1 00:00:00,800 --> 00:00:04,040 Speaker 1: Welcome to the Bloomberg Markets Podcast. I'm Paul Sweeney alongside 2 00:00:04,040 --> 00:00:06,920 Speaker 1: my co host Matt Miller. Every business day, we bring 3 00:00:06,960 --> 00:00:11,520 Speaker 1: you interviews from CEOs, market crows, and Bloomberg experts, along 4 00:00:11,560 --> 00:00:15,600 Speaker 1: with essential market moving news. Find the Bloomberg Markets Podcast 5 00:00:15,600 --> 00:00:18,479 Speaker 1: on Apple Podcasts or wherever you listen to podcasts, and 6 00:00:18,480 --> 00:00:22,599 Speaker 1: at Bloomberg dot com slash podcast. Last night was that 7 00:00:22,600 --> 00:00:24,520 Speaker 1: at a dinner with some friends Matt, including a young 8 00:00:24,520 --> 00:00:26,920 Speaker 1: woman who just graduated from nursing school. She's gonna start 9 00:00:26,920 --> 00:00:30,200 Speaker 1: her first full time job the Children's Hospital Philadelphia, which 10 00:00:30,200 --> 00:00:32,479 Speaker 1: is a great, great hospital, and it just she was 11 00:00:32,560 --> 00:00:36,280 Speaker 1: so enthusiastic and so passionate and committed. It just made 12 00:00:36,280 --> 00:00:38,760 Speaker 1: me feel good because you think about the folks of 13 00:00:38,840 --> 00:00:41,720 Speaker 1: it on our front lines of during this pandemic um 14 00:00:41,760 --> 00:00:44,280 Speaker 1: and just the stress they've been put under, and you 15 00:00:44,400 --> 00:00:46,559 Speaker 1: just wonder, you know, how they do it. UM. That's 16 00:00:46,560 --> 00:00:48,400 Speaker 1: where we like to talk to folks that are really 17 00:00:48,760 --> 00:00:51,800 Speaker 1: uh touched, you know, really tapped into that part of 18 00:00:51,840 --> 00:00:55,240 Speaker 1: the healthcare system. Jennet Elkin, president and Chief executive Officer 19 00:00:55,240 --> 00:00:58,200 Speaker 1: of Icon Medical Network, joins us Icon Medical found in 20 00:00:58,800 --> 00:01:02,440 Speaker 1: places physicians and actitioners on assignment in hospitals and health 21 00:01:02,440 --> 00:01:05,479 Speaker 1: care facilities in the US, so she really knows what's 22 00:01:05,480 --> 00:01:07,520 Speaker 1: going on the front lines. Janet, thanks so much for 23 00:01:07,600 --> 00:01:10,680 Speaker 1: joining us here. Again, it seems like in parts of 24 00:01:10,720 --> 00:01:13,240 Speaker 1: this country and other parts around the world, we're getting 25 00:01:13,240 --> 00:01:18,280 Speaker 1: another wave of COVID um cases. Here. What's it like 26 00:01:18,319 --> 00:01:22,960 Speaker 1: on the front lines. It's still extraordinarily busy, as you 27 00:01:23,000 --> 00:01:27,399 Speaker 1: can imagine. In addition to that, though, given that we're 28 00:01:27,440 --> 00:01:30,880 Speaker 1: seeing requirements for the vaccine really go up, as you 29 00:01:30,920 --> 00:01:34,360 Speaker 1: can imagine if they would do have to stop this 30 00:01:34,440 --> 00:01:37,479 Speaker 1: at some point. But what's happening now is it's getting 31 00:01:37,520 --> 00:01:40,480 Speaker 1: harder to place nurses who won't get the vaccine. So 32 00:01:40,600 --> 00:01:43,280 Speaker 1: it's kind of closing an interesting time right now in 33 00:01:43,360 --> 00:01:46,600 Speaker 1: terms of staffing these facilities. Well, I mean, do you 34 00:01:46,640 --> 00:01:49,640 Speaker 1: want to place a nurse who won't get the vaccine? 35 00:01:50,040 --> 00:01:55,120 Speaker 1: Do I really want a medical professional who, uh is 36 00:01:55,200 --> 00:01:59,960 Speaker 1: that obtuse working on me? I don't think so. Oh, 37 00:02:00,120 --> 00:02:03,120 Speaker 1: given that my dad died early from COVID even if 38 00:02:03,160 --> 00:02:06,240 Speaker 1: you hadn't, yeah, you really don't. So what's happening now 39 00:02:06,360 --> 00:02:10,560 Speaker 1: is that they're gravitating nurses towards those nurses towards facility 40 00:02:10,639 --> 00:02:13,480 Speaker 1: and also there are a few physicians out there who 41 00:02:13,520 --> 00:02:16,200 Speaker 1: won't get vaccinated, but it's becoming more difficult for them. 42 00:02:16,240 --> 00:02:19,560 Speaker 1: And in a way, although that's hard for facilities, it 43 00:02:19,680 --> 00:02:23,760 Speaker 1: also means that hopefully we will get more people vaccinated 44 00:02:24,000 --> 00:02:27,440 Speaker 1: and be able to affect better patient care. Janet, you know, 45 00:02:27,960 --> 00:02:29,840 Speaker 1: you know our views here in New York City obviously 46 00:02:29,919 --> 00:02:32,520 Speaker 1: skewed for much parts of for many parts of the 47 00:02:32,560 --> 00:02:36,560 Speaker 1: country talked to us about healthcare per you know, system 48 00:02:36,639 --> 00:02:40,400 Speaker 1: and staffing in more rural parts of America. I know 49 00:02:40,480 --> 00:02:43,920 Speaker 1: that was a challenge even before the pandemic. What's it 50 00:02:44,000 --> 00:02:48,160 Speaker 1: like now it continues to be. I mean, you've got, 51 00:02:48,600 --> 00:02:51,880 Speaker 1: if you think about it, not only COVID and what 52 00:02:52,040 --> 00:02:55,239 Speaker 1: that's caused in terms of medium more practitioners, the fact 