1 00:00:05,519 --> 00:00:14,080 Speaker 1: Welcome to Trillions. I'm Joel Weber and I'm Eric Beltis Eric. 2 00:00:14,640 --> 00:00:17,320 Speaker 1: I'm excited about today's guest. His name is John Hoffman. 3 00:00:17,560 --> 00:00:22,400 Speaker 1: He looks after invest Goes American E t F business 4 00:00:22,400 --> 00:00:27,000 Speaker 1: and index strategies. Why is Investo so interesting? Yeah, you know, 5 00:00:27,120 --> 00:00:29,960 Speaker 1: they're they're in the heart of the industry. They've been 6 00:00:29,960 --> 00:00:32,360 Speaker 1: around for a long time, and you know, they acquired 7 00:00:32,640 --> 00:00:36,160 Speaker 1: power Shares and they're the fourth biggest disher, so they're 8 00:00:36,600 --> 00:00:40,240 Speaker 1: you know, maybe a little less publicized because they're the 9 00:00:40,240 --> 00:00:42,839 Speaker 1: biggest outside of the big three. But they have a 10 00:00:42,840 --> 00:00:46,080 Speaker 1: three hundred and sixty three billion UM and they've taken 11 00:00:46,080 --> 00:00:48,839 Speaker 1: in twenty billion dollars this year, which again puts them 12 00:00:48,840 --> 00:00:51,919 Speaker 1: about third or fourth in flows this year. Again, those 13 00:00:51,960 --> 00:00:55,160 Speaker 1: are ridiculously big numbers for E t F s UM. 14 00:00:55,200 --> 00:00:58,400 Speaker 1: You know there it's very difficult business to to get 15 00:00:58,520 --> 00:01:01,120 Speaker 1: going in And they have two hundred and thirty three 16 00:01:01,120 --> 00:01:05,000 Speaker 1: funds and they've taken in cash in a hundred and 17 00:01:05,040 --> 00:01:07,800 Speaker 1: sixty three of them this year, which to me really 18 00:01:07,840 --> 00:01:10,959 Speaker 1: speaks at what's going on. There's a feeding frenzy in 19 00:01:11,080 --> 00:01:14,120 Speaker 1: ets this year more than any other that I've ever seen, 20 00:01:14,560 --> 00:01:17,320 Speaker 1: and that number to get that. You know, we know 21 00:01:17,400 --> 00:01:19,520 Speaker 1: they've taken money to the queues. I mean they're the 22 00:01:19,560 --> 00:01:22,039 Speaker 1: big stud blockbuster e TF You here about that are 23 00:01:22,080 --> 00:01:24,760 Speaker 1: there's you kind of know they've taken in money, but 24 00:01:24,800 --> 00:01:31,119 Speaker 1: they've hundred and sixty three including some interesting areas like commodities, uh, 25 00:01:31,480 --> 00:01:34,080 Speaker 1: the value, there's a there's a bunch of different things 26 00:01:34,120 --> 00:01:37,360 Speaker 1: that I think would be good time to just look at, 27 00:01:37,800 --> 00:01:40,800 Speaker 1: you know, what's going on this year From an issuers standpoint, 28 00:01:40,880 --> 00:01:43,959 Speaker 1: they have a great uh point of view as to 29 00:01:44,000 --> 00:01:47,000 Speaker 1: who's buying them, why and what's going on. Yeah, the 30 00:01:47,000 --> 00:01:52,080 Speaker 1: whole customer conversation is an interesting one, this time on 31 00:01:52,160 --> 00:01:58,680 Speaker 1: trillions the E T F Feeding Frenzy with Investigo's John Hoffman. John, 32 00:01:58,720 --> 00:02:01,920 Speaker 1: Welcome to Trillians. Hey Joel, Hey Eric, thanks for having 33 00:02:01,960 --> 00:02:04,320 Speaker 1: me today. Okay, So when I think of Investco, I 34 00:02:04,360 --> 00:02:07,360 Speaker 1: think of the cues Q q Q. You've got a 35 00:02:07,400 --> 00:02:10,480 Speaker 1: ton of other E T s as Eric just mentioned, Um, 36 00:02:10,680 --> 00:02:13,320 Speaker 1: two and thirty three. I think how many of those 37 00:02:13,360 --> 00:02:16,840 Speaker 1: can you name off the top of your head? You 38 00:02:16,880 --> 00:02:21,120 Speaker 1: know what? Um, that's a good question. Now, two D 39 00:02:21,200 --> 00:02:23,680 Speaker 1: and thirty would be challenging. The tickers for each one 40 00:02:23,720 --> 00:02:26,480 Speaker 1: would certainly be challenging and help. But um, I've been 41 00:02:26,520 --> 00:02:28,520 Speaker 1: here for nearly every one of these launches and so 42 00:02:28,800 --> 00:02:31,800 Speaker 1: they're all my babies, um, all of our babies. And 43 00:02:31,880 --> 00:02:34,120 Speaker 1: so I don't have a favorite. I don't have a 44 00:02:34,200 --> 00:02:37,119 Speaker 1: least favorite. Um, but that you are right, there's quite 45 00:02:37,160 --> 00:02:39,520 Speaker 1: a few and and uh and and we'll continue to 46 00:02:39,560 --> 00:02:41,960 Speaker 1: expand that as we hear from more clients about how 47 00:02:42,000 --> 00:02:44,840 Speaker 1: to help them build better portfolios. Okay, so that's a 48 00:02:44,840 --> 00:02:48,400 Speaker 1: lot of babies. And I'm curious, you know, being the 49 00:02:48,440 --> 00:02:51,480 Speaker 1: fourth biggest issuer and you have the black Rocks and 50 00:02:51,480 --> 00:02:54,400 Speaker 1: the Vanguards in the State Street and then there's a 51 00:02:54,400 --> 00:02:56,200 Speaker 1: little bit of a falloff in terms of a u 52 00:02:56,360 --> 00:02:58,640 Speaker 1: M before you get to investco And I'm curious, how 53 00:02:58,639 --> 00:03:03,960 Speaker 1: do you guys think about eating with that big three? Yeah, 54 00:03:04,000 --> 00:03:05,919 Speaker 1: so this is a question. It's an interesting questions when 55 00:03:05,960 --> 00:03:07,560 Speaker 1: we get a lot and you know, I think that 56 00:03:07,680 --> 00:03:11,720 Speaker 1: we've been incredibly deliberate and intentional intentional uh as as 57 00:03:11,720 --> 00:03:14,160 Speaker 1: it relates to our product design and development and who 58 00:03:14,240 --> 00:03:16,880 Speaker 1: we are in the market. Um, you know, in a 59 00:03:16,880 --> 00:03:19,919 Speaker 1: lot of ways, we've really carved out and built and 60 00:03:19,960 --> 00:03:22,359 Speaker 1: pioneered the you know what what today is referred to 61 00:03:22,440 --> 00:03:25,400 Speaker 1: as the smart beta category. UM, we do things in 62 00:03:25,480 --> 00:03:28,640 Speaker 1: beta as well, but our core competency and really what 63 00:03:28,680 --> 00:03:32,160 Speaker 1: we invented and pioneered was this idea of smart beta. 64 00:03:32,200 --> 00:03:34,600 Speaker 1: Again today we all call it smart beta. UM, I 65 00:03:34,639 --> 00:03:36,720 Speaker 1: can tell you back in the early two thousand's when 66 00:03:36,720 --> 00:03:40,200 Speaker 1: I was talking with clients, that terminology didn't even exist. 67 00:03:40,280 --> 00:03:41,760 Speaker 1: And so if you go, Joe, I think all the 68 00:03:41,800 --> 00:03:44,080 Speaker 1: way back to the beginning, which is, um, you know 69 00:03:44,120 --> 00:03:46,280 Speaker 1: where we still are today in terms of how we 70 00:03:46,320 --> 00:03:49,080 Speaker 1: think about the business. We thought that the E t 71 00:03:49,240 --> 00:03:52,880 Speaker 1: F was a tremendous you know, delivery vehicle for investment 72 00:03:52,880 --> 00:03:55,040 Speaker 1: purposes for all the reasons that everybody knows today. Their 73 00:03:55,080 --> 00:03:58,480 Speaker 1: low cost, they're transparent, tax efficient, These things rattle off 74 00:03:58,480 --> 00:04:01,840 Speaker 1: of everybody's tongue today. Twenty years ago, you know, that 75 00:04:01,960 --> 00:04:04,480 Speaker 1: was still a new idea. But our idea was, let's 76 00:04:04,520 --> 00:04:09,040 Speaker 1: take that benefit rich delivery vehicle, the vehicle for delivering 77 00:04:09,080 --> 00:04:13,360 Speaker 1: investment returns, and let's track in disease that are actually 78 00:04:13,400 --> 00:04:16,280 Speaker 1: built to be investable. And that was the combination that 79 00:04:16,320 --> 00:04:19,080 Speaker 1: we put together, which was new at the time. Today 80 00:04:19,120 --> 00:04:21,840 Speaker 1: it's it's well known and well called, you know, are 81 00:04:21,880 --> 00:04:25,080 Speaker 1: documented as smart Beta, but that's what we were born on. 82 00:04:25,600 --> 00:04:27,880 Speaker 1: That's what we pioneer, that's what we invented. And it's 83 00:04:27,920 --> 00:04:32,760 Speaker 1: all about providing investors better ways to invest. And and 84 00:04:32,760 --> 00:04:35,680 Speaker 1: and Joel, I think about you know, the first index 85 00:04:36,279 --> 00:04:38,680 Speaker 1: was built in the eighteen nineties, right, I mean people 86 00:04:38,680 --> 00:04:41,840 Speaker 1: are driving Model T forwards back in this time per day. 87 00:04:41,839 --> 00:04:44,760 Speaker 1: It might even be before the Model T forward fast 88 00:04:44,760 --> 00:04:47,479 Speaker 1: forward to today. Um. You know, nineteen fifties you had 89 00:04:47,520 --> 00:04:50,919 Speaker 1: the SMP five index. Come all the way today you 90 00:04:51,000 --> 00:04:55,360 Speaker 1: have better technology, more data, more insights. And our idea 91 00:04:55,360 --> 00:04:59,200 Speaker 1: was take all of that advanced technology and partner it 92 00:04:59,240 --> 00:05:03,600 Speaker 1: with a benefit rich vehicle for delivery. Combine that beneficial 93 00:05:03,640 --> 