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 pros, and Bloomberg experts, along 4 00:00:11,560 --> 00:00:15,560 Speaker 1: with essential market moving news. Find the Bloomberg Markets podcast 5 00:00:15,560 --> 00:00:18,479 Speaker 1: called Apple Podcasts or wherever you listen to podcasts, and 6 00:00:18,480 --> 00:00:24,160 Speaker 1: at Bloomberg dot com Slash podcast in the Bloomberg Interactive 7 00:00:24,160 --> 00:00:27,320 Speaker 1: Broker studio. As we speak, Jenna Drosos. She is all 8 00:00:27,360 --> 00:00:31,720 Speaker 1: tested up for the COVID passing with colors. I would 9 00:00:31,720 --> 00:00:35,360 Speaker 1: say she's the CEO of Signet Jewelers based in Accord, Ohio. 10 00:00:35,360 --> 00:00:38,000 Speaker 1: It's a publicly traded company. S i G is a 11 00:00:38,040 --> 00:00:40,600 Speaker 1: ticker about a four billion dollar market. Cappin. Jenna, thanks 12 00:00:40,600 --> 00:00:43,240 Speaker 1: so much for joining us here. Talk to us about 13 00:00:43,440 --> 00:00:46,920 Speaker 1: the jewelry business in the world of a global pandemic. 14 00:00:47,000 --> 00:00:48,919 Speaker 1: Tell us what the last couple of years have been 15 00:00:48,960 --> 00:00:50,720 Speaker 1: like for your business. The sixth sign it is I 16 00:00:50,800 --> 00:00:54,520 Speaker 1: read that Signal is the world's largest retailer of diamond jewelry. 17 00:00:54,600 --> 00:00:57,800 Speaker 1: Is that true? Yes, that's right. So we operate under 18 00:00:57,840 --> 00:01:02,000 Speaker 1: a number of retail banners that many customers no k sales. 19 00:01:02,160 --> 00:01:06,720 Speaker 1: Jared Banter by piercing Pagoda. We have an online purely 20 00:01:06,840 --> 00:01:10,560 Speaker 1: digital play retailer, James Allen dot com. Just recently in 21 00:01:10,560 --> 00:01:13,480 Speaker 1: the last year purchased Diamonds Direct and Rocks Box, which 22 00:01:13,520 --> 00:01:16,680 Speaker 1: is the number one jewelry rental and subscription business in 23 00:01:16,720 --> 00:01:19,480 Speaker 1: the US. So we are number one in the US 24 00:01:19,520 --> 00:01:22,959 Speaker 1: both in bricks and mortar and e commerce. We're also 25 00:01:23,000 --> 00:01:26,200 Speaker 1: the number one jeweler in Canada with People's Jewelers and 26 00:01:26,280 --> 00:01:28,959 Speaker 1: in the UK with Ernest Jones and H. Samuel. So 27 00:01:29,080 --> 00:01:31,840 Speaker 1: I'm just looking at your fundamentals here on the Bloomberg. 28 00:01:31,880 --> 00:01:33,640 Speaker 1: It's great with any stock you can take GF go 29 00:01:33,800 --> 00:01:38,000 Speaker 1: and see your revenue. Uh and um, EPs, you guys 30 00:01:38,040 --> 00:01:42,080 Speaker 1: aren't doing great business obviously, up fifty percent year over 31 00:01:42,200 --> 00:01:45,280 Speaker 1: year in terms of revenue growth EPs at a near 32 00:01:45,319 --> 00:01:50,120 Speaker 1: record high. UM. Why Why is that? This is really 33 00:01:50,120 --> 00:01:53,920 Speaker 1: the culmination of several years of transformation that the company 34 00:01:53,960 --> 00:01:56,440 Speaker 1: has been under and I'm very proud of our team 35 00:01:56,480 --> 00:01:59,280 Speaker 1: for embracing those strategies and for the passion that they have. 36 00:01:59,520 --> 00:02:02,600 Speaker 1: We we have been working to drive out all costs 37 00:02:02,640 --> 00:02:05,440 Speaker 1: that customers don't see or care about, and we've invested, 38 00:02:05,520 --> 00:02:09,359 Speaker 1: We've invested that in creating a much stronger digital presence. 39 00:02:09,760 --> 00:02:12,079 Speaker 1: What we know about shoppers as they came through COVID 40 00:02:12,160 --> 00:02:15,519 Speaker 1: is that they're much more interested in searching and browsing 41 00:02:15,560 --> 00:02:18,760 Speaker 1: online before they go to a retail store. In fact, 42 00:02:18,760 --> 00:02:22,880 Speaker 1: in our business, now nine of our highest value customers, 43 00:02:22,919 --> 00:02:25,520 Speaker 1: so people who spend more than five dollars with us, 44 00:02:25,960 --> 00:02:30,560 Speaker 1: interact with us both online and in stores. So this 45 00:02:30,680 --> 00:02:33,960 Speaker 1: this is growth. I mean, if you look across different 46 00:02:33,960 --> 00:02:37,359 Speaker 1: segments and I know you have a ton of new 47 00:02:37,680 --> 00:02:43,320 Speaker 1: kind of high tech businesses springing up, is online sales 48 00:02:43,360 --> 00:02:47,680 Speaker 1: your your biggest growth business. It's definitely the biggest new 49 00:02:47,800 --> 00:02:51,680 Speaker 1: interaction point for our customers. Still about eighty percent of 50 00:02:51,800 --> 00:02:55,120 Speaker 1: stores and jewels of sales in jewelry happen in store, 51 00:02:55,639 --> 00:02:59,000 Speaker 1: so people aren't buying as much online, but they're definitely 52 00:02:59,040 --> 00:03:02,560 Speaker 1: getting informed on line. We have features now like virtual 53 00:03:02,680 --> 00:03:07,720 Speaker 1: try on online, virtual jewelry consulting, asynchronous chat where you 54 00:03:07,720 --> 00:03:09,840 Speaker 1: can chat with someone one day and come back to 55 00:03:09,919 --> 00:03:13,320 Speaker 1: the same chat a week later. So we've really invested 56 00:03:13,320 --> 00:03:16,200 Speaker 1: in digital tools to make the shopping experience easy. So 57 00:03:16,320 --> 00:03:18,680 Speaker 1: talk to us about the pandemic that two years did 58 00:03:18,720 --> 00:03:22,000 Speaker 1: you shut down stores and how did you manage that. 59 00:03:22,240 --> 00:03:24,560 Speaker 1: I'm guessing it's a regional situation in different parts of 60 00:03:24,560 --> 00:03:28,720 Speaker 