WEBVTT - The Mystery of Smart-Beta, Explained

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<v Speaker 1>Welcome to trillions. I'm Joel Webber and I'm Eric bel Tunis. Eric.

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<v Speaker 1>We've been doing this for a little bit now, but

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<v Speaker 1>we haven't spent that much time talking about what's basically

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<v Speaker 1>the hottest trend in ETFs, which is smart beta. Yeah,

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<v Speaker 1>it's one of them. I think people forget that smart

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<v Speaker 1>beta is of e t F assets, so it's a

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<v Speaker 1>big chunk um. The other virtually is all what we

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<v Speaker 1>call cheap beta, which is you know, the smp F

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<v Speaker 1>t F and we called the plane vanilla side. But

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<v Speaker 1>this is up from nothing ten years ago, so it

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<v Speaker 1>is a it's growing faster on a percentage basis than

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<v Speaker 1>e t F as a whole, and it's a really

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<v Speaker 1>interesting dynamic area. This is where a lot of the

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<v Speaker 1>innovation and new products are being launched. So how are

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<v Speaker 1>we supposed to think about this thing called smart beta. Well,

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<v Speaker 1>it's very it can be confusing a lot of times.

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<v Speaker 1>People think it sounds like something you get at the

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<v Speaker 1>g n C store. Yeah, I mean right, I know,

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<v Speaker 1>you're like a way container little double chocolate smart beta.

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<v Speaker 1>It's definitely jargon e um and it's got a buzzword

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<v Speaker 1>type feel to it. But um, you know. Essentially, a

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<v Speaker 1>lot of people will give you different definitions of it.

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<v Speaker 1>To me, you know, the metaphor I use is the

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<v Speaker 1>way people describe different religions, right they there's this thing

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<v Speaker 1>that they say, it's like a bunch of people touching

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<v Speaker 1>an elephant in a dark room, in the way different

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<v Speaker 1>religions describing God. It's the same thing, but it's just

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<v Speaker 1>being Uh, they're feeling a different part of it, but

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<v Speaker 1>ultimately it's the same thing to me. Smarting Right now,

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<v Speaker 1>what is that I'm in a dark room? You don't

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<v Speaker 1>want to know. No, let's say you're touching the trunk.

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<v Speaker 1>Somebody else is touching the side. My point is that

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<v Speaker 1>smart beata kind of can mean different things to different people. Uh,

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<v Speaker 1>it's controversial, and I think that a lot of people

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<v Speaker 1>instead of thinking you need to like capture it and

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<v Speaker 1>be done with understanding it in two seconds, I think

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<v Speaker 1>you need to just accept that it's a little bit

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<v Speaker 1>of a mystery to some people. There's a complexity to

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<v Speaker 1>it and there's differing opinions. As long as you embrace

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<v Speaker 1>that and sort of go into this conversation we're about

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<v Speaker 1>to have knowing that you're gonna understand a little more.

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<v Speaker 1>I think that's the way to go. You gotta lower

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<v Speaker 1>the bar on this because you can't really just get

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<v Speaker 1>it done in like two or three sentences. If I

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<v Speaker 1>had to do it in one sentence, what would you

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<v Speaker 1>how would you describe it? I would say smart Beta

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<v Speaker 1>is trying to take Peter Lynch's brain and put it

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<v Speaker 1>into our two D two's think. In other words, you're

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<v Speaker 1>trying to take the best of active management, but putting

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<v Speaker 1>it into a rules based index that an e t

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<v Speaker 1>F track. So it's basically a conversion of active and

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<v Speaker 1>trying to make it better and more efficient and cheaper

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<v Speaker 1>and deliver it in a better structure. This week, Gun Trillion,

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<v Speaker 1>the Mystery of smart Beta. Okay, Eric, we've got some guests.

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<v Speaker 1>This is really important because I think every one of

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<v Speaker 1>these guests, including you and me, we'll have a different

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<v Speaker 1>perspective on smart Beta. So we're all sort of touching

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<v Speaker 1>the elephant in your dark room, your creepy dark room

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<v Speaker 1>filled with an elephant and us. Yeah, it's almost akin

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<v Speaker 1>to when you go to a conference. So an ETF conferences,

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<v Speaker 1>there's a panel, you tend to have people from different lenses.

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<v Speaker 1>So we're trying to sort of capture that so that

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<v Speaker 1>you can get all of the viewpoints and then you

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<v Speaker 1>can sort of come up with your own sort of

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<v Speaker 1>view on it. One of them is remote, so he's

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<v Speaker 1>in his own dark room touching a different elephant. Near

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<v Speaker 1>case are a columnst with Bloomberg gad fly high near Hello,

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<v Speaker 1>he's in d C. Joining us in the booth is

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<v Speaker 1>Tom Seraphagus, who is a colleague of yours at Bloomberg Intelligence,

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<v Speaker 1>where he's an et F analyst. Also came from Oppenheimer

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<v Speaker 1>before he was at Bloomberg uh and has some experience

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<v Speaker 1>with smart beata et F. Sah, how are you. I'm

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<v Speaker 1>doing great, Thanks for joining. So Tom, can you help

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<v Speaker 1>start this discussion around what is smart beata. Let's definance

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<v Speaker 1>so that you know, before people get in the deep

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<v Speaker 1>to the pool with us, we have an understanding of

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<v Speaker 1>what we're talking about. Yeah. Sure. And so before I

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<v Speaker 1>joined here, I was at on the other side of

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<v Speaker 1>the table, so on the issue side. And you have

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<v Speaker 1>to remember that a lot of these active shops have

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<v Speaker 1>a tremendous amount of resources, right They've got portfolio managers

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<v Speaker 1>and analysts. So I think in a very brief way,

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<v Speaker 1>what they were trying to do is take the mind

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<v Speaker 1>of the portfolio manager Peter Rearle and sure someone else saying, Hey,

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<v Speaker 1>when you're picking stocks, what are things you're looking at?

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<v Speaker 1>How are you running your screens? What are you looking at?

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<v Speaker 1>Let's take your approach, put it, write it down, put

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<v Speaker 1>it in an index, and launch an e t F

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<v Speaker 1>over it. So, um, you know, the the definition of

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<v Speaker 1>smart data. It's not so clear, right, it's a very

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<v Speaker 1>gray area. But it's really trying to take a lot

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<v Speaker 1>of these approaches, democratize it, put in e TF and

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<v Speaker 1>make it available to the masses as a product, as

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<v Speaker 1>a problem, buy off the shelf, right, how do you

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<v Speaker 1>think about it? I think those are both good. Both

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<v Speaker 1>Eric and Tom's definitions I think are both good. I'll

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<v Speaker 1>just try to simplify it even further because I think

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<v Speaker 1>it's really important to convey to to investors that this

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<v Speaker 1>is actually very simple in concept. All this is is

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<v Speaker 1>traditional active management. All that all the strategies that they've

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<v Speaker 1>always loved and have been used for decades by every

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<v Speaker 1>active manager ever. Value you know, buying cheaper companies, buying

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<v Speaker 1>you know, high growth companies, buying smaller companies, whatever the

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<v Speaker 1>strategy that you like is effectively giving it to a

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<v Speaker 1>computer and letting a computer run it. That's really all

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<v Speaker 1>it is. And the reason that's important to convey is

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<v Speaker 1>the the the act of taking it away from the

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<v Speaker 1>from the human and giving it to the computer gives

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<v Speaker 1>the investor several advantages that are really important. One, it

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<v Speaker 1>makes it a lot cheaper because you can you know,

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<v Speaker 1>the computer doesn't cost as much as the human. That's

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<v Speaker 1>the first thing that's you know, that's a good thing.

