1 00:00:00,040 --> 00:00:13,760 Speaker 1: Bloomberg Audio Studios, podcasts, radio news. This is the Bloomberg 2 00:00:13,800 --> 00:00:17,880 Speaker 1: Surveillance Podcast. Catch us live weekdays at seven am Eastern 3 00:00:18,200 --> 00:00:21,960 Speaker 1: on Apple CarPlay or Android Auto with the Bloomberg Business App. 4 00:00:22,320 --> 00:00:25,640 Speaker 1: Listen on demand wherever you get your podcasts, or watch 5 00:00:25,760 --> 00:00:27,600 Speaker 1: us live on YouTube solver. 6 00:00:28,000 --> 00:00:30,280 Speaker 2: You know, our guests are smarter than we are. Yeah, 7 00:00:30,400 --> 00:00:34,280 Speaker 2: it's ninety eight degrees high in Paris today, which is 8 00:00:34,320 --> 00:00:36,959 Speaker 2: not quite like Phoenix, where it's one hundred and eight 9 00:00:37,040 --> 00:00:41,279 Speaker 2: degrees to drive Hi today Lake Tahoe, which is where 10 00:00:41,360 --> 00:00:45,879 Speaker 2: Nancy Tangler has Lake Tahoe's fifty five degrees. 11 00:00:46,040 --> 00:00:47,919 Speaker 3: She's got it all figured out, like. 12 00:00:48,040 --> 00:00:50,839 Speaker 4: She's got the heat on. She's smarter than we are. 13 00:00:50,880 --> 00:00:53,600 Speaker 2: Hero, Nancy Tangler, thank you so much for joining us 14 00:00:53,600 --> 00:00:59,400 Speaker 2: today with Laffert Tangler Investments. How do you approach your 15 00:00:59,440 --> 00:01:05,200 Speaker 2: port given the in June thirty and earnings and revenue 16 00:01:05,240 --> 00:01:07,920 Speaker 2: season beginning July fourteenth. 17 00:01:08,920 --> 00:01:13,960 Speaker 5: Yeah, Good morning Tom, Good morning Paul. Well, it's always tricky, 18 00:01:14,080 --> 00:01:17,040 Speaker 5: isn't it. I mean, we have had a very good year, 19 00:01:17,240 --> 00:01:20,760 Speaker 5: so you know, we're well ahead of the benchmarks, and 20 00:01:20,800 --> 00:01:24,760 Speaker 5: that's because we rotated early out of some of trimming 21 00:01:24,880 --> 00:01:27,120 Speaker 5: back some of the tech names that we're still overweight 22 00:01:27,200 --> 00:01:30,640 Speaker 5: technology in adding to some of the infrastructure names, and 23 00:01:30,680 --> 00:01:36,000 Speaker 5: then across sectors, what we're seeing is that AI productivity 24 00:01:36,120 --> 00:01:40,480 Speaker 5: really is impacting margins and impacting cost savings and growth 25 00:01:40,800 --> 00:01:45,720 Speaker 5: across the economic sectors. So we are selectively adding and 26 00:01:45,800 --> 00:01:49,200 Speaker 5: this weakness what we call the summer so swoon in 27 00:01:49,320 --> 00:01:52,440 Speaker 5: technology is likely a time when we'll be adding. 28 00:01:52,160 --> 00:01:52,880 Speaker 6: To some names. 29 00:01:54,280 --> 00:01:56,240 Speaker 3: In your notes, which are just great, Nancy, thank you. 30 00:01:56,240 --> 00:02:00,000 Speaker 3: You've got some commentary from the CEO of Uber who says, 31 00:02:00,120 --> 00:02:02,720 Speaker 3: Dy five percent of our engineers now use AI coding 32 00:02:02,760 --> 00:02:06,200 Speaker 3: tools monthly, and more than ten percent of code is 33 00:02:06,280 --> 00:02:11,760 Speaker 3: now written autonomously by AI coding agents. Boy, to try 34 00:02:11,800 --> 00:02:14,160 Speaker 3: to figure out how to invest in AI, it's almost 35 00:02:14,200 --> 00:02:19,760 Speaker 3: like everywhere you look, AI is impacting this economy. How 36 00:02:19,760 --> 00:02:23,480 Speaker 3: do you think about trying to get full exposure, proper 37 00:02:23,520 --> 00:02:24,799 Speaker 3: exposure to AI. 38 00:02:26,360 --> 00:02:28,720 Speaker 5: Well, you know, our investing theme, Paul, has been old 39 00:02:28,720 --> 00:02:32,320 Speaker 5: economy companies that have pivoted to the new technologies. Our 40 00:02:32,360 --> 00:02:35,440 Speaker 5: original poster childhood was Walmart. But you can see it 41 00:02:35,480 --> 00:02:38,080 Speaker 5: in the notes that it's across sectors. I mean a 42 00:02:38,120 --> 00:02:41,360 Speaker 5: company like EL three Harris saying our employees are producing 43 00:02:41,360 --> 00:02:43,679 Speaker 5: twenty five percent more revenue than they were a few 44 00:02:43,720 --> 00:02:44,440 Speaker 5: years ago. 45 00:02:44,639 --> 00:02:46,320 Speaker 4: Thanks to the impact of AI. 46 00:02:46,800 --> 00:02:50,119 Speaker 5: Is important to understand as an investor, so we sit 47 00:02:50,200 --> 00:02:52,160 Speaker 5: on all the calls. We do this for our clients. 48 00:02:52,240 --> 00:02:56,120 Speaker 5: Not everyone can has the luxury of listening and talking 49 00:02:56,120 --> 00:02:59,600 Speaker 5: to management on a regular basis, but it's important to 50 00:02:59,639 --> 00:03:02,320 Speaker 5: look at at who the leaders are at these companies 51 00:03:02,320 --> 00:03:05,760 Speaker 5: that are pivoting in the right direction. So jaxtapose Walmart 52 00:03:05,800 --> 00:03:09,680 Speaker 5: against Target and you'll see really dramatic price performance over 53 00:03:09,680 --> 00:03:12,800 Speaker 5: the last five years because Target got behind in walmart 54 00:03:12,880 --> 00:03:17,200 Speaker 5: S date ahead. So it's a bit of an art form, 55 00:03:17,520 --> 00:03:20,280 Speaker 5: but effectively that is what we're looking for in our 56 00:03:20,280 --> 00:03:23,320 Speaker 5: earning's called notes, and we're using AI to identify the themes. 57 00:03:24,000 --> 00:03:26,720 Speaker 3: Nancy, Tom and I we talk a lot about Microsoft 58 00:03:27,160 --> 00:03:29,680 Speaker 3: recently because we see the stockdown, you know, twenty five percent, 59 00:03:29,680 --> 00:03:31,800 Speaker 3: and you think about we all grew up with Microsoft 60 00:03:31,840 --> 00:03:34,760 Speaker 3: as being obviously just one of the best in class 61 00:03:34,760 --> 00:03:39,280 Speaker 3: companies globally with just tremendous financial results here, but they 62 00:03:39,320 --> 00:03:42,160 Speaker 3: seem to be not participating in this AI story. How 63 00:03:42,160 --> 00:03:44,760 Speaker 3: do you think about some of these big software companies 64 00:03:45,000 --> 00:03:46,119 Speaker 3: like a Microsoft. 65 00:03:46,840 --> 00:03:48,400 Speaker 5: You know, I was looking at it this morning, and 66 00:03:48,840 --> 00:03:51,480 Speaker 5: that is the right question to be asking. We may 67 00:03:51,480 --> 00:03:54,240 Speaker 5: be adding to it here soon. We own it across 68 00:03:54,280 --> 00:03:56,880 Speaker 5: all of our large cap strategies. It's one of our 69 00:03:56,880 --> 00:04:00,160 Speaker 5: twelve best ideas. It hasn't been the best idea, which 70 00:04:00,200 --> 00:04:02,960 Speaker 5: is why you have a portfolio. But I think the 71 00:04:03,000 --> 00:04:10,800 Speaker 5: company will ultimately monetize AI and grow Azure in a 72 00:04:10,880 --> 00:04:14,720 Speaker 5: really disc London meaningful manner. But it is tied to 73 00:04:14,760 --> 00:04:18,240 Speaker 5: open AI, and I think today's announcement is not a 74 00:04:18,240 --> 00:04:20,719 Speaker 5: surprise to those of us who have been watching the company. 