1 00:00:06,040 --> 00:00:09,200 Speaker 1: Welcome on Trillions. I'm Joel Webber and I'm Eric bel Tunis. 2 00:00:14,880 --> 00:00:19,960 Speaker 1: Eric new launch just happened very much, caught your attention 3 00:00:20,520 --> 00:00:22,720 Speaker 1: and you immediately we're like, we gotta get these guys 4 00:00:22,760 --> 00:00:26,680 Speaker 1: on Trillions to talk to him. What's the product. Yeah, 5 00:00:26,720 --> 00:00:30,800 Speaker 1: there's two launches a year, that's over one a day, 6 00:00:31,520 --> 00:00:33,880 Speaker 1: and I don't know, maybe five or six just catch 7 00:00:34,000 --> 00:00:37,000 Speaker 1: my attention big time over the course of the year. 8 00:00:37,440 --> 00:00:39,479 Speaker 1: This is one of them. Because just when you think 9 00:00:39,520 --> 00:00:42,160 Speaker 1: there's no white space left and etf, somebody comes around 10 00:00:42,159 --> 00:00:45,480 Speaker 1: with something that's pretty original and this is really interesting idea. 11 00:00:45,479 --> 00:00:47,440 Speaker 1: It's called night Shares, that's the name of the brand, 12 00:00:48,040 --> 00:00:50,919 Speaker 1: and it really tries to put into reality something that 13 00:00:50,960 --> 00:00:53,560 Speaker 1: we've been reading about over the past several years where 14 00:00:53,880 --> 00:00:56,640 Speaker 1: you see this article or study that that points out that, hey, 15 00:00:56,680 --> 00:00:59,920 Speaker 1: if you only hold the U S Stock market at night, 16 00:01:00,000 --> 00:01:01,720 Speaker 1: in other words, you buy at the clothes and you 17 00:01:01,760 --> 00:01:04,080 Speaker 1: sell it the open, so you hold it overnight and 18 00:01:04,120 --> 00:01:07,160 Speaker 1: you don't hold it during the day. You crush holding 19 00:01:07,200 --> 00:01:10,400 Speaker 1: it during the day. There's something about that. It's like 20 00:01:10,440 --> 00:01:13,759 Speaker 1: a phenomenon, but it's really never been tried in reality 21 00:01:13,840 --> 00:01:17,040 Speaker 1: because there are real world issues that have probably stopped 22 00:01:17,040 --> 00:01:19,319 Speaker 1: some people from trying it, Um. But here we have 23 00:01:19,319 --> 00:01:21,040 Speaker 1: an et f issuer or that's come out and said 24 00:01:21,040 --> 00:01:22,560 Speaker 1: we're going to try to do this, and they have 25 00:01:22,600 --> 00:01:27,679 Speaker 1: two launches that have our live which is the large 26 00:01:27,680 --> 00:01:30,319 Speaker 1: caps and then a small cap version. So they're trying 27 00:01:30,319 --> 00:01:33,520 Speaker 1: to capture what they call the night effect. Um. And 28 00:01:33,600 --> 00:01:36,000 Speaker 1: you know, we'll there, we'll go into, you know, some 29 00:01:36,080 --> 00:01:40,039 Speaker 1: of the hurdles and challenges, but it's gonna be a 30 00:01:40,040 --> 00:01:45,360 Speaker 1: fascinating experiment. Joining us on trillions is gonna be Max Cookman, 31 00:01:45,440 --> 00:01:49,680 Speaker 1: he's this chief investment officer, and Bruce Levine he's the 32 00:01:49,760 --> 00:01:59,200 Speaker 1: CEO this time on trillions, the night Effect Bruce, Max, 33 00:01:59,200 --> 00:02:02,440 Speaker 1: welcome to Trillion, Thanks so much for having us, nice 34 00:02:02,440 --> 00:02:05,960 Speaker 1: to be here. Can you explain the big idea here, 35 00:02:06,000 --> 00:02:10,320 Speaker 1: Bruce absolutely, Um. You know Eric touched on it. The 36 00:02:10,320 --> 00:02:14,960 Speaker 1: big idea is that there are some unusual differences between 37 00:02:15,000 --> 00:02:17,960 Speaker 1: what happens in the markets overnight and during the daytime session, 38 00:02:18,480 --> 00:02:23,200 Speaker 1: and the overnight session historically has shown far better returns 39 00:02:23,280 --> 00:02:27,760 Speaker 1: and it's far better behaved from volatility standpoint. So we 40 00:02:27,800 --> 00:02:31,080 Speaker 1: find the night session to be a really interesting, uh 41 00:02:31,240 --> 00:02:34,920 Speaker 1: place to play, and we brought ETF to market that 42 00:02:35,080 --> 00:02:38,320 Speaker 1: would for the first time separate these very unique and 43 00:02:38,400 --> 00:02:44,040 Speaker 1: differentiated return streams between the day and night and and max. 44 00:02:44,760 --> 00:02:48,840 Speaker 1: How do you actually set this up to work? Right? 45 00:02:48,880 --> 00:02:51,519 Speaker 1: Because it's as Eric mentioned in the in the beginning there, 46 00:02:52,000 --> 00:02:56,040 Speaker 1: it seems like, you know, very obvious idea, but like, 47 00:02:56,120 --> 00:02:59,400 Speaker 1: how do you actually bring this into practice? Yeah, and 48 00:02:59,639 --> 00:03:01,760 Speaker 1: this is actually one of the things that made me 49 00:03:01,800 --> 00:03:04,440 Speaker 1: think a bit of the myth of Prometheus, where we're 50 00:03:04,480 --> 00:03:08,360 Speaker 1: taking something that exists that was uncapturable for for a 51 00:03:08,400 --> 00:03:12,120 Speaker 1: common investor in bringing it down to them. Um, it 52 00:03:12,200 --> 00:03:14,320 Speaker 1: actually is is a little bit more complex, and it 53 00:03:14,360 --> 00:03:17,840 