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<v Speaker 1>The second thing is they're more transparent because you've turned

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<v Speaker 1>it over to a computer. You've had to write rules

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<v Speaker 1>about how this thing will look. And investors can read

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<v Speaker 1>these rules and they can see exactly what they're buying,

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<v Speaker 1>So that's useful to And the other thing is that

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<v Speaker 1>it allows them. It allows us to to um to

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<v Speaker 1>fine tune how we think about these various styles. So

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<v Speaker 1>for example, me and you, we might both like value, right,

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<v Speaker 1>but you might like it more than me, So I

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<v Speaker 1>can write a computer program for you that gives you

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<v Speaker 1>more value and less value for me, and so on.

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<v Speaker 1>And these are things that are more difficult to do

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<v Speaker 1>with human beings. So that's all it is. That sounds simple.

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<v Speaker 1>Let me add in here to dovetail to my original

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<v Speaker 1>definition and just go and how the term came about,

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<v Speaker 1>because this probably will help. A consulting firm named Towers

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<v Speaker 1>Watson is who coined the phrase smart beta, and this

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<v Speaker 1>is exactly how they defined it in their literature in

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<v Speaker 1>your two thousand. Smart beta is simply about trying to

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<v Speaker 1>identify good investment ideas that can be structured better. So

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<v Speaker 1>think about it. What do people not like about an

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<v Speaker 1>active mutual fund? Their high cost uh they have the

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<v Speaker 1>manager could be emotional and make decisions based on the

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<v Speaker 1>current trends, and they have distribute capital gains regardless of

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<v Speaker 1>whether you if even if you stayed invested, you've got

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<v Speaker 1>tax bill. Now, if you take that active mutual fund

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<v Speaker 1>strategy and you put it into a rules based index,

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<v Speaker 1>you essentially eliminate the emotion, right because it's gonna rebalance

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<v Speaker 1>at least us said it's a robot. You're gonna lower

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<v Speaker 1>the feet because there's less overhead. And the ETF structure

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<v Speaker 1>so usually like a third as cheap as or a

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<v Speaker 1>third as expensive as an active mutual fund, and they're

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<v Speaker 1>et f s are very tax efficients. You can have

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<v Speaker 1>some decent turnover inside the fund, and yet no capital

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<v Speaker 1>gains get distributed, so you eliminate three of the baggage

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<v Speaker 1>of the active mutual fund when you cross it over. So,

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<v Speaker 1>in a way, Towers Watson definition is true. It's just

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<v Speaker 1>been mutated over the years and piss people off because

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<v Speaker 1>they think that it means smart means better, and it's

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<v Speaker 1>not necessarily better. It's better, a better way to deliver something,

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<v Speaker 1>not you're gonna definitely outperform unless we're clear. There's also

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<v Speaker 1>different names for smart beta. It's not like smart beta

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<v Speaker 1>is the only one, right Tom, Like, what other what

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<v Speaker 1>other terms can mean smart beta? Yeah, I mean there's

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<v Speaker 1>a lot of terminology that's been thrown out. People call

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<v Speaker 1>it strategic beta, tarnative beta, active beta, um, you know.

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<v Speaker 1>And a lot of people will get caught on, get

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<v Speaker 1>caught up in the semantics because they think that, oh,

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<v Speaker 1>if it's not smart beta, it's dumb beta. Right. It's not.

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<v Speaker 1>It's not so binary that it's just one or the other.

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<v Speaker 1>So a lot of people send they get caught up

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<v Speaker 1>in the semantics and kind of forget, like, what is

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<v Speaker 1>the bigger theme here? What are these products giving you?

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<v Speaker 1>What are they offering you? Can you help me embrace

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<v Speaker 1>the complicated a little bit here, because one of the

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<v Speaker 1>main differences with smart beta is with a with a

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<v Speaker 1>normal ETF the most popular ones to play vanilla ones,

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<v Speaker 1>those are all market cap weighted, right, So help me

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<v Speaker 1>better understand what sometimes the differences with smart beta. Right

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<v Speaker 1>when the Towers Watson definition, they would call all that

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<v Speaker 1>bulk beta. So there's just two bulk beta, which is

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<v Speaker 1>market cap weighted. This I think a lot of people

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<v Speaker 1>just called beta. So just tell me what market cap

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<v Speaker 1>is right like that? Right, So the SMP five hundred,

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<v Speaker 1>the bigger the stocks market cap, the bigger the waiting, right,

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<v Speaker 1>so as stocks get bigger, that sort the top waitings

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<v Speaker 1>in the Sapier, Apple, Microsoft, Amazon, Right, you got it. Now,

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<v Speaker 1>that is another way to view smart beta and how

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<v Speaker 1>some people do it. If you're in the index fund

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<v Speaker 1>were world or the vanguard world and you're used to

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<v Speaker 1>market cap weighted products which are very popular, smart beta

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<v Speaker 1>to you seems like a mutation or a twist on

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<v Speaker 1>the market cap waiting structure. So you could actually view

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<v Speaker 1>smart beta from that lens and either look at it

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<v Speaker 1>as you know, a way to try to do better

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<v Speaker 1>than the market cap waited next, because you're gonna change

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<v Speaker 1>the way the index works. You're gonna maybe wait by

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<v Speaker 1>dividends instead of market cap. You're gonna wait by size.

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<v Speaker 1>You could wait by a collection of fundamentals. That is

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<v Speaker 1>another way to view it. So you can see you

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<v Speaker 1>can see smart beta from the active side or from

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<v Speaker 1>the passive side and describe it different ways. But it

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<v Speaker 1>sounds kind of controversial, right, Well, it is. The word

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<v Speaker 1>smart is the controversial part. But I equated to Obamacare,

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<v Speaker 1>right remember that what was the real name of the bill?

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<v Speaker 1>I don't even remember the patient and affordable care branding

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<v Speaker 1>right there, right, so even Obama started calling it Obamacare.

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<v Speaker 1>Smart beta is just a buzzword that you cannot beat down.

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<v Speaker 1>People have come along, like Tom said morning Star Targic

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<v Speaker 1>called a strategic beta, scientific beta, alternative beta, quantiment indexes.

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<v Speaker 1>How about that one anti benchmark is the France calls

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<v Speaker 1>it that active betas You just keep coming back to

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<v Speaker 1>smart beta. Smart beta sticks. It's sticks. But the words

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<v Speaker 1>smart is what has made it controversial because at the

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<v Speaker 1>end of the day, you may or may not outperform.

