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Speaker 1: Wokeroom trillions. I'm Joel Webber and I'm Eric Belchernes Eric.

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Speaker 1: Last year at this time we did a March Madness

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Speaker 1: inspired episode maybe my favorite of the year of all

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Speaker 1: the episodes of what we did, and this year we

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Speaker 1: wanted to one of it. Yeah, this is the episode

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Speaker 1: where we bring in as many people as possible, just

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Speaker 1: a total pile on. And this time we thought of

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Speaker 1: an idea. You know, we're fans of the show Shark Tank,

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Speaker 1: and we thought of an idea of how about we

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Speaker 1: get a bunch of people to pitch their idea for

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Speaker 1: a new ETF. Right, I've got a great idea. Yeah,

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Speaker 1: I know you actually, you're you actually pitched. Here's the

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Speaker 1: bloomberg innecks is so yours is legit um. And the

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Speaker 1: reason I thought this was good this year is because

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Speaker 1: this year is the first year ever we're closures are

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Speaker 1: outnumbering new launches and ETFs um. The industry is getting

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Speaker 1: harder and harder. I think the fee war the downmarket

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Speaker 1: last year has created even more hesitancy to launch new products.

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Speaker 1: And I was speaking with Mike Venuto at tie To

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Speaker 1: et F Services, which helps launch new ETF He said

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Speaker 1: only about one per cent of e t f s pitched,

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Speaker 1: you know, in the world, get greenlit and make it

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Speaker 1: to market, So the bar is pretty high. And the

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Speaker 1: other thing is when you look at how much it

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Speaker 1: costs to launch an e t F, it's about fifty

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Speaker 1: then it cost two to support it. So with all

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Speaker 1: that and the difficulty of getting new assets and well

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Speaker 1: we've talked about that a lot um, the pitch is important.

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Speaker 1: So we thought this would be a fun way to

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Speaker 1: explore maybe how pitch has happened and to help us

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Speaker 1: judge these pitches. We brought back last year's judge, David Papadopoulos,

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Speaker 1: who's a senior editor with Bloomberg News. And David isn't

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Speaker 1: going to play the issuer per se. He's gonna play

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Speaker 1: the seed capital investor. Because Mike Venuta was also saying

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Speaker 1: that if you come with prepared seed capital, you have

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Speaker 1: way more likely to get greenlit than how much he's

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Speaker 1: gonna have a hundred million dollars to distribute. That's a

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Speaker 1: pretty good race. Yeah, going from an editor at Bloomberg

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Speaker 1: News to like seed investor, a senior Okay, all right,

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Speaker 1: so he's going to basically hear a bunch of pitches

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Speaker 1: from people in Bloomberg Intelligence who work with you and

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Speaker 1: also within Bloomberg News, and we're gonna hear a bunch

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Speaker 1: of ideas. Everybody's got one. You've got basically one minute

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Speaker 1: minute to make your pitch, and Mr Papadopolis is going

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Speaker 1: to judge us all on our ideas and then pick

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Speaker 1: a winner and some runners up. I was thinking he'd

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Speaker 1: do fifty million to the top prize, thirty million to

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Speaker 1: number two, and then twenty million to number three. Okay,

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Speaker 1: So Mr Papadopoulos, what are you gonna be looking for

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Speaker 1: as we make our pitches? So I'm looking for a

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Speaker 1: few things here. Um one is at some ovel course,

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Speaker 1: there's gotta be a certain wow factor, right like you've

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Speaker 1: got to You've got to you've got to get get

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Speaker 1: my attention. This might seem slightly contradictory. At the same time,

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Speaker 1: I don't want a whole lot of b s. I

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Speaker 1: don't want a lot of I don't want gimmicks. They

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Speaker 1: have to be you know, um, smart themes, you know,

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Speaker 1: with good fundamentals and things I can believe in. And

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Speaker 1: it's also important for me that they're not overly complex

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Speaker 1: or complicated I'm ultimately not sophisticated enough here to get

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Speaker 1: the hocus focus. So that's that's kind of where I'm

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Speaker 1: coming from, right, Okay, I'll take it. So, joining us

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Speaker 1: from Bloomberg News Carolina Wilson, Sarah Ponzac, Any Massa, Ben Stepman,

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Speaker 1: Rachel Evans, and Suzanne Woolley. Eric. On the b I side,

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Speaker 1: we have James Seffert, myself, Tom Sarah Fagus, and Morgan Barna,

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Speaker 1: who is our newest member and she's coming into us

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Speaker 1: from d C. And I'm joining also from episode did

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Speaker 1: week on Trilliant et F Tank. Alright, first up, Carolina Wilson,

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Speaker 1: you were the first one to walk in the door.

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Speaker 1: Let's hear your pitch, Papa Abels, let me introduce you

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Speaker 1: to my taker FRAT, which is my college focus Consumer

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Speaker 1: e t F. The latest string of e t F

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Speaker 1: s that have actually found success and growth in today's

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Speaker 1: et F market are thematic funds that can subbend for

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Speaker 1: some type of sector exposure. In this case, it would

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Speaker 1: be something like consumer Discretionary. FRAT is a win win

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Speaker 1: for issuers and money managers trying to carouse the next

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Speaker 1: generation of money. Why not give them a theme that

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Speaker 1: they're all too familiar with holding products that have governed

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Speaker 1: their day to day lives. But in a measure diversified way,

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Speaker 1: FRAT has four equally weighted sector bands and one shorting

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Speaker 1: component that makes up fifteen percent of the portfolio. The

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Speaker 1: four sector bands will market cap weight their constituents, which

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Speaker 1: include one cannabis companies to food and drink think Chipotle, Anahizer, Bush,

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Speaker 1: Monster Energy, three technology entertainment thinks Spotify, Facebook, Netflix, gaming

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Speaker 1: stocks and for retail, which I have dominated by none

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Speaker 1: other than Amazon. And that fifteen percent shorting component I

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Speaker 1: mentioned FRAT will short navy At the student loan company.

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Speaker 1: But oh, I like that. Not only are you getting

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Speaker 1: a boost from marijuana focus names, but you're also neatly

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Speaker 1: exposed to them. Market's favorite fang coort And my favorite

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Speaker 1: part of it all, there's a ten percent that has

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Speaker 1: not been accounted for, and that's because FRAT has a

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Speaker 1: temper cent allocation to cash, which is saving up for

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Speaker 1: when uber I p o s. So I'm long dope

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Speaker 1: and this thing, and I'm sure student's interesting. Now there's

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Speaker 1: some appeal to this. I I do see the value

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Speaker 1: of this, But who do you anticipate. Who are your

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Speaker 1: natural buyers of this at so not likely not college

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Speaker 1: students because they're broke and they have money. But people

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Speaker 1: that believe in the college consumer. And the amount of

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Speaker 1: stuff that these people are consuming. Why should I believe

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Speaker 1: in the college consumer? Do they take a growth prospect?

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Speaker 1: Bro like these are twenty two year old consumers, but

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Speaker 1: but for down the road. But they have no money

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Speaker 1: now growth potential, and they do spend like money that

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Speaker 1: they don't have, right, which is why I also we

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Speaker 1: have this students. That is true, that's fact checked. Example,

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Speaker 1: back test shows that Fred over the past five years

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Speaker 1: has returned more than over what period of time five years.

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Speaker 1: Of course, past performance is no guarantee of ure. Next up, Sarah. Now,

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Speaker 1: Sarah has taken this really seriously. I think she may

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Speaker 1: have slept in this room overnight to get ready for it,

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Speaker 1: all right, and she's been like talking trash to me

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Speaker 1: all week about okay, alright, well, let's let's end it

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Speaker 1: all right, all right, It seems everyone is always talking

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Speaker 1: about millennials nowadays, but what about Generation Z? This year?

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Speaker 1: Gen Z is expected to surpass millennials as the most

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Speaker 1: populous generation. As some agents of their mid twenties. So

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Speaker 1: to gouge future spending patterns, you have to get into

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Speaker 1: the psyche of this new largest demographic. Gen Z cares

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Speaker 1: about who is who, who is doing what. They grew

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Speaker 1: up on social media platforms like Instagram and Snapchat, and

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Speaker 1: the influencer culture is real. Take Kylie Jenner for instance,

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Speaker 1: she promoted her makeup line on Instagram and is now

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Speaker 1: the youngest self made billionaire. Influencers are powerful. The influencer

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Speaker 1: economy et F ticker who Who is a new exchange

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Speaker 1: traded fund that holds companies that partner with the top

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Speaker 1: twenty influencers from athletes to actors, public figures, and more.

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Speaker 1: Stocks will be weighted based on their associated influencers rank.

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Speaker 1: And this is the global diversified fund. Take Christian Christiano

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Speaker 1: Ronalda right now, he's the number one top influencer Electronic arts, Nike,

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Speaker 1: Abbott Labs, all companies he partners with, Selena Comes, she

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Speaker 1: partners with Adidas and Coca Cola, Arianna Grande, the Rock

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Speaker 1: under Armor. You get the idea. So who who not

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Speaker 1: the band? No? Not the band? Um alright, so give

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Speaker 1: me a sense of some more of the products here

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Speaker 1: We're we're some more of the companies we're talking about here,

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Speaker 1: so some other companies. Beyonce is the top six influencer

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Speaker 1: right now. She partners with PepsiCo. You also have Kylie

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Speaker 1: Jenner of course with makeup at Alta ut Taylor Swift Ups,

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Speaker 1: Target A, T and T, Comcast, So you really get

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Speaker 1: this mix of different sectors. So right now it's holding

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Speaker 1: consumer discretionary companies, consumer staple companies, telecom, healthcare. So that way,

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Speaker 1: when you have a downturn like we did at the

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Speaker 1: end of last year, who actually fell less than the

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Speaker 1: broader market? And there are there what do we know

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Speaker 1: out there in terms of e t F already that

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Speaker 1: that approach gen Z? There are not any This would

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Speaker 1: be the first e t F at this who my

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Speaker 1: e t F would be the first one that actually

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Speaker 1: acknowledges gen Z. So who is Sarah? That's who first

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Speaker 1: of its kinds um all right, I mean I'm hearing

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Speaker 1: a lot of more gen Z talk, including in our

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Speaker 1: own newsroom, which is probably a contrarian indicator. All right.