00:05:07,320 Speaker 1: attributes of active management and passive and deliver them in 94 00:05:07,360 --> 00:05:11,640 Speaker 1: this new digital format. And that technology, um is as 95 00:05:11,640 --> 00:05:14,279 Speaker 1: relevant today as it was fifteen years ago. And that's 96 00:05:14,279 --> 00:05:17,680 Speaker 1: how we've really you know, carved our our core focus, 97 00:05:18,160 --> 00:05:21,200 Speaker 1: if you will, from a product development and more importantly 98 00:05:21,400 --> 00:05:24,800 Speaker 1: from a client experienced perspective. Yeah, and that's UM something 99 00:05:24,839 --> 00:05:27,000 Speaker 1: that we see. Uh. You know, I always say you 100 00:05:27,000 --> 00:05:29,160 Speaker 1: could put Mickey Mantle Rookie cards in an e t 101 00:05:29,360 --> 00:05:31,760 Speaker 1: F and it would probably be the best possible way 102 00:05:31,880 --> 00:05:34,560 Speaker 1: to trade Mickey mantle rookie cards, which is why we're 103 00:05:34,640 --> 00:05:38,520 Speaker 1: very pro bitcoin ETF. We've seen everything thrown in there, China, 104 00:05:38,560 --> 00:05:42,039 Speaker 1: a shares, active, just pure active smart beta themes. It 105 00:05:42,120 --> 00:05:46,520 Speaker 1: really is a amazing structure now that is known. And 106 00:05:46,600 --> 00:05:48,680 Speaker 1: you know et has been taking in money every year 107 00:05:48,760 --> 00:05:52,960 Speaker 1: for uh two decades. So this year though, it's gotten insane. 108 00:05:53,040 --> 00:05:56,320 Speaker 1: Right that ets typically take in about two billion a day. 109 00:05:56,360 --> 00:05:59,440 Speaker 1: This year they've taken in four billion a day. And 110 00:05:59,560 --> 00:06:03,599 Speaker 1: I guess I'm just curious, what's going on? Why is 111 00:06:03,680 --> 00:06:06,520 Speaker 1: there such an uptick in money coming in this year? 112 00:06:06,520 --> 00:06:10,279 Speaker 1: What's your take on that? Yeah, so again i'd widen 113 00:06:10,320 --> 00:06:12,480 Speaker 1: out the lens, right. The e t F is a technology. 114 00:06:12,520 --> 00:06:17,279 Speaker 1: It's a technological innovation for delivering investment returns and it's 115 00:06:17,360 --> 00:06:20,960 Speaker 1: it's perfectly it's very you know, great design. Um, when 116 00:06:20,960 --> 00:06:24,320 Speaker 1: you think about great design and simplicity, um, you know, 117 00:06:24,360 --> 00:06:27,280 Speaker 1: think about the Google Search interface, one little bar. You know, 118 00:06:27,360 --> 00:06:30,680 Speaker 1: they've done an incredible job keeping that simple. I think 119 00:06:30,680 --> 00:06:33,520 Speaker 1: about the iPhone and how easy it is to use. 120 00:06:33,600 --> 00:06:37,279 Speaker 1: You know, my kids can unlock my iPhone and take pictures. Um, 121 00:06:37,320 --> 00:06:39,839 Speaker 1: you know, it's just intuitive. And so this is the 122 00:06:39,880 --> 00:06:44,279 Speaker 1: e t F represents a disruptive technology and innovation. I 123 00:06:44,320 --> 00:06:46,400 Speaker 1: think that you know, we go back thirty years, or 124 00:06:46,480 --> 00:06:49,279 Speaker 1: you think of the time horizon, it's still in its 125 00:06:49,279 --> 00:06:52,279 Speaker 1: early stages when you think of this, not in time 126 00:06:52,600 --> 00:06:55,680 Speaker 1: or in assets, but in network effects. And so we 127 00:06:55,720 --> 00:06:59,279 Speaker 1: think about you know, not necessarily um that the growth 128 00:06:59,279 --> 00:07:04,400 Speaker 1: more recently over this long horizon ten distinct network effects 129 00:07:04,440 --> 00:07:07,080 Speaker 1: that are playing out in the E t F segment. 130 00:07:07,200 --> 00:07:09,800 Speaker 1: And network effects is really just a fancy way of saying, 131 00:07:10,120 --> 00:07:13,320 Speaker 1: the more people that use a service, the more valuable 132 00:07:13,560 --> 00:07:16,280 Speaker 1: you know, the service is. Right. I use the analogy 133 00:07:16,280 --> 00:07:18,480 Speaker 1: of Uber. Right, if there's one car on the Uber 134 00:07:18,520 --> 00:07:22,320 Speaker 1: network and you push the button, um, it's not very useful. 135 00:07:22,320 --> 00:07:24,480 Speaker 1: When there's ten thousand a million, when there's a car 136 00:07:24,520 --> 00:07:28,240 Speaker 1: at every corner, that network is very, very useful and powerful. 137 00:07:28,560 --> 00:07:30,960 Speaker 1: And what we're seeing, Eric is is this network effect 138 00:07:31,040 --> 00:07:33,600 Speaker 1: play out in e t F s. We're still in 139 00:07:33,680 --> 00:07:36,480 Speaker 1: some of the mid stages of these network effects, things 140 00:07:36,480 --> 00:07:40,600 Speaker 1: like model portfolios, the growth of retail, you know, self directed. 141 00:07:41,000 --> 00:07:46,200 Speaker 1: But it's really about this incredibly efficient technology for delivering 142 00:07:46,440 --> 00:07:49,960 Speaker 1: investment returns. That's that's powering this growth. And every time 143 00:07:49,960 --> 00:07:52,800 Speaker 1: we have a disruptive event, Um, you know, think back 144 00:07:52,840 --> 00:07:55,680 Speaker 1: to two thousand, two thousand and eight. Coming out of 145 00:07:55,680 --> 00:07:59,000 Speaker 1: oh eight, the E t F product grew significantly. Coming 146 00:07:59,000 --> 00:08:02,240 Speaker 1: out of two thousand, the product grew significantly. As we 147 00:08:02,280 --> 00:08:05,240 Speaker 1: come through the pandemic. You know, money has moved out 148 00:08:05,280 --> 00:08:08,520 Speaker 1: of older structures and it's coming into new and so 149 00:08:08,640 --> 00:08:10,320 Speaker 1: you know, yes, it's it's a trend that I think 150 00:08:10,360 --> 00:08:12,720 Speaker 1: people are looking at today. Uh. You know that the 151 00:08:12,800 --> 00:08:15,600 Speaker 1: numbers are staggering. We're on pace for a trillion dollars 152 00:08:15,600 --> 00:08:18,160 Speaker 1: of inflows here in the US. But this is really 153 00:08:18,200 --> 00:08:21,960 Speaker 1: just a continuation of a trend that's been in motion 154 00:08:22,040 --> 00:08:24,440 Speaker 1: for quite some time. And you know, we think a 155 00:08:24,440 --> 00:08:28,600 Speaker 1: lot about the big macro trends that are powering this 156 00:08:29,240 --> 00:08:32,000 Speaker 1: and those haven't changed. Right when you think about the 157 00:08:32,640 --> 00:08:35,960 Speaker 1: move to fiduciary, when you think about the move from 158 00:08:36,280 --> 00:08:38,960 Speaker 1: active investing to passive, which again we think the words 159 00:08:38,960 --> 00:08:44,040 Speaker 1: are wrong. They're almost all investors are are active investors. Uh. 160 00:08:44,120 --> 00:08:48,520 Speaker 1: You know some of these trends around regulation, um, technological innovation. 161 00:08:48,840 --> 00:08:52,079 Speaker 1: This industry is going to change more in the next 162 00:08:52,160 --> 00:08:55,760 Speaker 1: five years than it has in the past fifty. And 163 00:08:55,800 --> 00:08:59,960 Speaker 1: it's just an acceleration of continuation of this trend around 164 00:09:00,400 --> 00:09:04,640 Speaker 1: better technology for driving investment returns. One of the lanes 165 00:09:04,880 --> 00:09:07,640 Speaker 1: that we find opening up more in terms of people 166 00:09:07,720 --> 00:09:10,920 Speaker 1: using e t F s is the direct do it 167 00:09:10,920 --> 00:09:14,160 Speaker 1: yourself retail investor, and a strand of that is the 168 00:09:14,240 --> 00:09:20,000 Speaker 1: sort of like yolo retail trader type, and where you 169 00:09:20,040 --> 00:09:23,200 Speaker 1: really get to meet them is on TikTok. They make 170 00:09:23,320 --> 00:09:26,200 Speaker 1: some there's some wild videos on there. It's really if 171 00:09:26,200 --> 00:09:28,439 Speaker 1: you just type in an e t F hashtag, you'll 172 00:09:28,440 --> 00:09:31,000 Speaker 1: find some fun stuff on there, some more serious, some 173 00:09:31,360 --> 00:09:34,960 Speaker 1: just downright and saying, um, you have an interesting story 174 00:09:35,040 --> 00:09:37,960 Speaker 1: here about s pH D and the power of TikTok. 175 00:09:38,240 --> 00:09:41,880 Speaker 1: Can you go over that? So we're talking about TikTok here, 176 00:09:41,880 --> 00:09:45,400 Speaker 1: all right? Um, So I would start with, you know 177 00:09:45,440 --> 00:09:48,120 Speaker 1: this idea that what's driving this this direct market growth. 