53 00:02:55,280 --> 00:02:56,799 Speaker 1: that they didn't have enough to begin with in the 54 00:02:56,880 --> 00:02:59,560 Speaker 1: rural areas, and then on top of that as fallout 55 00:02:59,639 --> 00:03:01,440 Speaker 1: from OVID, and I think how it made people. We 56 00:03:01,560 --> 00:03:05,480 Speaker 1: think things the great resignation. Yes, we see it in 57 00:03:05,560 --> 00:03:08,840 Speaker 1: terms of nurses, physicians resigning, but some things you may 58 00:03:08,840 --> 00:03:11,600 Speaker 1: not think about, or even the recruiters who work for 59 00:03:11,639 --> 00:03:15,680 Speaker 1: health care facilities to place more permanent employees, they're also 60 00:03:15,720 --> 00:03:19,160 Speaker 1: moving on. So Jennet. Where are we in terms of 61 00:03:19,160 --> 00:03:21,080 Speaker 1: the pipeline? Again, last night I had dinner with a 62 00:03:21,080 --> 00:03:23,520 Speaker 1: young woman who just graduated nursing school. Where are we 63 00:03:23,560 --> 00:03:29,440 Speaker 1: in terms of putting out doctors, nurses, nurse practitioners, things 64 00:03:29,880 --> 00:03:34,160 Speaker 1: like that? Is how's the pipeline? I mean, the pipeline 65 00:03:34,200 --> 00:03:37,360 Speaker 1: is obviously not great. It takes quite a while to 66 00:03:37,880 --> 00:03:40,600 Speaker 1: be able to get your degree. Of course, physicians the 67 00:03:40,640 --> 00:03:45,240 Speaker 1: most right um CRNAs, which are advanced practice nurses who 68 00:03:45,280 --> 00:03:48,320 Speaker 1: go on traditional training. But even for our ends, I 69 00:03:48,360 --> 00:03:51,400 Speaker 1: mean it's they can't get them out fast enough. Now 70 00:03:51,560 --> 00:03:53,640 Speaker 1: the person who had dinner with is going to chop 71 00:03:53,840 --> 00:03:56,560 Speaker 1: which children's hospital and Filly is one of the most 72 00:03:56,600 --> 00:03:59,920 Speaker 1: desirable ones. But think about the hospitals that don't have 73 00:04:00,160 --> 00:04:04,520 Speaker 1: that kind of reputation. It's getting extraordinarily difficult to be 74 00:04:04,600 --> 00:04:08,480 Speaker 1: able to place in a practitioners. I wonder what your 75 00:04:08,480 --> 00:04:11,880 Speaker 1: take is on the Build Back Better bill, And not 76 00:04:11,960 --> 00:04:13,960 Speaker 1: because I want you to take a political stance, In 77 00:04:14,000 --> 00:04:19,600 Speaker 1: fact I don't, but it does seem that it's extraordinarily 78 00:04:19,600 --> 00:04:24,839 Speaker 1: difficult in America, especially compared to other countries, for um, 79 00:04:24,920 --> 00:04:27,560 Speaker 1: for mothers to go to work, for mothers to get 80 00:04:27,560 --> 00:04:31,679 Speaker 1: an education and to go to work compared to you know, Germany, 81 00:04:31,680 --> 00:04:34,400 Speaker 1: where I spend most of my time because childcare is 82 00:04:35,320 --> 00:04:38,839 Speaker 1: expensive and it's an arduous process for a lot of 83 00:04:38,880 --> 00:04:41,120 Speaker 1: people to to feed their kids. I mean, is this 84 00:04:41,160 --> 00:04:45,359 Speaker 1: going to help? Hopefully it will, And you know, you 85 00:04:45,400 --> 00:04:48,040 Speaker 1: bring up an excellent point. It is difficult. You can't 86 00:04:48,040 --> 00:04:49,880 Speaker 1: do it all at the same time. This is why 87 00:04:49,920 --> 00:04:54,520 Speaker 1: we're seeing for physicians such an uptick in them wanting 88 00:04:54,560 --> 00:04:57,840 Speaker 1: to do telehealth because they don't have to these travelers, 89 00:04:58,040 --> 00:05:01,240 Speaker 1: they don't have to travel to another occasion. They can 90 00:05:01,400 --> 00:05:04,240 Speaker 1: do it from home and that's making a big difference. 91 00:05:04,279 --> 00:05:07,880 Speaker 1: But of course those things in healthcare can't be done 92 00:05:08,279 --> 00:05:10,920 Speaker 1: in terms of telehealth. But we if we don't do something, 93 00:05:10,960 --> 00:05:14,119 Speaker 1: it's only going to get that much worse. All right, Joanna, 94 00:05:14,160 --> 00:05:15,760 Speaker 1: thank you so much for joining us. We appreciate it. 95 00:05:15,800 --> 00:05:20,000 Speaker 1: Janet Elkin, President and chief executive officer of Icon Medical Network. 96 00:05:24,040 --> 00:05:26,720 Speaker 1: One of the analysts that we have on a lot 97 00:05:27,040 --> 00:05:29,680 Speaker 1: Dan Ives. I think he's one of the most listened 98 00:05:29,680 --> 00:05:31,520 Speaker 1: to analysts on Wall Street when it comes to the 99 00:05:31,520 --> 00:05:35,200 Speaker 1: tech area, and he is, to be fair bullish. Every 100 00:05:35,240 --> 00:05:37,400 Speaker 1: company that he covers. He has an outperform on like 101 00:05:37,440 --> 00:05:42,040 Speaker 1: thirty different companies of Penn State, Nitney exactly, he said, 102 00:05:42,120 --> 00:05:45,440 Speaker 1: tweeted today, we believe there's five trillion dollars of e 103 00:05:45,560 --> 00:05:48,760 Speaker 1: V auto market up for grabs, with Tesla likely to 104 00:05:48,800 --> 00:05:50,840 Speaker 1: own two and a half trillion dollars of this pie. 105 00:05:51,120 --> 00:05:53,360 Speaker 1: We estimate China is worth four hund dollars per share 106 00:05:53,400 --> 00:05:56,320 Speaker 1: of the Testla story for two, raising our price target 107 00:05:56,520 --> 00:05:58,880 Speaker 1: from eleven to four hundred with our bul case of 108 00:05:58,920 --> 00:06:02,679 Speaker 1: eighteen hundred. So he's a big believer here. He's been right. Um, 109 00:06:02,720 --> 00:06:05,520 Speaker 1: we have another uh Tesla fan, at least in terms 110 00:06:05,560 --> 00:06:10,520 Speaker 1: of the car. Uh. Matt Winkler, Bloomberg News editor in 111 00:06:10,600 --> 00:06:14,440 Speaker 1: chief emeritus and also the author of a piece on Rivian. 