1: the country doing different types of policies. So we we 61 00:03:28,800 --> 00:03:31,360 Speaker 1: took a very proactive stance on that to keep our 62 00:03:31,400 --> 00:03:35,720 Speaker 1: team members safe. UM we closed our stores almost exactly 63 00:03:35,760 --> 00:03:39,120 Speaker 1: two years ago on March twenty three. That was a 64 00:03:39,240 --> 00:03:42,040 Speaker 1: scary thing to do for a retailer that was very 65 00:03:42,040 --> 00:03:45,760 Speaker 1: brick and mortar focused, but we had already been transforming 66 00:03:45,800 --> 00:03:50,680 Speaker 1: our digital operations the Christmas before. UM. Everyone of our 67 00:03:50,760 --> 00:03:53,720 Speaker 1: sales associates had been working with iPads in the store, 68 00:03:54,080 --> 00:03:56,400 Speaker 1: so within forty eight hours we turned those on in 69 00:03:56,440 --> 00:03:59,400 Speaker 1: their living rooms and they were still able to serve 70 00:04:00,040 --> 00:04:03,920 Speaker 1: of our customers. Our digital business really exploded during that 71 00:04:04,000 --> 00:04:06,800 Speaker 1: time period and we were ready to lean into that pivot. 72 00:04:07,240 --> 00:04:10,640 Speaker 1: And and I would say, if anything, it accelerated our transformation. 73 00:04:10,680 --> 00:04:13,559 Speaker 1: That's you know that amazed me talking to different luxury 74 00:04:13,600 --> 00:04:17,400 Speaker 1: retailers about how customers did make the pivot to digital. Like, 75 00:04:17,440 --> 00:04:19,279 Speaker 1: if I'm gonna lay down a big chunk of money 76 00:04:19,279 --> 00:04:22,479 Speaker 1: for something, whether it's a diamond or an automobile or 77 00:04:22,480 --> 00:04:24,840 Speaker 1: a fur coat, I want to see it, touch it, 78 00:04:24,880 --> 00:04:27,640 Speaker 1: feel it. But that wasn't necessarily the case. Do you 79 00:04:27,640 --> 00:04:30,640 Speaker 1: buy a lot of fur coats? I do not. Well, 80 00:04:31,000 --> 00:04:32,520 Speaker 1: you know you have to. You have to think about 81 00:04:32,520 --> 00:04:35,359 Speaker 1: what matters most in each category, and in jewelry, the 82 00:04:35,440 --> 00:04:38,440 Speaker 1: two key things that customers are looking for before they 83 00:04:38,440 --> 00:04:43,679 Speaker 1: make an expensive purchase our consultation or advice and visualization. 84 00:04:43,800 --> 00:04:46,200 Speaker 1: You want to see what it looks like. But think 85 00:04:46,240 --> 00:04:48,560 Speaker 1: about trying to look at a diamond in a store 86 00:04:48,720 --> 00:04:51,839 Speaker 1: using a loop. It's not very easy. I mean, you 87 00:04:51,839 --> 00:04:53,560 Speaker 1: pull it back and forth in front of your eye. 88 00:04:53,560 --> 00:04:56,200 Speaker 1: You can't see the diamond that Well, we came up 89 00:04:56,200 --> 00:04:59,359 Speaker 1: with a technology where we take hundreds of photos of 90 00:04:59,360 --> 00:05:02,960 Speaker 1: a diamond, blow it up forty times in HD You 91 00:05:03,000 --> 00:05:06,320 Speaker 1: can actually see that the you know, a diamond much 92 00:05:06,400 --> 00:05:09,680 Speaker 1: better now digitally than you can't even in the store. Yeah, 93 00:05:09,680 --> 00:05:12,760 Speaker 1: I'm sure that's that's the case. What about the current 94 00:05:12,800 --> 00:05:16,039 Speaker 1: war in Ukraine? How and the sanctions on Russia? How 95 00:05:16,080 --> 00:05:20,159 Speaker 1: difficult is that as a diamond retailer When I'm I've 96 00:05:20,200 --> 00:05:24,040 Speaker 1: read that Russia maybe the world's largest supplier of raw diamonds. 97 00:05:25,520 --> 00:05:29,040 Speaker 1: So thankfully we don't have any operations on the ground 98 00:05:29,080 --> 00:05:32,679 Speaker 1: in Russia or Ukraine, but we did act very quickly 99 00:05:32,760 --> 00:05:36,240 Speaker 1: on this um. Signet has been a leader in responsible 100 00:05:36,240 --> 00:05:39,320 Speaker 1: and ethical sourcing of jewelry now for more than a decade, 101 00:05:39,320 --> 00:05:42,880 Speaker 1: where founders of the Responsible Jewelry Council, members of the 102 00:05:42,920 --> 00:05:46,080 Speaker 1: World Diamond Council, and we actually go above and beyond 103 00:05:46,200 --> 00:05:50,560 Speaker 1: that and have our own Signet Responsible Sourcing protocol. So 104 00:05:50,640 --> 00:05:53,320 Speaker 1: customers for many years have been able to count on 105 00:05:53,480 --> 00:05:58,799 Speaker 1: everything in a Signet store being pristinely sourced. And we're agile. 106 00:05:59,200 --> 00:06:01,640 Speaker 1: We have a group of changing vendors. We've gone to them, 107 00:06:01,640 --> 00:06:04,599 Speaker 1: We've said we don't want any diamonds sourced after this 108 00:06:04,680 --> 00:06:08,040 Speaker 1: conflict that came from Russia in our jewelry. We've stopped 109 00:06:08,040 --> 00:06:11,280 Speaker 1: our own direct interaction and so customers can feel very 110 00:06:11,320 --> 00:06:14,000 Speaker 1: good about buying jewelry at Signet. All right, Jenna, thank 111 00:06:14,040 --> 00:06:15,720 Speaker 1: you so much for coming, and we really appreciate you 112 00:06:15,760 --> 00:06:19,800 Speaker 1: coming into our studios here today. Jennet Drosos, CEO of 113 00:06:19,839 --> 00:06:22,920 Speaker 1: Signet Jewelers again public and traded company s i G. 114 00:06:23,080 --> 00:06:26,159 Speaker 1: They're based in Akron, Ohio, but Jenna joins us here 115 00:06:26,200 --> 00:06:32,640 Speaker 1: in New York and we appreciate that. All Right, Supreme 116 00:06:32,680 --> 00:06:36,039 Speaker 1: Court nomination, got another one coming. That means we're gonna 117 00:06:36,080 --> 00:06:39,080 Speaker 1: have some holly contested I guess some hearings, if you will. 118 00:06:39,279 --> 00:06:42,360 Speaker 1: June Grasso, host of Bloomberg Law and Bloomberg Opinion, joins 119 00:06:42,400 --> 00:06:44,839 Speaker 1: us here in our Bloomberg Interactive Brooker Studio. All right, 120 00:06:44,920 --> 00:06:48,360 Speaker 1: So Katanji Brown Jackson, June, what can you tell us 121 00:06:48,360 --> 00:06:54,279 Speaker 1: about Katanji Brown Jackson? Well, she is currently uh appellate 122 00:06:54,320 --> 00:06:56,720 Speaker 1: court on the d C Circuit Court of Appeals, which 123 00:06:56,760 --> 00:06:59,719 Speaker 1: is sort of known as the second highest court in 124 00:06:59,720 --> 00:07:02,159 Speaker 1: the and it's the feeder court for the Supreme Court. 