Speaker 1: requires uh some knowledge of derivatives, that requires understanding how 54 00:03:18,040 --> 00:03:21,919 Speaker 1: the futures market works, how total return swaps work. Because 55 00:03:21,919 --> 00:03:25,359 Speaker 1: we really want to create an efficient exposure tonight effect 56 00:03:25,360 --> 00:03:30,080 Speaker 1: where we really make it um something that considers the impact, 57 00:03:30,080 --> 00:03:34,040 Speaker 1: that considers tea costs and um. The way we're implementing 58 00:03:34,040 --> 00:03:37,520 Speaker 1: it right now is we're buying futures at the close 59 00:03:37,600 --> 00:03:39,880 Speaker 1: and selling them at the open, and as we scale, 60 00:03:39,920 --> 00:03:44,760 Speaker 1: we're able to really expand on that construction to continue 61 00:03:44,760 --> 00:03:49,440 Speaker 1: making it highly efficient. Okay, UM, I want to circle 62 00:03:49,440 --> 00:03:52,560 Speaker 1: back on you call tea cost transaction costs. That's been 63 00:03:52,600 --> 00:03:56,120 Speaker 1: a big worry or I guess something people who pointed 64 00:03:56,120 --> 00:03:58,800 Speaker 1: out when a table I just for one second, I 65 00:03:58,840 --> 00:04:01,760 Speaker 1: want to get back to the night effect, Bruce. And also, 66 00:04:02,640 --> 00:04:06,360 Speaker 1: can you explain why why would the stock market do 67 00:04:06,520 --> 00:04:08,960 Speaker 1: better at night than during the day. What factors are 68 00:04:09,000 --> 00:04:11,880 Speaker 1: contributing to that? And that's a really great question, and 69 00:04:11,920 --> 00:04:15,200 Speaker 1: it was so interesting to look at it. And the 70 00:04:15,240 --> 00:04:18,400 Speaker 1: first time you see this data, it's just stunning. Uh. 71 00:04:18,560 --> 00:04:20,280 Speaker 1: You know, there's been research done for a long time. 72 00:04:20,320 --> 00:04:22,440 Speaker 1: There's sort of three buckets of reasons. I call it. 73 00:04:22,880 --> 00:04:24,960 Speaker 1: One is just that there's news flow when the markets 74 00:04:24,960 --> 00:04:29,120 Speaker 1: are closed. So this could be earnings announcements, which although 75 00:04:29,160 --> 00:04:32,920 Speaker 1: not universally positive on balanced stocks trade up and then 76 00:04:33,320 --> 00:04:36,160 Speaker 1: M and A, which is generally extremely positive for the market. 77 00:04:36,240 --> 00:04:37,760 Speaker 1: So those all happen when the markets are closed, so 78 00:04:37,760 --> 00:04:40,440 Speaker 1: you have to be invested to catch them. The second 79 00:04:40,480 --> 00:04:45,320 Speaker 1: thing is just structural de risking that seems to happen 80 00:04:45,320 --> 00:04:50,280 Speaker 1: among institutions. And an example this would be an et 81 00:04:50,360 --> 00:04:55,560 Speaker 1: F market making firm. Their business is to play between 82 00:04:55,600 --> 00:04:58,000 Speaker 1: the bid and the ask all day long, but their 83 00:04:58,040 --> 00:05:00,839 Speaker 1: business is not to hold inventory overnight, so at the 84 00:05:00,880 --> 00:05:02,440 Speaker 1: end of the day, they kind of flatten out their 85 00:05:02,440 --> 00:05:05,520 Speaker 1: positions and then they kind of read buying the next morning. 86 00:05:06,120 --> 00:05:07,640 Speaker 1: And then the last one is also kind of there's 87 00:05:07,640 --> 00:05:09,600 Speaker 1: a bunch of complexities that you can avoid if you 88 00:05:09,640 --> 00:05:12,760 Speaker 1: just get out by the end of the day. So, um, 89 00:05:12,800 --> 00:05:17,320 Speaker 1: we found this pattern, uh of the night effect happens worldwide, 90 00:05:17,400 --> 00:05:20,240 Speaker 1: which is interesting. So there must be something going on, 91 00:05:20,920 --> 00:05:24,240 Speaker 1: you know, And it's I've seen people pitch their whole 92 00:05:24,240 --> 00:05:26,919 Speaker 1: investment strategy to investors, and what they pitch is we 93 00:05:26,960 --> 00:05:29,159 Speaker 1: get out so you can sleep at night. And and 94 00:05:29,200 --> 00:05:31,239 Speaker 1: it also almost leaves something on the table for those 95 00:05:31,279 --> 00:05:35,120 Speaker 1: that are you know, not so m scared by the 96 00:05:35,160 --> 00:05:38,080 Speaker 1: overnight session. Yeah, we we think that your money should 97 00:05:38,120 --> 00:05:42,000 Speaker 1: work while you sleep, not and not make you, you you know, 98 00:05:42,240 --> 00:05:46,080 Speaker 1: work harder during the day. Well, I mean, I guess 99 00:05:46,120 --> 00:05:48,960 Speaker 1: people who invest in bitcoin may differ from that because 100 00:05:49,160 --> 00:05:51,120 Speaker 1: on the weekend you can see them having to suffer 101 00:05:51,360 --> 00:05:53,440 Speaker 1: when all the stock people are like, I'm not I 102 00:05:53,680 --> 00:05:55,360 Speaker 1: have nothing to worry about on the weekend. But anyway, 103 00:05:55,760 --> 00:05:58,360 Speaker 1: but it's true, the market doesn't ever truly sleep. It's 104 00:05:58,400 --> 00:06:01,800 Speaker 1: just you only see the prices in action during those 105 00:06:01,880 --> 00:06:04,560 Speaker 1: whatever eight hours during the day. But it's still