1 00:00:06,320 --> 00:00:09,040 Speaker 1: Welcome to trillions. I'm Joel Weber and I'm Eric bel 2 00:00:09,080 --> 00:00:14,240 Speaker 1: Tunis Eric, I've lost track of time. Has it been 3 00:00:14,280 --> 00:00:16,800 Speaker 1: two months? Three months? What day of the week is that? 4 00:00:16,840 --> 00:00:21,479 Speaker 1: I don't even know? It's Tuesday. I know this because 5 00:00:22,000 --> 00:00:25,560 Speaker 1: I'm actually going away for a couple of days on Thursday. 6 00:00:25,640 --> 00:00:28,520 Speaker 1: So now I've got back into some degree of a calendar. Oh, 7 00:00:28,520 --> 00:00:32,760 Speaker 1: you've got like a countdown. You're you're going to travel somewhere. Yeah, man, 8 00:00:32,920 --> 00:00:36,800 Speaker 1: I'm I'm I'm I'm risking it. My dad lives in 9 00:00:36,800 --> 00:00:40,120 Speaker 1: the Panhandle of Florida, Miramar Beach. They opened the beaches 10 00:00:40,120 --> 00:00:43,120 Speaker 1: there a couple of weeks ago. He's lives by himself. 11 00:00:43,200 --> 00:00:45,360 Speaker 1: He's been going crazy. So I'm gonna bring my oldest son. 12 00:00:45,360 --> 00:00:48,920 Speaker 1: We're gonna fly down on on tickets that were a 13 00:00:49,000 --> 00:00:52,320 Speaker 1: third of the normal cost and then use that extra 14 00:00:52,360 --> 00:00:54,800 Speaker 1: budget to you know, eat like kings down there, go 15 00:00:54,840 --> 00:00:57,200 Speaker 1: to the beach. It's gonna be nice and hot and warm. 16 00:00:57,320 --> 00:00:59,680 Speaker 1: To be careful when we, you know, leave the house 17 00:01:00,680 --> 00:01:02,520 Speaker 1: through the you know, the airport and the airplane. But 18 00:01:02,560 --> 00:01:05,280 Speaker 1: we have masks, and you're braver than I am, my friend, 19 00:01:05,800 --> 00:01:07,720 Speaker 1: So you're going to the beach. And you're taking a 20 00:01:07,840 --> 00:01:11,600 Speaker 1: flight to Florida, which brings us to the theme of 21 00:01:11,680 --> 00:01:15,400 Speaker 1: this episode of Trains. Um, we're gonna speak with Frank Holmes, 22 00:01:15,800 --> 00:01:20,000 Speaker 1: the CEO of the E t F Jets, which I'm 23 00:01:20,000 --> 00:01:23,319 Speaker 1: really excited about because this E t F right now, 24 00:01:23,480 --> 00:01:25,680 Speaker 1: Eric's just there seems to be a ton of interest 25 00:01:25,720 --> 00:01:29,280 Speaker 1: in it, right yeah, you know, Um, I'm calling it 26 00:01:29,440 --> 00:01:33,200 Speaker 1: Jet Sanity because it reminds me of Lynn Sanity. Remember 27 00:01:33,200 --> 00:01:35,800 Speaker 1: that little point guard Asian point guard from like two 28 00:01:35,840 --> 00:01:39,680 Speaker 1: thousand twelve who came off the bench and like schooled 29 00:01:39,760 --> 00:01:41,880 Speaker 1: Kobe Bryant and like took over New York City for 30 00:01:41,920 --> 00:01:46,400 Speaker 1: about two months. This is yeah, this is the same thing, 31 00:01:46,440 --> 00:01:48,280 Speaker 1: except for an E T F. Let me give you 32 00:01:48,320 --> 00:01:53,560 Speaker 1: some numbers on jets. Jets went like years with a 33 00:01:53,680 --> 00:01:56,360 Speaker 1: flow here and there over the course of a year. 34 00:01:56,880 --> 00:02:01,880 Speaker 1: Then it goes down like right during the crisis. Since 35 00:02:01,920 --> 00:02:05,040 Speaker 1: it went down, it's attracted a lot of people looking 36 00:02:05,080 --> 00:02:07,640 Speaker 1: to play a rebound. But here's the stats that I'm 37 00:02:07,720 --> 00:02:10,919 Speaker 1: just so blown away by. It's taken in flows for 38 00:02:11,080 --> 00:02:15,520 Speaker 1: forty eight forty nine straight days, which is unheard of. 39 00:02:16,040 --> 00:02:19,400 Speaker 1: Vanguard does that on occasion, and that's Vanguard. This is 40 00:02:19,400 --> 00:02:22,400 Speaker 1: a theme et F. It's also taken in six and 41 00:02:22,480 --> 00:02:26,720 Speaker 1: sixty three million. This fund had maybe twenty million UM 42 00:02:26,720 --> 00:02:29,600 Speaker 1: three months ago, and so we compared it to other 43 00:02:29,680 --> 00:02:33,239 Speaker 1: theme ETFs when they quote caught fire like Robo, m 44 00:02:33,360 --> 00:02:37,799 Speaker 1: J and Hack, and those did nothing. They couldn't even 45 00:02:37,840 --> 00:02:40,839 Speaker 1: touch this amount of intensity in terms of a theme 46 00:02:40,880 --> 00:02:44,720 Speaker 1: ETF sort of like capturing the moment. So there's that, 47 00:02:44,880 --> 00:02:48,560 Speaker 1: and then there's the issue of all the people buying it. 48 00:02:48,720 --> 00:02:51,600 Speaker 1: A lot of them are likely retail investors who are 49 00:02:51,600 --> 00:02:54,000 Speaker 1: taken the other side of a trade for more and Buffett. 