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Speaker 1: Hello, and welcome to What Goes Up, a weekly markets podcast.

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Speaker 1: My name is Mike Reagan and I'm a senior editor

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Speaker 1: at Bloomberg. This week on the show, has all this

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Speaker 1: rotation made you see sick? Yet? Earlier this year was

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Speaker 1: the massive rotation out of big tech and other growth

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Speaker 1: stocks and into more cyclical and value oriented stocks. But

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Speaker 1: a whip of hawkishness from the Federal Reserve has caused

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Speaker 1: everyone to sort of jumped back to the other side

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Speaker 1: of the boat again and growth is outperforming once again,

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Speaker 1: at least for now. Now some people are saying the

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Speaker 1: market is falling for a head fake from the Fed.

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Speaker 1: But we want to get into it with the head

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Speaker 1: strategist at a major pioneering quantitative fund manager. But first

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Speaker 1: I want to bring in our co host. And sorry

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Speaker 1: to all the Charlie Pellet fans out there, but no

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Speaker 1: Charlie Pellet intro this this week. And that's because as

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Speaker 1: this co host is, there's no mystery about her. She's

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Speaker 1: been on the show before and gotten to Charlie Pellet treatment.

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Speaker 1: Her name is vill Donna hi Rich. She is a

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Speaker 1: cross asset reporter at Bloomberg. Vill Donna, what do you

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Speaker 1: have to say for yourself, well, I wouldn't be opposed

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Speaker 1: if we had another Charlie Pellet treatment. Here you are.

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Speaker 1: You're disappointed, aren't you? Everyone loves the Charlie Charlie. All right,

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Speaker 1: I'm sorry. I apologize next time, but I will put

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Speaker 1: out Vill Donna, as many of you know, is what

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Speaker 1: I consider the chief crazy things correspondent for what goes up.

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Speaker 1: Many of the crazy things I've brought to the show

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Speaker 1: have been courtesy of Bill Donna. You're actually very sane

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Speaker 1: and level headed for someone who is such an expert

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Speaker 1: in crazy things. Though, I gotta say they're just really

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Speaker 1: interesting to read. And I have what I think is

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Speaker 1: a pretty good one you know today. Okay, good, I

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Speaker 1: got a good one. So hopefully we don't have the

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Speaker 1: same one that that would be awkward, and by all means,

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Speaker 1: if you see something crazy, a reminder that we have

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Speaker 1: a podcast hotline that's just sitting here waiting for you

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Speaker 1: to leave us a voicemail. Vil Donna, our our old

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Speaker 1: friends Sarah promised she would call the hotline and leave

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Speaker 1: us some crazy things. But um alas so far, I'm

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Speaker 1: like a kid on Christmas checking the voicemail and I'm

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Speaker 1: nothing in my stocking. But I'm thinking maybe she's just

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Speaker 1: forgotten the numbers, so I'll give the number. It's uh

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Speaker 1: six four or six three two four three four nine.

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Speaker 1: Oh so, please don't give us a call, leave us

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Speaker 1: a voicemail and maybe we'll play it on the show.

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Speaker 1: But let's get to that. Guest, as I said, he

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Speaker 1: is the head of investment strategists at a big fund manager,

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Speaker 1: uh that manages about six d and thirty seven billion

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Speaker 1: dollars in assets. His name is West Krill, head strategist

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Speaker 1: at Dimensional Fund Advisors. West, Welcome to the show, excited

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Speaker 1: to be here, Thanks for having me today. Absolutely absolutely, West,

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Speaker 1: I've got good news. I'm gonna start off with what

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Speaker 1: we call in the industry, a softball question for you,

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Speaker 1: uh so, so that's my gift to you today. But

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Speaker 1: I'm just want to talk a little bit from your

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Speaker 1: perspective about the approach Dimensional takes to investing. Now. Obviously,

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Speaker 1: Dement sal as I said in the intro, considered a

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Speaker 1: very pioneering firm that was sort of one of the

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Speaker 1: first to be at the intersection of kind of the

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Speaker 1: academic thinking about markets and actually managing money using those

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Speaker 1: types of approaches. In the real world. For example, the

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Speaker 1: founders studied under Eugene Fama and Kenneth's French Um. But

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Speaker 1: I'm curious just for you to explain to us what

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Speaker 1: is dimensionals approach to investing. Yeah, of course, So you know,

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Speaker 1: we're founded in nineteen eighty one and we've always been

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Speaker 1: built on implementing the great ideas in finance, and to

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Speaker 1: your point, you know, a lot of that is cultivating

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Speaker 1: these deep connections with some of the luminaries in the

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Speaker 1: academic world Fama and French, like you mentioned, Robert Merton,

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Speaker 1: Robert Novi, Mars. So that's been really instrumental in the

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Speaker 1: way that we've built our firm. And then a central

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Speaker 1: tenant to our investment philosophy is our deep seated belief

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Speaker 1: in markets. So what that means is when we go

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Speaker 1: to UH seek to outperform markets, we do so not

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Speaker 1: by trying to outguess market prices and figure out where

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Speaker 1: they've gone wrong, but by emphasizing certain groups of securities

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Speaker 1: with higher expected returns based on research, very rigorous research

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Speaker 1: from the academic community. And of course you know, we

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Speaker 1: have a fanatical emphasis on the role of implementation. We

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Speaker 1: feel that's a really critical level of expertise to have

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Speaker 1: when you're trying to translate these ideas from the academic

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Speaker 1: world into real world value add investments for our clients.

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Speaker 1: I know you guys recently converted a bunch of your

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Speaker 1: mutual funds into e t s and it was a

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Speaker 1: really big deal in the world of ets, and I'd

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Speaker 1: love to chat about that in a second, but maybe

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Speaker 1: you can tell us a little bit about what types

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Speaker 1: of things your clients and people who've been having conversations

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Speaker 1: with recently have been asking you about them what's been

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Speaker 1: on their minds? And I asked, because I'm thinking of

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Speaker 1: all of the fund manager surveys and all these different

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Speaker 1: surveys that we tend to see from from week to week,

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Speaker 1: where some of the topics recently, I feel like have

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Speaker 1: been changing. Where the virus used to be at the

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Speaker 1: top of of mind for a lot of people and

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Speaker 1: it's sort of fallen off and now it's more fed

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Speaker 1: and questions around inflation, yes, certainly, I mean those come

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Speaker 1: up in conversations. I would say the foremost conversation topic

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Speaker 1: for us, and this has been the case really for years,

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Speaker 1: is the performance of small cat value versus large cap growth,

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Speaker 1: And you know, it's been interesting as you've sort of

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Speaker 1: seen a cee saw in terms of the sentiment behind

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Speaker 1: those questions. For a while, it was, you know, small

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Speaker 1: cap value underperforming large growth concerns around that, and then

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Speaker 1: when you had small cat value coming roaring back and

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Speaker 1: people would start to ask how much longer can this last?

