um. So it

550
00:30:56,080 --> 00:30:59,680
Speaker 1: is it's like an upgraded version of gold. I think

551
00:30:59,720 --> 00:31:02,080
Speaker 1: I get liquid with gold faster than I could get

552
00:31:02,120 --> 00:31:05,400
Speaker 1: liquid with bitcoin in size, and I certainly could trade

553
00:31:05,480 --> 00:31:08,440
Speaker 1: gold for more things than I could for bitcoin right now.

554
00:31:08,680 --> 00:31:12,440
Speaker 1: That's definitely true. That is definitely true any early stage technology. Uh,

555
00:31:12,880 --> 00:31:14,800
Speaker 1: it takes a while to get up the spectrum. I'm

556
00:31:14,800 --> 00:31:17,280
Speaker 1: not sure you're right about the liquidity in size. It

557
00:31:17,320 --> 00:31:19,840
Speaker 1: depends on You can get liquid and bitcoin at very

558
00:31:19,920 --> 00:31:24,080
Speaker 1: reasonable sizes very quickly. Certainly golds are deeper million in bitcoin.

559
00:31:24,160 --> 00:31:26,280
Speaker 1: I I didn't know you were that well off, But

560
00:31:26,440 --> 00:31:29,600
Speaker 1: that's that's what this is for a friend friend, so

561
00:31:29,760 --> 00:31:31,080
Speaker 1: he wants to know how he can get the hell

562
00:31:31,120 --> 00:31:33,720
Speaker 1: out of this, and uh, there are there are some

563
00:31:33,880 --> 00:31:37,560
Speaker 1: dollar limitations on the coin. That is true. It is

564
00:31:37,560 --> 00:31:40,200
Speaker 1: an early stage technology. Uh, and I'm not I'm not

565
00:31:40,440 --> 00:31:43,080
Speaker 1: claiming it's more established than gold. You know, if you

566
00:31:43,120 --> 00:31:44,920
Speaker 1: look back at gold when it came off the US

567
00:31:44,960 --> 00:31:48,440
Speaker 1: gold standard, it went through a period of rapidly rising

568
00:31:48,520 --> 00:31:51,160
Speaker 1: prices and massive volatility and a years when it went up,

569
00:31:51,160 --> 00:31:54,080
Speaker 1: a percent years when it went down. We just don't

570
00:31:54,120 --> 00:31:57,120
Speaker 1: remember that. Uh, this is a new sovereign store of value.

571
00:31:57,160 --> 00:32:00,080
Speaker 1: Would expect sort of an asymptotic rise in price, and

572
00:32:00,160 --> 00:32:04,160
Speaker 1: you would expect massive volatility. And if I'm right about bitcoin,

573
00:32:04,320 --> 00:32:06,840
Speaker 1: ten years from now, it will be boring like gold

574
00:32:06,920 --> 00:32:09,760
Speaker 1: to uh, and that's what we're waiting for. That's not

575
00:32:09,920 --> 00:32:12,000
Speaker 1: the first word that comes to mind when I think

576
00:32:12,000 --> 00:32:14,920
Speaker 1: about bitcoin. It's boring. But by the way, people forget

577
00:32:15,400 --> 00:32:20,600
Speaker 1: how many draw downs has Amazon had, Apple had, gees

578
00:32:20,600 --> 00:32:25,200
Speaker 1: in the middle of a major Successful companies go through

579
00:32:25,280 --> 00:32:27,880
Speaker 1: that on a regular basis. We tend not to want

580
00:32:27,920 --> 00:32:30,120
Speaker 1: to think about. That's right. And bitcoin has gone through

581
00:32:30,240 --> 00:32:33,800
Speaker 1: seven six or seven plus draw downs in the past,

582
00:32:34,320 --> 00:32:35,880
Speaker 1: and each of those that set the stage for a

583
00:32:35,920 --> 00:32:39,440
Speaker 1: new rally. Now I'm not saying that will necessarily happen here, um,

584
00:32:39,680 --> 00:32:43,280
Speaker 1: but you know it's down, it's up over the last

585
00:32:43,320 --> 00:32:47,240
Speaker 1: two years. So it depends on your perspective. So let's

586
00:32:47,280 --> 00:32:50,280
Speaker 1: talk a little bit about the index that you guys

587
00:32:50,320 --> 00:32:53,440
Speaker 1: are putting together. You created the index, you're using it

588
00:32:53,560 --> 00:32:55,680
Speaker 1: as a basis for an e t F. You've already

589
00:32:55,720 --> 00:32:58,560
Speaker 1: filed with the SEC. So let's talk a little bit

590
00:32:58,560 --> 00:33:01,840
Speaker 1: about that filing. What you're what do you disclosing that filing,

591
00:33:01,920 --> 00:33:05,360
Speaker 1: and what should someone who's interested in buying an e

592
00:33:05,520 --> 00:33:09,400
Speaker 1: t F that will hold coins an index of coins

593
00:33:09,480 --> 00:33:12,520
Speaker 1: actually look like. Yeah, so, uh, we have filed two

594
00:33:12,560 --> 00:33:15,800
Speaker 1: applications for cryptocurrency e t F S one is a

595
00:33:15,920 --> 00:33:19,160
Speaker 1: index basket that holds the top ten crypto assets and

596
00:33:19,320 --> 00:33:22,240
Speaker 1: one is bitcoin only. So wait a second, I could

597
00:33:22,320 --> 00:33:25,720
Speaker 1: buy bitcoin when this is finally approved through an ETF.

598
00:33:25,880 --> 00:33:28,880
Speaker 1: That would be the hope that if the SEC approves

599
00:33:28,960 --> 00:33:30,280
Speaker 1: the ct F, you will be able to buy it

600
00:33:30,320 --> 00:33:31,960
Speaker 1: through an e t F the same way you buy

601
00:33:32,120 --> 00:33:36,560
Speaker 1: gold through g l D or silver for through SLV. Uh.

602
00:33:36,840 --> 00:33:39,800
Speaker 1: You know, it's the same idea. It's easy exposure in

603
00:33:39,880 --> 00:33:42,920
Speaker 1: a familiar brokerage window to something you otherwise have to

604
00:33:42,960 --> 00:33:46,040
Speaker 1: buy in a different way. And so there have been

605
00:33:46,120 --> 00:33:49,480
Speaker 1: multiple bitcoin ETFs filed. For what it's worth. Uh, we're

606
00:33:49,560 --> 00:33:52,480
Speaker 1: moving forward more aggressively on our end with the bitcoin

607
00:33:52,600 --> 00:33:56,840
Speaker 1: filing than the index filing um. But uh yeah, we're

608
00:33:56,880 --> 00:33:59,800
Speaker 1: we're we're hopeful, uh and optimistic that we can work

609
00:33:59,840 --> 00:34:02,400
Speaker 1: with SEC. They've raised legitimate issues, but we hope we

610
00:34:02,440 --> 00:34:04,400
Speaker 1: can work through it and we'll see. And this isn't

611
00:34:04,520 --> 00:34:07,200
Speaker 1: an i c oh so a lot of these initial

612
00:34:07,280 --> 00:34:10,960
Speaker 1: coin offerings have been played with. Now this is an

613
00:34:11,000 --> 00:34:16,080
Speaker 1: e t F equity trading vehicle that will hold bitcoin.

614
00:34:16,280 --> 00:34:19,160
Speaker 1: That's that's the hope. So now there's been a lot

615
00:34:19,239 --> 00:34:24,280
Speaker 1: of scams not on that, but some of these wallets

616
00:34:24,360 --> 00:34:29,000
Speaker 1: and various coin offerings, and people have been hyping it

617
00:34:29,120 --> 00:34:31,880
Speaker 1: up some A number of celebrities got associated with this

618
00:34:32,000 --> 00:34:34,680
Speaker 1: and got into trouble with your sec You're trying to

619
00:34:34,760 --> 00:34:40,000
Speaker 1: do the most plane vanilla offering you can with bitcoin

620
00:34:40,120 --> 00:34:43,440
Speaker 1: as the underlying asset. That is right. So so a

621
00:34:43,520 --> 00:34:45,360
Speaker 1: lot of those I c O s were scams. I

622
00:34:45,400 --> 00:34:48,560
Speaker 1: think we're illegal, uh, and we'll be will be prosecuted.

623
00:34:48,560 --> 00:34:50,600
Speaker 1: People are going to jail. I think people will are

624
00:34:50,640 --> 00:34:52,640
Speaker 1: going to jail and I think they should uh. And

625
00:34:52,760 --> 00:34:54,880
Speaker 1: it brought out a lot of bad actors in the

626
00:34:54,920 --> 00:34:58,640
Speaker 1: space because there's such massive wealth accumulation. But that doesn't

627
00:34:58,680 --> 00:35:01,400
Speaker 1: mean that there aren't legitimate thing. So right now we

628
00:35:01,600 --> 00:35:05,360
Speaker 1: have crypto index fund that's available for credited investors. We

629
00:35:05,400 --> 00:35:08,320
Speaker 1: have a Bitcoin for one for credited investors. But the

630
00:35:08,400 --> 00:35:11,000
Speaker 1: hope is we can launch an e t F that

631
00:35:11,080 --> 00:35:14,200
Speaker 1: gives that exposure to everyone. It makes it safe, cheap

632
00:35:14,200 --> 00:35:16,520
Speaker 1: and easy to gain exposure to the market. I hope

633
00:35:16,560 --> 00:35:20,360
Speaker 1: you've picked out a nice um security symbols. Oh, the

634
00:35:20,480 --> 00:35:23,480
Speaker 1: ticker ticker choice is a big deal. It really is.

