1 00:00:00,240 --> 00:00:11,240 Speaker 1: Bloomberg Audio, Studios, podcasts, radio News. This is Bloomberg Intelligence 2 00:00:11,320 --> 00:00:13,400 Speaker 1: with Scarletfoo and Paul Sweeney. 3 00:00:13,520 --> 00:00:15,600 Speaker 2: How do you think the FED is looking at tariffs? 4 00:00:15,760 --> 00:00:16,960 Speaker 2: The uncertainty of terriffs. 5 00:00:17,040 --> 00:00:19,119 Speaker 3: Let's take a look at the sectors and how they. 6 00:00:19,120 --> 00:00:21,360 Speaker 2: Performed a lot of investors getting whip salt every day 7 00:00:21,400 --> 00:00:22,160 Speaker 2: by news. 8 00:00:21,880 --> 00:00:26,040 Speaker 1: Events, breaking market headlines, and corporate news from across the globe. 9 00:00:26,040 --> 00:00:28,639 Speaker 4: Could we see a market disruption of market events? 10 00:00:28,720 --> 00:00:30,760 Speaker 2: So people just too exuberant out there? 11 00:00:30,880 --> 00:00:33,479 Speaker 4: You see some so called low quality stocks driving this 12 00:00:33,520 --> 00:00:34,320 Speaker 4: short term rally. 13 00:00:34,360 --> 00:00:39,120 Speaker 1: Bloomberg Intelligence with Scarletfoo and Paul Sweeney on Bloomberg Radio, 14 00:00:39,320 --> 00:00:41,200 Speaker 1: YouTube and Bloomberg Originals. 15 00:00:42,200 --> 00:00:44,880 Speaker 3: I'm Paul Sweeney and I'm marm Melinda filling in for Scarlettfoo. 16 00:00:45,000 --> 00:00:47,360 Speaker 2: On today's Bloomberg Intelligence Show. We dig inside the big 17 00:00:47,360 --> 00:00:49,960 Speaker 2: business stories impacting Wall Street and the global markets. 18 00:00:50,200 --> 00:00:52,440 Speaker 3: Each and every week, we provide in depth research and 19 00:00:52,560 --> 00:00:54,480 Speaker 3: data on some of the two thousand companies and one 20 00:00:54,560 --> 00:00:57,280 Speaker 3: hundred and thirty industries are analysts cover worldwide. 21 00:00:57,360 --> 00:01:00,120 Speaker 2: Today, we'll look at why the cloud based software company 22 00:01:00,160 --> 00:01:02,800 Speaker 2: Salesforce gave a strong outlook for sales in the current quarter. 23 00:01:03,080 --> 00:01:05,480 Speaker 3: Class well dive into why shares of the aerospace company 24 00:01:05,520 --> 00:01:08,480 Speaker 3: Airbus plunged and how this might affect the delivery of 25 00:01:08,480 --> 00:01:10,000 Speaker 3: its newly produced jets. 26 00:01:10,160 --> 00:01:12,280 Speaker 2: But first we begin with some news in the casino 27 00:01:12,360 --> 00:01:13,200 Speaker 2: and gaming space. 28 00:01:13,560 --> 00:01:16,240 Speaker 3: This week, New York Mets owner Steve Cohen won approval 29 00:01:16,280 --> 00:01:18,800 Speaker 3: to operate a casino next to City Fields and Queens. 30 00:01:19,080 --> 00:01:22,200 Speaker 2: It's one of the three projects select different gambling licenses 31 00:01:22,240 --> 00:01:24,040 Speaker 2: in New York City, and this was done by the 32 00:01:24,080 --> 00:01:26,760 Speaker 2: State Gaming Commission's Facility Location Board. 