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Speaker 1: Next up, we have Joel Weber. Okay, as you guys

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Speaker 1: might know, Bloomberg Intelligence tracks more thies in industries from energy,

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Speaker 1: to technology, to retail, to finance. Once a year, Bloomberg

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Speaker 1: business Week, the magazine that I edit, partners with b

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Speaker 1: I Bloomberg Intelligence to do something called fifty Companies to Watch.

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Speaker 1: Not all of those are winners. We call it watch.

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Speaker 1: Some might be up, some you might be down. Thirty

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Speaker 1: of those are US listed. So the goal of this

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Speaker 1: exercise is to identify companies that will face an unusual

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Speaker 1: challenge in the coming year or opposed to release blockbuster

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Speaker 1: products or services. The analysts considers stuff like revenue growth, margins,

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Speaker 1: market share, debt, and even other factors like economic conditions.

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Speaker 1: I got reader fanmail on this one. When we did

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Speaker 1: this just a couple of weeks ago, portfolio manager emailed

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Speaker 1: me to say, I don't know what your crystal ball is.

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Speaker 1: Forty of those companies our way up. So here's here's

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Speaker 1: my idea. We're gonna rebalance this thing quarterly. We're gonna

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Speaker 1: be long, forty short ten. Here's the ticker fitty fitty Wait,

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Speaker 1: how many letters f I D Y f I T

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Speaker 1: Y which is currently held by a Fidelity fund. But

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Speaker 1: we'll take it's it's up there, forty long ten short, um, Like,

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Speaker 1: who who would be in this long list right now,

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Speaker 1: and who would be sure? It's a great question, right

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Speaker 1: because I think the part of this is US versus international,

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Speaker 1: So you're gonna have this. It's gonna be very global.

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Speaker 1: But the stuff that you'd be long on right now

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Speaker 1: would be like Fast Retailing would be one based on

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Speaker 1: the research that we did. That's a company that we

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Speaker 1: think has great international growth. But you'd be short something

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Speaker 1: probably like Ford or uh, General Motors. I'm afford right, Geer,

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Speaker 1: you should all for it. But basically you'd be rebalancing

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Speaker 1: this so that you'd constantly have tin that you're short

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Speaker 1: forty that you're long. Got it? No hit me? What's

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Speaker 1: the criteria again for this? Beyond you know, your big

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Speaker 1: brain and the big brains of the b I folks.

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Speaker 1: So I think this is a great amplifier because we're

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Speaker 1: going to curate a list that we're confident just like

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Speaker 1: this guy recognized we've been out performing. So we're gonna

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Speaker 1: go along the ones that that we we have great

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Speaker 1: confidence in out performing. And then we're going to amplify

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Speaker 1: it even more by being short ones that we think

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Speaker 1: are going to underperform the market. Okay, Mic drop next up?

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Speaker 1: James sever, an analyst with Bloomberg Intelligence. James go Alright,

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Speaker 1: so my e t F s, I have a pair

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Speaker 1: of ETFs and they're revolving around two. Where is that

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Speaker 1: We hear a lot when you watch any sort of

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Speaker 1: financial news risk on and risk off. So when you

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Speaker 1: see risk on, there are certain e t f s,

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Speaker 1: are certain stocks that you're gonna own, and when you're

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Speaker 1: thinking risk off, there's certain stocks you're gonna go to

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Speaker 1: if you need to maintain equity exposure. So this combines

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Speaker 1: multiple factors and sectors into two et F So the

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Speaker 1: risk on factor E t F is gonna hold growth, momentum, size,

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Speaker 1: and high beta e t f s, And on the

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Speaker 1: sector side right now, it's gonna hold tech, consumer discretionary,

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Speaker 1: and communications. On the risk off side, you're gonna hold

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Speaker 1: low ball quality, dividend, growth and value. And from the

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Speaker 1: sector side, on risk off, you're gonna hold consumer staples

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Speaker 1: and utilities. Now, past past returns is an indicative of

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Speaker 1: future returns, but if you look at the returns over

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Speaker 1: the past five to seven years, you're gonna see the

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Speaker 1: risk on is outperformed by on the risk off. With

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Speaker 1: spy in the middle, there and then if you look

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Speaker 1: over the biggest downturn in December, it worked just as

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Speaker 1: expected with the risk off being down and the risk

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Speaker 1: on being down again with Spy in the middle over

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Speaker 1: that twenty four day period. Um, I am fascinated by this.

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Speaker 1: I think this is pretty cool. At the same time

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Speaker 1: as I said it to be getting I'm not smart

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Speaker 1: enough to understand all the ins and out. So again,

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Speaker 1: so explain to me. So I simultaneously am owning two ets.

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Speaker 1: Is that right where you've broken? Yeah, So you would

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Speaker 1: own if you if you believe there's risk on in

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Speaker 1: the market, or you think that there's gonna be a

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Speaker 1: bull market going forward for the next couple of years,

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Speaker 1: you're going to own the risk on factor e t F.

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Speaker 1: And if you're not, you're going to own the risk off.

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Speaker 1: So if if you're predicting a future downturn, you need

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Speaker 1: to maintain equity exposure. Theoretically people will go to utilities

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Speaker 1: or some lower volatility stocks, and this is just going

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Speaker 1: to group all those low volatility factors or risk off

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Speaker 1: factors together. Well, I think Sarah Pons wants to wants

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Speaker 1: to chime in here. Do I have a question you

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Speaker 1: said in risk on Right now, it's holding momentum. But

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Speaker 1: haven't you yourself done a lot of research lately that

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Speaker 1: momentum is actually risk off right now. Momentum momentum is

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Speaker 1: more highly correlated. Right now. It is a good point,

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Speaker 1: and I was thinking about it. But over the longer periods,

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Speaker 1: this is just an instance that and what's going on

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Speaker 1: with specific rebalance that happened to a certain et F.

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Speaker 1: It's not all. It's not all momentum ETFs. But right

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Speaker 1: now that's just a stint in. What's going over over

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Speaker 1: the long term, momentum is gonna outperform Noble markets. What's

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Speaker 1: the ticker r O n N for risk on and

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Speaker 1: r o f F for risk of roth. But this

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Speaker 1: is like the Yang last year a little bit. Yeah,

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Speaker 1: but I need to decide which of these two I'm

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Speaker 1: moving in and out of. Theoretically, yes, or you could

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Speaker 1: listen to the or you could listen to the talking heads,

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Speaker 1: but you could listen to the talking heads on on

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Speaker 1: Bloomer TV to know which one to put in. But

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Speaker 1: typically when you launch these dual type of partnerships, dual

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Speaker 1: ETFs are more than one et F, they split them

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Speaker 1: evenly and then let the allocators go and they benefit

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Speaker 1: when something is going good in that area. So if

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Speaker 1: much of people a phone, money there. So next up

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Speaker 1: we have from our DC studio is Morgan Barnet, who

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Speaker 1: is a new associate for Bloomberg Intelligence Fund and ETF Research.

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Speaker 1: U Mo're gonna take it away, Okay, I am pitching

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Speaker 1: a largely US based equity theme fund. So the Supreme

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Speaker 1: Court reversed a sports betting ban that I think is

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Speaker 1: going to really open the door for UM companies that

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Speaker 1: do gaming and uh sort of gambling to really capture

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Speaker 1: what was formerly sort of offline betting. So more states

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Speaker 1: are going to fall the first seven and this is

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Speaker 1: about a hundred and fifty billion in off market sports

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Speaker 1: wagering annually. UM. Along with that, there's so much UM

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Speaker 1: content on demand for entertainment, and so I kind of

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Speaker 1: think the stirs a counter current for more live entertainment experiences.

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Speaker 1: So is this a theme fund UM? Well? Equal weight

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Speaker 1: company is UM here that have direct exposure companies like

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Speaker 1: Live Nation, Trip Advisor, Event Bright Madison, Square Garden, And

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Speaker 1: then there's some new listings of pure play E sports companies.

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Speaker 1: I know we've talked about UM gaming, but sports you

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Speaker 1: got to wrap it up. E Sports Companies, Allied Sports,

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Speaker 1: super League Gaming, and Modern Times are all coming online.

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Speaker 1: Got it well? As a lifelong gambler, Yeah, I mean

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Speaker 1: she just like it. I can see his heart trains

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Speaker 1: up when she said gambling. You know, I was just like, whoa,

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Speaker 1: you got me so? All right? So you're both tapping

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Speaker 1: into like the Live Nations and the trip Advisors, right,

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Speaker 1: that could ride this way a bit. But tell me again,

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Speaker 1: the names are the more the companies that are actually

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Speaker 1: more directly involved in the game. Because I also maybe

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Speaker 1: I need to set up some accounts that MGM, Eldorado,

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Speaker 1: and BOYD have all made um decent partnerships and acquisitions

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Speaker 1: in the space god and what's the ticker E L

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Speaker 1: I V Entertainment Live L Live. I think he likes

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Speaker 1: the gambling part more more than the entertainment party. You

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Speaker 1: don't get out much, do you know. I'm too busy gambler.

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Speaker 1: Thank you Morgan? All right, I think Eric, I think

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Speaker 1: it's your turn. Okay, what's the one thing we all hate? Okay,

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Speaker 1: don't answer that, but I know one thing we all hate, um,

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Speaker 1: and that is Monday's And guess who else hates Monday's

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Speaker 1: the market. If you look at the days of the week,

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Speaker 1: Monday is the only day since where the market is

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Speaker 1: down on average. Every other day it's positive. So this

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Speaker 1: is a very simple idea. It's called x mon the

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Speaker 1: calendar shares S and P five x Monday's e t F.