50 00:02:54,240 --> 00:02:56,600 Speaker 1: So you've got this David and Goliath trade going on, 51 00:02:56,919 --> 00:02:59,360 Speaker 1: Buffetts selling airlines, and you've got a lot of retails 52 00:02:59,360 --> 00:03:01,680 Speaker 1: saying no, it's to go up. And who will win 53 00:03:01,720 --> 00:03:04,120 Speaker 1: we don't know, but it's fascinating story. So I'm looking 54 00:03:04,160 --> 00:03:08,919 Speaker 1: at the Jets share price and it's basically been flat 55 00:03:09,120 --> 00:03:12,360 Speaker 1: until early February, and then all of a sudden it 56 00:03:12,360 --> 00:03:19,279 Speaker 1: starts to come down, and by March it has plunged 57 00:03:19,919 --> 00:03:24,040 Speaker 1: from about just around thirty dollars UM in the middle 58 00:03:24,080 --> 00:03:30,000 Speaker 1: of February to about twelve dollars in mid March. It's 59 00:03:30,040 --> 00:03:32,079 Speaker 1: sort of recovered and then has kind of come back 60 00:03:32,080 --> 00:03:34,800 Speaker 1: down and now it's aid about twelve dollars. That is 61 00:03:34,840 --> 00:03:48,000 Speaker 1: an epic, epic change, this time on trillions. Jet Sanity, Frank, 62 00:03:48,120 --> 00:03:51,400 Speaker 1: welcome to trillions. I gotta ask you, this has been 63 00:03:51,840 --> 00:03:56,840 Speaker 1: um clearly a weird stretch in the history of the world. 64 00:03:57,480 --> 00:03:59,560 Speaker 1: And you know you happen to be sort of like 65 00:04:00,040 --> 00:04:03,920 Speaker 1: lying in a cockpit of a plane that your business 66 00:04:03,960 --> 00:04:06,880 Speaker 1: model has been really disrupted. Here when did you get 67 00:04:06,880 --> 00:04:09,960 Speaker 1: a sense of how bad this might get? Well, you know, 68 00:04:10,040 --> 00:04:12,840 Speaker 1: I started this at this jet c t F five 69 00:04:12,920 --> 00:04:17,080 Speaker 1: years ago and that was almost where the where I 70 00:04:17,160 --> 00:04:20,640 Speaker 1: launched it with a flow started coming in massively and 71 00:04:20,640 --> 00:04:23,080 Speaker 1: it went nowhere. We went to a hundred millions shortly 72 00:04:23,800 --> 00:04:26,920 Speaker 1: right after we launched it, and then it went nowhere, sideways, 73 00:04:27,040 --> 00:04:29,960 Speaker 1: up and down. And it's interesting because you mentioned hack. 74 00:04:30,120 --> 00:04:33,679 Speaker 1: You know, Hack didn't really grow until Sony was hacked 75 00:04:33,920 --> 00:04:35,800 Speaker 1: and all of a sudden it woke up. And the 76 00:04:35,839 --> 00:04:39,839 Speaker 1: same thing happens with with the airline ETF. And we've 77 00:04:39,839 --> 00:04:43,400 Speaker 1: been doing webcasts now four times a year to r 78 00:04:43,640 --> 00:04:46,960 Speaker 1: A S only and family offices across the nation. We've 79 00:04:47,000 --> 00:04:49,880 Speaker 1: done about twenty of them over the past five years, 80 00:04:49,960 --> 00:04:54,040 Speaker 1: and it seems that this audience and specially heads funds 81 00:04:54,080 --> 00:04:57,120 Speaker 1: that play the airline industry, came into it. We know 82 00:04:57,320 --> 00:04:59,880 Speaker 1: that we've had a lot of small heads funds that 83 00:05:00,400 --> 00:05:02,320 Speaker 1: will go along the e t F to short the 84 00:05:02,320 --> 00:05:05,040 Speaker 1: stocks they don't like in the airline industry, and they 85 00:05:05,080 --> 00:05:07,360 Speaker 1: play it this way as they're sort of a pear's trade. 86 00:05:08,360 --> 00:05:12,719 Speaker 1: But it really accelerated as the fun fell. It's just 87 00:05:12,920 --> 00:05:15,880 Speaker 1: like hack. Hack had to get solely to get hacked 88 00:05:16,040 --> 00:05:18,800 Speaker 1: to all of a sudden being become aware, and that's 89 00:05:18,839 --> 00:05:22,240 Speaker 1: it took place here. When we analyze thematic e t 90 00:05:22,440 --> 00:05:25,479 Speaker 1: F s, we always say they need a shiny object 91 00:05:25,520 --> 00:05:28,960 Speaker 1: moment to get going, and you're right. Hack was the 92 00:05:29,000 --> 00:05:32,719 Speaker 1: sony hack. But the thing was that boosted cybersecurity stocks. 93 00:05:33,320 --> 00:05:35,800 Speaker 1: Same thing with Robo and MJ it was when they 94 00:05:35,800 --> 00:05:38,599 Speaker 1: went up. This is the rare case where the shiny 95 00:05:38,640 --> 00:05:42,240 Speaker 1: object was in the decline. And I'm guessing it's the 96 00:05:42,279 --> 00:05:44,680 Speaker 1: pe ratio. I think at one point the pe of 97 00:05:45,240 --> 00:05:48,760 Speaker 1: jets was like four or five. I think I looked 98 00:05:48,800 --> 00:05:51,000 Speaker 1: one time the only thing lower was Nigeria and the 99 00:05:51,040 --> 00:05:55,640 Speaker 1: coal industry. How much of the people are retail bottom callers? 