635
00:35:23,640 --> 00:35:29,120
Speaker 1: People don't appreciate Remember move that that exploded and you

636
00:35:29,480 --> 00:35:32,200
Speaker 1: or hack for that matter, h A c K, which

637
00:35:32,280 --> 00:35:34,040
Speaker 1: is now in the midst of litigation. I hope it

638
00:35:34,080 --> 00:35:38,360
Speaker 1: gets resolved sooner rather than later. Um. But uh, having

639
00:35:38,480 --> 00:35:40,880
Speaker 1: and it's been shown even with equities, if you have

640
00:35:41,000 --> 00:35:43,440
Speaker 1: a good ticker symbol, Yeah, it's worth a couple of

641
00:35:43,520 --> 00:35:46,960
Speaker 1: percents in performance over time, And it makes perfect sense.

642
00:35:47,040 --> 00:35:49,879
Speaker 1: It makes behavioral sense. I think it matters a great deal.

643
00:35:50,040 --> 00:35:51,799
Speaker 1: And I can't wait until the day that we get

644
00:35:51,840 --> 00:35:54,239
Speaker 1: to pick and disclose the time. I'm assuming you have

645
00:35:54,400 --> 00:35:57,080
Speaker 1: one reserved than you just can't disclose. You never know.

646
00:35:58,440 --> 00:36:00,879
Speaker 1: So so let's talk a little bit about the methodology

647
00:36:01,080 --> 00:36:04,720
Speaker 1: of the index. Is it simply just the ten biggest

648
00:36:04,800 --> 00:36:08,000
Speaker 1: coins or the ten most liquid coins? How you putting

649
00:36:08,040 --> 00:36:10,680
Speaker 1: that together? So at one level, the indexes for for

650
00:36:10,800 --> 00:36:14,480
Speaker 1: our fund is the ten largest coins. But of course

651
00:36:14,560 --> 00:36:16,759
Speaker 1: everything in crypto, which is why I got interested, is

652
00:36:16,800 --> 00:36:19,200
Speaker 1: more complex than it is in equity. So like you

653
00:36:19,320 --> 00:36:21,320
Speaker 1: and I could say what is the price of IBM,

654
00:36:21,360 --> 00:36:23,719
Speaker 1: and we would say the exact same number. If you

655
00:36:23,760 --> 00:36:25,640
Speaker 1: ask me what the price of bitcoin is, I'd have

656
00:36:25,719 --> 00:36:28,800
Speaker 1: to look at different exchanges merge them together. Um. So

657
00:36:28,960 --> 00:36:32,120
Speaker 1: everything is more difficult, but it is a market capuated

658
00:36:32,160 --> 00:36:34,879
Speaker 1: index of crypto assets. And and let me say why,

659
00:36:34,880 --> 00:36:38,560
Speaker 1: I think that's an interesting strategy. Um, we don't know

660
00:36:38,800 --> 00:36:41,759
Speaker 1: for well, yeah, well we don't know what will happen

661
00:36:41,800 --> 00:36:45,399
Speaker 1: in crypto, right, it's early. These are competing protocols, they're

662
00:36:45,440 --> 00:36:48,520
Speaker 1: each optimized for a different use case. And I'm not

663
00:36:48,640 --> 00:36:52,120
Speaker 1: smart enough to know five years from now whether Bitcoin

664
00:36:52,280 --> 00:36:55,080
Speaker 1: or ethereum, or light coin or man narrow or these

665
00:36:55,120 --> 00:36:57,400
Speaker 1: other assets will be the most important. I just don't know.

666
00:36:57,920 --> 00:36:59,600
Speaker 1: And so the index gives you a simple way to

667
00:36:59,680 --> 00:37:02,440
Speaker 1: make a simple bet, which is, I think crypto will

668
00:37:02,480 --> 00:37:05,200
Speaker 1: be more important in the future than it is today. Uh.

669
00:37:05,520 --> 00:37:07,120
Speaker 1: And if if that's the bet you want to make,

670
00:37:07,200 --> 00:37:09,200
Speaker 1: you want to make a broadly diverse fig. So why

671
00:37:09,360 --> 00:37:12,279
Speaker 1: the top ten and not the top Yeah, there's a

672
00:37:12,400 --> 00:37:14,600
Speaker 1: very big power law on crypto. So the top ten

673
00:37:14,680 --> 00:37:18,799
Speaker 1: captures about in the market, and after that liquidity falls out.

674
00:37:19,120 --> 00:37:20,759
Speaker 1: If you think back to the equity market, in the

675
00:37:20,800 --> 00:37:23,200
Speaker 1: early days of emerging markets, you would only buy large

676
00:37:23,280 --> 00:37:26,040
Speaker 1: caps and then large mid and now you buy everything.

677
00:37:26,320 --> 00:37:29,040
Speaker 1: I think the same thing is true with crypto. Makes sense.

678
00:37:29,800 --> 00:37:33,160
Speaker 1: I know the venture capital world has been very interested

679
00:37:33,280 --> 00:37:37,880
Speaker 1: in everything from um, crypto to blockchain, So what have you.

680
00:37:38,880 --> 00:37:42,160
Speaker 1: Bitcoin has some pretty high profile backers. What do you

681
00:37:42,239 --> 00:37:45,600
Speaker 1: see in the VC space when it comes to cryptocurrency. Yeah,

682
00:37:45,600 --> 00:37:47,799
Speaker 1: a lot of interest and a lot of interest that's

683
00:37:47,800 --> 00:37:51,200
Speaker 1: trickling into the endowment and pension space that's investing into

684
00:37:51,239 --> 00:37:54,800
Speaker 1: crypto through funds like the injurycent Fund or some of

685
00:37:54,840 --> 00:37:57,239
Speaker 1: the other funds. A lot of the firms are trying

686
00:37:57,280 --> 00:37:59,560
Speaker 1: to solve one of two problems. Either they're part of

687
00:37:59,640 --> 00:38:03,760
Speaker 1: a step publishing this institutional ecosystem. Because remember crypto emerged

688
00:38:03,800 --> 00:38:06,239
Speaker 1: as a retail asset. It trades on lightly or non

689
00:38:06,320 --> 00:38:09,480
Speaker 1: regulated exchanges, so you're seeing a lot of investment into

690
00:38:09,520 --> 00:38:13,200
Speaker 1: regulated exchanges like backed, which is from Ice, which is

691
00:38:13,280 --> 00:38:16,359
Speaker 1: launching in Q one. Uh. That's one thing, and then

692
00:38:16,400 --> 00:38:19,480
Speaker 1: the other thing is companies that are improving on the

693
00:38:19,560 --> 00:38:23,120
Speaker 1: underlying technology and the blockchain technology or building applications on

694
00:38:23,239 --> 00:38:27,320
Speaker 1: top of that. UH. And like any VC boom, valuations

695
00:38:27,320 --> 00:38:30,040
Speaker 1: are probably too high. They'll be a pullback, but but

696
00:38:30,120 --> 00:38:32,680
Speaker 1: it's exciting and it means there's a big infusion of

697
00:38:32,760 --> 00:38:35,120
Speaker 1: capital and big infusion of people working on the project.

698
00:38:35,440 --> 00:38:39,759
Speaker 1: You mentioned the pensions and the endowments that have an

699
00:38:39,840 --> 00:38:43,480
Speaker 1: interest in this um, what other institutions are looking at this?

700
00:38:43,640 --> 00:38:46,799
Speaker 1: And and I would have to also bring up Fidelity.

701
00:38:47,400 --> 00:38:52,720
Speaker 1: All companies made a big early UM jump towards crypto.

702
00:38:52,920 --> 00:38:55,120
Speaker 1: Tell us what you know about that? Yeah, Fidelities hiring

703
00:38:55,200 --> 00:38:57,360
Speaker 1: up to a hundred and fifty people to build a

704
00:38:57,440 --> 00:39:01,160
Speaker 1: way for institutional investors to buy crypto and store it

705
00:39:01,320 --> 00:39:03,520
Speaker 1: with a name they trust. Right, one of the greatest

706
00:39:03,560 --> 00:39:06,080
Speaker 1: brand names in the future. You'll ask yourself why Fidelity

707
00:39:06,120 --> 00:39:08,680
Speaker 1: and why haven't I seen black Rock, State Street other

708
00:39:08,719 --> 00:39:12,360
Speaker 1: asset managers. The difference is the Fidelity is a family

709
00:39:12,400 --> 00:39:16,640
Speaker 1: owned firm, privately held, not public, still reputational risk in crypto.

710
00:39:16,800 --> 00:39:19,280
Speaker 1: The other big player in crypto is van Eck, also

711
00:39:19,400 --> 00:39:22,480
Speaker 1: privately held, also a family owned firm. We know, we

712
00:39:22,560 --> 00:39:24,520
Speaker 1: know John, and I don't think that's a surprise. I

713
00:39:24,640 --> 00:39:27,000
Speaker 1: think they're free to do it. Fidelity saw that this

714
00:39:27,160 --> 00:39:30,520
Speaker 1: is important. We know. We had conversations with two thousand

715
00:39:30,880 --> 00:39:35,240
Speaker 1: institutional and financial advisors UH last year. There is dramatic

716
00:39:35,280 --> 00:39:37,920
Speaker 1: interest in crypto. UH. They want good ways to get

717
00:39:37,920 --> 00:39:41,120
Speaker 1: exposure right now. Most of the ways are retail oriented

718
00:39:41,280 --> 00:39:43,600
Speaker 1: and non institutional grade. And so they say on an

719
00:39:43,600 --> 00:39:46,719
Speaker 1: opportunity to be first and they're doing it quite fascinating.