like 106 00:06:04,560 --> 00:06:06,080 Speaker 1: like a lot of times, they'll be news out of 107 00:06:06,240 --> 00:06:10,200 Speaker 1: UM over the weekend or before the market, and I'll 108 00:06:10,200 --> 00:06:12,200 Speaker 1: do G I, P O and Bloomberg which is UM 109 00:06:12,279 --> 00:06:15,400 Speaker 1: intra day pricing, and I'll tweet out, you know, pre 110 00:06:15,520 --> 00:06:17,840 Speaker 1: market trading the S and P s up two on 111 00:06:17,880 --> 00:06:20,320 Speaker 1: this news or whatever. Now, I will say sometimes it's 112 00:06:20,360 --> 00:06:22,839 Speaker 1: bad like such and such a down on this news. 113 00:06:23,040 --> 00:06:24,400 Speaker 1: And I guess, Bruce, I'll come back to you on 114 00:06:24,440 --> 00:06:29,440 Speaker 1: that question, which is that you know, take something like earnings. Okay, fine, 115 00:06:29,920 --> 00:06:33,160 Speaker 1: in a good market, earnings will be good and announced 116 00:06:33,160 --> 00:06:35,159 Speaker 1: after the clothes. But wouldn't that wouldn't there be the 117 00:06:35,200 --> 00:06:38,200 Speaker 1: reverse in like this kind of market where it's harder 118 00:06:38,240 --> 00:06:41,599 Speaker 1: to get let's say we hit a recession or whatever. Um, 119 00:06:41,600 --> 00:06:45,679 Speaker 1: you know, wouldn't that just be negative for the night effect? Yeah? 120 00:06:45,720 --> 00:06:48,279 Speaker 1: You know, it's interesting when you look at the numbers 121 00:06:48,440 --> 00:06:50,360 Speaker 1: yere to day in a in a really tough market 122 00:06:50,400 --> 00:06:53,960 Speaker 1: where there's been a lot of news. Um. The you know, 123 00:06:54,000 --> 00:06:56,880 Speaker 1: if you were buying a hold here today, you're down 124 00:06:56,960 --> 00:06:59,200 Speaker 1: far more than if you were just owning the night session. 125 00:06:59,440 --> 00:07:01,479 Speaker 1: So you can see you can sort of feel this 126 00:07:01,680 --> 00:07:03,560 Speaker 1: viscerally if you've been in the markets here to date 127 00:07:03,760 --> 00:07:07,719 Speaker 1: where you've had all these days where uh, the markets 128 00:07:07,760 --> 00:07:11,200 Speaker 1: open kind of either slightly up, kind of flattershed slightly 129 00:07:11,200 --> 00:07:13,280 Speaker 1: down and then just start picking up steam to the 130 00:07:13,320 --> 00:07:17,840 Speaker 1: cell side. And so um, we have not seen nearly 131 00:07:17,880 --> 00:07:20,360 Speaker 1: as much you know, damage coming in the night session 132 00:07:20,640 --> 00:07:24,080 Speaker 1: this year, so um. And and that's consistent with our 133 00:07:24,120 --> 00:07:28,240 Speaker 1: research which was you see far more left tail events 134 00:07:28,280 --> 00:07:31,040 Speaker 1: happening during the day, you know, statistically than you do 135 00:07:31,320 --> 00:07:36,760 Speaker 1: happening a night. Okay, So I'm really curious. You guys 136 00:07:36,960 --> 00:07:39,840 Speaker 1: have had to have done a ton of back testing 137 00:07:39,880 --> 00:07:43,480 Speaker 1: on this. Um, how is it held up like both 138 00:07:43,600 --> 00:07:47,640 Speaker 1: both recently while you know, markets have been incredibly turbulent 139 00:07:47,720 --> 00:07:52,120 Speaker 1: so far this year, but also more historically, it's it's 140 00:07:52,120 --> 00:07:53,520 Speaker 1: held up really well. I mean, I'll give you an 141 00:07:53,520 --> 00:07:56,960 Speaker 1: example of small caps so UM year to date, if 142 00:07:57,000 --> 00:08:00,920 Speaker 1: you just held say, you know, a small cap up index, 143 00:08:01,360 --> 00:08:05,760 Speaker 1: you'd be down about two If you just held the 144 00:08:06,000 --> 00:08:09,840 Speaker 1: night portion, you'd be down less than six percent. So 145 00:08:10,000 --> 00:08:13,560 Speaker 1: it's pretty substantial. And as we look at it historically, UM, 146 00:08:13,600 --> 00:08:16,480 Speaker 1: it's important to note that this effect does not always 147 00:08:16,520 --> 00:08:18,480 Speaker 1: work right And and by the way, I think if 148 00:08:18,520 --> 00:08:20,960 Speaker 1: anyone comes on the podcast and says, hey, we found something. 149 00:08:21,360 --> 00:08:24,320 Speaker 1: It's always gonna work. It's always going to generate you alpha. 150 00:08:25,000 --> 00:08:27,960 Speaker 1: I would hope there's a lot of skepticism in the room. Um, 151 00:08:28,000 --> 00:08:29,400 Speaker 1: but we do find that if we do like a 152 00:08:29,480 --> 00:08:35,040 Speaker 1: rolling one three five year analysis of sharp ratios or 153 00:08:35,160 --> 00:08:41,480 Speaker 1: um or returns, the night effect consistently does outperform the 154 00:08:41,559 --> 00:08:44,360 Speaker 1: day's session. And it's across a lot of different betas. 