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Speaker 1: All it does is hold I V V right, it's

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Speaker 1: gonna buy it at Friday close because between the clothes

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Speaker 1: and the open you can pick up a few basis

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Speaker 1: points too. That's a good time to hold it, and

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Speaker 1: then it will um. So it'll sell it on Friday

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Speaker 1: and buy it on Tuesday. Monday the clothes and so

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Speaker 1: essentially you're going to get the market return minus Monday. Now,

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Speaker 1: there's a lot of theories on why Mondays are bad.

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Speaker 1: Companies report bad news on Friday's a lot of times

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Speaker 1: people get paranoid over the weekend. Right, the idle hands

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Speaker 1: are the devil's playthings. So people come in and selling

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Speaker 1: and guess what you would avoid catastrophe? What are the

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Speaker 1: worst market crashes known as Black Monday and Black Monday too,

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Speaker 1: which is August. You would have avoided those two. So

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Speaker 1: I'm selling Friday and I'm buying it Monday. What about

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Speaker 1: trading costs, comes a voice from the crowd. Yeah, sure,

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Speaker 1: so i VV trades at a point oh one percent spread,

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Speaker 1: so you would incur those but you're hoping to pick

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Speaker 1: up more than those trading costs over the long term.

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Speaker 1: So i VV I picked on purpose because it has

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Speaker 1: a real low expense ratio, but it's more liquid than VOO,

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Speaker 1: So to me, it's the perfect et F to use

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Speaker 1: for the strategy. All Right, I'm a little I'm just

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Speaker 1: a little surprised if I can chime in. Like all

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Speaker 1: the e t f s that Eric could come up

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Speaker 1: with with, this one feels a little lazy, lazy. Well,

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Speaker 1: my other idea was a little I don't know uma

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Speaker 1: of the time, we don't have more ideas well know

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Speaker 1: the reason ever, though it's hey, hold on a second,

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Speaker 1: I um, I think it's kind of cool. I got

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Speaker 1: two questions. So are we sure that it's not gimmicky? Though? Right? Like,

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Speaker 1: this isn't just some odd statistic laboration. This is like legit.

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Speaker 1: I mean, there's really something there. There are fundamental factors

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Speaker 1: for Monday always sucking. Yeah, Like I said, there's the

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Speaker 1: human behavioral people come in Monday they're cranky A lot

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Speaker 1: of times. If something bad happens on a Friday, it

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Speaker 1: gets worse on Monday because people have all weekend and

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Speaker 1: they don't think, oh, I'll be okay. Their brains go

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Speaker 1: to the negative there, like I better sell out? Are

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Speaker 1: you a shrink? Uh No, but I'm to psychology class.

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Speaker 1: You know you're psychoanalyzing the market. Well, behavior is a

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Speaker 1: big deal. That's why factors work. To me, this is

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Speaker 1: somewhat of a factor kind of play. My last question

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Speaker 1: for you is, like wise, guys like you who come

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Speaker 1: in and say, oh, I'm gonna short Monday, I mean,

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Speaker 1: is it possible that as you bring attention to this,

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Speaker 1: your e t F takes off that you're gonna wind

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Speaker 1: up are being out? You know the down mondays. If

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Speaker 1: this et F gets that big, you and I will

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Speaker 1: both be filthy rich by the time. So but yeah, ultimately,

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Speaker 1: if if everybody starts buying this, then yeah, there could

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Speaker 1: be an our super duper last question for you. So, like,

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Speaker 1: give me a rough sense of like what a typical

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Speaker 1: Monday return looks like these over the over a certain

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Speaker 1: period of time versus Tuesday, Wednesday, Thursday, Friday on average,

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Speaker 1: Mondays are down eight basis points on average since on Tuesday.

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Speaker 1: It's up five BIPs, Wednesday eight pips. Wednesday's actually the

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Speaker 1: best performing day for whatever reason, and Thursday four BIPs

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Speaker 1: for day five. So it's really like a seven almost

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Speaker 1: a ten basis point swing between Monday and any other day. Okay,

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Speaker 1: and you had ten basis points up, you know, over

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Speaker 1: weeks after weeks, after weeks, that's going to add up

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Speaker 1: to some alpha. Next up, Ben Steve Berman, who's on

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Speaker 1: the Wealth team at Bloomberg News, been the reigning champion

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Speaker 1: from last year. What was your idea with with last

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Speaker 1: year's March Madness winner. I was going for empty, which

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Speaker 1: is the retail et fright, and how was that done?

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Speaker 1: After I I have not checked. Give me four seconds here.

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Speaker 1: I did warn you that it wasn't gonna do well,

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Speaker 1: uh negative two. But we're waiting. We're still waiting for

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Speaker 1: the big home run, right, the big grand for me.

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Speaker 1: On the personal finance guy, I think long term, not

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Speaker 1: like the no this is I think in decades, not days,

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Speaker 1: and I won't be but alright, so as I said,

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Speaker 1: I'm I'm a personal finance guy. I think long term.

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Speaker 1: I was thinking about long term trends. How do how

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Speaker 1: do we invest in some of the big global long

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Speaker 1: term trends climate change? Okay, you can do that. There's

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Speaker 1: ways to do that. UM urbanization. You look at rural

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Speaker 1: areas all around the world, including the United States. They're shrinking,

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Speaker 1: populations going down. The economy of rural areas is shrinking.

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Speaker 1: Cities are booming, especially in Africa and especially in Asia,

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Speaker 1: but also the United States. UM, big cities are doing

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Speaker 1: really well, and outside metro prolitan areas, it's hard to

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Speaker 1: get a job. So it's thinking about UM. A urban

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Speaker 1: basically an urban ETF. So it's a it's it invests

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Speaker 1: in a whole range of sectors. So it could be finance, reets, uh, industrial, cranes, elevators, retail.

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Speaker 1: It goes after retail stores and retail companies that really

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Speaker 1: go after that urban consumer. The ticker is well, okay,

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Speaker 1: this the ticker could be city that's available, could be well,

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Speaker 1: I have a better one. You tell me why you

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Speaker 1: p p yuppy, Why we are gentrifying et F investing.

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Speaker 1: We're gentrifying EFF investing. As if et F investing needed gentrifying. UM,

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Speaker 1: give me some name, all right, so you said finance,

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Speaker 1: you said reach, you said cranes, Like, so what am I?

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Speaker 1: The man to walk would be the crane idea lift

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Speaker 1: I p O s. You would want that. So you

402
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Speaker 1: want some transportation in there. But the key is you

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Speaker 1: want something that's really focused on urban consumers all around

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Speaker 1: the world, not um not rural consumers. So like Amazon,

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Speaker 1: I think you would want to leave that out because

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Speaker 1: it's more of a broader play. It's got to be

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Speaker 1: really locked in on city super long, city super short essentially,

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Speaker 1: or just everything else is out, not shut, but everything

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Speaker 1: else is out, and you are changing this the makeup

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Speaker 1: of this fun Oh that's the other thing. We're like, Hi,

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Speaker 1: we gotta get a good team of like millennials sort

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Speaker 1: of taking artisanal approach to the index constructuring of this.

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Speaker 1: This really is pretty yuppy artisanal shares. Took me a

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Speaker 1: long time to come up with this guy approach. Just

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Speaker 1: stock selection, Okay, alright, yuppy yuppy with our tiginal rebalancing

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Speaker 1: is exactly okay, thank you bad, very good. Alright. Next

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Speaker 1: up Rachel Evans of Bloombrick News, a frequent guest on

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Speaker 1: Trillions No Pressure. Three do one make way for the

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Speaker 1: future trading under the ticket s h t K. The

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Speaker 1: stick of this fund is to invest in the megacaps

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Speaker 1: of the future. The fund or track and index of

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Speaker 1: the five most recently listed US companies, which it will equate,

423
00:25:12,240 --> 00:25:16,360
Speaker 1: rebalancing quarterly to limit trading costs. This thematic fund will

424
00:25:16,440 --> 00:25:19,840
Speaker 1: charge forty basis points, undercutting the average thematic a t

425
00:25:19,960 --> 00:25:23,159
Speaker 1: F by more than ten basis points. Uh. And we'll

426
00:25:23,200 --> 00:25:25,960
Speaker 1: look to beat the i PO focused funds that are

427
00:25:26,000 --> 00:25:30,000
Speaker 1: out there, which are currently charging about sixty basis points

428
00:25:30,119 --> 00:25:33,639
Speaker 1: twenty basis points more than this fund. M H. I

429
00:25:33,680 --> 00:25:35,280
Speaker 1: think I don't even need the time. Yeah, I was

430
00:25:35,280 --> 00:25:36,840
Speaker 1: going to say it. I was like making the first

431
00:25:36,840 --> 00:25:40,600
Speaker 1: one that's coming under. Yeah again, points for that, I feel. Yeah,

432
00:25:41,320 --> 00:25:46,439
Speaker 1: I see that. So you are every newly issued stack

433
00:25:47,480 --> 00:25:50,480
Speaker 1: you guys buy that's issued in the US, it is

434
00:25:50,480 --> 00:25:54,360
Speaker 1: issued in the United States of America. Now I see

435
00:25:54,359 --> 00:25:56,560
Speaker 1: the appeal to it. But I guess I just wonder,

436
00:25:56,600 --> 00:25:59,440
Speaker 1: so we're really nearly scooping it all up, and how

437
00:25:59,480 --> 00:26:01,920
Speaker 1: often do we then do we rotate these out so

438
00:26:02,040 --> 00:26:04,119
Speaker 1: once a quarter so, because you want to limit the

439
00:26:04,119 --> 00:26:06,680
Speaker 1: trading cost of kind of trading too frequently and quarterly

440
00:26:06,720 --> 00:26:09,359
Speaker 1: rebalancings relatively common. So that's when you kind of like

441
00:26:09,400 --> 00:26:12,240
Speaker 1: turn over the portfolio. I reckon, you've probably replaced the

442
00:26:12,280 --> 00:26:14,560
Speaker 1: stocks maybe every two years, would kind of like the

443
00:26:14,600 --> 00:26:17,040
Speaker 1: time you'd get a whole new portfolio. You can't see this.

