1 00:00:02,920 --> 00:00:12,600 Speaker 1: Bloomberg Audio Studios, Podcasts, radio news. This is Bloomberg Intelligence 2 00:00:12,640 --> 00:00:14,360 Speaker 1: with Alex Steinhl and Paul Sweeney. 3 00:00:14,520 --> 00:00:17,720 Speaker 2: The real app performance has been in US corporate high yield. 4 00:00:17,880 --> 00:00:20,200 Speaker 3: Are the companies lean enough? Have they trimmed all the fats? 5 00:00:20,320 --> 00:00:23,959 Speaker 2: The semiconductor business is a really cyclical business. 6 00:00:23,600 --> 00:00:27,200 Speaker 1: Breaking market headlines and corporate news from across the globe. 7 00:00:27,240 --> 00:00:29,880 Speaker 3: Do investors like the M and A that we've seen? 8 00:00:30,080 --> 00:00:31,000 Speaker 2: These are two. 9 00:00:31,040 --> 00:00:33,159 Speaker 4: Big time blue chip companies. 10 00:00:33,320 --> 00:00:36,920 Speaker 3: The window between the peak and cut changing super fast. 11 00:00:37,080 --> 00:00:41,680 Speaker 1: Bloomberg Intelligence with Alex Steinehl and Paul Sweeney on Bloomberg Radio. 12 00:00:43,080 --> 00:00:45,680 Speaker 4: Hey everyone, I'm Alex Steele and I'm Jen Ryan filling 13 00:00:45,680 --> 00:00:46,599 Speaker 4: in for Paul Sweeney. 14 00:00:46,680 --> 00:00:48,320 Speaker 5: On today's Bloomberg Intelligence Show. 15 00:00:48,360 --> 00:00:51,000 Speaker 3: We're going to dig inside the big business stories impacting 16 00:00:51,040 --> 00:00:52,559 Speaker 3: Wall Street and the global markets. 17 00:00:52,680 --> 00:00:55,160 Speaker 4: Each and every week we provide in depth research and 18 00:00:55,240 --> 00:00:57,800 Speaker 4: data on some of the two thousand companies and one 19 00:00:57,880 --> 00:01:00,520 Speaker 4: hundred and thirty industries our analysts cover worldorldwide. 20 00:01:00,560 --> 00:01:02,320 Speaker 3: Today, everyone to take a look at how computer tech 21 00:01:02,320 --> 00:01:04,880 Speaker 3: company Oracle is showing progress and it's been to capture 22 00:01:04,920 --> 00:01:06,319 Speaker 3: more of the competitive market. 23 00:01:06,520 --> 00:01:09,200 Speaker 4: Plus we'll discuss how a physics whiz made a fortune 24 00:01:09,240 --> 00:01:11,040 Speaker 4: betting on nature's catastrophes. 25 00:01:11,120 --> 00:01:12,679 Speaker 5: But first, let's take a look at retail. 26 00:01:12,720 --> 00:01:15,119 Speaker 3: You got Department store of Coals reported same store sales 27 00:01:15,160 --> 00:01:17,200 Speaker 3: that fell four point three percent in the fourth quarter. 28 00:01:17,480 --> 00:01:20,600 Speaker 3: That represents a small improvement over the five point five 29 00:01:20,600 --> 00:01:23,399 Speaker 3: percent decline during the prior quarter. It also shows, though, 30 00:01:23,640 --> 00:01:26,600 Speaker 3: that Coles has struggled to attract shoppers during the holiday 31 00:01:26,600 --> 00:01:27,360 Speaker 3: shopping season. 32 00:01:27,600 --> 00:01:30,000 Speaker 4: For more on this, we were joined by Mary Ross, 33 00:01:30,000 --> 00:01:34,000 Speaker 4: Gilbert Bloomberg Intelligence senior equity analyst covering retail, and Mary 34 00:01:34,000 --> 00:01:36,760 Speaker 4: told us she's still optimistic that Coals can boost growth. 35 00:01:37,240 --> 00:01:40,600 Speaker 6: They do have so Fora and I'm sure that so 36 00:01:40,720 --> 00:01:43,640 Speaker 6: Forora carries the brands that you care about. So so 37 00:01:43,760 --> 00:01:47,840 Speaker 6: Fora has been a key driver for Coals, and that's 38 00:01:47,880 --> 00:01:51,200 Speaker 6: the reason why their sales aren't that bad. You know, 39 00:01:51,200 --> 00:01:53,160 Speaker 6: if you look at the comp sales, they fell one 40 00:01:53,240 --> 00:01:56,480 Speaker 6: percent in the quarter at the stores, So total comp 41 00:01:56,520 --> 00:01:59,560 Speaker 6: sales were down four point three percent orders and consensus 42 00:01:59,560 --> 00:02:04,120 Speaker 6: three percent an estimate, but digital sales were down ten percent. 43 00:02:05,000 --> 00:02:08,600 Speaker 6: And now going forward, after we get beyond the first 44 00:02:08,680 --> 00:02:12,359 Speaker 6: quarter in twenty twenty four, we should see the overall 45 00:02:12,440 --> 00:02:17,040 Speaker 6: comp sales do better. One with this so Fora initiative, 46 00:02:17,400 --> 00:02:21,440 Speaker 6: because the comparable sales for so Fora was up twenty 47 00:02:21,480 --> 00:02:24,560 Speaker 6: five percent in the fourth quarter, so we've been seeing 48 00:02:24,600 --> 00:02:27,839 Speaker 6: double digit increases there, so that will help. But there's 49 00:02:27,840 --> 00:02:30,600 Speaker 6: a number of other initiatives, including the news that they're 50 00:02:30,639 --> 00:02:34,240 Speaker 6: going to be putting Babies or Us shops into about 51 00:02:34,280 --> 00:02:37,640 Speaker 6: two hundred stores by the fall, and that really fills 52 00:02:37,680 --> 00:02:40,640 Speaker 6: a void in the market. I'm sure you're aware that. Well, 53 00:02:40,720 --> 00:02:43,720 Speaker 6: what happened with Bye Bye a Baby and what about 54 00:02:44,080 --> 00:02:46,200 Speaker 6: Member Toys r US that used to be a go 55 00:02:46,240 --> 00:02:49,320 Speaker 6: to place when you were expecting or how you know 56 00:02:49,400 --> 00:02:52,320 Speaker 6: a baby. You could go there, get your strollers, get 57 00:02:52,320 --> 00:02:53,840 Speaker 6: all your products there. 58 00:02:54,200 --> 00:02:57,000 Speaker 4: We talk about what's good in their future. It sounds 59 00:02:57,040 --> 00:02:59,480 Speaker 4: like it's a lot of stuff that is not cold. 60 00:02:59,720 --> 00:03:03,840 Speaker 4: It's so far it's babies are us. What's the issue 61 00:03:04,000 --> 00:03:06,639 Speaker 4: with the fundamental core Coals offering. 62 00:03:07,320 --> 00:03:10,960 Speaker 6: So they're revamping the merchandise because that was part of it, 63 00:03:11,040 --> 00:03:13,880 Speaker 6: is just not having the right assortments. So they're redoing 64 00:03:13,919 --> 00:03:16,960 Speaker 6: shoes and they're going to be bringing in sketchers. They 65 00:03:16,960 --> 00:03:20,400 Speaker 6: already have Nike, they have Audi Doos, and now you're 66 00:03:20,440 --> 00:03:23,359 Speaker 6: also going to see them bring in some youth brands, 67 00:03:23,520 --> 00:03:27,720 Speaker 6: So they're going to bring in Quicksilver, Errol, Postall, Madden 68 00:03:28,280 --> 00:03:31,440 Speaker 6: limited to in Roxy, so those are also going to 69 00:03:31,480 --> 00:03:34,120 Speaker 6: be helping on the apparel side. So with the overall 70 00:03:34,240 --> 00:03:36,920 Speaker 6: revamp that they're doing on apparel, and some of their 71 00:03:36,960 --> 00:03:40,760 Speaker 6: private brands are actually they resonate pretty well, like for 72 00:03:41,000 --> 00:03:44,040 Speaker 6: in Babies, they have Jumping Beans that does really well. 73 00:03:44,640 --> 00:03:47,000 Speaker 6: So it's really a host of a lot of things 74 00:03:47,000 --> 00:03:48,680 Speaker 6: that they've done with the stores. If you go in 75 00:03:48,680 --> 00:03:52,200 Speaker 6: them now, they're a lot brighter. The culture there has 76 00:03:52,320 --> 00:03:55,640 Speaker 6: really been boosted. We've noticed a difference just from a 77 00:03:55,680 --> 00:03:59,560 Speaker 6: year ago on how much the stores have been transformed. 78 00:04:00,080 --> 00:04:00,920 Speaker 6: So that's helping. 79 00:04:01,320 --> 00:04:03,680 Speaker 3: Yeah, that's so interesting. When I went and I was 80 00:04:03,720 --> 00:04:06,320 Speaker 3: looking and you know, kids grow like weeds, right, my 81 00:04:06,400 --> 00:04:08,120 Speaker 3: daughter's ninees. I was looking for pants and I was like, 82 00:04:08,160 --> 00:04:10,240 Speaker 3: oh my god, they have Nike. I was like, genuinely 83 00:04:10,280 --> 00:04:12,920 Speaker 3: like it. I had lots of those moments whilst walking around. 84 00:04:13,400 --> 00:04:14,840 Speaker 4: I'm gonna have to check it out. 85 00:04:15,080 --> 00:04:17,280 Speaker 3: Okay, we're listening all the good stuff here. So why 86 00:04:17,279 --> 00:04:19,599 Speaker 3: did Coles give weaker than expected guides for the full year? 87 00:04:20,160 --> 00:04:22,640 Speaker 6: Part of that is because we had a new ruling 88 00:04:22,680 --> 00:04:26,880 Speaker 6: that came out from the Consumer Financial Bureau saying, Okay, 89 00:04:26,920 --> 00:04:29,080 Speaker 6: we're going to cap late fees on credit cards to 90 00:04:29,120 --> 00:04:32,720 Speaker 6: eight dollars. So that's going to have a negative impact 91 00:04:32,760 --> 00:04:35,719 Speaker 6: for department stores generally because they tend to have the 92 00:04:35,720 --> 00:04:38,520 Speaker 6: biggest exposure, and so Coles was one of them. They 93 00:04:38,600 --> 00:04:43,200 Speaker 6: generate a fair amount of income from their credit card portfolio, 94 00:04:43,520 --> 00:04:46,360 Speaker 6: and so they guided that that income will be down 95 00:04:46,480 --> 00:04:49,440 Speaker 6: mid teams and that's about one hundred and thirty five 96 00:04:49,560 --> 00:04:52,560 Speaker 6: ish million is what we're estimating the impact this year. 97 00:04:52,880 --> 00:04:56,160 Speaker 6: And that's not the full year impact. But they introduced 98 00:04:56,200 --> 00:04:59,480 Speaker 6: a co branded card and in twenty twenty five they 99 00:04:59,480 --> 00:05:01,839 Speaker 6: hope to be able the offset the loss of income 100 00:05:01,880 --> 00:05:03,560 Speaker 6: that you know they'll experience. 