1 00:00:05,960 --> 00:00:12,840 Speaker 1: Welcome to Trilliance. I'm Joel Weber, and I'm so Eric. 2 00:00:12,920 --> 00:00:15,680 Speaker 1: I'm the editor of Business Week. As you know, every 3 00:00:15,760 --> 00:00:18,320 Speaker 1: year we do this thing that we call the Jealousy List. 4 00:00:18,920 --> 00:00:22,279 Speaker 1: The Jealousy List is an exercise in humility. Have you 5 00:00:22,320 --> 00:00:25,360 Speaker 1: seen it? Yes? Yeah, no, I've seen him. You've done 6 00:00:25,360 --> 00:00:27,920 Speaker 1: it for a few years, right, multiple years, yeah, And 7 00:00:28,160 --> 00:00:31,520 Speaker 1: so the exercise is one that we invite not only 8 00:00:31,520 --> 00:00:33,320 Speaker 1: the staff of Business Week, but a bunch of our 9 00:00:33,320 --> 00:00:37,599 Speaker 1: contributors throughout the Bloomberg News universe to say, if there 10 00:00:37,680 --> 00:00:42,120 Speaker 1: was one story that someone other than you and and 11 00:00:42,159 --> 00:00:45,479 Speaker 1: Bloomberg did this year, what was it? What are you 12 00:00:45,680 --> 00:00:50,639 Speaker 1: most jealous of in the pantheon of journalism. We get 13 00:00:50,640 --> 00:00:53,120 Speaker 1: a ton of positive feedback about it every year, and 14 00:00:53,159 --> 00:00:55,240 Speaker 1: it makes for a great end of your reading list 15 00:00:55,520 --> 00:00:57,920 Speaker 1: that I encourage everyone to check out over the holidays 16 00:00:57,960 --> 00:01:02,800 Speaker 1: at Bloomberg dot com. And this year was you know, 17 00:01:02,960 --> 00:01:08,120 Speaker 1: everyone was doing good stuff during the pandemic. So it 18 00:01:08,240 --> 00:01:11,400 Speaker 1: was a special treat to be able to look across 19 00:01:11,600 --> 00:01:14,679 Speaker 1: everybody in journalism and say, here's some things that stood 20 00:01:14,680 --> 00:01:17,840 Speaker 1: out to us. And we figured we would take that 21 00:01:17,880 --> 00:01:21,480 Speaker 1: same exercise to trillions this episode and talk to some 22 00:01:21,560 --> 00:01:25,120 Speaker 1: of our main et F contributors and figure out what 23 00:01:25,240 --> 00:01:28,679 Speaker 1: they were jealous of. Yeah, and just curious, did you 24 00:01:28,800 --> 00:01:31,560 Speaker 1: have one that you were jealous of? Yeah? Of course. 25 00:01:32,280 --> 00:01:37,080 Speaker 1: And it was by New York Magazine and the story 26 00:01:37,200 --> 00:01:41,319 Speaker 1: was the World's best Bureaucrat. Do you know who that is? Oh? Yeah, 27 00:01:41,360 --> 00:01:46,039 Speaker 1: well you told yeah, So it was. It was a 28 00:01:46,080 --> 00:01:49,000 Speaker 1: great story that they did. I was super jealous of 29 00:01:49,000 --> 00:01:52,680 Speaker 1: it because, look like we talked about Jerome Pow a lot, 30 00:01:53,080 --> 00:01:55,520 Speaker 1: and we talked about the FED a lot. But the 31 00:01:55,560 --> 00:01:58,520 Speaker 1: way that they framed that, I just thought it was. 32 00:01:58,800 --> 00:02:01,200 Speaker 1: I read the article, It wasn't like I even learned 33 00:02:01,200 --> 00:02:03,160 Speaker 1: that much from it, but they just put it all 34 00:02:03,200 --> 00:02:06,600 Speaker 1: together in this great What was the main framing? Because 35 00:02:06,600 --> 00:02:08,640 Speaker 1: you know, Jerome call gets a lot of ink. Most 36 00:02:08,680 --> 00:02:11,639 Speaker 1: people understand he has big influence on the markets. What 37 00:02:11,680 --> 00:02:16,560 Speaker 1: was the framing here? So Josh Barrow, who you probably 38 00:02:16,600 --> 00:02:19,679 Speaker 1: know he's now a business insider, but he was columns 39 00:02:19,760 --> 00:02:23,320 Speaker 1: for for New York magazine, and and again I just 40 00:02:23,360 --> 00:02:26,040 Speaker 1: thought that it was like the framing of thinking of 41 00:02:26,120 --> 00:02:29,560 Speaker 1: Pale as a bureaucrat, which the trickle down effect and 42 00:02:29,680 --> 00:02:31,480 Speaker 1: why I would still want to talk about it on 43 00:02:31,520 --> 00:02:35,200 Speaker 1: trillions is that you know, he was Superman this year, right, 44 00:02:35,600 --> 00:02:40,600 Speaker 1: and the sun that radiated from the FED basically kept 45 00:02:41,160 --> 00:02:44,960 Speaker 1: the markets and the economy going right. And and so 46 00:02:45,040 --> 00:02:47,360 Speaker 1: the fact that we could talk about that but do 47 00:02:47,480 --> 00:02:50,320 Speaker 1: it through sort of a more of a novel framing, 48 00:02:50,360 --> 00:02:53,720 Speaker 1: I thought was to reach that wider audience that they 49 00:02:53,760 --> 00:02:56,639 Speaker 1: can reach. Yeah, that's really great, and yeah, Josh is 50 00:02:56,680 --> 00:02:59,520 Speaker 1: real good at um he's in the he's in the 51 00:02:59,560 --> 00:03:03,079 Speaker 1: wider world of news, but he knows the markets really well. 52 00:03:03,120 --> 00:03:05,440 Speaker 1: And I can see why you'd pick that. But also, 53 00:03:05,480 --> 00:03:07,639 Speaker 1: can I just go a little crazy with the Superman 54 00:03:07,680 --> 00:03:10,880 Speaker 1: metaphor here? I literally had the thought that you remember 55 00:03:10,919 --> 00:03:13,080 Speaker 1: at the end of Superman one, when he flies around 56 00:03:13,120 --> 00:03:16,200 Speaker 1: the earth like, you know, so fast that he rewinds time. 57 00:03:17,040 --> 00:03:19,079 Speaker 1: I swear as like the Fed kind of pulled the 58 00:03:19,120 --> 00:03:22,320 Speaker 1: Superman one because they made that huge fall in March 59 00:03:22,440 --> 00:03:26,000 Speaker 1: come kind of right back and they really rewound time 60 00:03:26,040 --> 00:03:28,680 Speaker 1: a little bit. It was really unbelievable. I think Superman 61 00:03:28,800 --> 00:03:32,160 Speaker 1: is a pretty apt metaphor. So joining us on this 62 00:03:32,200 --> 00:03:36,400 Speaker 1: episode we have Jako Petershill, who's an editor on the 63 00:03:36,400 --> 00:03:41,080 Speaker 1: Cross Asset team in London. First time on Trillions Clear Balentine, 64 00:03:41,200 --> 00:03:44,480 Speaker 1: who's a cross asset reporter, and Katie Gridfield, the markets 65 00:03:44,520 --> 00:03:48,440 Speaker 1: and et F reporter. And we'll also get Eric's jealousy 66 00:03:48,480 --> 00:04:03,400 Speaker 1: pick too, this time on Trillions Jealousy List. Alright, Yakobe, Claire, Katie, 67 00:04:03,400 --> 00:04:05,520 Speaker 1: great to have you on Trillions again, Thanks for joining us. 68 00:04:05,880 --> 00:04:09,480 Speaker 1: Thank you. Okay, Eric, I gave you mine. What was 69 00:04:10,000 --> 00:04:13,320 Speaker 1: the jealousy list item that you would put on your 70 00:04:13,360 --> 00:04:16,560 Speaker 1: list this year? Well, there's a lot. You know, I'm 71 00:04:16,560 --> 00:04:18,560 Speaker 1: in research, so I'm gonna kind of look to other 72 00:04:18,600 --> 00:04:21,960 Speaker 1: analysts as opposed to reporters. But um, the people I 73 00:04:22,040 --> 00:04:25,680 Speaker 1: tend to get jealous of our Dave Nadigg, Ben Johnson 74 00:04:25,720 --> 00:04:28,919 Speaker 1: at morning Star, Todd rosen Bluth, they always write, you know, 75 00:04:29,040 --> 00:04:30,640 Speaker 1: a couple of things a year that I am really 76 00:04:30,680 --> 00:04:34,120 Speaker 1: impressed by. But Dave Nadie in particular, had two articles 77 00:04:34,120 --> 00:04:37,640 Speaker 1: this year, won during the fixed income bond ETF sell 78 00:04:37,680 --> 00:04:40,720 Speaker 1: off that really nobody goes as deep into trading as him, 79 00:04:40,720 --> 00:04:41,960 Speaker 1: and I thought that was