155 00:08:45,320 --> 00:08:48,000 Speaker 1: Um let me let me just let me just jump 156 00:08:48,040 --> 00:08:50,760 Speaker 1: in there real quick. Um, So you talk about this. 157 00:08:50,920 --> 00:08:53,120 Speaker 1: I remember looking at the Bespoke study, which was the 158 00:08:53,120 --> 00:08:57,240 Speaker 1: one I think that the papers covered, the media covered 159 00:08:57,280 --> 00:08:59,400 Speaker 1: like a year ago. Bloomberg had an article on it. Anyway, 160 00:08:59,600 --> 00:09:04,240 Speaker 1: it shows that the night returns something like six and 161 00:09:04,280 --> 00:09:07,720 Speaker 1: the day was like flat or down. Even so, a 162 00:09:07,840 --> 00:09:10,240 Speaker 1: very cool chart. One line goes up big, one line 163 00:09:10,280 --> 00:09:13,360 Speaker 1: is flat. However, if you just held the S and 164 00:09:13,400 --> 00:09:16,560 Speaker 1: P five and didn't do just held at the whole time, 165 00:09:16,600 --> 00:09:20,600 Speaker 1: you were up. So I guess what would you say 166 00:09:20,600 --> 00:09:23,280 Speaker 1: to somebody who's like, well, what I'm not going to 167 00:09:23,400 --> 00:09:26,120 Speaker 1: just hold during the day, I'm gonna hold day and night. 168 00:09:26,280 --> 00:09:29,280 Speaker 1: Isn't that just easier? I would say, it's it's it's 169 00:09:29,320 --> 00:09:31,760 Speaker 1: a story of risk and return, right, and I think 170 00:09:32,120 --> 00:09:35,720 Speaker 1: especially in this environment where investors are looking for ways 171 00:09:35,800 --> 00:09:39,160 Speaker 1: to well create a more divorce PI portfolio, create a 172 00:09:39,160 --> 00:09:43,720 Speaker 1: more stable portfolio, it's really important to consider the denominator 173 00:09:44,040 --> 00:09:47,800 Speaker 1: of what should be really any acid allocation equation, which 174 00:09:47,880 --> 00:09:51,160 Speaker 1: is your standard deviation. And it's true about with large caps. 175 00:09:51,200 --> 00:09:53,120 Speaker 1: You do see a positive day effect. And yes, you 176 00:09:53,160 --> 00:09:57,360 Speaker 1: will earn more money if you hold twenty four hours 177 00:09:57,360 --> 00:10:00,120 Speaker 1: over most periods, but you will do so at the 178 00:10:00,200 --> 00:10:05,920 Speaker 1: expense of a disproportionately higher risk. Yeah. So I would 179 00:10:05,960 --> 00:10:09,160 Speaker 1: just add to that that potentially, Eric, you can expand 180 00:10:09,520 --> 00:10:12,880 Speaker 1: your equity exposure if you're playing in the lower risk 181 00:10:13,920 --> 00:10:16,640 Speaker 1: portion of them. You know of the equity market, and 182 00:10:16,679 --> 00:10:19,120 Speaker 1: that's what the night session is. So that's one thing. 183 00:10:19,760 --> 00:10:22,840 Speaker 1: And then the other thing I'll add is um that 184 00:10:23,000 --> 00:10:25,800 Speaker 1: chart you referenced was a was a large cap, but 185 00:10:25,840 --> 00:10:29,680 Speaker 1: what we found in small caps was really surprising, which 186 00:10:29,720 --> 00:10:33,720 Speaker 1: was that the day portion of the Russell too over 187 00:10:33,800 --> 00:10:39,559 Speaker 1: time was negative. So they're holding the night only actually 188 00:10:39,600 --> 00:10:42,360 Speaker 1: outperformed not only on the risk side, but on the 189 00:10:42,360 --> 00:10:53,600 Speaker 1: performance side. So I'm curious anything that ever seems this 190 00:10:53,679 --> 00:10:57,439 Speaker 1: good to be true feels like, just like, why hasn't 191 00:10:57,480 --> 00:10:59,880 Speaker 1: somebody else figured this out or figured out a way 192 00:10:59,880 --> 00:11:03,240 Speaker 1: it are this? And specifically I'm just thinking of hedge 193 00:11:03,240 --> 00:11:07,480 Speaker 1: funds who have you know, teams of analysts specifically trying 194 00:11:07,520 --> 00:11:10,600 Speaker 1: to find things like this that are just sitting in 195 00:11:10,600 --> 00:11:13,800 Speaker 1: in plain side, even if that plain side as the 196 00:11:13,880 --> 00:11:16,920 Speaker 1: lights off. But why, you know, why hasn't this been 197 00:11:16,960 --> 00:11:21,920 Speaker 1: exploited yet and what risks does that maybe create? Yeah, 198 00:11:21,960 --> 00:11:24,720 Speaker 1: so we know there's some hedge funds doing this trade 199 00:11:25,280 --> 00:11:28,440 Speaker 1: and you know there are people playing at it. UM 200 00:11:28,520 --> 00:11:30,959 Speaker 1: asked for why it's never been packaged as an E 201 00:11:31,040 --> 00:11:33,680 Speaker 1: t F M. I don't know, other than you know, 202 00:11:33,720 --> 00:11:36,360 Speaker 1: I've spent like twenty years doing E t F product 203 00:11:36,400 --> 00:11:38,280 Speaker 1: launches that I've never seen the research. In the minute 204 00:11:38,320 --> 00:11:41,800 Speaker 1: I saw it, I said, wow, this is really interesting. Um, 205 00:11:41,840 --> 00:11:46,480 Speaker 1: in terms of the risks. Uh, really, I think mind, 206 00:11:46,480 --> 00:11:49,360 Speaker 1: your question is if it works as it get arped away, 207 00:11:49,960 --> 00:11:54,040 Speaker 1: And that's a really fascinating question and I hope we 208 00:11:54,120 --> 00:11:58,360 Speaker 1: find out, UM. But the question is at what level right, 209 00:11:58,720 --> 00:12:02,520 Speaker 1: and even how structural it is and how the research 210 00:12:02,559 --> 00:12:05,120 Speaker 1: has been out there for a while and the phenomenon 211 00:12:05,240 --> 00:12:07,840 Speaker 1: persists are sensitive takes it would take quite a lot 212 00:12:07,920 --> 