720
00:39:46,840 --> 00:39:49,480
Speaker 1: I read a statistic a couple of months ago that

721
00:39:49,560 --> 00:39:54,239
Speaker 1: I was kind of shocked at. Approximately of all the

722
00:39:54,400 --> 00:39:59,759
Speaker 1: coins ever created have been lost, either there um in

723
00:40:00,000 --> 00:40:04,400
Speaker 1: crypted password access has been lost, or it's physically on

724
00:40:04,480 --> 00:40:07,879
Speaker 1: a drive that was destroyed or some source that. How

725
00:40:08,200 --> 00:40:10,720
Speaker 1: how accurate are those numbers? And if they are accurate,

726
00:40:11,239 --> 00:40:13,600
Speaker 1: how can this ever really be a serious asset class

727
00:40:13,719 --> 00:40:16,640
Speaker 1: If you know, think about all the VCR tapes and

728
00:40:16,760 --> 00:40:21,879
Speaker 1: cassettes people have that essentially technology has orphaned totally. Well,

729
00:40:22,360 --> 00:40:24,680
Speaker 1: you couldn't orphan this because all that's written on that

730
00:40:24,920 --> 00:40:27,200
Speaker 1: is like a fifty letter code. So you could literally

731
00:40:27,239 --> 00:40:29,080
Speaker 1: if you wanted to write it's a piece of paper

732
00:40:29,160 --> 00:40:31,200
Speaker 1: and you would have it. It is true that it's

733
00:40:31,239 --> 00:40:34,840
Speaker 1: a digital bearer instrument, like a bearer bond or like

734
00:40:34,920 --> 00:40:36,840
Speaker 1: a bar of gold, and so if you lose it,

735
00:40:37,440 --> 00:40:41,600
Speaker 1: and what you would lose is that it's lost. Um. Again,

736
00:40:41,640 --> 00:40:44,319
Speaker 1: you gotta think this is an early stage technology right now.

737
00:40:44,560 --> 00:40:46,680
Speaker 1: The UI for crypto is terrible. If you want to

738
00:40:46,760 --> 00:40:49,600
Speaker 1: email me, you can email Matt at Hogan dot com.

739
00:40:49,800 --> 00:40:52,279
Speaker 1: My first name and last name, easy memorable. If you

740
00:40:52,320 --> 00:40:55,360
Speaker 1: want to send me bitcoin. It's like fifty two random letters.

741
00:40:55,840 --> 00:40:59,239
Speaker 1: So I think the UI improvements will happen in and

742
00:40:59,280 --> 00:41:02,800
Speaker 1: will become easy to save, store, and spend crypto. I

743
00:41:02,840 --> 00:41:05,160
Speaker 1: think it's just a matter of software development. We have

744
00:41:05,280 --> 00:41:07,799
Speaker 1: been speaking with Matt Hogan. He is the global head

745
00:41:07,840 --> 00:41:10,840
Speaker 1: of Research. If you enjoy this conversation, be sure and

746
00:41:10,960 --> 00:41:13,520
Speaker 1: come back and check out the podcast extras, where we

747
00:41:13,640 --> 00:41:17,520
Speaker 1: keep the tape rolling and continue chatting about all things crypto.

748
00:41:18,160 --> 00:41:23,400
Speaker 1: You can find that at iTunes, Overcast, Bloomberg, Stitcher, wherever

749
00:41:23,560 --> 00:41:27,320
Speaker 1: your finer podcasts are sold. We love your comments, feedback

750
00:41:27,320 --> 00:41:31,160
Speaker 1: and suggestions right to us at m IB podcast. At

751
00:41:31,200 --> 00:41:34,480
Speaker 1: Bloomberg dot net. You can check out my daily column

752
00:41:34,600 --> 00:41:37,880
Speaker 1: that's on Bloomberg dot com slash Opinion. Follow me on

753
00:41:38,000 --> 00:41:41,960
Speaker 1: Twitter at Rid Halts. I'm Barry Hults. You're listening to

754
00:41:42,120 --> 00:41:59,520
Speaker 1: Master's in Business on Bloomberg Radio. Welcome to the podcast, Matt.

755
00:41:59,640 --> 00:42:02,360
Speaker 1: I'm I'm so glad we're having this conversation. I was

756
00:42:02,440 --> 00:42:05,880
Speaker 1: looking forward uh to doing this with you towards the

757
00:42:06,040 --> 00:42:09,720
Speaker 1: end of last year and things just got so crazy

758
00:42:09,840 --> 00:42:14,200
Speaker 1: with everything. I'm glad we waited a little while to

759
00:42:14,360 --> 00:42:18,520
Speaker 1: just let everything settle out. But I have to ask

760
00:42:19,560 --> 00:42:25,239
Speaker 1: from a well, first, was was bitcoin of bubble last year? Yes?

761
00:42:25,640 --> 00:42:28,120
Speaker 1: Total bubble, total bubble. I mean when we start the

762
00:42:28,200 --> 00:42:34,719
Speaker 1: year like two thousand, did you started around a couple

763
00:42:34,719 --> 00:42:38,480
Speaker 1: of thousand and then ended up at nineteen five something

764
00:42:38,600 --> 00:42:41,040
Speaker 1: like that, and their speculative fervor, and there was every

765
00:42:41,239 --> 00:42:44,160
Speaker 1: element of a bubble that you or I would recognize,

766
00:42:44,200 --> 00:42:48,799
Speaker 1: including your bartender, your Cabby and your Pete was the top.

767
00:42:49,239 --> 00:42:54,759
Speaker 1: And then was what is that retrenchment somewhere in there? Yeah, absolutely,

768
00:42:54,960 --> 00:42:57,719
Speaker 1: that's a that's a big move down. It is significant. Yes,

769
00:42:57,840 --> 00:43:00,920
Speaker 1: it is still up, you know scent from the start

770
00:43:00,960 --> 00:43:05,160
Speaker 1: of seen until now. So from a longer term perspective,

771
00:43:05,160 --> 00:43:07,360
Speaker 1: you know, people love to make fun of holdlers in

772
00:43:07,440 --> 00:43:10,399
Speaker 1: crypto to hold on for dear life. That's the same

773
00:43:10,520 --> 00:43:12,880
Speaker 1: thing as buy and hold in equity, so you just

774
00:43:12,960 --> 00:43:14,759
Speaker 1: have to have a little bit more perspective. But yes,

775
00:43:14,840 --> 00:43:17,320
Speaker 1: it was a massive run up and a massive pullback

776
00:43:17,560 --> 00:43:21,360
Speaker 1: the cues and as one from two thousand, two thousand

777
00:43:21,440 --> 00:43:27,879
Speaker 1: three down, So this is comparable. I think that's right.

778
00:43:28,000 --> 00:43:30,320
Speaker 1: And it did the same thing that happened in the Internet,

779
00:43:30,360 --> 00:43:33,239
Speaker 1: which is it attracted a huge amount of talent, attracted

780
00:43:33,280 --> 00:43:36,080
Speaker 1: a huge amount of capital. Uh, and it's been very

781
00:43:36,160 --> 00:43:39,960
Speaker 1: painful for investors. I think out of that for for investors,

782
00:43:40,120 --> 00:43:42,960
Speaker 1: or for the people who just jumped on blindly when

783
00:43:43,040 --> 00:43:45,239
Speaker 1: it had already begun to move aggressive the people who

784
00:43:45,320 --> 00:43:48,680
Speaker 1: jumped on blindly when it already moved aggressively. And also, um,

785
00:43:49,120 --> 00:43:52,960
Speaker 1: you know, volatile, highly moving assets encouraged bad behavioral responses.

786
00:43:53,160 --> 00:43:55,520
Speaker 1: There was bad activity, um, But it did bring a

787
00:43:55,560 --> 00:43:58,480
Speaker 1: lot of capital and interest in development to the ecosystem.

788
00:43:58,600 --> 00:44:01,920
Speaker 1: So I do think interesting things will be born from that.

789
00:44:02,160 --> 00:44:04,800
Speaker 1: But yeah, it was it was a difficult year. So

790
00:44:04,880 --> 00:44:06,680
Speaker 1: let's talk a little bit about E t F s.

791
00:44:06,800 --> 00:44:08,919
Speaker 1: You were the CEO of E t F dot com.

792
00:44:09,320 --> 00:44:13,520
Speaker 1: We've already discussed how the industry has begun to mature

793
00:44:13,640 --> 00:44:18,080
Speaker 1: and change since your involvement, and will will note that's

794
00:44:18,080 --> 00:44:21,960
Speaker 1: a correlation, maybe not a precise causation. But I have

795
00:44:22,080 --> 00:44:24,719
Speaker 1: to ask one of my favorite questions with anybody working

796
00:44:24,760 --> 00:44:27,759
Speaker 1: in E t F. Are there e t fs that

797
00:44:27,880 --> 00:44:35,799
Speaker 1: exist today that you think should not exist? Should not exist? Um? Yes, okay, yes,

798
00:44:35,920 --> 00:44:37,680
Speaker 1: and I know exactly what you're gonna say, but go ahead,

799
00:44:37,719 --> 00:44:40,279
Speaker 1: what is it? Volatility t F? Oh? Really, I'm wrong?

800
00:44:40,360 --> 00:44:41,960
Speaker 1: I didn't. That was really what did you want? What

801
00:44:42,320 --> 00:44:47,319
Speaker 1: I was expected? Like the three X inverse? Yeah, I don't.

802
00:44:47,320 --> 00:44:49,600
Speaker 1: I don't have a particular problem. I had more of

803
00:44:49,640 --> 00:44:51,439
Speaker 1: a problem with those when they first came out because

804
00:44:51,440 --> 00:44:54,839
Speaker 1: people didn't understand them. I feel that people understand them

805
00:44:54,880 --> 00:44:57,520
Speaker 1: now and the quality of disclosures and information around them

806
00:44:57,600 --> 00:45:00,600
Speaker 1: are better. My issue with volatility E T f s

807
00:45:01,080 --> 00:45:05,600
Speaker 1: is people still don't understand them. Uh, and they overwhelm

808
00:45:05,760 --> 00:45:10,080
Speaker 1: the actual volume of volatility futures, and there's massive contango

809
00:45:10,440 --> 00:45:13,920
Speaker 1: that just makes them. They're they're they're testing Zeno's paradox

810
00:45:13,960 --> 00:45:16,160
Speaker 1: of whether they can actually get to zero, and I

811
00:45:16,200 --> 00:45:18,200
Speaker 1: think they're doing so in harming and you can't just

812
00:45:18,280 --> 00:45:22,000
Speaker 1: go halfway. You don't that I don't know. We'll find out.