178 00:09:48,240 --> 00:09:51,520 Speaker 1: You know, there's a huge macro factor here of of 179 00:09:51,840 --> 00:09:56,160 Speaker 1: commissionless trading, commission free trading, which is reduced the frictions 180 00:09:56,240 --> 00:09:59,120 Speaker 1: to to transacting and so eric to your point, we 181 00:09:59,240 --> 00:10:03,120 Speaker 1: have seen really significant growth in this segment, and as 182 00:10:03,120 --> 00:10:06,200 Speaker 1: we unpacked the segment and see what drives the behaviors, 183 00:10:06,440 --> 00:10:09,960 Speaker 1: we are finding some very interesting elements of influence. One 184 00:10:10,000 --> 00:10:12,600 Speaker 1: of our more obscure tickers at the time had a 185 00:10:12,720 --> 00:10:16,240 Speaker 1: really high ownership on robin Hood, and as we looked 186 00:10:16,280 --> 00:10:20,240 Speaker 1: at the disproportionate ownership in robin Hood, what we attributed 187 00:10:20,280 --> 00:10:23,559 Speaker 1: it back to. What we found was a TikTok video 188 00:10:24,120 --> 00:10:27,880 Speaker 1: from an investor or a client that was putting forth 189 00:10:27,920 --> 00:10:31,720 Speaker 1: a strategy to hold this particular e t f UM 190 00:10:31,800 --> 00:10:33,800 Speaker 1: for a period of time, and we saw that video 191 00:10:33,840 --> 00:10:37,120 Speaker 1: go from a thousand hits to five thousand to fifty. 192 00:10:37,120 --> 00:10:40,240 Speaker 1: It ultimately had over half a million views, and the 193 00:10:40,240 --> 00:10:44,680 Speaker 1: correlation of account openings and transaction UH data on some 194 00:10:44,760 --> 00:10:48,800 Speaker 1: of the underlying platforms was really indicative of how powerful 195 00:10:49,080 --> 00:10:52,960 Speaker 1: all of these other mediums are around buying decisions and 196 00:10:53,000 --> 00:10:56,520 Speaker 1: asset flows in e t FS, something that again traditionally 197 00:10:57,200 --> 00:11:00,840 Speaker 1: was not our core focus, but increasingly is important to 198 00:11:00,920 --> 00:11:10,920 Speaker 1: understand the drivers of flows. Let's get into some tickers here, 199 00:11:10,960 --> 00:11:13,480 Speaker 1: because you know, I think they can be representative what's 200 00:11:13,520 --> 00:11:16,040 Speaker 1: going on. So in my opinion on the two to four, 201 00:11:16,080 --> 00:11:19,960 Speaker 1: I get the whole transformative technology. I think that's good 202 00:11:19,960 --> 00:11:23,120 Speaker 1: for two billion. I think the four is because the 203 00:11:23,160 --> 00:11:25,719 Speaker 1: market has breadth this year, and by breath I mean 204 00:11:25,840 --> 00:11:29,640 Speaker 1: small caps, value, international commodities, a lot of these left 205 00:11:29,640 --> 00:11:32,480 Speaker 1: behind places have been working for most of the year, 206 00:11:32,559 --> 00:11:35,480 Speaker 1: not the past month so much. But RSP is a 207 00:11:35,520 --> 00:11:37,480 Speaker 1: great example. So this is your equal weight at e 208 00:11:37,559 --> 00:11:40,080 Speaker 1: t F this year. It's your best selling e TF 209 00:11:40,600 --> 00:11:43,400 Speaker 1: better than the cues. And to me, the cues probably 210 00:11:43,400 --> 00:11:46,000 Speaker 1: defined last year. RSP this year it has more value 211 00:11:46,400 --> 00:11:49,720 Speaker 1: slate tilts of smaller companies, UM, and I want to 212 00:11:49,760 --> 00:11:52,959 Speaker 1: ask you about RSP. It's so simply just equate the SMP. 213 00:11:53,320 --> 00:11:55,120 Speaker 1: When I go to the money Show and interact with 214 00:11:55,240 --> 00:11:58,720 Speaker 1: direct retail investors, it's weird. I love hearing their questions 215 00:11:58,720 --> 00:12:01,760 Speaker 1: and I do get asked about equal eating a lot UM, 216 00:12:01,800 --> 00:12:05,200 Speaker 1: I guess. Just talk to me about what are people 217 00:12:05,240 --> 00:12:08,000 Speaker 1: buying here? What do you think of RSP? Like, how 218 00:12:08,040 --> 00:12:10,760 Speaker 1: are how are they using it? Are they replacing like 219 00:12:10,800 --> 00:12:12,600 Speaker 1: a voo or is this like a trade when I 220 00:12:12,600 --> 00:12:15,080 Speaker 1: say who, I mean, like a Vanguard five hundred or 221 00:12:15,080 --> 00:12:16,600 Speaker 1: is this like a trade where you add a little 222 00:12:16,679 --> 00:12:19,400 Speaker 1: RSP on top of your portfolio for a little juice 223 00:12:19,400 --> 00:12:22,439 Speaker 1: and then you trade out of it. So, Eric, I 224 00:12:22,480 --> 00:12:24,120 Speaker 1: think this gets right to the core of who we 225 00:12:24,160 --> 00:12:26,840 Speaker 1: are right and first off, we we believe in long 226 00:12:26,960 --> 00:12:31,160 Speaker 1: term investing. UM. And when you think about that, construct 227 00:12:31,600 --> 00:12:36,320 Speaker 1: our idea of providing you know, better return patterns and 228 00:12:36,320 --> 00:12:40,400 Speaker 1: and creating methodology that's more efficient. Let's take RSP as 229 00:12:40,400 --> 00:12:42,120 Speaker 1: the example or what is this? Is it a trade? 230 00:12:42,160 --> 00:12:44,480 Speaker 1: Is a short term? What are we looking at? So 231 00:12:44,520 --> 00:12:47,520 Speaker 1: it is simple. It equally waits the security, incredibly simple. 232 00:12:47,559 --> 00:12:51,040 Speaker 1: All five securities the SMP five received the same way. 233 00:12:51,120 --> 00:12:53,360 Speaker 1: What does it do? What it does is it provide 234 00:12:53,360 --> 00:12:57,000 Speaker 1: a more balanced exposure to the SMP five hundred. And 235 00:12:57,040 --> 00:12:59,959 Speaker 1: why have we seen it this year? Accelerate the SMP 236 00:13:00,080 --> 00:13:03,680 Speaker 1: five hundred. The top ten names right now have nearly 237 00:13:03,720 --> 00:13:07,200 Speaker 1: a thirty percent concentration, so you're getting, you know, a 238 00:13:07,320 --> 00:13:12,400 Speaker 1: very concentrated exposure to some large cap names um which 239 00:13:12,400 --> 00:13:13,880 Speaker 1: again a lot of the return is going to be 240 00:13:13,960 --> 00:13:17,480 Speaker 1: driven by those big, big stocks, right, those big companies. 241 00:13:17,840 --> 00:13:20,400 Speaker 1: What RSP does is provides you a little bit more 242 00:13:20,400 --> 00:13:24,120 Speaker 1: exposure to the size premium in the market. So it's 243 00:13:24,120 --> 00:13:27,040 Speaker 1: tilting a little bit more towards small cap right, which 244 00:13:27,080 --> 00:13:32,160 Speaker 1: again is a differentiated and rewarded return pattern. It's also 245 00:13:32,559 --> 00:13:35,360 Speaker 1: taking advantage of the value factor, so it's going to 246 00:13:35,440 --> 00:13:38,360 Speaker 1: tip a little bit more towards the value spectrum and 247 00:13:38,440 --> 00:13:40,640 Speaker 1: so we don't look at this over you know, a 248 00:13:40,760 --> 00:13:43,160 Speaker 1: day or a week or a month. We believe that 249 00:13:43,280 --> 00:13:47,960 Speaker 1: RSP can provide a very efficient core US equity exposure. 250 00:13:48,240 --> 00:13:50,559 Speaker 1: And to the tickers that you've referenced, that that broader 251 00:13:50,679 --> 00:13:53,560 Speaker 1: SMP five hundred exposures, you know, those are nearly a 252 00:13:53,600 --> 00:13:55,760 Speaker 1: trillion dollars in a u M when you add them 253 00:13:55,840 --> 00:13:58,600 Speaker 1: up right, And what we're finding is that clients are 254 00:13:58,600 --> 00:14:03,720 Speaker 1: looking to um ultimately balance their concentration a bit more 255 00:14:03,960 --> 00:14:07,520 Speaker 1: in the index, diversify a little bit differently. And that's 256 00:14:07,520 --> 00:14:10,240 Speaker 1: why this year, you know, we've seen significant flows there 257 00:14:10,520 --> 00:14:13,880 Speaker 1: and now I think RSP is the largest smart beta 258 00:14:14,120 --> 00:14:17,240 Speaker 1: e t F in the US market. You know, another 259 00:14:17,320 --> 00:14:19,720 Speaker 1: theme from this year that I'm really interested in talking 260 00:14:19,760 --> 00:14:22,920 Speaker 1: with you about has been the commodities boom. And you 261 00:14:22,960 --> 00:14:26,640 Speaker 1: all have a huge foothold in commodities, but specifically sort 262 00:14:26,640 --> 00:14:30,120 Speaker 1: of in commodity futures, and so I'm wondering how you 263 00:14:30,160 --> 00:14:33,760 Speaker 1: approached that because outside of basically the g l D 264 00:14:33,920 --> 00:14:36,080 Speaker 1: s of the world, you guys are basically the biggest 265 00:14:36,160 --> 00:14:39,240 Speaker 1: name name there. But but why focus on futures instead 266 00:14:39,240 --> 00:14:42,240 Speaker 1: of more of an equity play. Sure, so when we 267 00:14:42,360 --> 00:14:45,040 Speaker 1: entered the commodity space in the mid two thousand's. We 268 00:14:45,120 --> 00:14:47,640 Speaker 1: looked at what was already in the market, and you know, 269 00:14:47,680 --> 00:14:51,160 Speaker 1: there were some some great physical based capability and what 270 00:14:51,240 --> 00:14:55,760 Speaker 1: we saw was an opportunity to pioneer the future segment 271 00:14:56,240 --> 00:14:57,720 Speaker 1: UM and what I mean by that is, you know, 272 00:14:57,720 --> 00:14:59,880 Speaker 1: there were other futures products in the market, you know, 273 00:15:00,000 --> 00:15:02,600 Speaker 1: et f s buying futures. What we did was we 274 00:15:02,600 --> 00:15:05,760 Speaker 1: went back to our core DNA, which is about building 275 00:15:05,920 --> 00:15:09,640 Speaker 1: enhanced you know, strategies, and so we applied We partnered 276 