112 00:06:14,920 --> 00:06:18,080 Speaker 1: So I didn't realize you owned a Tesla car as well. Matt. 113 00:06:18,080 --> 00:06:19,840 Speaker 1: We talked about this on TV a couple of days ago. 114 00:06:20,120 --> 00:06:22,039 Speaker 1: Last I heard you were in a Toyota Avalon. What 115 00:06:22,080 --> 00:06:29,200 Speaker 1: happened two thousand and fourteen, to be precise. We acquired 116 00:06:29,600 --> 00:06:34,520 Speaker 1: a models and we're happily driving it to this day. Uh. 117 00:06:34,640 --> 00:06:38,000 Speaker 1: So you loved I know you loved the Avalon. I'll 118 00:06:38,040 --> 00:06:40,280 Speaker 1: never forget when you told me about that. You had 119 00:06:40,279 --> 00:06:42,560 Speaker 1: a lot of enthusiasm for it in terms of what 120 00:06:42,600 --> 00:06:46,239 Speaker 1: we see here at Rivan, it is if you didn't 121 00:06:46,240 --> 00:06:49,040 Speaker 1: know the Tesla story, it would be mind blowing the 122 00:06:49,120 --> 00:06:53,080 Speaker 1: fact that electric car maker truckmaker can come out and 123 00:06:53,120 --> 00:06:58,159 Speaker 1: get a hundred and twenty billion dollar market cap um 124 00:06:58,240 --> 00:07:00,760 Speaker 1: even though they've only sold probably this point three or 125 00:07:00,760 --> 00:07:05,039 Speaker 1: four hundred vehicles on the road. They're bigger than GM 126 00:07:05,200 --> 00:07:10,480 Speaker 1: by almost thirty five percent right now, How is it possible? 127 00:07:10,720 --> 00:07:15,240 Speaker 1: So what gets every investor excited Matt and Paul, I 128 00:07:15,280 --> 00:07:20,240 Speaker 1: think you agree is growth. That is always what brings 129 00:07:20,280 --> 00:07:26,000 Speaker 1: the market to its highest levels. And Tesla, for example, uh, 130 00:07:26,120 --> 00:07:29,760 Speaker 1: since it went public in two thousand and ten, has 131 00:07:29,800 --> 00:07:34,520 Speaker 1: seen four hundred times the growth of the average for 132 00:07:34,560 --> 00:07:39,880 Speaker 1: the automotive industry over a ten year period, which is unprecedented. 133 00:07:40,160 --> 00:07:44,679 Speaker 1: And that growth has enabled Tesla, as you now know UM, 134 00:07:44,840 --> 00:07:49,040 Speaker 1: to make a profit um and to get to a 135 00:07:49,120 --> 00:07:54,800 Speaker 1: point where even the doubters are now acknowledging that electric 136 00:07:54,920 --> 00:07:59,160 Speaker 1: vehicles are for real, they are the future. And Tesla 137 00:07:59,280 --> 00:08:02,280 Speaker 1: did that. So oh, it's set the stage for Ribbyan, 138 00:08:03,040 --> 00:08:06,480 Speaker 1: which is going in a somewhat different direction because its 139 00:08:06,520 --> 00:08:12,120 Speaker 1: focuses on trucks and suv but more particularly vans commercial 140 00:08:12,640 --> 00:08:18,280 Speaker 1: um traffic. Jeff Bezos, who needs no introduction, uh, and 141 00:08:18,440 --> 00:08:22,880 Speaker 1: his company Amazon already ordered a hundred thousand of these 142 00:08:23,000 --> 00:08:26,600 Speaker 1: Ribbyan bands, which haven't been produced yet. But that gives 143 00:08:26,600 --> 00:08:30,160 Speaker 1: you some idea of the anticipation of where this market 144 00:08:30,240 --> 00:08:33,760 Speaker 1: is going. And the stock market is always about the future, 145 00:08:33,800 --> 00:08:35,800 Speaker 1: it's not about the past, it's not about the rear 146 00:08:35,880 --> 00:08:40,920 Speaker 1: view mirror. So this explains why Ribbyan as of this 147 00:08:41,000 --> 00:08:46,240 Speaker 1: moment is number five in terms of market valuation among 148 00:08:46,280 --> 00:08:50,119 Speaker 1: the top ten automakers, having sold fewer than fifty vehicles. 149 00:08:50,120 --> 00:08:53,640 Speaker 1: Crazy and Matt, you're out with a column on all 150 00:08:53,720 --> 00:08:56,800 Speaker 1: of this talking about the v market and evaluations, and 151 00:08:56,840 --> 00:08:59,200 Speaker 1: along with your colleague Shinpay and Jennifer leew are really 152 00:08:59,240 --> 00:09:02,240 Speaker 1: some great data. As always, the number of the line 153 00:09:02,240 --> 00:09:03,760 Speaker 1: that kind of stuck out to me, Matt is, you know, 154 00:09:03,800 --> 00:09:05,920 Speaker 1: the market value of the top ten automakers is more 155 00:09:05,960 --> 00:09:10,719 Speaker 1: than two thirds electric, a reality considered improbable, if not impossible, 156 00:09:10,840 --> 00:09:14,160 Speaker 1: just a year ago. And I agree with that shocked me. 157 00:09:14,520 --> 00:09:20,800 Speaker 1: I mean, does that suggest