444
00:26:17,040 --> 00:26:19,480
Speaker 1: Brolina is nodding her head and approval behind you. Yes,

445
00:26:19,720 --> 00:26:25,960
Speaker 1: yes she is. She seems to like flavor over there.

446
00:26:26,160 --> 00:26:28,600
Speaker 1: She likes your pitch better than her own, it seems like.

447
00:26:30,880 --> 00:26:32,879
Speaker 1: But I would say as well that like looking at

448
00:26:32,920 --> 00:26:34,960
Speaker 1: kind of like funds that focus on I PO some

449
00:26:35,000 --> 00:26:38,760
Speaker 1: of which are less sophisticated, I would say they've done

450
00:26:38,840 --> 00:26:42,359
Speaker 1: very well, they're up this year, okay, But you're just

451
00:26:42,440 --> 00:26:44,280
Speaker 1: I guess the only thing they considerably, you're just right

452
00:26:44,359 --> 00:26:48,840
Speaker 1: blindly blanket buying them all. They tend to do well initially,

453
00:26:48,880 --> 00:26:52,280
Speaker 1: of course, but like, how much risk do I have?

454
00:26:52,320 --> 00:26:53,760
Speaker 1: Am I going to be? Are we gonna be stumbling

455
00:26:53,800 --> 00:26:56,600
Speaker 1: into some total blow ups? So that is the why

456
00:26:56,640 --> 00:26:58,000
Speaker 1: you have an a t F in the first place.

457
00:26:58,080 --> 00:26:59,840
Speaker 1: Rather than buying these stocks out right, you know, you

458
00:27:00,000 --> 00:27:02,000
Speaker 1: could buy left and then hey, maybe a lift gets

459
00:27:02,000 --> 00:27:04,080
Speaker 1: brought out by another company or goes to hell in

460
00:27:04,119 --> 00:27:06,560
Speaker 1: a handcar. Who knows. But the point of an et

461
00:27:06,680 --> 00:27:09,000
Speaker 1: f A is you have diversified exposure. Yes, it is

462
00:27:09,000 --> 00:27:12,120
Speaker 1: buying everything that lists, but that's how you get diversified exposure.

463
00:27:12,200 --> 00:27:14,119
Speaker 1: You get all of those companies are going to be

464
00:27:14,160 --> 00:27:18,359
Speaker 1: this future five hundred the future. Last question for you

465
00:27:18,400 --> 00:27:20,360
Speaker 1: before I let you go is that, UM, I understand

466
00:27:20,440 --> 00:27:23,159
Speaker 1: that you're buying companies of the future. But as Bloomberg

467
00:27:23,200 --> 00:27:25,840
Speaker 1: News as reporter recently maybe it was parts of yourself,

468
00:27:25,880 --> 00:27:28,879
Speaker 1: has said that companies that are ip owing are typically

469
00:27:28,880 --> 00:27:31,440
Speaker 1: I p owing at a much later age than they

470
00:27:31,560 --> 00:27:35,359
Speaker 1: used to. So am I really getting companies of the

471
00:27:35,400 --> 00:27:38,200
Speaker 1: future or this is still your first chance to buy

472
00:27:38,240 --> 00:27:40,800
Speaker 1: into them as an investor in the public market, So

473
00:27:40,920 --> 00:27:43,760
Speaker 1: better to get in sort of five years into their lifespan.

474
00:27:43,800 --> 00:27:46,160
Speaker 1: Will wait another ten or fifteen, You're still in kind

475
00:27:46,160 --> 00:27:48,639
Speaker 1: of that early arc of growth for these companies. That

476
00:27:48,760 --> 00:27:52,320
Speaker 1: was a good question. I had to come up with one.

477
00:27:53,840 --> 00:27:58,320
Speaker 1: I have a question, which is you're British. Um sadly

478
00:27:58,640 --> 00:28:02,280
Speaker 1: hell in a handcart we say Helena handbag. I've never

479
00:28:02,280 --> 00:28:12,080
Speaker 1: heard Helena. Oh my god, it's an Oregon thing. Okay, sorry,

480
00:28:14,320 --> 00:28:17,439
Speaker 1: Tom Sera, Vegas analysts with Bloomberg Intelligence Tommy, you got

481
00:28:17,440 --> 00:28:21,240
Speaker 1: about one minute, go for it. Okay. So this one

482
00:28:21,600 --> 00:28:24,000
Speaker 1: is the anti factory TF So let me sort of

483
00:28:24,040 --> 00:28:26,280
Speaker 1: set the stage for you. So there has just been

484
00:28:26,400 --> 00:28:30,159
Speaker 1: this big focus on everyone chasing factory t s. When

485
00:28:30,200 --> 00:28:34,040
Speaker 1: I say factor, I mean things like low volatility, momentum, value.

486
00:28:34,400 --> 00:28:36,800
Speaker 1: There is a lot of money sort of chasing these factors.

487
00:28:37,200 --> 00:28:41,440
Speaker 1: This one is basically looking for the island of misfit toys.

488
00:28:41,480 --> 00:28:44,120
Speaker 1: So what this does is actually it looks through the

489
00:28:44,200 --> 00:28:47,000
Speaker 1: really popular factory ts like the value one, the momentum

490
00:28:47,000 --> 00:28:49,600
Speaker 1: one that actually looks at the stocks that are not

491
00:28:49,680 --> 00:28:52,360
Speaker 1: owned by any of them. Right, So it's really a

492
00:28:52,400 --> 00:28:55,239
Speaker 1: contring indicator. And the reason I want to pick this

493
00:28:55,240 --> 00:28:57,360
Speaker 1: one because I think that investors have this sort of

494
00:28:57,360 --> 00:29:00,959
Speaker 1: love affair with contring indicators, are really looking or anything

495
00:29:00,960 --> 00:29:03,720
Speaker 1: to give them any insight into anything cracking in the

496
00:29:03,760 --> 00:29:07,400
Speaker 1: market or sort or any type of insight. So um

497
00:29:08,400 --> 00:29:10,840
Speaker 1: uh f wise, it's only basis points. I think it's

498
00:29:10,880 --> 00:29:14,160
Speaker 1: super competitive for a product like this, and you're probably

499
00:29:14,200 --> 00:29:17,240
Speaker 1: asking yourself like, who are the anti factor names, because

500
00:29:17,240 --> 00:29:19,960
Speaker 1: you're probably thinking these are like garbage stocks and no

501
00:29:20,000 --> 00:29:22,480
Speaker 1: one wants to touch. All Right, I'm wrapping up Greek.

502
00:29:22,720 --> 00:29:27,560
Speaker 1: Let me throw out some names, Facebook, Horizon, Intel, Right,

503
00:29:27,600 --> 00:29:29,680
Speaker 1: so there's nothing wrong with these companies just because they

504
00:29:29,680 --> 00:29:32,400
Speaker 1: don't meet the definition of a factor. Um, they've sort

505
00:29:32,440 --> 00:29:35,120
Speaker 1: of been shunned. So there's obviously very stable companies that

506
00:29:35,240 --> 00:29:40,600
Speaker 1: have disregarding the wrap up and uh um, so I'm

507
00:29:40,720 --> 00:29:42,320
Speaker 1: really looking for a need you have to pick up

508
00:29:42,360 --> 00:29:45,560
Speaker 1: on miss pricings that just because these stocks don't meet

509
00:29:45,600 --> 00:29:50,200
Speaker 1: the traditional factor difference as the ticker is great, I

510
00:29:50,200 --> 00:29:55,680
Speaker 1: think it's reject. I r j KT, reject, reject. Spell

511
00:29:55,720 --> 00:30:00,720
Speaker 1: it again for me. Are j KT alright? And how

512
00:30:00,760 --> 00:30:03,400
Speaker 1: often am I moving in and out of these anti

513
00:30:03,880 --> 00:30:08,160
Speaker 1: factor stocks? How often? Yeah? Good question, You're moving quarterly

514
00:30:08,200 --> 00:30:10,880
Speaker 1: because that coincides with how the other factory tests are

515
00:30:10,880 --> 00:30:14,320
Speaker 1: rebound typically the rebounce recorder. Um. So this one will

516
00:30:14,360 --> 00:30:16,680
Speaker 1: also rebounce a recorder as those ones. A rebound it

517
00:30:16,720 --> 00:30:18,120
Speaker 1: looks for all the names that are not in it,

518
00:30:18,160 --> 00:30:20,040
Speaker 1: and it will pick up the same name. The will

519
00:30:20,160 --> 00:30:22,160
Speaker 1: rebound in the same frequence Greek. Before I let you go,

520
00:30:22,280 --> 00:30:24,840
Speaker 1: I am a contrarian guy by nature, so this does

521
00:30:25,200 --> 00:30:29,040
Speaker 1: appeal to me at some level. But I guess, like,

522
00:30:29,080 --> 00:30:33,200
Speaker 1: how will right? I mean? These things are are our

523
00:30:33,240 --> 00:30:35,920
Speaker 1: anti factor for a reason right there? Out of favor.

