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Speaker 1: Welcome a brilliance. I'm Joel Webber and I'm Eric bel Tunis.

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Speaker 1: One of my favorite things to do at the end

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Speaker 1: of the show is often ask people's favorite tickers, and

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Speaker 1: one of the ones that I would always put on

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Speaker 1: that list probably would be Robo. And so you and

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Speaker 1: I've always talked about Robo, and that led us to

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Speaker 1: today's episode. Yeah, No, Robo is fascinating. Um. I keep

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Speaker 1: seeing these Boston Dynamic videos where you've got like a

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Speaker 1: robot like doing a flip and landing on his feet,

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Speaker 1: or a little robot dog. It looks like it's from

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Speaker 1: Minority Report, like going up and down into parks and

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Speaker 1: monitoring people, and it really kind of it's freaks you

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Speaker 1: out in a way, but it also excites you. Um.

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Speaker 1: I guess having seen at a lot of movies in

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Speaker 1: the eighties, you can't imagine a world where robots are

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Speaker 1: a big part. So I think the robo theme really

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Speaker 1: captured the imagination of people. And that's what a theme

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Speaker 1: etf had to do. It can't just outperform, it also

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Speaker 1: has to capture the imagination. And so this firm put

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Speaker 1: out Robo had a big hit, and then they started

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Speaker 1: making some other e t F s, and it's a

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Speaker 1: great story because the other e t F s are

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Speaker 1: also futuristic in design and really speak to both interesting

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Speaker 1: themes we can discuss as well as the way E

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Speaker 1: t F fishers, you know, try to navigate a tough

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Speaker 1: market with product design launches and keeping up the assets

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Speaker 1: in in you know, their existing hits. So what's the

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Speaker 1: company and who's our guest. The company's Robo Global and

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Speaker 1: they would be you know, we've talked about that that

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Speaker 1: term indie independent. They are classic indie issuer. And the

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Speaker 1: guests today would be Nina Deeca, who's a senior research

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Speaker 1: annelist over there. So she's kind of like we had

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Speaker 1: Paul by Aki on a lot of e t F

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Speaker 1: fishers have hardcore knowledge specialists to help answer advisor questions

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Speaker 1: on these strategies, and that's what she does this time

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Speaker 1: on Trillions Inside Robo Hi, Nina, welcome to Trillions. Hey,

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Speaker 1: how are you? Thank you so much for having me

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Speaker 1: on your show today. Thanks for joining. So we've spent

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Speaker 1: a little bit of time here talking about robo um,

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Speaker 1: which will I think we'll talk a little bit more about.

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Speaker 1: But you specifically work on another E t F which

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Speaker 1: is called h tech. What's that's right, that's our Healthcare

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Speaker 1: Technology and Innovation Index that trades as an a t

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Speaker 1: F globally. We've got a trading on two exchanges and

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Speaker 1: it's been live for over a year UM and it

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Speaker 1: is basically our compilation. We we follow a similar methodology

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Speaker 1: to the Robo et F as you just mentioned, UM,

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Speaker 1: where we use fundamental research to choose the best in

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Speaker 1: class companies that represent all the disruption happening in healthcare

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Speaker 1: over the next five to ten years. We look at

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Speaker 1: areas such as robotics, virtual care, gene c guincing diagnostics,

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Speaker 1: precision medicine. These are all the areas that we think

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Speaker 1: are being very much transformed and and have offer a

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Speaker 1: wide breadth of investment opportunity. Eric has been a pretty

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Speaker 1: good year for them. Yeah, I'm just looking at the

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Speaker 1: performance now. I Mean, we talk a lot on the

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Speaker 1: show about how flows go one of two places, dirt

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Speaker 1: cheap or shiny objects. And robo makes the shiny objects,

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Speaker 1: and h tech is in shiny object mode. It's up

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Speaker 1: fifty since launching in June. That's double XLV, which is

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Speaker 1: the Healthcare ETF. It's even greater than XBI, the biotech

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Speaker 1: ETF and for perspective, the market was about so, um,

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Speaker 1: this is a real performance surge here and it's got

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Speaker 1: about sixty million in assets, So that tells you how

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Speaker 1: hard it is. You've gotta you've got to sustain this

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Speaker 1: performance for a little while to get you know, into

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Speaker 1: the big asset numbers. But mina, what's behind the performance?

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Speaker 1: Like which part of those things you just mentioned is

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Speaker 1: driving that return. There's a bunch of things. One, as

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Speaker 1: you mentioned, the things that I just mentioned are driving

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Speaker 1: diversity in in our portfolio offerings. So rather than just

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Speaker 1: looking at one area like telehealth or just genomics, we're

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Speaker 1: looking across the board at the a lot of different

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Speaker 1: areas including diagnostics, precision medicine, et cetera. And so what

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Speaker 1: you what you the advantage of that is you get

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Speaker 1: to capture the growth that's happening. Um And when one

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Speaker 1: thing is in favor, others might fall out of favor.

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Speaker 1: But by having that diversity, it shields you from the

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Speaker 1: volatility that's happening. Mind you, these are largely growth stocks.

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Speaker 1: In fact, um about half of the index are our

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Speaker 1: companies that are less than ten billion dollars in market cap, So,

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Speaker 1: talk to us how you go about building an index

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Speaker 1: like this, What what was the what was the blank

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Speaker 1: white slate that you sort of started with here, and

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Speaker 1: how did you go about executing the strategy? I mean,

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Speaker 1: so the template was robo. We had six plus years

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Speaker 1: of proven success. And what we did with Robo is

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Speaker 1: we looked at not just whose driving innovation in robotics,

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Speaker 1: automation and AI, but the picks and the shovels that

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Speaker 1: are also enabling companies to have robotics, automation and AI.