101 00:05:04,040 --> 00:05:04,719 Speaker 5: But we'll see. 102 00:05:04,720 --> 00:05:06,600 Speaker 6: But that's one of the reasons why you're going to 103 00:05:06,680 --> 00:05:08,560 Speaker 6: see some pressure on the margin's side. 104 00:05:08,720 --> 00:05:12,000 Speaker 4: What's the consumer favorite these days? I mean, you've listed 105 00:05:12,040 --> 00:05:14,599 Speaker 4: all these interesting brands turning up at Coal's, but is 106 00:05:14,600 --> 00:05:16,520 Speaker 4: that enough to get the consumers through the door, or 107 00:05:16,640 --> 00:05:18,120 Speaker 4: you know, can you tell us a little bit more 108 00:05:18,120 --> 00:05:20,560 Speaker 4: broadly about the retail space. Are there other shops that 109 00:05:20,600 --> 00:05:22,200 Speaker 4: consumers are preferring these days? 110 00:05:22,880 --> 00:05:23,120 Speaker 7: Yeah? 111 00:05:23,160 --> 00:05:25,680 Speaker 6: Well, clearly off price. And when you think about what's 112 00:05:25,720 --> 00:05:28,760 Speaker 6: happening here with Coals, they're buying frequently, which is more 113 00:05:28,760 --> 00:05:31,360 Speaker 6: of an off price strategy there all the buying occurs 114 00:05:31,360 --> 00:05:34,279 Speaker 6: on a weekly basis. Tom Kingsbury, who's the CEO. 115 00:05:35,000 --> 00:05:35,640 Speaker 8: He is the. 116 00:05:35,560 --> 00:05:39,880 Speaker 6: One who turned Burlington Stores into the fast growing off 117 00:05:39,960 --> 00:05:41,560 Speaker 6: price retailer. 118 00:05:41,120 --> 00:05:41,600 Speaker 8: That it is. 119 00:05:42,000 --> 00:05:45,320 Speaker 6: He lends a lot of credibility. So yes, you're seeing 120 00:05:45,320 --> 00:05:48,400 Speaker 6: the consumer that's attracted to Coals, they also shop at 121 00:05:48,400 --> 00:05:51,080 Speaker 6: off price, and off price has been a big winner 122 00:05:51,200 --> 00:05:54,880 Speaker 6: for that value consumer. And then other retailers that are 123 00:05:54,880 --> 00:05:58,839 Speaker 6: doing well are those that are executing and really delivering 124 00:05:58,880 --> 00:06:02,560 Speaker 6: on the merchandise. And I'm speaking to apparel retailers like 125 00:06:02,560 --> 00:06:07,480 Speaker 6: an Abercrombie Urban Outfitters with their anthropology and their free 126 00:06:07,520 --> 00:06:11,400 Speaker 6: people brands. So it's really it's kind of a tale 127 00:06:11,400 --> 00:06:14,880 Speaker 6: of two stories. Those that are executing are delivering on results, 128 00:06:15,440 --> 00:06:18,719 Speaker 6: and here we're in a transition phase at Coal's and 129 00:06:18,760 --> 00:06:20,760 Speaker 6: they're hoping to be able to turn the tide of 130 00:06:20,800 --> 00:06:24,599 Speaker 6: declining sales for this department store operator. And they do 131 00:06:24,680 --> 00:06:28,200 Speaker 6: have one benefit. They're off the mall, not in the mall. 132 00:06:28,520 --> 00:06:31,520 Speaker 6: That makes them different, so it's easier you know, to 133 00:06:31,560 --> 00:06:33,640 Speaker 6: get into the parking lot, get into the store and 134 00:06:33,680 --> 00:06:36,799 Speaker 6: get you know, and get out again. So it's easier access. 135 00:06:37,200 --> 00:06:39,839 Speaker 6: And like you pointed out, they have Amazon returns. It's 136 00:06:39,920 --> 00:06:43,480 Speaker 6: not additive to sales, but it does bring in traffic. True, 137 00:06:43,520 --> 00:06:47,280 Speaker 6: and then more importantly, so Fora has been the biggest driver. 138 00:06:47,520 --> 00:06:50,599 Speaker 4: Our Thanks to Mary Ross Gilbert Bloomberg Intelligence senior equity 139 00:06:50,640 --> 00:06:52,440 Speaker 4: analyst covering retail, we. 140 00:06:52,440 --> 00:06:54,880 Speaker 3: Move now to the airline industry and Boeing. So Boeing 141 00:06:54,920 --> 00:06:57,120 Speaker 3: has been dealing with the growing fallout from an early 142 00:06:57,279 --> 00:07:01,040 Speaker 3: January accident that has since plunged the company into crisis, 143 00:07:01,040 --> 00:07:04,160 Speaker 3: and it's also caused Boeing to reduced aircraft deliveries. 144 00:07:03,880 --> 00:07:04,440 Speaker 5: As a result. 145 00:07:04,600 --> 00:07:07,080 Speaker 4: Southwest Airlines announced this week that it plans to cut 146 00:07:07,120 --> 00:07:10,920 Speaker 4: capacity this year, halt most hiring, and review its spending plants. 147 00:07:11,160 --> 00:07:14,640 Speaker 4: And separately, Boeing said that it's aircraft deliveries trailed rival 148 00:07:14,680 --> 00:07:15,760 Speaker 4: Airbus last month. 149 00:07:15,880 --> 00:07:17,080 Speaker 5: So let's get more on all of this. 150 00:07:17,200 --> 00:07:20,280 Speaker 3: We were joined by George Ferguson, Bloomberg Intelligence Senior Aerospace, 151 00:07:20,360 --> 00:07:23,240 Speaker 3: Defense and Airlines analyst, and we asked him how challenges 152 00:07:23,240 --> 00:07:25,960 Speaker 3: of Boeing will impact the US airline market going forward. 153 00:07:26,280 --> 00:07:29,320 Speaker 9: I think that, you know, the Boeing challenges will provide 154 00:07:29,400 --> 00:07:32,400 Speaker 9: a little bit of firmness to the marketplace. But I 155 00:07:32,440 --> 00:07:34,840 Speaker 9: still see, I think a US airline market that looks 156 00:07:34,840 --> 00:07:38,280 Speaker 9: like it has plenty of capacity in it, and I 157 00:07:38,360 --> 00:07:42,920 Speaker 9: still think fares are flatish to maybe going down for 158 00:07:43,000 --> 00:07:46,600 Speaker 9: the year unless Boeing really curtails their deliveries for the year. 159 00:07:47,160 --> 00:07:50,160 Speaker 4: Yeah, it's interesting because if I read this issue about 160 00:07:50,200 --> 00:07:53,000 Speaker 4: Boeing and I read this cut in capacity, but my 161 00:07:53,080 --> 00:07:54,840 Speaker 4: first thought is going to be that that means higher 162 00:07:54,840 --> 00:07:58,280 Speaker 4: prices for consumers. So what accounts for the difference there? 163 00:07:58,840 --> 00:08:00,920 Speaker 9: Well, first of all, I think the US market already 164 00:08:01,000 --> 00:08:05,240 Speaker 9: had sufficient capacity last year. I think we're bouncing back 165 00:08:05,240 --> 00:08:07,640 Speaker 9: from a pandemic. We saw a bunch of sort of 166 00:08:07,720 --> 00:08:11,600 Speaker 9: revenge travel earlier in this bounce back, and that was 167 00:08:11,720 --> 00:08:14,040 Speaker 9: very leisure driven. I don't think we're going to see 168 00:08:14,080 --> 00:08:17,400 Speaker 9: as much of the leisure driven travel this year. Not 169 00:08:17,480 --> 00:08:19,120 Speaker 9: that I got to pay whatever it's going to take 170 00:08:19,520 --> 00:08:21,560 Speaker 9: to get down to Disney, so you'll see it. 171 00:08:21,640 --> 00:08:23,000 Speaker 10: Maybe a smaller. 172 00:08:22,560 --> 00:08:26,080 Speaker 9: Growth amount in leisure and business isn't fully back. 173 00:08:26,120 --> 00:08:27,000 Speaker 10: We know that. 174 00:08:27,320 --> 00:08:29,920 Speaker 9: So we've got twenty nineteen more than twenty nineteen levels 175 00:08:29,960 --> 00:08:33,880 Speaker 9: of capacity in the marketplace, less business and maybe a 176 00:08:33,920 --> 00:08:37,520 Speaker 9: little more leisure. So when I add that all up again, 177 00:08:37,600 --> 00:08:40,000 Speaker 9: I kind of see a market that looks like it's 178 00:08:40,040 --> 00:08:42,560 Speaker 9: got plenty of capacity. If you look at the guidance 179 00:08:42,600 --> 00:08:46,800 Speaker 9: that Southwest gave on revenue per available seat mile, they 180 00:08:46,960 --> 00:08:50,040 Speaker 9: lowered that at this discussion, So it tells me that 181 00:08:50,080 --> 00:08:52,520 Speaker 9: the market is weaker. You know, at this guidance point, 182 00:08:52,800 --> 00:08:55,199 Speaker 9: the market is weaker than they initially thought. 183 00:08:55,480 --> 00:08:57,600 Speaker 10: And at the same time, fuel prices were a little 184 00:08:57,600 --> 00:08:59,400 Speaker 10: bit higher. So what it looks like. 185 00:08:59,360 --> 00:09:01,520 Speaker 9: To me is Southwest numbers are going to come in 186 00:09:01,640 --> 00:09:05,240 Speaker 9: lighter than we expected in one queue. That's not a 187 00:09:05,280 --> 00:09:08,120 Speaker 9: super healthy market. That's on a market that's got so 188 00:09:08,200 --> 00:09:10,280 Speaker 9: much constraint that they can price whatever they want to 189 00:09:10,400 --> 00:09:12,760 Speaker 9: for airline tickets and make lots of profits. 190 00:09:12,840 --> 00:09:15,599 Speaker 3: Okay, so it's a trifecta, Like they do have a 191 00:09:15,640 --> 00:09:18,360 Speaker 3: specific Boeing issue and the fuel prices and then the 192 00:09:18,360 --> 00:09:22,880 Speaker 3: broader softer market that's a general airline issue. United also 193 00:09:23,360 --> 00:09:26,000 Speaker 3: told Boeing to stop building seven thirty seven Max. 194 00:09:25,840 --> 00:09:29,400 Speaker 5: Ten jets for the carrier. That sounds dramatic and bad. 195 00:09:29,400 --> 00:09:30,520 Speaker 5: What does that actually mean? 196 00:09:31,000 --> 00:09:33,320 Speaker 9: You know, I think it sounds like Scott Kirby, the 197 00:09:33,360 --> 00:09:35,480 Speaker 9: CEO of United, is just getting real about what he 198 00:09:35,520 --> 00:09:37,800 Speaker 9: thinks Boeing can deliver in the near term. I guess, 199 00:09:37,880 --> 00:09:39,959 Speaker 9: you know, if you sit around and you kind to 200 00:09:40,040 --> 00:09:41,600 Speaker 9: hope and hope and hope they're going to get the 201 00:09:41,600 --> 00:09:45,199 Speaker 9: Max ten certified, and you wait on those deliveries based 202 00:09:45,240 --> 00:09:47,719 Speaker 9: on that hope, and the certification keeps getting pushed out, 203 00:09:47,720 --> 00:09:51,480 Speaker 9: and it's really hard to plan. So Scott Kirby said, hey, look, 204 00:09:51,840 --> 00:09:54,440 Speaker 9: stop worrying about the Dash ten. Just bring me Dashed on. 205 00:09:54,559 --> 00:09:57,240 Speaker 9: He's saying, look, I just want airplanes. Bring me airplanes. 