good. But the one that 80 00:04:42,120 --> 00:04:44,680 Speaker 1: recently came out that I wish I wrote, and I 81 00:04:44,720 --> 00:04:47,799 Speaker 1: was thinking of writing, and I'm probably going to quote 82 00:04:47,839 --> 00:04:51,040 Speaker 1: in this book I'm working on, is an article called 83 00:04:51,080 --> 00:04:53,520 Speaker 1: how big is too big? And it's an e t 84 00:04:53,640 --> 00:04:57,159 Speaker 1: F trends And essentially there's been this steady drumbeat of 85 00:04:57,200 --> 00:05:00,480 Speaker 1: like worrying that the et F fish it were passive 86 00:05:00,480 --> 00:05:03,599 Speaker 1: issuers are getting too big. Vanguard and black Rock in particular, 87 00:05:04,000 --> 00:05:07,240 Speaker 1: they own eight percent each of the average stock. That's 88 00:05:07,279 --> 00:05:11,599 Speaker 1: a lot. It's the most uh. Ever, and this institutionalization 89 00:05:11,760 --> 00:05:15,000 Speaker 1: of holdings where you have maybe I don't know two 90 00:05:15,040 --> 00:05:17,719 Speaker 1: dozen firms that have really a huge amount of power 91 00:05:18,240 --> 00:05:21,800 Speaker 1: over corporate America. And it's an interesting issue and it's legit, 92 00:05:21,960 --> 00:05:24,919 Speaker 1: but a lot of the academics they just sort of 93 00:05:24,960 --> 00:05:30,160 Speaker 1: worry about it without really providing any any major evidence. Uh. 94 00:05:30,279 --> 00:05:35,000 Speaker 1: For example, like airline tickets would go up incredibly because 95 00:05:35,000 --> 00:05:38,839 Speaker 1: there'd be no motive for the owners of the stocks 96 00:05:38,880 --> 00:05:41,400 Speaker 1: to The motive would be for them to make more money, 97 00:05:41,400 --> 00:05:43,320 Speaker 1: so they'd increase airline tickets. But there's a lot of 98 00:05:43,320 --> 00:05:46,960 Speaker 1: counterpoints and then they really never provide any solutions for 99 00:05:47,000 --> 00:05:49,800 Speaker 1: this uh in these in these papers, they really you know, 100 00:05:49,800 --> 00:05:52,080 Speaker 1: what, what what do you want to break up the index funds? 101 00:05:52,080 --> 00:05:54,640 Speaker 1: Ban index funds um The other thing is the index 102 00:05:54,680 --> 00:05:56,880 Speaker 1: funds obviously do a lot of good, so most people 103 00:05:56,880 --> 00:05:59,400 Speaker 1: who own them don't really care about this issue. So 104 00:05:59,440 --> 00:06:02,880 Speaker 1: there's a lot of cross currents in this particular issue. 105 00:06:03,160 --> 00:06:06,119 Speaker 1: But Dave just broke it down, really made a simple 106 00:06:06,200 --> 00:06:09,279 Speaker 1: way to explain why they are worrying about it, but 107 00:06:09,360 --> 00:06:11,760 Speaker 1: did kind of ding them for for this, you know, 108 00:06:11,880 --> 00:06:15,160 Speaker 1: idea of here's what he has this quote. With this 109 00:06:15,240 --> 00:06:17,840 Speaker 1: concentration and ownership, the knee jerk reaction from pundits and 110 00:06:17,880 --> 00:06:21,479 Speaker 1: academics alike will be and is already let's prove this 111 00:06:21,560 --> 00:06:24,960 Speaker 1: is a problem. And I do find that somewhat part 112 00:06:25,000 --> 00:06:27,800 Speaker 1: of this. But he goes through the concerns, goes through 113 00:06:27,800 --> 00:06:31,520 Speaker 1: some counterpoints, and then he also goes through what we 114 00:06:31,560 --> 00:06:34,920 Speaker 1: shouldn't do and what we could do, and I like that. 115 00:06:35,000 --> 00:06:38,200 Speaker 1: I like that uh adding of solutions in there. So 116 00:06:38,760 --> 00:06:41,200 Speaker 1: it was just a really good, well rounded article. I 117 00:06:41,279 --> 00:06:44,320 Speaker 1: highly recommend reading it, especially if you get a little 118 00:06:44,360 --> 00:06:47,000 Speaker 1: alarmed by some article that has the headline of like 119 00:06:47,839 --> 00:06:51,440 Speaker 1: is Vanguard too big or is uh passive going to 120 00:06:51,520 --> 00:06:54,440 Speaker 1: raise your airline tickets? Um, just read this piece and 121 00:06:54,520 --> 00:06:56,359 Speaker 1: it will give you a more well rounded picture of 122 00:06:56,360 --> 00:07:00,520 Speaker 1: the situation. It's pretty nerdy, it is, but it's you know, 123 00:07:00,560 --> 00:07:04,000 Speaker 1: when it's an ongoing issue, and it's one that um, 124 00:07:04,200 --> 00:07:06,599 Speaker 1: you know, the academics would argue that it's not that 125 00:07:06,640 --> 00:07:11,120 Speaker 1: wonky because this could could affect consumers. So anybody who 126 00:07:11,320 --> 00:07:15,560 Speaker 1: buys goods, flies and airplanes, not this year, but regularly. Uh, 127 00:07:15,600 --> 00:07:18,640 Speaker 1: this could affect you. That's what they would say. And 128 00:07:18,880 --> 00:07:22,040 Speaker 1: a lot of people on the index side would you know, 129 00:07:22,080 --> 00:07:24,120 Speaker 1: beg the differ. But that's why it's an issue that 130 00:07:24,520 --> 00:07:26,920 Speaker 1: has a lot of depth in my opinion, because it 131 00:07:26,920 --> 00:07:30,200 Speaker 1: really strikes at the heart of markets and capitalism. Okay, Claire, 132 00:07:30,240 --> 00:07:34,120 Speaker 1: did Eric just steal your jealousy list item? No? Um, 133 00:07:34,320 --> 00:07:37,720 Speaker 1: I had had a different one. I um, it was 134 00:07:37,800 --> 00:07:40,320 Speaker 1: an article and it's technically e t N s and 135 00:07:40,360 --> 00:07:42,280 Speaker 1: not E t f s, but I think it can 136 00:07:42,400 --> 00:07:45,760 Speaker 1: can qualify. But what remind us what E t N is? 137 00:07:46,040 --> 00:07:50,520 Speaker 1: So E t N s are unsecured debt obligations. They 138 00:07:50,560 --> 00:07:52,520 Speaker 1: sound similar to e t F s, but they're actually 139 00:07:52,840 --> 00:07:56,040 Speaker 1: pretty different, um in the in the sense that they're 140 00:07:56,080 --> 00:07:59,840 Speaker 1: similar to bonds. Um they have a maturity date. One 141 00:07:59,880 --> 00:08:02,200 Speaker 1: of the things people like about them is that they 142 00:08:02,200 --> 00:08:05,000 Speaker 1: are leveraged a lot of the times and can deliver 143 00:08:05,640 --> 00:08:09,480 Speaker 1: big returns, but they can also really amplify losses UM, 144 00:08:09,520 --> 00:08:13,120 Speaker 1: and they really came into the spotlight this year during 145 00:08:13,160 --> 00:08:15,440 Speaker 1: all the volatility in March and then you know the 146 00:08:15,520 --> 00:08:18,080 Speaker 1: storage back to all time highs and just how that 147 00:08:18,160 --> 00:08:22,640 Speaker 1: market activity really whipsawed these exchange traded notes that counts 148 00:08:22,800 --> 00:08:25,640 Speaker 1: will go with it so UM. But it was one 149 00:08:25,720 --> 00:08:30,440 Speaker 1: that Akani Otani and Sebastian pelle Haero did for the 150 00:08:30,520 --> 00:08:32,760 Speaker 1: Raw Street Journal UM. It came out at the beginning 151 00:08:32,800 --> 00:08:36,160 Speaker 1: of June UM and its title is bankrupt in just 152 00:08:36,280 --> 00:08:41,400 Speaker 1: two weeks. Individual investors get burned by collapse of complex securities, 153 00:08:42,120 --> 00:08:46,920 Speaker 1: and it was all about more retail, smaller investors that 154 00:08:47,200 --> 00:08:51,320 Speaker 1: put all their money into UM E t N s UM. 155 00:08:51,480 --> 00:08:54,240 Speaker 1: Some of them were talking about their retirement savings going 156 00:08:54,280 --> 00:08:58,240 Speaker 1: in there trying to UM get returns on those and 157 00:08:58,360 --> 00:09:02,199 Speaker 