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Speaker 1: And one of those areas that we focused on in

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Speaker 1: robo was healthcare. We saw so much disruption happening in

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Speaker 1: that area that it warranted its own strategy. So, like

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Speaker 1: I said, last year, we launched h Tech, which focus

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Speaker 1: exclusively on healthcare innovation, and we said, what are the

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Speaker 1: areas and we came up with our own proprietary list

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Speaker 1: of um so as I mentioned, lab, automation is one, diagnostics, UH,

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Speaker 1: precision medicine, telemedicine, and and we said these are the

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Speaker 1: nine areas that we believe represent the most disruption. Now

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Speaker 1: it's not just enough to say, okay, we're going to

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Speaker 1: look at genomics and then do a Google Search and

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Speaker 1: just put all the genomics names in here. We actually

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Speaker 1: went through all the companies and chose which ones we

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Speaker 1: believe our best in class. They have to be market leaders,

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Speaker 1: technology leaders, and they also have to uh follow some

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Speaker 1: financial criteria of ours strong balance sheet um uh they

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Speaker 1: can't break various criteria in terms of ev sales and UM.

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Speaker 1: And then the debts evada ratio are important criteria to

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Speaker 1: us as well. And how do you how do you

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Speaker 1: go about figuring out what the waitings are going to

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Speaker 1: be across those nine categories? We haven't. Interestingly, we have

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Speaker 1: a scoring system and I'll have to show it to

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Speaker 1: you sometime, but it's it's a it's a pretty in

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Speaker 1: depth intranet that we have where every single company in

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Speaker 1: our universe that we analyze has a score UM. There

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Speaker 1: are several thousand actually that we that we do conduct

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Speaker 1: fundamental research on and through that methodology, the ones that

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Speaker 1: mind up with the top scores are the ones that

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Speaker 1: get included in the index UM. And then we've got

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Speaker 1: a quarterly process where we rebalance, so we actually trind

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Speaker 1: the outperformers and we add positions to the underperformers because

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Speaker 1: again we're looking at the long term here, and for

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Speaker 1: them to have even made it in the index means

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Speaker 1: that we're looking at their growth out of the next

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Speaker 1: at least five years. So UM so it does help

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Speaker 1: maintain that we're always buying low and selling high, and

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Speaker 1: and then at that quarterly time, if there is a

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Speaker 1: new company that we want to introduce to the index

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Speaker 1: or one that needs to get kicked out because it

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Speaker 1: no longer meets our criteria, we have an extensive review process.

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Speaker 1: We have a team of ten advisors who are world

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Speaker 1: renowned experts in the fields in which they operate UM,

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Speaker 1: such as the founder of Amazon Robotics and the director

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Speaker 1: of AI at M I T. These are the people

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Speaker 1: that we also work with UM to help decide which

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Speaker 1: companies belong in the index. One thing I would be

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Speaker 1: curious about to know is when you're talking to advisors

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Speaker 1: about a product like this, Clearly it's a little more

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Speaker 1: volatile than XLV because it's it's gonna have smaller stocks

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Speaker 1: and the waiting is such that there's more volatility. How

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Speaker 1: do you use it in a portfolio? Like? What does

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Speaker 1: this replace? Is this sort of like the hot sauce

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Speaker 1: that you just use a little on top to maybe

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Speaker 1: give your portfolio a little extra seasoning, or is this

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Speaker 1: replacing something bigger? It's it could actually be complementary. So

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Speaker 1: you mentioned earlier how you think you find the world

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Speaker 1: of robotics and innovation very interesting, and a lot of

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Speaker 1: people might think they already have exposure to that. Same

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Speaker 1: with healthcare UM a lot of investors are like, I

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Speaker 1: already have healthcare more portfolio. But you mentioned earlier the

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Speaker 1: performance of h tech UM compared to some of the

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Speaker 1: largest UH index is traded in the world for healthcare

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Speaker 1: and and there's a huge difference. So when you look

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Speaker 1: at the underlying assets within the e t f s,

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Speaker 1: what you'll find with ours is that there's or less

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Speaker 1: overlap between our healthcare index and comparable indices, as well

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Speaker 1: as our robotics index and comparable indices. So UM So

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Speaker 1: if you're looking for exposure to healthcare innovation, it's not

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Speaker 1: enough to just say you have healthcare in your portfolio.

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Speaker 1: You want to specifically look at the underlying assets, and

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Speaker 1: so with ours, if you want that diversified exposure to

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Speaker 1: these cutting edge areas, UM, h tech is probably a

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Speaker 1: strong area to be adding and complementing your existing portfolio.