75 00:04:21,040 --> 00:04:23,320 Speaker 5: I don't think the company's ready to go public. I 76 00:04:23,360 --> 00:04:26,160 Speaker 5: personally think they need a new leader. No one's called 77 00:04:26,200 --> 00:04:28,120 Speaker 5: me to ask that. You know what I think about 78 00:04:28,400 --> 00:04:31,080 Speaker 5: Sam Altman, But I think the company is fraught and 79 00:04:31,160 --> 00:04:33,240 Speaker 5: it is impacting Microsoft. 80 00:04:33,680 --> 00:04:36,200 Speaker 2: Does Microsoft have to be more Apple like? Do they 81 00:04:36,240 --> 00:04:39,440 Speaker 2: need to get out and be more aggressive about identifying 82 00:04:39,640 --> 00:04:42,920 Speaker 2: profit and the allocation of profit to shareholders? 83 00:04:44,160 --> 00:04:45,400 Speaker 4: Yeah? I do think that, Tom. 84 00:04:45,440 --> 00:04:47,599 Speaker 5: I think they need to be better at communicating it 85 00:04:48,279 --> 00:04:51,760 Speaker 5: because what shareholders are hearing as well, we're supply constrained 86 00:04:51,920 --> 00:04:57,039 Speaker 5: on infrastructure Azure and we can't spend enough, and that's 87 00:04:57,040 --> 00:04:59,279 Speaker 5: not what investors want to hear. 88 00:04:59,560 --> 00:05:01,240 Speaker 4: Okay, I get to cut to the chase. 89 00:05:01,360 --> 00:05:04,760 Speaker 2: I mean, is there anybody in Lake Tahoe, Nevada who's 90 00:05:04,800 --> 00:05:05,680 Speaker 2: not a billionaire? 91 00:05:05,760 --> 00:05:09,480 Speaker 4: Nancy? Are you just like something you're surrounded by? I mean, 92 00:05:09,600 --> 00:05:10,600 Speaker 4: is it out of control? 93 00:05:10,720 --> 00:05:13,160 Speaker 2: Is it like if you go down to Heidi's pancake 94 00:05:13,200 --> 00:05:16,880 Speaker 2: house or Ernie's coffee shop? Is it like a whole 95 00:05:16,880 --> 00:05:20,320 Speaker 2: new Lake Tyo after all because of the tax strategies 96 00:05:20,320 --> 00:05:21,760 Speaker 2: of the Western States. 97 00:05:22,640 --> 00:05:25,520 Speaker 5: Yeah, I'm an inclined village. It's a thousand year, one 98 00:05:25,560 --> 00:05:29,800 Speaker 5: thousand percent right. Lakefront homes are going from anywhere between 99 00:05:29,800 --> 00:05:32,839 Speaker 5: fifty to one hundred and fifty million dollars just a 100 00:05:32,839 --> 00:05:35,240 Speaker 5: few years ago of pre COVID, let's say it was 101 00:05:35,279 --> 00:05:38,360 Speaker 5: three to five million. I'm one street off the lake. 102 00:05:38,440 --> 00:05:42,560 Speaker 5: But world's apart. Elon Musk's cousin is building an underwater 103 00:05:43,080 --> 00:05:46,760 Speaker 5: hockey pool and dorms because he has to fly in 104 00:05:46,880 --> 00:05:49,760 Speaker 5: the players because nobody in the US plays it. So 105 00:05:50,279 --> 00:05:55,160 Speaker 5: it's it is nuts. They're changing. Larry Ellison bought the Hyatt. 106 00:05:55,440 --> 00:05:58,720 Speaker 5: He turned the lone Eagle Grill into a nobu. I 107 00:05:58,760 --> 00:06:01,760 Speaker 5: think that's where we're going, And yeah, it's okay. 108 00:06:01,800 --> 00:06:03,320 Speaker 2: So it's going to be It's going to be like 109 00:06:03,440 --> 00:06:07,440 Speaker 2: Jackson Hole where the normal non billionaires like Nancy. 110 00:06:07,200 --> 00:06:10,400 Speaker 4: Tangler get pushed out and you're gonna have to drive 111 00:06:10,440 --> 00:06:11,640 Speaker 4: in from Las Vegas. 112 00:06:13,680 --> 00:06:16,480 Speaker 5: Well, I own my home, so I'm going to I'm 113 00:06:16,880 --> 00:06:21,360 Speaker 5: spikee not remodeling it because it's a quaint old Taho home. 114 00:06:21,480 --> 00:06:22,679 Speaker 4: So we'll see how that goes. 115 00:06:23,120 --> 00:06:25,440 Speaker 3: I'm Telly, tell me it's that money leaving California to 116 00:06:25,480 --> 00:06:28,400 Speaker 3: go right across oh yeah state line to this inclined village, Nevada. 117 00:06:28,680 --> 00:06:30,440 Speaker 4: How do you get out of Lake Tow? Do you 118 00:06:30,480 --> 00:06:33,880 Speaker 4: fly to Phoenix to come visit us at our world headquarters? 119 00:06:33,920 --> 00:06:34,080 Speaker 2: You go? 120 00:06:34,200 --> 00:06:37,560 Speaker 4: You know, are you like nonsense? I mean the billionaire bros. 121 00:06:37,640 --> 00:06:40,839 Speaker 4: I'm telling you maybe she's all she's on art Laughers 122 00:06:40,880 --> 00:06:43,400 Speaker 4: Gulf Stream. Yeah, okay, that's how do you get here? 123 00:06:43,800 --> 00:06:47,240 Speaker 4: How do you travel out of Lake toh oh Reno? 124 00:06:47,800 --> 00:06:50,880 Speaker 4: You drive to Reno. Nothing's convenient, but that that used 125 00:06:50,880 --> 00:06:51,839 Speaker 4: to be part of the charm. 126 00:06:52,320 --> 00:06:55,040 Speaker 5: Now you know, they're they're gussying up the place and 127 00:06:55,120 --> 00:06:57,600 Speaker 5: I'm less comfortable than I used to be walking around 128 00:06:57,640 --> 00:06:58,480 Speaker 5: in hiking clothes. 129 00:06:58,800 --> 00:06:59,720 Speaker 4: Nancy, thank you so much. 130 00:06:59,760 --> 00:07:03,880 Speaker 2: Dance Tangler from Lake Tahoe Today with Laffer Tangler, and 131 00:07:03,920 --> 00:07:06,040 Speaker 2: I just can't say enough about as you mentioned, the 132 00:07:06,120 --> 00:07:09,960 Speaker 2: quality of our research note is just outstanding. Stay with 133 00:07:10,040 --> 00:07:13,720 Speaker 2: us more from Bloomberg Surveillance coming up after this. 134 00:07:20,960 --> 00:07:24,520 Speaker 1: You're listening to the Bloomberg Surveillance podcast. Catch us Live 135 00:07:24,600 --> 00:07:27,760 Speaker 1: weekday afternoons from seven to ten am Eastern Listen on 136 00:07:27,840 --> 00:07:31,239 Speaker 1: Apple Karplay and Android Auto with the Bloomberg Business app, 137 00:07:31,440 --> 00:07:33,120 Speaker 1: or watch us Live on YouTube. 138 00:07:33,240 --> 00:07:36,080 Speaker 4: Diane Swank has been more than patient. When you're from Chicago. 139 00:07:36,360 --> 00:07:39,520 Speaker 2: Yeah, and it's white Sox cubs, you know you listening. 