1: sort of learned in by that UM possibility of having 158 00:09:02,240 --> 00:09:05,400 Speaker 1: really outsized gains from these leveraged E t N s 159 00:09:05,679 --> 00:09:09,280 Speaker 1: and how UM some of them just got completely wiped 160 00:09:09,320 --> 00:09:12,560 Speaker 1: out during the volatility in March. And what I really 161 00:09:12,559 --> 00:09:14,720 Speaker 1: liked about it was that it it talked to these 162 00:09:14,760 --> 00:09:17,920 Speaker 1: individual investors, which isn't something that's easy to do to 163 00:09:18,000 --> 00:09:20,319 Speaker 1: find people willing to talk about how much money they 164 00:09:20,360 --> 00:09:23,640 Speaker 1: lost um, and also to be able to sort of 165 00:09:23,640 --> 00:09:27,080 Speaker 1: tell their stories, which is something that I wish we 166 00:09:27,240 --> 00:09:29,880 Speaker 1: did more in our articles and one of the goals 167 00:09:29,920 --> 00:09:33,360 Speaker 1: of mine moving into But I thought they did a 168 00:09:33,400 --> 00:09:36,880 Speaker 1: great job of just really laying out, um, kind of 169 00:09:36,920 --> 00:09:40,480 Speaker 1: why these investors would go into the products, some of 170 00:09:40,520 --> 00:09:44,000 Speaker 1: them trying to boost their retirement savings, UM, just their 171 00:09:44,120 --> 00:09:47,360 Speaker 1: idea that bond yields are so low, um, and just 172 00:09:47,400 --> 00:09:49,960 Speaker 1: sort of searching for products. And there's been such a 173 00:09:50,000 --> 00:09:55,040 Speaker 1: discussion over whether there's enough regulation around these e t 174 00:09:55,280 --> 00:09:59,120 Speaker 1: n s and enough disclaimers to sort of prevent retail 175 00:09:59,160 --> 00:10:02,080 Speaker 1: investors from going into them um. And there's a lot 176 00:10:02,120 --> 00:10:03,839 Speaker 1: of back and forth on that debate. But it's sort 177 00:10:03,880 --> 00:10:06,559 Speaker 1: of hard to read this article and not think, Wow, 178 00:10:06,679 --> 00:10:08,840 Speaker 1: something is sort of messed up in the sense that 179 00:10:09,200 --> 00:10:13,560 Speaker 1: these people can lose so much money from these products. Claire, 180 00:10:13,600 --> 00:10:15,719 Speaker 1: that's a good one. I think e t n s 181 00:10:15,760 --> 00:10:18,439 Speaker 1: are kind of like the wild cousin of the E 182 00:10:18,559 --> 00:10:21,559 Speaker 1: t F. They arguably shouldn't even be under the same umbrella. 183 00:10:21,600 --> 00:10:24,360 Speaker 1: They just they are though. But yeah, a lot of 184 00:10:24,360 --> 00:10:25,920 Speaker 1: them closed. This was a year where a lot of 185 00:10:25,920 --> 00:10:28,559 Speaker 1: exotics closed, so a lot of this worry probably took 186 00:10:28,559 --> 00:10:30,480 Speaker 1: care of itself with all those closures like t vix 187 00:10:31,040 --> 00:10:33,960 Speaker 1: u w T. In our rating system, we call these 188 00:10:33,960 --> 00:10:37,800 Speaker 1: the the n C seventeen products. They're worse than rated 189 00:10:37,920 --> 00:10:41,560 Speaker 1: r UM. But the E t F tent is so big, 190 00:10:42,160 --> 00:10:44,200 Speaker 1: and picking a product that you don't understand is is 191 00:10:44,200 --> 00:10:47,120 Speaker 1: definitely a possibility and something that is you know, should 192 00:10:47,160 --> 00:10:50,600 Speaker 1: be looked at and you know, talked about more. But 193 00:10:50,760 --> 00:10:52,559 Speaker 1: or Yako, you want to talk about Europe and how 194 00:10:52,600 --> 00:10:55,320 Speaker 1: insane it is over there? Um, what in terms of 195 00:10:55,360 --> 00:10:58,240 Speaker 1: E t n s. Yeah, they let anything go there. Yeah, 196 00:10:58,240 --> 00:11:01,640 Speaker 1: there's a as a company called Leverage Shares out here 197 00:11:01,679 --> 00:11:05,319 Speaker 1: that does basically their whole product is just it's an 198 00:11:05,320 --> 00:11:07,560 Speaker 1: e t F that gives you leveraged exposure to a 199 00:11:07,600 --> 00:11:09,920 Speaker 1: single stock. So you can buy this e t F 200 00:11:09,960 --> 00:11:11,640 Speaker 1: as a way of like getting like I mean, I 201 00:11:11,679 --> 00:11:13,640 Speaker 1: don't think it goes up to like seven times or anything, 202 00:11:13,640 --> 00:11:16,440 Speaker 1: but they definitely have like triple leverage TESLA exposure and 203 00:11:16,440 --> 00:11:17,760 Speaker 1: it's an e t F and you just buy it 204 00:11:17,760 --> 00:11:21,000 Speaker 1: on an exchange. It's it's bizarre. Um. And of course Eric, 205 00:11:21,240 --> 00:11:23,840 Speaker 1: you know from the past, we also have like seven 206 00:11:23,880 --> 00:11:27,839 Speaker 1: times you know, negative docks index e t N s 207 00:11:27,880 --> 00:11:29,880 Speaker 1: that are you know, issued by sock Gin and banks 208 00:11:29,920 --> 00:11:32,160 Speaker 1: like that, and those are always fun, Joel. They know 209 00:11:32,200 --> 00:11:35,080 Speaker 1: how to party in Europe. That's the bottom. Mean you 210 00:11:35,120 --> 00:11:37,640 Speaker 1: could you imagine if all that stuff was on robin Hood. 211 00:11:38,160 --> 00:11:40,720 Speaker 1: Oh my god. The three x tesla on robin Hood 212 00:11:40,800 --> 00:11:44,160 Speaker 1: is quite is something to think about. Yeah, yeah, there's 213 00:11:44,160 --> 00:11:45,720 Speaker 1: a bit more freedom out here in Europe. You know. 214 00:11:45,760 --> 00:11:47,760 Speaker 1: It's like, you know, we have nude beaches, we have 215 00:11:47,960 --> 00:11:51,719 Speaker 1: like underage drinking and yeah, it goes right, it goes 216 00:11:51,760 --> 00:12:03,560 Speaker 1: fits right. In hatch bars we heard from Quare Now 217 00:12:03,720 --> 00:12:07,439 Speaker 1: Wall Street Journal gave her pains? What gave you pains? 218 00:12:07,440 --> 00:12:09,640 Speaker 1: What are you jealous of? Okay, so if you know, 219 00:12:09,720 --> 00:12:12,040 Speaker 1: but you know, I dabble in volatility a lot too, 220 00:12:12,120 --> 00:12:14,920 Speaker 1: And and this story is kind of it's mostly about volatility, 221 00:12:14,960 --> 00:12:18,280 Speaker 1: but it's tangentially related to to the et P space because, 222 00:12:18,320 --> 00:12:21,480 Speaker 1: as we know, back in ten, a lot of E 223 00:12:21,559 --> 00:12:24,240 Speaker 1: t F and e t N investors got burned trading volatility. 224 00:12:24,840 --> 00:12:27,800 Speaker 1: A similar thing happened this year UM, but in a 225 00:12:27,880 --> 00:12:31,840 Speaker 1: sort of positive twist, it was less UM retail investors 226 00:12:31,880 --> 00:12:34,560 Speaker 1: that got burned than the institutions. UM. This year, so 227 00:12:34,600 --> 00:12:38,040 Speaker 1: that was kind of a heartwarming sort of development. UM. 228 00:12:38,120 --> 00:12:40,559 Speaker 1: So my article that I'm jealous of this year is 229 00:12:40,600 --> 00:12:44,680 Speaker 1: called how to Lose a Billion dollars Without Really Trying UM, 230 00:12:44,720 --> 00:12:46,800 Speaker 1: which is an awesome title, and it was written by 231 00:12:46,880 --> 00:12:50,840 Speaker 1: Leanna Or for Institutional Investor magazine UM, and basically it's 232 00:12:50,880 --> 00:12:53,280 Speaker 1: a it's a long feature and a sort of postmortem 233 00:12:53,720 --> 00:12:56,760 Speaker 1: UM that makes the argument that trading volatility was actually 234 00:12:56,800 --> 00:13:00,640 Speaker 1: the the w or like the sub toxic subprime riggage 235 00:13:00,840 --> 00:13:04,520 Speaker 1: of the Corona crash. Everyone knows what happened right in March, 236 00:13:04,800 --> 00:13:07,560 