813
00:45:22,239 --> 00:45:26,560
Speaker 1: UM explain contango for people who don't understand sure. So

814
00:45:26,760 --> 00:45:28,840
Speaker 1: contango is when you buy a future, you're buying the

815
00:45:28,960 --> 00:45:30,520
Speaker 1: right to buy it at a future day. Let's say

816
00:45:30,560 --> 00:45:32,839
Speaker 1: thirty days in the future. Let's say oil to take

817
00:45:32,840 --> 00:45:36,160
Speaker 1: account example, is fifty dollars now the future maybe trading

818
00:45:36,200 --> 00:45:39,000
Speaker 1: at If you buy it at fifty five and the

819
00:45:39,160 --> 00:45:42,279
Speaker 1: spot price doesn't move from fifty over the next month,

820
00:45:42,360 --> 00:45:45,680
Speaker 1: that future is going to converge down to fifty, and

821
00:45:45,719 --> 00:45:48,399
Speaker 1: you're gonna lose five dollars. That's ten percent of your money.

822
00:45:48,840 --> 00:45:52,320
Speaker 1: The problem with volatility futures is that they almost always

823
00:45:52,440 --> 00:45:55,640
Speaker 1: trade in contango, and it is a very sharp contango,

824
00:45:56,000 --> 00:45:59,600
Speaker 1: and so you're losing not just a couple percent, you

825
00:45:59,680 --> 00:46:02,360
Speaker 1: maybe losing ten or of your money every month. And

826
00:46:02,480 --> 00:46:06,120
Speaker 1: I think people bought those with the thought, hey, volatility

827
00:46:06,200 --> 00:46:08,160
Speaker 1: is at record lows, it's going to go up. That

828
00:46:08,239 --> 00:46:12,960
Speaker 1: thought was right eventually, eventually, um. But what they didn't

829
00:46:12,960 --> 00:46:16,320
Speaker 1: realize is you're not buying VIX. You're buying VIX futures,

830
00:46:16,400 --> 00:46:19,239
Speaker 1: and there's just a massive delta between the words VIX

831
00:46:19,600 --> 00:46:22,960
Speaker 1: and VIX futures, and that delta is squashing investors. So

832
00:46:23,120 --> 00:46:26,799
Speaker 1: as long as I'm testing you, let's do backwardization. Backwardation

833
00:46:26,920 --> 00:46:29,200
Speaker 1: is the exact opposite. If oil is at fifty, you

834
00:46:29,239 --> 00:46:31,399
Speaker 1: buy it at forty five. As long as the spot

835
00:46:31,440 --> 00:46:34,279
Speaker 1: price stays at fifty, you make five dollars, which is whatever.

836
00:46:35,920 --> 00:46:39,160
Speaker 1: Uh And and that's a more positive situation. My issue

837
00:46:39,200 --> 00:46:41,080
Speaker 1: with e t f s and all these futures based

838
00:46:41,120 --> 00:46:44,920
Speaker 1: ETFs is a lot of they're available to all retail investors,

839
00:46:45,320 --> 00:46:48,360
Speaker 1: and retail investors may think I'm buying oil that's the

840
00:46:48,480 --> 00:46:51,239
Speaker 1: spot number that I see on TV, and that's not

841
00:46:51,360 --> 00:46:54,440
Speaker 1: you're buying oil futures. Now it's disclosed and disclaimed. Uh.

842
00:46:54,520 --> 00:46:57,480
Speaker 1: And I'm generally in favor of ETFs existing in these markets,

843
00:46:57,520 --> 00:47:00,480
Speaker 1: and and probably they should even exist in volatile but

844
00:47:00,600 --> 00:47:05,040
Speaker 1: the educational burden required is massive, or else mom and

845
00:47:05,080 --> 00:47:06,880
Speaker 1: Pop can buy them and get crushed. So now they

846
00:47:06,920 --> 00:47:09,400
Speaker 1: are a different gold DTF. You mentioned g l D.

847
00:47:10,880 --> 00:47:13,160
Speaker 1: Am I misunderstand that I'm on the impression g l

848
00:47:13,239 --> 00:47:18,040
Speaker 1: D represents physical gold held in volts it owns. But

849
00:47:18,160 --> 00:47:19,920
Speaker 1: there are other e t F and I don't remember

850
00:47:20,000 --> 00:47:24,200
Speaker 1: which that are actually trading gold futures, not buying the gold.

851
00:47:24,320 --> 00:47:26,560
Speaker 1: That's right. Uh. And some of these are leveraged and

852
00:47:26,680 --> 00:47:29,840
Speaker 1: some of them are inverse, etcetera. That's that's exactly right.

853
00:47:29,920 --> 00:47:32,239
Speaker 1: So when you get into leverage, you may well use

854
00:47:32,280 --> 00:47:35,120
Speaker 1: futures to get those leverage. There may even be one

855
00:47:35,400 --> 00:47:37,960
Speaker 1: x gold futures et s. I'm not sure. I don't

856
00:47:38,000 --> 00:47:40,640
Speaker 1: know why anyone would buy gold always trades at a

857
00:47:40,680 --> 00:47:43,359
Speaker 1: persistent entango that's about equal to the risk free rate.

858
00:47:43,440 --> 00:47:45,680
Speaker 1: So you're just losing a little bit of money. Um.

859
00:47:45,920 --> 00:47:48,160
Speaker 1: The one advantage it would give you is is their

860
00:47:48,239 --> 00:47:50,760
Speaker 1: taxes futures, which if you hold them for short periods

861
00:47:50,760 --> 00:47:53,640
Speaker 1: of time, is a beneficial tax treatment. So there may

862
00:47:53,680 --> 00:47:56,479
Speaker 1: be a tax angle for short term traders of gold.

863
00:47:57,320 --> 00:48:03,560
Speaker 1: That's kind of um. So, so that's one particular e

864
00:48:03,719 --> 00:48:06,920
Speaker 1: t F um that you don't think I ort to exist.

865
00:48:08,400 --> 00:48:11,640
Speaker 1: I was wanted to steer the conversation a slightly different directions.

866
00:48:11,640 --> 00:48:14,600
Speaker 1: So let me throw this at you. How do you

867
00:48:15,080 --> 00:48:19,320
Speaker 1: look at the Darwinian process of all these e t

868
00:48:19,560 --> 00:48:23,799
Speaker 1: F s coming out each year, most of which don't survive. Yeah,

869
00:48:23,880 --> 00:48:26,160
Speaker 1: I think that's great. I think that's great. If you

870
00:48:26,239 --> 00:48:29,560
Speaker 1: didn't have that process, you wouldn't have a significant you

871
00:48:29,560 --> 00:48:32,200
Speaker 1: wouldn't have the e t F industry for starters, right,

872
00:48:32,280 --> 00:48:35,399
Speaker 1: the e t F industry really uh in real life

873
00:48:35,560 --> 00:48:37,440
Speaker 1: was launched at b g I. When they launched a

874
00:48:37,520 --> 00:48:39,319
Speaker 1: huge number of e t F s, it wiped out

875
00:48:39,360 --> 00:48:41,440
Speaker 1: bonuses at b g I for three years. All the

876
00:48:41,560 --> 00:48:44,200
Speaker 1: executives were angry, but they were like, let's give this

877
00:48:44,320 --> 00:48:47,200
Speaker 1: a shot, and and all of the a lot of

878
00:48:47,239 --> 00:48:48,960
Speaker 1: the e t F that we take for granted today,

879
00:48:49,560 --> 00:48:51,840
Speaker 1: we're spaghetti on the wall like a lot of factory

880
00:48:51,960 --> 00:48:54,520
Speaker 1: t f s low volatility e t F s um

881
00:48:55,040 --> 00:49:00,400
Speaker 1: So you can't get innovation without some misses. And so

882
00:49:00,560 --> 00:49:04,440
Speaker 1: I'm fine with them being launched and closed. So what

883
00:49:04,680 --> 00:49:07,680
Speaker 1: what is Jeff Bezos's comment if if you're not failing,

884
00:49:07,760 --> 00:49:10,120
Speaker 1: you're not taking any risks. If that's exactly right, you

885
00:49:10,200 --> 00:49:13,440
Speaker 1: have to at least try and just recognize we don't

886
00:49:13,480 --> 00:49:16,400
Speaker 1: know what's gonna work, but we won't know until it

887
00:49:16,760 --> 00:49:19,080
Speaker 1: until we you know, put up the flag, pas, until

888
00:49:19,120 --> 00:49:21,239
Speaker 1: we give it a shot. And you know, the first

889
00:49:21,360 --> 00:49:24,960
Speaker 1: the first article about all the e t F s

890
00:49:25,000 --> 00:49:28,200
Speaker 1: needing to exist, I think ran I'm gonna get this wrong.

891
00:49:28,239 --> 00:49:30,320
Speaker 1: I think it ran in Investment News in two thousand

892
00:49:30,360 --> 00:49:32,920
Speaker 1: and three. They're like, we've reached the end of e

893
00:49:33,040 --> 00:49:35,680
Speaker 1: t F innovation and development. You can already buy stocks

894
00:49:35,719 --> 00:49:38,279
Speaker 1: and bonds and that was like that was it? Uh?