140 00:07:39,440 --> 00:07:40,920 Speaker 4: She wool. That's a lot of. 141 00:07:40,880 --> 00:07:43,720 Speaker 2: Math, Dan, Thank you so much for waiting as we 142 00:07:44,160 --> 00:07:47,320 Speaker 2: discuss New York City as supports as well. 143 00:07:47,840 --> 00:07:50,720 Speaker 4: There's going to be a sport, Diane, that you're expert in. 144 00:07:51,200 --> 00:07:53,720 Speaker 4: And that's the next and the next after that, and 145 00:07:53,760 --> 00:07:57,840 Speaker 4: the next after that. Chairman Warsh press conference, when does 146 00:07:57,880 --> 00:08:00,960 Speaker 4: he really become chairman? Is a hole. 147 00:08:02,640 --> 00:08:04,400 Speaker 7: That's going to be I think one of the most 148 00:08:04,400 --> 00:08:07,080 Speaker 7: important things that we see is how he handles Jackson 149 00:08:07,160 --> 00:08:10,560 Speaker 7: Hole and what he telegraphs. Obviously he doesn't want to 150 00:08:10,560 --> 00:08:13,160 Speaker 7: do forward guidance, which actually at this point in time, 151 00:08:13,200 --> 00:08:15,680 Speaker 7: I think forward guidance is not the best thing to 152 00:08:15,720 --> 00:08:18,800 Speaker 7: be doing, so I have some sympathy for that, you know, 153 00:08:18,920 --> 00:08:21,080 Speaker 7: forward guidance in a time when you have such high 154 00:08:21,160 --> 00:08:23,960 Speaker 7: levels of uncertainty and we can have so many different 155 00:08:24,040 --> 00:08:26,960 Speaker 7: kinds of pivot in what policy could be I think 156 00:08:27,080 --> 00:08:31,480 Speaker 7: is a it adds to uncertainty rather than clarity. And 157 00:08:31,520 --> 00:08:33,680 Speaker 7: that's what you know, we've been struggling with with the 158 00:08:33,720 --> 00:08:34,320 Speaker 7: FED all year. 159 00:08:35,400 --> 00:08:39,199 Speaker 3: Inflation here, we've got oil continuing to come down here Diane, 160 00:08:39,240 --> 00:08:42,160 Speaker 3: with seemingly some light at the end of the tunnel 161 00:08:42,200 --> 00:08:45,840 Speaker 3: as it relates to a rent. What's your underlying inflation 162 00:08:46,000 --> 00:08:48,240 Speaker 3: call these days? Even with energy coming down. 163 00:08:49,559 --> 00:08:51,640 Speaker 7: So we are really worried about. I'm a little bit 164 00:08:51,679 --> 00:08:53,720 Speaker 7: more on you know, the Austin goals beside of the 165 00:08:53,760 --> 00:08:56,000 Speaker 7: equation of the FED these days. Although he won't use 166 00:08:56,040 --> 00:08:58,600 Speaker 7: the word hawk, he talks about himself as a data dog, 167 00:08:58,720 --> 00:09:02,640 Speaker 7: but it really is important we think that underlying inflation 168 00:09:02,720 --> 00:09:05,400 Speaker 7: and the service sectors remain too high. We know that 169 00:09:05,920 --> 00:09:08,000 Speaker 7: it's been a bit of whack the mole with what's 170 00:09:08,120 --> 00:09:12,400 Speaker 7: pushing service sector inflation, but the hay shaped economy is 171 00:09:12,440 --> 00:09:14,000 Speaker 7: not helping. I mean, try to go to a live 172 00:09:14,040 --> 00:09:17,480 Speaker 7: sporting event or a live concert these days, and it 173 00:09:17,520 --> 00:09:20,880 Speaker 7: really is a luxury, kind of ultra wealthy kind of 174 00:09:20,880 --> 00:09:23,040 Speaker 7: thing you can do now because you can't afford to 175 00:09:23,040 --> 00:09:25,680 Speaker 7: buy some of these tickets. And I think that's important. 176 00:09:25,760 --> 00:09:28,800 Speaker 7: The other issues, of course, aging demographics pushing up costs 177 00:09:28,800 --> 00:09:32,120 Speaker 7: of healthcare. But we also have other issues in the pipeline, 178 00:09:32,120 --> 00:09:35,280 Speaker 7: and that's a sequencing of AI. The costs associated with 179 00:09:35,440 --> 00:09:39,520 Speaker 7: AI are hitting ahead of the productivity being scaled, and 180 00:09:39,559 --> 00:09:42,880 Speaker 7: that's important because that's not ameliorating those costs. In fact, 181 00:09:42,920 --> 00:09:45,480 Speaker 7: we heard some announcements yesterday that we're going to see 182 00:09:45,559 --> 00:09:49,160 Speaker 7: a lot more consumer electronic inflation going forward, and that's 183 00:09:49,200 --> 00:09:52,840 Speaker 7: something that had been deflating for decades. So this is 184 00:09:52,840 --> 00:09:55,400 Speaker 7: a very different situation than what we saw during the 185 00:09:55,440 --> 00:09:56,240 Speaker 7: dot com bubble. 186 00:09:56,440 --> 00:09:59,200 Speaker 2: Dane smiche fabric of all you do out of Michigan 187 00:09:59,800 --> 00:10:02,360 Speaker 2: is the way we do business away from three zip 188 00:10:02,400 --> 00:10:05,880 Speaker 2: codes in Manhattan. I've been asking about our addiction to 189 00:10:06,160 --> 00:10:11,880 Speaker 2: a sprightly stimulus led nominal GDP across America? Are we 190 00:10:11,960 --> 00:10:15,200 Speaker 2: addicted to five percent plus nominal GDP? 191 00:10:17,320 --> 00:10:20,240 Speaker 7: Well, you know, I mean with a nominal GDP with 192 00:10:20,400 --> 00:10:23,480 Speaker 7: inflation accelerating that's not as great what we have seen. 193 00:10:23,520 --> 00:10:26,600 Speaker 7: What I'm worried about is not exactly just the nominal 194 00:10:26,640 --> 00:10:30,120 Speaker 7: pace of GDP, but that it's so concentrated that we 195 00:10:30,200 --> 00:10:33,600 Speaker 7: have so much of GDP going into the AI boom 196 00:10:34,000 --> 00:10:37,240 Speaker 7: and derived from the wealth that it's generated. And that 197 00:10:37,360 --> 00:10:41,520 Speaker 7: is something that's not even gains and in fact, inflation itself, 198 00:10:42,000 --> 00:10:44,320 Speaker 7: it compounds over time, and so the fact that we've 199 00:10:44,320 --> 00:10:47,280 Speaker 7: had five years of it, you now have price levels 200 00:10:47,320 --> 00:10:49,720 Speaker 7: that are too high and out of reach for too many. 201 00:10:50,040 --> 00:10:53,360 Speaker 7: At the same time, that wealth is compounded as well, 202 00:10:53,679 --> 00:10:57,040 Speaker 7: and so those who are the wealthiest, with large stock portfolios, 203 00:10:57,080 --> 00:11:00,319 Speaker 7: they have a significant cushion to be able to orbit 204 00:11:00,360 --> 00:11:03,439 Speaker 7: the shock of inflation. Where inflation hits those who can 205 00:11:03,480 --> 00:11:05,600 Speaker 7: afford it beast the hardest. 206 00:11:05,960 --> 00:11:08,400 Speaker 3: How About on the other side of the FED mandate, 207 00:11:08,640 --> 00:11:11,360 Speaker 3: the labor market. We got a print yesterday that seemed 208 00:11:11,360 --> 00:11:15,280 Speaker 3: to suggest the labor market remains pretty darn resilient out there. 