125 00:07:02,640 --> 00:07:05,840 Speaker 1: And um, she was a district court judge for ten years. 126 00:07:05,839 --> 00:07:07,960 Speaker 1: She just had a hearing last year to get onto 127 00:07:07,960 --> 00:07:10,000 Speaker 1: the d C Circuit Court of a judge. She has 128 00:07:10,040 --> 00:07:13,840 Speaker 1: a background as a public defender, which is something that's 129 00:07:13,880 --> 00:07:17,080 Speaker 1: so unusual on the court. The last person who defended 130 00:07:17,280 --> 00:07:21,080 Speaker 1: criminals who sat on the court was um was it 131 00:07:21,200 --> 00:07:25,080 Speaker 1: was decades ago. So what what? Um? What we're saying 132 00:07:25,160 --> 00:07:29,040 Speaker 1: seeing is that she might be attacked because of her 133 00:07:29,240 --> 00:07:32,720 Speaker 1: defense of you know people, and that's one of the 134 00:07:32,760 --> 00:07:37,320 Speaker 1: attacks that they lodged when she was at her I 135 00:07:37,360 --> 00:07:40,560 Speaker 1: just remember, I just remember the Cavanaugh hearing being so ugly, 136 00:07:41,120 --> 00:07:44,000 Speaker 1: so ugly, and so many images that are seriously, people's 137 00:07:44,040 --> 00:07:46,120 Speaker 1: you know, literally television images. How do you think this 138 00:07:46,120 --> 00:07:48,880 Speaker 1: one's gonna go? Well, if you remember the Amy Coney 139 00:07:48,920 --> 00:07:51,640 Speaker 1: Barrett hearings, which were after the caval hearings were not 140 00:07:51,680 --> 00:07:55,240 Speaker 1: that ugly. Probably you remember that because you remember Kavanaugh 141 00:07:55,240 --> 00:07:58,280 Speaker 1: because it stood out, and we remember Clarence Thomas. There 142 00:07:58,280 --> 00:08:00,680 Speaker 1: are some hearings that really and out, and a lot 143 00:08:00,680 --> 00:08:04,400 Speaker 1: of times you don't remember what what the the nominee said. 144 00:08:04,440 --> 00:08:07,560 Speaker 1: You worry you remember what the attack on the nominee was. 145 00:08:07,640 --> 00:08:10,080 Speaker 1: It's all about the questions in these kinds of hearings. 146 00:08:10,080 --> 00:08:12,640 Speaker 1: It's all about the senators getting their questions in it. 147 00:08:12,760 --> 00:08:15,760 Speaker 1: So you'll find a lot of the Republican senators who 148 00:08:15,840 --> 00:08:20,920 Speaker 1: have presidential ambitions, like Josh Holly Ted Cruz are going 149 00:08:21,000 --> 00:08:24,160 Speaker 1: to be on the attack most likely in these hearings. 150 00:08:24,200 --> 00:08:27,480 Speaker 1: Even though I mean her record is I would say, 151 00:08:27,880 --> 00:08:31,080 Speaker 1: I mean it's it's difficult to assail her on certain points. 152 00:08:31,080 --> 00:08:34,600 Speaker 1: For example, the hot button issues like abortion, religious rights. 153 00:08:34,640 --> 00:08:37,400 Speaker 1: She hasn't written about that. She's been on the court 154 00:08:37,480 --> 00:08:40,760 Speaker 1: for only a few months, so she hasn't written about that, 155 00:08:41,000 --> 00:08:42,920 Speaker 1: and her as a district court judge, you don't write 156 00:08:42,920 --> 00:08:44,559 Speaker 1: about those things. So they're not gonna be able to 157 00:08:44,600 --> 00:08:46,800 Speaker 1: get her on that. So they found other things too, 158 00:08:47,640 --> 00:08:52,120 Speaker 1: assail her on whoa like what? Like what? That's a 159 00:08:52,120 --> 00:08:55,360 Speaker 1: good question. That's a good question. Let me with that 160 00:08:55,400 --> 00:08:58,400 Speaker 1: without we don't want to get political about it, obviously, 161 00:08:58,720 --> 00:09:02,960 Speaker 1: Um but if you when you were at Harvard Law 162 00:09:03,200 --> 00:09:06,120 Speaker 1: or wherever you studied, I'm sure you had to take 163 00:09:06,160 --> 00:09:09,400 Speaker 1: the other side occasionally, right, So put yourself in the 164 00:09:09,440 --> 00:09:14,600 Speaker 1: shoes of a white male Republican. I wonder which one 165 00:09:14,880 --> 00:09:18,440 Speaker 1: of the few that around the Judiciary Committee, all of 166 00:09:18,480 --> 00:09:21,840 Speaker 1: them except for one, there's one. There's one female Republican. 167 00:09:22,080 --> 00:09:23,959 Speaker 1: I will tell you, because we know what they're going 168 00:09:23,960 --> 00:09:26,160 Speaker 1: to attack on. Basically, they're going, what would you do 169 00:09:26,200 --> 00:09:28,680 Speaker 1: if you were advising the Republican Party? How do you 170 00:09:28,720 --> 00:09:32,200 Speaker 1: get rid of kenjy kb J? Can't do it. They 171 00:09:32,240 --> 00:09:34,440 Speaker 1: can't get rid of her unless the Democrats, who have 172 00:09:34,480 --> 00:09:37,360 Speaker 1: held together, by the way, all fifty Democrats on all 173 00:09:37,440 --> 00:09:40,679 Speaker 1: of Biden's nominees. Unless one of them suddenly says Joe 174 00:09:40,760 --> 00:09:43,559 Speaker 1: Manchin kristin cinema, Oh, I'm not going to support her. 175 00:09:43,880 --> 00:09:46,520 Speaker 1: They really can't get her. And the thing is that 176 00:09:46,640 --> 00:09:49,080 Speaker 1: so the attacks are going to be. Mitch McConnell has 177 00:09:49,080 --> 00:09:51,960 Speaker 1: already signaled this. She's soft on crime. She was a 178 00:09:51,960 --> 00:09:55,240 Speaker 1: public a federal public defender, so she's soft on crime. 