00:15:09,640 --> 00:15:12,800 Speaker 1: with Deutsche Bank in this lineup in the mid two thousand's, 277 00:15:13,280 --> 00:15:16,720 Speaker 1: and we actually utilize an intelligent index. So the index 278 00:15:17,040 --> 00:15:20,360 Speaker 1: looks at the shape of the futures curve and identifies 279 00:15:20,600 --> 00:15:24,000 Speaker 1: where to roll futures kind of like a manager would, uh, 280 00:15:24,040 --> 00:15:26,760 Speaker 1: you know, and in a more active fund, identifying the 281 00:15:26,800 --> 00:15:30,600 Speaker 1: most opportune place to roll forward those futures. And so 282 00:15:30,680 --> 00:15:35,640 Speaker 1: DBC was our flagship product there broad commodity exposure. We 283 00:15:35,720 --> 00:15:38,680 Speaker 1: then expanded on that and got to the individual sectors 284 00:15:38,800 --> 00:15:42,080 Speaker 1: d B A and agriculture d B O and oil 285 00:15:42,680 --> 00:15:45,760 Speaker 1: UM And as we continued to iterate and work with clients, 286 00:15:46,040 --> 00:15:49,360 Speaker 1: one of the opportunities we found was a way to 287 00:15:49,480 --> 00:15:52,840 Speaker 1: deliver this without a K one, and so we created 288 00:15:52,920 --> 00:15:56,960 Speaker 1: p DBC, which is a very similar product to DBC 289 00:15:57,600 --> 00:16:01,600 Speaker 1: holding futures, but it had a structure that enables us 290 00:16:01,600 --> 00:16:05,200 Speaker 1: to pass through a TONE nine instead of a K one. Again, 291 00:16:05,400 --> 00:16:08,520 Speaker 1: there's tradeoffs and benefits of each of these structures. In 292 00:16:08,520 --> 00:16:10,720 Speaker 1: this instance, that's what we were solving for. And now 293 00:16:10,840 --> 00:16:13,760 Speaker 1: that's a uh, you know, a six billion dollar fund 294 00:16:14,160 --> 00:16:18,440 Speaker 1: um providing you know, a broad exposure to commodities, which 295 00:16:18,720 --> 00:16:21,040 Speaker 1: you know Joel. In this idea of long term investing, 296 00:16:21,560 --> 00:16:25,640 Speaker 1: what we see is model portfolio builders you know, attracted 297 00:16:25,720 --> 00:16:30,120 Speaker 1: to the correlation properties of commodities and so you know, 298 00:16:30,280 --> 00:16:32,480 Speaker 1: Eric would probably ask is this a short term trade? 299 00:16:32,960 --> 00:16:36,880 Speaker 1: I would argue that a well constructed portfolio is going 300 00:16:36,920 --> 00:16:41,720 Speaker 1: to find you know, value in a correlation pattern that's 301 00:16:41,800 --> 00:16:44,640 Speaker 1: different than stocks and bonds. Uh. And so we think 302 00:16:44,640 --> 00:16:46,920 Speaker 1: that in many ways this is an allocation in a 303 00:16:46,960 --> 00:16:52,160 Speaker 1: long term asset allocation. Yeah, certainly. And I think the 304 00:16:52,280 --> 00:16:56,280 Speaker 1: one thing with these commodity futures et s and we 305 00:16:56,320 --> 00:16:58,200 Speaker 1: have a traffic light system and we do give them 306 00:16:58,200 --> 00:17:00,840 Speaker 1: a red light although the system and saying it's good 307 00:17:00,920 --> 00:17:03,200 Speaker 1: or bad it's it's most like movie ratings, like, hey, 308 00:17:03,200 --> 00:17:04,960 Speaker 1: this is this is kind of like a rated R 309 00:17:05,359 --> 00:17:08,120 Speaker 1: E T F. And the reason we say that simply 310 00:17:08,280 --> 00:17:12,080 Speaker 1: is because of rolling futures. When you roll futures, you 311 00:17:12,119 --> 00:17:14,560 Speaker 1: tend to pay more for the next month than the 312 00:17:14,600 --> 00:17:17,560 Speaker 1: month you just sold because people know that you don't 313 00:17:17,600 --> 00:17:20,280 Speaker 1: want to get delivery of oil to your health. So 314 00:17:20,320 --> 00:17:24,320 Speaker 1: the storage costs are kind of baked into this roll cost. 315 00:17:24,359 --> 00:17:26,200 Speaker 1: So I'm not saying you could do it any better 316 00:17:26,200 --> 00:17:28,440 Speaker 1: if you trade the futures on your own, but there 317 00:17:28,560 --> 00:17:31,280 Speaker 1: is it's not really seeing the expense ratio. Do you 318 00:17:31,320 --> 00:17:34,040 Speaker 1: try to like warn clients of this or how do 319 00:17:34,080 --> 00:17:38,399 Speaker 1: you explain canentango and this idea of rolling futures because 320 00:17:38,920 --> 00:17:41,000 Speaker 1: in some of them, like oil in particular, it can 321 00:17:41,040 --> 00:17:44,840 Speaker 1: be a pretty hefty cost over the years. Now it 322 00:17:44,920 --> 00:17:47,879 Speaker 1: could go opposite and actually benefit you when there's a 323 00:17:47,960 --> 00:17:50,280 Speaker 1: rush for commodities. I get that that's more like a 324 00:17:50,320 --> 00:17:53,560 Speaker 1: full moon I think normal circumstances, though, is you do 325 00:17:53,640 --> 00:17:56,919 Speaker 1: pay for the role? Yeah, Eric, You're spot on, And 326 00:17:56,960 --> 00:17:59,240 Speaker 1: that's actually what the product is designed to do is 327 00:17:59,359 --> 00:18:03,600 Speaker 1: optimize is that role. So it has rules built into 328 00:18:03,640 --> 00:18:06,320 Speaker 1: the index to look at the shape, so to get 329 00:18:06,400 --> 00:18:10,720 Speaker 1: very granular and specific, it looks at the particular curves. 330 00:18:10,720 --> 00:18:13,040 Speaker 1: So let's say we're in oil and we're going to 331 00:18:13,160 --> 00:18:16,520 Speaker 1: roll a contract. It's going to calculate the implied roll 332 00:18:16,600 --> 00:18:19,359 Speaker 1: yield on the next thirteen months, and then it's going 333 00:18:19,440 --> 00:18:21,919 Speaker 1: to select the place on the curve that would be 334 00:18:21,960 --> 00:18:24,880 Speaker 1: the most optimal to roll um. And if you think 335 00:18:24,920 --> 00:18:28,080 Speaker 1: about the first generation of futures based commodity products, they 336 00:18:28,080 --> 00:18:31,119 Speaker 1: did exactly what you said. They statically rolled every month 337 00:18:31,320 --> 00:18:34,159 Speaker 1: front month, you know, regardless of the shape of the curve. 338 00:18:34,560 --> 00:18:36,399 Speaker 1: And what we did was we said, hey, hold on 339 00:18:36,440 --> 00:18:39,439 Speaker 1: a second, there might be a more intelligent way to 340 00:18:39,600 --> 00:18:43,640 Speaker 1: do this by using a basic algorithm that calculates roll 341 00:18:43,760 --> 00:18:47,040 Speaker 1: yield um and identifies the place to to to roll 342 00:18:47,080 --> 00:18:49,080 Speaker 1: onto the curve. And eric, that's what we've been doing 343 00:18:49,480 --> 00:18:51,840 Speaker 1: in all of our products. It's you know, it's not 344 00:18:51,960 --> 00:18:56,120 Speaker 1: about um. You know, the each one has its own 345 00:18:56,160 --> 00:19:00,240 Speaker 1: design um to take a little bit of intelligence. Will 346 00:19:00,240 --> 00:19:05,440 Speaker 1: be an index, right, it's passively managed index based rules methodology, 347 00:19:05,600 --> 00:19:08,600 Speaker 1: but put a little bit of intelligence into the product 348 00:19:09,160 --> 00:19:12,000 Speaker 1: to create a better outcome in again, you know, will 349 00:19:12,000 --> 00:19:15,359 Speaker 1: these outperform in every market? Absolutely? Not right. There will 350 00:19:15,400 --> 00:19:18,320 Speaker 1: be periods of underperformance. But what we're hired to do 351 00:19:18,760 --> 00:19:23,400 Speaker 1: is provide the return pattern to clients for that particular index. 352 00:19:23,600 --> 00:19:25,680 Speaker 1: And that's what we do, you know, really really well. 353 00:19:26,800 --> 00:19:29,120 Speaker 1: CUT is your is your wood E t F right, 354 00:19:29,480 --> 00:19:33,320 Speaker 1: which you know is much more friendly. Let's call it 355 00:19:33,440 --> 00:19:37,520 Speaker 1: UM since it's it's a PG rated UM et F 356 00:19:37,560 --> 00:19:40,119 Speaker 1: and in the stop light system. So how do you 357 00:19:40,160 --> 00:19:42,000 Speaker 1: how do you think about being such a big name 358 00:19:42,000 --> 00:19:45,800 Speaker 1: in commodities but then basically having different tools for different people. 359 00:19:45,840 --> 00:19:49,199 Speaker 1: I guess yeah, I would draw the parallel to you know, 360 00:19:49,280 --> 00:19:53,639 Speaker 1: microprocessors in a computer, right, we create these microprocessors that 361 00:19:53,720 --> 00:19:57,760 Speaker 1: provide return patterns to clients. CUT is providing the return 362 00:19:57,840 --> 00:20:02,000 Speaker 1: pattern of the equities UM in the timber market. If 363 00:20:02,000 --> 00:20:04,600 Speaker 1: you want to buy timber directly, UM, you know, there's 364 00:20:04,640 --> 00:20:06,840 Speaker 1: ETFs that hold those futures. If you want to get 365 00:20:06,880 --> 00:20:10,399 Speaker 1: closer to the eggs and and the underlying UM you know, 366 00:20:10,840 --> 00:20:14,119 Speaker 1: grains and metals, we can provide that exposure as well. 367 00:20:14,520 --> 00:20:19,399 Speaker 1: So CUT is a basket of securities that are focused 368 00:20:19,920 --> 00:20:23,639 Speaker 1: in that particular market. It's the equity exposure, uh, you know, 369 00:20:23,720 --> 00:20:27,240 Speaker 1: not necessarily the futures exposure and so again, Joel, I 370 00:20:27,280 --> 00:20:32,000 Speaker 1: think it's about providing more return patterns to clients. You know, 371 00:20:32,040 --> 00:20:35,760 Speaker 1: we get this question, is there the rise of the thematics? Right? 