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<v Speaker 1>You're just going to have a different return stream than

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<v Speaker 1>a market cap weighted index. Okay, Eric, can we actually

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<v Speaker 1>break this thing down and talk about smart beta in

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<v Speaker 1>real life. Let's call it a case study. Do you

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<v Speaker 1>have an example of a smart beta e t F

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<v Speaker 1>and can you walk me through how how it did

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<v Speaker 1>what it did? Right? So, here's a classic one came

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<v Speaker 1>out in two thousand five. So this is like early

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<v Speaker 1>settler smart beta product, right, This was the Power Shares FO.

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<v Speaker 1>I can picture it out in the homestead it Well,

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<v Speaker 1>back then it was a lot of open frontier people

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<v Speaker 1>put flags everywhere. Now that's why the t flants. He

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<v Speaker 1>is very crowded, hard to come up with new ideas.

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<v Speaker 1>There's not much white space left, so to speak. But

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<v Speaker 1>this really was one of the first ones. It's the

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<v Speaker 1>Power Shares Foutsie Raffie US one thousand portfolio tik R

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<v Speaker 1>PRF can see that again. No, Um, here's what it does.

0:11:08.800 --> 0:11:11.600
<v Speaker 1>It's pretty simple. It tracks stocks based on four fundamental

0:11:11.679 --> 0:11:15.480
<v Speaker 1>measures right book value, cash flow, sales, and dividends. So

0:11:16.000 --> 0:11:19.240
<v Speaker 1>it just screens stocks a thousand stocks by those metrics,

0:11:19.480 --> 0:11:22.559
<v Speaker 1>comes up with a score, sorts them by that, and

0:11:22.640 --> 0:11:25.319
<v Speaker 1>then every quarter it looks for which ones go to

0:11:25.400 --> 0:11:27.040
<v Speaker 1>the top, and then it waits them by the score,

0:11:27.120 --> 0:11:29.800
<v Speaker 1>and that's the that's how the index works, and that's

0:11:29.840 --> 0:11:32.040
<v Speaker 1>what the e t F tracks. It just that's all

0:11:32.080 --> 0:11:34.319
<v Speaker 1>it does. And it it goes on like a little robot.

0:11:34.520 --> 0:11:37.280
<v Speaker 1>It is. It's a total how often does it rebalance quarterly?

0:11:37.880 --> 0:11:40.439
<v Speaker 1>So it is it's almost like a robotic version of

0:11:40.480 --> 0:11:42.400
<v Speaker 1>a stock analyst, right, because it's doing things that a

0:11:42.480 --> 0:11:45.680
<v Speaker 1>researcher would look for. Those are definitely popular fundamental metrics.

0:11:46.280 --> 0:11:49.240
<v Speaker 1>Here's where I think this is a great example of

0:11:49.320 --> 0:11:51.560
<v Speaker 1>how it works, especially on the lack of emotion side.

0:11:51.920 --> 0:11:54.559
<v Speaker 1>In two thousand and eight, right bank stocks were hated.

0:11:55.160 --> 0:11:58.040
<v Speaker 1>Nobody wanted to buy City Group at any of these stocks. Well,

0:11:58.080 --> 0:12:00.240
<v Speaker 1>as you know, they got cheaper on a value ation

0:12:00.280 --> 0:12:03.800
<v Speaker 1>basis because everybody sold them. Well, this thing is a robot.

0:12:03.840 --> 0:12:05.839
<v Speaker 1>It doesn't it doesn't read the news, it doesn't know

0:12:05.880 --> 0:12:07.840
<v Speaker 1>what's going on. It isn't not getting yelled at by clients.

0:12:08.120 --> 0:12:11.480
<v Speaker 1>So it rebalanced into financials in a big way. It

0:12:11.559 --> 0:12:14.880
<v Speaker 1>had fifty financials in the beginning of two thousand nine.

0:12:15.280 --> 0:12:17.840
<v Speaker 1>Doubled down on it, doubled down it went. It went

0:12:17.920 --> 0:12:20.920
<v Speaker 1>into the burning building, as Warren Buffett would say, big

0:12:21.000 --> 0:12:26.320
<v Speaker 1>time with with a suit of gasoline. And on top

0:12:26.360 --> 0:12:28.439
<v Speaker 1>of that, I mean, like, I assume maybe the guy

0:12:28.520 --> 0:12:31.280
<v Speaker 1>in charge of this who is whom so the person

0:12:31.320 --> 0:12:33.839
<v Speaker 1>who made the indexes Rob or not, and I'm guessing

0:12:33.960 --> 0:12:36.079
<v Speaker 1>Rob maybe got some heat for that he did. So

0:12:36.360 --> 0:12:38.319
<v Speaker 1>I interviewed him from my book and he said that

0:12:38.760 --> 0:12:41.840
<v Speaker 1>institutional funds that tracked that index on a separate account

0:12:41.840 --> 0:12:44.360
<v Speaker 1>basis called up and said, do not do the rebalance.

0:12:44.480 --> 0:12:47.880
<v Speaker 1>We do not want to do this exactly, and in

0:12:47.960 --> 0:12:49.439
<v Speaker 1>separate account you can do that. The e t F

0:12:49.559 --> 0:12:53.199
<v Speaker 1>cannot well guess who won after five years. Basically, that

0:12:53.320 --> 0:12:58.680
<v Speaker 1>rebalance accounted for almost all of the firm's out performance

0:12:58.720 --> 0:13:05.400
<v Speaker 1>over the next five years and came from the financials

0:13:05.679 --> 0:13:08.959
<v Speaker 1>read that one rebalance. Now Ben Johnson the Morning Star

0:13:09.040 --> 0:13:11.560
<v Speaker 1>calls it the immaculate rebalance. He thinks that I'm bringing

0:13:11.640 --> 0:13:14.280
<v Speaker 1>up a extreme situation. He also brings up that a

0:13:14.320 --> 0:13:16.280
<v Speaker 1>lot of investors in the e t F left too

0:13:16.720 --> 0:13:19.360
<v Speaker 1>because they couldn't handle it, and so part of smart beta,

0:13:19.400 --> 0:13:22.000
<v Speaker 1>this brings up the behavior if you really want to

0:13:22.040 --> 0:13:24.760
<v Speaker 1>benefit from it, and the lack of emotion, you have

0:13:24.880 --> 0:13:26.760
<v Speaker 1>to hang in there. So the e t F did

0:13:26.800 --> 0:13:28.400
<v Speaker 1>its job going the burning building, but a lot of

0:13:28.440 --> 0:13:31.640
<v Speaker 1>investors couldn't handle the heat either. So that's why all

0:13:31.720 --> 0:13:34.439
<v Speaker 1>of that is important to point out there. But that

0:13:34.600 --> 0:13:37.480
<v Speaker 1>is an example of how the smart beta can work

0:13:37.559 --> 0:13:40.520
<v Speaker 1>for you and arguably be better than a human being manager.