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Speaker 1: So some people like I already have biotech al right, Well,

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Speaker 1: we have like less than of our portfolio would be

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Speaker 1: names that you would even fall into that category. And

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Speaker 1: yet even within those companies, we might have names that

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Speaker 1: are not already in your portfolio. In fact, when you

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Speaker 1: look at someone's uh typical investment strategy around healthcare, you'll

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Speaker 1: find that they're most heavily weighed in large cap pharmaceutical

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Speaker 1: and healthcare services companies managed care. We have hardly any

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Speaker 1: exposure to large cap pharma and managed care. So I

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Speaker 1: want to put you on the spot a little bit,

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Speaker 1: your Nina, because has been UM an interesting year to

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Speaker 1: say the least. And I'm curious sort of what the

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Speaker 1: h tech portfolio look like pre pandemic, the before times

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Speaker 1: if you remember those, the quaint before times too. Now,

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Speaker 1: how how was how was the product changed over the

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Speaker 1: course of the year. Interestingly, when so you mentioned our

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Speaker 1: performance over the last twelve months, and it's also it's

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Speaker 1: also done UM performed pretty well over thirty year to date,

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Speaker 1: and and so it's not just the pandemic that has

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Speaker 1: accelerated the index performance or hurt it UM. And so

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Speaker 1: when you take a step back and you think what's

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Speaker 1: what's driving um the markets in general. Oh, we've got

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Speaker 1: the elections, we've got the vaccine, we've got the risk

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Speaker 1: around no one traveling anymore. But interestingly, healthcare innovation tends

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Speaker 1: to be resilient to a lot of those themes because, um,

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Speaker 1: people need healthcare and they need healthcare innovation regardless of

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Speaker 1: what's going on. So just case in point, if you

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Speaker 1: look at new healthcare legislation over the last five to

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Speaker 1: ten years, it's been pro innovation, and a lot of

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Speaker 1: the new legislation that's been passed was bipartisan. So it's

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Speaker 1: not that it didn't matter who was going to be

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Speaker 1: in the White House after this election season, um, but

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Speaker 1: it's it's just that a lot of these themes are

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Speaker 1: supported by all sides. Nobody's arguing that we shouldn't detect

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Speaker 1: cancer earlier or telehealth earlier. So that's one component of it. UM.

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Speaker 1: Regarding the pandemic, if you looked at the headlines in

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Speaker 1: March and April, you probably saw every other day a

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Speaker 1: new company that was working on a vaccine, for a

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Speaker 1: new company that was working on diagnostics um or I

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Speaker 1: shouldn't say a new company, but an additional company and

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Speaker 1: what I want to say is that we already had

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Speaker 1: a lot of those in our portfolio, because when you

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Speaker 1: only select the leaders and the best in class companies,

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Speaker 1: you tend to be already be well positioned for when

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Speaker 1: something like a pandemic takes place. So we already had

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Speaker 1: um quite Dell in our portfolio. For example, we had

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Speaker 1: backed in Dickinson and so because we already did the

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Speaker 1: homework to say these are the people that are best

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Speaker 1: positioned for growth and innovation, it's no surprise that they

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Speaker 1: were also the best position to be the first to

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Speaker 1: market with the covid test um. Maderna we added in March,

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Speaker 1: and they had just announced that they were going to

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Speaker 1: start a clinical trial for their m RNA vaccine. That's

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Speaker 1: not why we put them in. There's always a risk

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Speaker 1: around that, and we're not looking for near term events.

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Speaker 1: We brought Maderna in because they have over twenty other

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Speaker 1: UH drugs in clinical trials right now, ten of which

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Speaker 1: are vaccines. They're working on HIV, RS V CMB, They've

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Speaker 1: got so many other diseases that they're working on, and

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Speaker 1: they're using AI in every facet of what they do

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Speaker 1: in their research and development process. That's why Maderna was

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Speaker 1: able to come up with the COVID vaccine so quickly,

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Speaker 1: and that's what qualified them for the h Tech Index.

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Speaker 1: So when you stick to the methodology and you pull

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Speaker 1: in these technological innovators first, then when something happens that's

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Speaker 1: big and market moving and thematic um, you tend to

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Speaker 1: be well positioned for it. So so I'm also really interested, Um,

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Speaker 1: I'm really interested in another person in the et F world,

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Speaker 1: Cathy Would, who's had just an insane year. And one

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Speaker 1: of the things that you realize when you look inside

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Speaker 1: Cathy's products, especially arc Um, is that Tesla has a

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Speaker 1: ten percent waiting right. She's been extremely bullish on Tesla

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Speaker 1: and as she said on on Trillions before you know

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Speaker 1: it's it's a it's a long term position, but she

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Speaker 1: will actively trade that stock throughout the course of a

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Speaker 1: quarter even um to try and maximize performance. And I'm wondering,

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Speaker 1: you know, your largest holding at the moment is around

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Speaker 1: two what do you what do you make of a

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Speaker 1: Cathy Would style strategy and and and why why not

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Speaker 1: have something that you're you're more more bullish on than

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Speaker 1: just a two percent waiting Our methodology across our in

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Speaker 1: disees is a modified equal waiting because parts of our

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Speaker 1: fundamentals is that we believe in diversity and and diversified exposure.

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Speaker 1: As you recently saw with the Fiser renouncement about their

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Speaker 1: vaccine and and the ninety scent efficacy, and all the

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Speaker 1: diagnostic stocks that had the COVID test took a hit

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Speaker 1: because people thought we're not going to need COVID tests anymore. Well,

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Speaker 1: um H tech did not take that big of a hit.

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Speaker 1: And and that's just one example of one day's news.

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Speaker 1: So when you're dealing with innovation for us, for our methodology,

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Speaker 1: we want to offer that diversity because no one company

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Speaker 1: can pull down the whole index. And so when someone's

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Speaker 1: looking for a long term investment that they can kind

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Speaker 1: of set it and forget it and let us do

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Speaker 1: the groundwork. Um there, there's a little bit less for

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Speaker 1: them to worry about on a day to day or

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Speaker 1: even on a year to year basis. UH. And not

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Speaker 1: to discount what ARC is doing, because those are brilliant strategies,

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Speaker 1: but they are quite different from ours, which once again

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Speaker 1: takes me back to how our strategy could be quite

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Speaker 1: complementary to some of the other products that are out there.