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Speaker 1: And then you know, now you see that at least

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Speaker 1: in this past quarter as small value has been underperforming

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Speaker 1: large growth again. So you know, I think it reinforces

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Speaker 1: a couple of different billion points for investors investors to

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Speaker 1: keep in mind. The first is just the uncertainty around

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Speaker 1: these premiums. So you know, the premise behind the small

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Speaker 1: cat value stocks having higher expectory turns in the market

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Speaker 1: is a very simple one. It's the idea that you're

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Speaker 1: paying less for a stream of future cash flows, and

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Speaker 1: that's a very evergreen concept. But we also know that

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Speaker 1: stock returns are volatile, and these premiums can be negative

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Speaker 1: for sustained periods of time, but they can also show

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Speaker 1: up in really large magnitudes really quickly. The return difference

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Speaker 1: between small value and large growth in the US as

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Speaker 1: of March thirty one over the trailing six month period

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Speaker 1: was sixty two percentage points. That's one of the largest

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Speaker 1: return deltas over such a short period of time ever.

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Speaker 1: But it's not uncommon for these premiums to show up

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Speaker 1: in a hurry, and this has obvious implications for investors.

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Speaker 1: It means that you need to be disciplined in terms

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Speaker 1: of your approach to capturing these and it also means

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Speaker 1: from an investment management standpoint, we need to be continuously

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Speaker 1: pursuing these groups of stocks and a very accurate way,

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Speaker 1: so that our investors know what they can expect from

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Speaker 1: our investment approach, you know. So I want to talk

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Speaker 1: about that what Vildana mentioned, the conversion of of some

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Speaker 1: of your funds into et apps. I mean, you're still

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Speaker 1: cominently a mutual fund manager, but you've you know, began

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Speaker 1: the process of converting some into e t f s,

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Speaker 1: And to me, I wonder, you know, in the bigger

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Speaker 1: scheme of things, that seems to me like perhaps part

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Speaker 1: of the natural evolution of quant investing. You know, I

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Speaker 1: think back to one when you were founded, but I

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Speaker 1: can't imagine the man hours and the labor required to

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Speaker 1: do just a simple regression study. Say, going back you know,

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Speaker 1: a few decades. It must have been, you know, and

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Speaker 1: an army of of people with visors and calculators. There's

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Speaker 1: all Texas instrument calculators. However, it was done. But is

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Speaker 1: that part of it? Just that you know, uh, the

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Speaker 1: computing power and the brain power on Wall Street is

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Speaker 1: kind of caught up with the quant uh sort of strategies,

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Speaker 1: and you know, it's now a lot you're able to

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Speaker 1: do it a lot cheaper, able to put it in

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Speaker 1: an ETF rapper, and and do it at a much

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Speaker 1: less cost basis than than you would say, years ago

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Speaker 1: in the equal fund space. Is does that sound right?

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Speaker 1: Is it? Is it kind of part of that evolution? Well,

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Speaker 1: I think that, you know, the E t F conversion

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Speaker 1: was was a very exciting thing for us because that conversion,

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Speaker 1: that type of event had not happened at that scale before.

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Speaker 1: And those particular strategies that were converted are managed with

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Speaker 1: an eye towards minimizing the tax impact for investors, and

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Speaker 1: the et F rapper gives you another tool in the toolkit,

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Speaker 1: uh to mitigate or to increase the tax efficiency of

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Speaker 1: those strategies. And so that was a very important thing

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Speaker 1: for us. But we like to say we're wrapper agnostic.

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Speaker 1: You know, we believe both the mutual fund and et

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Speaker 1: f rappers those type of vehicles do have a place

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Speaker 1: depending on an investor's objectives. But I think one of

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Speaker 1: the things you're kind of hinting at with this what

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Speaker 1: i'll call the rise and systematic investing. You know, that's

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Speaker 1: something that we have noticed, even going back further again

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Speaker 1: to your point. You know, you mentioned how the ability

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Speaker 1: to identify factors within the investment data, uh is a

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Speaker 1: lot easier now that it used to be. You know,

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Speaker 1: We're used to have computers the size of entire rooms

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Speaker 1: like the and I'm sitting in that you needed to

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Speaker 1: run regressions to identify these kind of parameters. Uh. Yeah,

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Speaker 1: Now it's much timplt. You could probably do it on

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Speaker 1: a smartphone. At this point. There is actually an academic

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Speaker 1: by the name of Campbell Harvey who keeps track of

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Speaker 1: all of the factors that have been identified in the

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Speaker 1: academic literature, and last time I checked, it was up

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Speaker 1: over five hundred. Uh And in fact, another academic named

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Speaker 1: John Cochrane refers to this as the factors zoo Um. Now,

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Speaker 1: this is not to say that there's that many, maybe

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Speaker 1: hundreds of different distinct sources of expected returns. A lot

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Speaker 1: of these are probably variations of the same economic concept

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Speaker 1: that are repackaged, but I think it does bring the

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Speaker 1: conversation back to the importance of implementation. It's one thing

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Speaker 1: to identify a group of securities that, based on historical

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Speaker 1: data while outperform in a simulation. Bringing that to a

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Speaker 1: real world investment solution where you deliver the outperformance net

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Speaker 1: of implementation costs is a different story altogether. And I'll

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Speaker 1: give you one really simple example. The Russell two thousand,

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Speaker 1: a small cap index we know from the research as

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Speaker 1: small cap secure. These have higher expected returns than large caps. Well,

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Speaker 1: the small cap Russell two thousand index has historically underperformed

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Speaker 1: the Russell one thousand index going back to seventy nine.

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Speaker 1: So that's one example. We're just identifying a group of

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Speaker 1: stocks you expect to have higher returns. Doesn't always pan

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Speaker 1: out an investment vehicle. You really need this level of

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Speaker 1: expertise and the research, design, management, and last but not least,

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Speaker 1: trading of a strategy to capture these sources of higher

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Speaker 1: expector returns for investors. I want to ask you and

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Speaker 1: Mike and I were chatting about this right before our conversation.

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Speaker 1: But when it comes to some of those factors, does

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Speaker 1: it feel like all of the good ones have already

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Speaker 1: been sort of discovered and exploited and repackages, you say,

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Speaker 1: or is there something else out there that you you're

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Speaker 1: finding really exciting? I think that's certainly a challenge, you know,

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Speaker 1: especially let's say you're a finance student these days compared

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Speaker 1: to one thirty years ago, to find something that hasn't

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Speaker 1: already been discovered. There's certainly the incentive to try and

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Speaker 1: look for something that's new. Um, But I think that,

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Speaker 1: you know, just because some of these core kind of

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Speaker 1: acid allocation determining building blocks like size, value or profitability,

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Speaker 1: you know, even if you can't add on to those necessarily,

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Speaker 1: there's a lot of other inputs into a strategy that

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Speaker 1: need to be taken into account. And that's where you know,

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Speaker 1: some of the really exciting research has been done, uh,

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Speaker 1: you know, internally with our research team, where we look

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Speaker 1: at things like this, where you find shorter term drivers

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Speaker 1: of expected returns that are really tradeoffs that you have

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Speaker 1: to balance against things like size, value or profitability. You know,

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Speaker 1: if you think about a value strategy, how to stocks

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Speaker 1: often become value stocks while it's following a period of

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Speaker 1: relative underperformance versus their peers. What do we know from

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Speaker 1: the phenomenon of momentum within the cross section of stocks. Well,

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Speaker 1: stocks that have had relatively poor returns uh in previous

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Speaker 1: periods tend to continue to have relatively poor returns in

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Speaker 1: the short run. And so addition, all sources of information

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Speaker 1: about expector returns like that are really crucial to Again,

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Speaker 1: even for these well established factors like size, value, and profitability,