0:13:41.200 --> 0:13:45.280
<v Speaker 1>Near do you have a case study that rivals erics? Well,

0:13:45.360 --> 0:13:47.199
<v Speaker 1>and I don't know if it rivals erics, but it's

0:13:47.200 --> 0:13:51.199
<v Speaker 1>a little bit different. Okay, why not? Okay, yeah, let's

0:13:51.280 --> 0:13:53.880
<v Speaker 1>let's let's let's get it on. Um. There are two

0:13:53.880 --> 0:13:55.439
<v Speaker 1>et f s that I wanted to bring up that

0:13:55.600 --> 0:13:58.520
<v Speaker 1>illustrate the point that I made earlier about giving you

0:13:59.120 --> 0:14:03.040
<v Speaker 1>different types different depths of exposure. Um. So, for example,

0:14:03.120 --> 0:14:06.160
<v Speaker 1>I looked at value at the at value as as

0:14:06.160 --> 0:14:09.240
<v Speaker 1>an active strategy, and one value e t F, which

0:14:09.280 --> 0:14:11.959
<v Speaker 1>is basically a factor, right, like to simplify that, like

0:14:12.400 --> 0:14:15.680
<v Speaker 1>value and there are many different types of factors. Value

0:14:15.840 --> 0:14:19.040
<v Speaker 1>is basically probably the most famous one, right, Yeah, it's

0:14:19.120 --> 0:14:20.920
<v Speaker 1>most famous, and for a good reason, by the way,

0:14:21.000 --> 0:14:25.160
<v Speaker 1>because in the it has it works very often. I mean,

0:14:25.160 --> 0:14:26.760
<v Speaker 1>in other words, if if you looked, if you back

0:14:26.800 --> 0:14:29.880
<v Speaker 1>tested all these various types of factors value and quality

0:14:29.960 --> 0:14:33.400
<v Speaker 1>and momentum and so on, the batting the success rate

0:14:33.480 --> 0:14:36.560
<v Speaker 1>for value over rolling periods is exceedingly high, so it's

0:14:36.680 --> 0:14:41.400
<v Speaker 1>very popular over time, that's right. And it's also intuitively appealing,

0:14:41.520 --> 0:14:43.880
<v Speaker 1>right because it makes sense that if you buy a

0:14:44.000 --> 0:14:46.240
<v Speaker 1>company that's beaten down, you should get paid more than

0:14:46.280 --> 0:14:48.520
<v Speaker 1>a company that's not. Right. It just that has intuitive

0:14:48.800 --> 0:14:50.960
<v Speaker 1>appeal and the and the you know, and the numbers

0:14:51.040 --> 0:14:53.560
<v Speaker 1>check out. So that's why it's so popular. And there

0:14:53.600 --> 0:14:55.880
<v Speaker 1>are there are two different ETFs that you can buy

0:14:56.160 --> 0:14:58.400
<v Speaker 1>that give you different types of exposure to it. One

0:14:58.640 --> 0:15:01.800
<v Speaker 1>is VTV, which is the Vanguard Value e t F,

0:15:02.400 --> 0:15:05.160
<v Speaker 1>and that E t F sorts stocks based on a

0:15:05.320 --> 0:15:09.200
<v Speaker 1>value uh based on a value sort, and then awaits

0:15:09.240 --> 0:15:11.640
<v Speaker 1>them by market cap. So that's one way that you

0:15:11.680 --> 0:15:14.360
<v Speaker 1>can get value. But by contrast, you can also buy

0:15:14.400 --> 0:15:16.640
<v Speaker 1>a different value t F that's v l U E,

0:15:16.880 --> 0:15:19.200
<v Speaker 1>which is the I Shares Edge m S C I

0:15:19.800 --> 0:15:22.560
<v Speaker 1>U S a value factor E t F. Don't ask

0:15:22.600 --> 0:15:24.360
<v Speaker 1>me why these names have to be this long. And

0:15:24.480 --> 0:15:27.720
<v Speaker 1>the difference here is that this two sorts by value,

0:15:27.800 --> 0:15:30.640
<v Speaker 1>but then it also waits by value, and so the

0:15:30.720 --> 0:15:33.400
<v Speaker 1>difference is you get more value exposure in the Eye

0:15:33.440 --> 0:15:35.640
<v Speaker 1>Shares Fund than you do in the Vanguard fund. That

0:15:35.800 --> 0:15:38.240
<v Speaker 1>that doesn't make the Eye Shares fund better, but it

0:15:38.320 --> 0:15:41.120
<v Speaker 1>allows investors to express a preference as to how much

0:15:41.240 --> 0:15:43.600
<v Speaker 1>value they want in their portfolio. If they want more,

0:15:43.720 --> 0:15:45.360
<v Speaker 1>they go for the eye shares. If they want less,

0:15:45.400 --> 0:15:47.080
<v Speaker 1>they go for the vangord Um. I would like to

0:15:47.160 --> 0:15:49.640
<v Speaker 1>use a metaphor we Tom and I we use that.

0:15:49.720 --> 0:15:51.360
<v Speaker 1>We have this thing called the smart data spectrum and

0:15:51.400 --> 0:15:53.600
<v Speaker 1>what Near just described. If you could picture a spectrum.

0:15:54.120 --> 0:15:55.840
<v Speaker 1>On one side, you have v t V. It's got

0:15:56.280 --> 0:15:57.640
<v Speaker 1>just a little bit of value. It's going to do

0:15:57.720 --> 0:16:00.960
<v Speaker 1>better if the regular market to doing well because it's

0:16:01.040 --> 0:16:04.200
<v Speaker 1>mostly bulk beta. V l u E is sort of

0:16:04.240 --> 0:16:06.760
<v Speaker 1>in the middle um and the value factor in the

0:16:06.840 --> 0:16:08.960
<v Speaker 1>name is important because when you see that, that means

0:16:09.000 --> 0:16:11.200
<v Speaker 1>it's waiting by the factor that's going to give you

0:16:11.320 --> 0:16:13.320
<v Speaker 1>more juice. It's almost like v t V is o

0:16:13.440 --> 0:16:17.960
<v Speaker 1>duels and vlu E barely any alcohol, and we have

0:16:18.040 --> 0:16:20.080
<v Speaker 1>to think like like two cases to get you know,

0:16:20.200 --> 0:16:23.600
<v Speaker 1>buzz the middle. There is vlu E that's going to

0:16:23.640 --> 0:16:25.760
<v Speaker 1>be more like just a regular beer like a Budweiser.

0:16:26.240 --> 0:16:29.600
<v Speaker 1>But then there's even ones that go further that are

0:16:29.760 --> 0:16:32.400
<v Speaker 1>more hardcore value. Because v l u E and Near

0:16:32.480 --> 0:16:35.720
<v Speaker 1>probably knows this has a volatility screen, So it's got

0:16:35.800 --> 0:16:40.040
<v Speaker 1>this like screen to kick out really hardcore value stocks

0:16:40.120 --> 0:16:43.000
<v Speaker 1>because it's trying to sell it to advisors who don't

0:16:43.000 --> 0:16:45.920
<v Speaker 1>want that crazy of a ride. But there are more

0:16:46.120 --> 0:16:50.480
<v Speaker 1>pure value like west Gray's q val the quant shares

0:16:50.800 --> 0:16:52.360
<v Speaker 1>that are on the far end, which would be like

0:16:52.440 --> 0:16:58.120
<v Speaker 1>that German beer that has exactly So I think this

0:16:58.360 --> 0:17:02.200
<v Speaker 1>is a fascinating development in the E t F world.