209 00:11:16,520 --> 00:11:18,920 Speaker 7: Labor market has remained resilient, and at the end of 210 00:11:18,960 --> 00:11:20,839 Speaker 7: the day, the Fed the only thing they can do 211 00:11:21,000 --> 00:11:24,360 Speaker 7: is managed those aggregate figures. And I think that's really 212 00:11:24,360 --> 00:11:26,959 Speaker 7: important because what we're seeing now is even as the 213 00:11:27,040 --> 00:11:30,560 Speaker 7: labor market is relatively resilient, and we've been running at 214 00:11:30,600 --> 00:11:33,280 Speaker 7: a four point three percent unemployment rate, which the FED 215 00:11:33,559 --> 00:11:38,080 Speaker 7: considers pretty much full employment under the hood. Under employments 216 00:11:38,360 --> 00:11:41,080 Speaker 7: is much higher than it was pre pandemic, and the 217 00:11:41,160 --> 00:11:44,400 Speaker 7: duration of unemployment has risen while quit rates have fallen, 218 00:11:44,440 --> 00:11:48,920 Speaker 7: which sort of reflects an uncertainty that workers have out there. 219 00:11:49,040 --> 00:11:52,640 Speaker 7: They're not job hopping to a better and more productive firm, 220 00:11:53,080 --> 00:11:56,079 Speaker 7: and that's important as well. But at this point in time, 221 00:11:56,480 --> 00:11:59,200 Speaker 7: the FED, you can see their pivot and their focus 222 00:11:59,240 --> 00:12:02,320 Speaker 7: has gone from worrying about the labor markets had the 223 00:12:02,360 --> 00:12:04,960 Speaker 7: equation to worrying about inflation, which is I think what 224 00:12:05,000 --> 00:12:07,559 Speaker 7: they have to worry about right now because over time, 225 00:12:08,200 --> 00:12:10,640 Speaker 7: increased costs affect the labor market as well. 226 00:12:11,160 --> 00:12:13,240 Speaker 2: Dan, thank you so much, thank you, thank you, thank you. 227 00:12:13,320 --> 00:12:16,520 Speaker 2: Diane swank with us this morning. Year just huge news. 228 00:12:16,600 --> 00:12:19,080 Speaker 4: I thought this was like a sleeper snooze festival today. 229 00:12:19,320 --> 00:12:21,960 Speaker 4: Now what happened to that? Yeah, exactly, and I'll have 230 00:12:22,000 --> 00:12:23,040 Speaker 4: to see on that as well. 231 00:12:23,120 --> 00:12:26,240 Speaker 2: Diane Swanker is with KPMG, her chief economists. 232 00:12:26,559 --> 00:12:30,719 Speaker 4: Stay with us. More from Bloomberg Surveillance coming up after this. 233 00:12:37,960 --> 00:12:41,560 Speaker 1: You're listening to the Bloomberg Surveillance Podcast. Catch us live 234 00:12:41,640 --> 00:12:44,760 Speaker 1: weekday afternoons from seven to ten am Eastern Listen on 235 00:12:44,880 --> 00:12:48,520 Speaker 1: Applecarplay and Android Otto with the Bloomberg Business app, or 236 00:12:48,679 --> 00:12:50,160 Speaker 1: watch us live on YouTube. 237 00:12:50,240 --> 00:12:52,840 Speaker 2: It's a good time to speak to Christen at Bitterly. 238 00:12:53,800 --> 00:12:57,680 Speaker 2: I love this Wealth at Work City a global markets. 239 00:12:57,679 --> 00:12:58,800 Speaker 4: What does Wealth at Work? 240 00:12:59,200 --> 00:13:01,520 Speaker 8: So, what it is is we actually design and to 241 00:13:01,800 --> 00:13:06,480 Speaker 8: end customized solutions for firms and their employees. So it 242 00:13:06,520 --> 00:13:08,720 Speaker 8: was born out of the law from Group. So we 243 00:13:08,760 --> 00:13:12,080 Speaker 8: work with lawyers, entry level associates through the most senior partners. 244 00:13:12,400 --> 00:13:16,440 Speaker 8: We also cover the firms themselves. We cover asset managers, 245 00:13:16,480 --> 00:13:20,760 Speaker 8: professional services, pre ipo post ipo companies, and actually our 246 00:13:20,760 --> 00:13:23,080 Speaker 8: own employees at City and so the ideas you know, 247 00:13:23,160 --> 00:13:26,800 Speaker 8: the industry really deep. You serve the entirety of their 248 00:13:26,800 --> 00:13:29,920 Speaker 8: employee base and then you're able to anticipate their needs 249 00:13:29,960 --> 00:13:32,440 Speaker 8: before they even though they have are they have they. 250 00:13:32,360 --> 00:13:36,720 Speaker 2: Learned from idiots like me to save sooner, quicker and bigger. 251 00:13:36,880 --> 00:13:37,480 Speaker 6: That's our goal. 252 00:13:37,559 --> 00:13:39,760 Speaker 8: So we lead with planning and we want to make 253 00:13:39,800 --> 00:13:43,320 Speaker 8: sure that people invest and they invest early on and 254 00:13:43,400 --> 00:13:45,160 Speaker 8: that they save. But Tom, I would say one of 255 00:13:45,200 --> 00:13:47,440 Speaker 8: the things that we see most commonly is that a 256 00:13:47,440 --> 00:13:50,200 Speaker 8: lot of people they may save, but they don't invest. 257 00:13:50,440 --> 00:13:53,360 Speaker 8: So one of the very common fact patterns, and this 258 00:13:53,480 --> 00:13:55,439 Speaker 8: is across when you think of all of those industries, 259 00:13:55,760 --> 00:13:58,319 Speaker 8: the legal industry, the asset management industry. 260 00:13:58,600 --> 00:14:00,680 Speaker 6: You know, even at city you'll see. 261 00:14:00,440 --> 00:14:03,160 Speaker 8: People who are making good salaries and they have saved, 262 00:14:03,200 --> 00:14:05,160 Speaker 8: but they have all of their money in a savings account. 263 00:14:05,440 --> 00:14:08,680 Speaker 8: And then you think of like with inflationary pressures, like, yeah, 264 00:14:08,679 --> 00:14:10,520 Speaker 8: so you're saving money, but you also have to have 265 00:14:10,559 --> 00:14:11,720 Speaker 8: that money work for you as well. 266 00:14:11,760 --> 00:14:14,760 Speaker 6: So we lead with planning. We help people help. 267 00:14:14,600 --> 00:14:17,160 Speaker 8: Themselves, and we really try to make sure to free 268 00:14:17,200 --> 00:14:18,959 Speaker 8: up their headspace so that way they can focus on 269 00:14:19,000 --> 00:14:19,840 Speaker 8: their families. 270 00:14:20,600 --> 00:14:26,760 Speaker 6: It's true, it's true. Free up your head space, so 271 00:14:26,800 --> 00:14:31,040 Speaker 6: you're focusing on your family. Let's hear it, after. 272 00:14:30,840 --> 00:14:33,320 Speaker 4: Thought, free up your head space, empty. 273 00:14:33,000 --> 00:14:37,440 Speaker 8: The dishwasher, watch the World Cup, maybe toot a little 274 00:14:37,440 --> 00:14:37,800 Speaker 8: bit of that. 275 00:14:38,160 --> 00:14:38,880 Speaker 4: How are lawyers? 276 00:14:39,160 --> 00:14:41,480 Speaker 3: It seems like the law business is a good business. 277 00:14:41,480 --> 00:14:42,440 Speaker 6: It's a great business. 278 00:14:42,600 --> 00:14:43,360 Speaker 4: Yeah, how have of the. 279 00:14:43,280 --> 00:14:45,720 Speaker 3: Trend's been recently? Let's when you go into a Paul 280 00:14:45,720 --> 00:14:49,560 Speaker 3: Weiser one of these other big, big firms, everybody's I 281 00:14:49,560 --> 00:14:50,360 Speaker 3: think doing pretty well. 282 00:14:50,360 --> 00:14:51,160 Speaker 6: They're doing really well. 283 00:14:51,200 --> 00:14:52,840 Speaker 8: So like when you look at the legal industry, and 284 00:14:52,920 --> 00:14:56,360 Speaker 8: we have a business called advisory services, and so if 285 00:14:56,360 --> 00:14:58,640 Speaker 8: you think about it, there's no cell side research on 286 00:14:58,840 --> 00:15:02,640 Speaker 8: private partner and so we have a team that basically 287 00:15:02,640 --> 00:15:05,520 Speaker 8: goes out interviews all of the execs and managing partners. 