100 00:05:56,400 --> 00:05:58,560 Speaker 1: They do you find versus sort of the hedge funds 101 00:05:59,800 --> 00:06:02,920 Speaker 1: at the beginning was predominantly heads funds that came in. 102 00:06:03,920 --> 00:06:07,400 Speaker 1: That's what we've we've found, uh, And what we would 103 00:06:07,400 --> 00:06:10,880 Speaker 1: hear from them is that they've done this research of 104 00:06:10,960 --> 00:06:13,040 Speaker 1: how long did it take for the airline industry to 105 00:06:13,160 --> 00:06:18,600 Speaker 1: rebound after the tech bubble after nine eleven, after Stars 106 00:06:18,960 --> 00:06:22,039 Speaker 1: after two thousand and eight nine That trough to peak, 107 00:06:22,760 --> 00:06:26,800 Speaker 1: Uh took from eight months to eighteen months, and was 108 00:06:26,920 --> 00:06:30,640 Speaker 1: from eight to a hundred percent return on your money. 109 00:06:31,080 --> 00:06:33,880 Speaker 1: And they were the first coming in looking for that bounce. 110 00:06:35,440 --> 00:06:39,359 Speaker 1: So I gotta ask because when you know, the last 111 00:06:39,400 --> 00:06:42,720 Speaker 1: time something that's significant really happened to the airline industry 112 00:06:42,800 --> 00:06:46,480 Speaker 1: was September eleventh, So here we are almost twenty years later. 113 00:06:47,080 --> 00:06:50,680 Speaker 1: Airlines clearly came back after that. UM, you had a 114 00:06:50,720 --> 00:06:53,919 Speaker 1: lot of institutional investors, including really noteworthy ones like the 115 00:06:53,920 --> 00:06:57,120 Speaker 1: Warren Buffets of the world after the financial crisis, who 116 00:06:57,160 --> 00:06:59,080 Speaker 1: came in and and you know, doubled down and made 117 00:06:59,080 --> 00:07:02,200 Speaker 1: a ton of money. But like the outlook for airlines 118 00:07:02,320 --> 00:07:04,760 Speaker 1: right now, like we could just be looking at a 119 00:07:04,760 --> 00:07:08,039 Speaker 1: lot of video conferences going forward and business travel that 120 00:07:08,160 --> 00:07:12,360 Speaker 1: never comes back. What's your outlook for the airline industry 121 00:07:12,680 --> 00:07:16,920 Speaker 1: from where you're sitting. So what is different is that 122 00:07:17,040 --> 00:07:21,200 Speaker 1: the Beltway agencies and party what they like to call 123 00:07:21,240 --> 00:07:26,200 Speaker 1: it sometimes and the and the administration are very cognizant 124 00:07:26,680 --> 00:07:31,080 Speaker 1: uh being slow to support the airline industry. The FA 125 00:07:31,320 --> 00:07:33,920 Speaker 1: came out and said one in fifteen jobs are related 126 00:07:33,920 --> 00:07:37,400 Speaker 1: to the airline industry. So it has a huge multiplying 127 00:07:37,400 --> 00:07:40,600 Speaker 1: effect in his crucial for the hotels are turned around. 128 00:07:40,880 --> 00:07:43,920 Speaker 1: Right now in Vegas, there's two hundred thousand empty rooms, 129 00:07:44,200 --> 00:07:47,680 Speaker 1: three thousand people have lost their jobs. Uh, something's got 130 00:07:47,680 --> 00:07:50,720 Speaker 1: to come back to get this multiplying effect of the economy. 131 00:07:51,080 --> 00:07:55,600 Speaker 1: So there's a much greater focus on revising the airline 132 00:07:55,680 --> 00:08:00,360 Speaker 1: industry based on previous studies. So that's the big game 133 00:08:00,440 --> 00:08:04,440 Speaker 1: changer here. And you saw from the cares Act how 134 00:08:04,520 --> 00:08:08,560 Speaker 1: fast they responded, even when the negotiations were quick, get 135 00:08:08,560 --> 00:08:11,960 Speaker 1: the money in maintained and get this industry turned around. 136 00:08:12,280 --> 00:08:15,600 Speaker 1: So I think that that's very positive, a constructive. The 137 00:08:15,720 --> 00:08:18,120 Speaker 1: other thing that's really interesting for me is is the 138 00:08:18,200 --> 00:08:22,760 Speaker 1: t s A publishes every day how many people they 139 00:08:23,120 --> 00:08:27,560 Speaker 1: for the four airports they tracked, UH people they've screened, 140 00:08:28,080 --> 00:08:32,640 Speaker 1: and that bottomed in April, we were almost doubled a 141 00:08:32,720 --> 00:08:35,960 Speaker 1: number of people flying every day, and and there's new 142 00:08:36,000 --> 00:08:39,000 Speaker 1: indicators coming out. And the other thing we've noticed is 143 00:08:39,120 --> 00:08:42,880 Speaker 1: Google trends, so looking for people looking for hotels and 144 00:08:42,920 --> 00:08:46,880 Speaker 1: looking for travel. That's picked up, and it's really