0:17:02.280 --> 0:17:05.080
<v Speaker 1>In this could make smart beta confusing to people, but

0:17:05.359 --> 0:17:07.640
<v Speaker 1>really what you got to figure out is how much

0:17:07.800 --> 0:17:11.720
<v Speaker 1>juice or factor content, how much aggressiveness do you want

0:17:11.840 --> 0:17:13.480
<v Speaker 1>in this smart beta e t F because they have

0:17:13.600 --> 0:17:16.560
<v Speaker 1>all flavors, Tom, can you give me a case study

0:17:16.680 --> 0:17:19.680
<v Speaker 1>the tops erics. Yeah, so mine's a little bit different

0:17:19.800 --> 0:17:22.080
<v Speaker 1>in that, you know what the example that Eric gave

0:17:22.200 --> 0:17:24.320
<v Speaker 1>is more takes the mind of the act of manager

0:17:24.400 --> 0:17:27.520
<v Speaker 1>and it kicks out the emotion. Right. This the product

0:17:27.560 --> 0:17:28.919
<v Speaker 1>I want to talk about is a little bit more

0:17:28.960 --> 0:17:32.320
<v Speaker 1>about targeting a specific outcome or helping somebody targeted outcomes.

0:17:32.359 --> 0:17:33.879
<v Speaker 1>So let's just say you want to own the market,

0:17:34.400 --> 0:17:36.040
<v Speaker 1>but you want to own it in the least vollowed

0:17:36.040 --> 0:17:38.080
<v Speaker 1>a way. You don't want to own the riskiest stocks.

0:17:38.320 --> 0:17:40.840
<v Speaker 1>So I want to bring up SPLV, which is the

0:17:41.040 --> 0:17:45.639
<v Speaker 1>SMP five Low Volatility et F by Power Shares. The

0:17:45.760 --> 0:17:47.800
<v Speaker 1>name long enough. I was gonna say, Eric, we should

0:17:47.800 --> 0:17:50.119
<v Speaker 1>do a whole episode about the longest names in the

0:17:50.200 --> 0:17:51.840
<v Speaker 1>e t F in the et F world. A new

0:17:51.880 --> 0:17:53.960
<v Speaker 1>one was just filed that broke the record. Really Yeah,

0:17:54.000 --> 0:17:57.639
<v Speaker 1>the goobelly pet parents, Pet companions and their parents and

0:17:57.760 --> 0:18:02.200
<v Speaker 1>pet Ecosystem TMF. What I know, there's a multiple reasons

0:18:02.240 --> 0:18:05.960
<v Speaker 1>why that's insanely amazing. We don't know yet, but it's

0:18:06.000 --> 0:18:08.600
<v Speaker 1>gotta have five. I think it's gonna be kitty or doggie,

0:18:08.640 --> 0:18:11.520
<v Speaker 1>but um, that's a whole different story. A couple of

0:18:11.520 --> 0:18:14.719
<v Speaker 1>east also have thirteen fourteen words in the name, but um,

0:18:14.840 --> 0:18:17.600
<v Speaker 1>that one's long. Okay, back to SPLV, uh sure, And

0:18:17.760 --> 0:18:20.320
<v Speaker 1>why I wanted to highlight this one is because it's

0:18:20.359 --> 0:18:22.880
<v Speaker 1>in a smart bit of category that's gotten pretty popular.

0:18:23.440 --> 0:18:25.520
<v Speaker 1>It's just it's low volatility, right, so it's owning the

0:18:25.560 --> 0:18:28.720
<v Speaker 1>market in the least volatial way. So this launched back

0:18:28.760 --> 0:18:31.480
<v Speaker 1>in two thousand and eleven. And if you remember what

0:18:31.600 --> 0:18:33.520
<v Speaker 1>happened in the summer of two thousand eleven was the

0:18:33.640 --> 0:18:36.119
<v Speaker 1>U S got downgraded by the SMP. There's a lot

0:18:36.160 --> 0:18:38.000
<v Speaker 1>of market volatility, and this thing kind of got put

0:18:38.080 --> 0:18:40.879
<v Speaker 1>on the map like, hey, it's down less than the market.

0:18:41.600 --> 0:18:45.520
<v Speaker 1>So it's very simple messogy it is and it's very simple,

0:18:45.520 --> 0:18:47.160
<v Speaker 1>and I think this is why it's had some success

0:18:47.280 --> 0:18:49.680
<v Speaker 1>is it takes the SMP five hundred and it says

0:18:49.800 --> 0:18:51.720
<v Speaker 1>we are only going to take the one hundred least

0:18:51.800 --> 0:18:55.160
<v Speaker 1>vottle stocks. It's very simple, right, so you're gonna own

0:18:55.200 --> 0:18:58.280
<v Speaker 1>on hundred least bottle stocks in the SMP. So when

0:18:58.320 --> 0:19:00.440
<v Speaker 1>you look at you know, some big draw sounds in

0:19:00.520 --> 0:19:03.400
<v Speaker 1>the SMP, it's down less, holds up a little bit better.

0:19:04.040 --> 0:19:06.040
<v Speaker 1>So it's kind of maybe like a little bit of

0:19:06.080 --> 0:19:07.639
<v Speaker 1>a foam O E t F that you still want

0:19:07.680 --> 0:19:10.600
<v Speaker 1>to own the market, but you want to do it

0:19:10.640 --> 0:19:13.360
<v Speaker 1>in at least volowed away um. And it's twenty five

0:19:13.359 --> 0:19:15.080
<v Speaker 1>basis points. It's been out for a lot. It's gotten

0:19:15.080 --> 0:19:18.440
<v Speaker 1>pretty big, about six six or seven billion. Also like

0:19:18.520 --> 0:19:21.359
<v Speaker 1>that you didn't uh, you didn't pampa product that you

0:19:21.440 --> 0:19:23.520
<v Speaker 1>used to work on. That's that's classic of you. And

0:19:23.840 --> 0:19:25.720
<v Speaker 1>let me talk. I want to add on to this

0:19:25.720 --> 0:19:28.639
<v Speaker 1>because it's interesting. When SPLV came out, it tracks just

0:19:28.800 --> 0:19:31.879
<v Speaker 1>those one stocks, so it has no sector. It doesn't

0:19:31.880 --> 0:19:34.040
<v Speaker 1>care where it just goes where it ends up, having

0:19:34.359 --> 0:19:37.560
<v Speaker 1>typically overweight to utilities and staples, which are always usually

0:19:37.600 --> 0:19:41.600
<v Speaker 1>the less volatile stocks. So some investors think, oh, well

0:19:41.800 --> 0:19:44.920
<v Speaker 1>those are more susceptible to rising rates, or they don't

0:19:44.920 --> 0:19:47.639
<v Speaker 1>want to be overweight these sectors. So our Shares came

0:19:47.640 --> 0:19:50.560
<v Speaker 1>out with a version that has sector bands, and then

0:19:50.600 --> 0:19:52.560
<v Speaker 1>there's multiple products that do a little of both and

0:19:52.640 --> 0:19:55.200
<v Speaker 1>so but SPLV was like sort of the speaking of

0:19:55.240 --> 0:19:57.040
<v Speaker 1>the frontier. That was like the first one that nailed

0:19:57.080 --> 0:20:00.320
<v Speaker 1>down low vall. Now there's probably forty five produc that

0:20:00.440 --> 0:20:03.280
<v Speaker 1>do some twist on that to sort of again it's