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Speaker 1: making sure that we capture our fair share of those

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Speaker 1: still a very important part of implementation. Uh, what's I'm

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Speaker 1: great glad you brought up Cam Harvey. We've had him

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Speaker 1: on the show a few times. Not in a while, though,

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Speaker 1: But listeners, if you wanna hear more of the thoughts

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Speaker 1: of Camp, scroll back on the on the phone a

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Speaker 1: few a year or two and we had a couple

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Speaker 1: of good episodes with Cam. I getting back on. But

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Speaker 1: wes I wanna talk about what I What I mentioned

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Speaker 1: at the top of the show is basically what appears

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Speaker 1: to be kind of a reversal in the rotation back

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Speaker 1: to growth and tech leadership. Now, Uh, maybe the thinking

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Speaker 1: is the FED took a little bit of the wind

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Speaker 1: out of the sales of the reflation trade that was

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Speaker 1: boosting Uh, you know, the banks, the energy companies, the

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Speaker 1: real cyclical and value sectors of the market. How are

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Speaker 1: you thinking about that? Is uh, you know, and Bildad

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Speaker 1: has written about this and some others that a lot

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Speaker 1: of people think this is kind of a wrong react

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Speaker 1: and from the market to rotate this aggressively back into growth,

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Speaker 1: that there's still some jewice left to be squeezed out

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Speaker 1: of the value and cyclical trade. How are you thinking

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Speaker 1: about it? Well, we can start with first principles when

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Speaker 1: it comes to why we would believe any value premium

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Speaker 1: or size premium or profitability premium in the first place.

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Speaker 1: And it's based on the fact that there are differences

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Speaker 1: and discount rates across stocks. Right, Investors are going to

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Speaker 1: require different rates of return to hold different stocks. Just

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Speaker 1: like if you had a whole population of people went

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Speaker 1: to the bank for alone, they're likely to get different

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Speaker 1: interest rates from the bank, and so it's similar that

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Speaker 1: we would expect something like that to be true for

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Speaker 1: first stock discount rates, size, value, and profitability are just

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Speaker 1: based on using price combined with fundamentals to identify these

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Speaker 1: differences and expect to returns, which means that every single day,

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Speaker 1: based on the information known to market participants, there's some

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Speaker 1: stocks with higher expected returns than others. And that's what

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Speaker 1: we're talking about with these expected premiums, such as the

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Speaker 1: value premium. So we expect this premium every day, and

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Speaker 1: I know from the data that these premiums can be volatile.

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Speaker 1: If you just look on a rolling you know, one

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Speaker 1: year basis about of twelve month periods going back to

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Speaker 1: the nineteen twenties, and the US growth is outperformed value,

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Speaker 1: and I think that really hints at this notion of

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Speaker 1: the difference between realized returns and expector returns. So many

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Speaker 1: people had attributed the strong performance of growth stocks versus

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Speaker 1: value and you know, kind of that decade leading up

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Speaker 1: to the big turnaround for value recently, and they kind

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Speaker 1: of laid that at the feet of the FED. But

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Speaker 1: when you look at the performance of those growth stocks

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Speaker 1: over that period where they were churning out twenty per

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Speaker 1: year in terms of returns, you have to ask yourself

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Speaker 1: as an investor, do I believe the expected return for

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Speaker 1: this asset classes that seems awfully high and I think

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Speaker 1: we would look at that and say a good portion

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Speaker 1: of that was an unexpected component of the return that

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Speaker 1: might have been based on great success for some of

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Speaker 1: these companies, that could have been unexpected to a certain extent.

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Speaker 1: Certainly when you look at their valuation as they were

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Speaker 1: creeping up, they were still are very very high. Um. So,

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Speaker 1: when I think about is the question of is there

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Speaker 1: any juice left exqueeze from this limon? My question would be, well,

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Speaker 1: what's changed about your expectation for the value premium? As

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Speaker 1: long as you believe that low prices associated with higher

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Speaker 1: expector returns, there's plenty of juice left to squeeze because

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Speaker 1: we still expect a value premium every single day, you

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Speaker 1: know us. I'm curious how your approach fits in with

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Speaker 1: the year like this, Uh, you know, and I know,

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Speaker 1: being anchored in sort of the academic approach of investing

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Speaker 1: and very much anchored to the efficient market hypothesis at dimensional.

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Speaker 1: Then boy, we enter a year like one, right, and

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Speaker 1: we've got all of a sudden, all the discount brokerages

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Speaker 1: just completely get rid of commissions. You've got all these

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Speaker 1: people stuck at home. Uh, they can't go out. They

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Speaker 1: can't bet on sports. You know, they've got a lot

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Speaker 1: of spare cash, whether it be because of that or

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Speaker 1: because of the stimulus from the government and whatnot. And

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Speaker 1: we have this phenomenon like the at its stocks just

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Speaker 1: going going absolutely nuts. And it's hard to for me

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Speaker 1: to sort of wrap my head around how a student

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Speaker 1: of sort of efficient market theory can can kind of

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Speaker 1: operate in that environment. I mean, Um, does it change

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Speaker 1: your approach at all to see this type of behavior?

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Speaker 1: And half jokingly, I asque is there perhaps a Reddit

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Speaker 1: factor that can be exploited? You know, is there a

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Speaker 1: Wall Street bets factor that you could somehow quantify and

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Speaker 1: and try to play with and and feel free to

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Speaker 1: tell me I'm crazy for thinking that. I've I've heard

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Speaker 1: it before, but I'm just curious how you think about

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Speaker 1: a year like this, Um, with that academic background, that

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Speaker 1: efficient markets theory background, Uh, with the market that's a

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Speaker 1: lot of times just being driven by day traders, you know,

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Speaker 1: place some trades based on what they read on Reddit

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Speaker 1: and what they think the crowd, where they think the

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Speaker 1: crowd is going to go next. Well, I think it

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Speaker 1: reinforces the need for flexibility within your investment approach and

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Speaker 1: having a daily process. So you know, when we look

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Speaker 1: at the price change for a visual securities, I mean

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Speaker 1: we know it can happen because of maybe a change

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Speaker 1: in the expectation for the future for the cash flows

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Speaker 1: of the firm. It could reflect a change in the

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Speaker 1: discount rate that's assigned to those expected future cash flows.

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Speaker 1: Very difficult, if not impossible, to disentangle those two effects.

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Speaker 1: But what we do know is that when price is higher,

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Speaker 1: expect to returns are lower. So where that's relevant is

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Speaker 1: if you have a strategy, like say one that's focused

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Speaker 1: on small cat value stocks. Well, if you have a

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Speaker 1: company like one of the ones you're mentioning that started

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Speaker 1: off a small cat value and all of a sudden

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Speaker 1: it's prices now making it one of the largest two

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Speaker 1: or three companies in the US, well, then at that

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Speaker 1: point it's not really fitting the definition of higher expected

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Speaker 1: returns in accordance with a small cat value portfolio. So

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Speaker 1: if I have a daily process, then I can make

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Speaker 1: the determination to sell that out of the portfolio at

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Speaker 1: that time. It's funny when you look at, uh, you know,

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Speaker 1: some of the index approaches. You can use the Rustle

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Speaker 1: two thousand value as an example, where as of May

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Speaker 1: thirty one, you've got game Stop and AMC still within

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Speaker 1: the index, and at that time they were accounting for

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Speaker 1: about one and a half percentage point of the index. Uh.