that the traditional automakers they've 158 00:09:20,880 --> 00:09:23,520 Speaker 1: just missed it or can they catch up? Do you think, well, 159 00:09:23,559 --> 00:09:28,400 Speaker 1: they will have to catch up because probably by the 160 00:09:28,400 --> 00:09:34,360 Speaker 1: internal combustion engine will be a museum piece. And so, uh, 161 00:09:34,400 --> 00:09:40,280 Speaker 1: that's not a secret at this point. And so anyway, 162 00:09:40,640 --> 00:09:44,360 Speaker 1: the uh, the rest of the industry gets to that 163 00:09:44,440 --> 00:09:47,319 Speaker 1: point is going to be the story. And so they're 164 00:09:47,360 --> 00:09:49,920 Speaker 1: going to do it all kinds of ways. But for sure, 165 00:09:50,960 --> 00:09:54,040 Speaker 1: the ev makers can do only one thing, which is 166 00:09:54,080 --> 00:09:58,520 Speaker 1: make electric vehicles. The rest of the industry has a 167 00:09:58,600 --> 00:10:03,240 Speaker 1: much messier, more difficult, challenging task ahead. I've erected a 168 00:10:03,320 --> 00:10:07,000 Speaker 1: museum to the internal combustion engine at my house. Increasingly 169 00:10:07,040 --> 00:10:10,920 Speaker 1: I feel guiltier and guiltier about driving these cars, I 170 00:10:10,960 --> 00:10:16,840 Speaker 1: will admit, because there's such huge emitters globally right internal 171 00:10:16,840 --> 00:10:22,360 Speaker 1: combustion engines really contributing to um greenhouse gas emissions build 172 00:10:22,440 --> 00:10:25,679 Speaker 1: up and climate climate change. Do you think we're gonna 173 00:10:25,720 --> 00:10:30,200 Speaker 1: need continue to need government incentives Matt, for electric cars 174 00:10:30,320 --> 00:10:34,720 Speaker 1: and investment in infrastructure from the government in order to 175 00:10:34,880 --> 00:10:37,599 Speaker 1: make a change, to make that switch bigger. Here's the 176 00:10:37,640 --> 00:10:43,000 Speaker 1: best answer to that question, Matt. California is the best 177 00:10:43,040 --> 00:10:47,559 Speaker 1: performing economy in the United States, subject of another column 178 00:10:47,600 --> 00:10:50,000 Speaker 1: you had recently, and it's number five in the world. 179 00:10:50,679 --> 00:10:52,840 Speaker 1: If it were a country, it's number five in the world. 180 00:10:53,679 --> 00:10:56,839 Speaker 1: California is the place, more so than any other state, 181 00:10:57,760 --> 00:11:04,400 Speaker 1: where people's preferences and government policy converge. They converge, they're 182 00:11:04,440 --> 00:11:07,520 Speaker 1: not at odds with each other. And that's why they're 183 00:11:07,520 --> 00:11:12,600 Speaker 1: more e vs in California than anywhere else. Uh in 184 00:11:12,640 --> 00:11:18,440 Speaker 1: the US and where you could easily see I mean 185 00:11:19,720 --> 00:11:24,079 Speaker 1: the growth of evs accelerating and the fact that Rivan 186 00:11:25,400 --> 00:11:29,880 Speaker 1: is an Irvine, California based company. Tesla of course started 187 00:11:30,120 --> 00:11:34,280 Speaker 1: in California and Palo Auto. Even though it's moving its 188 00:11:34,280 --> 00:11:39,120 Speaker 1: headquarters to Texas, the place where Tesla makes its vehicles 189 00:11:39,240 --> 00:11:43,040 Speaker 1: is still Fremont. So that's not going to change, if anything, 190 00:11:43,160 --> 00:11:45,080 Speaker 1: that the production is going to go up. So the 191 00:11:45,080 --> 00:11:49,200 Speaker 1: answer your question is yes, Um, this just only accelerates, 192 00:11:50,040 --> 00:11:51,800 Speaker 1: all right, Matt, thank you so much for joining us. 193 00:11:51,800 --> 00:11:55,520 Speaker 1: Really appreciated. Matt Winkler, Editor in chief emeritus founder of 194 00:11:55,720 --> 00:11:59,200 Speaker 1: Bloomberg News. He's something, Have you driven electrical? I'm not? 195 00:11:59,679 --> 00:12:02,200 Speaker 1: All My God, are serious? I'm not. You have to 196 00:12:02,280 --> 00:12:04,560 Speaker 1: try it, all right. I think that makes a convert 197 00:12:04,600 --> 00:12:06,640 Speaker 1: and a lot of people when you experienced the I 198 00:12:06,679 --> 00:12:11,160 Speaker 1: think it might be in the market. We'll see red 199 00:12:11,160 --> 00:12:12,880 Speaker 1: and green on the screen is a good friend. Tom 200 00:12:12,960 --> 00:12:14,880 Speaker 1: Keene likes to say, let's see what the action is 201 00:12:14,920 --> 00:12:17,800 Speaker 1: with the small cap stocks. We do that every day 202 00:12:17,800 --> 00:12:24,240 Speaker 1: at this time with Bloomberg Market Reporter. Yes, across asset 203 00:12:25,120 --> 00:12:28,960 Speaker 1: markets correspondent actually, but thanks the Russell two thousand down 204 00:12:29,040 --> 00:12:32,079 Speaker 1: zero point four percent on the day. Riskoff moved across 205 00:12:32,080 --> 00:12:34,400 Speaker 1: the market. The Rustle two thousands. No different you under 206 00:12:34,440 --> 00:12:36,840 Speaker 1: the hood, though you have some deal news. Simmons First 207 00:12:36,920 --> 00:12:40,240 Speaker 1: National has agreed to acquire Spirit of Texas Bank shars 208 00:12:40,240 --> 00:12:42,439 Speaker 1: in a cash and stock deal valued at about five 209 00:12:42,880 --> 00:12:46,040 Speaker 1: eighty one million dollars. Spirit of Texas Bank shares. The 210 00:12:46,080 --> 00:12:49,520 Speaker 1: takers st x B shares are up eight percent um. 211 00:12:49,640 --> 00:12:52,600 Speaker 1: You also have Simmons First National Tier s f n 212 00:12:52,640 --> 00:12:55,360 Speaker 1: C shares are down six percent to the downside. I'm 213 00:12:55,360 --> 00:12:57,680 Speaker 1: sad to say the other stories are all downside stories. 