00:12:11,280 Speaker 1: of capital to r to trage it away if if 213 00:12:11,320 --> 00:12:14,840 Speaker 1: that's even going to occur. I mean, for me, there 214 00:12:15,000 --> 00:12:18,280 Speaker 1: there's no question that hedge funds are doing it. We 215 00:12:18,280 --> 00:12:20,240 Speaker 1: we have a sister company that that is a hedge fund, 216 00:12:20,240 --> 00:12:22,960 Speaker 1: which is actually where of this effect was discovered UM 217 00:12:23,000 --> 00:12:26,680 Speaker 1: and this is one of our strongest um effects that 218 00:12:26,760 --> 00:12:32,960 Speaker 1: we do capture there. And we just see that a 219 00:12:32,960 --> 00:12:36,920 Speaker 1: lot of structural things, whether it's earnings, economics, announcement, et cetera, 220 00:12:37,000 --> 00:12:40,160 Speaker 1: they do occur when cash markets are closed. You see, 221 00:12:40,160 --> 00:12:44,160 Speaker 1: investor makeup is very different between who trades in equities 222 00:12:44,440 --> 00:12:47,120 Speaker 1: when US markets are closed in terms of European institutions 223 00:12:47,240 --> 00:12:50,839 Speaker 1: and Asian institutions, and so those are the things that 224 00:12:50,880 --> 00:12:53,720 Speaker 1: are really key versus if I say, hey, I found 225 00:12:53,720 --> 00:12:55,679 Speaker 1: this really cool skew and options and I'm going to 226 00:12:55,760 --> 00:12:58,360 Speaker 1: trade on it. Well, yeah, once you start doing that 227 00:12:58,400 --> 00:13:02,160 Speaker 1: in size, everyone else starts reverse engineering it and you 228 00:13:02,200 --> 00:13:05,319 Speaker 1: see about alpha fade UM. We think the structural reasons 229 00:13:05,480 --> 00:13:10,720 Speaker 1: is why this effect can be significantly more persistent. So 230 00:13:10,880 --> 00:13:13,800 Speaker 1: right now you've you've got US focused products. But at 231 00:13:13,800 --> 00:13:16,200 Speaker 1: the beginning you mentioned that you've noticed this night effect 232 00:13:16,240 --> 00:13:21,920 Speaker 1: actually has global potential, right, so I'm wondering, you know, what, 233 00:13:21,920 --> 00:13:26,160 Speaker 1: what kind of global ideas are you kind of eyeing here, 234 00:13:26,160 --> 00:13:32,320 Speaker 1: and what what challenges withoud that product potentially create. So 235 00:13:32,360 --> 00:13:36,000 Speaker 1: we have a pretty long product development queue because it 236 00:13:36,120 --> 00:13:39,360 Speaker 1: when you start to really dig into this night effect, 237 00:13:39,400 --> 00:13:41,959 Speaker 1: there's lots of different ways to work with it, and 238 00:13:42,040 --> 00:13:44,000 Speaker 1: so we would expect at some point to have products 239 00:13:44,000 --> 00:13:48,880 Speaker 1: that offer us investors, um perhaps the chance to be 240 00:13:49,000 --> 00:13:52,000 Speaker 1: in different segments of the market at different times over 241 00:13:52,080 --> 00:13:54,920 Speaker 1: the twenty four hour cycle, so that we're sort of 242 00:13:54,960 --> 00:14:00,320 Speaker 1: capturing the right effect differently as time persists. Uh, so 243 00:14:00,880 --> 00:14:05,079 Speaker 1: you know, stay tuned for that. Um, Okay, we gotta 244 00:14:05,200 --> 00:14:08,400 Speaker 1: here's the big challenge. So I've seen people right about 245 00:14:08,400 --> 00:14:11,120 Speaker 1: this the replies on Twitter, and this is part of 246 00:14:11,160 --> 00:14:15,520 Speaker 1: what the factor world sometimes bumps up against, especially momentum, 247 00:14:15,640 --> 00:14:18,160 Speaker 1: is the fact that you have to trade a lot 248 00:14:18,240 --> 00:14:20,560 Speaker 1: to keep up with this. So I'm just gonna do 249 00:14:20,680 --> 00:14:24,520 Speaker 1: quick math correct if I'm wrong. Let's say I know 250 00:14:24,600 --> 00:14:27,160 Speaker 1: you're using futures, but let's say you held spy during 251 00:14:27,160 --> 00:14:31,000 Speaker 1: the night only to one basis point a bit as spread. 252 00:14:31,280 --> 00:14:33,360 Speaker 1: So if you add up two hundred days of doing that, 253 00:14:33,400 --> 00:14:37,520 Speaker 1: what is that three four hundred basis points of trading costs. 254 00:14:37,520 --> 00:14:40,400 Speaker 1: That's four So that's like a hurdle to get over. 255 00:14:41,040 --> 00:14:43,640 Speaker 1: And because it's ongoing, it's like a constant corrosion to 256 00:14:43,760 --> 00:14:46,880 Speaker 1: the returns and that has been I think one of 257 00:14:46,920 --> 00:14:51,240 Speaker 1: the biggest um pushbacks on this strategy is that it 258 00:14:51,320 --> 00:14:53,840 Speaker 1: can't be done in the wild because transaction costs would 259 00:14:53,840 --> 00:14:56,920 Speaker 1: eat you alive. So what's your plan for that? Yeah, 260 00:14:56,960 --> 00:15:01,680 Speaker 1: that's absolutely um probably the and the strategy hasn't been 261 00:15:01,720 --> 00:15:04,280 Speaker 1: tried before. So look, our goal is to give you 262 00:15:04,320 --> 00:15:10,920 Speaker 1: the greatest institutional execution quality we can and to do it, 263 00:15:11,720 --> 00:15:14,000 Speaker 1: you know, across we're looking across a number of different 