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Speaker 1: And you know, you might even think of that is

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Speaker 1: a almost a Yao Ming like outlier, like if you

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Speaker 1: had Yamming visiting a kindergarten class in the size of screpancy.

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Speaker 1: Kind of the picture you would get if you think

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Speaker 1: about those two companies in a small value index. But

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Speaker 1: they weren't alone. In fact, you had about fifteen percent

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Speaker 1: of the Russell two thousand values holdings were actually in

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Speaker 1: the top one thousand largest in the US, which is

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Speaker 1: obviously the domain of the Russell and thousand indusicries. So

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Speaker 1: you know, again that's kind of a function of the

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Speaker 1: way that indusseries do their rebalancing in the case of

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Speaker 1: the Russell in disease once per year. We believe in

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Speaker 1: having a daily process that we can reflect changes in

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Speaker 1: market prices throughout the year and rebalance our portfolios incrementally,

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Speaker 1: and you need flexibility to do that. You have to

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Speaker 1: flex flexibility across names through time and individual names, so

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Speaker 1: you're not beholding the one individual trade. In that way,

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Speaker 1: you can dynamically react to the way prices changed to

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Speaker 1: continuously pursue higher expector returns and manage risk at the

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Speaker 1: same time. I gotta say, I would to see Yao

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Speaker 1: Ming visited kindergarten class. I'd I'd pay, I'd pay cover

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Speaker 1: charts for that, Dott, I'm sure you would. Most of

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Speaker 1: my sports jokes go over my head. Sorry about that.

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Speaker 1: But but to go back to what Mike was saying

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Speaker 1: about this year, Um, you know, returns have been really great.

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Speaker 1: I think we were checking the numbers just this morning.

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Speaker 1: It's been the second best first half of the year

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Speaker 1: in about two decades or so. And then at the

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Speaker 1: same time you have all these naysayer's warning about bubble

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Speaker 1: and pockets, bubbles and pockets of the markets that are

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Speaker 1: sort of bubblicious, if I can use that word. But

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Speaker 1: is that thanks is that a prevalent sense right now

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Speaker 1: or is it just uh something that you here all

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Speaker 1: the time anyway, or is there sort of this sense

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Speaker 1: of paranoia that's just a bit more prevalent just because

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Speaker 1: the market has been doing so well for the last year. Well,

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Speaker 1: the danger with using the expectation or the fear of

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Speaker 1: a bubble to influential asset allocation decisions is the possibility

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Speaker 1: that you might be wrong in the enormous opportunity costs

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Speaker 1: for doing so. And again, you know, I keep on.

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Speaker 1: I think twenty was a great example of all the

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Speaker 1: case studies that you can use where if you look

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Speaker 1: at the flows that we're going into money market funds

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Speaker 1: in Q one of I mean, it was close to

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Speaker 1: seven billion of dollars presumably going out of equities into

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Speaker 1: money market funds, and then what happens subsequent to the

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Speaker 1: end of Q one that year, Will you had any

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Speaker 1: enormous tear We had equities globally, you know, delivering thirty

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Speaker 1: some percentage points worth of return over the next two quarters.

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Speaker 1: So that's what's potentially on the table if you let

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Speaker 1: expectations of when maybe these premiums are gonna show up

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Speaker 1: in the future influence what you're gonna do. We don't

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Speaker 1: know when these premiums we're going to show up. That's

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Speaker 1: kind of the nature of you know, not just the

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Speaker 1: equity premium, but size, value and profitability, you know, the

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Speaker 1: value premium. Again, we keep one back to this one

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Speaker 1: because it's been in the news so much lately one

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Speaker 1: out of twenty months in the US historically. So this

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Speaker 1: is data going back to value stocks outperform growth stocks

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Speaker 1: by seven and a half percent inch points. That's fifteen

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Speaker 1: times what their unconditional average was. Uh So, I think

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Speaker 1: that just this notion that things can turn very quickly

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Speaker 1: unless you know what the news that's going to influence

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Speaker 1: expectations in the future is going to be. Then the

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Speaker 1: most tried and true method of capturing your fair share

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Speaker 1: of the market return and of these premiums is that

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Speaker 1: stay consistently invested so when they do show up, you're

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Speaker 1: there to capture them. At the same time, we do

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Speaker 1: have this wrong cohort that's been consistently buying, which is

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Speaker 1: which has been the retail investor. I read a note

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Speaker 1: earlier this week that said last Friday was a record

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Speaker 1: day for retail traders buying equities. I'm wondering how you

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Speaker 1: guys are thinking about the retail investor and their involvement

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Speaker 1: in the market, and how much of your conversion from

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Speaker 1: of your mutual funds into e t s is aimed

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Speaker 1: at attracting retail money potentially. Yeah, one of the benefits

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Speaker 1: for us having different investment solutions in different rappers, whether

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Speaker 1: it's open and mutual funds, ETF, separately managed accounts. We

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Speaker 1: want our clients to have lots of different ways to

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Speaker 1: use dimensionals investment solutions within the way they're building an

432
00:22:18,520 --> 00:22:22,160
Speaker 1: asset allegation for their clients and you know, so we

433
00:22:22,200 --> 00:22:23,600
Speaker 1: want at the end of the day to have all

434
00:22:23,640 --> 00:22:25,280
Speaker 1: those choices on the table for them. But we still

435
00:22:25,400 --> 00:22:28,680
Speaker 1: very much believe in the idea of having these financial intermediaries.

436
00:22:28,680 --> 00:22:30,800
Speaker 1: And again, some of the lessons we've been talking about

437
00:22:31,160 --> 00:22:33,880
Speaker 1: of the opportunity costs from deviating at the market at

438
00:22:33,920 --> 00:22:38,560
Speaker 1: the wrong time or not being consistently exposed to these

439
00:22:38,560 --> 00:22:41,920
Speaker 1: premiums can be greatly mitigated by you know, for example,

440
00:22:42,119 --> 00:22:46,040
Speaker 1: an an investor having an advisor who helps helps them

441
00:22:46,040 --> 00:22:49,000
Speaker 1: stay consistent with their investment approach. And we feel like

442
00:22:49,040 --> 00:22:52,200
Speaker 1: it's a very big benefit for investors. And then all

443
00:22:52,200 --> 00:22:54,240
Speaker 1: of our investment solutions are really tailored so that they

444
00:22:54,240 --> 00:22:56,280
Speaker 1: can make the best decisions of how to peace these

445
00:22:56,320 --> 00:23:16,439
Speaker 1: things together consistent with the goals of their you know,

446
00:23:16,480 --> 00:23:20,200
Speaker 1: West says, regular listeners will know, Um, I think I'm

447
00:23:20,359 --> 00:23:23,560
Speaker 1: contractually obligated to discuss inflation on the on the show,

448
00:23:24,080 --> 00:23:26,919
Speaker 1: perhaps legally obligated. I think they passed a law somewhere

449
00:23:26,920 --> 00:23:31,160
Speaker 1: all podcast hosts must discuss inflation. But I mean, obviously

450
00:23:31,200 --> 00:23:34,280
Speaker 1: the big wild card, the big variable everyone's top of

451
00:23:34,320 --> 00:23:37,520
Speaker 1: mind this year. Will it be transitory or not? How