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Speaker 1: So just to fall up on one point you said

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Speaker 1: while you guys were talking, I looked at the overlap

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Speaker 1: between h tech and XLV because a lot of investors

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Speaker 1: are going to use XLV probably or have in the past.

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Speaker 1: That's the big healthcare spider, And it looks like there's

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Speaker 1: only overlaps, so there's definitely a lot of original I

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Speaker 1: think the droll the the waiting where you have much

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Speaker 1: more parity between the top weighted and the lowest weighted

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Speaker 1: that does sometimes give some m and a pop, whereas

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Speaker 1: if you overweight a couple of stocks, you're not going

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Speaker 1: to feel the smaller stocks that much. But um, I

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Speaker 1: think this one looks designed like a classic theme. Um.

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Speaker 1: With that said, you know, just because you're in a

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Speaker 1: position of research, is there one or two things about

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Speaker 1: the future of healthcare that gets you excited? Like, could

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Speaker 1: you take us into the like hospital or the doctor's

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Speaker 1: office and explain something we're gonna see in like ten

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Speaker 1: years that like would blow us away. Sure. Well, one

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Speaker 1: thing that's already blown everybody away this year is telemedicine

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Speaker 1: the doctor patient visit. Because even a few years ago

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Speaker 1: I used to run surveys on the cell side of

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Speaker 1: of adoption to try to gauge are people interested in

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Speaker 1: having a video visit with the doctor? And the vast

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Speaker 1: majority of the people didn't even know it existed and

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Speaker 1: certainly didn't even want to try it. Now people prefer

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Speaker 1: it because once you try something that's easier, cheaper, you

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Speaker 1: don't have to leave your house, you don't have to

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Speaker 1: leave the office. Um. Once you had exposure to it

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Speaker 1: and you see how how easy it is to do,

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Speaker 1: you're more likely to do it again. Telemedicine is only

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Speaker 1: one small aspect of a bigger theme known as virtual care,

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Speaker 1: and in the next five to ten years, virtual care

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Speaker 1: is going to underlie every facet of healthcare. So when

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Speaker 1: we talk about doctor patient visits, uh, tele ADOCT for example,

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Speaker 1: just reported that their visits are up three times your

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Speaker 1: year over year. Um, that's just one small component. When

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Speaker 1: we talk about virtual care, we're not just talking about

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Speaker 1: doctor patient visits. We're talking about doctor to doctor communication,

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Speaker 1: patient to patient communications. So patients are bringing in their families, UM,

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Speaker 1: device to doctor, device to device, patient to device, and

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Speaker 1: that acquires a lot of underlying infrastructure. Teleduct, a company

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Speaker 1: in the h Tech indexes really well positioned to capitalize

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Speaker 1: on that theme through their acquisition of in Touch, which

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Speaker 1: is one such or company that provides this underlying software

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Speaker 1: infrastructure that can help enable all of this connectivity even

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Speaker 1: in the o R. Like in Touch hasn't a partnership

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Speaker 1: with Intuitive Surgical that helps UM a physician. I'm not

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Speaker 1: sure if you're familiar with how surgical robotics works, but

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Speaker 1: when you are, when you're the surgeon and you're conducting

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Speaker 1: a robotic assistant surgery, your head is looking inside of

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Speaker 1: a console. UM, and like think about virtual reality types

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Speaker 1: of things, So your your head is looking inside of

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Speaker 1: a console. And then to look at other devices and

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Speaker 1: gather other data during the procedure, you have to pick

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Speaker 1: your head up and look around and look at some

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Speaker 1: other device or application. UM. With in Touch and their

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Speaker 1: integration capabilities, they're working on bringing some of that visibility

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Speaker 1: into the council, so it's one less thing that the

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Speaker 1: physician has to look for. And so that's that's just

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Speaker 1: one small example. UM. We can also see you examples

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Speaker 1: of telerobotic surgery. UH. There's a physician Dr Patel in

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Speaker 1: India that's already conducted at least five telerobotic surgeries from

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Speaker 1: twenty miles away. This is really interesting to me. So, uh,

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Speaker 1: you're saying that, let's say Joel is in Brooklyn like

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Speaker 1: you are. You both are, and he doesn't want to

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Speaker 1: travel because of COVID, and I'm the doctor in Philadelphia.

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Speaker 1: I can actually operate on him via a robot. That's right,

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Speaker 1: that bet that That's what I was just gonna say.

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Speaker 1: So that technology is just on the cusp of adoption.

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Speaker 1: It's still an innovation, it's still very early days. But

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Speaker 1: with wide adoption of five G, that's going to enable

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Speaker 1: the further practice of that. And and I'll take your

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Speaker 1: example one step further. Um, that's great that someone from

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Speaker 1: Philadelphia can operate on people in Brooklyn, but the worldwide

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Speaker 1: implications are far greater in that someone in a large city,

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Speaker 1: world leading uh cardiologists can operate on somebody in the

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Speaker 1: in the far corners of the earth who might not

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Speaker 1: otherwise have access to that level of care. And so

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Speaker 1: when we talk about the most exciting things happening in healthcare,

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Speaker 1: we're looking at improving access to care at a lower

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Speaker 1: cost and also at a higher quality. And so if

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Speaker 1: we can get people uh, world class cardiologists to to

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Speaker 1: conduct their procedures who otherwise might not have had access.