264 00:15:14,080 --> 00:15:16,840 Speaker 1: vehicles to do it. We're starting out with futures and 265 00:15:16,880 --> 00:15:21,000 Speaker 1: you know what we see internally is that we think 266 00:15:21,000 --> 00:15:24,360 Speaker 1: we can trade you know, somewhere between a half a 267 00:15:24,360 --> 00:15:27,320 Speaker 1: basis point and a basis point per day. Okay, so 268 00:15:27,360 --> 00:15:30,720 Speaker 1: if you analyze that over two days, you know that's 269 00:15:32,600 --> 00:15:37,200 Speaker 1: basis points. And then we have cash collateral that backs 270 00:15:37,240 --> 00:15:40,760 Speaker 1: up the futures contracts that's going to sit in treasuries 271 00:15:40,800 --> 00:15:44,040 Speaker 1: and cash, and now that rates have popped up a 272 00:15:44,080 --> 00:15:45,600 Speaker 1: little bit, you know, we may be able to get 273 00:15:46,240 --> 00:15:49,240 Speaker 1: a large percentage of that offset from the cash collatoral. 274 00:15:50,560 --> 00:15:54,000 Speaker 1: Now let's explain this again, uh like the local third 275 00:15:54,000 --> 00:15:59,400 Speaker 1: grade style UM, because when you use futures, right, you 276 00:15:59,400 --> 00:16:02,400 Speaker 1: you you buy a little bit, but you get a lot. 277 00:16:02,440 --> 00:16:04,800 Speaker 1: So just explain the sort of dynamics of how you 278 00:16:04,800 --> 00:16:07,480 Speaker 1: can hold treasuries because when someone pulls this up, I 279 00:16:07,480 --> 00:16:09,720 Speaker 1: guess eventually they're going to see a bunch of treasuries 280 00:16:09,760 --> 00:16:12,200 Speaker 1: in here, right, They're not going to see the S 281 00:16:12,280 --> 00:16:14,560 Speaker 1: and P five hunter or anything like that. So just 282 00:16:14,680 --> 00:16:18,560 Speaker 1: explain how the future's exposure to treasuries works. And that's 283 00:16:18,560 --> 00:16:21,960 Speaker 1: a good question. So you know, futures are contracts, right, 284 00:16:22,000 --> 00:16:24,480 Speaker 1: so so it may just show up as we have 285 00:16:25,280 --> 00:16:30,760 Speaker 1: notional exposure. But but features don't have value themselves until 286 00:16:30,880 --> 00:16:34,360 Speaker 1: you you know, mark them from where you bought them 287 00:16:34,360 --> 00:16:36,880 Speaker 1: to where you sold them. So the holdings of the 288 00:16:36,880 --> 00:16:40,120 Speaker 1: fund will show up as treasuries, which we're gonna hold seven. 289 00:16:40,680 --> 00:16:45,120 Speaker 1: And it's the fact that we can you know, features 290 00:16:45,680 --> 00:16:49,640 Speaker 1: really provide some leverage in the sense of um, we 291 00:16:49,760 --> 00:16:53,960 Speaker 1: can uh sitting as treasuries, and they back the futures 292 00:16:54,200 --> 00:16:58,560 Speaker 1: contracts and allow us to hold larger amounts of futures. 293 00:16:58,560 --> 00:17:02,520 Speaker 1: So it's because of that that we're able to get 294 00:17:02,560 --> 00:17:07,240 Speaker 1: you know, sort of this cash collateral return source in 295 00:17:07,280 --> 00:17:11,119 Speaker 1: addition to staying invested in the equity market. And and 296 00:17:11,240 --> 00:17:14,440 Speaker 1: right now, the treasuries, I'm assuming you'll hold short term 297 00:17:14,440 --> 00:17:19,680 Speaker 1: debt right like two year or something like that. Yeah, 298 00:17:19,680 --> 00:17:24,000 Speaker 1: well we'll we'll we'll hold um fairly low duration treasuries. 299 00:17:24,119 --> 00:17:29,600 Speaker 1: We you know, will be smart about that. And certainly, UM, 300 00:17:29,640 --> 00:17:34,000 Speaker 1: you know, having run a pretty large derivative book, very 301 00:17:34,000 --> 00:17:36,760 Speaker 1: comfortable with saying that there's a right and a wrong 302 00:17:36,840 --> 00:17:40,119 Speaker 1: way due to collateral management, UM, and specially something like this, 303 00:17:40,200 --> 00:17:43,480 Speaker 1: we want to be safe. The goal is to offset 304 00:17:43,880 --> 00:17:48,040 Speaker 1: the tea costs and UM, I think at the current 305 00:17:48,400 --> 00:17:50,719 Speaker 1: you know, UM rate environment, we can do that with 306 00:17:51,040 --> 00:17:54,600 Speaker 1: very low duration. Did you file these after the FED 307 00:17:55,040 --> 00:17:58,080 Speaker 1: changed its mission from like keeping rates low to like 308 00:17:58,119 --> 00:18:01,720 Speaker 1: fighting inflation, because clearly that was a a good It's 309 00:18:01,840 --> 00:18:06,280 Speaker 1: arguably good timing in that you were looking for something 310 00:18:06,280 --> 00:18:10,080 Speaker 1: to offset this transaction cost. But did that play into 311 00:18:10,200 --> 00:18:12,920 Speaker 1: your filing filed in March? So I'm not exactly sure 312 00:18:12,920 --> 00:18:16,960 Speaker 1: when they changed. And and look, we were focused on 313 00:18:17,000 --> 00:18:19,600 Speaker 1: bringing this to market and and we were looking at 314 00:18:19,640 --> 00:18:23,840 Speaker 1: lots of different ways to run the fund, and I 315 00:18:23,880 --> 00:18:26,720 Speaker 1: think the fact that rates have popped up and has 316 00:18:27,200 --> 00:18:30,040 Speaker 1: maybe made