452
00:23:37,520 --> 00:23:41,639
Speaker 1: long does transitory really mean? How are you thinking about

453
00:23:41,640 --> 00:23:44,800
Speaker 1: inflation and and is it affecting the way you're thinking

454
00:23:44,800 --> 00:23:47,280
Speaker 1: about portfolios? You know, break it down to us about

455
00:23:47,520 --> 00:23:50,359
Speaker 1: you know, you're you're sort of thirty view of inflation

456
00:23:50,359 --> 00:23:53,560
Speaker 1: and what to do about it? Yeah? Absolutely, I mean

457
00:23:53,640 --> 00:23:55,399
Speaker 1: depending on you talk to, you get lots of differing

458
00:23:55,480 --> 00:23:58,680
Speaker 1: viewpoints in terms of their expectations for inflation. So it's

459
00:23:58,680 --> 00:24:01,479
Speaker 1: helpful for us to just look what is the market

460
00:24:01,520 --> 00:24:05,000
Speaker 1: in aggregate telling us about inflation expectations, And you know,

461
00:24:05,000 --> 00:24:07,399
Speaker 1: we can see that from some indicators. For example, you

462
00:24:07,440 --> 00:24:09,600
Speaker 1: can need to break even inflation, or the difference in

463
00:24:09,680 --> 00:24:13,560
Speaker 1: yields between nominal and inflation protected treasuries at the same maturity.

464
00:24:14,040 --> 00:24:17,480
Speaker 1: You can use the you know, the forward inflation expectations,

465
00:24:17,560 --> 00:24:19,919
Speaker 1: something like the five year five years. So if I

466
00:24:19,960 --> 00:24:22,840
Speaker 1: look at the five year break even inflation rate right now,

467
00:24:23,000 --> 00:24:24,679
Speaker 1: or at least as of a few weeks ago, it

468
00:24:24,800 --> 00:24:27,760
Speaker 1: was hovering around right around two point four percent. The

469
00:24:27,880 --> 00:24:30,199
Speaker 1: five year five year forward inflation, which is telling you

470
00:24:30,200 --> 00:24:33,080
Speaker 1: something about inflation expectations for the five year period after

471
00:24:33,760 --> 00:24:36,440
Speaker 1: the next five years, so basically covering ten four years here,

472
00:24:36,760 --> 00:24:39,560
Speaker 1: that number was around two point one percent. Both of

473
00:24:39,600 --> 00:24:43,320
Speaker 1: those numbers are pretty well on line with historical trends,

474
00:24:43,359 --> 00:24:45,560
Speaker 1: So looking at those indicators, it doesn't seem that the

475
00:24:45,600 --> 00:24:50,960
Speaker 1: market in aggregate is expecting particularly high inflation. And expecting

476
00:24:51,040 --> 00:24:54,120
Speaker 1: inflation is incorporating into security prices, whether you're buying you know,

477
00:24:54,240 --> 00:24:58,400
Speaker 1: stocks or bonds or anything that's in nominal terms, you're

478
00:24:58,400 --> 00:25:03,080
Speaker 1: getting compensation for expect and inflation. Now, some investors might

479
00:25:03,080 --> 00:25:06,360
Speaker 1: be particularly sensitive to inflation, and that means they might

480
00:25:06,359 --> 00:25:09,760
Speaker 1: be concerned with unexpected inflation. So, for example, if consumer

481
00:25:09,800 --> 00:25:14,280
Speaker 1: prices rise more than the broad market is expecting, then

482
00:25:14,760 --> 00:25:17,080
Speaker 1: they might want to seek additional protection for that. And

483
00:25:17,119 --> 00:25:20,240
Speaker 1: there are options, and it's sort of like the COVID vaccines,

484
00:25:20,280 --> 00:25:22,200
Speaker 1: where you have different ways to reach the same level

485
00:25:22,240 --> 00:25:27,720
Speaker 1: of inoculation. You can use treasury inflation protected securities which

486
00:25:27,800 --> 00:25:32,240
Speaker 1: will hedge on expected inflation. There's a consideration there, which

487
00:25:32,320 --> 00:25:34,280
Speaker 1: is that the yields on those are very very low.

488
00:25:34,359 --> 00:25:37,520
Speaker 1: The real interest rates for US treasuries are negative across

489
00:25:37,520 --> 00:25:40,920
Speaker 1: the board, across all maturities. Um. Then there's also the

490
00:25:41,000 --> 00:25:45,760
Speaker 1: possibility of having a fixed income solution which combines inflation

491
00:25:45,880 --> 00:25:49,760
Speaker 1: swap overlays, so you're getting you're gonna get paid real inflator,

492
00:25:49,800 --> 00:25:53,280
Speaker 1: actual inflation, and then it's overlaid. On corporate bond strategies,

493
00:25:53,320 --> 00:25:56,720
Speaker 1: we can expand your opportunities set two different levels of

494
00:25:56,720 --> 00:25:59,320
Speaker 1: credit and different currencies as well, so there are options

495
00:25:59,320 --> 00:26:03,200
Speaker 1: for investors who do have concerns about unexpected inflation. But

496
00:26:03,240 --> 00:26:06,600
Speaker 1: I think getting to this notion that expected inflation, which

497
00:26:06,640 --> 00:26:08,480
Speaker 1: is whatever the market believes is going to come to pass,

498
00:26:09,240 --> 00:26:12,800
Speaker 1: is being compensated in current security prices. And let's face it,

499
00:26:12,880 --> 00:26:15,120
Speaker 1: the market, when they're producing prices like this, they were

500
00:26:15,240 --> 00:26:17,320
Speaker 1: very difficult to out guests. We might all have our

501
00:26:17,359 --> 00:26:20,679
Speaker 1: opinions on what's gonna happen in the future, but looking

502
00:26:20,680 --> 00:26:24,520
Speaker 1: at the data around active fund managers outguessing market prices

503
00:26:24,680 --> 00:26:28,639
Speaker 1: is very difficult for most folks, you know, West. Before

504
00:26:28,680 --> 00:26:31,520
Speaker 1: we get to the crazy things, I just want to

505
00:26:31,560 --> 00:26:34,560
Speaker 1: get your your sort of current of the moment thoughts

506
00:26:34,640 --> 00:26:37,680
Speaker 1: on on asset allocation. If I can, And let's start,

507
00:26:37,960 --> 00:26:40,520
Speaker 1: you know, with the hypothetical sixty forty. Now, obviously there's

508
00:26:40,560 --> 00:26:43,359
Speaker 1: been a lot of debate recently of whether sixty is

509
00:26:43,400 --> 00:26:47,800
Speaker 1: dead or you know, what should go into that bucket? Um,

510
00:26:47,840 --> 00:26:50,440
Speaker 1: you know, should he be seventy thirty or whatever, whatever

511
00:26:50,480 --> 00:26:52,440
Speaker 1: the case may be. There's there's kind of a lot

512
00:26:52,520 --> 00:26:55,639
Speaker 1: of diversity of opinion on the whole notion of a

513
00:26:55,640 --> 00:26:58,840
Speaker 1: diverse what a diversified portfolio should should look like right now?

514
00:26:58,880 --> 00:27:02,640
Speaker 1: So I'm just kinda cure swear you stand on that idea. Um,

515
00:27:03,119 --> 00:27:06,240
Speaker 1: you know, are you a sixty forty type of guy? Uh?