372 00:20:36,000 --> 00:20:38,520 Speaker 1: I think that this is really about UM, you know, 373 00:20:38,640 --> 00:20:41,280 Speaker 1: or the rise of smart beta or some iteration of that. 374 00:20:41,640 --> 00:20:45,359 Speaker 1: This is really about the evolution of technology. The reason 375 00:20:45,440 --> 00:20:50,040 Speaker 1: why the Dow Jones Industrial Average is price weighted is 376 00:20:50,040 --> 00:20:52,080 Speaker 1: because that was the only way you could calculate it 377 00:20:52,119 --> 00:20:55,760 Speaker 1: every day in nineteen hundred. Right today, we can calculate 378 00:20:55,840 --> 00:20:59,560 Speaker 1: things more efficiently with technology, and it's enabled us to 379 00:20:59,640 --> 00:21:03,600 Speaker 1: carve all the return patterns more precisely. And that's really 380 00:21:03,600 --> 00:21:08,040 Speaker 1: what we're focused on, is precision over return patterns UM 381 00:21:08,160 --> 00:21:14,440 Speaker 1: using modern technology wrapped inside of a very efficient delivery mechanism. Yeah. Actually, 382 00:21:14,480 --> 00:21:17,080 Speaker 1: it's funny you say the rise of thematics. We've tried. 383 00:21:17,119 --> 00:21:20,680 Speaker 1: We've really distilled this down into into two buckets, cheap 384 00:21:20,760 --> 00:21:25,320 Speaker 1: beta or dirt cheap and shiny objects UM, and I 385 00:21:25,320 --> 00:21:31,000 Speaker 1: would put thematics are commodities things that are just happening UM, 386 00:21:31,040 --> 00:21:33,520 Speaker 1: but not happening a little, not like outperforming the SMP 387 00:21:33,640 --> 00:21:37,080 Speaker 1: by one percent like the old days, but literally crushing 388 00:21:37,119 --> 00:21:40,119 Speaker 1: it UM or providing something very unique. And that leads 389 00:21:40,119 --> 00:21:42,680 Speaker 1: me to another area that I want to ask you about, 390 00:21:42,680 --> 00:21:48,399 Speaker 1: which is crypto. And look, there's now fifteen issuers that 391 00:21:48,440 --> 00:21:51,920 Speaker 1: have filed for crypto, including some big, bigger names like 392 00:21:52,040 --> 00:21:56,080 Speaker 1: van Neck, your competitor, Fidelity. Are you guys considering getting 393 00:21:56,240 --> 00:21:59,560 Speaker 1: getting involved in this, because if you're a leader in commodities, 394 00:22:00,040 --> 00:22:01,800 Speaker 1: you know, outside of g l D and i AU, 395 00:22:02,040 --> 00:22:05,080 Speaker 1: you're right there. I would think this would make sense 396 00:22:05,600 --> 00:22:08,600 Speaker 1: given that people want to use it for similar purposes, 397 00:22:08,960 --> 00:22:13,119 Speaker 1: non correlated returns shiny objects seems right up your alley. 398 00:22:13,119 --> 00:22:17,720 Speaker 1: How come you haven't filed yet? So we recently files 399 00:22:17,760 --> 00:22:21,000 Speaker 1: this as a public filing for again the equities capability 400 00:22:21,320 --> 00:22:25,080 Speaker 1: UM in both the blockchain. Yeah okay, I know, so 401 00:22:25,160 --> 00:22:30,919 Speaker 1: you okay, the blockchain etf that hold stocks. That makes sense, Um, okay, great, 402 00:22:31,160 --> 00:22:34,160 Speaker 1: But I'm talking about the real deal. Sure, so let's 403 00:22:34,160 --> 00:22:39,560 Speaker 1: get to it. So look, this blockchain, digital assets, cryptocurrency 404 00:22:39,640 --> 00:22:44,119 Speaker 1: again a substantial technological innovation. We are paying attention to 405 00:22:44,119 --> 00:22:47,119 Speaker 1: what we're doing, a tremendous amount of research and development 406 00:22:47,480 --> 00:22:49,640 Speaker 1: in the space. And I can tell you, having been 407 00:22:49,640 --> 00:22:52,919 Speaker 1: in these two worlds for a while, there's incredible parallels 408 00:22:52,960 --> 00:22:56,000 Speaker 1: between the e t F market and the digital asset 409 00:22:56,080 --> 00:22:59,119 Speaker 1: cryptocurrency market. I could extend you know that discussion if 410 00:22:59,160 --> 00:23:02,240 Speaker 1: if you want. We're spending a tremendous amount of energy 411 00:23:02,760 --> 00:23:06,160 Speaker 1: UM on this space. We've been engaged here for an 412 00:23:06,200 --> 00:23:09,119 Speaker 1: extended period of time, but we're seeing changes in the 413 00:23:09,160 --> 00:23:12,800 Speaker 1: market now that are increasing our focus in this segment. 414 00:23:12,880 --> 00:23:16,920 Speaker 1: And so UM again, it's a technology is really you know, 415 00:23:16,920 --> 00:23:20,760 Speaker 1: an investment in blockchain, investment in digital assets and cryptocurrency 416 00:23:20,920 --> 00:23:24,160 Speaker 1: is an investment in technology. And as you pointed out, 417 00:23:24,400 --> 00:23:28,440 Speaker 1: we have often pioneered new ways to gain exposure to 418 00:23:28,520 --> 00:23:31,440 Speaker 1: asset classes. So you think back to our build out 419 00:23:31,440 --> 00:23:34,359 Speaker 1: of bank loans, UH fixed income. There's a lot of 420 00:23:34,480 --> 00:23:38,040 Speaker 1: questions that need to be solved in this blockchain UH 421 00:23:38,160 --> 00:23:42,159 Speaker 1: more specifically bitcoin UH space. I would argue that the 422 00:23:42,160 --> 00:23:45,600 Speaker 1: first bitcoin et F is not the ending place. There 423 00:23:45,680 --> 00:23:49,480 Speaker 1: is going to be theoretically a whole series of return 424 00:23:49,560 --> 00:23:52,840 Speaker 1: patterns in this market, in this new asset class, and 425 00:23:52,880 --> 00:23:55,240 Speaker 1: it's something that we are again spending a lot of 426 00:23:55,359 --> 00:23:58,400 Speaker 1: energy on. Again, I think about its twelve year old 427 00:23:58,400 --> 00:24:02,000 Speaker 1: technology now, but where are we in the network effects 428 00:24:02,040 --> 00:24:05,879 Speaker 1: of this market? And Eric rest assured we are continuing 429 00:24:05,920 --> 00:24:09,840 Speaker 1: to drive innovation, thoughtful innovation, and this is a space 430 00:24:09,960 --> 00:24:12,560 Speaker 1: that you know, we're we are continuing to to put 431 00:24:12,680 --> 00:24:16,600 Speaker 1: energy against. So another product that we are really interested 432 00:24:16,640 --> 00:24:20,040 Speaker 1: in is um sp l V, which is this low 433 00:24:20,119 --> 00:24:25,560 Speaker 1: volatility ETF that had been really popular and then sort 434 00:24:25,560 --> 00:24:29,120 Speaker 1: of um, you know, everybody left, it seemed, but now 435 00:24:29,160 --> 00:24:31,800 Speaker 1: it's actually starting to perform. So just just wondering, like 436 00:24:31,800 --> 00:24:36,159 Speaker 1: when you have a product like that that maybe is 437 00:24:37,680 --> 00:24:40,040 Speaker 1: you know, potential to have a moment, yet like, how 438 00:24:40,080 --> 00:24:42,560 Speaker 1: do you how do you like get people re excited 439 00:24:42,560 --> 00:24:44,919 Speaker 1: about it? Can I just actually add that because what 440 00:24:45,080 --> 00:24:48,879 Speaker 1: Droll talks about is something we have found, which is 441 00:24:49,600 --> 00:24:52,240 Speaker 1: you know, we call it do you get a second 442 00:24:52,280 --> 00:24:55,480 Speaker 1: bite at the Apple currency? Hedging ets just went through this. 443 00:24:55,560 --> 00:24:58,560 Speaker 1: They crushed it, Everybody rushed and it was like a craze. 444 00:24:59,040 --> 00:25:03,680 Speaker 1: Then they started underperforming the non hedged index. Everybody left, 445 00:25:04,240 --> 00:25:08,160 Speaker 1: they come back, they perform great over another year or two. 446 00:25:08,600 --> 00:25:12,320 Speaker 1: Nobody cares do you think that's going to happen to lovall? 