214 00:12:57,720 --> 00:13:01,000 Speaker 1: And Nanta Pharmaceuticals down eleven percent of the tickers e 215 00:13:01,120 --> 00:13:04,839 Speaker 1: n t A after discontinuing development of its oral hepatitis 216 00:13:04,920 --> 00:13:08,360 Speaker 1: B drug based on emerging safety concerns. You also have 217 00:13:08,440 --> 00:13:11,560 Speaker 1: Bell Ring ticker b r b R down eight percent, 218 00:13:11,720 --> 00:13:15,319 Speaker 1: maker of nutrition supplements, posting fiscal fourth quarter revenue that 219 00:13:15,440 --> 00:13:19,720 Speaker 1: fell short of consensus estimates, and lastly, Record Systems UH 220 00:13:19,840 --> 00:13:22,400 Speaker 1: down six percent, ticker r e k R, and AI 221 00:13:22,520 --> 00:13:25,760 Speaker 1: technology company that is also the worst performer in the 222 00:13:25,840 --> 00:13:29,240 Speaker 1: Russell two thousand index, missing three third quarter excuse me 223 00:13:29,400 --> 00:13:32,000 Speaker 1: consensus estimates on both the top and bottom lines, and 224 00:13:32,160 --> 00:13:36,760 Speaker 1: saying revenue will fall in the coming quarters. Bloom Now, 225 00:13:36,840 --> 00:13:38,679 Speaker 1: what's the exact title here? I want to get this right? 226 00:13:38,760 --> 00:13:42,200 Speaker 1: Markets correspondent for Bloomberg TV and radio. Have you thought 227 00:13:42,200 --> 00:13:46,920 Speaker 1: about a different title? As interesting as I think, I 228 00:13:47,000 --> 00:13:50,840 Speaker 1: was already a markets reporter, reporter and a correspondent. I 229 00:13:50,840 --> 00:13:54,800 Speaker 1: don't know it's a title upgrade. It's a markets reporter. 230 00:13:54,920 --> 00:13:56,280 Speaker 1: First I did it on print. Now I'm doing it 231 00:13:56,320 --> 00:13:58,600 Speaker 1: on TV and radio. So all right? Are we gonna 232 00:13:58,600 --> 00:14:01,520 Speaker 1: go with that? Mant? I think editor at large sounds 233 00:14:01,520 --> 00:14:04,960 Speaker 1: good and pretty is a triple threat because she writes 234 00:14:05,000 --> 00:14:09,000 Speaker 1: for Ben, she's on TV, and she's on radio. Actually 235 00:14:09,000 --> 00:14:11,440 Speaker 1: a quadruple threat because she does quick take as well, 236 00:14:12,200 --> 00:14:14,040 Speaker 1: and she probably does some social media thing that I 237 00:14:14,080 --> 00:14:16,280 Speaker 1: don't even know about. I know Matt doesn't follow me 238 00:14:16,320 --> 00:14:19,640 Speaker 1: on Twitter, so you wouldn't know. This is a very 239 00:14:19,680 --> 00:14:23,200 Speaker 1: public call out. I fall out. I follow mostly people 240 00:14:23,200 --> 00:14:27,400 Speaker 1: who drive race cars or ride motorcycles. So basically to 241 00:14:27,440 --> 00:14:29,160 Speaker 1: get Matt to follow me, I have to go get 242 00:14:29,200 --> 00:14:31,800 Speaker 1: a car and drive it around. I think so. And 243 00:14:31,840 --> 00:14:34,840 Speaker 1: when it went a Grand Prix, all right, great, Thanks 244 00:14:34,880 --> 00:14:37,080 Speaker 1: so much for joining us. We always love getting your 245 00:14:37,080 --> 00:14:39,480 Speaker 1: thoughts there on the market. Avery Sheffield joins us now 246 00:14:39,520 --> 00:14:42,720 Speaker 1: every Managing Director and Senior Portfolio off Long Short Equity 247 00:14:43,360 --> 00:14:47,200 Speaker 1: head Funds Strategy at Rockefeller Asset Management. Every We just 248 00:14:47,240 --> 00:14:51,880 Speaker 1: got through great, great third quarter earnings. I thought i'd 249 00:14:51,920 --> 00:14:55,600 Speaker 1: see more, hear more concern and guidance as it relates 250 00:14:55,640 --> 00:14:59,600 Speaker 1: to supply chains, global supply chains. You know, they called 251 00:14:59,600 --> 00:15:02,240 Speaker 1: it out it. We're still seeing some pretty good guidance there. 252 00:15:02,240 --> 00:15:06,120 Speaker 1: What are your thoughts? Yes, I mean you know this 253 00:15:06,320 --> 00:15:09,720 Speaker 1: as the supply chain concerns. Um, we're really in focus 254 00:15:09,960 --> 00:15:12,360 Speaker 1: kind of late August, kind of beginning with one of 255 00:15:12,360 --> 00:15:16,400 Speaker 1: the major global footwear's announcements and then through September. You know, 256 00:15:16,600 --> 00:15:19,760 Speaker 1: my instinct was that this was kind of a buy 257 00:15:19,880 --> 00:15:23,600 Speaker 1: the dip opportunity because for key reasons, like one is 258 00:15:24,280 --> 00:15:27,120 Speaker 1: um that when you we've seen when you have supply 259 00:15:27,200 --> 00:15:31,280 Speaker 1: chain dynamics issues, it leads to less inventory and less 260 00:15:31,320 --> 00:15:34,200 Speaker 1: inventory needs you know, less supply and and and and 261 00:15:34,280 --> 00:15:36,960 Speaker 1: that match with demand allows for pricing power. But from 262 00:15:36,960 --> 00:15:39,920 Speaker 1: a fundamental perspective on supply chain, no, there there are 263 00:15:39,920 --> 00:15:43,320 Speaker 1: a few companies that are heavily have been heavily reliant 264 00:15:43,400 --> 00:15:46,680 Speaker 1: on UM and this is an apparel retail sector UM 265 00:15:46,680 --> 00:15:48,760 Speaker 1: that have been heavily reliant on regions that have had 266 00:15:48,800 --> 00:15:53,400 Speaker 1: significant shutdowns. And they are they're absolutely experiencing UM less supply. 