516
00:27:06,280 --> 00:27:08,159
Speaker 1: And if so, what you know, what exactly are you

517
00:27:08,160 --> 00:27:10,720
Speaker 1: putting in your sixty? What are you putting in your forty?

518
00:27:10,760 --> 00:27:12,040
Speaker 1: You know a lot of people saying you've got to

519
00:27:12,040 --> 00:27:13,679
Speaker 1: take a little more risk in the forty, get some

520
00:27:13,720 --> 00:27:16,600
Speaker 1: credit in there, some corporate credit, maybe some em debt,

521
00:27:16,640 --> 00:27:18,879
Speaker 1: that sort of thing. How are you thinking about it all?

522
00:27:19,640 --> 00:27:23,120
Speaker 1: And how much bigcoin is part of that? We're dose

523
00:27:23,200 --> 00:27:26,080
Speaker 1: coin for that matter. Well, I'll start with what the

524
00:27:26,080 --> 00:27:29,200
Speaker 1: theory tells us, and it tells us that your asset allocation,

525
00:27:29,320 --> 00:27:32,000
Speaker 1: especially that split between equities and fixed income, is going

526
00:27:32,040 --> 00:27:35,040
Speaker 1: to be a function of really the relative amount of

527
00:27:35,359 --> 00:27:38,879
Speaker 1: actual invested capital you have versus your human capital. So

528
00:27:38,920 --> 00:27:41,000
Speaker 1: when you first start out working, where most of your

529
00:27:41,000 --> 00:27:43,680
Speaker 1: assets on your quote unquote balance sheet, if you want

530
00:27:43,680 --> 00:27:45,919
Speaker 1: to call it, that is your human capital, your ability

531
00:27:45,920 --> 00:27:48,399
Speaker 1: to continue to work to save more money and contribute

532
00:27:48,440 --> 00:27:51,359
Speaker 1: to your savings in the future. And as you transition

533
00:27:51,400 --> 00:27:53,760
Speaker 1: through your working life, when you get closer to retirement,

534
00:27:54,119 --> 00:27:57,640
Speaker 1: obviously you've exhausted more of your human capital, probably don't

535
00:27:57,640 --> 00:27:59,960
Speaker 1: want to work forever, but hopefully you've been able to

536
00:28:00,000 --> 00:28:03,359
Speaker 1: accumulate more in terms of invested assets. So when you

537
00:28:03,400 --> 00:28:06,119
Speaker 1: think about the riskiness of each one of those components,

538
00:28:06,400 --> 00:28:09,000
Speaker 1: your human capital is a much more stable and lower

539
00:28:09,119 --> 00:28:13,160
Speaker 1: risk component than your investment capital. So when you're when

540
00:28:13,200 --> 00:28:15,479
Speaker 1: you're young, when you're starting off in your working career,

541
00:28:15,920 --> 00:28:17,800
Speaker 1: that means that most of your balance sheet is in

542
00:28:18,160 --> 00:28:20,800
Speaker 1: quote unquote lower risk assets. You might take more risk

543
00:28:20,840 --> 00:28:23,679
Speaker 1: in terms of your invested assets, so that's why you

544
00:28:23,760 --> 00:28:27,439
Speaker 1: might see a higher allocation equities when you're at a

545
00:28:27,560 --> 00:28:31,120
Speaker 1: younger investment age. Obviously, as you proceed through your investment lifetime,

546
00:28:31,440 --> 00:28:34,560
Speaker 1: you start to transition or de risk your financial assets

547
00:28:34,560 --> 00:28:37,919
Speaker 1: and you start to transition into more fixed income heavy allocation.

548
00:28:38,440 --> 00:28:40,880
Speaker 1: So you know, that's something that I think is probably

549
00:28:40,880 --> 00:28:43,120
Speaker 1: a good starting point when you're thinking about how much

550
00:28:43,320 --> 00:28:45,200
Speaker 1: you know you how much do you want to continue

551
00:28:45,200 --> 00:28:47,440
Speaker 1: to work, how much, how on target you are in

552
00:28:47,520 --> 00:28:48,880
Speaker 1: terms of what you've been able to say for your

553
00:28:48,880 --> 00:28:51,720
Speaker 1: financial goals, and you can make your equity fixed determination

554
00:28:51,760 --> 00:28:55,320
Speaker 1: from there. Now, within each one of those sleeves, I

555
00:28:55,360 --> 00:28:56,960
Speaker 1: start with the notion that you want it to be

556
00:28:57,000 --> 00:29:01,160
Speaker 1: as diversified as possible. So when within the equity sleeve,

557
00:29:01,280 --> 00:29:04,360
Speaker 1: maybe have a global allocation and two equities, does that

558
00:29:04,400 --> 00:29:07,040
Speaker 1: mean you're gonna hold just an exact fac simile of

559
00:29:07,040 --> 00:29:09,280
Speaker 1: the global market portfolio? Maybe not. You might have reasons

560
00:29:09,280 --> 00:29:13,000
Speaker 1: to deviate. US based investors tend to have a home

561
00:29:13,040 --> 00:29:15,560
Speaker 1: bias towards US stocks, you might have an overweight there.

562
00:29:15,920 --> 00:29:18,480
Speaker 1: But I think broad diverse vacation is a very important

563
00:29:18,520 --> 00:29:22,360
Speaker 1: component within the fixed income Some of that depends on

564
00:29:22,440 --> 00:29:25,400
Speaker 1: what your ultimate goals are, and let's say your goals

565
00:29:25,400 --> 00:29:30,040
Speaker 1: are to support consumption within retirement. That kind of sets

566
00:29:30,120 --> 00:29:32,160
Speaker 1: up almost like a liability, Like if you were to

567
00:29:32,160 --> 00:29:35,280
Speaker 1: think of a same insurance company that has cash flow

568
00:29:35,400 --> 00:29:38,400
Speaker 1: needs at certain periods of time, those are liabilities that

569
00:29:38,400 --> 00:29:40,600
Speaker 1: they're going to try and hedge with their fixed income.

570
00:29:40,920 --> 00:29:43,800
Speaker 1: And this is where maybe a liability driven investment approach

571
00:29:43,880 --> 00:29:46,360
Speaker 1: might work. Where you have fixed income that has a

572
00:29:46,480 --> 00:29:51,440
Speaker 1: duration that's taylor or connected to whatever the liabilities are. Uh,

573
00:29:51,440 --> 00:29:54,480
Speaker 1: those cash flow needs you have in retirement, they have

574
00:29:54,480 --> 00:29:57,120
Speaker 1: a duration associated with them and it changes through time.

575
00:29:57,640 --> 00:30:00,320
Speaker 1: So by having a dynamic allocation, you're fixing. Um, that's

576
00:30:00,400 --> 00:30:03,040
Speaker 1: one example of how you would taylor that fixed income

577
00:30:03,120 --> 00:30:07,239
Speaker 1: sleeve to whatever your needs are. Well, don I'm just

578
00:30:07,240 --> 00:30:10,200
Speaker 1: glad West when he started talking about people getting further

579
00:30:10,240 --> 00:30:13,560
Speaker 1: along into the workforce and closer to the retirement age

580
00:30:13,600 --> 00:30:18,440
Speaker 1: that he didn't point right at me. I'm glad about that. Well, Well,

581
00:30:18,480 --> 00:30:22,080
Speaker 1: listeners can't see, but he did. Actually everybody knows he

582
00:30:22,120 --> 00:30:25,360
Speaker 1: did point at Mike fair enough, fair enough as he should,

583
00:30:25,400 --> 00:30:29,000
Speaker 1: as he should stand clearer of the craziest things we

584
00:30:29,040 --> 00:30:33,720
Speaker 1: saw in markets this week? Well, West, great conversation. I

585
00:30:33,720 --> 00:30:36,480
Speaker 1: think that is our segue to the crazy things that

586
00:30:36,680 --> 00:30:38,600
Speaker 1: I know you brought a good one for us. I'm

587
00:30:38,640 --> 00:30:40,880
Speaker 1: gonna save yours for last. But West, how about you?