206 00:09:57,520 --> 00:09:59,880 Speaker 9: I think the market's generally going to be strong for me. 207 00:10:00,400 --> 00:10:02,719 Speaker 9: He's in the premium segment too, right, which I think 208 00:10:02,720 --> 00:10:05,280 Speaker 9: from the guidance we saw from Airlines, premium is holding 209 00:10:05,360 --> 00:10:05,760 Speaker 9: up better. 210 00:10:06,120 --> 00:10:07,520 Speaker 10: So he wants airplanes. 211 00:10:07,840 --> 00:10:09,439 Speaker 9: He wants to go out and find some of those 212 00:10:09,440 --> 00:10:11,880 Speaker 9: three twenty one larger scale from Airbus. 213 00:10:12,280 --> 00:10:14,280 Speaker 10: I think it's okay. I think Scott's being a realist. 214 00:10:14,520 --> 00:10:16,520 Speaker 9: There's a lot of challenges right now at Boeing, and 215 00:10:16,559 --> 00:10:19,480 Speaker 9: it feels to me like certification. 216 00:10:18,960 --> 00:10:20,480 Speaker 10: For the Dash seven and the Dash ten. 217 00:10:21,000 --> 00:10:23,040 Speaker 9: You know, the dashten being the biggest variant of the 218 00:10:23,040 --> 00:10:26,040 Speaker 9: seven thirty seven. There's just almost no way they're going 219 00:10:26,120 --> 00:10:28,959 Speaker 9: to get pushed out longer than what we expect given 220 00:10:29,000 --> 00:10:31,320 Speaker 9: the problems in manufacturing and Boeing right now. 221 00:10:31,640 --> 00:10:32,200 Speaker 5: And what is that? 222 00:10:32,280 --> 00:10:34,400 Speaker 4: So is there any redacross that we should start thinking 223 00:10:34,400 --> 00:10:35,359 Speaker 4: about for Airbus? 224 00:10:36,240 --> 00:10:39,600 Speaker 9: Here's the challenge of this industry right the readacross is. Look, 225 00:10:39,720 --> 00:10:41,560 Speaker 9: Airbus ought to be able to go get a lot 226 00:10:41,600 --> 00:10:43,720 Speaker 9: more orders for its Airbus A three to twenty one. 227 00:10:44,320 --> 00:10:46,959 Speaker 9: But the problem Scott has, and he's a really good 228 00:10:47,040 --> 00:10:49,960 Speaker 9: customer and they're working hard to find him slots, is 229 00:10:50,000 --> 00:10:52,679 Speaker 9: that they probably can't get him three twenty one's for 230 00:10:52,840 --> 00:10:55,880 Speaker 9: four or five years from now. So that doesn't fix 231 00:10:55,920 --> 00:10:59,720 Speaker 9: his near term problems. And customers that would be smaller 232 00:10:59,720 --> 00:11:02,480 Speaker 9: than United have an even larger problem because air Bus 233 00:11:02,559 --> 00:11:03,880 Speaker 9: isn't going to work as hard to try to get 234 00:11:03,920 --> 00:11:07,880 Speaker 9: them into the delivery cadence. The industry is operating at 235 00:11:08,000 --> 00:11:11,720 Speaker 9: sort of max capacity now. It's pushing its supply chains 236 00:11:11,760 --> 00:11:14,959 Speaker 9: to do better, but we just don't see increases of 237 00:11:15,080 --> 00:11:17,800 Speaker 9: you know, build rates kind of more than ten percent 238 00:11:17,880 --> 00:11:20,720 Speaker 9: per year at best. It's really hard to bring up 239 00:11:20,720 --> 00:11:24,360 Speaker 9: that supply chain, So I think the duopoly means that 240 00:11:24,640 --> 00:11:26,920 Speaker 9: Airbus can't really capitalize that well on this. 241 00:11:27,520 --> 00:11:30,200 Speaker 4: If you think about what the challenges are facing Boeing, 242 00:11:30,600 --> 00:11:32,680 Speaker 4: is there much of a difference to the company if 243 00:11:32,720 --> 00:11:35,240 Speaker 4: we get a soft economic landing, a hard economic landing, 244 00:11:35,320 --> 00:11:36,000 Speaker 4: or no landing. 245 00:11:36,920 --> 00:11:39,560 Speaker 10: Honestly, I think for all the air framers there isn't. Right. 246 00:11:39,640 --> 00:11:43,920 Speaker 9: So again, Airbus and Boeing building aircraft at rates much 247 00:11:44,000 --> 00:11:46,960 Speaker 9: lower than the customers are demanding right now. You know, 248 00:11:47,000 --> 00:11:49,080 Speaker 9: customers like Scott Kirby want to come in and buy 249 00:11:49,120 --> 00:11:51,920 Speaker 9: a three twenty one's next three or four years, can't 250 00:11:51,960 --> 00:11:52,480 Speaker 9: get them. 251 00:11:52,760 --> 00:11:53,800 Speaker 10: So I think even in. 252 00:11:53,800 --> 00:11:58,920 Speaker 9: A hard landing, soft landing, no recession environment, these folks 253 00:11:58,960 --> 00:12:02,440 Speaker 9: just keep working on making the supply chain better, so 254 00:12:02,480 --> 00:12:04,920 Speaker 9: the supply chain can put more of the components on 255 00:12:04,960 --> 00:12:07,920 Speaker 9: the factory floor and build more aircraft. 256 00:12:07,960 --> 00:12:08,720 Speaker 10: Although I would. 257 00:12:08,559 --> 00:12:12,480 Speaker 9: Say maybe in a harder economic landing it might free 258 00:12:12,559 --> 00:12:15,240 Speaker 9: up some of the labor that they need and keep 259 00:12:15,280 --> 00:12:18,560 Speaker 9: some of the labor more stable at their suppliers. And 260 00:12:18,600 --> 00:12:22,319 Speaker 9: that's really the challenge right here, is labor at the suppliers. 261 00:12:22,720 --> 00:12:25,920 Speaker 9: Stabilizing it. You need smart people there who've been doing 262 00:12:26,160 --> 00:12:28,080 Speaker 9: the process for a long time, so they do it 263 00:12:28,160 --> 00:12:31,040 Speaker 9: right all the time, know the right processes and procedures. 264 00:12:31,360 --> 00:12:33,880 Speaker 3: All right, our thanks to George ferguson Bloomberg Intelligence and 265 00:12:33,920 --> 00:12:35,920 Speaker 3: your Aerospace, Defense and Airlines analyst. 266 00:12:36,160 --> 00:12:38,520 Speaker 4: Coming up, we'll break down why investors were excited this 267 00:12:38,559 --> 00:12:40,720 Speaker 4: week about the computer tech company Oracle. 268 00:12:41,040 --> 00:12:43,440 Speaker 3: You were listening to Bloomberg Intelligence some on Bloomberg Radio, 269 00:12:43,520 --> 00:12:46,080 Speaker 3: providing in depth research and data on two thousand companies 270 00:12:46,120 --> 00:12:48,840 Speaker 3: in one hundred and thirty industries. You can access Bloomberg 271 00:12:48,880 --> 00:12:50,760 Speaker 3: Intelligence through Bigo on the terminal. 272 00:12:50,840 --> 00:12:53,880 Speaker 4: I'm Alex Steele and I'm Jen Ryan. This is Bloomberg. 273 00:13:00,960 --> 00:13:04,840 Speaker 1: You're listening to the Bloomberg Intelligence podcast. Catch us live 274 00:13:04,920 --> 00:13:07,600 Speaker 1: weekdays at ten am Eastern on Apple car Play and 275 00:13:07,600 --> 00:13:10,679 Speaker 1: Android Auto with the Bloomberg Business app. Listen on demand 276 00:13:10,679 --> 00:13:15,559 Speaker 1: wherever you get your podcasts, or watch us live on YouTube. 277 00:13:16,000 --> 00:13:18,520 Speaker 4: Hey everyone, I'm Alex Steel and I'm Jen Ryan filling 278 00:13:18,520 --> 00:13:19,480 Speaker 4: in for Paul Sweeney. 279 00:13:19,600 --> 00:13:21,280 Speaker 5: We moved next to e SG. 280 00:13:21,520 --> 00:13:24,520 Speaker 3: That's Environmental, Social and Governance Strategy. It's been one of 281 00:13:24,520 --> 00:13:26,280 Speaker 3: the main themes over the past few years. 282 00:13:26,400 --> 00:13:29,480 Speaker 4: And you know Alex Annett thirteen billion dollars was pulled 283 00:13:29,520 --> 00:13:32,560 Speaker 4: last year from US based sustainable funds due to subparer 284 00:13:32,559 --> 00:13:36,400 Speaker 4: investment performance and heightened political scrutiny. That's according to analysts 285 00:13:36,400 --> 00:13:37,200 Speaker 4: at morning Stars. 286 00:13:37,200 --> 00:13:39,680 Speaker 3: So we were joined this week by SEEN contractor Bloomberg 287 00:13:39,720 --> 00:13:42,040 Speaker 3: Intelligence and your ESG strategists, and she took a look 288 00:13:42,040 --> 00:13:44,719 Speaker 3: at ESG ETFs and we first asked her to give 289 00:13:44,720 --> 00:13:47,080 Speaker 3: her outlook for the ETFs in twenty twenty four. 290 00:13:47,120 --> 00:13:51,040 Speaker 7: In the US. We expect to continue it pause now. 291 00:13:51,320 --> 00:13:53,480 Speaker 7: I would say last year was the first time that 292 00:13:53,600 --> 00:13:56,880 Speaker 7: flu is sterne negative. We sought about four billion in 293 00:13:57,000 --> 00:14:00,559 Speaker 7: outfluce for me SG ETFs. Though I will say that 294 00:14:00,920 --> 00:14:03,480 Speaker 7: I don't think that represents some kind of like mass 295 00:14:03,600 --> 00:14:06,080 Speaker 7: exodus from the strategy. And I'm happy to tell you why. 296 00:14:06,160 --> 00:14:09,360 Speaker 7: I just see a pause sort of less outflows but 297 00:14:09,440 --> 00:14:13,040 Speaker 7: also less inflows. If you look at the outflows, most 298 00:14:13,040 --> 00:14:15,800 Speaker 7: of it were from a handful of funds, right, So 299 00:14:15,880 --> 00:14:18,320 Speaker 7: in a world where you have five hundred plus funds, 300 00:14:18,360 --> 00:14:21,560 Speaker 7: if one loses money, and it's really one that's all 301 00:14:21,640 --> 00:14:25,320 Speaker 7: fifty percent of most outflows, it's a change in one 302 00:14:25,360 --> 00:14:28,480 Speaker 7: investor sentiment. It's not like one hundred funds picking up 303 00:14:28,520 --> 00:14:29,280 Speaker 7: and selling off. 304 00:14:29,920 --> 00:14:33,000 Speaker 3: Do you think though money flows more into other areas 305 00:14:33,040 --> 00:14:36,760 Speaker 3: of ESG ETFs, like in Europe whose policy and I 306 00:14:36,760 --> 00:14:39,480 Speaker 3: guess commitment. I mean, I say commitment because we don't 307 00:14:39,520 --> 00:14:42,440 Speaker 3: really know how all the energy transition stuff will shake 308 00:14:42,480 --> 00:14:44,760 Speaker 3: out in terms of allocating capital, but where it seems 309 00:14:44,760 --> 00:14:47,360 Speaker 3: like it's more consistent with messaging. 