524
00:30:36,040 --> 00:30:37,880
Speaker 1: How long do we need to sit on these things

525
00:30:37,920 --> 00:30:42,080
Speaker 1: for before they start you know, paying paying off for us? Yeah,

526
00:30:42,160 --> 00:30:44,400
Speaker 1: good question. And why I think this product has the

527
00:30:44,400 --> 00:30:47,480
Speaker 1: potential be a disruptor. So because let's look at value

528
00:30:47,480 --> 00:30:50,560
Speaker 1: for example, value has been underperforming for ten years. So

529
00:30:50,600 --> 00:30:53,160
Speaker 1: if you actually look at a value index, if you

530
00:30:53,240 --> 00:30:55,760
Speaker 1: take the worst value names, you would have outperformed the

531
00:30:55,800 --> 00:30:59,400
Speaker 1: best value names over the last five years. So why

532
00:30:59,440 --> 00:31:01,920
Speaker 1: I think this is disruptors because if anti factor starts

533
00:31:01,920 --> 00:31:04,760
Speaker 1: to do well, it's sort of underpins everything else. So

534
00:31:04,840 --> 00:31:07,480
Speaker 1: sort of saying, hey, factors aren't working and there's so

535
00:31:07,560 --> 00:31:10,400
Speaker 1: much money chasing these factors. The potential for this to

536
00:31:10,400 --> 00:31:13,200
Speaker 1: be a disruptor I think is huge. So you're essentially

537
00:31:13,280 --> 00:31:16,320
Speaker 1: trying to use their hype against them and exactly, and

538
00:31:16,320 --> 00:31:18,680
Speaker 1: I think as factory investing gets more popular, there's gonna

539
00:31:18,680 --> 00:31:21,560
Speaker 1: be more and more money chasing the same stocks based

540
00:31:21,600 --> 00:31:23,840
Speaker 1: on the same factor. Definitely. For what it's worth about

541
00:31:23,880 --> 00:31:25,720
Speaker 1: Tunis is sort of nodding his head about. Tunis is

542
00:31:25,760 --> 00:31:28,440
Speaker 1: into this one. He wants he doesn't he doesn't have

543
00:31:28,480 --> 00:31:31,760
Speaker 1: the cash I have right now, but he might he mighty.

544
00:31:31,960 --> 00:31:33,960
Speaker 1: It appeals. I'm a contrarian too, so it appeals to

545
00:31:33,960 --> 00:31:36,320
Speaker 1: me on that level, and I'm actually shocked this one

546
00:31:36,400 --> 00:31:39,280
Speaker 1: isn't a product. Well done, Thank you, great, thanks good

547
00:31:45,720 --> 00:31:49,280
Speaker 1: all right. Next up Annie massa reporter with bloom Brick News. Annie,

548
00:31:49,400 --> 00:31:52,880
Speaker 1: three to one. Okay, allow me to propose to you

549
00:31:53,480 --> 00:31:56,880
Speaker 1: the wedding e t F turning under the ticker I

550
00:31:57,000 --> 00:31:59,920
Speaker 1: d O this E t F track to be spoken

551
00:32:00,040 --> 00:32:03,160
Speaker 1: decks of companies uniquely positioned to profit off of the

552
00:32:03,240 --> 00:32:07,400
Speaker 1: seventy two billion dollar US wedding industry now that includes

553
00:32:07,480 --> 00:32:11,480
Speaker 1: jewelers Tiffany and co Ca Jewelers, Registry, go to like

554
00:32:11,560 --> 00:32:16,200
Speaker 1: bed Bath and Beyond, formal wear retailers like Nordstrom, beverage

555
00:32:16,200 --> 00:32:20,600
Speaker 1: companies Anhezzard Bush, and tech companies like Amazon, stunt i,

556
00:32:20,680 --> 00:32:24,720
Speaker 1: po Pinterest a popular one with brides and even um

557
00:32:25,000 --> 00:32:28,400
Speaker 1: drone part makers because drones are the future of wedding

558
00:32:28,440 --> 00:32:32,760
Speaker 1: photography got to capture those aerial shots. Couples spent an

559
00:32:32,760 --> 00:32:35,920
Speaker 1: average of forty four thousand dollars a year that's up

560
00:32:35,960 --> 00:32:39,560
Speaker 1: more than sixty um a year over year on their

561
00:32:39,600 --> 00:32:43,160
Speaker 1: weddings in the US, and this a t F gives

562
00:32:43,160 --> 00:32:47,040
Speaker 1: you an exposure to a wide array of industries, um,

563
00:32:47,080 --> 00:32:50,840
Speaker 1: giving it a real, I think, special flavor. As anyone

564
00:32:50,880 --> 00:32:56,360
Speaker 1: who knows sound okay, just last last note, as anybody

565
00:32:56,360 --> 00:32:58,680
Speaker 1: who's ever been in a long term relationship knows past

566
00:32:58,720 --> 00:33:05,400
Speaker 1: results are non indicative. Future excellent. All Right, it's a

567
00:33:05,400 --> 00:33:07,560
Speaker 1: pretty good it's a pretty good ticker, and I like

568
00:33:09,280 --> 00:33:11,720
Speaker 1: it's I like how approachable it is. But let me

569
00:33:11,720 --> 00:33:16,400
Speaker 1: ask you a couple of questions. Here. Seventy billion dollar industry. Uh,

570
00:33:16,400 --> 00:33:18,880
Speaker 1: and these folks spend forty four thousand on average in

571
00:33:18,880 --> 00:33:22,440
Speaker 1: their weddings up six But is this really a growth

572
00:33:22,600 --> 00:33:26,280
Speaker 1: industry though? Like am I I mean absolutely? I mean

573
00:33:26,320 --> 00:33:28,280
Speaker 1: I thought I thought I thought marriage was kind of

574
00:33:28,400 --> 00:33:31,480
Speaker 1: I mean, you could short this whole thing. You can, Yeah,

575
00:33:31,480 --> 00:33:34,520
Speaker 1: you can also go short if you're better. But but

576
00:33:35,000 --> 00:33:37,480
Speaker 1: the other piece of it is millennials are increasingly getting

577
00:33:37,520 --> 00:33:39,960
Speaker 1: their parents to pay for their weddings, meaning that the

578
00:33:39,640 --> 00:33:42,760
Speaker 1: cost of weddings, wedding spending is actually going on. In

579
00:33:42,800 --> 00:33:46,720
Speaker 1: a minute, yeah, I'm gonna be paying for my sorry

580
00:33:46,720 --> 00:33:50,280
Speaker 1: to tell you, okay, So I all right, so this

581
00:33:50,360 --> 00:33:53,520
Speaker 1: is growth. This is I'm gonna be buy growth, And

582
00:33:53,560 --> 00:33:56,920
Speaker 1: it's I'm not sure I buy that. I mean Tiffany, Yeah,

583
00:33:57,000 --> 00:34:08,480
Speaker 1: Tiffany for a wedding registrates there for the right. So

584
00:34:08,520 --> 00:34:11,200
Speaker 1: this is my other question, So is it you're kind

585
00:34:11,200 --> 00:34:13,440
Speaker 1: of all You're slightly all over the place in terms

586
00:34:13,440 --> 00:34:15,920
Speaker 1: of what you're wedging in here. I mean like Amazon

587
00:34:16,120 --> 00:34:18,960
Speaker 1: for weddings, but in that sense like Amazon could be

588
00:34:19,000 --> 00:34:21,719
Speaker 1: for I get it, but he could be at that

589
00:34:21,719 --> 00:34:25,640
Speaker 1: point Amazon, you then could almost apply to anything. Um,

590
00:34:26,840 --> 00:34:30,160
Speaker 1: I do like there are elements here already using the ticker,

591
00:34:30,920 --> 00:34:37,160
Speaker 1: I feel like catching on. The next is up six

592
00:34:37,719 --> 00:34:42,799
Speaker 1: from when from the year before from Okay, this is

593
00:34:42,800 --> 00:34:51,200
Speaker 1: according to Bride's magazine. One of the odds right now,

594
00:34:51,320 --> 00:34:54,000
Speaker 1: one are the odds that spending on weddings went up

595
00:34:54,040 --> 00:34:56,719
Speaker 1: six one year. I think the odds of that are

596
00:34:56,760 --> 00:35:04,160
Speaker 1: something like zero. Right, But Brides, it isn't a second,

597
00:35:04,800 --> 00:35:08,560
Speaker 1: There isn't the father's footing. The bill is a good

598
00:35:08,560 --> 00:35:09,920
Speaker 1: market because that you could look at it as a

599
00:35:09,960 --> 00:35:13,480
Speaker 1: hedge on your wedding, that you're paying for it kind of,

600
00:35:13,560 --> 00:35:16,040
Speaker 1: it's a way to hedge out the costs. That's that's

601
00:35:16,040 --> 00:35:24,440
Speaker 1: a clever, that's smart. Next up, Susanne Woolle. Susanne had

602
00:35:24,640 --> 00:35:27,799
Speaker 1: a premature exit from the tournament last year with she

603
00:35:27,840 --> 00:35:30,440
Speaker 1: picked a great one move but kind of got bounced.

604
00:35:30,800 --> 00:35:33,839
Speaker 1: My colleague Ben Steverman just knocked me out of the park.

605
00:35:34,480 --> 00:35:37,000
Speaker 1: It was sad. Yeah, he was pretty brutal. I gotta

606
00:35:37,000 --> 00:35:40,440
Speaker 1: admit but it marked. But now is your chance at redemption? Yeah? Alright,

607
00:35:40,440 --> 00:35:42,759
Speaker 1: so so you're ready for shark tank. I am. Okay,

608
00:35:42,800 --> 00:35:44,839
Speaker 1: here we go. Make your pitch. This ETF is nothing

609
00:35:44,840 --> 00:35:48,360
Speaker 1: about redemption. My chip pitch is for Evil ticker symbol

610
00:35:48,480 --> 00:35:52,080
Speaker 1: e v I L. Unsurprisingly, the ticker symbol is available.

611
00:35:53,040 --> 00:35:56,040
Speaker 1: Evil will invest in anything that plays to people's baser

612
00:35:56,120 --> 00:35:59,080
Speaker 1: instincts or as harmful to society in some way. That

613
00:35:59,160 --> 00:36:01,840
Speaker 1: means a good invest Companies that profit from selling unhealthy

614
00:36:01,840 --> 00:36:05,360
Speaker 1: snack foods, that are big polluters, that promote vaping, anything

615
00:36:05,400 --> 00:36:09,440
Speaker 1: that definitely is not good. Lots of people you know

616
00:36:09,560 --> 00:36:13,279
Speaker 1: indirectly benefit from, you know, vir publicly traded companies from

617
00:36:13,280 --> 00:36:15,239
Speaker 1: things that aren't very good and don't realize it. And

618
00:36:15,280 --> 00:36:19,279
Speaker 1: this just allows them to invest in more honest, targeted way.