0:20:03.280 --> 0:20:05.119
<v Speaker 1>like soda flavors or whatever, and they serve it up

0:20:05.119 --> 0:20:08.480
<v Speaker 1>in different ways. But SPLV was the first. How often

0:20:08.560 --> 0:20:11.560
<v Speaker 1>does it change those one stocks that it holds. It

0:20:11.600 --> 0:20:13.680
<v Speaker 1>does it every quarter. Every every quarter, it's going to

0:20:13.760 --> 0:20:15.720
<v Speaker 1>rank the stocks and it's going to take the one hundred,

0:20:16.680 --> 0:20:19.800
<v Speaker 1>which can be tough because let's say utilities got creamed, right,

0:20:20.320 --> 0:20:22.199
<v Speaker 1>You're gonna have to take some down performance until let

0:20:22.280 --> 0:20:25.120
<v Speaker 1>thing rebalances into wherever the next low ball is. That's

0:20:25.160 --> 0:20:33.680
<v Speaker 1>why these things take a stomach Okay, I love these

0:20:33.760 --> 0:20:36.000
<v Speaker 1>case studies that really helped me figure out sort of

0:20:36.320 --> 0:20:40.360
<v Speaker 1>how these products can perform nearer. I'm gonna come back

0:20:40.359 --> 0:20:42.840
<v Speaker 1>to you because in addition to writing for Bloomberg, Godfly,

0:20:43.359 --> 0:20:46.440
<v Speaker 1>you also touch other people's money right right Well, in

0:20:46.680 --> 0:20:49.280
<v Speaker 1>addition to writing for Bloomberg, I also run an asset

0:20:49.320 --> 0:20:52.359
<v Speaker 1>management firm. Um, so you know, I manage money for

0:20:52.440 --> 0:20:55.840
<v Speaker 1>other people, and um, I am. I've always been a

0:20:55.920 --> 0:20:59.080
<v Speaker 1>big believer in active management. I think that the evidence

0:20:59.640 --> 0:21:03.120
<v Speaker 1>for are certain types. There's a lot of quackery out there,

0:21:03.400 --> 0:21:06.720
<v Speaker 1>without question, but I think, um, the evidence for the

0:21:06.960 --> 0:21:10.000
<v Speaker 1>types of factors that we're talking about today, Um, you know,

0:21:10.240 --> 0:21:13.440
<v Speaker 1>value and some of the other's quality, momentum and so on,

0:21:13.920 --> 0:21:16.879
<v Speaker 1>I think is is well documented in the academic literature,

0:21:16.920 --> 0:21:19.520
<v Speaker 1>and I think not controversial. Everyone agrees about it and

0:21:19.600 --> 0:21:22.520
<v Speaker 1>so on, um and so um. And so I've I've

0:21:22.560 --> 0:21:25.440
<v Speaker 1>been sort of an early adopter of these smart beta

0:21:25.480 --> 0:21:28.520
<v Speaker 1>funds just because their active management more cheaply. So, if

0:21:28.560 --> 0:21:30.800
<v Speaker 1>you believe in active management, and you should pay as

0:21:30.840 --> 0:21:32.879
<v Speaker 1>little as possible for it, and so smart data is

0:21:32.920 --> 0:21:35.040
<v Speaker 1>perfect for that. The question is, Okay, now you've got

0:21:35.080 --> 0:21:37.080
<v Speaker 1>all these options, what do you do with them, And

0:21:37.280 --> 0:21:39.080
<v Speaker 1>this is where it's early days, and there's a lot

0:21:39.119 --> 0:21:40.960
<v Speaker 1>of confusion about what to do. But what I would

0:21:41.000 --> 0:21:44.120
<v Speaker 1>propose and what I actually do is I use them

0:21:44.160 --> 0:21:47.639
<v Speaker 1>for simple diversification. You know, it stands to reason that

0:21:47.680 --> 0:21:49.600
<v Speaker 1>if you don't know which strategy is going to do

0:21:49.680 --> 0:21:51.840
<v Speaker 1>well over the next period, then you just want to

0:21:51.880 --> 0:21:55.040
<v Speaker 1>diversify across these strategies. In my opinion, it just makes

0:21:55.080 --> 0:21:57.480
<v Speaker 1>sense to instead of putting all your eggs in the

0:21:57.560 --> 0:22:00.760
<v Speaker 1>market cap index or value index or whatever, have exposure

0:22:00.800 --> 0:22:03.800
<v Speaker 1>to various types of things. And these smart data products

0:22:04.119 --> 0:22:06.680
<v Speaker 1>allow you to do that relatively cheaply, and I think

0:22:06.720 --> 0:22:08.680
<v Speaker 1>that's the first step on the bus. If investors take

0:22:08.680 --> 0:22:11.359
<v Speaker 1>away anything from this podcast, in my opinion, what they

0:22:11.400 --> 0:22:14.080
<v Speaker 1>ought to take is look at your portfolio, see what

0:22:14.200 --> 0:22:16.360
<v Speaker 1>kind of exposures you have. If you have too much

0:22:16.440 --> 0:22:19.439
<v Speaker 1>in one particular type or style of investing or factor,

0:22:19.760 --> 0:22:22.160
<v Speaker 1>however you want to call it, then look at look

0:22:22.200 --> 0:22:25.080
<v Speaker 1>at smart data funds and diversify across them so that

0:22:25.160 --> 0:22:27.600
<v Speaker 1>your eggs are in different baskets. Which puts me back

0:22:27.640 --> 0:22:32.960
<v Speaker 1>in a dark room touching an elephant um tom when

0:22:33.040 --> 0:22:35.679
<v Speaker 1>you are on the other side of the table. How

0:22:35.760 --> 0:22:38.520
<v Speaker 1>are you guys seeing investors use this both from like

0:22:38.600 --> 0:22:41.480
<v Speaker 1>a retail perspective but also like the institutional Yeah, so

0:22:41.520 --> 0:22:43.800
<v Speaker 1>I think it really comes down to, now the ets

0:22:43.880 --> 0:22:46.119
<v Speaker 1>that are coming out, they're trying to solve a problem, right,

0:22:46.160 --> 0:22:47.560
<v Speaker 1>So it really comes down to what are you trying

0:22:47.600 --> 0:22:50.840
<v Speaker 1>to solve? So are you using an active manager that

0:22:50.920 --> 0:22:53.280
<v Speaker 1>maybe you're not happy with, like you have a value manager,

0:22:53.440 --> 0:22:55.600
<v Speaker 1>Maybe you might want to look at a value smart

0:22:55.600 --> 0:22:57.520
<v Speaker 1>beta et F Do you want to be in the market,

0:22:57.640 --> 0:23:00.680
<v Speaker 1>but you want to be in the lowest vault as possible.

0:23:00.880 --> 0:23:03.159
<v Speaker 1>So it's about talking to your clients, are talking to

0:23:03.200 --> 0:23:06.560
<v Speaker 1>investors and finding a problem. It's not just all the

0:23:06.640 --> 0:23:09.920
<v Speaker 1>tools are now out there, right, the toolbox has gotten

0:23:10.200 --> 0:23:12.320
<v Speaker 1>really big. It's just about figuring out what are you

0:23:12.359 --> 0:23:14.680
<v Speaker 1>trying to accomplish. And that's the conversation we constantly have

0:23:14.760 --> 0:23:16.560
<v Speaker 1>with clients that this is the problem that I have.