310 00:14:46,960 --> 00:14:51,000 Speaker 7: One hundred percent. So Europe is still ninety nine percent 311 00:14:51,040 --> 00:14:54,440 Speaker 7: of the ESGTF flows. It's about okay, yeah, it's about 312 00:14:54,520 --> 00:14:57,240 Speaker 7: not the forty billion, and I mentioned US as a 313 00:14:57,320 --> 00:15:01,080 Speaker 7: negative four billions, so very big divide. That being said, 314 00:15:01,160 --> 00:15:03,560 Speaker 7: in terms of strategy, we are seeing a bit of 315 00:15:03,600 --> 00:15:06,000 Speaker 7: a I want to call it an expansion, you know, 316 00:15:06,160 --> 00:15:09,520 Speaker 7: a move to climate, to move to more of the thematics, 317 00:15:09,600 --> 00:15:10,920 Speaker 7: that kind of move. 318 00:15:11,000 --> 00:15:12,960 Speaker 4: I guess could you explain that a little bit more? 319 00:15:13,040 --> 00:15:15,520 Speaker 7: Sure? So, when we think of ESG, I think of 320 00:15:15,560 --> 00:15:19,680 Speaker 7: a broad sort of environmental, social, and governance strategy, all three. 321 00:15:20,120 --> 00:15:24,000 Speaker 7: What I find people concentrating on more now is one 322 00:15:24,040 --> 00:15:26,640 Speaker 7: of the eds or the G right, more of the themes. 323 00:15:26,680 --> 00:15:29,120 Speaker 7: And I think a piece of that in the US 324 00:15:29,280 --> 00:15:32,440 Speaker 7: is this push against the ESG label sort of all 325 00:15:32,520 --> 00:15:35,480 Speaker 7: three combined, which is why it's you know, focusing on 326 00:15:35,520 --> 00:15:38,520 Speaker 7: something simpler like gender or climate things like that. 327 00:15:38,880 --> 00:15:42,880 Speaker 3: Why do you think that in the US ESG ETFs 328 00:15:42,960 --> 00:15:46,040 Speaker 3: haven't been maybe as popular as over in Europe. Is 329 00:15:46,080 --> 00:15:48,720 Speaker 3: it the quality of the ETFs or is it the 330 00:15:48,760 --> 00:15:50,280 Speaker 3: feelings behind ESG. 331 00:15:51,040 --> 00:15:53,480 Speaker 7: So I think it's two things. So first, they were 332 00:15:53,600 --> 00:15:56,600 Speaker 7: very popular about twenty twenty two, I want to say, 333 00:15:56,600 --> 00:15:59,880 Speaker 7: almost as popular as Europe, but overtook Europe a little 334 00:15:59,880 --> 00:16:03,160 Speaker 7: bit in terms of growth. That being said, I think 335 00:16:03,200 --> 00:16:06,640 Speaker 7: the political backlash has had quite a bit of implication on, 336 00:16:07,280 --> 00:16:11,360 Speaker 7: you know, its continued growth. Also, the one challenge in 337 00:16:11,400 --> 00:16:15,520 Speaker 7: the US is that growth has been very concentrated to 338 00:16:15,560 --> 00:16:18,320 Speaker 7: a few investors, which means that just a handful of 339 00:16:18,320 --> 00:16:20,840 Speaker 7: investors put large chunks of money. So what we need 340 00:16:20,880 --> 00:16:23,440 Speaker 7: today is we need a wide investor base, which I 341 00:16:23,480 --> 00:16:25,960 Speaker 7: think is going to slow because of this backlash. 342 00:16:26,160 --> 00:16:28,040 Speaker 4: I wonder if you could talk a little bit about 343 00:16:28,080 --> 00:16:30,800 Speaker 4: the sentiment there in the US, and can you, if possible, 344 00:16:31,000 --> 00:16:36,400 Speaker 4: look ahead past the November election here, depending on who wins, 345 00:16:36,440 --> 00:16:38,640 Speaker 4: who takes the oval office what do you think that 346 00:16:38,720 --> 00:16:39,720 Speaker 4: will do to sentiment. 347 00:16:40,600 --> 00:16:43,680 Speaker 7: I think it's definitely going to be driven by who 348 00:16:43,680 --> 00:16:46,120 Speaker 7: comes into office, but at the same time, also who 349 00:16:46,160 --> 00:16:49,160 Speaker 7: controls some of the states right. And that being said, 350 00:16:50,000 --> 00:16:52,360 Speaker 7: the way I see it is if you have like 351 00:16:52,400 --> 00:16:54,920 Speaker 7: the SEC regulation and you have a number of states 352 00:16:54,960 --> 00:16:57,600 Speaker 7: suing the SEC because of that, that's going to continue 353 00:16:57,680 --> 00:16:58,920 Speaker 7: to have a sort of a little bit of a 354 00:16:58,960 --> 00:16:59,880 Speaker 7: negative backlash. 355 00:17:00,520 --> 00:17:03,840 Speaker 3: Also, I mean, the backlash started before we even the. 356 00:17:03,800 --> 00:17:07,679 Speaker 7: Backlash right the back right. So I think the presidential 357 00:17:07,800 --> 00:17:10,480 Speaker 7: cycle will have some impact. But I think the whole 358 00:17:11,119 --> 00:17:13,399 Speaker 7: sort of backlash has to come down a little bit 359 00:17:13,520 --> 00:17:15,880 Speaker 7: or go in some direction for this to have well 360 00:17:16,160 --> 00:17:16,800 Speaker 7: some impact. 361 00:17:16,840 --> 00:17:19,000 Speaker 3: What do you make of the idea that maybe ESG 362 00:17:19,240 --> 00:17:22,120 Speaker 3: doesn't actually help companies profits like. 363 00:17:22,359 --> 00:17:26,200 Speaker 7: Yeah, I mean, I can't for certain say that ESG 364 00:17:26,359 --> 00:17:29,440 Speaker 7: has proven to outperform. I don't think anybody can say 365 00:17:29,440 --> 00:17:32,399 Speaker 7: that unless they've done some kind of fancy quant analysis. 366 00:17:32,440 --> 00:17:35,119 Speaker 7: We're starting to do that. I think we still have 367 00:17:35,240 --> 00:17:38,320 Speaker 7: too limited a time history of data to actually make 368 00:17:38,359 --> 00:17:40,840 Speaker 7: any kind of implication yet. 369 00:17:41,040 --> 00:17:44,480 Speaker 4: It's interesting, though, because I always understood the support for 370 00:17:44,560 --> 00:17:48,000 Speaker 4: DEI and the support for ESG came in part from 371 00:17:48,359 --> 00:17:51,439 Speaker 4: the new generation of consumers, for millennials who want to 372 00:17:51,520 --> 00:17:55,359 Speaker 4: vote with their pocketbook, and also the diversification that's coming 373 00:17:55,520 --> 00:17:58,640 Speaker 4: in the United States workforce. How does that ply into 374 00:17:58,680 --> 00:18:01,480 Speaker 4: your view that the ESG back clash my fade away 375 00:18:01,480 --> 00:18:01,720 Speaker 4: a bit. 376 00:18:02,200 --> 00:18:05,280 Speaker 7: So I guess I have two opinions there. So my 377 00:18:05,359 --> 00:18:08,000 Speaker 7: one opinion, as we've been saying for years that this 378 00:18:08,080 --> 00:18:10,960 Speaker 7: whole transfer of with is going to happen, we still 379 00:18:11,000 --> 00:18:14,720 Speaker 7: see the ESG investor base as highly institutional and it's 380 00:18:14,760 --> 00:18:18,200 Speaker 7: not very retail based. So in that sense, I haven't 381 00:18:18,240 --> 00:18:21,360 Speaker 7: seen this transfer of money come into effect. Will that 382 00:18:21,400 --> 00:18:24,120 Speaker 7: have at least not in the ESGDF food, Will that 383 00:18:24,280 --> 00:18:28,000 Speaker 7: happen OVID generations and you know over to time period. 384 00:18:28,680 --> 00:18:31,560 Speaker 7: I do think so, but we haven't seen it yet, 385 00:18:31,600 --> 00:18:33,480 Speaker 7: and we've been talking about it for a long time. 386 00:18:33,840 --> 00:18:37,920 Speaker 4: Our thanks to Streen contractor Bloomberg Intelligence senior ESG strategists. 387 00:18:37,920 --> 00:18:39,399 Speaker 3: All right, let's go to tech. Now, look at the 388 00:18:39,480 --> 00:18:42,600 Speaker 3: computer technology company Oracle. At the beginning of the week, 389 00:18:42,640 --> 00:18:45,360 Speaker 3: Oracle reported total sales in the third quarter rose over 390 00:18:45,400 --> 00:18:48,439 Speaker 3: seven percent to thirteen point three billion dollars. That was 391 00:18:48,560 --> 00:18:50,639 Speaker 3: roughly in line with analyst expectations. 392 00:18:50,720 --> 00:18:53,440 Speaker 4: And you know alex Oracle also said that cloud revenue 393 00:18:53,480 --> 00:18:56,800 Speaker 4: jumped twenty five percent and that excited investors. On Tuesday, 394 00:18:57,119 --> 00:19:00,000 Speaker 4: Oracle shares posted their biggest gain in more than two years. 395 00:19:00,080 --> 00:19:02,879 Speaker 3: So we were joined by Brody Ford, Bloomberg Technology reporter, 396 00:19:02,920 --> 00:19:04,800 Speaker 3: and we asked him why the street was so excited 397 00:19:04,800 --> 00:19:05,960 Speaker 3: about Oracles results. 