588
00:30:41,040 --> 00:30:44,320
Speaker 1: Have you seen anything crazy in markets in the last week? Yeah,

589
00:30:44,320 --> 00:30:46,360
Speaker 1: there was one that kind of caught my attention, and

590
00:30:46,480 --> 00:30:49,600
Speaker 1: it happened right when there was a press conference for

591
00:30:49,720 --> 00:30:53,440
Speaker 1: the Portugal soccer team, during which Christian Ano Ronaldo came

592
00:30:53,520 --> 00:30:55,959
Speaker 1: up to the stage and as part of their promotional

593
00:30:56,040 --> 00:30:58,520
Speaker 1: period for Coca Cola, there were, of course, to Coca

594
00:30:58,520 --> 00:31:01,520
Speaker 1: Cola bottles sitting right next to his microphone, and of

595
00:31:01,560 --> 00:31:04,120
Speaker 1: course his reaction was to remove those from the table

596
00:31:04,440 --> 00:31:07,000
Speaker 1: and hold up a bottle of water, I guess, encouraging

597
00:31:07,000 --> 00:31:10,040
Speaker 1: people to drink water. What was notable about this was

598
00:31:10,120 --> 00:31:13,400
Speaker 1: that that day Coca Cola stock went down about four

599
00:31:13,440 --> 00:31:17,040
Speaker 1: billion dollars, so, uh, you know, whether it's caused and effect,

600
00:31:17,040 --> 00:31:19,400
Speaker 1: whether it's just a coincidence. Kind of interesting because Coca

601
00:31:19,400 --> 00:31:23,360
Speaker 1: Cola actually owns some water distribution companies, so you know,

602
00:31:23,400 --> 00:31:26,160
Speaker 1: they should be able to benefit from a widespread surge

603
00:31:26,200 --> 00:31:29,640
Speaker 1: and water consumption. But that was certainly one that was notable.

604
00:31:30,320 --> 00:31:33,440
Speaker 1: That was that's a great one. That's a perfect crazy thing.

605
00:31:33,480 --> 00:31:36,360
Speaker 1: And I you know, interestingly, you would think the margins

606
00:31:36,400 --> 00:31:38,600
Speaker 1: on water are probably a lot higher for Coke anyway,

607
00:31:38,760 --> 00:31:41,040
Speaker 1: I guess maybe it wasn't the De Saunty brand or

608
00:31:41,080 --> 00:31:45,040
Speaker 1: whatever Cokes brand is that, but that's that's a good one.

609
00:31:45,160 --> 00:31:47,240
Speaker 1: That's a pretty good one. And then another guy pushed

610
00:31:47,240 --> 00:31:49,800
Speaker 1: aside the Heineken I think too, they he didn't want

611
00:31:49,840 --> 00:31:53,520
Speaker 1: to be associated with Heineken, so little uh, a little

612
00:31:54,120 --> 00:31:56,520
Speaker 1: activism in the in the soccer world. And then they

613
00:31:56,560 --> 00:31:58,760
Speaker 1: I think they were all told stop doing this, just

614
00:31:58,840 --> 00:32:04,440
Speaker 1: leave the cokes and for the sponsor. That's right, that's right,

615
00:32:04,680 --> 00:32:06,320
Speaker 1: all right, that's a good one. And I'm mine is

616
00:32:06,480 --> 00:32:09,320
Speaker 1: very food oriented too. And you may argue with me

617
00:32:09,400 --> 00:32:12,800
Speaker 1: that this is not exactly a market story, but I

618
00:32:12,840 --> 00:32:15,680
Speaker 1: will push back on that because my crazy thing is

619
00:32:15,720 --> 00:32:19,720
Speaker 1: about the avocado market uh Albana. And to prove it's

620
00:32:19,720 --> 00:32:22,320
Speaker 1: a ballad topic, there is a ticker on the Bloomberg

621
00:32:22,360 --> 00:32:25,040
Speaker 1: for avocado prices out of Mexico, so you know you

622
00:32:25,040 --> 00:32:27,200
Speaker 1: can you can run a regression on it. The seasonality

623
00:32:27,200 --> 00:32:28,520
Speaker 1: on it is interesting. I don't know if you want

624
00:32:28,560 --> 00:32:31,080
Speaker 1: to get into the avocado trade West, but I encourage

625
00:32:31,080 --> 00:32:33,640
Speaker 1: you check it out. But this is a really good

626
00:32:33,640 --> 00:32:35,920
Speaker 1: story from the Wall Street Journal, one of their a

627
00:32:36,040 --> 00:32:39,040
Speaker 1: head stories on page one, and it's about the fact

628
00:32:39,080 --> 00:32:43,800
Speaker 1: that avocados have gotten so pricey that there are these

629
00:32:43,960 --> 00:32:47,640
Speaker 1: organized gangs going in and trying to to basically rob

630
00:32:47,680 --> 00:32:50,959
Speaker 1: avocado farms and what the farmers are doing to prevent it.

631
00:32:50,960 --> 00:32:54,680
Speaker 1: They talk about one farmer in South Africa. He's got

632
00:32:54,760 --> 00:33:02,600
Speaker 1: motion activated infrared cameras around the hundred seventy acre farm. Um,

633
00:33:02,680 --> 00:33:06,480
Speaker 1: he's also got on stand by a rapid response team

634
00:33:06,520 --> 00:33:11,160
Speaker 1: that's led by a next military guy, complete with tracker dogs,

635
00:33:11,480 --> 00:33:13,840
Speaker 1: and they try to you know, immediately react to the

636
00:33:13,840 --> 00:33:17,680
Speaker 1: avocado thiefs as they come in. Um. One of my

637
00:33:17,720 --> 00:33:20,959
Speaker 1: favorite things in Mexico. The drug cartels are actually fighting

638
00:33:20,960 --> 00:33:24,120
Speaker 1: over the avocado crop now because the prices prices have

639
00:33:24,240 --> 00:33:27,479
Speaker 1: got so far. But they say, you know, these just

640
00:33:27,560 --> 00:33:32,520
Speaker 1: aren't sort of smash and grab guys that they basically

641
00:33:32,600 --> 00:33:35,760
Speaker 1: planned this to a t. And the general describes it

642
00:33:35,840 --> 00:33:41,440
Speaker 1: as large career grapht raids on farms where they can

643
00:33:41,640 --> 00:33:45,720
Speaker 1: basically steal about a ton of avocados in a very

644
00:33:45,720 --> 00:33:48,320
Speaker 1: short time I think like a couple hours, and then

645
00:33:48,840 --> 00:33:51,080
Speaker 1: they take it, they launder it onto the black avocado

646
00:33:51,160 --> 00:33:54,880
Speaker 1: market and uh and make a fortunate it so fascinating stuff.