searched 145 00:08:46,880 --> 00:08:50,760 Speaker 1: in Asia, which is sort of bottomed first. And I 146 00:08:50,800 --> 00:08:54,320 Speaker 1: think as we come back into this economy, we're going 147 00:08:54,360 --> 00:08:57,400 Speaker 1: to see more and more searches and and the sentiment, 148 00:08:57,480 --> 00:09:01,920 Speaker 1: the quant funds that you sentiment indicators are looking at 149 00:09:01,960 --> 00:09:05,200 Speaker 1: these two factors and they're plowing into it. That's what 150 00:09:05,280 --> 00:09:09,080 Speaker 1: we hear and what we see. Well, what's interesting to me. 151 00:09:09,559 --> 00:09:11,959 Speaker 1: You look at the holdings of this just so people listening, No, 152 00:09:12,120 --> 00:09:15,480 Speaker 1: it's in it. It's pretty obvious. Southwest Airlines, American Airlines, 153 00:09:15,520 --> 00:09:18,400 Speaker 1: Delta Airlines, United Airlines. Then you get down to things 154 00:09:18,400 --> 00:09:23,280 Speaker 1: like Spirit Airlines, um Quantas, So it's global, but it's 155 00:09:23,320 --> 00:09:28,040 Speaker 1: not just a market cap waited plane vanilla or just 156 00:09:28,360 --> 00:09:33,600 Speaker 1: simplistic uh construction. There's a couple of wirings in the 157 00:09:33,640 --> 00:09:36,760 Speaker 1: design of this e t F talk about how the 158 00:09:36,760 --> 00:09:39,480 Speaker 1: actual process works to put these holdings in there. Although 159 00:09:39,480 --> 00:09:43,400 Speaker 1: they seem obvious, it might not be exactly what people think. Right, Well, 160 00:09:43,679 --> 00:09:46,480 Speaker 1: thank you for that opportunity, because there was thousands of 161 00:09:46,520 --> 00:09:51,400 Speaker 1: hours put into this UH and to understand it is 162 00:09:51,440 --> 00:09:55,280 Speaker 1: it um. What we looked at is that there's lots 163 00:09:55,320 --> 00:09:58,080 Speaker 1: of bull of Zilian currencies and they can really be 164 00:09:58,200 --> 00:10:02,800 Speaker 1: a big drag or head wind or tail winds your performance. 165 00:10:03,280 --> 00:10:05,440 Speaker 1: So when we created this, we said, okay, what are 166 00:10:05,440 --> 00:10:08,599 Speaker 1: the most five most important factors. And each night it 167 00:10:08,600 --> 00:10:11,160 Speaker 1: would take eight hours ago and test a factor. And 168 00:10:11,160 --> 00:10:13,640 Speaker 1: then we tested on two systems. We tested on fact 169 00:10:13,679 --> 00:10:16,680 Speaker 1: Set and we tested on Bloomberg to go back over 170 00:10:16,760 --> 00:10:19,520 Speaker 1: ten years of data that see the robustness of which 171 00:10:19,559 --> 00:10:26,160 Speaker 1: factor is UH deals well with rise economy, following economy, kruptcies, etcetera. 172 00:10:26,520 --> 00:10:29,920 Speaker 1: So we distilled them down to five key factors. And 173 00:10:29,960 --> 00:10:32,800 Speaker 1: then we took a look at waitings and we found 174 00:10:32,840 --> 00:10:39,000 Speaker 1: that the four big guys that is American Airlines, Delta, H, Southwest, 175 00:10:39,080 --> 00:10:43,880 Speaker 1: and United they capture about eighty of the traffic UH. 176 00:10:43,920 --> 00:10:48,760 Speaker 1: And so the portfolio because of limitations of legatory limitations, 177 00:10:48,800 --> 00:10:52,200 Speaker 1: we said, have we maximized that? And we have four names. 178 00:10:52,600 --> 00:10:56,040 Speaker 1: Those names twelve percent each and each quarter we re 179 00:10:56,280 --> 00:10:59,239 Speaker 1: calibrate those. So that's forty eight percent of the portfolio 180 00:10:59,800 --> 00:11:04,400 Speaker 1: is really capturing the bulk of domestic travel. Now, when 181 00:11:04,440 --> 00:11:07,199 Speaker 1: we went to foreign names and went outside of that 182 00:11:07,520 --> 00:11:11,840 Speaker 1: like uh IS, we went one for twenty names, and 183 00:11:11,920 --> 00:11:15,760 Speaker 1: that mitigated this currency volatility and allows us to catch 184 00:11:15,800 --> 00:11:19,320 Speaker 1: those stocks that have the best factors like highest castle 185 00:11:19,400 --> 00:11:22,719 Speaker 1: returns to investor capital growth and revue last quarter or 186 00:11:22,800 --> 00:11:26,920 Speaker 1: four quarters gulth and castle last quo four quarters UH 187 00:11:27,200 --> 00:11:29,920 Speaker 1: and other factors they look at for traffic flow of 188 00:11:30,000 --> 00:11:33,560 Speaker 1: the humory passenger seats, who have et cetera UH, and 189 00:11:33,720 --> 00:11:36,720 Speaker 1: in between there in between those twenty names we have 190 00:11:36,840 --> 00:11:40,240 Speaker 1: that are foreign and the four big names, we have 191 00:11:40,320 --> 00:11:43,880 Speaker 1: a small group of names that are that are airports. 