619
00:36:19,400 --> 00:36:21,640
Speaker 1: It will also be a sort of like a litmus test.

620
00:36:22,120 --> 00:36:24,560
Speaker 1: If it fails, it doesn't attract assets, it doesn't do

621
00:36:24,600 --> 00:36:28,120
Speaker 1: well then like great, that says good things society. What

622
00:36:28,239 --> 00:36:31,799
Speaker 1: about my money? If it does well, it says like

623
00:36:31,800 --> 00:36:34,799
Speaker 1: we're all going to hell in a handbasket. But again

624
00:36:36,040 --> 00:36:39,440
Speaker 1: catching up on the bright side, it will be a

625
00:36:39,440 --> 00:36:42,080
Speaker 1: really a mark of dishonor to be part of this

626
00:36:42,160 --> 00:36:45,560
Speaker 1: et f so that may sort of incurage good behavior. Um,

627
00:36:45,600 --> 00:36:50,560
Speaker 1: that is the sound of us exiting. Can I just

628
00:36:50,640 --> 00:36:53,480
Speaker 1: mention that it's Um, it's expense ratio is going to

629
00:36:53,480 --> 00:36:57,359
Speaker 1: be point six six six. I'm not going to help

630
00:36:57,360 --> 00:36:59,480
Speaker 1: it with. I don't think it will make more money,

631
00:36:59,640 --> 00:37:03,839
Speaker 1: but it's very meta, you know. Um. Anyway, you can

632
00:37:03,880 --> 00:37:05,759
Speaker 1: also use two to three times leverage to make it

633
00:37:05,800 --> 00:37:10,400
Speaker 1: really wicked. Um, you could short a companion ticker called

634
00:37:10,440 --> 00:37:13,480
Speaker 1: like good. If we think evil is just too bad

635
00:37:13,480 --> 00:37:15,880
Speaker 1: a ticker, we could call it well hell is available.

636
00:37:15,920 --> 00:37:18,600
Speaker 1: But we could also call it UNPC And then we

637
00:37:18,640 --> 00:37:25,480
Speaker 1: appeal to sort of jerk x E s g um, well,

638
00:37:25,520 --> 00:37:32,000
Speaker 1: it's obviously very clever, but he says, but you yourself

639
00:37:32,120 --> 00:37:40,799
Speaker 1: sort of seemed to be hoping it fails. No, Um, well, yeah,

640
00:37:41,560 --> 00:37:44,799
Speaker 1: I appreciate the like I appreciate like sort of the

641
00:37:45,320 --> 00:37:51,120
Speaker 1: undiluted evil of it. Just an abstract repeal to people's face.

642
00:37:51,280 --> 00:37:54,400
Speaker 1: I mean, this is not going away bad behavior. You know,

643
00:37:54,719 --> 00:37:58,239
Speaker 1: it's it's a very solid base to build a product on,

644
00:37:58,640 --> 00:38:01,560
Speaker 1: especially you know this, say shy, I get it, all right,

645
00:38:01,760 --> 00:38:05,719
Speaker 1: thank you evil, no problem. All right, that was all

646
00:38:05,760 --> 00:38:10,800
Speaker 1: the pitches. Those were good. So yeah, you want to remember.

647
00:38:10,880 --> 00:38:13,480
Speaker 1: I go walk the hall. Okay, all right, let me

648
00:38:13,520 --> 00:38:15,399
Speaker 1: go step out for a minute. Okay, take a take

649
00:38:15,400 --> 00:38:17,319
Speaker 1: a little breathe. Alright, take a little breathe and take

650
00:38:17,320 --> 00:38:20,120
Speaker 1: a little breather. I'll be back in the meantime. No

651
00:38:20,239 --> 00:38:37,680
Speaker 1: fighting amongst you, Sarah, I think a ship. Okay, so

652
00:38:37,719 --> 00:38:39,919
Speaker 1: we're back. You took a little walk around the block,

653
00:38:40,360 --> 00:38:44,720
Speaker 1: collected your thoughts. You did some scoring like in figure skating. Okay,

654
00:38:44,960 --> 00:38:48,359
Speaker 1: let's hear it. So here we go, one by one,

655
00:38:48,680 --> 00:38:51,400
Speaker 1: first come, first served. Carlina Wilson came up first with

656
00:38:51,520 --> 00:38:56,400
Speaker 1: frat clever name. Uh, there's some positives to it, but

657
00:38:56,480 --> 00:38:59,239
Speaker 1: here's my issue. I gave it a six out of ten.

658
00:38:59,760 --> 00:39:02,719
Speaker 1: And because as nice as solid as the name is,

659
00:39:02,760 --> 00:39:05,080
Speaker 1: I think these kids are broke. I don't think I

660
00:39:05,120 --> 00:39:07,279
Speaker 1: think you could also be call this broke. This Uh,

661
00:39:07,400 --> 00:39:11,000
Speaker 1: this is I just don't ultimately know that it's enough

662
00:39:11,920 --> 00:39:15,719
Speaker 1: of a growth business for me to tap into Sara Pons,

663
00:39:15,719 --> 00:39:20,560
Speaker 1: who I gave a seven too. Uh. It just it

664
00:39:20,680 --> 00:39:22,880
Speaker 1: just feels right, the whole gen Z trade. I mean,

665
00:39:22,920 --> 00:39:26,080
Speaker 1: I'm I'm just sort of feeling it's a touch ethereal

666
00:39:26,120 --> 00:39:29,319
Speaker 1: to me, but I I'm going with a seven. Joe

667
00:39:29,400 --> 00:39:36,520
Speaker 1: Weber fitty five. Here's about thing again, this one was

668
00:39:36,600 --> 00:39:42,480
Speaker 1: definitely shorting costs. Well, you're essentially telling me this one

669
00:39:42,520 --> 00:39:44,320
Speaker 1: to trust you. That's I kind of felt there's a

670
00:39:44,360 --> 00:39:45,840
Speaker 1: little bit too much of what I'm telling you to

671
00:39:45,880 --> 00:39:49,520
Speaker 1: trust Bloomberg Intelligence, but you know, don't shift it on me.

672
00:39:51,600 --> 00:39:54,560
Speaker 1: And it was it was also a touch too ethereal.

673
00:39:54,600 --> 00:39:58,080
Speaker 1: But but all right, but fifty gets a five, so

674
00:39:58,080 --> 00:40:03,040
Speaker 1: we're thematically linked up there. Ron and Rof James I

675
00:40:03,080 --> 00:40:08,000
Speaker 1: gave a six to. I very much find appeal in

676
00:40:08,120 --> 00:40:11,240
Speaker 1: Ron and Roff, But again I found it a touch

677
00:40:11,320 --> 00:40:15,560
Speaker 1: too convoluted. Uh, And I thought there were too many

678
00:40:15,640 --> 00:40:18,279
Speaker 1: moving parts, especially in a Yeah, you've got something to say.

679
00:40:18,320 --> 00:40:22,080
Speaker 1: What's convoluted about risk on and risk off? What's what's

680
00:40:22,160 --> 00:40:27,080
Speaker 1: convoluted about um is that there are you know, within

681
00:40:27,160 --> 00:40:29,799
Speaker 1: each sector of the risk on risk off, Right, there

682
00:40:29,800 --> 00:40:32,440
Speaker 1: were there were different, you know, elements to it that

683
00:40:32,480 --> 00:40:35,520
Speaker 1: you were telling me that I had to write U

684
00:40:35,800 --> 00:40:38,439
Speaker 1: figure out how to break down the investment and and

685
00:40:38,440 --> 00:40:40,920
Speaker 1: and invested, depending you know, in different times. I just

686
00:40:40,960 --> 00:40:44,680
Speaker 1: sort of felt like in a sixty second pitch there

687
00:40:44,719 --> 00:40:46,080
Speaker 1: was a fair amount to get my head around. But

688
00:40:46,120 --> 00:40:48,680
Speaker 1: that's the opposite of yoursue with Jewels, which was there

689
00:40:48,680 --> 00:40:50,600
Speaker 1: they're telling you what to own, and this is like

690
00:40:50,640 --> 00:40:54,759
Speaker 1: allowing you to own your own research. That's against you.

691
00:40:57,680 --> 00:40:59,959
Speaker 1: I think if anything actually is going to revise ron

692
00:41:00,040 --> 00:41:04,239
Speaker 1: Off from a six to a three, we now know

693
00:41:04,320 --> 00:41:07,640
Speaker 1: what's gonna last. Alright, very good, But if you want

694
00:41:07,680 --> 00:41:12,720
Speaker 1: to keep and go for it, alright, Morgan Live gets

695
00:41:12,760 --> 00:41:15,480
Speaker 1: a seven. I believe this is the second seven we

696
00:41:15,560 --> 00:41:19,920
Speaker 1: now have. Um is a gambler. I believe in this industry.

697
00:41:20,000 --> 00:41:22,319
Speaker 1: I don't know. I think there's a little bit too

698
00:41:22,400 --> 00:41:24,040
Speaker 1: much hype in terms of how much this is gonna

699
00:41:24,080 --> 00:41:28,239
Speaker 1: grow UM, but I believe in it is enough to

700
00:41:28,239 --> 00:41:29,799
Speaker 1: to sort of feel like we we might want to

701
00:41:29,800 --> 00:41:32,720
Speaker 1: think about putting some money there. I'm not totally feeling

702
00:41:32,719 --> 00:41:35,560
Speaker 1: the ticker Elive is a little it's a little it's

703
00:41:35,560 --> 00:41:39,560
Speaker 1: a little flat to me. Next up, is Mr Belcrinus

704
00:41:39,640 --> 00:41:41,880
Speaker 1: with x mon And as much as this pains me,

705
00:41:42,480 --> 00:41:45,160
Speaker 1: I gave him a big number. I gave him a nine.