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Speaker 1: That's going to be a huge improvement and we have

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Speaker 1: a massive runway of growth for that. So when we

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Speaker 1: talk about virtual care, we talk about their large runway

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Speaker 1: for growth. Don't just think about doctor patient visits. There

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Speaker 1: are just so many more things that can be happening. UM.

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Speaker 1: There is one other area where we can reach people

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Speaker 1: in the far corners of the world everywhere, and is

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Speaker 1: with early cancer detection. Today, about the people who are

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Speaker 1: diagnosed with cancer are diagnosed in this community setting, whereas

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Speaker 1: the genetic testing and the more sophisticated tools are all

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Speaker 1: being done at university medical centers. UM. But that's only

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Speaker 1: affecting like of the population. And so how can we

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Speaker 1: get more people access to those types of tools and technologies.

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Speaker 1: Enter the world of early cancer testing. And you talked

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Speaker 1: about M and A earlier. We've seen an explosion of

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Speaker 1: M and A in just the last couple of months

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Speaker 1: with in VTA acquiring archer d x um, Aluminous announcement

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Speaker 1: of Grail Exact Science as announcement of thrive UM, we've

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Speaker 1: already seen ten billion dollars worth of M and A

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Speaker 1: happened in very recent months due to this upcoming anticipated

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Speaker 1: seventy five billion dollar market opportunity for early answer detection

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Speaker 1: and and that that is one of the most exciting

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Speaker 1: things right now. And each tech definitely has exposure. Every

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Speaker 1: company I just named is in the H Tech index

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Speaker 1: seld This. This is really interesting to me because traditionally

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Speaker 1: active management meant you go over the same five hundred

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Speaker 1: stocks and try to find an edge. And that is

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Speaker 1: where I think some money are flowing out of that style,

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Speaker 1: and where it's flowing to is things like factor quant

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Speaker 1: now e t f s and these themes. You can

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Speaker 1: see the appeal here. I'm gonna go core, cheap beta,

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Speaker 1: and then I'll add a little H tech to try

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Speaker 1: to ride something that's you know, potentially going to work

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Speaker 1: for me in the future. But that said, these are

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Speaker 1: a little more volatile than the sort of stockpicking active

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Speaker 1: mutual fund. But to me, this is the new evolution

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Speaker 1: of active you know, I'm I'm really curious. Part of

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Speaker 1: what you're describing there with the early cancer detection is,

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Speaker 1: you know, there's another theme here in the background, which is, um,

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Speaker 1: we're seeing a baby boom generation only older, right, And

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Speaker 1: I'm wondering how much that factors into sort of the

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Speaker 1: companies that you're talking about and their strategies or is

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Speaker 1: it truly a more universal approach where because health care

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Speaker 1: might have implications for somebody who's a baby boomer, but

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Speaker 1: it also could have implications for those of us who

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Speaker 1: are you know, a little bit younger than that. So no,

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Speaker 1: your spot on what are the reasons why? So when

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Speaker 1: we talk about thematic investing, there's UM, there's there's often

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Speaker 1: an emotional aspect. People feel like they want to do

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Speaker 1: the right thing and invest in an area to maybe

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Speaker 1: diversify their portfolio, to to help them feel like they're

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Speaker 1: investing in areas that are um, good for the planet

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Speaker 1: or good for society. And one of the favorite things

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Speaker 1: about my job is that health care innovation meets that

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Speaker 1: it checks that box, but no one's arguing that it's

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Speaker 1: actually happening this this is not a fad, right, So

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Speaker 1: UM like, for example, the early cancer detect and then

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Speaker 1: I just talked about UM. Only a third of cancers

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Speaker 1: today are detected in stage one in stage two, but

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Speaker 1: that's when it's the most treatable. And if you can

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Speaker 1: identify someone's cancer in the earlier stages and estimated hundred

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Speaker 1: thousand lives could be saved every year in the US alone.

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Speaker 1: That's you know, I think about this around the upcoming

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Speaker 1: holiday season. That's a hundred thousand people who are going

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Speaker 1: to be sitting at the holidays at dinner and and

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Speaker 1: and and and enjoying their meals with their family every year.

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Speaker 1: And so when you think about that, it kind of

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Speaker 1: checks that that we need to do this box And

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Speaker 1: there's no one arguing that this isn't here to stay,

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Speaker 1: and that it's actually happening, that it's coming because billions

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Speaker 1: of dollars are being are flowing into this from a

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Speaker 1: research and development standpoint, and it has to happen. And

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Speaker 1: the technology is here. So if the technology is here

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Speaker 1: and the need is here, it's going to happen. You

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Speaker 1: threw out a number there that I just wanna dwell

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Speaker 1: on for a second hundred thousand figure, which made me

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Speaker 1: just think of, you know, this has been such a

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Speaker 1: tragic year. We've lost hundreds of thousands of Americans now um,

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Speaker 1: millions around the world, UM. And I'm just curious, you know, like,

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Speaker 1: you know, we've had this fiser news that you mentioned earlier.