179 00:09:55,280 --> 00:09:58,080 Speaker 1: And also Josh Holly came out with something a week 180 00:09:58,120 --> 00:10:01,600 Speaker 1: ago that has not been raised in the three times 181 00:10:01,600 --> 00:10:05,040 Speaker 1: she's been before the Judiciary Committee and including the one 182 00:10:05,080 --> 00:10:07,319 Speaker 1: time that she was there when he was questioning her, 183 00:10:07,600 --> 00:10:12,880 Speaker 1: and that's that she's soft on child pornographers. That her sentencing. Now, 184 00:10:13,000 --> 00:10:16,559 Speaker 1: this is a good area for Republicans because who doesn't 185 00:10:16,840 --> 00:10:20,640 Speaker 1: hate child pornographers? You know, it's just certainly the Republicans 186 00:10:21,160 --> 00:10:25,360 Speaker 1: do right, and the Democrats do y'all do right. It's 187 00:10:25,400 --> 00:10:28,160 Speaker 1: and also it doesn't involve and it's about sentencing, and 188 00:10:28,200 --> 00:10:33,160 Speaker 1: it doesn't involve the sensitive area of racist, racist sentencing, 189 00:10:33,160 --> 00:10:36,640 Speaker 1: you know where that's been alleged. So she in point 190 00:10:36,679 --> 00:10:40,480 Speaker 1: of fact, she's um, I think about nine defendants and 191 00:10:40,559 --> 00:10:45,080 Speaker 1: she has sentenced to to below two to the minimum 192 00:10:45,400 --> 00:10:49,760 Speaker 1: and I think seven to the a little below the minimum. 193 00:10:50,040 --> 00:10:53,400 Speaker 1: Why wouldn't you just throw away the key because it's 194 00:10:53,480 --> 00:10:56,480 Speaker 1: it's child pornography. For child pornography, this is your your 195 00:10:56,720 --> 00:10:58,680 Speaker 1: what you have stuff on your computer? Right? You could 196 00:10:58,679 --> 00:11:01,679 Speaker 1: go to prison for decade. The laws are really out 197 00:11:01,760 --> 00:11:04,120 Speaker 1: of date, and in those cases, some of them, the 198 00:11:04,120 --> 00:11:08,120 Speaker 1: federal prosecutors recommended below the minimum. The sentencing laws are 199 00:11:08,120 --> 00:11:11,120 Speaker 1: out of date. And this all the judges, about six 200 00:11:11,720 --> 00:11:16,760 Speaker 1: judges sentenced below the maximum on those kinds of crimes 201 00:11:16,800 --> 00:11:19,800 Speaker 1: because it's you know, you have to compare them to 202 00:11:20,080 --> 00:11:23,400 Speaker 1: you know, murder, two different arson. What's the timing on 203 00:11:23,400 --> 00:11:27,840 Speaker 1: this whole process. They expect that before the Senate goes 204 00:11:27,880 --> 00:11:31,240 Speaker 1: away on its Easter break that the process will be done, 205 00:11:31,240 --> 00:11:33,320 Speaker 1: and maybe they'll be a vote before then. They're hoping 206 00:11:33,360 --> 00:11:35,600 Speaker 1: that they will be a vote before them. And from 207 00:11:35,600 --> 00:11:37,560 Speaker 1: your perspective, what do you think the odds are of 208 00:11:37,559 --> 00:11:40,240 Speaker 1: her getting confirmed here? I think the odds are. I'm 209 00:11:40,240 --> 00:11:44,560 Speaker 1: gonna say, just to leave, just to leave a so 210 00:11:44,600 --> 00:11:47,600 Speaker 1: Matt will tell me later on. But that doesn't do 211 00:11:47,640 --> 00:11:50,480 Speaker 1: anything really for the direction now. And that's why that's 212 00:11:50,480 --> 00:11:52,360 Speaker 1: why this is not going to be you know, one 213 00:11:52,360 --> 00:11:56,280 Speaker 1: of those like Kavanaugh that meant something, Amy Coney, Barrett, 214 00:11:56,360 --> 00:12:00,000 Speaker 1: that meant something. But this is just replacing one liberal 215 00:12:00,160 --> 00:12:02,680 Speaker 1: with another liberal in a court that has a sixth 216 00:12:03,240 --> 00:12:07,040 Speaker 1: person conservative majority. All right, all right, Juan, thank you 217 00:12:07,040 --> 00:12:09,920 Speaker 1: so much for joining us here in our studio June Grasso, 218 00:12:10,040 --> 00:12:13,520 Speaker 1: host of Bloomberg Law and Bloomberg Opinion, giving us the 219 00:12:13,600 --> 00:12:18,040 Speaker 1: latest on the Supreme Court process. Hopefully, Uh, get the 220 00:12:18,160 --> 00:12:21,240 Speaker 1: Katanji Brown Jackson. I guess if you're a member of Congress, 221 00:12:21,240 --> 00:12:27,559 Speaker 1: I'd like to get this done by easter. Well, we've 222 00:12:27,600 --> 00:12:30,000 Speaker 1: been spending a lot of time recently talking about the 223 00:12:30,120 --> 00:12:32,680 Speaker 1: rates market, the yield curve. We're at or near inversion 224 00:12:32,720 --> 00:12:35,080 Speaker 1: in various portions of the yield curve. What does that mean? 225 00:12:35,600 --> 00:12:37,920 Speaker 1: Let's bring in r J. Gallow, Senior portfolio manager for 226 00:12:38,000 --> 00:12:41,280 Speaker 1: Federated Hermes. R J. When you see certain parts of 227 00:12:41,320 --> 00:12:44,960 Speaker 1: the U S yield curve at or near inversion, does 228 00:12:44,960 --> 00:12:49,960 Speaker 1: that meaningfully raised the recession risk in your mind? Good morning? 