33 00:01:27,080 --> 00:01:29,720 Speaker 3: Cohen, the Hedge Fund Mobile submitted an eight billion dollar 34 00:01:29,840 --> 00:01:33,080 Speaker 3: casino proposal with partner hard Rock International and was picked 35 00:01:33,080 --> 00:01:37,080 Speaker 3: alongside genting groups Resorts World and Ballys. These three projects 36 00:01:37,080 --> 00:01:40,440 Speaker 3: are expected to generate significant revenue and create thousands of 37 00:01:40,520 --> 00:01:41,160 Speaker 3: jobs for. 38 00:01:41,200 --> 00:01:43,400 Speaker 2: More and all. This guest host Alex Simonova and I 39 00:01:43,480 --> 00:01:46,080 Speaker 2: were joined by Brian Eggert, Bloomberg Intelligence senior Gaming and 40 00:01:46,160 --> 00:01:49,080 Speaker 2: launching analysts. We first asked Brian to talk about what 41 00:01:49,200 --> 00:01:51,919 Speaker 2: the licenses represent and where we go from here. 42 00:01:52,040 --> 00:01:55,520 Speaker 5: So this is a fairly protractive process involving ultimately di 43 00:01:55,560 --> 00:01:57,840 Speaker 5: selection of three recipients. By the way, the only three 44 00:01:57,920 --> 00:02:00,840 Speaker 5: left in the running after a few others were limited 45 00:02:00,960 --> 00:02:06,080 Speaker 5: and dropped out, and really it authorized resort casinos for 46 00:02:06,280 --> 00:02:08,760 Speaker 5: the downstate New York area, mostly in New York City. 47 00:02:08,800 --> 00:02:12,320 Speaker 5: And as it turns out, the three qualified casino applicants, 48 00:02:12,320 --> 00:02:14,800 Speaker 5: if you will, really are are in New York City 49 00:02:14,800 --> 00:02:16,880 Speaker 5: but outside the Borough of Manhattan itself. 50 00:02:17,240 --> 00:02:21,079 Speaker 4: Brian, just looking at your note on these license approvals, 51 00:02:21,120 --> 00:02:24,440 Speaker 4: you write that they face a narrow path to decent 52 00:02:24,520 --> 00:02:26,480 Speaker 4: returns on investment. Can you please talk to us a 53 00:02:26,520 --> 00:02:27,680 Speaker 4: little bit more about that idea? 54 00:02:28,800 --> 00:02:30,880 Speaker 5: Sure? So, what we assume for those resorts is they 55 00:02:30,919 --> 00:02:34,840 Speaker 5: will get what I would call a gaming revenue premium 56 00:02:34,880 --> 00:02:38,360 Speaker 5: and room rate premium of ten twenty percent to other 57 00:02:39,000 --> 00:02:43,120 Speaker 5: kind of high end urban area resorts such as the 58 00:02:43,120 --> 00:02:47,799 Speaker 5: Burgata and Atlantic City wins Encore in Boston. However, are 59 00:02:47,880 --> 00:02:50,760 Speaker 5: concerned if in terms of the return prospects are that 60 00:02:51,120 --> 00:02:54,160 Speaker 5: development costs are quite high and perhaps some of the 61 00:02:54,240 --> 00:02:58,520 Speaker 5: targeted non gaming contribution elements might be a bit ambitious. 62 00:02:58,520 --> 00:03:00,840 Speaker 5: So for that reason, when we worked the numbers, we 63 00:03:00,919 --> 00:03:04,040 Speaker 5: came up with something like a ten percent return on investment, 64 00:03:04,080 --> 00:03:07,920 Speaker 5: which is certainly a bit less than most operators would 65 00:03:07,919 --> 00:03:10,400 Speaker 5: expect to attain in these regional markets. 66 00:03:11,120 --> 00:03:14,079 Speaker 2: So I'm thinking here I mean again, I'm just thinking 67 00:03:14,080 --> 00:03:17,080 Speaker 2: about Steve Cohen's I was looking at his plans in 68 00:03:17,120 --> 00:03:20,160 Speaker 2: conjunction with his city field. He obviously he owns the Mets. 69 00:03:20,560 --> 00:03:23,919 Speaker 2: City field is out there, the National Tennis centers out there. 