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Speaker 1: We hope that there's a vaccine uh that has distribution,

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Speaker 1: maybe by end of the year, we could start seeing

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Speaker 1: it hopefully early next year. I'm just curious. You know,

431
00:24:23,160 --> 00:24:26,600
Speaker 1: there's there will be a um a post COVID reality

432
00:24:26,680 --> 00:24:30,520
Speaker 1: that will eventually get to and I'm wondering what you

433
00:24:30,560 --> 00:24:35,639
Speaker 1: would expect to happen um UH to h tech in

434
00:24:35,680 --> 00:24:38,560
Speaker 1: that post COVID world. How much of you know, the

435
00:24:38,600 --> 00:24:41,000
Speaker 1: inflows that you've even seen this year has just been

436
00:24:41,480 --> 00:24:45,640
Speaker 1: COVID becoming such a dominant theme in making people be

437
00:24:45,680 --> 00:24:49,000
Speaker 1: thinking about healthcare. Well, it's a great question, and that's

438
00:24:49,040 --> 00:24:50,560
Speaker 1: the other reason why I bring it back to our

439
00:24:50,600 --> 00:24:54,879
Speaker 1: core methodology. Maderna, for example, we didn't bring them in

440
00:24:54,920 --> 00:24:56,960
Speaker 1: because of the COVID vaccine. We brought them in because

441
00:24:56,960 --> 00:25:00,000
Speaker 1: of the twenty other innovative m R and A technology

442
00:25:00,000 --> 00:25:02,200
Speaker 1: needs that they have in the pipeline. Keep in mind

443
00:25:02,240 --> 00:25:06,960
Speaker 1: that in particularly in gene therapy, when something new gets approved,

444
00:25:07,119 --> 00:25:10,000
Speaker 1: it's a positive catalyst for all of the other players

445
00:25:10,040 --> 00:25:12,720
Speaker 1: in this space, and Madurn is very well positioned to

446
00:25:12,760 --> 00:25:14,960
Speaker 1: capitalize on that. So we get one MR and a

447
00:25:15,040 --> 00:25:18,680
Speaker 1: technology that works and gets FDA approved, and and these

448
00:25:18,720 --> 00:25:21,280
Speaker 1: guys have this rich pipeline to continue to grow and

449
00:25:21,720 --> 00:25:24,080
Speaker 1: in a vast runway for growth in all these other

450
00:25:24,119 --> 00:25:33,560
Speaker 1: therapeutic areas. For years, I wish we could play sticks

451
00:25:33,640 --> 00:25:36,480
Speaker 1: the Mr. Roboto song. UM, big fan of that one

452
00:25:36,480 --> 00:25:40,960
Speaker 1: when I was a little kid. But anyway, Robo was robos.

453
00:25:41,040 --> 00:25:43,000
Speaker 1: You know the reason you're here. I think Robo put

454
00:25:43,000 --> 00:25:45,560
Speaker 1: you guys on the map. It was in your first

455
00:25:45,600 --> 00:25:48,119
Speaker 1: launch and you're in a bit a big hit. Most

456
00:25:48,440 --> 00:25:51,440
Speaker 1: firms don't. Aren't that lucky. It went to two point

457
00:25:51,480 --> 00:25:54,359
Speaker 1: five billion down to one point five billion now because

458
00:25:54,400 --> 00:25:58,440
Speaker 1: you inspired all this competition. There's bots. Black Rock got

459
00:25:58,440 --> 00:26:00,280
Speaker 1: into it. I think there's a leverage GT if that's

460
00:26:00,280 --> 00:26:02,280
Speaker 1: how you know a product is a big hit when

461
00:26:02,280 --> 00:26:06,080
Speaker 1: there's a two x version. Anyway, Um, it's it's cooled

462
00:26:06,080 --> 00:26:09,280
Speaker 1: down a little this this area, but it's this year

463
00:26:09,480 --> 00:26:15,600
Speaker 1: it's pretty good inception. What's the latest in the robotics market?

464
00:26:15,760 --> 00:26:19,600
Speaker 1: And I guess maybe take somebody through who all they

465
00:26:19,600 --> 00:26:23,080
Speaker 1: know is maybe you know, uh, the vacuum cleaner that

466
00:26:23,119 --> 00:26:25,800
Speaker 1: goes around the house or the Boston Dynamics video of

467
00:26:25,840 --> 00:26:28,639
Speaker 1: the robot doing a flip. What else is in the

468
00:26:28,680 --> 00:26:31,520
Speaker 1: portfolio that that you're serving up here that is, you know,

469
00:26:32,200 --> 00:26:36,600
Speaker 1: exciting about robotics. So so you bring up some great

470
00:26:36,600 --> 00:26:40,280
Speaker 1: examples and UM, we basically break it down into areas

471
00:26:40,840 --> 00:26:47,639
Speaker 1: including computing, processing, AI, UM, sensing, integration. UH. Robo is

472
00:26:47,760 --> 00:26:51,720
Speaker 1: very well positioned to capitalize on because of our presence

473
00:26:51,720 --> 00:26:54,800
Speaker 1: and logistics and annovation. The very fast growing world of

474
00:26:54,840 --> 00:26:58,800
Speaker 1: e commerce is on fire. UM. We've got three D printing,

475
00:26:58,880 --> 00:27:02,800
Speaker 1: we've got consumer ad US, we've got healthcare, food and agriculture.

476
00:27:02,960 --> 00:27:05,399
Speaker 1: So we're diversified across all these areas where there's some

477
00:27:05,520 --> 00:27:10,000
Speaker 1: very exciting things happening. You mentioned the some historic outflows

478
00:27:10,040 --> 00:27:13,119
Speaker 1: and yes, we do have UH inflows coming back in

479
00:27:13,320 --> 00:27:16,520
Speaker 1: and and largely tied to the strong performance. UM. You

480
00:27:16,640 --> 00:27:21,280
Speaker 1: also mentioned another one bots and UM, I'll say that, UH,

481
00:27:21,280 --> 00:27:25,520
Speaker 1: it's a totally different methodology. We have less than overlap

482
00:27:25,640 --> 00:27:29,320
Speaker 1: with that index. That strategy uses a market cap waiting

483
00:27:30,080 --> 00:27:32,840
Speaker 1: UH they have an average market cap of sixty one

484
00:27:32,880 --> 00:27:37,360
Speaker 1: billion versus robo, where we're more focused on those upcoming players.