Speaker 1: VIC spike to a record UM, and a lot of 237 00:13:07,600 --> 00:13:10,640 Speaker 1: people were short volatility, a lot of sophisticated hedge funds, 238 00:13:10,960 --> 00:13:13,800 Speaker 1: a lot of pension funds that invest you know, our 239 00:13:13,880 --> 00:13:17,960 Speaker 1: grandparents money for them, UM, and so pretty much everyone 240 00:13:18,080 --> 00:13:21,680 Speaker 1: was like uniformly burnt on this. Ironically, who came out 241 00:13:21,720 --> 00:13:25,120 Speaker 1: sort of not so badly as the retail investor because 242 00:13:25,679 --> 00:13:27,960 Speaker 1: if you guys remember Posten, there was a lot of 243 00:13:28,000 --> 00:13:32,000 Speaker 1: sort of reform in the volatility etp space UM, and 244 00:13:32,000 --> 00:13:34,640 Speaker 1: these things became kind of a lot less nuclear and 245 00:13:34,679 --> 00:13:38,080 Speaker 1: a lot less popular, So there wasn't as much retail 246 00:13:38,120 --> 00:13:42,240 Speaker 1: speculation on volatility. This time around UM and and in fact, 247 00:13:42,320 --> 00:13:44,400 Speaker 1: a lot of the banks that did things like issue 248 00:13:44,440 --> 00:13:47,600 Speaker 1: these crazy structured notes that were sort of leverage bets 249 00:13:47,600 --> 00:13:50,000 Speaker 1: on volatility, they ended up getting burned a lot more 250 00:13:50,040 --> 00:13:53,360 Speaker 1: than the retail investors who actually bought these things. So 251 00:13:53,640 --> 00:13:56,200 Speaker 1: it was a kind of a bit of poetic justice. Yeah. 252 00:13:56,320 --> 00:13:58,840 Speaker 1: I really loved this story. It was really nicely done 253 00:13:58,840 --> 00:14:02,199 Speaker 1: with a lot of colors. So that mine. Leanna is awesome. 254 00:14:02,320 --> 00:14:05,080 Speaker 1: She just writes these deep dives that I wish I 255 00:14:05,120 --> 00:14:08,720 Speaker 1: had the time or brain to do. Um. I hope 256 00:14:08,760 --> 00:14:12,800 Speaker 1: she's listening because I think she's great. And by the way, Yakob, 257 00:14:12,880 --> 00:14:15,800 Speaker 1: you bring up a good point with every two or 258 00:14:15,840 --> 00:14:18,080 Speaker 1: three years to get a teachable moment in et s, 259 00:14:18,120 --> 00:14:20,320 Speaker 1: I think and X I V was that one like 260 00:14:20,400 --> 00:14:22,800 Speaker 1: three years ago, and it kind of did correct itself. 261 00:14:22,800 --> 00:14:25,400 Speaker 1: They neutered all the leverage ones. People worried about t 262 00:14:25,520 --> 00:14:27,240 Speaker 1: VIX now that did get up to about I think 263 00:14:27,240 --> 00:14:29,920 Speaker 1: it was seven billion in March because it was just 264 00:14:30,080 --> 00:14:32,040 Speaker 1: I think it returned two thousand percent in like three 265 00:14:32,040 --> 00:14:34,680 Speaker 1: months or two months or something. But then that's also 266 00:14:34,800 --> 00:14:39,480 Speaker 1: gone now and so the real Vixie, you know, uh, 267 00:14:40,360 --> 00:14:44,520 Speaker 1: leveraged kind of potential problem. Child's children are pretty much 268 00:14:44,560 --> 00:14:47,640 Speaker 1: gone at this point, although I think there's two, there's 269 00:14:47,680 --> 00:14:50,240 Speaker 1: a couple in the hopper. But what was a problem 270 00:14:50,240 --> 00:14:52,360 Speaker 1: in one of I thought Katie did a great job 271 00:14:52,400 --> 00:14:55,000 Speaker 1: covering this one was USO. That was the teachable moment 272 00:14:55,080 --> 00:14:57,400 Speaker 1: this year? Um, Katie, you want to talk about us 273 00:14:57,480 --> 00:15:00,560 Speaker 1: so real quick and what happened that I'm STI scarred? 274 00:15:00,680 --> 00:15:04,480 Speaker 1: I would say it definitely was a teachable moment. But basically, 275 00:15:04,760 --> 00:15:08,640 Speaker 1: USO invested in the front month oil contract, which, as 276 00:15:08,680 --> 00:15:13,600 Speaker 1: we know in April went negative negative thirty seven per barrel, 277 00:15:13,680 --> 00:15:16,360 Speaker 1: which is just hard to wrap your mind around. So 278 00:15:16,520 --> 00:15:20,880 Speaker 1: USL was scrambling to re shift its holdings, which contracts 279 00:15:21,120 --> 00:15:25,160 Speaker 1: it uh it invested in, and it it did that. Um, 280 00:15:25,200 --> 00:15:28,760 Speaker 1: but I believe it's now still under investigation by the SEC. 281 00:15:29,000 --> 00:15:31,160 Speaker 1: Eric maybe jump in here because I might get it 282 00:15:31,160 --> 00:15:35,080 Speaker 1: wrong over whether it properly disclosed to its investors what 283 00:15:35,200 --> 00:15:37,080 Speaker 1: it was doing with its holdings and how it was 284 00:15:37,120 --> 00:15:43,120 Speaker 1: shifting them around. Yeah, I believe that's still a open investigation. 285 00:15:43,120 --> 00:15:44,640 Speaker 1: That might be a rough word for it. But I'm 286 00:15:44,640 --> 00:15:47,120 Speaker 1: not sure they're going to be liable because if you 287 00:15:47,200 --> 00:15:50,720 Speaker 1: read the prospectives they talk about this being possible, um, 288 00:15:50,760 --> 00:15:54,640 Speaker 1: but it was. It was just oil mcgeddon. Nobody thought 289 00:15:54,640 --> 00:15:58,600 Speaker 1: that futures could go negative, and the idea was, you know, 290 00:15:58,680 --> 00:16:00,480 Speaker 1: do we let futures go negative and then we'll have 291 00:16:00,520 --> 00:16:03,480 Speaker 1: to owe people money like the people, or do we 292 00:16:03,840 --> 00:16:07,040 Speaker 1: completely newter the exposure and water it down. And they 293 00:16:07,120 --> 00:16:10,400 Speaker 1: chose the safe route. And so the ultimately the problem 294 00:16:10,400 --> 00:16:12,280 Speaker 1: with it then was that people who who wanted it 295 00:16:12,560 --> 00:16:15,640 Speaker 1: for the hardcore front month exposure didn't get it. They 296 00:16:15,680 --> 00:16:18,200 Speaker 1: weren't getting that oil rebound like they wanted to. So 297 00:16:18,480 --> 00:16:21,160 Speaker 1: the whole thing was a big mess. USO ties into 298 00:16:21,200 --> 00:16:24,360 Speaker 1: the retail story because it was a very popular stock 299 00:16:24,440 --> 00:16:26,880 Speaker 1: on not a stock and et up on robin Hood 300 00:16:26,880 --> 00:16:29,280 Speaker 1: when you could still track their day to day holdings. 301 00:16:29,600 --> 00:16:32,880 Speaker 1: People just kept piling into US. So even as all 302 00:16:32,960 --> 00:16:36,760 Speaker 1: this turmoil was unfolding, because I guess retail investors were 303 00:16:36,800 --> 00:16:39,480 Speaker 1: like this invests in oil. I want to bet on 304 00:16:39,480 --> 00:16:42,120 Speaker 1: the bottom and oil here we go. And Joel, you 305 00:16:42,160 --> 00:16:45,040 Speaker 1: know what's interesting about oil. It's that's one of the 306 00:16:45,080 --> 00:16:48,120 Speaker 1: things I'll get texts about from old college friends and stuff, 307 00:16:48,280 --> 00:16:50,240 Speaker 1: when they see oil go down that much that it 308 00:16:50,280 --> 00:16:53,320 Speaker 1: makes like the CBS Nightly News with Lester Holt or 309 00:16:53,400 --> 00:16:56,040 Speaker 1: whatever they want in they feel like they're Warren Buffett. 310 00:16:56,080 --> 00:16:58,720 Speaker 1: They're like, I'm I'm buying at the bottom and USO 311 00:16:58,840 --> 00:17:00,800 Speaker 1: is kind of the only way to get that exposure. 