647
00:33:54,880 --> 00:33:57,560
Speaker 1: I know. Our colleague Tracy Alloway loves to chart the

648
00:33:57,600 --> 00:34:01,920
Speaker 1: correlation of avocado prices with bitcoin, so uh, another reason

649
00:34:01,920 --> 00:34:04,520
Speaker 1: why this is I think a good candidate for our

650
00:34:04,520 --> 00:34:07,200
Speaker 1: crazy things. Well, Dona, I don't know if you'll if

651
00:34:07,200 --> 00:34:11,200
Speaker 1: you'll allow me this uh, this rare commodity trade to

652
00:34:11,280 --> 00:34:14,239
Speaker 1: be a crazy thing. I'll allow it. And I'll even

653
00:34:14,239 --> 00:34:16,279
Speaker 1: allow you to name it. You can name it the

654
00:34:16,520 --> 00:34:22,000
Speaker 1: guacamole cartel. I'm open. I'm open to other names, other suggestions.

655
00:34:22,080 --> 00:34:26,640
Speaker 1: Guack cartel. I like that, all right, not bad? All right?

656
00:34:26,800 --> 00:34:30,040
Speaker 1: What do you have first, Fildanna. Mine is not food related,

657
00:34:30,120 --> 00:34:33,759
Speaker 1: but I'm leaving the planet for for mine. Uh, and

658
00:34:33,880 --> 00:34:37,360
Speaker 1: it's I read this story about Procter and Gamble saying

659
00:34:37,520 --> 00:34:40,680
Speaker 1: that they've signed an agreement with NASA to test laundry

660
00:34:40,719 --> 00:34:44,880
Speaker 1: solutions in the International Space Station, which I thought was

661
00:34:45,160 --> 00:34:48,600
Speaker 1: really interesting because there are no washing machines in space,

662
00:34:48,719 --> 00:34:53,080
Speaker 1: so basically what happens astronauts just wear the same clothes

663
00:34:53,160 --> 00:34:57,080
Speaker 1: over and over until they're like totally disgusting. And so

664
00:34:57,200 --> 00:34:59,759
Speaker 1: this is a way for them to try to make

665
00:35:00,000 --> 00:35:05,480
Speaker 1: continuous space living actually a possibility, I suppose. So there.

666
00:35:05,560 --> 00:35:09,280
Speaker 1: I guess they're not sure how Proctu and Gamble detergent

667
00:35:09,400 --> 00:35:13,640
Speaker 1: behaves in space. Well, you can't, you can't. You can't

668
00:35:13,680 --> 00:35:17,120
Speaker 1: wash clothes in space, and so they're trying to figure

669
00:35:17,160 --> 00:35:20,200
Speaker 1: out a way to actually make that happen. Huh, that's

670
00:35:20,200 --> 00:35:22,120
Speaker 1: a good one. I'm i gonna say, if they can

671
00:35:22,120 --> 00:35:29,200
Speaker 1: make dry shampoo, maybe they can make dry detergent. That's right, right, right, Again,

672
00:35:29,239 --> 00:35:30,880
Speaker 1: there's not a lot of dirt in space either, I

673
00:35:30,880 --> 00:35:34,560
Speaker 1: imagine those uh International Space Station is a pretty sterile environment,

674
00:35:34,600 --> 00:35:39,399
Speaker 1: so how much no, because astronauts have to exercise two

675
00:35:39,400 --> 00:35:42,799
Speaker 1: hours a day. Oh gotcha, gotcha? So there you can

676
00:35:42,800 --> 00:35:45,839
Speaker 1: get pretty gross. So they've got pit stains on their

677
00:35:45,920 --> 00:35:48,440
Speaker 1: their space suits and stuff. I guess wow. All right,

678
00:35:48,480 --> 00:35:50,799
Speaker 1: well that seems like I'm glad to hear that. I'm

679
00:35:50,960 --> 00:35:54,240
Speaker 1: you know, if this whole space tourism thing kicks off further,

680
00:35:54,520 --> 00:35:57,839
Speaker 1: that's that's gonna that's gonna come in handy. I don't know, West,

681
00:35:57,840 --> 00:35:59,359
Speaker 1: I don't know how you trade that one is there.

682
00:35:59,600 --> 00:36:02,719
Speaker 1: I don't know what the end market is for for

683
00:36:02,920 --> 00:36:06,040
Speaker 1: detergent in space. Still wrapping my my head around the

684
00:36:06,040 --> 00:36:10,880
Speaker 1: expectations there. All right, what the check back on that?

685
00:36:10,920 --> 00:36:12,480
Speaker 1: We'll see how they did on that experiment. That's a

686
00:36:12,480 --> 00:36:13,839
Speaker 1: good one, Bill Dona. I don't know if the share

687
00:36:13,840 --> 00:36:16,319
Speaker 1: price moved or not, but no, but it was just

688
00:36:16,360 --> 00:36:19,439
Speaker 1: a fun read. Yeah. Well, hopefully you know you won't

689
00:36:19,440 --> 00:36:21,479
Speaker 1: see so match you're not in a press conference. Push

690
00:36:21,520 --> 00:36:26,640
Speaker 1: the tide pods away from him anyway, that would be

691
00:36:26,960 --> 00:36:28,400
Speaker 1: that would make the share person, that would make it

692
00:36:28,400 --> 00:36:33,080
Speaker 1: share absolutely anyway, vel Data, Hirich uh West Krill. So

693
00:36:33,160 --> 00:36:34,600
Speaker 1: happy to have you on the show. Really enjoyed the

694
00:36:34,600 --> 00:36:37,200
Speaker 1: conversation and hopefully we can do it again sometime. Yeah,

695
00:36:37,239 --> 00:36:47,719
Speaker 1: thanks for having me. It was great. What Goes Up.

696
00:36:47,719 --> 00:36:49,879
Speaker 1: We'll be back next week. Until then, you can find

697
00:36:49,920 --> 00:36:52,800
Speaker 1: us on the Bloomberg Terminal, website and app where wherever

698
00:36:52,840 --> 00:36:55,239
Speaker 1: you get your podcasts. We'd love it if you took

699
00:36:55,239 --> 00:36:57,320
Speaker 1: the time to rate and review the show on Apple

700
00:36:57,360 --> 00:37:00,480
Speaker 1: Podcasts so more listeners can find us. And you can

701
00:37:00,480 --> 00:37:04,600
Speaker 1: find us on Twitter, follow me at Reaganonymous, Bildonna is

702
00:37:04,719 --> 00:37:08,279
Speaker 1: at Bildonna high Rich. You can also follow Bloomberg Podcasts

703
00:37:08,400 --> 00:37:11,600
Speaker 1: at podcasts. I thank you to Charlie Pellet to Bloomberg

704
00:37:11,680 --> 00:37:14,160
Speaker 1: Radio in the voice of the New York City Subway System.

705
00:37:14,200 --> 00:37:16,800
Speaker 1: What Goes Up is produced by Topor forhez ahead of

706
00:37:16,800 --> 00:37:20,920
Speaker 1: Bloomberg Podcasts is Francesco Levy. Thanks for listening. See you

707
00:37:20,960 --> 00:37:21,359
Speaker 1: next time,