229 00:12:50,520 --> 00:12:54,560 Speaker 1: I think it reflects the fact that we have a 230 00:12:54,640 --> 00:12:57,360 Speaker 1: shock going on, sort of a series of them, the 231 00:12:57,400 --> 00:12:59,840 Speaker 1: most notable being the Russian invasion of Ukraine in the 232 00:13:00,000 --> 00:13:03,040 Speaker 1: area economic impacts in terms of the West response to 233 00:13:03,240 --> 00:13:09,239 Speaker 1: that invasion. Uh. That's a clear aggregate supply shock, broad based, exogenous, 234 00:13:09,320 --> 00:13:12,640 Speaker 1: if you will, coming from the geopolitical realm. UM, and 235 00:13:12,679 --> 00:13:17,000 Speaker 1: that historically increases the risk of recession. UM. Add to 236 00:13:17,040 --> 00:13:21,000 Speaker 1: that that the Feds in tightening mode. UH, and historically 237 00:13:21,040 --> 00:13:24,040 Speaker 1: that also suggests increased risk of recession. Oftentimes, when the 238 00:13:24,120 --> 00:13:27,520 Speaker 1: FED has to pivot aggressively to fight inflation, the result 239 00:13:28,000 --> 00:13:31,680 Speaker 1: is a recession eventually ensues. So we're facing both of 240 00:13:31,720 --> 00:13:35,040 Speaker 1: those factors, the geopolitical shock and in the sense one 241 00:13:35,360 --> 00:13:38,720 Speaker 1: pivot from transitory too inflation is a problem. It makes 242 00:13:38,720 --> 00:13:41,120 Speaker 1: sense that the Yolk curb is flattening given both of 243 00:13:41,160 --> 00:13:43,559 Speaker 1: those you put those two together, it's clear that the 244 00:13:43,559 --> 00:13:46,520 Speaker 1: recession risk is rising in the market's mind. However, I 245 00:13:46,520 --> 00:13:48,839 Speaker 1: don't think the Yolk curb inverting is causal. I don't 246 00:13:48,840 --> 00:13:53,360 Speaker 1: think that ever causes recessions. I understand that people you know, 247 00:13:53,440 --> 00:13:57,240 Speaker 1: borrow short, land long, and can slow down uh the 248 00:13:57,280 --> 00:14:00,360 Speaker 1: financial mechanism that you see in financial intermediation. But I 249 00:14:00,360 --> 00:14:02,200 Speaker 1: think that the flattening of the curve is more people's 250 00:14:02,240 --> 00:14:05,640 Speaker 1: expectations that recession risk has risen. It's not a causal 251 00:14:05,679 --> 00:14:08,480 Speaker 1: relationship in my mind. I mean, some people have been 252 00:14:08,520 --> 00:14:10,960 Speaker 1: saying lately the yield curve may have caused COVID nineteen. 253 00:14:11,640 --> 00:14:14,720 Speaker 1: We saw it invert right before the pandemic. That was 254 00:14:14,760 --> 00:14:16,480 Speaker 1: a joke to those who didn't get it. I'm looking 255 00:14:16,480 --> 00:14:20,720 Speaker 1: at Paul's face, thinking he didn't get that correlation. He 256 00:14:20,760 --> 00:14:23,480 Speaker 1: didn't get that. No, I mean obviously that that was 257 00:14:23,520 --> 00:14:26,880 Speaker 1: our most recent recession, right, And UH, if you believe 258 00:14:26,920 --> 00:14:29,440 Speaker 1: in the predictive qualities of an inverted yield curve, you've 259 00:14:29,440 --> 00:14:31,480 Speaker 1: got to give it a lot of credit for that. Um. 260 00:14:32,040 --> 00:14:35,200 Speaker 1: No one could could have seen that coming. Nonetheless, we 261 00:14:35,320 --> 00:14:40,560 Speaker 1: have very high inflation and there is concerns of a 262 00:14:40,680 --> 00:14:43,880 Speaker 1: growth slow down. UM. Even if we don't go into 263 00:14:43,880 --> 00:14:47,120 Speaker 1: a recession, it looks like we could almost grind to 264 00:14:47,160 --> 00:14:51,560 Speaker 1: a halt here. Are you worried about stagflation? UM? I 265 00:14:51,600 --> 00:14:55,320 Speaker 1: think about six to twelve months ago, the words stagflation 266 00:14:55,360 --> 00:14:58,240 Speaker 1: sort of made my skin crawls. You know, it seems 267 00:14:58,320 --> 00:15:01,400 Speaker 1: inappropriate for the context that the time. I now think 268 00:15:01,440 --> 00:15:04,160 Speaker 1: it's a word we should be using. Uh. It's very 269 00:15:04,160 --> 00:15:09,880 Speaker 1: clear that the exogenous shock arising from the conflict, UH 270 00:15:10,320 --> 00:15:13,600 Speaker 1: is the kind of thing that results in broad based inflation, 271 00:15:13,640 --> 00:15:17,160 Speaker 1: which was already bad before the Russian troops invaded Ukraine. 272 00:15:17,680 --> 00:15:21,760 Speaker 1: It's also the kind of thing that produces demand destruction 273 00:15:21,880 --> 00:15:25,479 Speaker 1: ultimately slows down economic activities. So I do think stagpulation 274 00:15:25,520 --> 00:15:28,760 Speaker 1: is an appropriate word probably more so for Europe. Maybe 275 00:15:28,760 --> 00:15:30,880 Speaker 1: I'm being extreme, but I think when you actually have 276 00:15:31,040 --> 00:15:35,440 Speaker 1: recession outcomes and inflation together, uh, stagflation is the right 277 00:15:35,480 --> 00:15:37,840 Speaker 1: word to use now here in the United States. I 278 00:15:37,880 --> 00:15:41,040 Speaker 1: think it's a stagflationary shock. Uh. We may be able 279 00:15:41,080 --> 00:15:44,400 Speaker 1: to skirt a recession. The risks clearly risen, as evidenced 280 00:15:44,400 --> 00:15:48,000 Speaker 1: by the yokurve um, but it's not baked in the cake. 281 00:15:48,080 --> 00:15:50,120 Speaker 1: I mean, we have a lot of strong economic momentum 282 00:15:50,160 --> 00:15:53,360 Speaker 1: here in both the labor market, balance sheets are strong, 283 00:15:53,440 --> 00:15:56,960 Speaker 1: both for households and businesses. Uh, there's a good chance 284 00:15:57,040 --> 00:16:00,120 Speaker 1: that the United States can sort of power through this um. 285 00:16:00,160 --> 00:16:02,800 Speaker 1: That said, global markets are global in nature, and the 286 00:16:02,840 --> 00:16:04,760 Speaker 1: response that you're seeing in terms of the Yoeld curve 287 00:16:05,440 --> 00:16:08,400 Speaker 1: I