267 00:15:53,840 --> 00:15:57,479 Speaker 1: But many, many, you know, apparel and an accessories manufacturers 268 00:15:57,480 --> 00:16:00,520 Speaker 1: have distributed supply chains around the world, and it looked 269 00:16:00,600 --> 00:16:02,440 Speaker 1: like they were going to be able to manage through this. 270 00:16:02,520 --> 00:16:06,400 Speaker 1: You know, it's some incremental freight and shipping costs UM 271 00:16:06,400 --> 00:16:08,840 Speaker 1: shifting around, you know, which inventories they were gonna hold. 272 00:16:08,840 --> 00:16:11,440 Speaker 1: But it started to become evidence I think by October 273 00:16:11,680 --> 00:16:13,320 Speaker 1: that many of the companies we're going to get through 274 00:16:13,360 --> 00:16:16,000 Speaker 1: this relatively unscathed. And that's certainly what we've seen in 275 00:16:16,000 --> 00:16:20,160 Speaker 1: the results. I have got to ask, you have a 276 00:16:20,240 --> 00:16:25,360 Speaker 1: degree in neuroscience UM from Pomona. First of all, what 277 00:16:25,640 --> 00:16:28,080 Speaker 1: is that and is that like science of the brain? 278 00:16:28,160 --> 00:16:30,520 Speaker 1: I think? And what and what does that? What? What 279 00:16:30,640 --> 00:16:35,320 Speaker 1: kind of edge does that give you? Oh so yes, 280 00:16:35,400 --> 00:16:37,840 Speaker 1: I am a neuroscience major, and that is a science 281 00:16:37,840 --> 00:16:40,720 Speaker 1: of the brain, and it includes hard sciences as well 282 00:16:40,760 --> 00:16:43,920 Speaker 1: as psychology. And look, I I studied it because I 283 00:16:43,960 --> 00:16:47,280 Speaker 1: find I find how I find science and how the 284 00:16:47,360 --> 00:16:50,200 Speaker 1: human brain works to be fascinating. From a training perspective, 285 00:16:50,200 --> 00:16:52,160 Speaker 1: this WI be speaking to anyone else looking to figure 286 00:16:52,160 --> 00:16:54,160 Speaker 1: out what to study in college, certainly to become an 287 00:16:54,200 --> 00:16:57,280 Speaker 1: investor or anything else. Um, something like neuroscience gives you 288 00:16:57,320 --> 00:17:00,720 Speaker 1: just a very strong foundation in science, in the analytics 289 00:17:00,720 --> 00:17:05,080 Speaker 1: and the math, um, asking questions, posing hypotheses, really trying 290 00:17:05,119 --> 00:17:08,120 Speaker 1: to figure out, um, the answers to to open ended questions. 291 00:17:08,400 --> 00:17:10,520 Speaker 1: So that's I think good training for anyone. And then 292 00:17:10,640 --> 00:17:13,240 Speaker 1: the psychology, of of course, is what what really plays 293 00:17:13,280 --> 00:17:15,800 Speaker 1: in every day and behavioral finance is something and I 294 00:17:15,800 --> 00:17:20,239 Speaker 1: find absolutely financing and assassinating and um and focus on 295 00:17:20,359 --> 00:17:22,240 Speaker 1: kind of on a daily basis of how that's playing 296 00:17:22,240 --> 00:17:24,440 Speaker 1: into my investment decisions and those of others. And you 297 00:17:24,720 --> 00:17:27,919 Speaker 1: went from there to Wharton, so, uh, you clearly know 298 00:17:27,960 --> 00:17:30,040 Speaker 1: what you're talking about when it comes to business as well. 299 00:17:30,280 --> 00:17:34,199 Speaker 1: What do you think about this renewed COVID explosion in 300 00:17:34,359 --> 00:17:40,160 Speaker 1: Austria and Germany, we're seeing lockdowns, We're seeing mandated vaccines. 301 00:17:40,680 --> 00:17:42,320 Speaker 1: Just when we thought it was kind of all over, 302 00:17:44,119 --> 00:17:46,480 Speaker 1: right well, I mean, you know the nature of viruses, 303 00:17:46,600 --> 00:17:50,040 Speaker 1: they keep coming around, right so UM, but the question 304 00:17:50,080 --> 00:17:52,280 Speaker 1: is how severe are they when when they when? When 305 00:17:52,280 --> 00:17:55,800 Speaker 1: they come around, and we're still seeing hospitalization rates flow. 306 00:17:55,880 --> 00:17:57,760 Speaker 1: I mean there are certain areas, right whereas a lot 307 00:17:57,800 --> 00:18:00,560 Speaker 1: of unvaccinated people that you're seeing UM in Austria and 308 00:18:00,600 --> 00:18:03,520 Speaker 1: a few other places that are UM that are causing 309 00:18:03,560 --> 00:18:06,040 Speaker 1: you know, some concern and leading to these lockdowns. But 310 00:18:06,240 --> 00:18:07,760 Speaker 1: I think we're really the tail end of it. I 311 00:18:07,760 --> 00:18:09,760 Speaker 1: mean you, I mean, look, I think we're going