447 00:25:14,400 --> 00:25:16,600 Speaker 1: So we we've been getting a lot of questions on 448 00:25:16,640 --> 00:25:19,760 Speaker 1: lovall in particular recently. It's been a big part of 449 00:25:19,760 --> 00:25:22,520 Speaker 1: our client discussions, and i'd widen the lenser, and go 450 00:25:22,600 --> 00:25:26,840 Speaker 1: back to when we launched LOVAL. The same day we 451 00:25:26,920 --> 00:25:30,000 Speaker 1: launched it, we launched high Beta. So kind of the 452 00:25:30,080 --> 00:25:32,560 Speaker 1: Yin and the Yang. And now we've got ten years 453 00:25:32,720 --> 00:25:35,439 Speaker 1: of history on these two products. Again, lo vall a 454 00:25:35,440 --> 00:25:37,040 Speaker 1: lot of attention there. I can tell you. When we're 455 00:25:37,080 --> 00:25:40,840 Speaker 1: developing these products, you know, we had discussions interning which 456 00:25:40,840 --> 00:25:43,440 Speaker 1: one is going to be more implemented. And I can 457 00:25:43,480 --> 00:25:45,679 Speaker 1: tell you that, um, there was a thinking that Hi 458 00:25:45,840 --> 00:25:49,280 Speaker 1: beta was gonna be the revolutionary product because it's going 459 00:25:49,320 --> 00:25:52,240 Speaker 1: to provide this this new return pattern, and much too 460 00:25:52,320 --> 00:25:57,200 Speaker 1: many people's surprise, lo Val took off SPLV for its 461 00:25:57,240 --> 00:26:00,400 Speaker 1: different return pattern. Now we're ten years later, we can 462 00:26:00,400 --> 00:26:03,200 Speaker 1: look at these two and see how they performed, how 463 00:26:03,240 --> 00:26:05,960 Speaker 1: they gathered assets. Um, you know, they're kind of again 464 00:26:06,000 --> 00:26:08,760 Speaker 1: the Yin and the Yang. One holds the lowest volatility 465 00:26:08,800 --> 00:26:11,560 Speaker 1: stocks of the s MP five, the other one holds 466 00:26:11,600 --> 00:26:15,400 Speaker 1: the highest beta securities. And again CAPM would tell us 467 00:26:15,440 --> 00:26:19,639 Speaker 1: that high beta should beat low volatility. You're rewarded for 468 00:26:19,680 --> 00:26:22,760 Speaker 1: the risk you're taking. There, And ten years later, high 469 00:26:22,760 --> 00:26:27,879 Speaker 1: Beta SpHb has performed better than sp lv. Uh, but 470 00:26:27,960 --> 00:26:32,879 Speaker 1: ironically sp LV has you know, significantly larger assets, and 471 00:26:32,960 --> 00:26:37,160 Speaker 1: so these are capabilities and return patterns that we don't 472 00:26:37,200 --> 00:26:41,000 Speaker 1: look at eric. You know, in in isolation, there's low volatility, 473 00:26:41,040 --> 00:26:45,400 Speaker 1: there's high beta, there's momentum, there's quality. We offer those 474 00:26:45,440 --> 00:26:48,359 Speaker 1: as well, and we do see some rotation through the 475 00:26:48,400 --> 00:26:52,119 Speaker 1: different factors based on where we are in market cycles. 476 00:26:52,160 --> 00:26:55,920 Speaker 1: But our role is to provide the return pattern. And 477 00:26:56,040 --> 00:26:58,399 Speaker 1: you know what we're seeing in the more much shorter 478 00:26:58,480 --> 00:27:01,280 Speaker 1: time horizon here is that you know, there is starting 479 00:27:01,280 --> 00:27:04,199 Speaker 1: to be a return to quality, a return sent to 480 00:27:04,280 --> 00:27:08,199 Speaker 1: low volatility UM. And again you look at the pandemic period, 481 00:27:08,760 --> 00:27:11,960 Speaker 1: I would point out that low volatility underperformed during that 482 00:27:12,000 --> 00:27:15,840 Speaker 1: period of period where it should have you know, done well. Um. 483 00:27:15,880 --> 00:27:18,000 Speaker 1: Having said that, you know, we've looked back on this 484 00:27:18,080 --> 00:27:21,600 Speaker 1: through different times and we've seen the strategy underperform. But 485 00:27:21,680 --> 00:27:25,439 Speaker 1: the behavioral finance element of this index, you know, people 486 00:27:25,640 --> 00:27:29,800 Speaker 1: will will ultimately um sell at the wrong time, is 487 00:27:29,800 --> 00:27:33,000 Speaker 1: certainly evident in this and we think that the anomaly 488 00:27:33,080 --> 00:27:36,320 Speaker 1: of low volatility is still as relevant today as it 489 00:27:36,480 --> 00:27:46,080 Speaker 1: was in prior markets. One of the things you bring 490 00:27:46,160 --> 00:27:50,840 Speaker 1: up is the idea that smart beta takes the emotion 491 00:27:51,200 --> 00:27:55,000 Speaker 1: out of active management, because you are have a system, 492 00:27:55,040 --> 00:27:58,040 Speaker 1: there's criteria, it rebounces in a schedule. It's almost like 493 00:27:58,200 --> 00:28:01,280 Speaker 1: R two D two. It's a droid. No matter what happens, 494 00:28:01,320 --> 00:28:03,479 Speaker 1: the thing just does what it is programmed to do. 495 00:28:04,160 --> 00:28:06,080 Speaker 1: This really came up. I'm sure you're gonna love this 496 00:28:06,080 --> 00:28:08,240 Speaker 1: story because it's favorab alters towards your e t F. 497 00:28:08,280 --> 00:28:10,119 Speaker 1: But it could have gone the other way, which is 498 00:28:10,200 --> 00:28:13,320 Speaker 1: p e J, which is the Dynamic Leisure e t F, 499 00:28:13,680 --> 00:28:15,640 Speaker 1: which you know, it's one of these ETF that holds 500 00:28:15,640 --> 00:28:18,240 Speaker 1: a lot of the stocks that benefit from the reopening trade. 501 00:28:18,480 --> 00:28:21,399 Speaker 1: So it and JETS were used quite a bit. Now 502 00:28:21,440 --> 00:28:25,119 Speaker 1: it's interesting, is it bought um a m C, the 503 00:28:25,160 --> 00:28:30,160 Speaker 1: movie theater chain, and then a MC gets hijacked by 504 00:28:30,200 --> 00:28:33,080 Speaker 1: the Wall Street bets and Reddit crowd goes up like 505 00:28:33,320 --> 00:28:38,640 Speaker 1: I don't know, something ridiculous. And then p e J 506 00:28:38,920 --> 00:28:45,000 Speaker 1: sells a m C the next quarter and it's perfectly timed. It. 507 00:28:45,000 --> 00:28:46,960 Speaker 1: I gotta be honest, this was like a trade that 508 00:28:47,240 --> 00:28:49,800 Speaker 1: no human could do because once the stock is that good, 509 00:28:49,840 --> 00:28:52,040 Speaker 1: it's almost hard to let go like that. But you 510 00:28:52,120 --> 00:28:53,920 Speaker 1: did it, and I guess I just want to talk 511 00:28:53,960 --> 00:28:58,160 Speaker 1: about the concept of rebalancing luck or how people who 512 00:28:58,160 --> 00:29:01,280 Speaker 1: are et F investors should think about balancing. Should they 513 00:29:01,320 --> 00:29:04,360 Speaker 1: look at how often it does? Um? What would you 514 00:29:04,400 --> 00:29:08,360 Speaker 1: recommend on that front? Yeah, so you hit on a 515 00:29:08,360 --> 00:29:10,080 Speaker 1: lot of topics. Are the first one I go back 516 00:29:10,120 --> 00:29:12,960 Speaker 1: to is you know PEJ was launched in the early 517 00:29:13,000 --> 00:29:15,680 Speaker 1: two thousands, sat in fifty million dollars in a u 518 00:29:15,840 --> 00:29:18,440 Speaker 1: M kind of did Joel's comments earlier, and then had 519 00:29:18,480 --> 00:29:20,440 Speaker 1: its day in the sun and went from fifty million 520 00:29:21,040 --> 00:29:25,080 Speaker 1: to four billion, mostly about this reopening trade. And Eric, 521 00:29:25,280 --> 00:29:28,680 Speaker 1: as you point out, the securities in the portfolio, Uh, 522 00:29:28,880 --> 00:29:32,760 Speaker 1: you know provided a targeted exposure to the reopening trade 523 00:29:32,800 --> 00:29:37,160 Speaker 1: and so we saw significant inflows there. Rebalancing is key 524 00:29:37,200 --> 00:29:41,280 Speaker 1: to good portfolio management, and so smart beta codes that 525 00:29:41,360 --> 00:29:43,920 Speaker 1: into it, right, and so this particular e t F 526 00:29:44,240 --> 00:29:50,600 Speaker 1: rebalances and reconstitutes four times a year unemotionally predefined. Um. 527 00:29:50,640 --> 00:29:54,280 Speaker 1: Just as you pointed out, Um, you know does things systematically, 528 00:29:54,640 --> 00:29:58,320 Speaker 1: and it's that systematic nature that is important to the 529 00:29:58,440 --> 00:30:01,040 Speaker 1: return pattern. And to your point, you know, as you 530 00:30:01,080 --> 00:30:03,360 Speaker 1: as you mentioned, you know, this was a very well 531 00:30:03,400 --> 00:30:05,920 Speaker 1: timed re balance with a MC. So let me let 532 00:30:05,920 --> 00:30:09,120 Speaker 1: me unpack that for for a quick second. The index 533 00:30:09,360 --> 00:30:15,760 Speaker 1: looks at price, momentum, earnings momentum, quality, management, action, and 534 00:30:15,920 --> 00:30:19,840 Speaker 1: value and it rates them every quarter on that and 535 00:30:19,880 --> 00:30:22,200 Speaker 1: then it takes the thirty names that are you know, 536 00:30:22,320 --> 00:30:25,240 Speaker 1: scoring the best on those attributes, which again they're just 537 00:30:25,280 --> 00:30:28,440 Speaker 1: common sense attributes that a manager would would use. That's 538 00:30:28,480 --> 00:30:32,240 Speaker 1: what it holds in the portfolio. In this instance, it 539 00:30:32,360 --> 00:30:37,080 Speaker 1: actually um you know, on on on the May rebalance um. 540 00:30:37,200 --> 00:30:40,320 Speaker 1: Right before the rebalance, AMC was at twenty six dollars 541 00:30:40,320 --> 00:30:43,640 Speaker 1: a share. The calendar turned, we rebalance on the first 542 00:30:43,720 --> 00:30:47,240 Speaker 1: day of June, and it actually sold AMC at sixty 543 00:30:47,240 --> 00:30:50,000 Speaker 1: two dollars a share much as you pointed out, you know, 544 00:30:50,160 --> 00:30:52,120 Speaker 1: a trade that would have been hard to do if 545 00:30:52,120 --> 00:30:55,640 Speaker 1: it wasn't systematic. But I point back to, really, you 546 00:30:55,640 --> 00:31:00,000 Speaker 1: know that the idea that rebalancing is important in portfolio construction, 547 00:31:00,000 --> 00:31:03,120 Speaker 1: and as you ask, it's important for investors to understand 548 00:31:03,360 --> 00:31:06,400 Speaker 1: how does their fund rebalance, how frequently, how does it 549 00:31:06,480 --> 00:31:10,800 Speaker 1: select securities. That's a key element to understand in e 550 00:31:10,880 --> 00:31:15,320 Speaker 1: t F And my favorite story is our fundamentally weighted 551 00:31:15,440 --> 00:31:19,000 Speaker 1: e t F PRF, which is a you know, a 552 00:31:19,040 --> 00:31:23,240 Speaker 1: one thousand security portfolio in the thick of the financial 553 00:31:23,280 --> 00:31:27,280 Speaker 1: crisis back in in in March of oh nine, it 554 00:31:27,400 --> 00:31:31,920 Speaker 1: was going through its annual reconstitution and it was looking 555 00:31:31,960 --> 00:31:35,080 Speaker 1: at the banking sector and saying, how big is the banks? 