895
00:49:38,320 --> 00:49:40,680
Speaker 1: And those those have appeared over and over and over again,

896
00:49:40,760 --> 00:49:43,239
Speaker 1: So never discount. I don't think we'll ever get to

897
00:49:43,320 --> 00:49:45,200
Speaker 1: the end of ETF And so let me ask you

898
00:49:45,520 --> 00:49:49,479
Speaker 1: a different version. It seems that and you'll your geek

899
00:49:49,560 --> 00:49:54,239
Speaker 1: so you'll appreciate this. We don't have a Gaussian distribution

900
00:49:54,640 --> 00:49:58,800
Speaker 1: of firms and assets. It's say, very much a fathead

901
00:49:58,840 --> 00:50:02,160
Speaker 1: long tail where you have the big four, really the

902
00:50:02,200 --> 00:50:06,800
Speaker 1: big three, Vanguard, black Rock, State Street. I'm trying to

903
00:50:06,840 --> 00:50:11,279
Speaker 1: even think who is the next closest after them, and

904
00:50:11,440 --> 00:50:14,799
Speaker 1: that's you get down the spectrum, I mean, your your

905
00:50:14,840 --> 00:50:17,600
Speaker 1: power law distribution is it's three, and then it begins

906
00:50:17,640 --> 00:50:21,960
Speaker 1: to fall off pretty rapidly. Why have only three companies

907
00:50:22,080 --> 00:50:27,120
Speaker 1: captured so much of the investing public's mind share and

908
00:50:28,000 --> 00:50:31,680
Speaker 1: assets and the actual dollars share? Black Rock is six

909
00:50:31,760 --> 00:50:34,520
Speaker 1: trillion going on seven trillion, Vanguard is five on the

910
00:50:34,560 --> 00:50:37,960
Speaker 1: way to six trillion with a T. Why is it

911
00:50:38,080 --> 00:50:40,719
Speaker 1: just a handful of companies that seem to be the

912
00:50:40,800 --> 00:50:43,560
Speaker 1: biggest winners in this space? Because ETFs are a natural

913
00:50:43,680 --> 00:50:47,759
Speaker 1: monopoly system, unlike traditional active mutual funds. In active mutual funds,

914
00:50:47,800 --> 00:50:50,719
Speaker 1: you need a Cambrian explosion, different guys trying different things.

915
00:50:51,000 --> 00:50:53,960
Speaker 1: In e t F land, a large liquid ETF is

916
00:50:54,040 --> 00:50:56,840
Speaker 1: better than a small, illiquid ETF. So if you already

917
00:50:56,920 --> 00:51:00,520
Speaker 1: have good exposure to the SNP five, you don't really

918
00:51:00,600 --> 00:51:03,680
Speaker 1: need other funds. Now other funds have popped up because

919
00:51:03,719 --> 00:51:06,560
Speaker 1: you get distribution in different channels. There may be two

920
00:51:06,719 --> 00:51:09,360
Speaker 1: or three e t f s offering broad based exposure,

921
00:51:09,640 --> 00:51:12,840
Speaker 1: but you're going to see severe concentration in e t

922
00:51:13,000 --> 00:51:16,160
Speaker 1: F assets as long as they're dominated by index exposure,

923
00:51:16,520 --> 00:51:18,480
Speaker 1: because larger is better in e t f s, and

924
00:51:18,600 --> 00:51:21,400
Speaker 1: that is a good thing for investors, and I think

925
00:51:21,440 --> 00:51:24,920
Speaker 1: it will persist maybe indefinitely and certainly for the next

926
00:51:24,960 --> 00:51:27,279
Speaker 1: ten years. So larger is better, and I'm going to

927
00:51:27,360 --> 00:51:31,840
Speaker 1: guess that's the function of a combination of scale, quality

928
00:51:32,280 --> 00:51:36,520
Speaker 1: and liquidity of those Yeah, scale it costs, right, It's

929
00:51:36,560 --> 00:51:38,360
Speaker 1: it's cheaper to run a large et F than it

930
00:51:38,440 --> 00:51:40,839
Speaker 1: is a small et F. There are just no advantages

931
00:51:41,120 --> 00:51:44,280
Speaker 1: to a small ETF. Now, small ETFs can be liquid

932
00:51:44,680 --> 00:51:47,800
Speaker 1: and they can do innovative things, but you can't launch

933
00:51:47,840 --> 00:51:50,560
Speaker 1: a me too e t F without a unique distribution

934
00:51:50,600 --> 00:51:55,000
Speaker 1: mechanism like trials Schwab has and expected to gain assets.

935
00:51:55,080 --> 00:51:58,200
Speaker 1: They will just all go mostly, not all, but mostly

936
00:51:58,280 --> 00:52:00,719
Speaker 1: they'll go to the large players. And that's why it's

937
00:52:00,719 --> 00:52:03,320
Speaker 1: a great business for for black Rock and Vanguarden and

938
00:52:03,440 --> 00:52:06,719
Speaker 1: State Street. Quite fascinating. I know I only have you

939
00:52:06,840 --> 00:52:09,480
Speaker 1: for a finite amount of time. Let's jump to my

940
00:52:09,760 --> 00:52:13,160
Speaker 1: favorite questions. And I'm gonna throw a few curve bowls

941
00:52:13,239 --> 00:52:16,800
Speaker 1: at you with this. Let's start. What's the most important

942
00:52:16,880 --> 00:52:22,600
Speaker 1: thing people don't know about Matt Hoagland's which is an

943
00:52:22,640 --> 00:52:26,640
Speaker 1: inside joe about Matt Hogan. Let's see, my career started

944
00:52:26,680 --> 00:52:30,680
Speaker 1: as a minor league baseball mascot. Uh. Yeah, I was

945
00:52:30,719 --> 00:52:34,839
Speaker 1: a nine ft seal for the double A Portland's Sea Dogs. Um. Now,

946
00:52:34,960 --> 00:52:37,879
Speaker 1: I I say that in jest. My career path has

947
00:52:37,880 --> 00:52:41,759
Speaker 1: been very unusual. I've been a speechwriter, I've worked in biotech,

948
00:52:41,880 --> 00:52:44,680
Speaker 1: I've been a biotech portfolio manager. I ran et f

949
00:52:44,760 --> 00:52:48,799
Speaker 1: dot com, now I'm in crypto. Um. All those are

950
00:52:48,880 --> 00:52:52,320
Speaker 1: only united by the the how much I like to

951
00:52:52,440 --> 00:52:55,799
Speaker 1: talk about things that seem complex. Um. But but that's

952
00:52:55,840 --> 00:52:57,960
Speaker 1: the new unique thing about my career. It's been very

953
00:52:58,640 --> 00:53:02,960
Speaker 1: varied over time. Well, well that's uh, that's certainly interesting enough.

954
00:53:03,960 --> 00:53:07,680
Speaker 1: Why is this lighting up? Um? Tell us about your

955
00:53:07,760 --> 00:53:12,719
Speaker 1: early mentors who helped shape this serpentine career of yours. Yeah.

956
00:53:12,800 --> 00:53:15,239
Speaker 1: The number one person who comes to mind is a

957
00:53:15,320 --> 00:53:18,760
Speaker 1: former guest of yours, which is Dave Nodding. Dave Nodding

958
00:53:18,920 --> 00:53:21,200
Speaker 1: hired me when I was a minor league mascot to

959
00:53:21,320 --> 00:53:24,760
Speaker 1: become a biotech analyst at the at the transparent mutual

960
00:53:24,840 --> 00:53:29,279
Speaker 1: fund he was running at the time, Macro Meta Markets Market. Yeah,

961
00:53:29,400 --> 00:53:32,200
Speaker 1: we ran open Fund, which was the first mutual fund

962
00:53:32,280 --> 00:53:35,800
Speaker 1: to disclose its trades in real time, way ahead of

963
00:53:35,800 --> 00:53:38,680
Speaker 1: the way ahead of it. We had live video where

964
00:53:38,719 --> 00:53:41,920
Speaker 1: you could watch us trade. Um and and I learned

965
00:53:41,920 --> 00:53:44,920
Speaker 1: a lot of things from Dave. Uh. He continues to

966
00:53:45,000 --> 00:53:46,839
Speaker 1: be a good friend and we've worked together at three

967
00:53:46,960 --> 00:53:52,040
Speaker 1: or four companies since. Um. He he taught me the

968
00:53:52,440 --> 00:53:55,600
Speaker 1: core importance of being honest with your colleagues when you

969
00:53:55,640 --> 00:53:57,400
Speaker 1: go to work. And I think the first company you

970
00:53:57,480 --> 00:54:00,200
Speaker 1: work for in a serious way and the first sin

971
00:54:00,280 --> 00:54:03,120
Speaker 1: you work for is really important in shaping how you

972
00:54:03,200 --> 00:54:06,680
Speaker 1: view the world and how how your career progresses. Interesting

973
00:54:06,920 --> 00:54:10,279
Speaker 1: and uh Dave is now with c BO when he

974
00:54:10,480 --> 00:54:12,520
Speaker 1: runs E t F dot com. Yeah, he sits in

975
00:54:12,600 --> 00:54:16,120
Speaker 1: my former seat. That's funny. So what in what let's

976
00:54:16,160 --> 00:54:20,120
Speaker 1: talk about investors one investors influenced the way you think

977
00:54:20,200 --> 00:54:24,080
Speaker 1: about things like E t F S or crypto. Yeah.