485
00:27:37,880 --> 00:27:40,639
Speaker 1: UM are we haven't our average market cap of of

486
00:27:41,960 --> 00:27:45,800
Speaker 1: bill and so these are smaller companies, they're more up

487
00:27:45,840 --> 00:27:48,520
Speaker 1: and coming, and they're really well positioned to capitalize on

488
00:27:48,560 --> 00:27:51,800
Speaker 1: some of these things that you just mentioned UM autonomous

489
00:27:51,880 --> 00:27:58,040
Speaker 1: vehicles for example, UM uh drone capabilities. These are all

490
00:27:58,080 --> 00:28:00,600
Speaker 1: areas where we're paying close to event, close attention, and

491
00:28:00,600 --> 00:28:03,160
Speaker 1: so our advisors and so we want to make sure

492
00:28:03,160 --> 00:28:06,560
Speaker 1: that we're on the cutting edge UM and looking back

493
00:28:06,640 --> 00:28:09,600
Speaker 1: someone someone's going to say, wow, this no one had

494
00:28:09,640 --> 00:28:12,000
Speaker 1: even heard of this a few years ago, Well, chances

495
00:28:12,000 --> 00:28:13,560
Speaker 1: are we might have already had the tools and the

496
00:28:13,640 --> 00:28:17,800
Speaker 1: parts enabling that innovation already in our index. So it's

497
00:28:17,840 --> 00:28:19,760
Speaker 1: it's it's a place to be if you want to

498
00:28:19,760 --> 00:28:22,959
Speaker 1: be present before everyone else hears about it and it

499
00:28:23,000 --> 00:28:25,920
Speaker 1: becomes fully widely adopted. You know, I want to ask

500
00:28:26,119 --> 00:28:30,240
Speaker 1: um uh just about think because that's uh your your

501
00:28:30,359 --> 00:28:34,280
Speaker 1: latest launch. What's what's the strategy and the vision there? Sure,

502
00:28:34,400 --> 00:28:39,880
Speaker 1: so similar methodology fundamental analysis is deployed, and now we're

503
00:28:39,920 --> 00:28:43,040
Speaker 1: looking at a smaller group of companies UM. So we

504
00:28:43,120 --> 00:28:46,360
Speaker 1: whereas we have over e d companies with the robo

505
00:28:46,440 --> 00:28:50,040
Speaker 1: and H tech indexes E, T F, S, M, think, Tooker, TH,

506
00:28:50,280 --> 00:28:54,920
Speaker 1: H and Q has fewer than seventy I believe, and

507
00:28:55,040 --> 00:28:57,840
Speaker 1: UM and we're looking at specifically across two different areas

508
00:28:57,880 --> 00:29:01,920
Speaker 1: applications and services as well as infrastructure UM and within

509
00:29:02,000 --> 00:29:05,719
Speaker 1: that we're looking at areas such as consumer healthcare, factory automation,

510
00:29:06,320 --> 00:29:11,040
Speaker 1: cognitive computing, semiconductor, and then big data and analytics. And

511
00:29:11,120 --> 00:29:15,880
Speaker 1: specifically we're looking at companies who are using AI meaningfully

512
00:29:16,320 --> 00:29:18,520
Speaker 1: in a way that is going to drive their growth

513
00:29:18,720 --> 00:29:21,120
Speaker 1: and UM and that they're offering some sort of cutting

514
00:29:21,200 --> 00:29:25,240
Speaker 1: edge leading disruption. It can't just be that they happen

515
00:29:25,320 --> 00:29:28,640
Speaker 1: to have a i UM that's that's helping with one

516
00:29:28,680 --> 00:29:32,360
Speaker 1: of their business processes. And you know, Nina, I gotta

517
00:29:32,360 --> 00:29:35,480
Speaker 1: follow up on the Boston Dynamics. This is this company.

518
00:29:35,640 --> 00:29:37,560
Speaker 1: I don't even know, you know what else they do,

519
00:29:37,600 --> 00:29:39,880
Speaker 1: but they put out these videos that always go viral

520
00:29:40,440 --> 00:29:42,640
Speaker 1: and it's a video of a literal robot doing like

521
00:29:42,680 --> 00:29:45,800
Speaker 1: a front flip and going. One of them was opening

522
00:29:45,800 --> 00:29:49,760
Speaker 1: a dishwasher and emptying the dishes. Another one was at

523
00:29:49,760 --> 00:29:53,360
Speaker 1: a park. And sometimes they're they're either scary and exciting

524
00:29:53,360 --> 00:29:56,080
Speaker 1: at the same time. People make jokes about the terminator.

525
00:29:56,920 --> 00:29:58,800
Speaker 1: Are we going to see a world where there's like

526
00:29:58,960 --> 00:30:01,680
Speaker 1: robots like walking on the street, like you know, policemen

527
00:30:01,760 --> 00:30:05,480
Speaker 1: and things like that, Like how how much are the

528
00:30:05,560 --> 00:30:07,320
Speaker 1: robots from the movie is going to show up in

529
00:30:07,320 --> 00:30:10,200
Speaker 1: our life. So we already have robots in parts of

530
00:30:10,240 --> 00:30:13,360
Speaker 1: the world doing things that humans do in other parts

531
00:30:13,400 --> 00:30:18,280
Speaker 1: of the world. For example, UM autonomous vehicles delivering packages

532
00:30:18,720 --> 00:30:22,320
Speaker 1: UM that largely have have come in handy during the

533
00:30:22,320 --> 00:30:26,160
Speaker 1: pandemic when people couldn't get their houses. Are also robots,

534
00:30:26,200 --> 00:30:29,600
Speaker 1: like I said in factory and automation UM, which was

535
00:30:29,640 --> 00:30:33,200
Speaker 1: handy during the pandemic because they enabled the factory to

536
00:30:33,240 --> 00:30:35,600
Speaker 1: keep running without as many people having to come into work.