706
00:41:45,440 --> 00:41:53,120
Speaker 1: Whoa Joel called it lazy, but again in what is Joel? What?

707
00:41:53,239 --> 00:42:00,359
Speaker 1: What was Joel's rating? So? I mean, I think what

708
00:42:00,480 --> 00:42:03,600
Speaker 1: it's apt. Remember it is the sixty second elevator pitch.

709
00:42:03,640 --> 00:42:07,719
Speaker 1: You gotta get my attention quickly. There's a storyline with

710
00:42:07,760 --> 00:42:10,960
Speaker 1: this that I could very easily get my head around. Uh.

711
00:42:11,040 --> 00:42:14,719
Speaker 1: And there's a believability factor to it. I think you know,

712
00:42:14,800 --> 00:42:17,120
Speaker 1: you went back like eighty years of data that shows

713
00:42:17,160 --> 00:42:20,959
Speaker 1: this is not just some gimmicky, you know sort of thing. Um,

714
00:42:21,160 --> 00:42:25,919
Speaker 1: and I found these things attractive. It's right now nine

715
00:42:26,000 --> 00:42:30,680
Speaker 1: you are, you are in first in the clubhouse. Um

716
00:42:30,719 --> 00:42:38,000
Speaker 1: Ben Steveerman City right, reigning champion. Well City was one option,

717
00:42:38,040 --> 00:42:42,600
Speaker 1: but yup, yu alright. I gave this an eight. I

718
00:42:42,640 --> 00:42:45,080
Speaker 1: just think actually that the whole urbanization thing is huge.

719
00:42:45,560 --> 00:42:48,840
Speaker 1: I think it's it's here to stay, it's global, it's

720
00:42:48,880 --> 00:42:51,640
Speaker 1: it's real, it's part frankly why the world. In some

721
00:42:51,680 --> 00:42:54,320
Speaker 1: ways it's so screwed up right to divide, political divide

722
00:42:54,320 --> 00:42:56,319
Speaker 1: and all that. And you know between rural and urban,

723
00:42:56,360 --> 00:43:00,560
Speaker 1: but you know, unwealthy and and poor rurals got growth.

724
00:43:00,840 --> 00:43:02,600
Speaker 1: You've got a ton of growth. I mean it may

725
00:43:02,600 --> 00:43:05,600
Speaker 1: not necessarily make the world of great places and ways,

726
00:43:05,640 --> 00:43:07,759
Speaker 1: but I think it's it's just destined to keep growing.

727
00:43:07,880 --> 00:43:09,759
Speaker 1: And whether it's city or whether it's yuppy, those are

728
00:43:09,760 --> 00:43:12,640
Speaker 1: good takers. I gave it an eight. He consistently brings

729
00:43:12,680 --> 00:43:18,760
Speaker 1: the power. So you're saying it was three better than okay,

730
00:43:19,520 --> 00:43:25,000
Speaker 1: and and five better than it was five better than

731
00:43:25,080 --> 00:43:31,719
Speaker 1: Ron Row. Yeah, um, Rachel Evans stick, I give a six. Two.

732
00:43:31,760 --> 00:43:35,640
Speaker 1: Where's Rachel? She's angry. So because she's so angry, I'm

733
00:43:35,640 --> 00:43:38,279
Speaker 1: gonna have Bluetoon's explain why I got a six? No,

734
00:43:38,800 --> 00:43:44,279
Speaker 1: uh no, I I liked it. I in the end,

735
00:43:45,520 --> 00:43:48,960
Speaker 1: And I know you're telling me that, right, the genius

736
00:43:48,960 --> 00:43:51,520
Speaker 1: of buying all five of the most recent is that's

737
00:43:51,520 --> 00:43:53,279
Speaker 1: gonna get me all this wustions. I don't know. I

738
00:43:53,280 --> 00:43:57,560
Speaker 1: don't know. There's something about blanket buying all the craft

739
00:43:57,640 --> 00:44:00,359
Speaker 1: that's that's that's and the great stuff that's put out there.

740
00:44:00,400 --> 00:44:02,080
Speaker 1: I just didn't want it. Especially I'm a little bit

741
00:44:02,120 --> 00:44:04,880
Speaker 1: thrown by the by this trend of older and older

742
00:44:04,880 --> 00:44:07,239
Speaker 1: companies I p oing, but a six is a good

743
00:44:07,280 --> 00:44:09,960
Speaker 1: number to beat beat old by one, and it beat

744
00:44:10,000 --> 00:44:11,879
Speaker 1: run Rock. I guess he's saying he didn't like your hand.

745
00:44:16,440 --> 00:44:21,680
Speaker 1: The Greek with reject um I give it is he

746
00:44:21,800 --> 00:44:26,200
Speaker 1: is the Greek on Hey, how you doing? I gave

747
00:44:26,239 --> 00:44:29,080
Speaker 1: you a seven, which as of right now puts you

748
00:44:29,120 --> 00:44:32,960
Speaker 1: in a tie for third. I believe that, you know,

749
00:44:33,360 --> 00:44:35,239
Speaker 1: if I'm gonna be doling out a hundred million, there's

750
00:44:35,239 --> 00:44:37,319
Speaker 1: got to be some contrarian play in here. This is,

751
00:44:37,360 --> 00:44:39,319
Speaker 1: this is I thought this was the best contrarian play.

752
00:44:39,360 --> 00:44:42,720
Speaker 1: Although evils also were evils also a good contrarian play.

753
00:44:42,880 --> 00:44:46,040
Speaker 1: I also think that there's indeed, you just get so

754
00:44:46,160 --> 00:44:49,760
Speaker 1: much hype around the fact or stuff and all that that. Um,

755
00:44:49,800 --> 00:44:52,359
Speaker 1: if you write, we're gonna be holding onto this stuff

756
00:44:52,400 --> 00:44:56,000
Speaker 1: for a decent period of time, right to cash in, um,

757
00:44:56,040 --> 00:45:01,440
Speaker 1: I think it makes sense. Uh so seven for reject Annie,

758
00:45:02,040 --> 00:45:07,000
Speaker 1: I do, where are you? I'll give you a six? Wow,

759
00:45:07,080 --> 00:45:10,680
Speaker 1: I'm shocked by that. That's okay, Why are you shocked?

760
00:45:11,040 --> 00:45:14,400
Speaker 1: I don't know. I thought it came off. It just

761
00:45:14,440 --> 00:45:16,480
Speaker 1: came off. You can't explain it, is it? Because it

762
00:45:16,520 --> 00:45:19,760
Speaker 1: was such a polished pitch of so many good ideas.

763
00:45:19,840 --> 00:45:21,600
Speaker 1: It was very good. There's there was no issue with

764
00:45:21,640 --> 00:45:24,160
Speaker 1: the pitch. The pitch was killer. The name is killer,

765
00:45:25,160 --> 00:45:29,800
Speaker 1: who the idea killer who truly believes in the institution

766
00:45:29,840 --> 00:45:32,920
Speaker 1: of marriage is a crazy growth industry. Raise your hands, people,

767
00:45:33,000 --> 00:45:37,040
Speaker 1: you can and I'm not stopping you from pitching this elsewhere.

768
00:45:37,040 --> 00:45:43,400
Speaker 1: You want to keep pitching. Know the pitch was killer.

769
00:45:43,440 --> 00:45:46,680
Speaker 1: Everybody's a little upset here in this phase. It was good.

770
00:45:46,880 --> 00:45:50,680
Speaker 1: But the last thing, the last little issue I had

771
00:45:50,800 --> 00:45:52,879
Speaker 1: was just a little it's too dispersed, like I don't

772
00:45:53,160 --> 00:45:55,319
Speaker 1: really like I don't. I'm strongly get my head around

773
00:45:55,360 --> 00:45:59,880
Speaker 1: having Amazon as a as a bet on the wedding industry.

774
00:46:00,040 --> 00:46:04,480
Speaker 1: Moving on, knife through my heart and it was robbed, robbed. Alright,

775
00:46:04,480 --> 00:46:06,200
Speaker 1: well you got you guys, give her some money to

776
00:46:06,280 --> 00:46:14,719
Speaker 1: your own then now accepting other people's money. Evil was

777
00:46:14,760 --> 00:46:16,880
Speaker 1: super close. In the end, I gave it a six.

778
00:46:17,120 --> 00:46:19,040
Speaker 1: It was super closer. Here's the thing. It is a

779
00:46:19,120 --> 00:46:24,160
Speaker 1: lot of fun. It's awesome. Five. You know what, I'll

780
00:46:24,200 --> 00:46:28,719
Speaker 1: take half six points. I'll take zero point six from Joel.

781
00:46:30,360 --> 00:46:32,360
Speaker 1: We've got a six six. Joel will get to go

782
00:46:32,440 --> 00:46:36,480
Speaker 1: down to a four. Four, right, okay? Four four right,

783
00:46:37,440 --> 00:46:42,799
Speaker 1: it sounds better five four point four six or so.

784
00:46:42,920 --> 00:46:47,239
Speaker 1: I think it's super fun. It's in the end um

785
00:46:47,320 --> 00:46:49,680
Speaker 1: it's uh. I don't think people are going to put

786
00:46:49,719 --> 00:46:53,480
Speaker 1: money into it, but it's it's because it's evil. So

787
00:46:54,680 --> 00:46:59,520
Speaker 1: that's it. That's a wrap. Eric, there's a certain wind

788
00:47:00,080 --> 00:47:05,440
Speaker 1: t can you can you even say it? Joel? Say

789
00:47:05,480 --> 00:47:07,879
Speaker 1: it again? You know I called it lazy. I called

790
00:47:07,920 --> 00:47:12,040
Speaker 1: it lazy? Ye man, yeah, nowns who gets the last laugh?