978
00:54:24,640 --> 00:54:28,240
Speaker 1: Jack Bogel uh Is is the only investor who really

979
00:54:28,960 --> 00:54:31,640
Speaker 1: matters to me. Maybe my grandfather a little bit, but

980
00:54:31,719 --> 00:54:33,680
Speaker 1: I'm one of the so I work in crypto, I'm

981
00:54:33,719 --> 00:54:35,880
Speaker 1: one of the most boring investors in the world. I

982
00:54:35,920 --> 00:54:39,040
Speaker 1: don't think I have traded my portfolio other to rebalance

983
00:54:39,440 --> 00:54:42,600
Speaker 1: in eight or nine years. Uh and sort of the

984
00:54:43,480 --> 00:54:47,360
Speaker 1: um the overwhelming math that Bogel presented right. I started

985
00:54:47,360 --> 00:54:49,760
Speaker 1: my career on the active side as an active biotech

986
00:54:49,800 --> 00:54:52,919
Speaker 1: analyst and then an active biotech portfolio manager. I learned

987
00:54:53,000 --> 00:54:56,720
Speaker 1: the hard way that active doesn't work, and so pivoting

988
00:54:56,760 --> 00:55:00,720
Speaker 1: into indexing and learning from Bogel UH set the stage

989
00:55:00,760 --> 00:55:02,720
Speaker 1: for my E T F career and set the stage

990
00:55:03,360 --> 00:55:06,879
Speaker 1: even for my crypto career. Although that probably makes Jack

991
00:55:06,960 --> 00:55:10,200
Speaker 1: Bogel want to throw his head against the wall and

992
00:55:10,520 --> 00:55:15,080
Speaker 1: also a prior guest one of my heroes. That's fantastic

993
00:55:15,160 --> 00:55:17,560
Speaker 1: to hear. So let's talk about books. What are some

994
00:55:17,840 --> 00:55:23,480
Speaker 1: of your favorite books, be they investing, non investing, fiction, nonfiction, crypto,

995
00:55:23,800 --> 00:55:26,600
Speaker 1: or other. I knew you would ask about books. I

996
00:55:26,680 --> 00:55:29,480
Speaker 1: was thinking about the most important books I've read. The

997
00:55:29,520 --> 00:55:32,880
Speaker 1: most important book to my life probably was a heartbreaking

998
00:55:32,920 --> 00:55:36,640
Speaker 1: work of staggering genius by Dave Eggers, who both writes

999
00:55:36,719 --> 00:55:39,799
Speaker 1: with unique clarity and also came at a time when

1000
00:55:39,840 --> 00:55:44,440
Speaker 1: I needed to rediscover my agency and ability to shape

1001
00:55:44,480 --> 00:55:46,000
Speaker 1: my life in the way that I wanted, and that

1002
00:55:46,160 --> 00:55:50,440
Speaker 1: was a very important book for me. Um after that, Uh,

1003
00:55:50,600 --> 00:55:53,840
Speaker 1: it's it's a weird amalgam of of a handful of

1004
00:55:54,280 --> 00:55:58,200
Speaker 1: poetry books and then whatever I've been reading most recently.

1005
00:55:58,320 --> 00:56:00,320
Speaker 1: So the book I've been reading most recent Lee is

1006
00:56:00,360 --> 00:56:03,440
Speaker 1: a History of California. I'm a transplant to California. I

1007
00:56:03,560 --> 00:56:10,080
Speaker 1: moved there ten years ago. Everybody a transplant, I basically it. Uh.

1008
00:56:10,160 --> 00:56:12,480
Speaker 1: And my kids are learning all about California history the

1009
00:56:12,520 --> 00:56:14,680
Speaker 1: same way I learned about Virginia history when I was

1010
00:56:14,719 --> 00:56:17,480
Speaker 1: a kid. At the time, I thought that was just history,

1011
00:56:17,800 --> 00:56:19,719
Speaker 1: But it turns out you learned different things depending where

1012
00:56:19,760 --> 00:56:21,520
Speaker 1: you grow up. What's the name of the book. It's

1013
00:56:21,560 --> 00:56:24,680
Speaker 1: named California. Uh. And I'll tell one little anecdote from

1014
00:56:24,719 --> 00:56:27,839
Speaker 1: it that that that empowered me. If you go to California,

1015
00:56:27,840 --> 00:56:30,480
Speaker 1: it looks like sort of the especially southern California, it

1016
00:56:30,560 --> 00:56:33,000
Speaker 1: looks like the Mediterranean. All the houses are in these

1017
00:56:33,080 --> 00:56:36,920
Speaker 1: Mediterranean styles. And I assume this was organic, but in

1018
00:56:37,120 --> 00:56:41,000
Speaker 1: fact it wasn't. It all started uh in in in

1019
00:56:41,120 --> 00:56:44,120
Speaker 1: Santa Barbara, when Santa Barbara burned to the ground. And

1020
00:56:44,200 --> 00:56:49,600
Speaker 1: at the time it was twenties, Okay, at the time,

1021
00:56:50,160 --> 00:56:52,000
Speaker 1: there was a lot of advertising to get people to

1022
00:56:52,040 --> 00:56:54,960
Speaker 1: move out there, and people were deliberately casting it as

1023
00:56:55,040 --> 00:56:58,200
Speaker 1: the Mediterranean of the Americas, and so they built it

1024
00:56:58,360 --> 00:57:01,400
Speaker 1: in its physical presence to look like that. And what

1025
00:57:01,600 --> 00:57:03,960
Speaker 1: that reminded me of was something that I had forgotten,

1026
00:57:04,000 --> 00:57:06,960
Speaker 1: which is the importance of narrative in the ability to

1027
00:57:07,040 --> 00:57:09,920
Speaker 1: shape reality and how how being able to define and

1028
00:57:10,040 --> 00:57:12,920
Speaker 1: see what it could be actually can lead to physical

1029
00:57:13,040 --> 00:57:16,040
Speaker 1: developments that that become entrenched and just become a part

1030
00:57:16,080 --> 00:57:18,240
Speaker 1: of society. And I thought that was an interesting life

1031
00:57:18,280 --> 00:57:21,920
Speaker 1: immenstating art there you go, exactly interesting. And as long

1032
00:57:22,000 --> 00:57:25,560
Speaker 1: as you mentioned poetry, Yeah, we're a very um hip

1033
00:57:26,000 --> 00:57:29,680
Speaker 1: audience of listeners. Give us, uh, what's your who's your

1034
00:57:29,720 --> 00:57:34,280
Speaker 1: favorite poet or their favorite Well, yeah, August Klein's Dollars,

1035
00:57:34,640 --> 00:57:37,000
Speaker 1: Red Sauce, Whiskey and Snow is one of my favorite

1036
00:57:37,040 --> 00:57:40,520
Speaker 1: books of poetry. I think Red Sauce, Whiskey and Snow. Yeah,

1037
00:57:40,560 --> 00:57:43,160
Speaker 1: I think about fifty of the poems and there are terrible,

1038
00:57:43,520 --> 00:57:46,280
Speaker 1: but the other fifty are seen with such clarity and

1039
00:57:46,400 --> 00:57:49,320
Speaker 1: with with the kind of emotional connections that really resonate

1040
00:57:49,400 --> 00:57:52,120
Speaker 1: with me. Uh that it's it's an important book to me,

1041
00:57:52,200 --> 00:57:56,080
Speaker 1: and I read it regularly. That is quite fascinating. Um,

1042
00:57:56,440 --> 00:57:58,760
Speaker 1: So I have to ask. This is a question I

1043
00:58:00,200 --> 00:58:04,320
Speaker 1: we were talking about earlier, and I'm actually debating making

1044
00:58:04,400 --> 00:58:08,160
Speaker 1: this a regular question because our conversation about it was

1045
00:58:08,200 --> 00:58:12,640
Speaker 1: so fascinating. But what was your first car? My first

1046
00:58:12,760 --> 00:58:17,360
Speaker 1: car was a terrible as I said earlier, a terrible choice.

1047
00:58:17,800 --> 00:58:20,560
Speaker 1: I bought a Volkswagen Jetta shortly after I got my

1048
00:58:20,640 --> 00:58:23,760
Speaker 1: first job, and that was the disaster in like nine

1049
00:58:23,880 --> 00:58:29,000
Speaker 1: different ways. Really because my experience with Volkswagens, and this

1050
00:58:29,200 --> 00:58:32,800
Speaker 1: might have been cars of a different year of the sixties, eighties, whatever,

1051
00:58:33,360 --> 00:58:35,840
Speaker 1: they were indestructible. I had a VW Bug with three

1052
00:58:35,920 --> 00:58:39,920
Speaker 1: hundred thousand miles. My roommates Volkswagen Golf. We would just

1053
00:58:40,040 --> 00:58:42,680
Speaker 1: take it apart and swap out parts. I need a

1054
00:58:42,760 --> 00:58:45,960
Speaker 1: new fender and just take the old one to the junkyard. Hey,

1055
00:58:46,040 --> 00:58:49,800
Speaker 1: I need one of these five dollars like, you can't

1056
00:58:49,840 --> 00:58:52,560
Speaker 1: do that anymore. But they were pretty indestructible. Why was

1057
00:58:52,600 --> 00:58:55,680
Speaker 1: the Jetta so so? For two reasons. One, it was

1058
00:58:55,880 --> 00:59:00,440
Speaker 1: utterly destructible it constantly broke down, and to like it

1059
00:59:00,560 --> 00:59:03,600
Speaker 1: was an aspirational purchase, right, it was a poor man's

1060
00:59:03,920 --> 00:59:08,440
Speaker 1: uh's BMW you you improved on that with a poor

1061
00:59:08,480 --> 00:59:12,080
Speaker 1: men company? Yeah? Uh so. So I bought it because

1062
00:59:12,120 --> 00:59:14,840
Speaker 1: I thought, I'm a biotech portfolio manager. I need this

1063
00:59:15,000 --> 00:59:17,919
Speaker 1: nice new car. I could have done so many better

1064
00:59:18,160 --> 00:59:22,320
Speaker 1: things with that money than by this terrible car with

1065
00:59:22,480 --> 00:59:26,000
Speaker 1: a poor historical track record of reliability, which I knew

1066
00:59:26,080 --> 00:59:28,360
Speaker 1: when I bought it. But I liked the way it looked,

1067
00:59:28,400 --> 00:59:31,600
Speaker 1: and it was the people I was around owned Volkswagen Jettas,

1068
00:59:31,600 --> 00:59:33,400
Speaker 1: and I bought it. Uh And it was just a

1069
00:59:33,560 --> 00:59:36,880
Speaker 1: yoke on my neck until I finally sold it. That's

1070
00:59:37,000 --> 00:59:39,840
Speaker 1: very that's very funny. So, um, tell us about a

1071
00:59:39,920 --> 00:59:43,160
Speaker 1: time you failed and what you learned from the experience. Yeah.