398 00:19:06,400 --> 00:19:09,040 Speaker 11: There's been a big debate over the last year. Can 399 00:19:09,080 --> 00:19:12,520 Speaker 11: Oracle transform from this kind of old school on premise, 400 00:19:12,720 --> 00:19:15,160 Speaker 11: come to your office and install it on your servers 401 00:19:15,240 --> 00:19:18,760 Speaker 11: kind of company to really offering cloud infrastructure the way 402 00:19:18,760 --> 00:19:22,560 Speaker 11: we think about Amazon or Microsoft doing. The last couple 403 00:19:22,560 --> 00:19:25,199 Speaker 11: of quarters they were disappointing and people were starting to 404 00:19:25,280 --> 00:19:27,680 Speaker 11: wonder is this a flash in the pan? Is their 405 00:19:27,720 --> 00:19:31,000 Speaker 11: growth sustained? They said, hey, no, we actually got billions 406 00:19:31,000 --> 00:19:33,320 Speaker 11: more on orders than you expected. They had really strong 407 00:19:33,359 --> 00:19:37,000 Speaker 11: bookings growth. That's kind of reignited that enthusiasm that hey, 408 00:19:37,520 --> 00:19:41,040 Speaker 11: maybe Oracle really can be that, you know, fourth hyper 409 00:19:41,040 --> 00:19:43,480 Speaker 11: scaler after Google, Amazon and Microsoft. 410 00:19:43,880 --> 00:19:46,360 Speaker 4: But I guess you know, they've been having their ups 411 00:19:46,400 --> 00:19:49,360 Speaker 4: and downs. Their shares got really badly hit relatively speaking, 412 00:19:49,440 --> 00:19:52,080 Speaker 4: and so do you feel like the recovery today is 413 00:19:52,119 --> 00:19:54,400 Speaker 4: for real or what's going to be the next waystation 414 00:19:54,480 --> 00:19:55,240 Speaker 4: that investors have. 415 00:19:55,240 --> 00:19:55,680 Speaker 5: To look for? 416 00:19:55,880 --> 00:19:59,920 Speaker 11: So what's convinced them is that when you're offering cloud services, 417 00:20:00,080 --> 00:20:02,600 Speaker 11: people forget the cloud isn't in the sky, it's in 418 00:20:02,760 --> 00:20:05,959 Speaker 11: data centers in Virginia, and they need to build them 419 00:20:07,440 --> 00:20:10,879 Speaker 11: of the day. And so Oracle said that they're going 420 00:20:10,920 --> 00:20:13,240 Speaker 11: to spend ten billion dollars next year is building up 421 00:20:13,280 --> 00:20:15,080 Speaker 11: these data centers. And keep in mind a couple of 422 00:20:15,119 --> 00:20:18,280 Speaker 11: years back, they were spending two billion a year on capex. 423 00:20:18,320 --> 00:20:21,240 Speaker 11: Now it's ten. That's a real difference, and that's convincing 424 00:20:21,280 --> 00:20:25,440 Speaker 11: investors that, hey, they are actually building out their physical infrastructure. 425 00:20:25,840 --> 00:20:29,800 Speaker 11: In the AI era, everyone needs more cloud, everyone needs 426 00:20:29,840 --> 00:20:33,080 Speaker 11: more of this computing power. And Oracle does seem prime 427 00:20:33,160 --> 00:20:35,440 Speaker 11: to actually capture a lot of that demand. So people 428 00:20:35,480 --> 00:20:37,720 Speaker 11: will be watching whether these data centers do go up 429 00:20:37,760 --> 00:20:39,439 Speaker 11: in Virginia and other states. 430 00:20:39,680 --> 00:20:41,320 Speaker 3: I thought we didn't like it when companies spend a 431 00:20:41,320 --> 00:20:42,280 Speaker 3: lot of money on stuff. 432 00:20:42,800 --> 00:20:44,399 Speaker 11: We like it if it's going to come back and 433 00:20:45,040 --> 00:20:48,119 Speaker 11: give us something else, Right, I mean, what was that time? 434 00:20:48,160 --> 00:20:49,560 Speaker 3: So they're going to mass all this money. When do 435 00:20:49,640 --> 00:20:51,080 Speaker 3: they make money off of the money they just spent. 436 00:20:51,680 --> 00:20:54,760 Speaker 11: Yeah, it seems like it'd be pretty quick because if 437 00:20:54,800 --> 00:20:57,440 Speaker 11: you believe the executive's on the call, you know, executives 438 00:20:57,480 --> 00:21:00,960 Speaker 11: grand stand sometimes what they say that demand outpaces supply. 439 00:21:01,040 --> 00:21:02,840 Speaker 11: They've been saying this for a while that with the 440 00:21:02,880 --> 00:21:06,320 Speaker 11: AI era, everyone's rushing to get more computing power. They 441 00:21:06,359 --> 00:21:09,280 Speaker 11: can't provide it. So the second these data centers go live, 442 00:21:09,760 --> 00:21:11,760 Speaker 11: in theory, they should be able to convert that into 443 00:21:11,800 --> 00:21:13,040 Speaker 11: revenue very quickly. 444 00:21:13,720 --> 00:21:16,320 Speaker 4: Are they good at doing that quickly relative to other companies? 445 00:21:17,280 --> 00:21:24,680 Speaker 11: They are known for ruthless operational efficiency, so they should 446 00:21:24,760 --> 00:21:27,119 Speaker 11: they should be good at this, right. I mean, of 447 00:21:27,200 --> 00:21:30,439 Speaker 11: course the market could change, right Everything looks rosy with 448 00:21:30,520 --> 00:21:32,680 Speaker 11: AI right now to be able to train their own models. 449 00:21:33,359 --> 00:21:36,359 Speaker 11: Could we see a sea change? Hard to say, but 450 00:21:36,440 --> 00:21:39,680 Speaker 11: yesterday they got eighty billion in bookings. Once you book 451 00:21:39,720 --> 00:21:42,560 Speaker 11: you can't get out of it, so it's for a while. 452 00:21:42,920 --> 00:21:44,600 Speaker 3: So I also find it's interesting if we're going to 453 00:21:44,640 --> 00:21:48,719 Speaker 3: see cloud computing and AI be a cyclical industry or not. 454 00:21:48,800 --> 00:21:50,159 Speaker 5: Like, clearly it's a structural shift. 455 00:21:50,200 --> 00:21:52,320 Speaker 3: But will we see a ton of data centers come 456 00:21:52,359 --> 00:21:54,800 Speaker 3: on at the same time, like from different companies, and 457 00:21:54,800 --> 00:21:57,040 Speaker 3: then their core prices go down so the revenue isn't 458 00:21:57,040 --> 00:21:59,560 Speaker 3: as hot, Like will it be cyclical like chips are. 459 00:21:59,440 --> 00:22:00,359 Speaker 5: For example, or not? 460 00:22:00,600 --> 00:22:03,960 Speaker 11: It's a good question. There's one rule of software compared 461 00:22:04,000 --> 00:22:06,680 Speaker 11: to hardware that software is a lot stickier, right, I mean, 462 00:22:06,760 --> 00:22:09,119 Speaker 11: you buy chips, you have them, you don't need to 463 00:22:09,160 --> 00:22:13,840 Speaker 11: buy more. Once you start giving money to software providers, 464 00:22:13,880 --> 00:22:16,800 Speaker 11: you plan on x amount of come. You know, computational 465 00:22:16,840 --> 00:22:20,280 Speaker 11: power that usually doesn't go down. I mean, is there 466 00:22:20,320 --> 00:22:23,199 Speaker 11: a point where the growth will level off? Probably? I 467 00:22:23,280 --> 00:22:26,200 Speaker 11: struggle to see it, being like hardware, where hey, everybody 468 00:22:26,200 --> 00:22:29,800 Speaker 11: bought computers this year. Now the computer makers are sol 469 00:22:29,880 --> 00:22:31,360 Speaker 11: because nobody wants to buy anymore. 470 00:22:31,800 --> 00:22:33,840 Speaker 4: And then it's all they've got you on the subscriptions, 471 00:22:33,880 --> 00:22:36,800 Speaker 4: basically like what we all have at home. But now, 472 00:22:37,080 --> 00:22:39,199 Speaker 4: can you talk a little bit more about how Oracle 473 00:22:39,280 --> 00:22:40,320 Speaker 4: is benefiting from AI? 474 00:22:40,720 --> 00:22:41,480 Speaker 10: Yeah? 475 00:22:41,520 --> 00:22:43,159 Speaker 11: Well, and that's the big question for a lot of 476 00:22:43,160 --> 00:22:46,240 Speaker 11: software makers. Every software maker when they have positive results, 477 00:22:46,280 --> 00:22:49,840 Speaker 11: they say in their commentary, this is due to aid anything. 478 00:22:52,000 --> 00:22:55,520 Speaker 11: They call their new cloud version the Gen two AI. 479 00:22:56,359 --> 00:22:57,600 Speaker 11: Is everybody using it for AI? 480 00:22:57,720 --> 00:22:57,760 Speaker 7: No? 481 00:22:59,000 --> 00:23:01,800 Speaker 11: But what we though is that AI requires a ton 482 00:23:01,840 --> 00:23:05,520 Speaker 11: of computing power, and Oracle has marketed there specifically for 483 00:23:05,800 --> 00:23:08,520 Speaker 11: being good at training AI models, and so there's reason 484 00:23:08,560 --> 00:23:11,800 Speaker 11: to believe that folks are upping their demand due to 485 00:23:11,880 --> 00:23:15,639 Speaker 11: AI needs. But is this more than a couple of 486 00:23:15,720 --> 00:23:19,520 Speaker 11: percentage point difference. Most analysts don't think so at this point. 487 00:23:19,800 --> 00:23:22,119 Speaker 5: So it's still the cloud. It's still it's the cloud, 488 00:23:22,200 --> 00:23:23,639 Speaker 5: the data centers building all that out. 489 00:23:23,800 --> 00:23:26,719 Speaker 11: Yeah, you know, I think about you know, any companies running 490 00:23:26,720 --> 00:23:29,880 Speaker 11: all these you know, records, the terminal or anything like that. 491 00:23:30,040 --> 00:23:31,720 Speaker 11: Just it's more that kind of tradition stuff at this 492 00:23:31,720 --> 00:23:34,320 Speaker 11: point than it is training models, though that's probably part 493 00:23:34,359 --> 00:23:34,560 Speaker 11: of it. 494 00:23:35,119 --> 00:23:36,520 Speaker 3: I did want to point out too that maybe you 495 00:23:36,520 --> 00:23:38,600 Speaker 3: can comment on this one, that Bank America, the reason 496 00:23:38,600 --> 00:23:41,560 Speaker 3: why they upgrade their earnings, in part was because of 497 00:23:41,680 --> 00:23:45,560 Speaker 3: an investment cycle from big tech Microsoft, Amazon, Google, Meta 498 00:23:45,640 --> 00:23:48,000 Speaker 3: spending one hundred and eighty billion dollars in cap x. 499 00:23:48,040 --> 00:23:50,480 Speaker 3: They're in that reinvestment cycle, and I'm assuming you guys 500 00:23:50,520 --> 00:23:52,680 Speaker 3: like Oracle are going to be beneficiaries. 