288 00:15:05,640 --> 00:15:08,520 Speaker 8: The kind of C suite ad law firms understands top 289 00:15:08,560 --> 00:15:12,000 Speaker 8: line revenue trends, billing trends, they understand their expense base, 290 00:15:12,040 --> 00:15:13,280 Speaker 8: how they're investing in talent. 291 00:15:13,760 --> 00:15:14,240 Speaker 6: So what I. 292 00:15:14,200 --> 00:15:16,360 Speaker 8: Would say is like when you look at the overall 293 00:15:16,440 --> 00:15:20,080 Speaker 8: kind of like top line revenue growth, definitely they're very strong. 294 00:15:20,400 --> 00:15:22,560 Speaker 6: When you look at expenses, you. 295 00:15:22,520 --> 00:15:24,640 Speaker 8: Know, if you're a partnership, you have the same type 296 00:15:24,640 --> 00:15:27,360 Speaker 8: of expenses that we're dealing with now. Is like City Group, 297 00:15:27,440 --> 00:15:29,480 Speaker 8: Like you're thinking, how am I deploying AI? How am 298 00:15:29,520 --> 00:15:32,080 Speaker 8: I investing in talent? So you're starting to see like 299 00:15:32,160 --> 00:15:34,120 Speaker 8: that start to tick up. And so I would say 300 00:15:34,120 --> 00:15:35,920 Speaker 8: that's like a major trend to watch just. 301 00:15:35,880 --> 00:15:40,680 Speaker 3: AI helping the you know, kind of the junior associate 302 00:15:40,800 --> 00:15:42,600 Speaker 3: kind of thing get stuff done, because I would think 303 00:15:42,600 --> 00:15:43,600 Speaker 3: that would be huge. 304 00:15:43,360 --> 00:15:44,280 Speaker 6: It would help them. 305 00:15:44,320 --> 00:15:46,240 Speaker 8: But then it's also a risk in terms of if 306 00:15:46,280 --> 00:15:48,680 Speaker 8: you're in law school right now. So, like one of 307 00:15:48,720 --> 00:15:50,880 Speaker 8: the things that is very commonly said is instead of 308 00:15:50,920 --> 00:15:54,000 Speaker 8: having that traditional pyramid structure, it's now starting to look 309 00:15:54,040 --> 00:15:57,960 Speaker 8: more like a cylinder in terms of like attracting associate 310 00:15:58,000 --> 00:16:00,720 Speaker 8: talent and junior talent because the a I like if 311 00:16:00,760 --> 00:16:03,480 Speaker 8: a lot of junior talent was doing summarization, and then 312 00:16:03,520 --> 00:16:06,080 Speaker 8: a lot of corporates are pushing back and saying, wait, 313 00:16:06,120 --> 00:16:08,520 Speaker 8: if you have the first year associate on this and 314 00:16:08,600 --> 00:16:10,720 Speaker 8: AI can do it, you're not charging me the same amount. 315 00:16:10,880 --> 00:16:14,240 Speaker 2: I had a heavyweight bond person say to me the 316 00:16:14,360 --> 00:16:16,840 Speaker 2: other day. When I hold cord up in the food 317 00:16:16,880 --> 00:16:19,880 Speaker 2: court at ten fifteen on the couch, everybody knows I'm 318 00:16:19,880 --> 00:16:22,560 Speaker 2: going to plant myself there. And I talked to this 319 00:16:22,720 --> 00:16:26,960 Speaker 2: heavyweight bond person and they said they were the victim 320 00:16:27,040 --> 00:16:30,400 Speaker 2: of their own work, and that their work was to 321 00:16:30,440 --> 00:16:34,800 Speaker 2: be cautious and they missed the equity move. There's a 322 00:16:34,800 --> 00:16:38,320 Speaker 2: whole cadre of professionals who are too smart for their 323 00:16:38,360 --> 00:16:38,840 Speaker 2: own good. 324 00:16:39,160 --> 00:16:42,280 Speaker 8: They are, and if kind of going back to when 325 00:16:42,320 --> 00:16:44,400 Speaker 8: you think of and I hate to bring everything back 326 00:16:44,440 --> 00:16:47,640 Speaker 8: to planning, but one of the major mistakes people have 327 00:16:47,960 --> 00:16:50,680 Speaker 8: is that they have a long term plan, but then 328 00:16:50,680 --> 00:16:53,720 Speaker 8: they're trading headlines or that they're kind of reacting to 329 00:16:53,800 --> 00:16:56,040 Speaker 8: daily movements about what is the FED going to do? 330 00:16:56,080 --> 00:16:58,840 Speaker 8: What is the inflation print? And Tom I couldn't agree more. 331 00:16:58,840 --> 00:17:00,760 Speaker 8: I think sometimes, like your data day, you're so in 332 00:17:00,800 --> 00:17:03,760 Speaker 8: the weeds and markets that sometimes like you read all 333 00:17:03,800 --> 00:17:05,960 Speaker 8: these headlines and you're like, why would I put capital 334 00:17:06,000 --> 00:17:08,639 Speaker 8: to work given all of the potential risks out there? 335 00:17:08,680 --> 00:17:11,880 Speaker 2: So I think it's a huge deal within global wall stream. 336 00:17:11,960 --> 00:17:14,720 Speaker 2: Will people know it too much? I'm dumb as wood. 337 00:17:14,760 --> 00:17:17,840 Speaker 6: So that's all you need. A good financial advisor. 338 00:17:18,920 --> 00:17:19,640 Speaker 4: Kristin Biddley. 339 00:17:19,680 --> 00:17:21,720 Speaker 2: With us as we enjoy ripping up the script, we 340 00:17:21,760 --> 00:17:23,400 Speaker 2: can do that with someone from Notre Dame. 341 00:17:23,800 --> 00:17:25,760 Speaker 4: I mean, you know, think you know, they're they're flexible 342 00:17:25,760 --> 00:17:26,400 Speaker 4: and all that. 343 00:17:27,200 --> 00:17:29,960 Speaker 2: Fifty eight thousand, eight hundred and ninety eight on BIT 344 00:17:30,320 --> 00:17:32,960 Speaker 2: I asked Gary Gensler the other day with immense respect, 345 00:17:33,359 --> 00:17:35,160 Speaker 2: I said, Gary, what do you stay to the person 346 00:17:35,200 --> 00:17:38,720 Speaker 2: that about bitdog at one hundred and ten thousand? How 347 00:17:38,760 --> 00:17:43,479 Speaker 2: are you handling crypto loss? Given wealth at work? It's 348 00:17:43,560 --> 00:17:44,160 Speaker 2: city group. 349 00:17:44,640 --> 00:17:46,520 Speaker 8: So what I would say is like when you actually 350 00:17:46,600 --> 00:17:50,800 Speaker 8: look at like our client's exposure overall, it's it's pretty minimal. 351 00:17:50,920 --> 00:17:54,240 Speaker 8: Jee sweets, It's pretty it's pretty minimal. It's not something 352 00:17:54,280 --> 00:17:56,760 Speaker 8: that we have on an allocation basis within our portfolios. 353 00:17:56,760 --> 00:17:59,960 Speaker 8: I know some other firms do, so we absolutely facil 354 00:18:00,080 --> 00:18:03,280 Speaker 8: te transactions within like the ETF space and brokerage space, 355 00:18:03,560 --> 00:18:05,520 Speaker 8: but I would say, you know that from a like 356 00:18:05,680 --> 00:18:09,920 Speaker 8: acid allocation standpoint, we don't have a significant amount of exposure. 