to 312 00:18:09,800 --> 00:18:13,200 Speaker 1: see small, a small breakouts of COVID for a long time. 313 00:18:13,240 --> 00:18:15,440 Speaker 1: I mean, this virus is likely, you know, to mutate, 314 00:18:15,480 --> 00:18:18,160 Speaker 1: but as long as we've seen in Israel UM, getting 315 00:18:18,160 --> 00:18:21,480 Speaker 1: those booster shots really works. And I think these vaccine 316 00:18:21,520 --> 00:18:23,560 Speaker 1: mandates are really the answer. I mean a lot of 317 00:18:23,560 --> 00:18:26,639 Speaker 1: the lockdowns we've seen, or they're not really lockdowns, but 318 00:18:26,960 --> 00:18:31,879 Speaker 1: kind of slowing activity UM has been targeted to the 319 00:18:31,960 --> 00:18:36,280 Speaker 1: unvaccinated in many countries, and moving towards these mandatory vaccinations 320 00:18:36,400 --> 00:18:39,320 Speaker 1: I think is really the answer. Yep, I am vaxed 321 00:18:39,440 --> 00:18:42,040 Speaker 1: and boost. It's all set to go. Every Sheffield Managing 322 00:18:42,040 --> 00:18:45,480 Speaker 1: director and senior portfolio managed for Long Short Equity head 323 00:18:45,600 --> 00:18:53,040 Speaker 1: fun Strategy at Rockefeller Asset Management. I want to get 324 00:18:53,080 --> 00:18:55,800 Speaker 1: over right now to Jonathan Wade, he joins a senior 325 00:18:55,840 --> 00:19:01,400 Speaker 1: research channelist at Frost Investment Advisors. And before we get 326 00:19:01,720 --> 00:19:04,800 Speaker 1: into the meat of this uh interview, I gotta ask 327 00:19:04,840 --> 00:19:07,879 Speaker 1: you about a piece I saw in your bio. It says, 328 00:19:08,119 --> 00:19:12,240 Speaker 1: um current CFA, which I respect greatly and former c 329 00:19:12,400 --> 00:19:14,639 Speaker 1: p A for twenty plus years. I thought being a 330 00:19:14,720 --> 00:19:16,560 Speaker 1: c p A was like being a marine. Aren't you 331 00:19:16,600 --> 00:19:18,679 Speaker 1: like always a c p A once you were a 332 00:19:18,720 --> 00:19:21,800 Speaker 1: c p A. No. I kind of kind of leave 333 00:19:21,880 --> 00:19:23,840 Speaker 1: that in the background, you know, because everyone wants you 334 00:19:23,880 --> 00:19:27,320 Speaker 1: to ask accounting your tax question to you, So I 335 00:19:28,040 --> 00:19:32,960 Speaker 1: leave that in the background exactly. Yeah, all right, Jonathan. UM, 336 00:19:33,000 --> 00:19:37,640 Speaker 1: we've just come through some really good third quarter earnings. UM. 337 00:19:38,320 --> 00:19:39,879 Speaker 1: I think for a lot of people that gave them. 338 00:19:39,960 --> 00:19:42,159 Speaker 1: If you just look at the market reaction, that's kind 339 00:19:42,160 --> 00:19:44,880 Speaker 1: of what the market needed for this next leg. What's 340 00:19:44,880 --> 00:19:48,119 Speaker 1: your earnings outlook? Do you feel like this market's expensive 341 00:19:48,280 --> 00:19:50,000 Speaker 1: or did the earning story kind of come through on 342 00:19:50,040 --> 00:19:54,680 Speaker 1: that old pe analysis. Well, I mean, yeah, that's a 343 00:19:54,720 --> 00:19:57,560 Speaker 1: mixed question, right, I mean, because the valuation here is 344 00:19:57,600 --> 00:20:01,080 Speaker 1: a little a little pricey. But on the backdrop of this, 345 00:20:01,720 --> 00:20:06,320 Speaker 1: earnings look great, the economic outlook looks great. Um. The 346 00:20:06,920 --> 00:20:09,639 Speaker 1: when you think about the consumer being two thirds of 347 00:20:09,760 --> 00:20:13,399 Speaker 1: g d P in great shape, um under levered on 348 00:20:13,440 --> 00:20:16,879 Speaker 1: their balance sheet, ability to spend more, the intentions to 349 00:20:16,920 --> 00:20:18,840 Speaker 1: spend over the next twelve months or like an all 350 00:20:18,880 --> 00:20:22,200 Speaker 1: time high, and then you look at a business spending 351 00:20:23,720 --> 00:20:27,160 Speaker 1: the economy and capex intentions are high, cash on balance 352 00:20:27,200 --> 00:20:30,480 Speaker 1: sheet is very high. So we're cautiously optimistic as we 353 00:20:30,640 --> 00:20:34,400 Speaker 1: roll through the fourth quarter in two with the question being, 354 00:20:34,920 --> 00:20:37,119 Speaker 1: you know what happens with COVID and we're getting a 355 00:20:37,200 --> 00:20:40,159 Speaker 1: fresh out of that today. Yeah, exactly. I mean I 356 00:20:40,200 --> 00:20:45,239 Speaker 1: woke up this morning, perused the markets around three, and 357 00:20:45,320 --> 00:20:48,960 Speaker 1: then uh, I started listening to um Blues Traveler record, 358 00:20:49,080 --> 00:20:51,040 Speaker 1: you know, the one with Dance with Me Felicia. I 359 00:20:51,080 --> 00:20:54,359 Speaker 1: love that that record. And I looked back and all 360 00:20:54,400 --> 00:20:56,720 Speaker 1: of a sudden, I saw the dollar index was shooting up, 361 00:20:57,240 --> 00:20:59,600 Speaker 1: and the yen was gaining a lot of strength, and 362 00:20:59,640 --> 00:21:01,119 Speaker 1: there was a bit in bonds, and I thought what 363 00:21:01,160 --> 00:21:03,199 Speaker 1: the heck is going on? This has got to be 364 00:21:03,240 --> 00:21:07,120 Speaker 1: the COVID numbers, and indeed it