70 00:03:24,000 --> 00:03:26,200 Speaker 2: We had the world's fair situations, so there's a ton 71 00:03:26,240 --> 00:03:29,480 Speaker 2: of opportunity out there. It seems like these are going 72 00:03:29,520 --> 00:03:35,040 Speaker 2: to be more retail hotel than casino. How do you 73 00:03:35,040 --> 00:03:36,920 Speaker 2: think the mix of revenue is going to be there? 74 00:03:37,680 --> 00:03:39,960 Speaker 5: So this certainly is I think when we work the numbers, 75 00:03:40,760 --> 00:03:45,400 Speaker 5: we assume that with respect to either food and beverage 76 00:03:45,440 --> 00:03:49,080 Speaker 5: or retail entertainment revenue, those will be fairly sizable chunks 77 00:03:49,080 --> 00:03:53,360 Speaker 5: of the overall revenue PI probably cuatively close to half, 78 00:03:53,440 --> 00:03:57,280 Speaker 5: which is true of many kind of gaming resorts in 79 00:03:58,840 --> 00:04:01,480 Speaker 5: attractive environments get a lot of non gaming revenue. I 80 00:04:01,520 --> 00:04:04,400 Speaker 5: think the same will be true here. The question is 81 00:04:04,680 --> 00:04:06,880 Speaker 5: will it be enough and will be margins which we 82 00:04:07,280 --> 00:04:10,120 Speaker 5: take to be about thirty percent, be sufficient to get 83 00:04:10,200 --> 00:04:12,840 Speaker 5: a good return. But certainly, you know the logic of 84 00:04:12,840 --> 00:04:15,240 Speaker 5: having at nexas city field makes a lot of sense. 85 00:04:15,320 --> 00:04:18,440 Speaker 5: You know, the other locations valleys and a golf course 86 00:04:18,480 --> 00:04:21,320 Speaker 5: in the Bronx. You know, the the resorts world in 87 00:04:21,440 --> 00:04:25,359 Speaker 5: Queen's pretty much expanding and existing facility all have their merit. 88 00:04:25,400 --> 00:04:28,320 Speaker 5: The question is will be enough to get a decent return, 89 00:04:28,400 --> 00:04:32,160 Speaker 5: But certainly some of these locations have rational prospects. 90 00:04:32,760 --> 00:04:35,360 Speaker 4: What does this victory for these three companies mean for 91 00:04:35,400 --> 00:04:39,000 Speaker 4: their competitors like Sands MGM, When where do they go 92 00:04:39,080 --> 00:04:39,559 Speaker 4: from here? 93 00:04:40,560 --> 00:04:43,360 Speaker 5: So to be queer, You know, Sans exited this process 94 00:04:43,480 --> 00:04:48,280 Speaker 5: back in April. When exited in May, it's Hudson York 95 00:04:48,360 --> 00:04:52,599 Speaker 5: project because of community opposition at MGM in October because 96 00:04:52,600 --> 00:04:54,560 Speaker 5: of the licensed terms. But bear in mind that they 97 00:04:54,560 --> 00:04:57,479 Speaker 5: do have other prospects. You know, when is developing a 98 00:04:57,640 --> 00:05:01,720 Speaker 5: UAE resort of its own, gm is building in Osaka, Japan. 99 00:05:02,680 --> 00:05:04,320 Speaker 5: They all can buy back in their own stock. So 100 00:05:04,320 --> 00:05:09,200 Speaker 5: I think they're weighing this particular opportunity relative to other 101 00:05:09,279 --> 00:05:10,480 Speaker 5: development prospects. 102 00:05:10,960 --> 00:05:12,840 Speaker 2: So we're going to get the licenses by year end. 103 00:05:14,240 --> 00:05:16,800 Speaker 2: What's the time taime if anybody any of these three 104 00:05:17,240 --> 00:05:19,600 Speaker 2: licensed winners lay out of timetable for getting a shovel 105 00:05:19,600 --> 00:05:21,880 Speaker 2: in the ground and maybe even opening the doors. 