357 00:18:09,920 --> 00:18:12,199 Speaker 6: So it tends not to be like daily dialogue when 358 00:18:12,240 --> 00:18:14,080 Speaker 6: you're seeing this volatility in the market. 359 00:18:13,880 --> 00:18:18,760 Speaker 2: Plug interrupt SpaceX can't find a bid seventy eight. There 360 00:18:18,840 --> 00:18:21,400 Speaker 2: was a quick one forty sixish a couple of days ago. 361 00:18:21,720 --> 00:18:23,960 Speaker 2: I'm going to say quickly, folks, not looking at the 362 00:18:23,960 --> 00:18:27,120 Speaker 2: Bloomberg one forty five handle is not good. 363 00:18:27,160 --> 00:18:28,200 Speaker 4: We're not there yet. 364 00:18:28,119 --> 00:18:30,840 Speaker 3: Now, and this is free trade. The underwriters are out 365 00:18:30,880 --> 00:18:37,040 Speaker 3: of this game right now. Your clients are pretty substantial, 366 00:18:37,119 --> 00:18:38,359 Speaker 3: they've got that, they're pretty their. 367 00:18:38,240 --> 00:18:41,680 Speaker 6: Qualifying high earners yep, savers. Absolutely, So what's. 368 00:18:41,480 --> 00:18:44,440 Speaker 3: The alternative allocation for these folks? I'm sure that's abou 369 00:18:44,520 --> 00:18:46,920 Speaker 3: asking you about aughts and that kind of stuff, because 370 00:18:46,920 --> 00:18:47,639 Speaker 3: are pretty savvy. 371 00:18:47,920 --> 00:18:50,119 Speaker 8: Absolutely so, I think like One of the major major 372 00:18:50,160 --> 00:18:52,560 Speaker 8: themes kind of moving away from from crypto is just 373 00:18:52,800 --> 00:18:54,720 Speaker 8: what is the right asset allocation to be able to 374 00:18:54,720 --> 00:18:57,600 Speaker 8: withstand some of this volatility. So the headlines will always say, 375 00:18:57,680 --> 00:19:00,200 Speaker 8: you know, is the sixty forty the appropriate portfolio? Am 376 00:19:00,200 --> 00:19:03,399 Speaker 8: I getting the diversification and the breakdown and correlation? And 377 00:19:03,440 --> 00:19:05,680 Speaker 8: so what we tend to see is more probably like 378 00:19:05,760 --> 00:19:08,200 Speaker 8: a sixty thirty ten with a lot of investors, where 379 00:19:08,200 --> 00:19:11,800 Speaker 8: cash is still an important part of that portfolio. I 380 00:19:11,800 --> 00:19:15,200 Speaker 8: think the conversation on the cash piece is understanding are 381 00:19:15,240 --> 00:19:18,800 Speaker 8: you intentionally having this as an investment? Is it operating 382 00:19:18,840 --> 00:19:22,160 Speaker 8: cash or strategic cash? But we see that much more commonly, 383 00:19:22,400 --> 00:19:25,520 Speaker 8: and then I would say, like looking to whether it's alternatives, 384 00:19:25,560 --> 00:19:28,719 Speaker 8: private equity for example, or even something like gold. 385 00:19:29,000 --> 00:19:30,560 Speaker 6: Our CIO talks a lot about this. 386 00:19:31,000 --> 00:19:34,160 Speaker 8: We have positions gold positions in our portfolio simply because 387 00:19:34,160 --> 00:19:37,000 Speaker 8: it's a ballast. It's almost like a substitute for the tenure. 388 00:19:37,119 --> 00:19:40,000 Speaker 8: Given the volatility that we've seen in rates that you 389 00:19:40,240 --> 00:19:43,440 Speaker 8: want that type of correlation within your asset allocation? 390 00:19:43,560 --> 00:19:45,800 Speaker 4: Can you come back more often? Which office do you want? 391 00:19:46,040 --> 00:19:48,080 Speaker 8: I'm happy to come back. I'm at three eighty eight. 392 00:19:48,080 --> 00:19:50,160 Speaker 8: I'm in try back up, you will try work. 393 00:19:50,200 --> 00:19:53,400 Speaker 3: I'm in Triback Elevators on Global Wall Street at three eight. 394 00:19:53,480 --> 00:19:54,240 Speaker 6: That is not true. 395 00:19:54,280 --> 00:19:55,600 Speaker 4: It's them, I think. 396 00:19:55,640 --> 00:19:58,080 Speaker 8: So yeah, you know what you guys. I'm fighting you 397 00:19:58,119 --> 00:20:00,880 Speaker 8: down to three eighty eight. You guys can come down 398 00:20:00,880 --> 00:20:01,400 Speaker 8: to Trybacca. 399 00:20:01,400 --> 00:20:02,359 Speaker 6: Would you do that? 400 00:20:03,560 --> 00:20:06,720 Speaker 2: I haven't been below fifty seventh Street, I think. Do 401 00:20:06,760 --> 00:20:08,520 Speaker 2: you know the last time I was in Brooklyn? 402 00:20:09,040 --> 00:20:12,480 Speaker 6: Oh? 403 00:20:12,720 --> 00:20:16,320 Speaker 4: Are you in North Brooklyn? Do you have coffee at 404 00:20:16,560 --> 00:20:17,440 Speaker 4: Cafe Grumpy? 405 00:20:18,160 --> 00:20:20,720 Speaker 6: I don't know what Cafe Grumpy is. I'm going to 406 00:20:20,760 --> 00:20:23,760 Speaker 6: say Parks, not Parslop. I'm a cobble Hill girl. 407 00:20:23,880 --> 00:20:27,640 Speaker 8: Oh okay, sorry, are you visiting Brooklyn? 408 00:20:27,680 --> 00:20:28,199 Speaker 6: Can I get you? 409 00:20:30,160 --> 00:20:30,400 Speaker 9: Least? 410 00:20:31,359 --> 00:20:34,160 Speaker 4: There's a very story reason Bitterly of City Groupe. We'll 411 00:20:34,200 --> 00:20:38,520 Speaker 4: have her on more often, really informative. Stay with us. 412 00:20:38,520 --> 00:20:41,760 Speaker 4: More from Bloomberg Surveillance coming up after this. 413 00:20:49,040 --> 00:20:52,600 Speaker 1: You're listening to the Bloomberg Surveillance podcast. Catch us live 414 00:20:52,680 --> 00:20:56,200 Speaker 1: weekday afternoons from seven to ten am Eastern Listen on Apple, 415 00:20:56,240 --> 00:20:59,560 Speaker 1: Karplay and Android Otto with the Bloomberg Business app, or 416 00:20:59,680 --> 00:21:01,240 Speaker 1: watch it live on YouTube. 417 00:21:01,520 --> 00:21:04,200 Speaker 4: Our Roadex is Robert Schiffman. On credit and debt. 418 00:21:04,240 --> 00:21:07,960 Speaker 2: There's no one close with Kidder Peavity, with Ernstant Young, 419 00:21:08,119 --> 00:21:11,280 Speaker 2: with Donaldson, Lufkin jun at just a few years. 420 00:21:11,280 --> 00:21:13,600 Speaker 4: It shows us the age his maturity. As they say 421 00:21:13,640 --> 00:21:17,159 Speaker 4: around he is definitive on the credit, the debt of 422 00:21:17,280 --> 00:21:22,399 Speaker 4: Meg seven. Robert Schiffman, They're gonna have earnings and revenues. 423 00:21:22,440 --> 00:21:26,239 Speaker 2: There's gonna be a second quarter report. How will the 424 00:21:26,280 --> 00:21:31,119 Speaker 2: second quarter report adapt and adjust all this Capex debate? 425 00:21:32,840 --> 00:21:35,000 Speaker 10: Well, good morning, Chance, I don't know what it says 426 00:21:35,000 --> 00:21:38,400 Speaker 10: about me. That's just about every work pass has gone business. 