791
00:47:12,400 --> 00:47:16,320
Speaker 1: I guess you do? Uh dollars. So, so fifty millions

792
00:47:16,760 --> 00:47:20,160
Speaker 1: is a good hold. I was bounced early from the

793
00:47:20,160 --> 00:47:23,040
Speaker 1: other one, so I nice, Yeah, how does it feel?

794
00:47:23,400 --> 00:47:25,680
Speaker 1: What are you going to do with fifty million dollars

795
00:47:25,680 --> 00:47:27,759
Speaker 1: in your ETF? Honestly I picked this because I was

796
00:47:27,840 --> 00:47:30,760
Speaker 1: kind of surprised there wasn't a product like this, because,

797
00:47:30,920 --> 00:47:32,680
Speaker 1: like you said, you can get it in a minute,

798
00:47:32,920 --> 00:47:34,319
Speaker 1: and if it starts to get some of that out

799
00:47:34,360 --> 00:47:38,840
Speaker 1: performance performance plus easy to understand equals flows, I would

800
00:47:38,880 --> 00:47:42,399
Speaker 1: suspect that's right. I actually think, well, let's launch this thing.

801
00:47:43,920 --> 00:47:49,480
Speaker 1: You serious, you get the hundred millions, that's all hundred million, okay?

802
00:47:49,520 --> 00:47:53,680
Speaker 1: And so reigning out rounding out number two last year's winner,

803
00:47:53,920 --> 00:48:00,680
Speaker 1: Benn steps again. This guy's like, yeah, becomes ready to play,

804
00:48:01,120 --> 00:48:03,320
Speaker 1: but he also it almost like seems like he knows,

805
00:48:03,800 --> 00:48:06,240
Speaker 1: you know, investing wise, some of the things that appealed

806
00:48:06,239 --> 00:48:09,920
Speaker 1: to me. I believe in Empty. I believe in empty,

807
00:48:09,960 --> 00:48:13,280
Speaker 1: and even though empty hasn't paid off yet, it will

808
00:48:13,600 --> 00:48:17,560
Speaker 1: And no yuppy yuppi yuppy slash shitty whatever. Fine, we

809
00:48:17,640 --> 00:48:21,560
Speaker 1: need to finalize the name before I give you the money. Obviously, Um,

810
00:48:21,560 --> 00:48:25,680
Speaker 1: that's that's a winner. I had three people tied at seven, right,

811
00:48:26,320 --> 00:48:31,120
Speaker 1: but in that tiebreaker I went to I went to Ponzi,

812
00:48:36,760 --> 00:48:39,120
Speaker 1: so she gets story much. I will ultimately just and

813
00:48:39,120 --> 00:48:42,360
Speaker 1: I'm gonna probably rue the day that I believe in Already,

814
00:48:45,360 --> 00:48:49,400
Speaker 1: all year headlines you're going to see that are no

815
00:48:49,520 --> 00:48:57,560
Speaker 1: longer millennial gen z. Everyone's gonna hate in the best way,

816
00:48:59,320 --> 00:49:02,160
Speaker 1: Mr Papa was what did you learn in this whole

817
00:49:02,200 --> 00:49:07,280
Speaker 1: process that, um, absorbing pitches in sixty seconds is tricky?

818
00:49:07,520 --> 00:49:09,239
Speaker 1: And I don't know, I mean, Eric, you tell me

819
00:49:09,320 --> 00:49:13,359
Speaker 1: how realistically how quickly do people make decisions on what

820
00:49:13,440 --> 00:49:15,960
Speaker 1: E T F s to buy? But I do feel

821
00:49:16,000 --> 00:49:21,319
Speaker 1: like a storyline and a clear product that are easy

822
00:49:21,320 --> 00:49:23,840
Speaker 1: to get your head around. There. There feels to me

823
00:49:23,880 --> 00:49:25,480
Speaker 1: like there's a lot of value to that. I mean,

824
00:49:25,520 --> 00:49:28,919
Speaker 1: certainly in this kind of compressed format that was the case. Well,

825
00:49:29,640 --> 00:49:31,640
Speaker 1: I don't go to those pitch meetings, but generally I

826
00:49:31,640 --> 00:49:34,600
Speaker 1: would think so because that's what works flow wise for

827
00:49:34,640 --> 00:49:36,560
Speaker 1: these products that aren't just sort of cheap data. So

828
00:49:36,840 --> 00:49:40,680
Speaker 1: you give me some examples. Okay, example robotics. Um, everybody

829
00:49:40,719 --> 00:49:43,279
Speaker 1: understands robotics. They see the video of the robot jumping

830
00:49:43,320 --> 00:49:44,920
Speaker 1: over the car and they're like, oh yeah, big industry,

831
00:49:44,920 --> 00:49:47,600
Speaker 1: and then robot starts going up. Boom, there goes the flows.

832
00:49:47,960 --> 00:49:50,000
Speaker 1: There are other e t s that outperformed that don't

833
00:49:50,000 --> 00:49:52,160
Speaker 1: get the flows because I do think they're tougher for

834
00:49:52,200 --> 00:49:54,640
Speaker 1: people to understand. Um. So I do think the easy

835
00:49:54,680 --> 00:49:57,000
Speaker 1: to understand the thirty second pitch is a good idea

836
00:49:57,040 --> 00:49:59,480
Speaker 1: because if you can get the seed investor and to

837
00:49:59,600 --> 00:50:01,960
Speaker 1: understand and it or somebody in thirty seconds when it

838
00:50:02,000 --> 00:50:05,040
Speaker 1: has a good breakout performance, if people don't understand it,

839
00:50:05,080 --> 00:50:07,120
Speaker 1: I don't know if the performance is enough. So I

840
00:50:07,160 --> 00:50:09,520
Speaker 1: do think that's likely what people are looking for. I

841
00:50:09,560 --> 00:50:12,360
Speaker 1: asked Mike Venuto. He said, obviously seed capital is a

842
00:50:12,360 --> 00:50:14,400
Speaker 1: big one. If you have C capital will probably green

843
00:50:14,480 --> 00:50:16,080
Speaker 1: light you. And then the other one was he did

844
00:50:16,120 --> 00:50:18,280
Speaker 1: look for like if you could develop a family around it,

845
00:50:18,400 --> 00:50:20,799
Speaker 1: if it was easy to understand and simple, and if

846
00:50:20,800 --> 00:50:22,880
Speaker 1: there was obviously nothing really like it on the market.

847
00:50:23,600 --> 00:50:28,719
Speaker 1: How many, because like Any's pitch was great, But again, personally,

848
00:50:28,719 --> 00:50:30,640
Speaker 1: I just don't see how that's a growth industry. How

849
00:50:30,640 --> 00:50:32,560
Speaker 1: many e t F s are launched, like sort of

850
00:50:32,560 --> 00:50:35,080
Speaker 1: thematics are lace that are not that in a do

851
00:50:35,239 --> 00:50:38,600
Speaker 1: well that are not People are not selling growth like

852
00:50:38,680 --> 00:50:40,360
Speaker 1: you know, they're like I'm saying, here's an et F

853
00:50:40,440 --> 00:50:43,000
Speaker 1: with a great stable industry. Does that appeal to people

854
00:50:43,320 --> 00:50:45,200
Speaker 1: in the theme front? Not much? I think with the

855
00:50:45,200 --> 00:50:47,040
Speaker 1: theme ETF that's why they equal weight them. You gotta

856
00:50:47,080 --> 00:50:50,080
Speaker 1: juice those suckers up with them, like like all legal

857
00:50:50,160 --> 00:50:52,279
Speaker 1: p e d s, which is like equal waiting some

858
00:50:52,400 --> 00:50:54,960
Speaker 1: fang stocks. You juice them up and then they outperform.

859
00:50:55,280 --> 00:50:56,880
Speaker 1: A lot of people don't understand it's because they have

860
00:50:56,920 --> 00:51:00,799
Speaker 1: more risk, but they're outperforming nonetheless, and they go, oh,

861
00:51:00,880 --> 00:51:02,680
Speaker 1: and then the theme kind of kicks in. They're like, oh,

862
00:51:02,680 --> 00:51:09,400
Speaker 1: of course robotics or cybersecurity juice Like if I do

863
00:51:09,480 --> 00:51:12,160
Speaker 1: start out performing, I think people go, Yeah, of course

864
00:51:12,600 --> 00:51:15,000
Speaker 1: everybody spends a bundle on weddings. I did too, I

865
00:51:15,080 --> 00:51:18,759
Speaker 1: get it. I'll buy it all right. Thanks to David

866
00:51:18,760 --> 00:51:21,560
Speaker 1: Popadapo's for judging well. Thanks to our contestants for all

867
00:51:21,560 --> 00:51:24,600
Speaker 1: those great ideas. Maybe mine wasn't so great after all,

868
00:51:24,680 --> 00:51:26,480
Speaker 1: but you know that was a fun one, except for

869
00:51:26,520 --> 00:51:35,799
Speaker 1: coming in basically like a second to last. Thanks for

870
00:51:35,840 --> 00:51:38,080
Speaker 1: listening to New Trillions until next time. You can find

871
00:51:38,160 --> 00:51:42,600
Speaker 1: us on Bloomberg Terminal, Bloomberg dot com, Apple Podcast, Spotify,

872
00:51:42,719 --> 00:51:44,960
Speaker 1: and where else you like to listen. We'd love to

873
00:51:45,000 --> 00:51:49,040
Speaker 1: hear from you. We're on Twitter, I'm at Joel Webber Show,

874
00:51:49,400 --> 00:51:53,840
Speaker 1: He's at Eric Falcina's. Trillions is produced by Magnus Hendrickson.

875
00:51:54,320 --> 00:52:02,440
Speaker 1: Princessca Levy is the head of Bloomberg podcast The Totter