192 00:11:44,320 --> 00:11:49,040 Speaker 1: They can be airports, they can be Boeing Airbus UH, 193 00:11:49,120 --> 00:11:54,120 Speaker 1: they can be manufacturers, and that's where Hawaiian Airlines, Messa Airlines, 194 00:11:54,679 --> 00:11:58,800 Speaker 1: Spirit all these other sort of smaller airlines would show up. 195 00:11:59,160 --> 00:12:02,520 Speaker 1: But it's more of a consolidated name of those are 196 00:12:02,520 --> 00:12:06,079 Speaker 1: the most attractive, and each quarter we kicked them out 197 00:12:06,120 --> 00:12:08,360 Speaker 1: and we bring them in if they don't have the 198 00:12:08,440 --> 00:12:11,720 Speaker 1: highest cash board returns on invest in capital, if they're 199 00:12:11,720 --> 00:12:15,240 Speaker 1: not showing revue growing. So it's a dynamic approach each 200 00:12:15,320 --> 00:12:24,000 Speaker 1: quarter except for the big four names. So can you 201 00:12:24,040 --> 00:12:27,359 Speaker 1: walk us through sort of what happened this last rebalance, 202 00:12:27,400 --> 00:12:30,000 Speaker 1: because obviously that's in the middle of all of this, 203 00:12:30,120 --> 00:12:33,120 Speaker 1: like what what basically what opportunities did you guys see 204 00:12:33,160 --> 00:12:36,560 Speaker 1: and how did you really allocate things? Then give you 205 00:12:37,200 --> 00:12:39,559 Speaker 1: a really interesting part was that it was nine months 206 00:12:39,559 --> 00:12:44,120 Speaker 1: ago that Boeing was kicked out. Uh, and then all 207 00:12:44,160 --> 00:12:47,000 Speaker 1: the problems started coming. And you can see that showing 208 00:12:47,120 --> 00:12:49,960 Speaker 1: up in this this sort of quant approach quantum they 209 00:12:49,960 --> 00:12:51,960 Speaker 1: call it plunt of mentals, a combination of a quant 210 00:12:51,960 --> 00:12:57,000 Speaker 1: approach of factors and fundamental analysis um. And and so 211 00:12:57,160 --> 00:13:01,280 Speaker 1: we we see that rotation, and we see that we 212 00:13:01,400 --> 00:13:08,559 Speaker 1: own Messa populated. Then you have Hawaiian Airlines populated, Alaska populated. 213 00:13:08,800 --> 00:13:12,560 Speaker 1: How this quarter will take place? Uh, the March numbers 214 00:13:12,559 --> 00:13:16,080 Speaker 1: as they're slowly coming in. For the smaller names, we 215 00:13:16,160 --> 00:13:19,240 Speaker 1: don't have them all. All the financials are not published 216 00:13:19,320 --> 00:13:20,959 Speaker 1: to be able to give you how that change is 217 00:13:21,000 --> 00:13:24,240 Speaker 1: gonna happen this quarter. But there will be rotations, and 218 00:13:24,320 --> 00:13:26,839 Speaker 1: probably some of the biggest rotations will take outside of 219 00:13:26,880 --> 00:13:29,880 Speaker 1: the US where we have the twenty names. Remember this 220 00:13:29,960 --> 00:13:33,040 Speaker 1: is a this is a portfolio thirty three names, four 221 00:13:33,160 --> 00:13:37,040 Speaker 1: or forty eight percent and twenty or one. So it's 222 00:13:37,080 --> 00:13:40,360 Speaker 1: a very compressed portfolio. And our bogie is to beat 223 00:13:40,400 --> 00:13:43,679 Speaker 1: the New York Stock has change Global Airline Index. And 224 00:13:43,720 --> 00:13:46,199 Speaker 1: that's what we've done with this model, uh since we 225 00:13:46,360 --> 00:13:52,000 Speaker 1: launched it. And you know, let's obviously diversifying. You you 226 00:13:52,080 --> 00:13:54,240 Speaker 1: limit your upside, but you limit your downside, right, And 227 00:13:54,240 --> 00:13:57,320 Speaker 1: I think that's part of what people are interested in 228 00:13:57,360 --> 00:14:00,040 Speaker 1: when they buy an ETF over a single stock of 229 00:14:00,160 --> 00:14:03,199 Speaker 1: to do research on every single company UM. One question 230 00:14:03,240 --> 00:14:05,320 Speaker 1: I had just going back to the outlook on airlines, 231 00:14:05,400 --> 00:14:08,400 Speaker 1: is the price to earnings ratio on this is currently 232 00:14:08,480 --> 00:14:13,760 Speaker 1: nine and the price to earnings UM ratio for the 233 00:14:14,000 --> 00:14:19,880 Speaker 1: S and P is four. Right, the airlines do do they? 234 00:14:20,040 --> 00:14:23,480 Speaker 1: Do they need to even rebound fully, like let's say 235 00:14:23,520 --> 00:14:27,360 Speaker 1: they rebound halfway or six of the way. How much 236 00:14:27,600 --> 00:14:32,800 Speaker 1: could that validate the bottom calling or will therell be 237 00:14:32,880 --> 00:14:36,720 Speaker 1: bankruptcies which will take down the winners? How does that 238 00:14:36,720 --> 00:14:39,280 