427 00:21:38,440 --> 00:21:42,320 Speaker 10: So and hope we break that streak. Listen, there's a 428 00:21:42,359 --> 00:21:44,760 Speaker 10: lot of concern this morning. We go through these sort 429 00:21:44,800 --> 00:21:49,040 Speaker 10: of every couple of months that capital is going to 430 00:21:49,160 --> 00:21:52,800 Speaker 10: hold outright ecosystem. 431 00:21:53,200 --> 00:21:54,920 Speaker 4: I just okay, we've. 432 00:21:54,760 --> 00:21:57,720 Speaker 2: Got some audio difficulties here with mister Schiffman. We're going 433 00:21:57,760 --> 00:21:59,919 Speaker 2: to get that fix out. I mean, the guy is 434 00:22:00,119 --> 00:22:03,439 Speaker 2: good at, like, you know, scoping out the Capex cash 435 00:22:03,440 --> 00:22:07,040 Speaker 2: flows of a data center, but we can't hook them 436 00:22:07,119 --> 00:22:09,480 Speaker 2: up audio. No, we're working on it right now. We'll 437 00:22:09,480 --> 00:22:12,439 Speaker 2: get this hooked up in a moment. Here is well 438 00:22:12,560 --> 00:22:14,320 Speaker 2: published moments ago. 439 00:22:14,720 --> 00:22:20,080 Speaker 4: This is really important. Camab Muduwa and Ying Luthra. This 440 00:22:20,160 --> 00:22:24,920 Speaker 4: is really a wow story. Bond traders stunned. Is losses 441 00:22:24,960 --> 00:22:29,600 Speaker 4: on SpaceX's new debt keep growing right, the lead is 442 00:22:29,720 --> 00:22:34,840 Speaker 4: jaw dropping. SpaceX's blockbuster bond sale is weakening and price 443 00:22:35,840 --> 00:22:39,800 Speaker 4: so quickly in the secondary market. The traders say they 444 00:22:39,840 --> 00:22:45,440 Speaker 4: can't recall another recent deal that widened this sharply. And 445 00:22:45,720 --> 00:22:48,040 Speaker 4: you know, I think this is a huge developing story 446 00:22:48,080 --> 00:22:52,000 Speaker 4: for this Friday and into the weekend. Muda and Luthra 447 00:22:52,680 --> 00:22:56,000 Speaker 4: go out to the paper out thirty years and they 448 00:22:56,119 --> 00:22:59,800 Speaker 4: come in as much as point two eight percentage points wider. 449 00:23:00,720 --> 00:23:02,800 Speaker 4: This I don't think's in the zeitgeist right now. 450 00:23:02,920 --> 00:23:03,120 Speaker 9: Now. 451 00:23:03,240 --> 00:23:05,919 Speaker 3: I'm just looking at this reporting here traders saying moves 452 00:23:06,280 --> 00:23:10,400 Speaker 3: suggest fast money accounts tom rather than traditional buydhold investors 453 00:23:10,440 --> 00:23:13,080 Speaker 3: piled into the deal looking to flip it for a 454 00:23:13,200 --> 00:23:13,720 Speaker 3: quick profit. 455 00:23:13,800 --> 00:23:15,119 Speaker 4: We'll have to see, Robert Schiffman. 456 00:23:15,200 --> 00:23:18,879 Speaker 2: We believe continues with us right now with Bloomberg and intelligence. 457 00:23:19,200 --> 00:23:22,399 Speaker 4: Robert, I look at the state of your research on credit. 458 00:23:22,440 --> 00:23:25,719 Speaker 4: What are you going to be writing about into next week? 459 00:23:26,680 --> 00:23:29,720 Speaker 9: Yeah, Riton, I think the theme is the same for me. 460 00:23:30,359 --> 00:23:35,879 Speaker 9: I'm not necessarily seeing or feeling what's being reported out there. Obviously, listen, 461 00:23:35,960 --> 00:23:41,000 Speaker 9: every deal is not necessarily priced to perfect valuations, and 462 00:23:41,359 --> 00:23:45,679 Speaker 9: every equity is not trading to Alton High still, but 463 00:23:45,720 --> 00:23:48,560 Speaker 9: the amount of capital that still is flowing into this 464 00:23:48,640 --> 00:23:52,000 Speaker 9: ecosystem is enormous. I think it's only going to get bigger. 465 00:23:52,240 --> 00:23:54,560 Speaker 9: And all the data points that we're seeing continue to 466 00:23:54,640 --> 00:23:59,159 Speaker 9: suggest that demand is far up stripping supply, and you're 467 00:23:59,200 --> 00:24:02,359 Speaker 9: going to see capital chase that we could debate about 468 00:24:02,440 --> 00:24:06,840 Speaker 9: exactly where SpaceX should trade or what the multiples on 469 00:24:06,880 --> 00:24:09,720 Speaker 9: a hyperscaler should be. But are we going to see 470 00:24:09,840 --> 00:24:13,480 Speaker 9: sort of this flood of capital disappear anytime soon? I 471 00:24:13,520 --> 00:24:15,320 Speaker 9: don't think so. And in fact, I think you're going 472 00:24:15,359 --> 00:24:17,480 Speaker 9: to see much more capital raised over the next twelve 473 00:24:17,520 --> 00:24:19,040 Speaker 9: months than you did over the last twelve. 474 00:24:20,040 --> 00:24:23,399 Speaker 3: So Rob Toms just reporting some of the Bloomberg reporting 475 00:24:23,400 --> 00:24:27,520 Speaker 3: about SpaceX bonds trading a little bit weak here. How 476 00:24:27,760 --> 00:24:32,280 Speaker 3: the other big AI tech bond offerings over the last 477 00:24:32,320 --> 00:24:35,160 Speaker 3: several weeks have they been trading kind of in the aftermarket? 478 00:24:35,960 --> 00:24:39,119 Speaker 9: Yeah, Well, there's sort of two distinct markets when you 479 00:24:39,160 --> 00:24:42,280 Speaker 9: think about AIDET, or maybe three if you want to 480 00:24:42,440 --> 00:24:46,800 Speaker 9: start talking about private debt, But the vast majority of 481 00:24:46,840 --> 00:24:50,080 Speaker 9: debt that's coming is super high quality double A and 482 00:24:50,119 --> 00:24:52,800 Speaker 9: triple A bonds, and they've come at wider levels than 483 00:24:52,960 --> 00:24:56,560 Speaker 9: historical but basically have been trading in line with new 484 00:24:56,560 --> 00:25:01,560 Speaker 9: issue spreads. Investment ry tech bonds are about five seven 485 00:25:01,560 --> 00:25:03,879 Speaker 9: basis points wider than the investment grade Index, which is 486 00:25:03,960 --> 00:25:07,959 Speaker 9: close to historical or at least twenty year tights. Memes 487 00:25:08,000 --> 00:25:12,080 Speaker 9: like SpaceX or Oracle that have a different balance sheets 488 00:25:12,119 --> 00:25:15,520 Speaker 9: that have massive negative free cash flow that some can't 489 00:25:15,560 --> 00:25:19,400 Speaker 9: see ever turning around and see balance sheets just building 490 00:25:19,480 --> 00:25:22,800 Speaker 9: building building that and don't see the end are trading weaker, 491 00:25:24,160 --> 00:25:26,240 Speaker 9: and that's probably with it. That's not going to go away. 492 00:25:26,400 --> 00:25:29,240 Speaker 9: This is a shimmy story. You've got to see results, 493 00:25:29,560 --> 00:25:31,199 Speaker 9: and those results are probably not going to come for 494 00:25:31,240 --> 00:25:33,160 Speaker 9: another eighteen or thirty six months. 