think reflects the rising risks that are there. R J. 288 00:16:08,520 --> 00:16:10,840 Speaker 1: We got the oil on the move higher again today 289 00:16:11,200 --> 00:16:14,760 Speaker 1: w T I coot up over five about dollars a barrel, 290 00:16:15,040 --> 00:16:18,440 Speaker 1: just kind of, you know, reiterating in people's minds the 291 00:16:18,440 --> 00:16:21,600 Speaker 1: inflationary pressures that are out there in this economy. How 292 00:16:21,600 --> 00:16:24,120 Speaker 1: do you think about inflation, whether it's you know, the 293 00:16:24,200 --> 00:16:26,920 Speaker 1: duration of this inflationary cycle we're in or the severity 294 00:16:28,880 --> 00:16:32,680 Speaker 1: I'm struck by the fact that the markets still have 295 00:16:33,240 --> 00:16:36,640 Speaker 1: pretty high confidence. If you look at the the slope 296 00:16:36,680 --> 00:16:38,960 Speaker 1: or the yield curve of of the U S TIPS 297 00:16:38,960 --> 00:16:42,280 Speaker 1: break evens, UH, it's very downward sloping. It has been 298 00:16:42,280 --> 00:16:45,960 Speaker 1: inverted for some time, meaning that near term expectations for 299 00:16:46,000 --> 00:16:49,200 Speaker 1: inflation are much higher than long term expectations. So, for example, 300 00:16:49,800 --> 00:16:54,000 Speaker 1: UM I LB on your Bloomberg, the break even of 301 00:16:54,040 --> 00:16:56,480 Speaker 1: two and three years is are each well north of 302 00:16:56,520 --> 00:17:00,000 Speaker 1: four percent. Four seventy eight for two year break evens, 303 00:17:00,080 --> 00:17:04,400 Speaker 1: you know, astronomically high by by recent standards in recent decades. 304 00:17:04,800 --> 00:17:06,119 Speaker 1: When you go out to the ten year, it's down 305 00:17:06,200 --> 00:17:09,720 Speaker 1: to two high in the history of tips, but that's 306 00:17:09,760 --> 00:17:13,679 Speaker 1: still a sharp disinflation between the shorter break even and 307 00:17:13,720 --> 00:17:15,199 Speaker 1: the longer break even. You go all the way out 308 00:17:15,240 --> 00:17:17,920 Speaker 1: to the third year, it's a two. So I think 309 00:17:17,960 --> 00:17:20,879 Speaker 1: that the Fed has given the market what it needs 310 00:17:21,320 --> 00:17:23,800 Speaker 1: in the sense that the market needs to believe that 311 00:17:23,840 --> 00:17:26,720 Speaker 1: the Federal Reserve believes inflation fighting is still a huge 312 00:17:26,720 --> 00:17:29,000 Speaker 1: part of their mandate, and in fact they are now 313 00:17:29,000 --> 00:17:32,160 Speaker 1: focusing primarily on that side of their dual mandate. If 314 00:17:32,160 --> 00:17:34,840 Speaker 1: the Fed we're not to have done that, I think 315 00:17:34,880 --> 00:17:37,239 Speaker 1: we'd be facing a much more difficult bond market right 316 00:17:37,240 --> 00:17:40,680 Speaker 1: now than we already have UM in the sense that 317 00:17:40,760 --> 00:17:44,240 Speaker 1: nominal yields will be rising more rapidly, that these inflation 318 00:17:44,280 --> 00:17:46,679 Speaker 1: break even is probably wouldn't be nearly as inverted, and 319 00:17:46,760 --> 00:17:48,720 Speaker 1: losses would be more stark than they already are. And 320 00:17:48,720 --> 00:17:51,240 Speaker 1: it's been a pretty rough year for bonds. When you 321 00:17:51,400 --> 00:17:55,480 Speaker 1: think about the UH. The the Treasury Aggregate Index, for example, 322 00:17:56,000 --> 00:17:58,520 Speaker 1: is on a year today basis, the Bloomberg Agreed Index, 323 00:17:58,560 --> 00:18:03,840 Speaker 1: I should say, UH is now down five two percent, 324 00:18:03,960 --> 00:18:06,440 Speaker 1: and the Treasury Index itself, that component is down four 325 00:18:06,640 --> 00:18:10,479 Speaker 1: six So the inflation process, I think people believe if 326 00:18:10,520 --> 00:18:13,119 Speaker 1: that's doing what it needs to do, and inflation should 327 00:18:13,160 --> 00:18:15,359 Speaker 1: diminish as we move forward. If it doesn't happen, If 328 00:18:15,359 --> 00:18:17,840 Speaker 1: that doesn't happen, the bond market sell off will will 329 00:18:17,880 --> 00:18:21,719 Speaker 1: actually become more difficult, it will become more protractive. All right, 330 00:18:21,800 --> 00:18:23,920 Speaker 1: r J, thanks so much for joining us. Once again. 331 00:18:23,960 --> 00:18:27,359 Speaker 1: I always appreciate getting your perspective there are Gallo, senior 332 00:18:27,400 --> 00:18:32,800 Speaker 1: portfolio manager for Federated Hermes UH. Looking about stagflation is 333 00:18:32,840 --> 00:18:35,800 Speaker 1: something that is a term that's coming into our j's 334 00:18:35,960 --> 00:18:39,840 Speaker 1: vocabulary recently, and he's a wolverine, and he's a Michigan wolverine. 335 00:18:40,160 --> 00:18:43,000 Speaker 1: Actually was looking. I think he might have gone to 336 00:18:43,280 --> 00:18:46,399 Speaker 1: the University of Michigan for a four year period in 337 00:18:46,400 --> 00:18:51,560 Speaker 1: which Michigan won every single game. Is that right against 338 00:18:51,600 --> 00:18:56,919 Speaker 1: the Ohio State University. This is the Big Take, the 339 00:18:57,040 --> 00:19:01,080 Speaker 1: best of Boomberg's in depth original reporting from around the globe. 