501 00:23:52,720 --> 00:23:53,840 Speaker 5: Is that a link I can make? 502 00:23:55,040 --> 00:23:58,760 Speaker 11: I think it is probably more that they're all riding 503 00:23:58,800 --> 00:24:03,560 Speaker 11: similar trends, you know, Amazon, Microsoft, They've spoken also in 504 00:24:03,640 --> 00:24:06,760 Speaker 11: recent quarters that their customers are really focus on cutting costs. 505 00:24:06,800 --> 00:24:10,240 Speaker 11: That for the most part, everybody had transported a bunch 506 00:24:10,240 --> 00:24:12,000 Speaker 11: of things to the cloud and then they wanted to 507 00:24:12,040 --> 00:24:15,159 Speaker 11: cut costs, and that behavior was starting to change, you know, 508 00:24:15,280 --> 00:24:18,399 Speaker 11: the twenty twenty four budgets got approved, they started feeling 509 00:24:18,440 --> 00:24:20,879 Speaker 11: good again, and the investment was going up. And so 510 00:24:20,920 --> 00:24:23,080 Speaker 11: I think it's one that they're all riding a similar wave. 511 00:24:23,240 --> 00:24:23,680 Speaker 5: I see. 512 00:24:23,920 --> 00:24:24,080 Speaker 10: You know. 513 00:24:24,160 --> 00:24:27,440 Speaker 4: Let me ask you something internally about Oracle. Who's running 514 00:24:27,480 --> 00:24:29,200 Speaker 4: the company. Is it Larry Ellison? 515 00:24:29,560 --> 00:24:31,639 Speaker 11: It's crazy, right because you think about somebody like a 516 00:24:31,680 --> 00:24:34,440 Speaker 11: Bill Gates that's the same generation. He hasn't been there 517 00:24:34,480 --> 00:24:37,280 Speaker 11: for a decade or more. But yeah, Larry's still running that. 518 00:24:37,320 --> 00:24:39,960 Speaker 11: I mean, he's his title is not CEO, but he's 519 00:24:40,040 --> 00:24:43,520 Speaker 11: chairman and his CTO. He's, you know, on the earnings call, 520 00:24:43,640 --> 00:24:46,600 Speaker 11: talking back and forth with analysts. For someone of his 521 00:24:46,680 --> 00:24:48,600 Speaker 11: age and his generation, it's rare to see him still 522 00:24:48,680 --> 00:24:52,080 Speaker 11: running the company. But he continues to and there's no 523 00:24:52,119 --> 00:24:55,480 Speaker 11: reason to believe that will change anytime soon. So it's interesting. 524 00:24:55,760 --> 00:24:58,680 Speaker 3: All right, Thanks Berdy Berdi Ford, Bloomberg Technology reporter. 525 00:24:58,640 --> 00:25:00,600 Speaker 4: Coming up on the program, A look at It, Predicting 526 00:25:00,680 --> 00:25:03,399 Speaker 4: nature's catastrophes could become more profitable. 527 00:25:03,480 --> 00:25:06,439 Speaker 3: You're listening to Bloomberg Intelligence on Bloomberg Radio, providing in 528 00:25:06,480 --> 00:25:08,879 Speaker 3: depth research and data on two thousand companies in one 529 00:25:08,960 --> 00:25:12,040 Speaker 3: hundred and thirty industries. You can access Bloomberg Intelligence through 530 00:25:12,080 --> 00:25:13,360 Speaker 3: Bigo on the terminal. 531 00:25:13,400 --> 00:25:15,119 Speaker 5: I'm Alex Steele and I'm Jen Ryan. 532 00:25:15,320 --> 00:25:16,359 Speaker 6: This is Bloomberg. 533 00:25:21,600 --> 00:25:25,480 Speaker 1: You're listening to the Bloomberg Intelligence Podcast. Catch us live 534 00:25:25,560 --> 00:25:29,119 Speaker 1: weekdays at ten am Eastern on applecar Play and Android 535 00:25:29,119 --> 00:25:31,879 Speaker 1: Auto with the Bloomberg Business app. You can also listen 536 00:25:32,000 --> 00:25:35,080 Speaker 1: live on Amazon Alexa from our flagship New York station. 537 00:25:35,480 --> 00:25:38,240 Speaker 1: Just say Alexa Play Bloomberg eleven thirty. 538 00:25:39,440 --> 00:25:42,040 Speaker 4: Hey everyone, I'm Alex Steele and I'm Jen Ryan, filling 539 00:25:42,040 --> 00:25:42,960 Speaker 4: in for Paul Sweeney. 540 00:25:43,040 --> 00:25:44,439 Speaker 5: The move next to politics. 541 00:25:44,560 --> 00:25:48,120 Speaker 3: Earlier this week, Donald Trump clinched the Republican presidential nomination 542 00:25:48,520 --> 00:25:50,919 Speaker 3: and this sets up an election rematch in November with 543 00:25:51,000 --> 00:25:54,120 Speaker 3: current President Joe Biden, who secured the Democratic nomination. 544 00:25:54,359 --> 00:25:57,080 Speaker 4: For more, we were joined by Nathan Dean, senior policy 545 00:25:57,080 --> 00:25:59,960 Speaker 4: analyst at Bloomberg Intelligence. Nathan gave us his take on 546 00:26:00,000 --> 00:26:02,200 Speaker 4: and how investors should start to prepare for the election 547 00:26:02,359 --> 00:26:04,720 Speaker 4: cycle and what sectors may have more at stake. 548 00:26:05,160 --> 00:26:07,240 Speaker 2: What this race is essentially coming down to three things. 549 00:26:07,240 --> 00:26:10,119 Speaker 2: It's President buy and versus President Trump versus not voting. 550 00:26:10,359 --> 00:26:12,800 Speaker 2: But from an investor's standpoint, the way we're advising our 551 00:26:12,800 --> 00:26:16,000 Speaker 2: clients right now is start with the geopolitical the macro views, 552 00:26:16,080 --> 00:26:18,520 Speaker 2: because that's where the power of the presidency is a 553 00:26:18,560 --> 00:26:21,119 Speaker 2: little bit more powerful. And so you see statements like 554 00:26:21,119 --> 00:26:24,639 Speaker 2: President Trump saying fifty percent tariffs on China. Well, we've 555 00:26:24,680 --> 00:26:26,760 Speaker 2: been doing a lot of work with our FX strategists 556 00:26:26,840 --> 00:26:28,320 Speaker 2: on what does that do for the euro dollar? 557 00:26:28,400 --> 00:26:29,520 Speaker 5: What does that do for the dollar? 558 00:26:29,800 --> 00:26:32,159 Speaker 2: And Bloomberg Economics has put out some great pieces as 559 00:26:32,200 --> 00:26:35,159 Speaker 2: well on what that actually could be on the economy. 560 00:26:35,480 --> 00:26:37,240 Speaker 2: And so the second thing to keep in mind is 561 00:26:37,280 --> 00:26:40,800 Speaker 2: executive actions. What would a president do on day one? 562 00:26:40,880 --> 00:26:42,919 Speaker 2: You know, for President Biden, I think it's just par 563 00:26:43,040 --> 00:26:45,119 Speaker 2: for the course, go back to his State of the Union, 564 00:26:45,359 --> 00:26:46,960 Speaker 2: go back to the budget, and you'll get a little 565 00:26:47,000 --> 00:26:49,240 Speaker 2: bit idea of his priorities there. But when it comes 566 00:26:49,280 --> 00:26:51,560 Speaker 2: to President Trump on day one, you'll see a lot 567 00:26:51,560 --> 00:26:55,440 Speaker 2: of executive actions which are directed agencies within the executive 568 00:26:55,480 --> 00:26:59,280 Speaker 2: branch to go out and start regulatory changes. And that's 569 00:26:59,320 --> 00:27:02,520 Speaker 2: the third aspect for it is regulatory change. Now, regulatory 570 00:27:02,600 --> 00:27:04,919 Speaker 2: change takes a lot of time, and so from an 571 00:27:04,920 --> 00:27:07,919 Speaker 2: investor standpoint, it's something to keep in mind of. But 572 00:27:08,000 --> 00:27:11,639 Speaker 2: those geopolitical factors of trade and tariffs and national security 573 00:27:11,800 --> 00:27:13,879 Speaker 2: should be at the forefront of any investor trying to 574 00:27:13,880 --> 00:27:15,760 Speaker 2: figure out how does the election apply to them in 575 00:27:15,800 --> 00:27:16,600 Speaker 2: their portfolio. 576 00:27:16,760 --> 00:27:17,520 Speaker 5: So let's dig. 577 00:27:17,400 --> 00:27:19,440 Speaker 4: Into this a little bit. Do you have any in mind, 578 00:27:19,440 --> 00:27:22,359 Speaker 4: any sectors in particular that could really have more at 579 00:27:22,440 --> 00:27:24,720 Speaker 4: stake in the presidential election outcome? 580 00:27:25,359 --> 00:27:28,520 Speaker 2: Absolutely, it's energy, energy and energy. And so the reason 581 00:27:28,560 --> 00:27:30,359 Speaker 2: why I say that is there's this thing called the 582 00:27:30,359 --> 00:27:33,160 Speaker 2: Inflation Reduction Act. President Biden signed this to the law 583 00:27:33,200 --> 00:27:36,240 Speaker 2: back in twenty twenty two. A lot of investors, especially 584 00:27:36,240 --> 00:27:39,680 Speaker 2: non US investors, are taking the approach that because it's law, 585 00:27:39,880 --> 00:27:41,800 Speaker 2: it's going to be law for the get go. But 586 00:27:42,000 --> 00:27:44,399 Speaker 2: in the IRA, there are a lot of tax cares, 587 00:27:44,440 --> 00:27:47,000 Speaker 2: if you will, incentives and grants and so forth to 588 00:27:47,080 --> 00:27:51,359 Speaker 2: spur clean energy and clean energy initiatives. It's about seventy 589 00:27:51,359 --> 00:27:54,600 Speaker 2: five percent of the investment of the IRA is geared 590 00:27:54,640 --> 00:27:58,040 Speaker 2: towards these tax incentives. Now, if President Trump wins on 591 00:27:58,160 --> 00:28:00,480 Speaker 2: day one, he can put forth one of these executive 592 00:28:00,560 --> 00:28:03,480 Speaker 2: orders directing the Department of Treasury or to the Irs 593 00:28:03,520 --> 00:28:07,760 Speaker 2: to essentially just stop, stop work, stop these incentives and 594 00:28:07,800 --> 00:28:09,720 Speaker 2: so forth. There's some legalities that they have to work 595 00:28:09,760 --> 00:28:12,520 Speaker 2: through here, but effectively they will be able to use 596 00:28:12,520 --> 00:28:15,480 Speaker 2: a scalpel instead of a sledgehammer to start cutting away 597 00:28:15,480 --> 00:28:17,480 Speaker 2: a lot of those clean energy inities. 