us lean towards this particular way of running 317 00:18:30,040 --> 00:18:35,760 Speaker 1: the fund. Okay, well, I'm curious, Bruce, you have a 318 00:18:35,800 --> 00:18:39,119 Speaker 1: really interesting backstory. You've you've been in the e t 319 00:18:39,280 --> 00:18:43,040 Speaker 1: F world for a really long time. Um at I shares, 320 00:18:43,600 --> 00:18:47,200 Speaker 1: you help launch l qt h y G. These are 321 00:18:47,800 --> 00:18:52,040 Speaker 1: incredibly um successful bond ETFs. I'm just wondering, you know, 322 00:18:52,119 --> 00:18:53,720 Speaker 1: like all of this, like what have you what have 323 00:18:53,760 --> 00:18:56,120 Speaker 1: you learned from your experience in the industry that you're 324 00:18:56,119 --> 00:18:59,240 Speaker 1: going to be applying here. It has been an interesting, right, 325 00:18:59,280 --> 00:19:01,520 Speaker 1: you know, because I've seen different kinds of products, right, 326 00:19:01,640 --> 00:19:03,960 Speaker 1: some of them. In the early days of I shares, 327 00:19:04,040 --> 00:19:06,320 Speaker 1: it was just an educational thing. We were new with 328 00:19:06,400 --> 00:19:08,920 Speaker 1: this new fangled thing called an e t F and 329 00:19:08,960 --> 00:19:10,840 Speaker 1: once you've got people over the hump of understanding it, 330 00:19:10,880 --> 00:19:14,960 Speaker 1: they really put in. With wisdom Tree, we were new 331 00:19:15,000 --> 00:19:18,840 Speaker 1: with a different way to index, you know. Prior to 332 00:19:18,840 --> 00:19:21,600 Speaker 1: wisdom Tree and ETF, theres just beta and now they're 333 00:19:21,640 --> 00:19:24,439 Speaker 1: smart data, right, And wisdom Tree was a pioneer and 334 00:19:24,480 --> 00:19:26,560 Speaker 1: saying hey, there's a better way to create an index 335 00:19:27,480 --> 00:19:31,720 Speaker 1: and and it was an educational challenge, but now well 336 00:19:31,760 --> 00:19:34,080 Speaker 1: accepted that there's more than one way to index, and 337 00:19:34,119 --> 00:19:37,280 Speaker 1: we see what we're doing with night Shares is similar 338 00:19:37,280 --> 00:19:40,840 Speaker 1: to that in the sense of there is this sort 339 00:19:40,880 --> 00:19:44,639 Speaker 1: of thin slice of the market that is aware of 340 00:19:44,640 --> 00:19:47,000 Speaker 1: this research and a very large slice of the market 341 00:19:47,040 --> 00:19:50,000 Speaker 1: that's not so. First it's just educated and make aware 342 00:19:50,560 --> 00:19:54,320 Speaker 1: that it's out there. Uh. And then you know, people 343 00:19:54,320 --> 00:19:56,639 Speaker 1: will watch it and some will toe dip and some 344 00:19:56,720 --> 00:20:01,320 Speaker 1: will you know, wait for proof. And but we think 345 00:20:01,320 --> 00:20:06,639 Speaker 1: over time, you know, we've added a really interesting um 346 00:20:06,840 --> 00:20:09,919 Speaker 1: dynamic to the market. Uh. And I appreciate what Eric 347 00:20:09,960 --> 00:20:11,520 Speaker 1: said right at the beginning. It's just not that many 348 00:20:11,600 --> 00:20:16,160 Speaker 1: things that you know are truly differentiate in the market space. 349 00:20:22,840 --> 00:20:25,159 Speaker 1: I want to pitch Max on a product idea I have. 350 00:20:25,200 --> 00:20:26,480 Speaker 1: I think you guys would be the right ones to 351 00:20:26,560 --> 00:20:29,760 Speaker 1: launch it. We had a Shark Tank type episode about 352 00:20:29,800 --> 00:20:32,440 Speaker 1: two years ago where a bunch of reporters and analysts 353 00:20:32,440 --> 00:20:35,760 Speaker 1: pitched e T F ideas to a judge and mine, 354 00:20:36,240 --> 00:20:38,400 Speaker 1: I believe mine one, or it came in second or something, 355 00:20:38,440 --> 00:20:41,280 Speaker 1: but it was called X bond. It was just forgets 356 00:20:41,359 --> 00:20:44,200 Speaker 1: because it's just in his mind it was the greatest 357 00:20:44,200 --> 00:20:46,879 Speaker 1: pitch of all time, but yeah, you gotta see it 358 00:20:46,920 --> 00:20:50,880 Speaker 1: a little bit more Jamaican x mon Um, I wont, 359 00:20:50,920 --> 00:20:53,439 Speaker 1: at least in my mind. Um. And basically this is 360 00:20:53,440 --> 00:20:57,000 Speaker 1: the S and P five hundred x Mondays because you 361 00:20:57,040 --> 00:21:00,439 Speaker 1: know how like everybody freaks out over the weekend if 362 00:21:00,440 --> 00:21:03,720 Speaker 1: there's bad news Friday, and like you've black Monday seven, 363 00:21:03,840 --> 00:21:05,600 Speaker 1: then there was a black Monday too. Just seems like 364 00:21:05,640 --> 00:21:08,800 Speaker 1: Mondays are brutal days and they've done studies that Monday 365 00:21:08,920 --> 00:21:12,280 Speaker 1: does on average return a little less than the rest 366 00:21:12,320 --> 00:21:14,399 Speaker 1: of the week. What do you think of that idea? 367 00:21:14,480 --> 00:21:16,760 Speaker 1: And have you ever thought about actually explaining this out 368 00:21:16,760 --> 00:21:19,520 Speaker 1: of just the night but into other times, like just 369 00:21:19,560 --> 00:21:23,320 Speaker 1: making time your thing? Well, well, I definitely think that 370 00:21:23,359 --> 00:21:26,480 Speaker 1: in the t F game, having a good ticker is important, 371 00:21:26,480 --> 00:21:28,679 Speaker 1: so so Eric, if nothing else, you've definitely nailed that. 372 00:21:29,680 --> 00:21:33,760 Speaker 1: And that was a polite letdown. I think, Max, no, no no, no, no, 373 00:21:34,680 --> 00:21:37,320 Speaker 1: I mean, I I do think there's you know, if 374 00:21:37,320 --> 00:21:42,240 Speaker 1: you look at time overall, um and seasonality and you 375 00:21:42,280 --> 00:21:46,200 Speaker 1: know all of that, there there's more ground to cover there. 