312 00:17:01,360 --> 00:17:03,680 Speaker 1: And again, a teachable moment. I doubt we're going to 313 00:17:03,720 --> 00:17:06,560 Speaker 1: see that kind of frenzy next time. It sounds like 314 00:17:06,600 --> 00:17:09,880 Speaker 1: something your dad would call you about. Oh yeah, he does. 315 00:17:10,000 --> 00:17:12,920 Speaker 1: Yeah that. I don't know if that has enough for him, 316 00:17:12,920 --> 00:17:17,479 Speaker 1: though he likes even Yeah, that's it's probably two for him. 317 00:17:18,800 --> 00:17:20,600 Speaker 1: By the way, he keeps telling me about t vix 318 00:17:20,640 --> 00:17:22,840 Speaker 1: and how low it's gotten in his account because he 319 00:17:22,920 --> 00:17:26,040 Speaker 1: keeps reverse splitting, and uh, we have a lot of 320 00:17:26,040 --> 00:17:27,840 Speaker 1: fun on that. Yeah, I'm like, hey, but it's up. 321 00:17:28,160 --> 00:17:31,119 Speaker 1: I said t vix went up like two, and he 322 00:17:31,200 --> 00:17:34,199 Speaker 1: basically looked at it at the percentage he went up 323 00:17:34,240 --> 00:17:37,080 Speaker 1: was maybe like one percent, because that's how much he 324 00:17:37,080 --> 00:17:39,399 Speaker 1: had lost over the five years he's held it. Anyway, 325 00:17:39,400 --> 00:17:41,760 Speaker 1: the whole thing was it was funny. There's an episode 326 00:17:41,800 --> 00:17:45,160 Speaker 1: where we interview my dad about his experience with t vix, 327 00:17:45,600 --> 00:17:49,080 Speaker 1: and it's a classic case of you know what Claire 328 00:17:49,119 --> 00:17:51,360 Speaker 1: was talking about, how you have real people who buy 329 00:17:51,359 --> 00:17:53,600 Speaker 1: this stuff. He bought it because he thought Hillary was 330 00:17:53,600 --> 00:17:56,840 Speaker 1: gonna win and the market would just plunge. And he said, 331 00:17:56,840 --> 00:17:58,760 Speaker 1: what will go up to most if the market plunges? 332 00:17:58,800 --> 00:18:01,000 Speaker 1: And I said, well, t vix, but you gotta sell 333 00:18:01,040 --> 00:18:03,800 Speaker 1: it whether it works or not, in a week, and 334 00:18:03,840 --> 00:18:10,720 Speaker 1: he just didn't sell. It's a long term investor in TVA. Okay, Katie, 335 00:18:11,000 --> 00:18:14,000 Speaker 1: uh Uso? Was that? Was that your jealousy pick or 336 00:18:14,040 --> 00:18:16,920 Speaker 1: did you have something else? I think we did a 337 00:18:16,920 --> 00:18:20,240 Speaker 1: pretty good job covering Uso, so I'm actually my jealousy 338 00:18:20,280 --> 00:18:23,480 Speaker 1: pick is pretty recent. It's from earlier this month. It's 339 00:18:23,560 --> 00:18:26,439 Speaker 1: also from the Wall Street Journal, so Claire, we have 340 00:18:26,480 --> 00:18:31,240 Speaker 1: our targets, but it's by Shanna Schoenberger and it's on 341 00:18:31,400 --> 00:18:34,760 Speaker 1: a study that it's really fascinating. I wanted to write 342 00:18:34,800 --> 00:18:37,160 Speaker 1: about it, I just didn't get time. It was released 343 00:18:37,160 --> 00:18:40,280 Speaker 1: in October and it's about target date funds, which are 344 00:18:40,720 --> 00:18:44,159 Speaker 1: it's a one point for trillion dollar industry. It's extremely 345 00:18:44,200 --> 00:18:48,159 Speaker 1: important and uh it's it's exactly what it sounds like. 346 00:18:48,200 --> 00:18:52,600 Speaker 1: You know, investors pick a target date fund with a 347 00:18:52,680 --> 00:18:57,040 Speaker 1: specific date further retirement savings, and it glides them towards 348 00:18:57,080 --> 00:19:02,680 Speaker 1: that date and gradually shifts them into bonds. Yes, exactly, 349 00:19:02,720 --> 00:19:05,400 Speaker 1: you can just set it and forget it. You're on autopilot. 350 00:19:05,800 --> 00:19:09,159 Speaker 1: But this study was from David Brown, a professor at 351 00:19:09,200 --> 00:19:12,760 Speaker 1: the University of Arizona and Sean Davies, professor at the 352 00:19:12,840 --> 00:19:18,120 Speaker 1: University of Colorado at Boulder, and they found basically that 353 00:19:18,560 --> 00:19:22,280 Speaker 1: target date funds sponsors, because target date funds are funds 354 00:19:22,280 --> 00:19:25,840 Speaker 1: of funds, they charged basically two fees, and because of 355 00:19:25,880 --> 00:19:29,439 Speaker 1: those fees, they charged nearly two point five billion in 356 00:19:29,600 --> 00:19:33,160 Speaker 1: XS fees in seen alone versus what you could save 357 00:19:33,200 --> 00:19:36,119 Speaker 1: by just replicating those portfolios with a e t F. 358 00:19:36,680 --> 00:19:39,560 Speaker 1: So it just goes to show that the retire the 359 00:19:39,560 --> 00:19:43,800 Speaker 1: American retirement system could be improved if perhaps of e 360 00:19:43,920 --> 00:19:45,760 Speaker 1: t f s were allowed in for oh one case, 361 00:19:46,520 --> 00:19:50,560 Speaker 1: but just an incredibly important study and story, and she 362 00:19:50,640 --> 00:19:53,440 Speaker 1: did a great job. Added additional reporting where she talked 363 00:19:53,480 --> 00:19:56,400 Speaker 1: to some of the biggest target date fund sponsors, Vanguard 364 00:19:56,440 --> 00:20:00,159 Speaker 1: Fidelity and basically got them to defend their fees. So 365 00:20:00,640 --> 00:20:03,560 Speaker 1: great article. I wish I had written it, but she 366 00:20:03,920 --> 00:20:06,320 Speaker 1: beat me to the punch. Yeah. I think that's a 367 00:20:06,680 --> 00:20:10,920 Speaker 1: um a really good example as well of something that 368 00:20:11,040 --> 00:20:14,119 Speaker 1: I wish we could have covered UM. We definitely have 369 00:20:14,280 --> 00:20:17,800 Speaker 1: our our target set out for one about who we 370 00:20:17,840 --> 00:20:20,880 Speaker 1: have to be. But I think it's a tremendously Like 371 00:20:20,920 --> 00:20:23,720 Speaker 1: you said, it's UM one point four trillion, so it's 372 00:20:23,880 --> 00:20:27,199 Speaker 1: tremendously important for us to cover that and to be 373 00:20:27,280 --> 00:20:30,960 Speaker 1: talking about it. And one thing I will add about 374 00:20:30,960 --> 00:20:33,960 Speaker 1: the study is UM. You know, they estimate from that 375 00:20:34,040 --> 00:20:37,440 Speaker 1: two point five billion and XS fees, investors could save 376 00:20:37,480 --> 00:20:40,600 Speaker 1: about one percent per year by just replicating with E 377 00:20:40,680 --> 00:20:43,320 Speaker 1: t s. But that does kind of ignore the set 378 00:20:43,400 --> 00:20:46,200 Speaker 1: it and forget it mentality. You know, investors probably don't 379 00:20:46,200 --> 00:20:50,160 Speaker 1: want to be working to recreate these portfolios all the time, 380 00:20:50,240 --> 00:20:53,119 Speaker 1: but I mean it's still hugely important if you're saving 381 00:20:53,160 --> 00:20:56,359 Speaker 1: for retirement, that one percent matters a lot. And also 382 00:20:56,400 --> 00:20:59,840 Speaker 1: say that it seems to me that there's the et 383 00:21:00,040 --> 00:21:03,160 Speaker 1: has to become so popular. They trade, there's so much 384 00:21:03,160 --> 00:21:06,840 Speaker 1: innovation that most of the media has really covered them 385 00:21:06,840 --> 00:21:09,080 Speaker 1: to the point where ten years ago there was hardly 386 00:21:09,119 --> 00:21:13,760 Speaker 1: any coverage. Now it's very much matured into full coverage. 