106 00:05:22,680 --> 00:05:25,800 Speaker 5: So I think it'll vary by operator. But the expectations 107 00:05:25,800 --> 00:05:30,120 Speaker 5: that these resorts will generally open by twenty thirty or so. 108 00:05:30,560 --> 00:05:32,599 Speaker 5: It'll take a few years to develop. There was always 109 00:05:32,600 --> 00:05:37,200 Speaker 5: the possibility of construction challenges, but that's the target. And 110 00:05:37,240 --> 00:05:40,480 Speaker 5: of course our related to concerns since you mentioned MGM 111 00:05:41,080 --> 00:05:44,839 Speaker 5: was MGM Ballely's Caesars O operaate casinos in Atlantic City, 112 00:05:45,480 --> 00:05:50,000 Speaker 5: and you know, the proximity to Alantic City of resorts 113 00:05:50,040 --> 00:05:54,040 Speaker 5: with casino elements at this caliber certainly presents a potential 114 00:05:54,120 --> 00:05:56,000 Speaker 5: competitive challenge to Atlantic City itself. 115 00:05:56,600 --> 00:06:01,120 Speaker 2: AC. That's tough. That's tough because I would see you know, 116 00:06:01,480 --> 00:06:03,120 Speaker 2: on the parkway, Brian, I know you see it too. 117 00:06:03,480 --> 00:06:05,760 Speaker 2: We have for years, for twenty thirty years, we've seen 118 00:06:05,800 --> 00:06:09,080 Speaker 2: the limousines from New York City going down the Parkway 119 00:06:09,120 --> 00:06:11,520 Speaker 2: to AC. That's going to get it impacted, isn't. 120 00:06:11,279 --> 00:06:15,560 Speaker 5: It It will? I think you know, some operaters Burgata, 121 00:06:15,600 --> 00:06:18,960 Speaker 5: for example, a hard rock may hold up better than others. 122 00:06:19,040 --> 00:06:21,080 Speaker 5: But you know, there's always a challenge when you've got 123 00:06:21,400 --> 00:06:25,200 Speaker 5: this much additional gaming capacity with resort elements opening up 124 00:06:25,800 --> 00:06:29,720 Speaker 5: in relative close proximity to a to a key Atlantic 125 00:06:29,720 --> 00:06:30,680 Speaker 5: City feeder market. 126 00:06:31,160 --> 00:06:34,039 Speaker 3: Our thanks to Brian Eger, Bloomberg Intelligence Senior Gaming and 127 00:06:34,080 --> 00:06:35,039 Speaker 3: Lodging analysts. 128 00:06:35,080 --> 00:06:36,599 Speaker 2: We move now to the retail space. 129 00:06:36,800 --> 00:06:39,840 Speaker 3: This week, the department store chains Macy's posted better than 130 00:06:39,839 --> 00:06:42,839 Speaker 3: expected results last quarter. However, shares dropped if the company 131 00:06:42,880 --> 00:06:45,480 Speaker 3: pointed to a potential for soft demand from low income 132 00:06:45,520 --> 00:06:46,680 Speaker 3: shoppers for the current quarter. 133 00:06:47,120 --> 00:06:49,400 Speaker 2: For more, Nora and I were joined by Mary Ross 134 00:06:49,440 --> 00:06:52,520 Speaker 2: and Gilbert Bloomberg Intelligence senior equity analyst covering retail. 135 00:06:52,680 --> 00:06:55,360 Speaker 3: We first asked Mary to break down Macy's most recent quarter. 