Speaker 1: play out if say we go to fifty or six 239 00:14:39,720 --> 00:14:44,480 Speaker 1: in the next two years not a hundred. I think 240 00:14:44,520 --> 00:14:48,080 Speaker 1: that the difference is is that there's such a focus 241 00:14:48,200 --> 00:14:52,480 Speaker 1: by the government both politicians and the agencies to get 242 00:14:52,520 --> 00:14:57,479 Speaker 1: this industry turned around for job creation and the multiplying 243 00:14:57,480 --> 00:15:00,640 Speaker 1: effect from jobs from the airline industry. I've never seen 244 00:15:00,680 --> 00:15:04,200 Speaker 1: it before to this degree. Um, so I think you're 245 00:15:04,200 --> 00:15:07,840 Speaker 1: going to get a higher bet, higher percentage of survivors. 246 00:15:08,360 --> 00:15:12,160 Speaker 1: One that's really that's sort of that the dust was Avianca. 247 00:15:12,720 --> 00:15:17,600 Speaker 1: Arianca uh will hurt United because of debt lendings and 248 00:15:18,240 --> 00:15:22,480 Speaker 1: clone dusting. But really Avianca couldn't get government support because 249 00:15:22,480 --> 00:15:26,680 Speaker 1: after they restructured their company over fifteen years ago, um, 250 00:15:26,840 --> 00:15:29,800 Speaker 1: they moved at the Panama So the government of Columbia 251 00:15:29,920 --> 00:15:34,920 Speaker 1: wasn't going to support them because they don't pay corporate taxes. 252 00:15:34,920 --> 00:15:37,520 Speaker 1: Everything's went through Panama, and that was the case that 253 00:15:37,560 --> 00:15:40,440 Speaker 1: it couldn't get government support. But that's not here. Here 254 00:15:40,440 --> 00:15:43,320 Speaker 1: we've got to menace government support. And the same thing 255 00:15:43,640 --> 00:15:46,600 Speaker 1: is in Europe. And the other part that you're seeing 256 00:15:46,600 --> 00:15:49,040 Speaker 1: here is like today, I believe the said starts buying 257 00:15:50,880 --> 00:15:55,920 Speaker 1: corporate bond ets, so they're trying to create a stability. 258 00:15:56,320 --> 00:15:59,320 Speaker 1: They're trying to get those rates down because what's happened 259 00:16:00,040 --> 00:16:02,480 Speaker 1: in that market you don't really see like the tip 260 00:16:02,520 --> 00:16:05,320 Speaker 1: of the iceberg. Oh, the ten year government bonds down 261 00:16:05,320 --> 00:16:09,760 Speaker 1: to sixty basis points. Money is cheap, Actually it's not. Um. 262 00:16:09,880 --> 00:16:14,520 Speaker 1: The cost of mezzanine funding shot from about a four 263 00:16:14,560 --> 00:16:19,840 Speaker 1: percent role to eight to eleven percent role. Every heads 264 00:16:19,880 --> 00:16:22,440 Speaker 1: fund that's in that space, every special lender in that 265 00:16:22,520 --> 00:16:26,320 Speaker 1: space automatic, it's just ratchet it up with all these covenants. 266 00:16:26,360 --> 00:16:30,320 Speaker 1: For two year money is eight percent, it's not thirty 267 00:16:30,360 --> 00:16:33,720 Speaker 1: basis points. And so the government I think is coming 268 00:16:33,720 --> 00:16:37,280 Speaker 1: in to try to stabilize corporate lending by buying these 269 00:16:37,320 --> 00:16:41,640 Speaker 1: A T s. That's very beneficial to the airline industry. Also. 270 00:16:43,360 --> 00:16:45,400 Speaker 1: So let me let me ask a slightly different way 271 00:16:45,440 --> 00:16:47,800 Speaker 1: than what do you think the worst case scenario might 272 00:16:47,840 --> 00:16:52,000 Speaker 1: be for jets? Are you thinking okay? So engage in 273 00:16:52,040 --> 00:16:56,240 Speaker 1: the bounce. The bounce has historically been from eight to 274 00:16:56,280 --> 00:17:00,440 Speaker 1: a hundred and so if you're embarrassed, really, Barris, we 275 00:17:00,480 --> 00:17:01,920 Speaker 1: think it is going to be a short lived one. 276 00:17:02,400 --> 00:17:07,240 Speaker 1: Or are you then you're gonna get sun from the lows? Uh? 277 00:17:07,359 --> 00:17:09,720 Speaker 1: If they do tork it up that year from now, 278 00:17:09,880 --> 00:17:14,639 Speaker 1: we could see doubles. You've you've you mentioned how hedge 279 00:17:14,640 --> 00:17:17,640 Speaker 1: funds were in early and looking at holders, I can 280 00:17:17,640 --> 00:17:20,400 Speaker 1: see that it was like there's a Canner Fitzgerald position 281 00:17:20,520 --> 00:17:24,440 Speaker 1: and invest Net Asset Management uh ubs is in their 282 00:17:24,560 --> 00:17:29,359 Speaker 1: degreen capital management. Those are you know, people who tend 283 00:17:29,400 --> 00:17:31,479 Speaker 1: to know what they're doing when they're getting in here, 284 00:17:31,520 --> 00:17:34,720 Speaker 1: and you know, can stomach volatility. Eric also points out 285 00:17:34,760 --> 00:17:37,880 Speaker 1: that number of robin Hood investors over the last two 286 00:17:37,920 --> 00:17:43,280 Speaker 1: months went from three hundred to twenty thousand. That's pretty significant, 287 00:17:43,960 --> 00:17:46,560 Speaker 1: wondering what it's like to suddenly have that many retail 288 00:17:46,600 --> 00:17:52,480 Speaker 1: investors show up well, as I think it would take 289 00:17:52,520 --> 00:17:55,359 Speaker 1: a look at an ecosystem and you've got to have 290 00:17:55,720 --> 00:17:59,680 Speaker 1: minnows with the tunas and these sharks and there's whales. 