340 00:19:01,160 --> 00:19:04,080 Speaker 1: This is a really fast moving story that caused a 341 00:19:04,080 --> 00:19:07,879 Speaker 1: lot of outrage among investors. This is so fascinating. Market 342 00:19:07,960 --> 00:19:10,440 Speaker 1: shutdown in a way it's never done before. That's gonna 343 00:19:10,440 --> 00:19:13,880 Speaker 1: have consequences for years to come. The Big Take on 344 00:19:14,040 --> 00:19:18,800 Speaker 1: Bloomberg Radio. All Right, Matt, I've told you before I 345 00:19:18,840 --> 00:19:22,560 Speaker 1: take New Jersey Transit. Are we doing a sounder? I 346 00:19:22,800 --> 00:19:25,160 Speaker 1: just talk right over there. Oh well, no worries, Okay, 347 00:19:25,240 --> 00:19:27,359 Speaker 1: I gotta get this story. Did the sounder dud? We? Okay? 348 00:19:27,560 --> 00:19:29,280 Speaker 1: All right? But you know, so I take New Jersey 349 00:19:29,280 --> 00:19:31,520 Speaker 1: Transit in every day during the week man, and I 350 00:19:31,520 --> 00:19:34,000 Speaker 1: would say the trains now are maybe fifty full, but 351 00:19:34,040 --> 00:19:37,160 Speaker 1: on the weekends, just backed everybody's coming in and see 352 00:19:37,200 --> 00:19:39,159 Speaker 1: games and go to bars and restaurants and stuff. But 353 00:19:39,760 --> 00:19:42,080 Speaker 1: people ain't coming back to work in size, and that's 354 00:19:42,080 --> 00:19:44,440 Speaker 1: a problem for New York City. I think Alicia Diaz, 355 00:19:44,520 --> 00:19:46,760 Speaker 1: she's a writer for Bloomberg's Hop Live team, She's got 356 00:19:46,800 --> 00:19:50,040 Speaker 1: the big take story of the day again, Alicia, thanks 357 00:19:50,040 --> 00:19:51,600 Speaker 1: so much for joining us on our Bloomberg and Arctic 358 00:19:51,640 --> 00:19:54,080 Speaker 1: Broker studio. What you find came to work today? She 359 00:19:54,119 --> 00:19:56,760 Speaker 1: came to work today absolutely, which is probably more than 360 00:19:56,760 --> 00:20:01,280 Speaker 1: you can say for a lot of her supervisors. Um, 361 00:20:01,440 --> 00:20:03,280 Speaker 1: So we kind of looked at this as two groups. 362 00:20:03,280 --> 00:20:05,560 Speaker 1: There's there's the tourist group. You know, we we're not 363 00:20:05,600 --> 00:20:08,359 Speaker 1: having as many international visitors. And then also we're not 364 00:20:08,400 --> 00:20:10,880 Speaker 1: having those, like you mentioned, the people who are commuting 365 00:20:10,880 --> 00:20:14,679 Speaker 1: into the office. And so it seems like as a result, 366 00:20:14,680 --> 00:20:17,240 Speaker 1: a lot of those restaurants, the coffee shops, the places 367 00:20:17,280 --> 00:20:20,800 Speaker 1: around Midtown and fied I are kind of just struggling 368 00:20:20,800 --> 00:20:23,840 Speaker 1: to keep their doors open. And that what the kids 369 00:20:23,840 --> 00:20:26,680 Speaker 1: call the financial district. That's right, my daughter trying to 370 00:20:26,720 --> 00:20:28,440 Speaker 1: explain that to me as like kids, I've been working 371 00:20:28,440 --> 00:20:30,919 Speaker 1: down on Wall Street for thirty five years, just just 372 00:20:31,000 --> 00:20:35,000 Speaker 1: tuned into that as well. The kids who sit around 373 00:20:34,240 --> 00:20:37,440 Speaker 1: all right, so what has to happen here is it 374 00:20:37,960 --> 00:20:40,000 Speaker 1: are the tourist coming back, because I was in Midtown 375 00:20:40,000 --> 00:20:41,919 Speaker 1: a couple of weeks ago and I thought I felt 376 00:20:41,960 --> 00:20:46,040 Speaker 1: a much more European international tourist. Play are we seeing 377 00:20:46,040 --> 00:20:48,920 Speaker 1: any of that. It seems like it's slowly coming back, 378 00:20:49,080 --> 00:20:52,879 Speaker 1: especially with um you know, Oh Macron being subdued, but 379 00:20:53,600 --> 00:20:56,120 Speaker 1: it looks like more international tourist at least the level 380 00:20:56,119 --> 00:20:58,879 Speaker 1: it was before the pandemics still aren't returning, and that 381 00:20:58,960 --> 00:21:02,919 Speaker 1: could be to travel restrictions. Are still nervous about getting 382 00:21:02,920 --> 00:21:06,560 Speaker 1: COVID or spreading covid um, and international tourists had to 383 00:21:06,560 --> 00:21:08,200 Speaker 1: spend the most money, and so that's why a lot 384 00:21:08,200 --> 00:21:11,040 Speaker 1: of the sectors relying on the most. So the problem, 385 00:21:11,119 --> 00:21:14,919 Speaker 1: I mean, I can imagine here where we're sitting in Midtown, 386 00:21:15,480 --> 00:21:17,280 Speaker 1: the problem must be that no one's coming back to 387 00:21:17,320 --> 00:21:20,119 Speaker 1: the office because all of the big box stores, for example, 388 00:21:20,160 --> 00:21:22,680 Speaker 1: that are downstairs in this building or across the street 389 00:21:22,800 --> 00:21:27,280 Speaker 1: are empty still. I mean they haven't been um filled 390 00:21:27,320 --> 00:21:30,600 Speaker 1: back up again. I don't understand what the problem is 391 00:21:30,640 --> 00:21:34,320 Speaker 1: in the Bronx because here in New York seven seven 392 00:21:34,359 --> 00:21:37,080 Speaker 1: point six percent unemployments, some of the worst of any 393 00:21:37,080 --> 00:21:39,399 Speaker 1: major sitting in the country, But the Bronx is eleven 394 00:21:39,400 --> 00:21:43,040 Speaker 1: percent And it's not exactly a Wall Street hub up there, right, 395 00:21:43,080 --> 00:21:45,800 Speaker 1: So what's the problem. That's a great question. And it 396 00:21:45,880 --> 00:21:51,160 Speaker 1: seems like, um, this is also um, disproportionately impacting um 397 00:21:51,200 --> 00:21:53,560 Speaker 1: a lot of black workers as well. UM. And that 398 00:21:53,920 --> 00:21:57,399 Speaker 1: could be because um, you know, they're more so in 399 00:21:57,440 --> 00:22:01,040 Speaker 1: the service industry and they're more doing face to face 400 00:22:01,160 --> 00:22:03,640 Speaker 1: jobs like being in healthcare or that kind of thing, 401 00:22:03,680 --> 00:22:07,160 Speaker 1: and so um, that rate is almost double for for 402 00:22:07,200 --> 00:22:10,240 Speaker 1: other workers. And so UM, there could be some ties 403 00:22:10,320 --> 00:22:13,240 Speaker 1: to that. I get so workers and the Bronx basically 404 00:22:13,280 --> 00:22:15,680 Speaker 1: would well, they'd live in the Bronx, they'd come down 405 00:22:15,680 --> 00:22:18,640 Speaker 1: and work and fini die. But since no one's going 406 00:22:18,680 --> 00:22:21,560 Speaker 1: to Wall Street, they can't get those jobs back, which 407 00:22:21,600 --> 00:22:24,320 Speaker 1: is why their unemployment is higher. That's a very real possibility. 