1072
00:59:43,600 --> 00:59:46,880
Speaker 1: Uh So. When I was a biotech portfolio manager at

1073
00:59:46,920 --> 00:59:51,240
Speaker 1: open Fund, I bought a company called Titan Pharmaceuticals, which

1074
00:59:51,280 --> 00:59:52,880
Speaker 1: had a drug in front of the f D A.

1075
00:59:53,120 --> 00:59:56,600
Speaker 1: This is this is two thousand was when I think

1076
00:59:56,600 --> 01:00:00,280
Speaker 1: I made this purchase. Biotechs obviously a binary I'll come

1077
01:00:00,320 --> 01:00:02,640
Speaker 1: at the f D A uh And it went against

1078
01:00:02,720 --> 01:00:04,960
Speaker 1: me and I lost a huge amount of money, uh

1079
01:00:05,120 --> 01:00:07,840
Speaker 1: for the company. And I learned two really important things

1080
01:00:07,880 --> 01:00:10,400
Speaker 1: from that. When it happened, I thought I was gonna

1081
01:00:10,440 --> 01:00:13,160
Speaker 1: get fired because I was new to the job. And

1082
01:00:13,280 --> 01:00:15,520
Speaker 1: I just lost like two million dollars for the for

1083
01:00:15,640 --> 01:00:17,760
Speaker 1: the fund, which to me at the time having been

1084
01:00:17,840 --> 01:00:21,400
Speaker 1: a more money than more money than God uh. And no.

1085
01:00:21,760 --> 01:00:24,120
Speaker 1: One of the things I learned from my mentor Dave

1086
01:00:24,200 --> 01:00:26,560
Speaker 1: Nodding was all you have to do is own up

1087
01:00:26,600 --> 01:00:28,600
Speaker 1: to what went wrong and design a process so it

1088
01:00:28,640 --> 01:00:31,240
Speaker 1: doesn't happen again. And I did that and then just

1089
01:00:31,320 --> 01:00:32,960
Speaker 1: went on about my day. And I've used that with

1090
01:00:33,120 --> 01:00:36,560
Speaker 1: every subsequent failure in business, and it immediately clears the

1091
01:00:36,640 --> 01:00:38,720
Speaker 1: air and gets you on a better path. The other

1092
01:00:38,800 --> 01:00:42,120
Speaker 1: thing I learned, which was unique to investing in biotech

1093
01:00:42,200 --> 01:00:45,520
Speaker 1: but has application, was I had focused entirely on the

1094
01:00:45,600 --> 01:00:48,440
Speaker 1: wrong thing. So the sexy thing in biotech, the thing

1095
01:00:48,480 --> 01:00:51,480
Speaker 1: everyone talks about is does the drug work? And the

1096
01:00:52,160 --> 01:00:55,200
Speaker 1: the does drug work question for Titan was true, it

1097
01:00:55,280 --> 01:00:57,680
Speaker 1: seemed to work, but that is not what the FDA

1098
01:00:57,840 --> 01:01:00,240
Speaker 1: cares about. The FDA is a bunch of doctors, the

1099
01:01:00,320 --> 01:01:03,960
Speaker 1: hippocratic ghost says, first, do know, they care only about

1100
01:01:04,080 --> 01:01:07,640
Speaker 1: safety if it might work, but it's safe. They will

1101
01:01:07,720 --> 01:01:10,200
Speaker 1: prove it. This one there were risks, but there are

1102
01:01:10,240 --> 01:01:12,800
Speaker 1: also benefits, and they just shot it down and and

1103
01:01:12,880 --> 01:01:15,840
Speaker 1: it taught me that you have to frame things not

1104
01:01:16,080 --> 01:01:18,520
Speaker 1: from what you think is important, but what from the

1105
01:01:18,640 --> 01:01:21,600
Speaker 1: people who are in control of that I think is important.

1106
01:01:21,640 --> 01:01:26,320
Speaker 1: And in biotech that's safety. Efficacy is a distant second.

1107
01:01:26,720 --> 01:01:28,800
Speaker 1: And that's true like when I built the e t

1108
01:01:28,920 --> 01:01:31,200
Speaker 1: F conference. When you build an t F conference, you

1109
01:01:31,240 --> 01:01:33,120
Speaker 1: want to focus on what's going to go up the

1110
01:01:33,160 --> 01:01:36,040
Speaker 1: most the next year. Where should people invest? What financial

1111
01:01:36,080 --> 01:01:38,480
Speaker 1: advisors want to learn is how can I retain and

1112
01:01:38,560 --> 01:01:41,080
Speaker 1: grow up clients? Right? They want to know I want

1113
01:01:41,120 --> 01:01:42,840
Speaker 1: to make sure I don't get fired, and whether I

1114
01:01:42,880 --> 01:01:46,080
Speaker 1: can build a better portfolio is actually secondary to do

1115
01:01:46,200 --> 01:01:48,360
Speaker 1: I understand this, Can I talk about this? Will this

1116
01:01:48,440 --> 01:01:50,760
Speaker 1: help me win new clients? And sort of the ability

1117
01:01:50,840 --> 01:01:54,440
Speaker 1: to reframe what you think is important into what's actually

1118
01:01:54,480 --> 01:01:57,320
Speaker 1: important was an important lesson. So tell us what you

1119
01:01:57,400 --> 01:01:59,480
Speaker 1: do for fun? What do you do to relax or

1120
01:01:59,560 --> 01:02:02,080
Speaker 1: stay in ape outside of the office. Yeah, I'm a runner.

1121
01:02:02,320 --> 01:02:04,720
Speaker 1: I love to run, I love to hike, but I

1122
01:02:04,840 --> 01:02:08,160
Speaker 1: have uh, I have three kids, a wife who works,

1123
01:02:08,320 --> 01:02:10,200
Speaker 1: I work at a startup. I sit on boards. I

1124
01:02:10,240 --> 01:02:13,160
Speaker 1: have four chickens. Mostly I just try to keep all

1125
01:02:13,200 --> 01:02:15,920
Speaker 1: this plate spinning. But when I do get away, I

1126
01:02:16,040 --> 01:02:18,520
Speaker 1: like to I like to run or hike or be outside.

1127
01:02:18,640 --> 01:02:20,880
Speaker 1: So I'm gonna I'm gonna back you up a little

1128
01:02:20,920 --> 01:02:25,480
Speaker 1: bit because slipped into that whole running hiking family thing. Yeah,

1129
01:02:25,960 --> 01:02:29,640
Speaker 1: was something about chickens. Chickens. Yeah, yeah, So we went

1130
01:02:29,720 --> 01:02:31,640
Speaker 1: to the feed store with the kids to get some

1131
01:02:31,800 --> 01:02:33,680
Speaker 1: hay because we thought it'd be cute to have hay

1132
01:02:33,760 --> 01:02:36,600
Speaker 1: bales for a party for people to sit on. And

1133
01:02:36,920 --> 01:02:39,560
Speaker 1: in the feed store where two day old chicks, kids

1134
01:02:39,560 --> 01:02:43,360
Speaker 1: are very just sitting near near the They're adorable, so adorable,

1135
01:02:43,640 --> 01:02:46,880
Speaker 1: And so we brought home. I was convinced to bring

1136
01:02:46,960 --> 01:02:50,120
Speaker 1: home four chicks. Uh. They cost three dollars and seventy

1137
01:02:50,160 --> 01:02:53,640
Speaker 1: five cents each. If you want to know what chicks cost. Um, Yeah,

1138
01:02:53,720 --> 01:02:56,040
Speaker 1: I actually buy them by the dozen and it's a

1139
01:02:56,120 --> 01:02:59,840
Speaker 1: dollar rating nine. Well I should have learned. Um, Now

1140
01:03:00,120 --> 01:03:02,640
Speaker 1: they're two and a half months old. Uh. Now we've

1141
01:03:02,680 --> 01:03:04,960
Speaker 1: invested money in a chicken coop. The first egg that

1142
01:03:05,040 --> 01:03:06,480
Speaker 1: we get, which will be in like a month and

1143
01:03:06,520 --> 01:03:08,520
Speaker 1: a half, it's going to cost me about two thousand

1144
01:03:08,600 --> 01:03:15,439
Speaker 1: dollars and better. The chickens are great. The chickens are great.

1145
01:03:16,640 --> 01:03:18,760
Speaker 1: Can you interact with them as a pet or they

1146
01:03:18,880 --> 01:03:22,560
Speaker 1: just dumb a little dinosaurs running around. Actually they're very nice.

1147
01:03:22,920 --> 01:03:25,600
Speaker 1: They're very nice. I mean they feed them. They should

1148
01:03:25,640 --> 01:03:27,640
Speaker 1: be feed them. They like you. They each have their

1149
01:03:27,640 --> 01:03:33,640
Speaker 1: own personalities, Uh, distinct like you, noticeably different. You have

1150
01:03:33,720 --> 01:03:35,400
Speaker 1: the nice guys, you have sort of the sort of

1151
01:03:35,480 --> 01:03:38,840
Speaker 1: mean guys. They do different things. Um, they all look

1152
01:03:38,880 --> 01:03:41,560
Speaker 1: different because they're different breeds. Uh. They have a half

1153
01:03:41,600 --> 01:03:44,400
Speaker 1: life when you pick them up of about ninety seconds.