376 00:21:46,240 --> 00:21:50,080 Speaker 1: I think for us, um we're pretty focused on on 377 00:21:50,119 --> 00:21:52,560 Speaker 1: the night. We think there's a whole lot to do 378 00:21:52,640 --> 00:21:56,439 Speaker 1: in the nighttime before we start looking at other things. 379 00:21:56,480 --> 00:22:03,240 Speaker 1: But you know, certainly, um, the x mon is a 380 00:22:03,359 --> 00:22:06,320 Speaker 1: concept that that has some some grounding in reality. If 381 00:22:06,320 --> 00:22:08,760 Speaker 1: you do look at the Monday fact, you know, Monday 382 00:22:08,800 --> 00:22:12,439 Speaker 1: scaries are real. Yeah, no one likes Mondays. It's like 383 00:22:12,440 --> 00:22:16,239 Speaker 1: it also hits the heart. Now I hate Mondays. This 384 00:22:16,320 --> 00:22:19,560 Speaker 1: lines up with my values. Eric. The other key thing 385 00:22:19,960 --> 00:22:22,040 Speaker 1: is every ETF needs to have a good spokesman, So 386 00:22:22,040 --> 00:22:25,560 Speaker 1: you've got to get Garfield to be your spokesman. Or 387 00:22:25,560 --> 00:22:28,119 Speaker 1: that moment from office Space, somebody's been a case of 388 00:22:28,160 --> 00:22:31,640 Speaker 1: the Monday's. Yeah, yeah, I don't know. I think there's 389 00:22:31,640 --> 00:22:33,880 Speaker 1: something there. We'll see. Maybe if you guys have success, 390 00:22:33,920 --> 00:22:36,680 Speaker 1: you can branch out into other parts of the calendar. 391 00:22:36,720 --> 00:22:39,119 Speaker 1: You could also do a sell in may E t 392 00:22:39,320 --> 00:22:41,800 Speaker 1: F and just have one that just just doesn't hold 393 00:22:41,840 --> 00:22:44,320 Speaker 1: the stocks during the summer, although that's that's been proven 394 00:22:44,320 --> 00:22:47,560 Speaker 1: to be pretty much a lie. But anyway, there's definitely 395 00:22:47,600 --> 00:22:50,159 Speaker 1: some some some options here. I think in fact that 396 00:22:50,240 --> 00:22:52,080 Speaker 1: the name of the company that I thought of was 397 00:22:52,160 --> 00:22:55,200 Speaker 1: Calendar Shares. You guys are like you're the closest thing 398 00:22:55,240 --> 00:22:58,720 Speaker 1: to that sort of tongue in cheek idea. UM. So again, 399 00:22:58,760 --> 00:23:00,040 Speaker 1: that's part of the reason I was so interesting to 400 00:23:00,640 --> 00:23:03,560 Speaker 1: talk to you guys, because time hasn't really been sliced 401 00:23:03,640 --> 00:23:08,520 Speaker 1: up the way sectors have and countries and geographic regions, etcetera. Alright, 402 00:23:08,640 --> 00:23:15,399 Speaker 1: enough for America. Uh. Speaking of speaking of tickers, uh 403 00:23:15,440 --> 00:23:19,720 Speaker 1: in spy in i w M. Both of these are great. 404 00:23:19,760 --> 00:23:22,880 Speaker 1: You got the inn at the front. Um. We always 405 00:23:23,119 --> 00:23:27,600 Speaker 1: end with a ticker question. Um, Max, what is your 406 00:23:27,640 --> 00:23:30,400 Speaker 1: favorite E t F ticker that is not your own? 407 00:23:30,400 --> 00:23:34,240 Speaker 1: And Bruce will come to you next man. Um, I 408 00:23:34,600 --> 00:23:37,159 Speaker 1: have to say, SARK is my favorite ticker that's not 409 00:23:37,200 --> 00:23:41,240 Speaker 1: our own. That's good. That's the first one we've had. 410 00:23:41,760 --> 00:23:45,240 Speaker 1: That's the first. Bruce, Well, I'm a little partial because 411 00:23:45,240 --> 00:23:47,399 Speaker 1: I've been working with John Davy over story for a 412 00:23:47,440 --> 00:23:50,359 Speaker 1: long time and we love pp I uh the first 413 00:23:50,400 --> 00:23:55,080 Speaker 1: inflation Global inflation protected ETFUM, you know that that's a 414 00:23:55,119 --> 00:24:00,200 Speaker 1: great ticker. That is a good one. All right, Max Rus, 415 00:24:00,240 --> 00:24:03,240 Speaker 1: thanks so much for joining us on Trillians. Thanks thanks 416 00:24:03,240 --> 00:24:12,640 Speaker 1: for having us, Thanks for listening to trillions. Until next time, 417 00:24:12,680 --> 00:24:15,440 Speaker 1: you can find us on the Bloomberg Terminal, Bloomberg dot com, 418 00:24:15,560 --> 00:24:19,119 Speaker 1: Apple Podcast Spotify, and wherever else you'd like to listen. 419 00:24:19,720 --> 00:24:21,920 Speaker 1: We'd love to hear from you. We're on Twitter, I'm 420 00:24:22,000 --> 00:24:25,560 Speaker 1: at Joel Weber Show. He's at Eric Baltunas. This episode 421 00:24:25,560 --> 00:24:28,840 Speaker 1: of Trilliance was produced by Magnus Hendrickson. Francesca Levie is 422 00:24:28,840 --> 00:24:43,760 Speaker 1: the head of Bloomberg Podcast. Bye.