387 00:21:14,080 --> 00:21:15,960 Speaker 1: But I feel like they've left the mutual fund world 388 00:21:15,960 --> 00:21:19,080 Speaker 1: too much. There's not enough eiveballs and lights being shined 389 00:21:19,119 --> 00:21:21,000 Speaker 1: and what is still ten trillion dollars. There's a lot 390 00:21:21,040 --> 00:21:23,639 Speaker 1: of things going on there, and that's interesting to me, 391 00:21:24,200 --> 00:21:28,080 Speaker 1: given that mutual funds still have double uh if you 392 00:21:28,080 --> 00:21:30,119 Speaker 1: have money market funds more than double what E t 393 00:21:30,280 --> 00:21:33,800 Speaker 1: F s have uh, yet they are you know, get 394 00:21:33,880 --> 00:21:35,439 Speaker 1: maybe I don't know a third of the coverage, and 395 00:21:35,480 --> 00:21:37,440 Speaker 1: so it's good to see some of that, especially the 396 00:21:37,480 --> 00:21:39,760 Speaker 1: fore when k plans that you know why, because that 397 00:21:39,760 --> 00:21:41,600 Speaker 1: stuff isn't gonna get a lot of clicks. I'm sorry, 398 00:21:41,680 --> 00:21:44,600 Speaker 1: it's just target date fund this that, or it's just 399 00:21:44,640 --> 00:21:46,760 Speaker 1: not going to light it up. But it's good stuff. 400 00:21:47,280 --> 00:21:50,720 Speaker 1: I'll comfort myself with that. I also find that weird, Eric, 401 00:21:50,760 --> 00:21:53,359 Speaker 1: because particularly around March, when we were all talking about 402 00:21:53,440 --> 00:21:55,760 Speaker 1: like the l QD sort of dislocation, a lot of 403 00:21:55,800 --> 00:21:58,040 Speaker 1: that stuff was happening in mutual funds, much worse than 404 00:21:58,080 --> 00:21:59,560 Speaker 1: it was in E t F and there was really 405 00:21:59,560 --> 00:22:01,199 Speaker 1: no one or out to cover it except for like 406 00:22:01,280 --> 00:22:03,359 Speaker 1: you guys at b I. So I'm struck by that 407 00:22:03,400 --> 00:22:12,479 Speaker 1: as well. Okay, wait, Eric, you're gonna put on your 408 00:22:12,480 --> 00:22:16,760 Speaker 1: stand in Clauds costume because Claire Jacob Katie He's got 409 00:22:16,760 --> 00:22:20,080 Speaker 1: a gift for you. I do what what is it, Eric. 410 00:22:20,240 --> 00:22:22,520 Speaker 1: So I went through all of your articles and picked 411 00:22:22,600 --> 00:22:25,280 Speaker 1: one of each I get, I get updates of everything 412 00:22:25,280 --> 00:22:27,720 Speaker 1: you write, so you do great work. And I went 413 00:22:27,760 --> 00:22:29,359 Speaker 1: back and look through all of your articles to pick 414 00:22:29,400 --> 00:22:31,800 Speaker 1: out one of each of yours that I was jealous 415 00:22:31,800 --> 00:22:35,399 Speaker 1: of and just feel like, really nailed it. And so 416 00:22:35,520 --> 00:22:39,280 Speaker 1: I guess I'll start with Claire um. Claire's coverage of 417 00:22:39,320 --> 00:22:42,240 Speaker 1: Cathy Wood has been monumental to me. That's probably the 418 00:22:42,240 --> 00:22:44,960 Speaker 1: story of the year. Again, you know, seventeen billion of 419 00:22:45,000 --> 00:22:48,240 Speaker 1: assets and ARC isn't that much percentage wise, but she's 420 00:22:48,320 --> 00:22:51,320 Speaker 1: just bucked so many odds that you you just can't 421 00:22:51,320 --> 00:22:54,120 Speaker 1: not cover this story. And the one that I really 422 00:22:54,119 --> 00:22:57,000 Speaker 1: liked was Cathy Wood's fun bought more Tesla after shares 423 00:22:57,040 --> 00:23:01,800 Speaker 1: got quote slapped and she had us. See, you guys 424 00:23:01,800 --> 00:23:03,560 Speaker 1: can quote the people, and that's why I think you 425 00:23:03,640 --> 00:23:05,280 Speaker 1: had a lot of value. You can also do stuff 426 00:23:05,320 --> 00:23:08,040 Speaker 1: quicker than weekend in research, so you had you were 427 00:23:08,080 --> 00:23:10,439 Speaker 1: right on this article. Kathy shares her holdings every day 428 00:23:10,480 --> 00:23:13,200 Speaker 1: and she bought more when Tesla went down in September, 429 00:23:14,080 --> 00:23:15,960 Speaker 1: And the quote you have here is I was happy 430 00:23:15,960 --> 00:23:18,639 Speaker 1: it got slapped. We wait for those sorts of delays 431 00:23:18,680 --> 00:23:21,479 Speaker 1: where there's outright fear. If we think this thought has 432 00:23:21,560 --> 00:23:24,320 Speaker 1: dropped enough, we'll move in, and we did. Tesla has 433 00:23:24,359 --> 00:23:26,639 Speaker 1: gone up fifty six per cent since then, and it 434 00:23:26,720 --> 00:23:29,640 Speaker 1: really just, I don't know, adds to the whole mystique 435 00:23:29,680 --> 00:23:32,800 Speaker 1: of Kathy would just being like probably the zeitgeist, the 436 00:23:32,840 --> 00:23:35,720 Speaker 1: active manager of this era. And I think you've had, 437 00:23:35,800 --> 00:23:37,520 Speaker 1: you know, half a dozen articles on her that really 438 00:23:37,600 --> 00:23:39,639 Speaker 1: hit the spot, that one in particular. UM, thank you. 439 00:23:39,720 --> 00:23:42,080 Speaker 1: It's been really fun to cover her and to see 440 00:23:42,080 --> 00:23:44,639 Speaker 1: what she's doing. And I think especially you know, with 441 00:23:44,760 --> 00:23:47,840 Speaker 1: journalism in general, it's all about the people sort of 442 00:23:47,880 --> 00:23:49,800 Speaker 1: behind the market moves and these things like that, but 443 00:23:49,960 --> 00:23:53,240 Speaker 1: especially when it's an active manager who's actively making these 444 00:23:53,280 --> 00:23:57,080 Speaker 1: decisions to go into tesla um or things of that nature. 445 00:23:57,119 --> 00:23:59,840 Speaker 1: And so that's why I've really enjoyed being able to 446 00:23:59,880 --> 00:24:02,439 Speaker 1: in of you Kathy and sort of figure out and 447 00:24:02,440 --> 00:24:06,160 Speaker 1: write about what she's thinking behind some of these moves. UM. 448 00:24:06,200 --> 00:24:10,240 Speaker 1: And Okay, Yacob, speaking of arc I think you know 449 00:24:10,320 --> 00:24:13,040 Speaker 1: I'm going with this. Jacob had an article. I tweeted 450 00:24:13,040 --> 00:24:16,920 Speaker 1: this out and rarely my tweets go quote viral viral. 451 00:24:16,960 --> 00:24:19,520 Speaker 1: For me, is like maybe fifty retweets. For other people, 452 00:24:19,520 --> 00:24:23,199 Speaker 1: it's probably over a thousand. But um, most of our 453 00:24:23,240 --> 00:24:25,479 Speaker 1: stuff is too wonky to get much love. But Yakob 454 00:24:25,480 --> 00:24:29,199 Speaker 1: I tweeted out your JP Morgan article and people loved it. 455 00:24:29,240 --> 00:24:32,000 Speaker 1: And basically, I don't even know how you found this. 456 00:24:32,040 --> 00:24:33,800 Speaker 1: I'd like to know, but the article is basically the 457 00:24:33,840 --> 00:24:37,159 Speaker 1: title is JP Morgan offers you only Live once or 458 00:24:37,240 --> 00:24:41,040 Speaker 1: yolo trade to bet on ark ETFs where they basically, 459 00:24:41,840 --> 00:24:45,040 Speaker 1: you know, these Wall Street banks designed these structure products 460 00:24:45,040 --> 00:24:47,840 Speaker 1: for their high net worth clients or institutions, and in 461 00:24:47,840 --> 00:24:50,000 Speaker 1: this case, they made a structured product tied to e 462 00:24:50,119 --> 00:24:53,520 Speaker 1: t S from arc Um that basically packaged three of 463 00:24:53,600 --> 00:24:56,199 Speaker 1: the e t F s leverage one point five times 464 00:24:56,200 --> 00:24:59,600 Speaker 1: over six years. Um, it makes sense to me that 465 00:24:59,640 --> 00:25:02,240 Speaker 1: they would do this. I think we actually had direction 466 00:25:02,240 --> 00:25:04,640 Speaker 1: on e t F i Q once and I jokingly said, 467 00:25:04,680 --> 00:25:07,000 Speaker 1: when's the three x R e t F coming out? 468 00:25:07,119 --> 00:25:09,600 Speaker 1: Because normally when an e t F breaks through like 469 00:25:09,640 --> 00:25:11,159 Speaker 1: that and gets a couple of billion, you see a 470 00:25:11,240 --> 00:25:14,520 Speaker 1: leverage version of