598 00:28:17,840 --> 00:28:19,600 Speaker 5: I mean, you're talking my language here. 599 00:28:19,720 --> 00:28:21,720 Speaker 3: I mean a lot of oil companies that I talked 600 00:28:21,760 --> 00:28:25,520 Speaker 3: to like the IRA because they're getting subsidies, particularly if 601 00:28:25,520 --> 00:28:28,440 Speaker 3: they're dealing in carbon capture. Some yl companies are also 602 00:28:28,520 --> 00:28:31,200 Speaker 3: dabbling a little bit in hydrogen. I mean this bill 603 00:28:31,200 --> 00:28:33,160 Speaker 3: helped they like it. It helps them. 604 00:28:33,560 --> 00:28:36,040 Speaker 2: Yeah, absolutely, But that's one of the disconnects you often 605 00:28:36,040 --> 00:28:40,040 Speaker 2: hear about New York versus Washington, because in the Washington sense, 606 00:28:40,360 --> 00:28:42,400 Speaker 2: there was a bill earlier this year in which the 607 00:28:42,440 --> 00:28:46,040 Speaker 2: Republicans put forward essentially said we'll get the entire thing, 608 00:28:46,480 --> 00:28:48,680 Speaker 2: and so the messaging is different. And you know, the 609 00:28:48,680 --> 00:28:50,800 Speaker 2: reason why we think and our analysis is out on 610 00:28:50,840 --> 00:28:52,960 Speaker 2: the terminal, we don't think that there's going to be 611 00:28:53,040 --> 00:28:56,479 Speaker 2: that much change to the IRA other than specifically some 612 00:28:56,560 --> 00:28:59,520 Speaker 2: of these EV related tax credits, is because a lot 613 00:28:59,520 --> 00:29:01,440 Speaker 2: of the money and a lot of the infrastructure that's 614 00:29:01,480 --> 00:29:03,959 Speaker 2: being built in the United States are going to red states, 615 00:29:04,200 --> 00:29:07,000 Speaker 2: and so you often see statements from Republicans saying I 616 00:29:07,040 --> 00:29:10,120 Speaker 2: supported this initiative and even President Biden in a State 617 00:29:10,120 --> 00:29:12,120 Speaker 2: of the Union address last week said, look, if you 618 00:29:12,120 --> 00:29:13,640 Speaker 2: don't want the money or you want to take credit 619 00:29:13,640 --> 00:29:15,520 Speaker 2: for it, I'll certainly take the money and take credit 620 00:29:15,560 --> 00:29:18,000 Speaker 2: for it. So I think there's this disconnect between what's 621 00:29:18,000 --> 00:29:21,000 Speaker 2: happening in Washington and the markets. I expect that the 622 00:29:21,040 --> 00:29:24,640 Speaker 2: coalesce if President Trump wins, as the markets and especially 623 00:29:24,680 --> 00:29:27,160 Speaker 2: Wall Street investors have become to try and get in 624 00:29:27,200 --> 00:29:29,600 Speaker 2: to his inner ear and so forth, so to speak. 625 00:29:29,640 --> 00:29:33,400 Speaker 2: But certainly headline risk and you will see headlines associated 626 00:29:33,440 --> 00:29:35,240 Speaker 2: with that going up into the election. 627 00:29:35,680 --> 00:29:39,160 Speaker 4: Our thanks to Nathan Dean, senior policy analyst at Bloomberg Intelligence. 628 00:29:39,520 --> 00:29:42,280 Speaker 3: On this program, we often look at our favorite Bloomberg 629 00:29:42,320 --> 00:29:44,480 Speaker 3: Big Take stories of the week and you can read 630 00:29:44,520 --> 00:29:47,360 Speaker 3: them on the Bloomberg at Bloomberg dot com slash Big Take, 631 00:29:47,400 --> 00:29:49,400 Speaker 3: and this week we looked at the story of how 632 00:29:49,440 --> 00:29:53,560 Speaker 3: a physics whiz made a fortune betting on nature's catastrophes. 633 00:29:54,040 --> 00:29:57,440 Speaker 4: It delved into why predicting nature's catastrophes is in fact 634 00:29:57,480 --> 00:30:00,480 Speaker 4: a big business. We were joined by the stories author 635 00:30:00,680 --> 00:30:04,320 Speaker 4: Gatam Nike. He's a Bloomberg senior editor covering ESG investing. 636 00:30:04,760 --> 00:30:07,160 Speaker 4: We first asked Gaton for more background on what this 637 00:30:07,200 --> 00:30:07,880 Speaker 4: story means. 638 00:30:08,440 --> 00:30:12,800 Speaker 8: It has to do with insurance. So traditional insurance and reinsurance, 639 00:30:12,920 --> 00:30:16,240 Speaker 8: you know, do a fairly good job of covering modest 640 00:30:16,400 --> 00:30:20,520 Speaker 8: and medium sized catastrophes, you know, storms and hurricanes and earthquakes. 641 00:30:20,920 --> 00:30:23,680 Speaker 8: But every thirty fifty one hundred years you get a 642 00:30:23,880 --> 00:30:28,520 Speaker 8: Hurricane Katrina like event which is completely devastating in its scope. 643 00:30:28,640 --> 00:30:31,960 Speaker 8: And that's a kind of event that traditional insurance company 644 00:30:32,000 --> 00:30:35,840 Speaker 8: can't really handle. So they've turned to a new type 645 00:30:35,840 --> 00:30:37,440 Speaker 8: of asset class. Well it's not new, it's have been 646 00:30:37,480 --> 00:30:39,680 Speaker 8: around for twenty five years, but it's really coming into 647 00:30:39,720 --> 00:30:43,719 Speaker 8: its own more and more now, and it's called catastrophe bonds. 648 00:30:44,040 --> 00:30:45,680 Speaker 8: And the way it works is that instead of the 649 00:30:45,720 --> 00:30:49,720 Speaker 8: insurance company taking the risk should disaster happen, that risk 650 00:30:49,760 --> 00:30:53,120 Speaker 8: has passed on to Wall Street investors. So if the 651 00:30:53,200 --> 00:30:56,680 Speaker 8: disaster does happen, the Wall Street investors can lose some 652 00:30:56,880 --> 00:30:58,880 Speaker 8: or all of their money. So it's a pretty risky move. 653 00:30:59,240 --> 00:31:01,680 Speaker 8: But if it doesn't happen, and these bonds are only 654 00:31:02,120 --> 00:31:04,680 Speaker 8: they run for only three to five years, not for 655 00:31:04,760 --> 00:31:08,560 Speaker 8: much longer. If the disaster doesn't occur, then the investigates 656 00:31:08,600 --> 00:31:12,280 Speaker 8: to keep its original capital plus gets a hefty return 657 00:31:12,280 --> 00:31:13,960 Speaker 8: on top of that for taking that risk. 658 00:31:14,720 --> 00:31:17,440 Speaker 4: So your story, it's fascinating and there's stuffing to dig 659 00:31:17,480 --> 00:31:19,920 Speaker 4: into there. But you start off taking a look at 660 00:31:19,920 --> 00:31:22,320 Speaker 4: Formatt Capital Management, and this is the owner of the 661 00:31:22,320 --> 00:31:25,920 Speaker 4: world's biggest collection of catastrophe bonds. Can you talk a 662 00:31:25,960 --> 00:31:28,520 Speaker 4: little bit about their strategy and in particular, you know, 663 00:31:28,600 --> 00:31:30,440 Speaker 4: I just want to circle back to a comment that 664 00:31:30,480 --> 00:31:33,240 Speaker 4: you may just now that in this current environment, this 665 00:31:33,360 --> 00:31:35,040 Speaker 4: market is very, very interesting, and I wonder if you 666 00:31:35,080 --> 00:31:37,600 Speaker 4: could talk about how a warming planet is figuring into 667 00:31:37,600 --> 00:31:38,560 Speaker 4: for Met's strategy. 668 00:31:39,240 --> 00:31:42,440 Speaker 8: Sure, so, you know there are always hurricanes and earthquakes, 669 00:31:42,480 --> 00:31:45,040 Speaker 8: but the problem is that more and more people are 670 00:31:45,080 --> 00:31:48,200 Speaker 8: moving to Florida and California and other parts of coastal 671 00:31:48,640 --> 00:31:50,600 Speaker 8: regions in the world where you know, they want to 672 00:31:50,600 --> 00:31:53,160 Speaker 8: have a nice view and a nice seaside experience. But 673 00:31:53,760 --> 00:31:56,560 Speaker 8: those expensive homes are building. When they get hit by 674 00:31:56,560 --> 00:31:59,120 Speaker 8: a storm, they you know, tend to lose a lot 675 00:31:59,160 --> 00:32:02,080 Speaker 8: of money. So that is the real problem, is that 676 00:32:02,160 --> 00:32:04,840 Speaker 8: human beings are moving to these risky areas, and the 677 00:32:04,880 --> 00:32:08,480 Speaker 8: insurance industries either in some places like California, in Florida 678 00:32:08,560 --> 00:32:10,840 Speaker 8: walking away from it. They're not going to ensure people 679 00:32:11,200 --> 00:32:13,880 Speaker 8: the risks are too high, or they're turning to kind 680 00:32:13,880 --> 00:32:16,800 Speaker 8: of instruments like a catastrophe bond to do so. So 681 00:32:16,920 --> 00:32:20,800 Speaker 8: firmat Capital is the world's biggest cat bond investor. Their 682 00:32:20,880 --> 00:32:25,040 Speaker 8: assets are about ten billion dollars and they have a 683 00:32:25,160 --> 00:32:28,600 Speaker 8: very interesting strategy. So, like other cat bond investors, they 684 00:32:28,600 --> 00:32:31,880 Speaker 8: do buy these risk models which help you to predict 685 00:32:31,920 --> 00:32:36,040 Speaker 8: the likelihood of a hurricane occurring in a particular year 686 00:32:36,240 --> 00:32:38,680 Speaker 8: or over two three years. But what they do is 687 00:32:38,680 --> 00:32:42,240 Speaker 8: they add a magic source. Because the co founder of 688 00:32:42,400 --> 00:32:47,400 Speaker 8: this firm, John So, has a physics background, has a 689 00:32:47,400 --> 00:32:51,200 Speaker 8: biophysics degree from Harvard. He's been able to layer an 690 00:32:51,240 --> 00:32:56,000 Speaker 8: extra in a sophistication in trying to predict the likelihood 691 00:32:56,040 --> 00:32:58,960 Speaker 8: of risk and return for each of these potential catastrophes. 