408 00:22:24,560 --> 00:22:27,399 Speaker 1: So what are we hearing about how we're going to 409 00:22:27,480 --> 00:22:30,359 Speaker 1: repurpose some of these commercial real estate buildings in like 410 00:22:30,400 --> 00:22:32,320 Speaker 1: Midtown Manhattan for example. Ive hear some people saying, well, 411 00:22:32,320 --> 00:22:34,919 Speaker 1: maybe'll convert them into apartments. That might address maybe some 412 00:22:34,920 --> 00:22:36,800 Speaker 1: of the crazy craziness that we have here in the 413 00:22:37,080 --> 00:22:40,120 Speaker 1: in the residential rental market. What are you hearing? Yeah, 414 00:22:40,520 --> 00:22:43,360 Speaker 1: so we're hearing a mix of things. Definitely that residential 415 00:22:43,400 --> 00:22:47,240 Speaker 1: aspect where this could be more affordable housing. Some are 416 00:22:47,240 --> 00:22:49,560 Speaker 1: saying it's going to be more likely um, like luxury 417 00:22:49,560 --> 00:22:52,520 Speaker 1: apartment buildings and so, um, does that really address the 418 00:22:52,920 --> 00:22:56,679 Speaker 1: problem is another question. Um. I've also heard that this 419 00:22:56,760 --> 00:22:59,760 Speaker 1: kind of opens the door in terms of just recreating 420 00:23:00,080 --> 00:23:03,440 Speaker 1: town and maybe adding more cultural hobs or or more 421 00:23:03,440 --> 00:23:07,640 Speaker 1: biotech incubators and that type of thing, and really rethinking this, um, 422 00:23:07,640 --> 00:23:09,919 Speaker 1: like corporate centers doing that howny thing is gonna do that? 423 00:23:10,000 --> 00:23:12,960 Speaker 1: Is it the city administered the Mayor's office, is it 424 00:23:13,040 --> 00:23:14,640 Speaker 1: the I guess that may have been Office of Economic 425 00:23:15,040 --> 00:23:17,080 Speaker 1: Deployment or something in the city. Is it the city 426 00:23:17,320 --> 00:23:18,600 Speaker 1: that's really gonna do that or is it gonna be 427 00:23:18,640 --> 00:23:21,919 Speaker 1: maybe a public private partnership. Um. They've been talks at 428 00:23:22,000 --> 00:23:23,879 Speaker 1: least with the mayor's new plan of doing a public 429 00:23:23,960 --> 00:23:26,160 Speaker 1: private partnership and so I think that's a very real 430 00:23:26,200 --> 00:23:29,000 Speaker 1: possibility as well. Um. And they've just talked about like 431 00:23:29,080 --> 00:23:31,840 Speaker 1: inklings and ideas, but it doesn't seem like anything is 432 00:23:32,240 --> 00:23:35,280 Speaker 1: super concrete. Just yeah, UM, so interested to see what 433 00:23:35,520 --> 00:23:38,280 Speaker 1: kind of comes out of those plans and ideas. Is 434 00:23:38,320 --> 00:23:41,800 Speaker 1: there a connection with the crime level It seems kind 435 00:23:41,800 --> 00:23:43,520 Speaker 1: of silly to worry about crime if you're a kid 436 00:23:43,520 --> 00:23:45,720 Speaker 1: who grew up in their seventies, right, because there was 437 00:23:45,800 --> 00:23:48,680 Speaker 1: real crime back then relative to this. But this is 438 00:23:48,800 --> 00:23:51,919 Speaker 1: much worse than the kind of Giuliani Bloomberg Eras you know, 439 00:23:52,119 --> 00:23:58,280 Speaker 1: we see also a huge amount of homelessness, drug use, um, theft. 440 00:23:58,960 --> 00:24:02,040 Speaker 1: Is that is that a problem that's causing some of 441 00:24:02,040 --> 00:24:06,240 Speaker 1: this unemployment or is the unemployment problem that's causing that. 442 00:24:06,240 --> 00:24:08,560 Speaker 1: That's a great question, and I I think that there 443 00:24:08,680 --> 00:24:10,560 Speaker 1: is some aspect that we looked at in terms of 444 00:24:10,600 --> 00:24:14,600 Speaker 1: people leaving Manhattan. Um, it doesn't seem to be a 445 00:24:14,680 --> 00:24:17,399 Speaker 1: mass accidus by any means, but it seems like that 446 00:24:17,480 --> 00:24:19,880 Speaker 1: could be people starting to trickle out of the city, 447 00:24:19,920 --> 00:24:23,560 Speaker 1: whether it's due to high rent or or crime. And 448 00:24:23,840 --> 00:24:27,480 Speaker 1: um that being such a center of the economic hub 449 00:24:27,520 --> 00:24:30,120 Speaker 1: for the entire city, UM could have a big impact. 450 00:24:30,600 --> 00:24:32,800 Speaker 1: All Right, Alicia, thank you so much for joining us here. 451 00:24:32,840 --> 00:24:36,880 Speaker 1: Alicia didya. She's a reporter for a Bloomberg's Top Live team, 452 00:24:37,000 --> 00:24:39,880 Speaker 1: joining us here on a Bloomberg Interactive a broker studio. 453 00:24:41,800 --> 00:24:44,879 Speaker 1: Thanks for listening to the Bloomberg Markets podcast. You can 454 00:24:44,920 --> 00:24:48,720 Speaker 1: subscribe and listen to interviews with Apple Podcasts or whatever 455 00:24:48,800 --> 00:24:52,439 Speaker 1: podcast platform you prefer. I'm Matt Miller. I'm on Twitter 456 00:24:52,720 --> 00:24:56,719 Speaker 1: at Matt Miller. On False Sweeney, I'm on Twitter at 457 00:24:56,760 --> 00:24:59,600 Speaker 1: pt Sweeney. Before the podcast, you can always catch us 458 00:24:59,600 --> 00:25:03,119 Speaker 1: worldwide at Bloomberg Radio m