291 00:18:00,080 --> 00:18:03,320 Speaker 1: You need a complete ecosystem and uh and it's so 292 00:18:03,359 --> 00:18:05,560 Speaker 1: good to see that you have a bunch of minnows 293 00:18:05,600 --> 00:18:10,000 Speaker 1: because it does create a real dynamic market so that 294 00:18:10,040 --> 00:18:12,760 Speaker 1: you can see the volume trades millions of shares a day. 295 00:18:13,080 --> 00:18:17,560 Speaker 1: So I'm really thrilled about that UM and I think 296 00:18:17,600 --> 00:18:21,520 Speaker 1: that will continue. And I think that the idea that 297 00:18:21,600 --> 00:18:24,520 Speaker 1: more and these younger investors that are coming in through 298 00:18:24,600 --> 00:18:28,120 Speaker 1: Robin they're much more quick to take a look at 299 00:18:28,600 --> 00:18:30,480 Speaker 1: is the t S a data that comes with every 300 00:18:30,560 --> 00:18:34,720 Speaker 1: day tracking that putting moving averages on that data, or 301 00:18:34,720 --> 00:18:37,439 Speaker 1: look at Google trends, uh to all of a sudden 302 00:18:37,560 --> 00:18:40,240 Speaker 1: go along and trade in and out around those positions. 303 00:18:40,280 --> 00:18:43,480 Speaker 1: So I think it's great because it will attract bigger 304 00:18:43,520 --> 00:18:47,560 Speaker 1: institution money. I spend a lot of time tracking the 305 00:18:47,560 --> 00:18:50,280 Speaker 1: E T F industry, the winners and losers. To me, 306 00:18:50,320 --> 00:18:52,960 Speaker 1: it reminds me of Silicon Valley. Um, there's a lot 307 00:18:52,960 --> 00:18:56,000 Speaker 1: of innovation and but a lot of failure. Just talk 308 00:18:56,080 --> 00:18:58,800 Speaker 1: about take us into what it's just like to have 309 00:18:58,880 --> 00:19:02,479 Speaker 1: a hit, um, especially when it looked like, you know, 310 00:19:02,520 --> 00:19:05,720 Speaker 1: you go months and months with your literally an oblivion. Yeah. 311 00:19:05,840 --> 00:19:07,760 Speaker 1: I looked at it. It's like you're bobbing along and 312 00:19:07,800 --> 00:19:11,679 Speaker 1: it's averaging dollars a share, and then all of a sudden, 313 00:19:11,680 --> 00:19:14,840 Speaker 1: you know, you know, you have the pandemic hit. Yeah. 314 00:19:14,880 --> 00:19:17,199 Speaker 1: And once you get this kind of liquidity, even if 315 00:19:17,240 --> 00:19:19,240 Speaker 1: it goes up and some people take profits in your 316 00:19:19,240 --> 00:19:23,320 Speaker 1: assets maybe go down to three million, you've now become 317 00:19:23,960 --> 00:19:26,240 Speaker 1: the go to airline spots. So you're you've kind of 318 00:19:26,280 --> 00:19:30,160 Speaker 1: made it. But just talk about that catching fire. What's 319 00:19:30,160 --> 00:19:34,439 Speaker 1: that like to see inflows every day after months and 320 00:19:34,480 --> 00:19:36,480 Speaker 1: months where you saw maybe one day of inflows in 321 00:19:36,520 --> 00:19:39,400 Speaker 1: like a year and a half. Oh, it's a wonderful 322 00:19:39,440 --> 00:19:43,159 Speaker 1: feeling because I'm not have that elation since back in 323 00:19:43,200 --> 00:19:46,320 Speaker 1: two thousand and six, where we were getting fifty million 324 00:19:46,359 --> 00:19:49,880 Speaker 1: a day into our gold neutral funds. I went out 325 00:19:50,400 --> 00:19:52,240 Speaker 1: and say, okay, I've got to get into the ETS. 326 00:19:52,359 --> 00:19:55,240 Speaker 1: I have to get out of mutual funds, have to diversify. 