692 00:32:59,000 --> 00:33:02,360 Speaker 8: So his buying approach is quite clever and sophisticated and 693 00:33:02,400 --> 00:33:04,960 Speaker 8: he hopes to get an edge from that. So that's 694 00:33:05,040 --> 00:33:08,000 Speaker 8: where Fermat has really you know, they've been involved in 695 00:33:08,000 --> 00:33:12,760 Speaker 8: this market almost inception, and they use this extra edge 696 00:33:13,000 --> 00:33:15,760 Speaker 8: to try and beat the market and other catbon investors. 697 00:33:15,960 --> 00:33:17,960 Speaker 5: And has it worked. What are their returns like. 698 00:33:18,280 --> 00:33:20,719 Speaker 8: Yeah, so they returns last year, which is a very 699 00:33:20,720 --> 00:33:23,680 Speaker 8: good year for all investors, about twenty percent, and I 700 00:33:23,680 --> 00:33:25,600 Speaker 8: think a lot of other investors also came in at 701 00:33:25,640 --> 00:33:28,400 Speaker 8: that level. I should say that the interesting thing about 702 00:33:28,440 --> 00:33:31,360 Speaker 8: cat bonds, it's a really good diversifier. So you know, 703 00:33:31,440 --> 00:33:34,960 Speaker 8: unlike your regular you know, stocks of bonds that fluctuate 704 00:33:35,040 --> 00:33:38,960 Speaker 8: with market movements or the Federal Reserve decisions, a catastrophe 705 00:33:39,000 --> 00:33:43,480 Speaker 8: bonds outcome is down to mother nature. Either she's kind 706 00:33:43,600 --> 00:33:46,800 Speaker 8: or she's unkind. And if you diversify a portfolio with 707 00:33:46,920 --> 00:33:50,080 Speaker 8: cat bonds and you know, you get the benefits of that, 708 00:33:50,280 --> 00:33:53,600 Speaker 8: it's a really good diversitifier that has no correlation with 709 00:33:53,640 --> 00:33:55,440 Speaker 8: the rest of the financial markets. 710 00:33:55,800 --> 00:33:58,520 Speaker 4: Can you talk a little bit about how the current 711 00:33:58,600 --> 00:34:02,400 Speaker 4: environment and the insurance market it is affecting for met's returns, 712 00:34:02,440 --> 00:34:03,960 Speaker 4: because you know, you make the point in the story 713 00:34:04,040 --> 00:34:06,360 Speaker 4: that a lot of insurers are charging more to protect 714 00:34:06,360 --> 00:34:07,720 Speaker 4: customers from devastating weather. 715 00:34:07,920 --> 00:34:10,640 Speaker 8: Well, you know, last year was a record year for 716 00:34:10,680 --> 00:34:15,320 Speaker 8: the issuance of catastrophe bonds, and this year is looking 717 00:34:15,480 --> 00:34:18,399 Speaker 8: likely it's going to be again a pretty solid year, 718 00:34:18,880 --> 00:34:24,200 Speaker 8: and that reflects the insurance industry's desperate need to pass 719 00:34:24,239 --> 00:34:27,960 Speaker 8: on some of this risk beyond the traditional reinsurance industry 720 00:34:28,320 --> 00:34:31,239 Speaker 8: to Wall Street. Wall Street is a huge, you know, 721 00:34:32,400 --> 00:34:36,200 Speaker 8: deep pocket with trillions of dollars at its disposal, a 722 00:34:36,239 --> 00:34:41,360 Speaker 8: lot of you know, risk taking investors, unlike traditional insurance, 723 00:34:41,360 --> 00:34:44,799 Speaker 8: which is a lot more conservative. So as you can 724 00:34:44,840 --> 00:34:48,319 Speaker 8: see from just the number of new issuances that are 725 00:34:48,320 --> 00:34:52,080 Speaker 8: lined up for twenty twenty four that insurers are increasingly 726 00:34:52,160 --> 00:34:55,279 Speaker 8: turning to this market. So one of the issues a 727 00:34:55,320 --> 00:34:59,080 Speaker 8: problem is that secondary perils, as the industry likes to 728 00:34:59,080 --> 00:35:04,359 Speaker 8: call it so flood, wildfires, and thunderstorms are causing more 729 00:35:04,400 --> 00:35:07,160 Speaker 8: and more insurance damage as opposed to you know, a 730 00:35:07,239 --> 00:35:11,640 Speaker 8: hurricane Ian, a Hurricane Katrina like event, and insurers are 731 00:35:11,680 --> 00:35:16,080 Speaker 8: trying to figure out how can they protect their own portfolios, 732 00:35:16,120 --> 00:35:19,200 Speaker 8: their own balance sheets, but also provide insurance to people 733 00:35:19,239 --> 00:35:22,440 Speaker 8: when you have more of these type of events occurring, 734 00:35:22,520 --> 00:35:26,759 Speaker 8: this sort of medium size five ten billion dollar disasters 735 00:35:27,480 --> 00:35:29,880 Speaker 8: versus you know, the one sort a thirty year event, 736 00:35:30,480 --> 00:35:32,719 Speaker 8: and at the same time try to make sure that 737 00:35:32,800 --> 00:35:36,560 Speaker 8: you know their balance sheet is protected. That's not so 738 00:35:36,640 --> 00:35:39,120 Speaker 8: easy to do because we don't have much data on 739 00:35:39,200 --> 00:35:42,600 Speaker 8: these kind of secondary perils. And also the models that 740 00:35:42,640 --> 00:35:47,080 Speaker 8: are used that give an investor some certainty that okay, 741 00:35:47,120 --> 00:35:51,840 Speaker 8: they don't stand to lose. You know, typically rare hurricane 742 00:35:51,920 --> 00:35:54,520 Speaker 8: the loss estimate is somewhere in the region of two percent. 743 00:35:54,680 --> 00:35:57,240 Speaker 8: It's fairly low. The return you can get is something 744 00:35:57,360 --> 00:36:00,920 Speaker 8: like eight nine percent. So as long as that clarity 745 00:36:01,040 --> 00:36:05,239 Speaker 8: isn't there for these tornadoes, thunderstorms, ice storms that you 746 00:36:05,320 --> 00:36:08,520 Speaker 8: see in Texas, as long as that's happening, the insurance 747 00:36:08,560 --> 00:36:11,000 Speaker 8: industry is going to find it difficult to access the 748 00:36:11,040 --> 00:36:14,239 Speaker 8: camp bond market to cover those kind of perils which 749 00:36:14,280 --> 00:36:15,440 Speaker 8: are becoming more common. 750 00:36:15,880 --> 00:36:21,920 Speaker 3: Gotam, what are the main risk events that now a 751 00:36:22,040 --> 00:36:25,520 Speaker 3: CEO is modeling that may or may not happen, like 752 00:36:25,600 --> 00:36:27,520 Speaker 3: because he basically has a model what he thinks will 753 00:36:27,520 --> 00:36:30,040 Speaker 3: happen and then either take a little bit more risk 754 00:36:30,120 --> 00:36:33,239 Speaker 3: but for more reward, or avoid that altogether. But what 755 00:36:33,320 --> 00:36:34,920 Speaker 3: are the things you're seeing right now? 756 00:36:35,160 --> 00:36:38,239 Speaker 8: Well, you know, they own something like two hundred and 757 00:36:38,280 --> 00:36:42,000 Speaker 8: fifty or two hundred and eighty individual catastrophe bonds and 758 00:36:42,040 --> 00:36:44,520 Speaker 8: the whole market maybe has three hundred and twenty or so. 759 00:36:44,600 --> 00:36:47,399 Speaker 8: These are rough figures, so they are very dominant. They 760 00:36:47,400 --> 00:36:51,080 Speaker 8: own a vast swath of this whole market. You know, 761 00:36:51,120 --> 00:36:57,000 Speaker 8: that could include a tsunami campbond for Japan, or typhoon 762 00:36:57,080 --> 00:37:01,160 Speaker 8: camp bond for the Philippines, a hurricane cat bond for Mexico, 763 00:37:01,600 --> 00:37:05,800 Speaker 8: all kinds of different events. So I think their modeling 764 00:37:06,080 --> 00:37:11,919 Speaker 8: is primarily focused still on the big potential disasters such 765 00:37:11,920 --> 00:37:17,080 Speaker 8: as hurricanes or an earthquake in California or wildfires in California, 766 00:37:17,520 --> 00:37:20,400 Speaker 8: and less so on things like thunderstorms, because again they 767 00:37:20,440 --> 00:37:24,320 Speaker 8: don't really have the data or the sophisticated models yet, 768 00:37:24,480 --> 00:37:27,279 Speaker 8: but they're building up that because that's where the catastrophe 769 00:37:27,360 --> 00:37:29,200 Speaker 8: bond market is going to grow. It's going to move 770 00:37:29,239 --> 00:37:32,279 Speaker 8: away from the kind of Hurricane Katrina like events, the 771 00:37:32,360 --> 00:37:35,759 Speaker 8: rare of big disaster events, and more to you know, 772 00:37:36,080 --> 00:37:39,480 Speaker 8: Hurricane Sandy like event, which you know there is a 773 00:37:39,480 --> 00:37:43,560 Speaker 8: catbond for. You know, the New York Subway system has 774 00:37:43,600 --> 00:37:46,360 Speaker 8: acquired one hundred million catbord. I think they've renewed perhaps 775 00:37:46,480 --> 00:37:49,439 Speaker 8: the third time now to protect the subways from going 776 00:37:49,520 --> 00:37:53,160 Speaker 8: underwater should a Hurricane Sandy like event hit the city. 777 00:37:53,520 --> 00:37:56,280 Speaker 4: Head on our thanks to Gatin Nike. He's a Bloomberg 778 00:37:56,320 --> 00:37:58,680 Speaker 4: senior editor covering ESG Investing. 779 00:37:58,520 --> 00:38:03,040 Speaker 1: This is the Bloomberg In Intelligence podcast, available on apples, Spotify, 780 00:38:03,239 --> 00:38:06,920 Speaker 1: and anywhere else you get your podcasts. Listen live each weekday, 781 00:38:07,040 --> 00:38:10,000 Speaker 1: ten am to noon Eastern on Bloomberg dot com, the 782 00:38:10,120 --> 00:38:13,560 Speaker 1: iHeartRadio app tune In, and the Bloomberg Business app. You 783 00:38:13,600 --> 00:38:16,759 Speaker 1: can also watch us live every weekday on YouTube and 784 00:38:16,960 --> 00:38:18,560 Speaker 1: always on the Bloomberg terminal