556 00:31:35,160 --> 00:31:39,200 Speaker 1: Are the banks from a sales, cash flow book value, 557 00:31:39,520 --> 00:31:43,320 Speaker 1: dividends and it so these are still very important entities, 558 00:31:43,600 --> 00:31:46,760 Speaker 1: and it upweighted it's exposure to financials, you know, in 559 00:31:46,800 --> 00:31:49,880 Speaker 1: a very significant way. Um I remember the calls we 560 00:31:49,880 --> 00:31:53,120 Speaker 1: were getting from clients. You're buying financials right now? How 561 00:31:53,120 --> 00:31:55,160 Speaker 1: could this fund possibly be doing that? But when you're 562 00:31:55,200 --> 00:31:59,920 Speaker 1: looking at five year trailing on sales, cash flow book 563 00:32:00,040 --> 00:32:03,560 Speaker 1: value and dividend, city groups still a big organization. These 564 00:32:03,600 --> 00:32:07,000 Speaker 1: banks that were very small in size at that point 565 00:32:07,240 --> 00:32:11,320 Speaker 1: got upweighted in the index and that drove tremendous outperformance 566 00:32:11,800 --> 00:32:15,880 Speaker 1: from that rebalance forward, which again to your point, these 567 00:32:15,880 --> 00:32:18,520 Speaker 1: things can be timed well, but the important aspect is 568 00:32:18,560 --> 00:32:23,040 Speaker 1: continuing to rebalance, John, I just want to stay with this, 569 00:32:23,240 --> 00:32:25,880 Speaker 1: the rebalanced thing for a second longer because it's such 570 00:32:25,880 --> 00:32:28,920 Speaker 1: an important part of smart data. Right. It's like you've 571 00:32:28,960 --> 00:32:31,760 Speaker 1: got a robot basically that's gonna like do what it 572 00:32:31,840 --> 00:32:34,360 Speaker 1: does when you say it, when you tell it to 573 00:32:34,400 --> 00:32:37,840 Speaker 1: do what it does right. But within that, I'm even wondering, like, 574 00:32:38,800 --> 00:32:42,479 Speaker 1: do you all have a ranking system of like the 575 00:32:42,560 --> 00:32:45,400 Speaker 1: robots who like surprise you and do a really good 576 00:32:45,440 --> 00:32:48,120 Speaker 1: job and others that are like meet a little bit 577 00:32:48,120 --> 00:32:50,520 Speaker 1: more improvement on on the rebalancing abilities? How do you 578 00:32:50,520 --> 00:32:55,880 Speaker 1: guys evaluate that internally? So we're constantly looking at the 579 00:32:55,920 --> 00:32:59,640 Speaker 1: methodologies of the underlying indices and and and making sure 580 00:32:59,680 --> 00:33:02,680 Speaker 1: that they're providing the return pattern that we've stated UM 581 00:33:02,720 --> 00:33:06,440 Speaker 1: as the objective. Uh, and we've done enhancements and you know, 582 00:33:06,520 --> 00:33:10,800 Speaker 1: evolved in disease and changed indicase through time to ensure 583 00:33:10,800 --> 00:33:13,160 Speaker 1: that we're providing clients with with you know, the best 584 00:33:13,200 --> 00:33:16,400 Speaker 1: way of accessing that particular return. And I can tell 585 00:33:16,440 --> 00:33:19,360 Speaker 1: you again back in in in the early days of 586 00:33:19,400 --> 00:33:22,000 Speaker 1: e t F, says, we talked to clients about UM, 587 00:33:22,040 --> 00:33:26,000 Speaker 1: you know this this rebalance frequency UM. The initial reaction 588 00:33:26,120 --> 00:33:29,040 Speaker 1: from from traditional you know thinking was well, you're gonna 589 00:33:29,040 --> 00:33:31,760 Speaker 1: have you know, high turnover is going to you know, 590 00:33:32,000 --> 00:33:34,640 Speaker 1: is ultimately a negative attribute of of you know, what 591 00:33:34,680 --> 00:33:38,120 Speaker 1: we've been trained on in asset management. But the reality 592 00:33:38,160 --> 00:33:41,240 Speaker 1: is that turnover is what drives some of the tax 593 00:33:41,280 --> 00:33:44,480 Speaker 1: efficiency of the e t F. And so again, our 594 00:33:44,600 --> 00:33:47,880 Speaker 1: our core elements and focus has been about challenging convention, 595 00:33:48,280 --> 00:33:51,840 Speaker 1: you know, in the pursuit of innovation and rebalance. Frequency 596 00:33:51,960 --> 00:33:55,240 Speaker 1: is now something that everybody understands. UM. You know, drives 597 00:33:55,280 --> 00:33:58,720 Speaker 1: efficiency from a tax perspective. UH. And the ability to 598 00:33:58,640 --> 00:34:04,520 Speaker 1: to um make a potentially taxable gains at the fund level. UM. 599 00:34:04,680 --> 00:34:06,480 Speaker 1: Let me Uh. I kind of want to end the 600 00:34:06,480 --> 00:34:10,719 Speaker 1: conversation here talking a little business. UM. Two things I 601 00:34:10,719 --> 00:34:12,520 Speaker 1: want to ask about. They're both kind of related. Which 602 00:34:12,560 --> 00:34:17,000 Speaker 1: is just your your strategy for growth? UM? You know 603 00:34:17,080 --> 00:34:19,080 Speaker 1: it's tough. I mean, if Vanguard and black Rock are 604 00:34:19,080 --> 00:34:21,399 Speaker 1: going to take in se of the money that leaves 605 00:34:21,440 --> 00:34:24,839 Speaker 1: about for about a hundred firms, you guys are taking 606 00:34:24,840 --> 00:34:28,360 Speaker 1: a nice chunk of that. But people wonder how how 607 00:34:28,400 --> 00:34:31,239 Speaker 1: can you make it? How are what? How are you 608 00:34:31,239 --> 00:34:34,719 Speaker 1: going to grow? You guys acquired Guggenheim, you acquired Oppenheimer. 609 00:34:34,840 --> 00:34:38,240 Speaker 1: Some people will equate you with acquisitions, so I'm curious 610 00:34:38,280 --> 00:34:40,560 Speaker 1: if you have any there. And then the other thing 611 00:34:40,640 --> 00:34:43,480 Speaker 1: is this move with q q Q you come up 612 00:34:43,520 --> 00:34:47,000 Speaker 1: with q q q M, which essentially is the same thing, 613 00:34:47,560 --> 00:34:49,640 Speaker 1: but it's in a different type of structure. It's not 614 00:34:49,640 --> 00:34:51,560 Speaker 1: a unit investment trust, which means that you get to 615 00:34:51,560 --> 00:34:55,239 Speaker 1: actually make some money on it because the cues has 616 00:34:55,280 --> 00:34:59,880 Speaker 1: the kind of um uh structure. I'll let you a 617 00:35:00,000 --> 00:35:03,000 Speaker 1: explain it, but I guess why launch q q M 618 00:35:03,040 --> 00:35:06,839 Speaker 1: and who are you going to acquire next? Just break 619 00:35:06,880 --> 00:35:10,239 Speaker 1: the news here, yes, yeah, yeah, And I know this 620 00:35:10,320 --> 00:35:12,239 Speaker 1: is run on a delay, so that'll be interesting now 621 00:35:12,239 --> 00:35:15,080 Speaker 1: I'm not kidding. So the uh, the launch of q 622 00:35:15,239 --> 00:35:17,719 Speaker 1: q q M and and q q q J. You know, 623 00:35:17,760 --> 00:35:19,560 Speaker 1: we look back at it now we're a year past 624 00:35:19,600 --> 00:35:22,440 Speaker 1: that launch. Um q q q J you know, was 625 00:35:22,480 --> 00:35:26,000 Speaker 1: awarded the most innovative et F of opened up this 626 00:35:26,040 --> 00:35:29,200 Speaker 1: new segment of the queues, if you will, the next 627 00:35:29,280 --> 00:35:33,759 Speaker 1: one innovators looks so obvious today, right of course we're 628 00:35:33,760 --> 00:35:36,120 Speaker 1: gonna do q q q J. Q q q M 629 00:35:36,160 --> 00:35:38,960 Speaker 1: is now bigger than q q q j um at 630 00:35:38,960 --> 00:35:42,680 Speaker 1: one point three billion. It's accelerating. We're seeing clients that 631 00:35:42,800 --> 00:35:45,840 Speaker 1: preference you know fee um you know, moving to to 632 00:35:46,000 --> 00:35:48,320 Speaker 1: q q q M. It has a lower management fee. 633 00:35:48,520 --> 00:35:52,279 Speaker 1: But again it's really about providing clients more ways to 634 00:35:52,440 --> 00:35:56,120 Speaker 1: access you know, this incredibly important capability. This index, the 635 00:35:56,200 --> 00:35:59,520 Speaker 1: Nasdaq one hundred UM with different attributes again I gave 636 00:35:59,560 --> 00:36:03,560 Speaker 1: the example with DBC and p DBC K one and 637 00:36:03,640 --> 00:36:06,160 Speaker 1: no K one. Q q q M and q q 638 00:36:06,360 --> 00:36:12,080 Speaker 1: q provide very similar exposures but are structured differently depending 639 00:36:12,120 --> 00:36:14,680 Speaker 1: on a client's preference. And so you know, where there's 640 00:36:14,760 --> 00:36:19,520 Speaker 1: high priority for liquidity trading volume, q q Q, you know, 641 00:36:19,640 --> 00:36:22,080 Speaker 1: is one of the most traded securities in the world. 