327 00:19:55,400 --> 00:19:59,000 Speaker 1: And I picked an industry because I noticed Eric that 328 00:19:59,200 --> 00:20:03,160 Speaker 1: my flights were all of a sudden limited by you know, 329 00:20:03,320 --> 00:20:06,720 Speaker 1: five years ago, actually starting with ten years ago, the 330 00:20:06,840 --> 00:20:09,680 Speaker 1: options to fly had dropped, the cost of a ticket 331 00:20:09,680 --> 00:20:12,480 Speaker 1: went up. So I said, how do I make money 332 00:20:12,480 --> 00:20:14,159 Speaker 1: with this and launch a product? And there was no 333 00:20:14,200 --> 00:20:19,359 Speaker 1: other airline ETS, so launching it and and nurturing it along, 334 00:20:19,720 --> 00:20:21,840 Speaker 1: you know, it was. It was lots of love and 335 00:20:21,920 --> 00:20:25,399 Speaker 1: nurturing it because knowing uh, it took a couple of 336 00:20:25,440 --> 00:20:27,639 Speaker 1: years and all of a sudden, buffet starts recognizing the 337 00:20:27,680 --> 00:20:31,960 Speaker 1: high returns of investor capital. I think that the economy turns, 338 00:20:32,160 --> 00:20:34,840 Speaker 1: he comes back in. That's what I think it will 339 00:20:34,880 --> 00:20:38,960 Speaker 1: be the game changer. So much of UM the airline's 340 00:20:39,400 --> 00:20:42,640 Speaker 1: profitability has been rooted in sort of the business class 341 00:20:42,760 --> 00:20:47,879 Speaker 1: or first crap class traveler. If that uh segment doesn't 342 00:20:47,920 --> 00:20:51,679 Speaker 1: come back for a long time potentially because you know, 343 00:20:51,760 --> 00:20:54,000 Speaker 1: companies say, you know what, no more flying, you can 344 00:20:54,040 --> 00:20:56,800 Speaker 1: just do video conferencing. What does that mean for the 345 00:20:56,840 --> 00:21:00,600 Speaker 1: airline industry? Well, that would be tragic for the airline 346 00:21:00,600 --> 00:21:04,040 Speaker 1: indust is no doubt. But we we see the first 347 00:21:04,080 --> 00:21:07,359 Speaker 1: catering is the business. Business people can't wait to go 348 00:21:07,520 --> 00:21:10,359 Speaker 1: and sell and tell and you yell the products and sales. 349 00:21:10,440 --> 00:21:13,359 Speaker 1: You need to have sales. That's what drives revenue. And 350 00:21:13,880 --> 00:21:18,280 Speaker 1: human interaction is so important for that. And the Southwest airlines, Uh, 351 00:21:18,760 --> 00:21:22,680 Speaker 1: they see that something more, you know, more than a 352 00:21:22,800 --> 00:21:27,040 Speaker 1: third of their further passages or business, but sevent their 353 00:21:27,080 --> 00:21:30,400 Speaker 1: profits that have higher margins business. And we've we talked 354 00:21:30,400 --> 00:21:34,399 Speaker 1: about Warren Buffett earlier. What advice, Well, what would you 355 00:21:34,440 --> 00:21:39,400 Speaker 1: tell him if you could tell him anything right now? Oh, 356 00:21:39,760 --> 00:21:44,159 Speaker 1: I look up to this idol. I would just to 357 00:21:44,400 --> 00:21:46,520 Speaker 1: share with them that things will turn. He always talks 358 00:21:46,520 --> 00:21:50,919 Speaker 1: about betting on America UM and he's worried about ten 359 00:21:51,000 --> 00:21:54,440 Speaker 1: billion dollars. Then just go and plunk it down and 360 00:21:54,480 --> 00:21:57,760 Speaker 1: give lots of capital. Southwest it's it's by far, you know, 361 00:21:57,840 --> 00:22:00,159 Speaker 1: one of the best run airlines along with doubts up. 362 00:22:00,440 --> 00:22:03,080 Speaker 1: When you look at all these types of metrics, UM, 363 00:22:03,760 --> 00:22:07,080 Speaker 1: take them out. This is really fascinating. And you know, 364 00:22:07,200 --> 00:22:11,840 Speaker 1: congratulations on your against the odds hit product. UM. You 365 00:22:11,920 --> 00:22:14,840 Speaker 1: know it's only about one in every twenty or thirty 366 00:22:14,920 --> 00:22:18,080 Speaker 1: them ETFs gets to where you are with you know, 367 00:22:18,440 --> 00:22:21,320 Speaker 1: over a hundred couple hundred million, UM, but yours is 368 00:22:21,359 --> 00:22:24,560 Speaker 1: special because of the intensity. Again, it's reminds me of 369 00:22:24,720 --> 00:22:28,359 Speaker 1: it's the theme ETF equivalent of insanity. Frank, Frank Holmes, 370 00:22:28,440 --> 00:22:31,280 Speaker 1: thanks for joining us on Trillions. Thank you for the 371 00:22:31,320 --> 00:22:37,000 Speaker 1: opportunity sharing my story. Thanks for listening to Trillions. Until 372 00:22:37,080 --> 00:22:39,080 Speaker 1: next time. You can find us on the Bloomberg terminal, 373 00:22:39,359 --> 00:22:43,560 Speaker 1: Bloomberg dot com, Apple Podcast, Spotify, or wherever else you'd 374 00:22:43,560 --> 00:22:45,760 Speaker 1: like to listen. We'd love to hear from you. We're 375 00:22:45,800 --> 00:22:50,199 Speaker 1: on Twitter, I'm at Joel Weber Show, He's at Eric Baltunas, 376 00:22:50,520 --> 00:22:54,159 Speaker 1: and you can find Frank Holmes at Bulldog Holmes and 377 00:22:54,320 --> 00:22:59,199 Speaker 1: also at us Funds. This episode of Trillions was produced 378 00:22:59,200 --> 00:23:02,680 Speaker 1: by Magnus Hendrick. Francesca Levy is the head of Bloomberg 379 00:23:02,760 --> 00:23:03,840 Speaker 1: Podcast by