495 00:25:33,160 --> 00:25:35,600 Speaker 2: If there's two shiftman buckets, the ones that are going 496 00:25:35,640 --> 00:25:38,280 Speaker 2: to get it done on profit et cetera, and ones 497 00:25:38,320 --> 00:25:42,119 Speaker 2: like Oracle, maybe not which bucket is Facebook meta. 498 00:25:41,960 --> 00:25:44,679 Speaker 9: In Well, I actually think all of these guys are 499 00:25:44,720 --> 00:25:46,880 Speaker 9: going to get it done. I think there's enough demand 500 00:25:47,720 --> 00:25:51,000 Speaker 9: across the high quality and lower quality curve to fund 501 00:25:51,040 --> 00:25:53,320 Speaker 9: all these guys to get them up and running to 502 00:25:53,359 --> 00:25:57,760 Speaker 9: where you're going to see considerable growth for almost everybody, 503 00:25:57,920 --> 00:26:02,080 Speaker 9: not everyone, for almost everybody, but particularly these investment great names. 504 00:26:02,080 --> 00:26:05,720 Speaker 9: And I put Oracle and SpaceX into that bucket, the 505 00:26:05,840 --> 00:26:08,760 Speaker 9: alphabets and metas of the world. Listen, it's almost like 506 00:26:08,840 --> 00:26:11,639 Speaker 9: splitting hairs. Obviously, the core business for a name like 507 00:26:12,200 --> 00:26:15,520 Speaker 9: Alphabet and perhaps the LLM is a lot stronger, and 508 00:26:15,560 --> 00:26:17,840 Speaker 9: that'll make people feel a little bit better. But from 509 00:26:17,960 --> 00:26:21,280 Speaker 9: a credit trading perspective, they're honestly not going to be 510 00:26:21,359 --> 00:26:24,159 Speaker 9: differentiated that month much. I think it's going to be 511 00:26:24,560 --> 00:26:27,119 Speaker 9: more of an equity story than it is a credit story. 512 00:26:28,080 --> 00:26:30,879 Speaker 3: Rob In terms of new issuance, here, we're getting approaching July. 513 00:26:31,040 --> 00:26:31,919 Speaker 9: Here, are we going to. 514 00:26:32,040 --> 00:26:34,800 Speaker 3: See anything else hit the market this summer? Are we 515 00:26:34,800 --> 00:26:36,919 Speaker 3: going to wait till the fall before you see some 516 00:26:36,920 --> 00:26:37,680 Speaker 3: more new issues? 517 00:26:38,240 --> 00:26:40,800 Speaker 9: Well, I do think second half is going to slow down, 518 00:26:40,920 --> 00:26:44,160 Speaker 9: Like even though we can't look at what historically has happened, 519 00:26:44,200 --> 00:26:48,520 Speaker 9: because we're in a historically different environment. The vast majority 520 00:26:48,560 --> 00:26:51,639 Speaker 9: I think of twenty twenty six funding is complete. That 521 00:26:51,680 --> 00:26:54,040 Speaker 9: doesn't mean there's still not going to be big deals 522 00:26:54,640 --> 00:26:56,840 Speaker 9: or you know, there's also some surprises out there. A 523 00:26:56,880 --> 00:26:58,879 Speaker 9: lot of people didn't see an eighty five billion dollars 524 00:26:59,200 --> 00:27:02,399 Speaker 9: Alphabet deal coming. I think that sort of shows how 525 00:27:02,440 --> 00:27:05,280 Speaker 9: much demand there is because how much more money that 526 00:27:05,320 --> 00:27:07,760 Speaker 9: they want to spend. So you'll still see deals pop up. 527 00:27:07,760 --> 00:27:09,760 Speaker 9: I wouldn't be surprised to see a Meta deal. That 528 00:27:09,800 --> 00:27:13,320 Speaker 9: wouldn't be surprised to see a Microsoft deal. Still seeing 529 00:27:13,440 --> 00:27:18,199 Speaker 9: some private data center specific SPVs out there, But I 530 00:27:18,280 --> 00:27:21,639 Speaker 9: do think like this enormous supply that we saw in 531 00:27:21,680 --> 00:27:23,840 Speaker 9: the first half is going to slow down. I think 532 00:27:23,840 --> 00:27:27,760 Speaker 9: that's actually positive for bond technicals and spreads, and I 533 00:27:27,800 --> 00:27:31,080 Speaker 9: think we can actually mild the outperform. When I say we, 534 00:27:31,359 --> 00:27:34,600 Speaker 9: I mean the investment great tech space versus the rest 535 00:27:34,640 --> 00:27:38,160 Speaker 9: of the corporate index through the year end. 536 00:27:39,680 --> 00:27:42,359 Speaker 3: Is there a crowd out phenomenon out there? Rob, I 537 00:27:42,359 --> 00:27:45,080 Speaker 3: mean there's so much tech or so much money has 538 00:27:45,080 --> 00:27:47,080 Speaker 3: gone into some of these tech bond issuinges. 539 00:27:47,240 --> 00:27:48,760 Speaker 4: Is that crowding out some other issuers? 540 00:27:50,280 --> 00:27:52,800 Speaker 9: I don't think so. I mean, listen, this is the 541 00:27:52,840 --> 00:27:55,400 Speaker 9: shining new pat out there, and it's actually being offered 542 00:27:55,480 --> 00:27:59,480 Speaker 9: at better levels than anyone else you'd ever be able 543 00:27:59,480 --> 00:28:02,280 Speaker 9: to buy, So it's attracting a tremendous amount of capital, 544 00:28:02,320 --> 00:28:04,399 Speaker 9: and there's definitely a little bit of fom all out there. 545 00:28:04,760 --> 00:28:06,840 Speaker 9: I think that's you know, I certainly played into the 546 00:28:06,880 --> 00:28:11,520 Speaker 9: SpaceX bond deal. But is there capital available for non 547 00:28:11,600 --> 00:28:15,280 Speaker 9: tech corporates. Yes. The reality though is they just don't 548 00:28:15,280 --> 00:28:18,240 Speaker 9: need as much money. I think. I think if you 549 00:28:18,320 --> 00:28:20,000 Speaker 9: just look at you know, if you talk to no Hebert, 550 00:28:20,480 --> 00:28:22,640 Speaker 9: you know, he will tell you how tight spreads are, 551 00:28:22,640 --> 00:28:25,240 Speaker 9: both in high yield and in ig so if companies 552 00:28:25,280 --> 00:28:28,280 Speaker 9: want to come, they're cash on the sidelines to fund 553 00:28:28,480 --> 00:28:29,600 Speaker 9: a corporate America. 554 00:28:29,760 --> 00:28:31,879 Speaker 2: This has been wonderful, Robert Schiffan, thank you so much, 555 00:28:31,960 --> 00:28:35,200 Speaker 2: and we hugely appreciate the Daily Grind where we get 556 00:28:35,240 --> 00:28:38,560 Speaker 2: the Shiftman love node. You know, like seven fifteen, sure 557 00:28:38,600 --> 00:28:41,960 Speaker 2: everybody else is waking up sliding in at ten. Shiftman's 558 00:28:41,960 --> 00:28:43,120 Speaker 2: given us the note at seven to. 559 00:28:43,120 --> 00:28:45,720 Speaker 4: Fifteen you grow up on the t Yeah. 560 00:28:46,040 --> 00:28:50,880 Speaker 1: This is the Bloomberg Surveillance podcast, available on Apple, Spotify, 561 00:28:51,000 --> 00:28:54,760 Speaker 1: and anywhere else you get your podcasts. Listen live each 562 00:28:54,800 --> 00:28:58,640 Speaker 1: weekday seven to ten am Easter and on Bloomberg dot com, 563 00:28:58,800 --> 00:29:02,600 Speaker 1: the iHeartRadio app tune In, and the Bloomberg Business app. 564 00:29:02,880 --> 00:29:06,000 Speaker 1: You can also Watch US live every weekday on YouTube 565 00:29:06,280 --> 00:29:08,320 Speaker 1: and always on the Bloomberg terminal