it. And so they kind of joked 471 00:25:14,560 --> 00:25:17,640 Speaker 1: and didn't say anything. But I'm not surprised that this 472 00:25:17,720 --> 00:25:21,040 Speaker 1: is happening. But it really struck a nerve with people, 473 00:25:21,160 --> 00:25:22,919 Speaker 1: and I'm just curious how you found the article and 474 00:25:22,920 --> 00:25:27,640 Speaker 1: maybe if you want to explain how the product works. Yeah, sure, Um, 475 00:25:27,680 --> 00:25:29,679 Speaker 1: I mean these things this was a publicly you know, 476 00:25:29,800 --> 00:25:32,600 Speaker 1: SEC registered note. So I have a little search that 477 00:25:32,680 --> 00:25:35,120 Speaker 1: I have every once in a while, I I take 478 00:25:35,160 --> 00:25:38,200 Speaker 1: a little spin through the latest freaky you know, Wall 479 00:25:38,240 --> 00:25:41,040 Speaker 1: Street inventions, and um, yeah, I spotted arc. I had 480 00:25:41,080 --> 00:25:43,480 Speaker 1: never seen anything like this one because it was linked 481 00:25:43,480 --> 00:25:45,040 Speaker 1: to three RK E t F s and they're they're 482 00:25:45,080 --> 00:25:48,480 Speaker 1: certainly having like there's zeitgeist moment um. But I also 483 00:25:48,600 --> 00:25:51,560 Speaker 1: noticed it was crazy, like it's a six year note 484 00:25:51,880 --> 00:25:54,760 Speaker 1: leveraged one and a half times, Like like Eric, you 485 00:25:54,840 --> 00:25:57,400 Speaker 1: were talking about not holding these leveraged you know, vix 486 00:25:57,480 --> 00:25:59,359 Speaker 1: etp s for longer than a week, Like can you 487 00:25:59,400 --> 00:26:02,600 Speaker 1: imagine who holding something for six years that's a leverage 488 00:26:02,680 --> 00:26:04,679 Speaker 1: one and a half times. I mean, it's just wild. 489 00:26:04,720 --> 00:26:06,679 Speaker 1: I mean I fell in love as soon as I 490 00:26:06,680 --> 00:26:09,800 Speaker 1: saw it. Um. And so yeah, we we did this story. 491 00:26:09,840 --> 00:26:13,399 Speaker 1: And interestingly, a guy actually wrote in afterwards and I 492 00:26:13,440 --> 00:26:15,200 Speaker 1: don't think I'm gonna be able to do this story, 493 00:26:15,320 --> 00:26:16,680 Speaker 1: so I might as well kind of give him a 494 00:26:16,680 --> 00:26:20,000 Speaker 1: shout out on this financial advisor from Princeton, New Jersey, 495 00:26:20,040 --> 00:26:22,040 Speaker 1: which is not far from where you are. Eric wrote 496 00:26:22,080 --> 00:26:24,880 Speaker 1: in and said, hey, I was the one who came 497 00:26:24,960 --> 00:26:27,440 Speaker 1: up with this structure. I went to Ben P. Parry 498 00:26:27,520 --> 00:26:30,639 Speaker 1: Bah back in October to build me this exact same 499 00:26:30,680 --> 00:26:33,760 Speaker 1: note UM and he was like, I want credit, you know. 500 00:26:34,240 --> 00:26:37,040 Speaker 1: And and so Dan over at White Night Strategic Wealth 501 00:26:37,080 --> 00:26:40,159 Speaker 1: Advisors actually came up with this structure back in October 502 00:26:40,480 --> 00:26:42,960 Speaker 1: UM and and yeah, he told me like this is 503 00:26:42,960 --> 00:26:46,080 Speaker 1: a sleeve in his UM in some of his investors portfolio, 504 00:26:46,119 --> 00:26:48,399 Speaker 1: like they're already exposed to ARC. But he was like, 505 00:26:48,520 --> 00:26:50,679 Speaker 1: look why not, Like it was a kind of a 506 00:26:50,720 --> 00:26:52,879 Speaker 1: Yolow play. It's like, why not make this into a 507 00:26:52,880 --> 00:26:56,280 Speaker 1: tiny little sleeve of their portfolio. He's really a big 508 00:26:56,320 --> 00:26:58,399 Speaker 1: fan of Cathy would and he thinks the fact that 509 00:26:58,440 --> 00:27:02,120 Speaker 1: it's actively managed UM means that they're gonna just keep 510 00:27:02,160 --> 00:27:04,920 Speaker 1: on winning. You know that that's his sort of justification. 511 00:27:05,080 --> 00:27:07,440 Speaker 1: So anyway, yeah, it was. It was a weird story, 512 00:27:07,520 --> 00:27:12,240 Speaker 1: but thanks for highlighting it. That's amazing. That is amazing, 513 00:27:12,320 --> 00:27:17,480 Speaker 1: isn't it? Um Sign of the times? I the skeptic 514 00:27:17,760 --> 00:27:20,080 Speaker 1: of that UM and which I think you you had 515 00:27:20,119 --> 00:27:23,639 Speaker 1: in the stories I recall yago was that it also 516 00:27:23,840 --> 00:27:26,520 Speaker 1: is like, could you imagine a better indicator for the 517 00:27:26,920 --> 00:27:29,720 Speaker 1: top of the market than than that product? Yeah? Yeah, 518 00:27:29,760 --> 00:27:32,000 Speaker 1: And and in fairness that the terms. I I showed 519 00:27:32,000 --> 00:27:33,840 Speaker 1: it to a couple of you know, structured product geeks, 520 00:27:33,840 --> 00:27:35,680 Speaker 1: and they were like, no, these are not good terms, 521 00:27:35,760 --> 00:27:37,959 Speaker 1: you know, they're They're just like you will get screwed 522 00:27:37,960 --> 00:27:41,160 Speaker 1: on this note eventually, you know. But hey, it's it's 523 00:27:41,200 --> 00:27:45,440 Speaker 1: it's a fun ride while it lasts. Okay, So for Katie, look, 524 00:27:45,440 --> 00:27:47,639 Speaker 1: there's so there's so much to choose from Katie. It 525 00:27:47,720 --> 00:27:50,280 Speaker 1: was an embarrassment of I thought. I thought he was 526 00:27:50,280 --> 00:27:53,440 Speaker 1: gonna say, really, it was a really bad year, Katie, 527 00:27:53,480 --> 00:27:55,800 Speaker 1: it was a really bad year. You gotta pick it 528 00:27:55,880 --> 00:28:01,680 Speaker 1: up next year. But yeah, so look for of all um, 529 00:28:01,800 --> 00:28:04,439 Speaker 1: the headline of yours I like the best. So this 530 00:28:04,480 --> 00:28:06,800 Speaker 1: isn't the article, but just the headline this. I read 531 00:28:06,800 --> 00:28:08,080 Speaker 1: this and I was like, oh my god, there's so 532 00:28:08,160 --> 00:28:11,640 Speaker 1: much going on here. It's almost like sometimes your ability 533 00:28:11,680 --> 00:28:15,480 Speaker 1: to make the headlines seem downright Shakespearean is amazing. So 534 00:28:15,520 --> 00:28:19,359 Speaker 1: here's the headline about USO giant fund at heart of 535 00:28:19,400 --> 00:28:24,280 Speaker 1: oil storm. Loses most cash in four years. I just 536 00:28:24,840 --> 00:28:27,480 Speaker 1: I don't know. I just love that, Like the the 537 00:28:27,600 --> 00:28:30,919 Speaker 1: density of that headline is and the package drama in 538 00:28:30,960 --> 00:28:34,080 Speaker 1: there is amazing. So that's just that. That was my 539 00:28:34,119 --> 00:28:37,359 Speaker 1: favorite headline of yours. Now the story I like the 540 00:28:37,359 --> 00:28:43,000 Speaker 1: best is this one that was that was the stocking. 