0:23:16.720 --> 0:23:19.399
<v Speaker 1>I want income, but I also want low vall income.

0:23:19.520 --> 0:23:21.080
<v Speaker 1>So let's build a product that will give to you,

0:23:21.280 --> 0:23:24.080
<v Speaker 1>let's say, dividend paying stocks, but also with like a

0:23:24.160 --> 0:23:28.080
<v Speaker 1>low vall component to it. Solutions, Yeah, it has them exactly.

0:23:29.680 --> 0:23:34.440
<v Speaker 1>Heyntroll here now that I'm the editor of Bloomberg business Week.

0:23:34.880 --> 0:23:37.800
<v Speaker 1>I pulled a few strings for our loyal podcast listeners.

0:23:38.520 --> 0:23:43.360
<v Speaker 1>Go to business Week mag dot com slash trillions right

0:23:43.440 --> 0:23:47.600
<v Speaker 1>now for a thirty day free trial. If you like

0:23:47.720 --> 0:23:50.399
<v Speaker 1>what we're doing here on trillions, you're gonna love the

0:23:50.600 --> 0:23:54.520
<v Speaker 1>stories that we published in Bloomberg business Week. Here's that

0:23:54.640 --> 0:23:58.120
<v Speaker 1>special offer one more time. Go to business Week mag

0:23:58.480 --> 0:24:07.879
<v Speaker 1>dot com slash trillions for your free thirty day trial. Thanks. Okay,

0:24:08.040 --> 0:24:12.119
<v Speaker 1>last topic, what kind of due diligence should investors be

0:24:12.240 --> 0:24:17.080
<v Speaker 1>doing before they pick up these tools? Um, okay, I'll

0:24:17.119 --> 0:24:19.040
<v Speaker 1>take a crack at this. So when I look at

0:24:19.080 --> 0:24:21.680
<v Speaker 1>smart beta again, we have this spectrum and the way

0:24:21.800 --> 0:24:24.480
<v Speaker 1>we determine where on the spectrum it goes. Again, the

0:24:24.600 --> 0:24:27.240
<v Speaker 1>more quote beta that is in it, the more it

0:24:27.280 --> 0:24:31.000
<v Speaker 1>could just be a replacement. I think. The more volatile

0:24:31.080 --> 0:24:33.159
<v Speaker 1>it is, the more you could add it on as

0:24:33.240 --> 0:24:34.760
<v Speaker 1>like a little bit of hot sauce. But anyway to

0:24:35.840 --> 0:24:39.360
<v Speaker 1>determine what you're looking at, I would suggest a few things.

0:24:39.480 --> 0:24:42.040
<v Speaker 1>One is the index waiting methodology. Does it wait by

0:24:42.080 --> 0:24:45.760
<v Speaker 1>market cap? If so, it's probably gonna be not that volatile,

0:24:45.840 --> 0:24:48.320
<v Speaker 1>not that much exposure to any factor or anything. But

0:24:48.520 --> 0:24:51.479
<v Speaker 1>you get a little is it weighted towards the factor itself?

0:24:51.600 --> 0:24:54.240
<v Speaker 1>That's important. That's number one. Number two is the standard deviation,

0:24:54.359 --> 0:24:57.320
<v Speaker 1>which it's a simple term. If you fell asleep and

0:24:57.359 --> 0:24:59.320
<v Speaker 1>stats class like I did, I had to relearn it,

0:24:59.720 --> 0:25:05.200
<v Speaker 1>but so useful. It's just basically looking at past volatility

0:25:05.280 --> 0:25:07.560
<v Speaker 1>of this fund or stock or whatever it could be,

0:25:07.600 --> 0:25:09.920
<v Speaker 1>use for anything, and just telling you how bumpy the

0:25:10.000 --> 0:25:12.480
<v Speaker 1>ride will be. It's like almost like a ski slopes line,

0:25:12.560 --> 0:25:15.440
<v Speaker 1>like is this a black diamond or a blue square?

0:25:15.920 --> 0:25:19.680
<v Speaker 1>So standard deviation is basically how bumpy the ride will be.

0:25:20.000 --> 0:25:21.960
<v Speaker 1>But you need it relative to something. So I said,

0:25:22.000 --> 0:25:24.119
<v Speaker 1>just taking the standard deviation of s P Y or

0:25:24.200 --> 0:25:26.639
<v Speaker 1>the SMP fire, which I believe right now might be

0:25:26.680 --> 0:25:29.920
<v Speaker 1>around nine. That means there's a two thirds chance that

0:25:30.000 --> 0:25:32.119
<v Speaker 1>the annual return of the SMP over the next year

0:25:32.200 --> 0:25:35.320
<v Speaker 1>will be one way or the other, up or down.

0:25:35.720 --> 0:25:39.159
<v Speaker 1>So where is it versus nine percent? If it's you

0:25:39.359 --> 0:25:41.480
<v Speaker 1>are going to have a real volatile smart beta product.

0:25:41.800 --> 0:25:43.760
<v Speaker 1>If it's nine, it's about the same. And there's some

0:25:43.880 --> 0:25:46.280
<v Speaker 1>that are lower, like the low volley t F might

0:25:46.320 --> 0:25:49.879
<v Speaker 1>be more like eight percent, So figure that out. That

0:25:50.080 --> 0:25:52.080
<v Speaker 1>is huge because you don't want to buy something that's

0:25:52.119 --> 0:25:55.280
<v Speaker 1>too spicy for you or too lame or you know,

0:25:55.359 --> 0:25:57.280
<v Speaker 1>doesn't move around enough. So I think those are two

0:25:57.320 --> 0:25:59.800
<v Speaker 1>important stats. And then of course the fee I think

0:26:00.000 --> 0:26:02.000
<v Speaker 1>ast matter here and now you can get a smart

0:26:02.040 --> 0:26:05.239
<v Speaker 1>beta e t F for under twenty basis points. Uh,

0:26:05.359 --> 0:26:08.159
<v Speaker 1>so you should shop around a little bit. Although when

0:26:08.240 --> 0:26:10.880
<v Speaker 1>you're swinging for the fences, the fee isn't quite as important.

0:26:10.920 --> 0:26:13.280
<v Speaker 1>But I think expense ratio is interesting because the range

0:26:13.359 --> 0:26:16.880
<v Speaker 1>now is from a D to nine. There's a big range,

0:26:16.920 --> 0:26:19.080
<v Speaker 1>and there's a lot of cost pressure going on in

0:26:19.160 --> 0:26:22.000
<v Speaker 1>this space. So near when when our two D two

0:26:22.240 --> 0:26:24.200
<v Speaker 1>with the head of Peter Lynch shows up at your door,

0:26:24.280 --> 0:26:27.119
<v Speaker 1>what what do you do? Well? I think the I

0:26:27.560 --> 0:26:30.040
<v Speaker 1>think as an investor, you want to look at UM

0:26:30.280 --> 0:26:31.960
<v Speaker 1>if you look at nothing else, you want to look

0:26:32.000 --> 0:26:34.399
<v Speaker 1>at what's what's the factor that I'm buying and how

0:26:34.480 --> 0:26:36.000
<v Speaker 1>much am I paying for it? I think those are

0:26:36.080 --> 0:26:38.840
<v Speaker 1>one and two. But if I if I can UM,

0:26:39.040 --> 0:26:40.840
<v Speaker 1>let me, let me just use the time I have

0:26:41.040 --> 0:26:44.400
<v Speaker 1>for just just a little bit of advocacy for this industry.