537
00:30:36,120 --> 00:30:38,040
Speaker 1: So what what what I think what we're going to

538
00:30:38,120 --> 00:30:42,160
Speaker 1: see more quickly adopted are the types of robots that

539
00:30:42,200 --> 00:30:44,560
Speaker 1: are used indoors. So you mentioned them in the park,

540
00:30:44,640 --> 00:30:47,720
Speaker 1: you mentioned them in the household. The ones that are indoors,

541
00:30:47,880 --> 00:30:50,760
Speaker 1: whether it's a drone or a robot or something using

542
00:30:50,760 --> 00:30:55,040
Speaker 1: sensing technology. When it's contained within four walls, it tends

543
00:30:55,080 --> 00:31:01,360
Speaker 1: to have youwer regulatory concerns UM. For example, a vacuum

544
00:31:01,400 --> 00:31:04,120
Speaker 1: cleaner UM or or if you can have one to

545
00:31:04,160 --> 00:31:07,600
Speaker 1: emptier dishwasher or to to act like a personal assistant.

546
00:31:08,040 --> 00:31:10,720
Speaker 1: We're seeing more of that because it's more contained, it's

547
00:31:10,720 --> 00:31:16,160
Speaker 1: in one little network UM, whereas something like UMV'ST. Adoption

548
00:31:16,360 --> 00:31:20,280
Speaker 1: of autonomic autonomous vehicles might take a little bit longer

549
00:31:20,360 --> 00:31:24,280
Speaker 1: because we've got traffic, We've got UM there's just the

550
00:31:24,360 --> 00:31:28,960
Speaker 1: risks around potential car accidents and consumers and their decision making.

551
00:31:29,560 --> 00:31:32,480
Speaker 1: UM it's coming, and I do believe we're going to

552
00:31:32,520 --> 00:31:34,239
Speaker 1: have a world where we're seeing more and more of it,

553
00:31:34,400 --> 00:31:37,600
Speaker 1: like the like the Jetsons. But however, I think the

554
00:31:37,600 --> 00:31:39,560
Speaker 1: ones that we're going to see a faster, more rapid

555
00:31:39,760 --> 00:31:45,080
Speaker 1: adoption would are anything that's kind of already enclosed. Okay, Nina,

556
00:31:45,160 --> 00:31:46,959
Speaker 1: I'm gonna ask you a question that I ask everybody

557
00:31:46,960 --> 00:31:49,120
Speaker 1: at the end of trillions. What's your favorite et F

558
00:31:49,160 --> 00:31:53,760
Speaker 1: tick care that isn't one that you're affiliated with. UM.

559
00:31:53,800 --> 00:31:58,000
Speaker 1: I mean, I'll throw a point over to Kathy Wood

560
00:31:58,000 --> 00:32:00,800
Speaker 1: and I'll say r G is a pretty cool strategy.

561
00:32:01,160 --> 00:32:04,160
Speaker 1: UM it is vastly diversified from ours. So that's why

562
00:32:04,200 --> 00:32:05,800
Speaker 1: I don't feel threatened by it in any way. But

563
00:32:05,840 --> 00:32:08,960
Speaker 1: if you want a little bit more tight exposure to

564
00:32:09,000 --> 00:32:13,320
Speaker 1: that genomic world exclusively and uh and and they do.

565
00:32:13,360 --> 00:32:15,880
Speaker 1: They don't have the modified equal waiting, but it's it

566
00:32:16,000 --> 00:32:17,720
Speaker 1: is definitely outperforming a lot of the E T f

567
00:32:17,800 --> 00:32:19,560
Speaker 1: that are out there and and you know, mixed are

568
00:32:19,600 --> 00:32:22,120
Speaker 1: on fire right now, so that's another interesting one to

569
00:32:22,160 --> 00:32:26,280
Speaker 1: compliment into one's portfolio. Nina Deca, thank you so much

570
00:32:26,280 --> 00:32:34,440
Speaker 1: for joining us on Trilliance, Thanks for having me, Thanks

571
00:32:34,440 --> 00:32:37,280
Speaker 1: for listening to Trillions until next time. You can find

572
00:32:37,320 --> 00:32:41,800
Speaker 1: us on the Bloomberg Terminal, Bloomberg dot com, Apple Podcasts, Spotify,

573
00:32:42,080 --> 00:32:44,280
Speaker 1: and wherever else you like to listen. We'd love to

574
00:32:44,280 --> 00:32:47,400
Speaker 1: hear from you. We're on Twitter, I'm at Joel Weber Show,

575
00:32:47,840 --> 00:32:52,240
Speaker 1: He's at Eric Faltunas, and you can find robo Global

576
00:32:52,640 --> 00:32:56,560
Speaker 1: at robot Global. This episode of Trillions was produced by

577
00:32:56,640 --> 00:33:00,560
Speaker 1: Magnus Hendrickson. Francesco Levi is the head of Bloomberg Podcasting

578
00:33:01,120 --> 00:33:01,280
Speaker 1: by