541 00:28:43,120 --> 00:28:47,840 Speaker 1: This is the big present with the special Santa Claus wrapping. Um. Okay, 542 00:28:48,160 --> 00:28:52,320 Speaker 1: Wall Street theories on billions slashing through Schwab funds Okay, 543 00:28:52,440 --> 00:28:55,520 Speaker 1: not the most interesting topic. But the approach here is 544 00:28:55,560 --> 00:28:57,520 Speaker 1: fascinating and it's something we can't do and b I 545 00:28:57,600 --> 00:28:59,840 Speaker 1: so I'm jealous of this, but I also find that 546 00:29:00,160 --> 00:29:03,560 Speaker 1: smart of you. We don't know who's doing what in 547 00:29:03,640 --> 00:29:05,640 Speaker 1: e T s. This is one of the reason institutions 548 00:29:05,640 --> 00:29:08,760 Speaker 1: love using them. There's there's no trace and so every 549 00:29:08,760 --> 00:29:11,320 Speaker 1: time you see these flows, it's like a Sherlock Holmes mystery, 550 00:29:11,400 --> 00:29:13,840 Speaker 1: and you you've got to try to solve it. Now, 551 00:29:14,600 --> 00:29:17,840 Speaker 1: you could just sort of take a shot, or I 552 00:29:17,840 --> 00:29:20,800 Speaker 1: don't know, uh, go with the best theory. But I 553 00:29:20,880 --> 00:29:23,720 Speaker 1: love that you print all the theories. So you go 554 00:29:23,800 --> 00:29:25,560 Speaker 1: down here, you look at the flows, and then you've 555 00:29:25,600 --> 00:29:30,280 Speaker 1: got Okay, here's what James Pillow at Moore's and Kabat says, 556 00:29:30,320 --> 00:29:32,800 Speaker 1: I'm probably butchering that name. Here's what Nature a c 557 00:29:32,920 --> 00:29:35,160 Speaker 1: at the E T F Store says, Here's what Matt 558 00:29:35,200 --> 00:29:40,360 Speaker 1: Haley Maley at Miller says, Here's what Athanacios that's from 559 00:29:40,400 --> 00:29:42,680 Speaker 1: b I well, here's what he says, and here's what 560 00:29:42,720 --> 00:29:45,120 Speaker 1: Todd says. So you know, the reader can kind of 561 00:29:45,160 --> 00:29:48,520 Speaker 1: read all these and to me, this is just this 562 00:29:49,120 --> 00:29:51,800 Speaker 1: shines a light on the whole concept of flows and 563 00:29:51,880 --> 00:29:54,360 Speaker 1: E t F and how you never really ever know 564 00:29:54,600 --> 00:29:56,600 Speaker 1: unless the person who did it steps forward, and they 565 00:29:56,640 --> 00:29:59,520 Speaker 1: never do. And this happened recently with Claire's Voo article 566 00:30:00,080 --> 00:30:03,040 Speaker 1: saw eight billion dollars out and we you know, you 567 00:30:03,080 --> 00:30:04,920 Speaker 1: guys both were trying to put that together. Can you 568 00:30:04,960 --> 00:30:07,640 Speaker 1: talk a little bit about just trying to solve these 569 00:30:07,680 --> 00:30:11,120 Speaker 1: mysteries when it comes to flows. Yeah, well, credit were 570 00:30:11,160 --> 00:30:13,560 Speaker 1: credits do? I wrote that shop story with Claire, and 571 00:30:14,440 --> 00:30:17,440 Speaker 1: I wrote that Voo article with Claire, And I mean, 572 00:30:17,480 --> 00:30:19,160 Speaker 1: I want to give a shout out to our editors 573 00:30:19,160 --> 00:30:22,120 Speaker 1: who are I really appreciate that they let us have 574 00:30:22,160 --> 00:30:25,720 Speaker 1: that flexibility, because there's sometimes when Claire and I are 575 00:30:25,760 --> 00:30:28,800 Speaker 1: just chasing our tails and we do end up with 576 00:30:28,840 --> 00:30:32,000 Speaker 1: like five different theories for what could be behind a 577 00:30:32,080 --> 00:30:35,760 Speaker 1: huge movement, and it's impossible to know unless we hear 578 00:30:35,760 --> 00:30:37,480 Speaker 1: it from the horse's mouth, and a lot of the 579 00:30:37,520 --> 00:30:40,160 Speaker 1: times we don't even know who the horse is. So 580 00:30:40,440 --> 00:30:42,880 Speaker 1: I've I just love that format for when you do 581 00:30:43,000 --> 00:30:46,400 Speaker 1: see just you know, a huge outflow that everyone's talking about, 582 00:30:46,480 --> 00:30:49,959 Speaker 1: there's not one unifying theory that we're able to just 583 00:30:50,040 --> 00:30:52,480 Speaker 1: break it out and be like, you're the best guesses, 584 00:30:53,120 --> 00:30:56,440 Speaker 1: choose your own adventure, and uh, most of the times, 585 00:30:56,680 --> 00:30:59,120 Speaker 1: I mean, we get a lot of engagement from those articles, 586 00:30:59,120 --> 00:31:02,280 Speaker 1: which I also really appreciate, and you can get a 587 00:31:02,280 --> 00:31:05,160 Speaker 1: pretty good sense of what's going on. Yeah, I think 588 00:31:05,160 --> 00:31:07,800 Speaker 1: that adds a value to our readers too, to be 589 00:31:07,840 --> 00:31:09,920 Speaker 1: able to look at and say, hey, these are some 590 00:31:10,000 --> 00:31:13,840 Speaker 1: of the theories behind it um and that gives some 591 00:31:13,920 --> 00:31:16,200 Speaker 1: sort of more insight into our thinking too, instead of 592 00:31:16,280 --> 00:31:18,880 Speaker 1: us just sort of pretending like we know what's going on, 593 00:31:18,880 --> 00:31:21,840 Speaker 1: because a lot of times we just it's impossible to 594 00:31:21,880 --> 00:31:25,320 Speaker 1: actually know. And that wasn't this is a new thing, 595 00:31:25,440 --> 00:31:27,600 Speaker 1: this didn't happen, this is a So that's why I 596 00:31:27,600 --> 00:31:29,040 Speaker 1: wanted to point it out. I think it's a great 597 00:31:29,240 --> 00:31:32,960 Speaker 1: evolution of the articles rather than just as you said, 598 00:31:32,960 --> 00:31:34,440 Speaker 1: I think it's good just put all the theories out 599 00:31:34,480 --> 00:31:36,400 Speaker 1: there that that's the truth. The truth is you don't know, 600 00:31:36,520 --> 00:31:39,920 Speaker 1: and but here's the theories I did. Audience can be 601 00:31:39,960 --> 00:31:48,720 Speaker 1: the judge. All right. Congratulations to our Jealousy list honorees. Eric, 602 00:31:48,760 --> 00:31:51,000 Speaker 1: thank you for playing Santa Claus. You did a very 603 00:31:51,000 --> 00:31:55,920 Speaker 1: good job. Special special thing that was lame. That was 604 00:31:55,920 --> 00:31:58,960 Speaker 1: a lame ho ho by the way, joke just I 605 00:31:59,000 --> 00:32:01,440 Speaker 1: went to the mall on Friday morning. Every year I 606 00:32:01,440 --> 00:32:03,360 Speaker 1: go to the mall on a weekday morning to beat 607 00:32:03,400 --> 00:32:05,480 Speaker 1: the system and do Christma shoping when there's nobody there, 608 00:32:06,040 --> 00:32:08,480 Speaker 1: and I saw the Santa and it is behind these 609 00:32:08,480 --> 00:32:10,960 Speaker 1: plexiglass and they put the kids in front of the 610 00:32:11,000 --> 00:32:13,600 Speaker 1: glass so that maybe you don't see the glass. And 611 00:32:13,640 --> 00:32:16,200 Speaker 1: the photo was so sad. We we we did an 612 00:32:16,200 --> 00:32:21,200 Speaker 1: amazing story and and quick take collab um about Santa's 613 00:32:21,200 --> 00:32:24,480 Speaker 1: and snow globes. That was like a mal trend. They 614 00:32:24,480 --> 00:32:28,000 Speaker 1: have like a snow globe setup. So the story for 615 00:32:28,160 --> 00:32:30,440 Speaker 1: kids is that Santa got trapped in the snow globe. 616 00:32:31,120 --> 00:32:34,480 Speaker 1: Uh and special thanks to Clear Jakob and Katie for 617 00:32:34,480 --> 00:32:37,480 Speaker 1: for joining us and Trillions and and and sharing something 618 00:32:37,480 --> 00:32:40,320 Speaker 1: I know that hurts, which is what you were jealous of. 619 00:32:40,600 --> 00:32:43,520 Speaker 1: Happy holiday, So all of you guys, thank you, thank you, 620 00:32:48,200 --> 00:32:50,640 Speaker 1: thanks for listening to Trillions. Until next time. You can 621 00:32:50,680 --> 00:32:55,200 Speaker 1: find us on the Bloomberg Terminal, Bloomberg dot com, Apple Podcast, Spotify, 622 00:32:55,440 --> 00:32:57,560 Speaker 1: and wherever else you like to listen. We'd love to 623 00:32:57,600 --> 00:33:00,480 Speaker 1: hear from you. We're on Twitter, I'm at Joel ever Show, 624 00:33:00,720 --> 00:33:05,560 Speaker 1: He's at Eric Falcunas. You can find Katie at k Greifeld, 625 00:33:05,920 --> 00:33:12,280 Speaker 1: Claire at CFB Underscore eighteen, and Jacob at y Peter Steal. 626 00:33:13,000 --> 00:33:16,520 Speaker 1: This episode of Trillions was produced by Magnus Hendrickson. Francesca 627 00:33:16,600 --> 00:33:19,440 Speaker 1: Leedy is the head of Bloomberg Podcast by