0:26:44.840 --> 0:26:47.560
<v Speaker 1>I think I think there's something very important that we

0:26:47.680 --> 0:26:49.520
<v Speaker 1>need to solve for UM and I think we need

0:26:49.560 --> 0:26:52.040
<v Speaker 1>to solve for it very quickly if if smart beta

0:26:52.119 --> 0:26:54.159
<v Speaker 1>is going to take off, and that is, we need

0:26:54.240 --> 0:26:56.680
<v Speaker 1>to have some sort of labeling system to continue the

0:26:56.880 --> 0:27:00.000
<v Speaker 1>analogy from earlier UM that tells you how much alcohol

0:27:00.200 --> 0:27:03.520
<v Speaker 1>content is in the e t F is in this factor. So,

0:27:03.520 --> 0:27:05.600
<v Speaker 1>in other words, you need you if you're looking at

0:27:05.640 --> 0:27:09.000
<v Speaker 1>five value value factory t s. Let's just say you

0:27:09.119 --> 0:27:11.640
<v Speaker 1>have no idea how much value is in one versus

0:27:11.680 --> 0:27:13.800
<v Speaker 1>the other, and so as a consumer you can't make

0:27:13.840 --> 0:27:16.000
<v Speaker 1>it a smart decision about which one to buy. And

0:27:16.080 --> 0:27:18.040
<v Speaker 1>so we need to come up with a standardized system

0:27:18.280 --> 0:27:20.719
<v Speaker 1>to be able to say, right there almost like an

0:27:20.840 --> 0:27:23.240
<v Speaker 1>expense ratio, like you know what it costs, right It's

0:27:23.240 --> 0:27:25.840
<v Speaker 1>almost like an expense ratio that tells you this has

0:27:26.040 --> 0:27:28.520
<v Speaker 1>this percentage of value in it. And we can do

0:27:28.600 --> 0:27:30.280
<v Speaker 1>in any We can do it on a ten point scale,

0:27:30.359 --> 0:27:32.639
<v Speaker 1>we can do it on a D scale, we can

0:27:32.680 --> 0:27:34.520
<v Speaker 1>do it in any way you want. But we have

0:27:34.720 --> 0:27:36.159
<v Speaker 1>to do it, and there's a way to measure it.

0:27:36.200 --> 0:27:38.280
<v Speaker 1>It would be very easy to do. The industry is

0:27:38.280 --> 0:27:40.440
<v Speaker 1>going to push back against it because I don't think

0:27:40.600 --> 0:27:43.560
<v Speaker 1>ultimately I think they want this to be UM somewhat

0:27:43.600 --> 0:27:47.520
<v Speaker 1>confusing because it's very difficult to differentiate um if you

0:27:47.600 --> 0:27:50.280
<v Speaker 1>make a lot of information available to investors. But I

0:27:50.320 --> 0:27:51.960
<v Speaker 1>think we have to insist on it, and we have

0:27:52.080 --> 0:27:54.439
<v Speaker 1>to give investors that tool so they can they can

0:27:54.480 --> 0:27:58.040
<v Speaker 1>discriminate among the products. Spoken like a true Bloomberg Gadfly

0:27:58.119 --> 0:28:03.399
<v Speaker 1>columnist Tom, we set out to explore the mystery of

0:28:03.440 --> 0:28:07.000
<v Speaker 1>smart beta. Have we explored it? I think it's going

0:28:07.040 --> 0:28:10.080
<v Speaker 1>to be an ongoing debate, not just you know, beyond

0:28:10.160 --> 0:28:11.800
<v Speaker 1>this room, but it's going to be something that's going

0:28:11.840 --> 0:28:14.560
<v Speaker 1>to keep evolving in the ETF industry because the lines

0:28:14.600 --> 0:28:17.399
<v Speaker 1>are getting very, very blurry. Even the new players atting

0:28:17.440 --> 0:28:19.679
<v Speaker 1>in into the market, their traditional active shops that are

0:28:19.680 --> 0:28:23.120
<v Speaker 1>now launching ETFs. Now there's actively managed ETFs. The lines

0:28:23.160 --> 0:28:25.920
<v Speaker 1>getting very blurry. Well, you just heard a lot of

0:28:25.960 --> 0:28:28.960
<v Speaker 1>different takes on it, and it really depends on where

0:28:29.080 --> 0:28:31.439
<v Speaker 1>you're coming from. And you may find smart beta as

0:28:31.480 --> 0:28:34.199
<v Speaker 1>a solution to a boring core passive portfolio. You want

0:28:34.200 --> 0:28:36.720
<v Speaker 1>a little spice in your life, or you may have

0:28:36.840 --> 0:28:39.880
<v Speaker 1>too much spice and paying too much for the active managers.

0:28:39.880 --> 0:28:42.160
<v Speaker 1>So you think underperforming the mutual fund structure, and you

0:28:42.240 --> 0:28:45.000
<v Speaker 1>want to basically lower your fees and make it a

0:28:45.160 --> 0:28:48.720
<v Speaker 1>more clean, um cheaper version of what you were getting before.

0:28:48.800 --> 0:28:51.800
<v Speaker 1>So there's a lot of angles to this. Yeah, I

0:28:51.920 --> 0:28:54.840
<v Speaker 1>like the hot sauce. Hot sauce. Hot sauce is better

0:28:54.920 --> 0:28:59.360
<v Speaker 1>than the elephant. Alright near case are Tom Saraphagus. Thank

0:28:59.400 --> 0:29:01.640
<v Speaker 1>you so much for us for Trillians, Thanks, thanks for

0:29:01.680 --> 0:29:08.520
<v Speaker 1>having me, Thanks for listening to Trillions until next time.

0:29:08.640 --> 0:29:11.440
<v Speaker 1>You can find us on the Bloomberg terminal, Bloomberg dot com,

0:29:12.000 --> 0:29:15.880
<v Speaker 1>Apple podcasts, and whether else you listen to podcasts. We'd

0:29:15.880 --> 0:29:18.720
<v Speaker 1>love to hear from you. We're on Twitter, I'm at

0:29:18.880 --> 0:29:22.959
<v Speaker 1>Joel Weber Show. He's at Eric fall Tunas. You can

0:29:23.000 --> 0:29:26.560
<v Speaker 1>find near at near Casar and good luck spot on

0:29:26.600 --> 0:29:30.960
<v Speaker 1>this one, but Tom's at at T Sarah Vegas. Trillions

0:29:31.160 --> 0:29:34.600
<v Speaker 1>is produced by Magnus Hendrickson. Francesca Leedy is the head

0:29:34.600 --> 0:29:36.280
<v Speaker 1>of Bloomberg podcast Bye.