642 00:36:22,640 --> 00:36:26,000 Speaker 1: Where there's fee sensitivity, we're seeing clients implement q q 643 00:36:26,200 --> 00:36:29,960 Speaker 1: q M as it relates to to growth. UM. You know, 644 00:36:30,040 --> 00:36:34,799 Speaker 1: we have really continued to center our focus, UM, you know, 645 00:36:34,920 --> 00:36:37,719 Speaker 1: on on client outcomes, which which I think everybody would 646 00:36:37,719 --> 00:36:39,920 Speaker 1: talk about in this market. One of the things that 647 00:36:39,960 --> 00:36:42,640 Speaker 1: we think about within E t FS is, you know, 648 00:36:42,719 --> 00:36:46,680 Speaker 1: the client experience can only be, you know, at the 649 00:36:46,840 --> 00:36:51,319 Speaker 1: at the highest level equal to our our our employee experience, 650 00:36:51,360 --> 00:36:54,120 Speaker 1: and so we're spending a lot of time UM on 651 00:36:54,320 --> 00:36:59,080 Speaker 1: our employee morale culture people, knowing that if we get 652 00:36:59,120 --> 00:37:02,040 Speaker 1: the best people from an E t F perspective, UM, 653 00:37:02,080 --> 00:37:04,920 Speaker 1: we're going to continue to drive innovation and that's going 654 00:37:05,000 --> 00:37:09,120 Speaker 1: to extend beyond just product development, but really about again 655 00:37:09,200 --> 00:37:13,120 Speaker 1: that full ecosystem of how a client interfaces with E 656 00:37:13,200 --> 00:37:16,080 Speaker 1: t S And I know Eric, we talked about, UM, 657 00:37:16,160 --> 00:37:21,440 Speaker 1: the opportunity with direct indexing to create personalization. We think that, 658 00:37:21,520 --> 00:37:23,600 Speaker 1: you know, as a bit of a teaser here, there's 659 00:37:23,680 --> 00:37:26,600 Speaker 1: things that can be done around the client experience that 660 00:37:26,840 --> 00:37:32,319 Speaker 1: drive personalization in this traditional forty act rapper, and we're 661 00:37:32,320 --> 00:37:35,200 Speaker 1: spending more and more time around that full client experience 662 00:37:35,200 --> 00:37:38,240 Speaker 1: and that's what's going to drive our girl. My colleague 663 00:37:38,280 --> 00:37:42,719 Speaker 1: Ethnosios Sara Vegas really laid out a nice case for 664 00:37:42,800 --> 00:37:46,520 Speaker 1: why you guys should buy State Streets e t F business. UM, 665 00:37:46,760 --> 00:37:49,319 Speaker 1: it really emerged as well. And then one of your 666 00:37:49,520 --> 00:37:53,960 Speaker 1: ex colleagues, then Fulton, wrote about that also in E 667 00:37:54,040 --> 00:37:57,080 Speaker 1: t F dot Com, saying this would make a lot 668 00:37:57,080 --> 00:38:00,200 Speaker 1: of sense. So any any thoughts on that or you 669 00:38:00,239 --> 00:38:04,200 Speaker 1: just want to I'm gonna guess you're gonna pass. Look, 670 00:38:04,400 --> 00:38:07,480 Speaker 1: I would say, as you pointed out, historically we've grown 671 00:38:07,600 --> 00:38:11,000 Speaker 1: organically and inorganically. UM. You know you mentioned in the US, 672 00:38:11,280 --> 00:38:14,799 Speaker 1: you know, we we acquired the power shares business, Googgenheim's 673 00:38:14,800 --> 00:38:19,760 Speaker 1: ETF business. In Europe, we acquired the source business. Most recently, 674 00:38:20,000 --> 00:38:24,279 Speaker 1: you know, we we combined with the Oppenheimer Funds capability 675 00:38:24,360 --> 00:38:28,000 Speaker 1: here in the US. So we've grown both organically and inorganically. 676 00:38:28,360 --> 00:38:30,840 Speaker 1: And I think it all comes down to the client 677 00:38:30,920 --> 00:38:35,200 Speaker 1: experience and what makes most sense, and that's ultimately what 678 00:38:35,280 --> 00:38:38,040 Speaker 1: our north star is. And so I wouldn't comment on 679 00:38:38,040 --> 00:38:41,120 Speaker 1: one particular name. You know, there's there's there's news every 680 00:38:41,160 --> 00:38:44,040 Speaker 1: day and speculation every day on on all of these things. 681 00:38:44,600 --> 00:38:46,080 Speaker 1: But at the end of the day, you know, our 682 00:38:46,160 --> 00:38:49,400 Speaker 1: north star is about client and client experience, um, and 683 00:38:49,440 --> 00:38:52,120 Speaker 1: that's what's going to drive our decisions going forward. Okay, 684 00:38:52,120 --> 00:38:54,440 Speaker 1: I'm gonna try and get you say something about a 685 00:38:54,480 --> 00:38:56,439 Speaker 1: single name, but it'll be a little bit different, which 686 00:38:56,440 --> 00:38:58,920 Speaker 1: is we've talked about a lot of of Invesco's ETFs 687 00:38:58,960 --> 00:39:02,000 Speaker 1: here out of two and thirty three, is there anyone 688 00:39:02,280 --> 00:39:04,640 Speaker 1: that we didn't talk about that you have a special 689 00:39:04,640 --> 00:39:11,480 Speaker 1: affinity for. I know it's gonna say, go ahead, a 690 00:39:11,719 --> 00:39:15,520 Speaker 1: bullet chairs, that's my guess, but go ahead. You know 691 00:39:15,600 --> 00:39:19,319 Speaker 1: what I think? Um, Look, I I don't there's not 692 00:39:19,400 --> 00:39:22,279 Speaker 1: one of the Invesco loves bullet chairs. I would too, 693 00:39:22,280 --> 00:39:25,359 Speaker 1: They're great products. I'm just no, I look, I think 694 00:39:25,560 --> 00:39:28,600 Speaker 1: Look it's it's there's a technology associated with bullet chairs 695 00:39:28,640 --> 00:39:31,200 Speaker 1: that is innovative. It makes an et F feel like 696 00:39:31,239 --> 00:39:34,279 Speaker 1: a big bond, certainly an interesting capability and something that 697 00:39:34,320 --> 00:39:38,680 Speaker 1: we saw in the acquisition of Goggenheim. Having said that, um, 698 00:39:38,719 --> 00:39:41,680 Speaker 1: you know that there's not a particular product that I 699 00:39:41,719 --> 00:39:45,120 Speaker 1: would jump off the page, you know, in terms of newness, 700 00:39:45,280 --> 00:39:48,040 Speaker 1: maybe possibly Joel, if I had to answer it and 701 00:39:48,040 --> 00:39:51,279 Speaker 1: go somewhere. Um you know, our senior loan e t 702 00:39:51,480 --> 00:39:54,960 Speaker 1: F is one that um you know, a number of 703 00:39:55,000 --> 00:39:59,399 Speaker 1: teams across the organization worked on to Pioneer. We had 704 00:39:59,400 --> 00:40:01,719 Speaker 1: so many questions at the time of how to bring 705 00:40:01,760 --> 00:40:05,480 Speaker 1: this O t c UH structure on exchange something that 706 00:40:05,560 --> 00:40:10,120 Speaker 1: settles UH in much longer cycles and prices differently. And 707 00:40:10,480 --> 00:40:13,160 Speaker 1: today b k l N is one of the largest 708 00:40:13,280 --> 00:40:16,759 Speaker 1: loan funds in the world, and it was about opening exposure, 709 00:40:16,800 --> 00:40:20,279 Speaker 1: opening access to that return pattern, so one that we're 710 00:40:20,280 --> 00:40:22,960 Speaker 1: seeing more and more interested recently. But um, of the 711 00:40:23,080 --> 00:40:24,440 Speaker 1: as I said on the front end, you know I 712 00:40:24,480 --> 00:40:27,920 Speaker 1: love all two and five of our kids the same. Okay, 713 00:40:27,960 --> 00:40:31,080 Speaker 1: So let me also ask you a question that we 714 00:40:31,120 --> 00:40:33,760 Speaker 1: ask everyone at the end of Trilliance, which is favorite 715 00:40:33,760 --> 00:40:38,160 Speaker 1: et F ticker that is not your own favorite et 716 00:40:38,280 --> 00:40:39,880 Speaker 1: F ticker that's not my own. I'm gonna go with 717 00:40:39,960 --> 00:40:42,239 Speaker 1: MoU m Oo, just because that was one of the 718 00:40:42,360 --> 00:40:47,200 Speaker 1: early ones that um, you know, really created brand recognition 719 00:40:47,280 --> 00:40:50,279 Speaker 1: on its own, uh you know, early in the days there, 720 00:40:50,360 --> 00:40:53,799 Speaker 1: and and certainly a memorable one. That's a that's a 721 00:40:53,800 --> 00:40:57,319 Speaker 1: popular one. Yeah. John Hoppin thinks so much for joining 722 00:40:57,360 --> 00:41:00,640 Speaker 1: us on, Trillian, Joel, Eric, thank you so much for 723 00:41:00,680 --> 00:41:08,720 Speaker 1: the opportunity as a pleasure. Thanks for listening to Trillions 724 00:41:08,960 --> 00:41:11,360 Speaker 1: until next time. You can find us on the Bloomberg terminal, 725 00:41:11,640 --> 00:41:16,000 Speaker 1: Bloomberg dot com, Apple Podcasts, Spotify, and wherever else you 726 00:41:16,120 --> 00:41:18,560 Speaker 1: like to listen. We'd love to hear from you. We're 727 00:41:18,600 --> 00:41:22,440 Speaker 1: on Twitter, I'm at Joel Webber Show. He's at Eric Baltunas. 728 00:41:22,880 --> 00:41:27,360 Speaker 1: You can find Investco at investo Us. This episode of 729 00:41:27,360 --> 00:41:30,759 Speaker 1: Trillions was produced by Magnus Hendrickson. Francesica Levie is the 730 00:41:30,800 --> 00:41:40,640 Speaker 1: head of Bloomberg Podcast. Bye.