1154
01:03:44,760 --> 01:03:47,400
Speaker 1: If you hold them for more than ninety seconds, uh,

1155
01:03:47,600 --> 01:03:50,080
Speaker 1: they start to poop everywhere. And so you can pick

1156
01:03:50,120 --> 01:03:52,000
Speaker 1: them up and they're very cute, but the clock starts

1157
01:03:52,000 --> 01:03:54,240
Speaker 1: ticking them. You gotta like, you gotta put them down

1158
01:03:54,360 --> 01:03:57,680
Speaker 1: before disaster happens. That's hilarious. When when I lived in

1159
01:03:57,720 --> 01:04:00,960
Speaker 1: the city or next door neighbors had dozens of birds,

1160
01:04:01,520 --> 01:04:05,080
Speaker 1: and they had a cockatoo that was a baby. And

1161
01:04:05,440 --> 01:04:08,919
Speaker 1: when they would go away, you know, the one bird

1162
01:04:09,000 --> 01:04:13,120
Speaker 1: that needed attention was gonzo. So we would babysit this

1163
01:04:13,320 --> 01:04:17,280
Speaker 1: cockatoo and even at like a year old, I would

1164
01:04:17,360 --> 01:04:20,000
Speaker 1: hold him on my arm. He would put his wing

1165
01:04:20,080 --> 01:04:22,480
Speaker 1: around me and the two of us would watch TV.

1166
01:04:22,800 --> 01:04:27,280
Speaker 1: There you go, And he truly had a personality. He

1167
01:04:27,480 --> 01:04:31,800
Speaker 1: was very smart. I taught him to laugh. But they're

1168
01:04:31,840 --> 01:04:37,400
Speaker 1: known as really intelligent birds. Chickens aren't necessarily have that

1169
01:04:37,480 --> 01:04:40,880
Speaker 1: same reputation. So I was curious about the personality. And yeah,

1170
01:04:41,360 --> 01:04:44,440
Speaker 1: they still have some personality. We haven't watched much TV together,

1171
01:04:44,560 --> 01:04:47,120
Speaker 1: but but they do have personally. And all the kids, Okay,

1172
01:04:47,240 --> 01:04:50,280
Speaker 1: when mom makes chicken for dinner, that hasn't been Oh oh,

1173
01:04:50,400 --> 01:04:52,800
Speaker 1: so my kids are vegetarians are so this has not

1174
01:04:52,960 --> 01:04:56,120
Speaker 1: come up there, Yeah, hasn't come up, but they're ready

1175
01:04:56,120 --> 01:04:58,160
Speaker 1: to eat the eggs. Hold on a sec. You're not.

1176
01:04:58,400 --> 01:05:02,200
Speaker 1: I'm a vegetarian. You are. I've had meals with you.

1177
01:05:02,600 --> 01:05:06,360
Speaker 1: So I'm an opportunistic vegetarian. So so, so my rule is,

1178
01:05:06,600 --> 01:05:11,520
Speaker 1: I'm a vegetarian unless around there's gonna beat at the table, right,

1179
01:05:11,640 --> 01:05:14,280
Speaker 1: unless it's going to be really exceptional or different. You

1180
01:05:14,400 --> 01:05:17,840
Speaker 1: have to experience the world. So that's fair, opportunistic vegetarian,

1181
01:05:18,040 --> 01:05:23,640
Speaker 1: that's absolutely fair. Um, So, our last two questions. If

1182
01:05:23,680 --> 01:05:26,160
Speaker 1: you were giving some advice to a millennial who was

1183
01:05:26,320 --> 01:05:30,880
Speaker 1: interested in a career of either finance or crypto. What

1184
01:05:31,040 --> 01:05:33,240
Speaker 1: sort of advice would you give them? How do you

1185
01:05:33,320 --> 01:05:40,880
Speaker 1: think they should approach either of those fields? Interesting? And

1186
01:05:40,920 --> 01:05:44,480
Speaker 1: I'm not asking which would you steer them? I'm asking, Hey,

1187
01:05:44,560 --> 01:05:47,000
Speaker 1: what advice would you give them if they came asking

1188
01:05:47,000 --> 01:05:50,040
Speaker 1: about that? Yeah? So either I would advise them, as

1189
01:05:50,120 --> 01:05:52,320
Speaker 1: I do most young people, to take some time off

1190
01:05:52,360 --> 01:05:54,680
Speaker 1: and go travel and play around while they're young before

1191
01:05:54,720 --> 01:05:57,160
Speaker 1: they get serious about their career. If they didn't take

1192
01:05:57,240 --> 01:06:00,200
Speaker 1: that advice, which I think is good advice, um, I

1193
01:06:00,200 --> 01:06:04,880
Speaker 1: would encourage them to think most about their company, the

1194
01:06:05,000 --> 01:06:09,320
Speaker 1: company they choose, and their direct manager, and think the

1195
01:06:09,640 --> 01:06:14,240
Speaker 1: least about their intro salary, or their title or even

1196
01:06:14,400 --> 01:06:16,760
Speaker 1: what work they're going to be doing. It's vastly more

1197
01:06:16,840 --> 01:06:20,600
Speaker 1: important to engage yourself with a well run company, uh

1198
01:06:20,720 --> 01:06:22,760
Speaker 1: and with a good manager where you can learn good

1199
01:06:22,800 --> 01:06:25,400
Speaker 1: work habits than it is to make an extra four

1200
01:06:25,480 --> 01:06:29,360
Speaker 1: thousand dollars a year or to have a particular job

1201
01:06:29,440 --> 01:06:31,960
Speaker 1: that focuses on one skill set or another. So so

1202
01:06:32,080 --> 01:06:35,640
Speaker 1: pick your company careful, pick your manager really carefully, uh,

1203
01:06:35,720 --> 01:06:38,440
Speaker 1: and ignore all the rest. Sounds like it sounds like

1204
01:06:38,480 --> 01:06:41,320
Speaker 1: pretty good advice. And our final question, what is it

1205
01:06:41,480 --> 01:06:44,320
Speaker 1: that you know about the world of investing today that

1206
01:06:44,480 --> 01:06:47,920
Speaker 1: you wish you knew twenty something years ago when you

1207
01:06:48,000 --> 01:06:52,760
Speaker 1: first began? Uh, that's a good question obviously by apples

1208
01:06:52,800 --> 01:06:56,520
Speaker 1: the easy answer um, or by bitcoin you know when

1209
01:06:56,560 --> 01:07:02,000
Speaker 1: it first come? Uh don't know? Or bitcoin at four thousand?

1210
01:07:02,160 --> 01:07:03,680
Speaker 1: Or do you mean if you had a time machine

1211
01:07:03,680 --> 01:07:06,440
Speaker 1: and could go by time machine? So that's an easy question.

1212
01:07:06,520 --> 01:07:09,720
Speaker 1: I'm asking no time machine, no time machine. What do

1213
01:07:09,800 --> 01:07:13,040
Speaker 1: you know today that you wish you knew back then?

1214
01:07:13,280 --> 01:07:16,600
Speaker 1: That I get? Okay, great question. U. I learned every

1215
01:07:16,760 --> 01:07:19,880
Speaker 1: hard knock investing lesson there is to learn, uh, And

1216
01:07:20,040 --> 01:07:22,160
Speaker 1: so I could tell you not to do those things

1217
01:07:22,240 --> 01:07:26,880
Speaker 1: like uh like don't confuse. Uh your your lucky pick

1218
01:07:26,920 --> 01:07:29,160
Speaker 1: of a stock that went up with true skill. Uh,

1219
01:07:29,360 --> 01:07:34,040
Speaker 1: don't sell when you feel the painful feeling in your gut.

1220
01:07:34,560 --> 01:07:36,360
Speaker 1: Just buy and holding, never sell. But you wouldn't listen,

1221
01:07:36,800 --> 01:07:40,320
Speaker 1: So UM, I guess it would be just buy things.

1222
01:07:40,800 --> 01:07:43,320
Speaker 1: Selling things is where everything goes asunder. Just just buy

1223
01:07:43,440 --> 01:07:46,200
Speaker 1: things and hold them, uh and sit on it forever.

1224
01:07:46,840 --> 01:07:50,520
Speaker 1: Quite fascinating. We have been speaking with Matt Hogan. He

1225
01:07:50,920 --> 01:07:56,960
Speaker 1: is the global strategist at bit Wise Asset Management, Global

1226
01:07:57,000 --> 01:08:00,280
Speaker 1: head of Research. If you enjoy this conversation, well look

1227
01:08:00,360 --> 01:08:02,840
Speaker 1: up an intro down an Inch on Apple iTunes and

1228
01:08:02,960 --> 01:08:05,360
Speaker 1: you can see any of the other two hundred and

1229
01:08:05,480 --> 01:08:09,560
Speaker 1: fifties such conversations we've had over the past five or

1230
01:08:09,600 --> 01:08:14,520
Speaker 1: so years. Uh, you can find that at iTunes, Stitcher, overcast,

1231
01:08:14,560 --> 01:08:18,519
Speaker 1: Bloomberg dot com, wherever your final podcasts are sold. We

1232
01:08:18,640 --> 01:08:22,160
Speaker 1: love your comments, feedback and suggestions right to us at

1233
01:08:22,960 --> 01:08:26,320
Speaker 1: m IB podcast at Bloomberg dot net. I would be

1234
01:08:26,400 --> 01:08:28,960
Speaker 1: remiss if I did not thank the crack staff that

1235
01:08:29,040 --> 01:08:33,280
Speaker 1: helps put together this conversation each week. Carol and O'Brien

1236
01:08:33,560 --> 01:08:39,120
Speaker 1: is my audio engineer. Par Excellent Medina Parwana is our producer.

1237
01:08:39,600 --> 01:08:43,760
Speaker 1: Taylor Riggs is our booker slash producer. Atika vl Broun

1238
01:08:44,280 --> 01:08:47,559
Speaker 1: is our project manager. Michael bat Nick is my head

1239
01:08:47,600 --> 01:08:51,920
Speaker 1: of research. I'm Barry Retults. You've been listening to Masters

1240
01:08:51,960 --> 01:09:01,560
Speaker 1: in Business on Bloomberg Radio Thinks