was. Uh if that 365 00:21:07,240 --> 00:21:10,480 Speaker 1: turns into a real problem for the global economy, art stocks, 366 00:21:10,520 --> 00:21:14,520 Speaker 1: price for for perfection, well, I think at a certain 367 00:21:14,560 --> 00:21:16,840 Speaker 1: point you just we're gonna need to have to look 368 00:21:16,880 --> 00:21:19,280 Speaker 1: through COVID, you know, because it's it's not going to 369 00:21:19,359 --> 00:21:22,120 Speaker 1: be with us forever. We're eventually going to roll through this. 370 00:21:22,280 --> 00:21:25,600 Speaker 1: We like you said, we have the fighter pill that's 371 00:21:25,640 --> 00:21:28,080 Speaker 1: out there. Um, you know you think that that would 372 00:21:28,080 --> 00:21:30,080 Speaker 1: give you some reassurance that we're going to have some 373 00:21:30,119 --> 00:21:34,520 Speaker 1: return to normalcy soon. So alright, So Jonathan, what are 374 00:21:34,560 --> 00:21:37,120 Speaker 1: the areas that you guys are doing working right now? 375 00:21:37,160 --> 00:21:39,159 Speaker 1: I know there's a couple of camps out there. I'm 376 00:21:39,200 --> 00:21:41,040 Speaker 1: sticking with the you know, the big growth stocks that 377 00:21:41,080 --> 00:21:42,679 Speaker 1: have been so good to me for so long, and 378 00:21:43,080 --> 00:21:45,240 Speaker 1: the other camps say, now I'm swinging for the cyclical 379 00:21:45,280 --> 00:21:48,720 Speaker 1: trade here the reopening trade, and um, where do you 380 00:21:48,720 --> 00:21:52,639 Speaker 1: guys think about opportunity? Um? Well, see, we're you know, 381 00:21:52,680 --> 00:21:57,159 Speaker 1: broad investors. We value strategies and growth strategies. So uh, 382 00:21:57,160 --> 00:21:59,600 Speaker 1: you know, on these when we look to two, I 383 00:21:59,600 --> 00:22:01,240 Speaker 1: think there is the thought that we could see a 384 00:22:01,240 --> 00:22:03,160 Speaker 1: little bit of a cyclical bump at least in the 385 00:22:03,200 --> 00:22:06,440 Speaker 1: first half of the year on that reopening trade. So yeah, 386 00:22:06,440 --> 00:22:08,000 Speaker 1: we think there is a little bit of legs left 387 00:22:08,000 --> 00:22:11,119 Speaker 1: in that reopening trade, especially travel names that are getting 388 00:22:11,160 --> 00:22:13,679 Speaker 1: cocked today, and we think that they should see some 389 00:22:13,760 --> 00:22:17,520 Speaker 1: improvement rolls through. But also on the growth side, it's 390 00:22:17,720 --> 00:22:21,040 Speaker 1: I mean it's again you still have valuation to deal with. 391 00:22:21,080 --> 00:22:24,080 Speaker 1: You have the retail investor in there that's just crowding 392 00:22:24,080 --> 00:22:28,240 Speaker 1: into these momentum names. But otherwise we think that the 393 00:22:28,280 --> 00:22:31,480 Speaker 1: tech secular tail winds are here to stay and we'll 394 00:22:31,840 --> 00:22:35,120 Speaker 1: see a continuation of that through the next few years. Yeah, 395 00:22:35,119 --> 00:22:39,280 Speaker 1: the airline's got have gotten battered again today. I think 396 00:22:39,400 --> 00:22:43,119 Speaker 1: Ryan Air is down ten sessions in a row, and 397 00:22:43,119 --> 00:22:46,359 Speaker 1: I was looking at UM Ryan Air, I A G 398 00:22:46,880 --> 00:22:50,120 Speaker 1: and Leftanza today. Ryan Air over the last five years 399 00:22:50,200 --> 00:22:51,879 Speaker 1: is the only one that's given you any kind of games, 400 00:22:51,960 --> 00:22:57,119 Speaker 1: and that's only ten Liftanza and UH and I A 401 00:22:57,240 --> 00:23:01,800 Speaker 1: G are both down I think six and nine per 402 00:23:02,000 --> 00:23:06,120 Speaker 1: year respectively over the last five years. You don't really 403 00:23:06,160 --> 00:23:09,280 Speaker 1: want to invest in airline stock, do you, well, and 404 00:23:09,280 --> 00:23:12,160 Speaker 1: they've got the double Emmy of of energy prices moving 405 00:23:12,200 --> 00:23:16,400 Speaker 1: against them, and labor, labor, labor, Yeah, yeah, exactly, and 406 00:23:16,560 --> 00:23:19,080 Speaker 1: that's going to just be a huge destruction this upcoming 407 00:23:19,119 --> 00:23:21,800 Speaker 1: holiday season. So you know, I've got a daughter coming 408 00:23:21,800 --> 00:23:24,040 Speaker 1: home from college. I hope she makes it for the holidays, 409 00:23:24,080 --> 00:23:27,399 Speaker 1: So I hope she does too. Absolutely all right, Jonathan, 410 00:23:27,400 --> 00:23:29,720 Speaker 1: thanks so much for joining us. Jonathan Waite, Senior Research 411 00:23:29,800 --> 00:23:35,160 Speaker 1: Channel's Frost Investment Advisers. Thanks for listening to the Bloomberg 412 00:23:35,200 --> 00:23:38,600 Speaker 1: Markets podcast. You can subscribe and listen to interviews with 413 00:23:38,640 --> 00:23:43,440 Speaker 1: Apple Podcasts or whatever podcast platform you prefer. I'm Matt Miller. 414 00:23:43,720 --> 00:23:48,000 Speaker 1: I'm on Twitter at Matt Miller three. On Faull Sweeney, 415 00:23:48,000 --> 00:23:50,639 Speaker 1: I'm on Twitter at pt Sweeney. Before the podcast. You 416 00:23:50,640 --> 00:23:53,320 Speaker 1: can always catch us worldwide at Bloomberg Radio.