136 00:06:55,600 --> 00:06:58,640 Speaker 6: We saw, actually, I think great results coming out of 137 00:06:58,680 --> 00:07:03,120 Speaker 6: Macy's see but the company put out conservative fourth quarter 138 00:07:03,240 --> 00:07:06,560 Speaker 6: guidance and that's really what they always do. They seek 139 00:07:06,600 --> 00:07:09,440 Speaker 6: to beat their numbers, and so that guidance came in 140 00:07:09,640 --> 00:07:11,920 Speaker 6: very close, you know, at the high end. It's right 141 00:07:11,920 --> 00:07:15,040 Speaker 6: around where analysts are because they already saw strong results 142 00:07:15,080 --> 00:07:19,240 Speaker 6: come in from other retailers. But we think, when we 143 00:07:19,280 --> 00:07:23,000 Speaker 6: think about it, we think there's upside here. So we 144 00:07:23,160 --> 00:07:27,680 Speaker 6: really view the results as look Macy's name plate because 145 00:07:27,680 --> 00:07:29,640 Speaker 6: of all the changes that they're making, and what that 146 00:07:29,720 --> 00:07:32,920 Speaker 6: means is they're bringing in more relevant brands that are 147 00:07:32,920 --> 00:07:36,679 Speaker 6: resonating with their consumer. Not only that, but the stores 148 00:07:36,720 --> 00:07:41,400 Speaker 6: look brighter. There's really kind of exciting music in the stores. 149 00:07:41,520 --> 00:07:46,280 Speaker 6: The store associates are more engaged with the customer. We've 150 00:07:46,280 --> 00:07:49,080 Speaker 6: noticed that on our channel text, particularly on Black Friday, 151 00:07:49,480 --> 00:07:52,280 Speaker 6: we saw more traffic in the store than we've seen 152 00:07:52,320 --> 00:07:56,280 Speaker 6: in years past. So we think that the changes that 153 00:07:56,480 --> 00:08:00,360 Speaker 6: CEO Tony Sprain is making and he's really making his 154 00:08:00,480 --> 00:08:04,640 Speaker 6: cues from what he's done at Bloomingdale's, it's resonating, it's working, 155 00:08:04,680 --> 00:08:07,600 Speaker 6: and so we think this momentum is building and we 156 00:08:07,680 --> 00:08:09,840 Speaker 6: certainly saw it in the third quarter numbers with comp 157 00:08:09,920 --> 00:08:13,960 Speaker 6: sales two point seven percent for the Go Forwards stores, 158 00:08:14,480 --> 00:08:17,800 Speaker 6: and so with that, I mean that's a big improvement sequentially, 159 00:08:18,200 --> 00:08:20,600 Speaker 6: and so we think that's building, you know, going into 160 00:08:20,640 --> 00:08:23,720 Speaker 6: the fourth quarter and just with you know, the constant 161 00:08:23,760 --> 00:08:25,240 Speaker 6: improvement that we're seeing there. 162 00:08:25,720 --> 00:08:27,920 Speaker 3: So when most people think about the retail space right now, 163 00:08:27,960 --> 00:08:31,160 Speaker 3: a lot of people think about the transition to e commerce, 164 00:08:31,160 --> 00:08:33,040 Speaker 3: but it sounds as though, from what you're explaining, a 165 00:08:33,040 --> 00:08:35,280 Speaker 3: lot of people are going there in person. I mean, 166 00:08:35,320 --> 00:08:38,040 Speaker 3: I'm looking at Coals, I'm looking at Dillard's. What are 167 00:08:38,080 --> 00:08:41,360 Speaker 3: they doing in particular that's really attracting customers to come 168 00:08:41,400 --> 00:08:44,800 Speaker 3: through the doors. Is it also collaborations with celebrities by chance? 169 00:08:45,360 --> 00:08:48,280 Speaker 6: Yes, you raised a valid point, and it is. It 170 00:08:48,320 --> 00:08:53,440 Speaker 6: does include collaborations. So for example, they Aqua you know, 171 00:08:53,520 --> 00:08:56,839 Speaker 6: they're under their Bloomingdale's brand currently has a collapse going 172 00:08:56,880 --> 00:09:02,120 Speaker 6: out with a designer out to move on and so yes, 173 00:09:02,160 --> 00:09:06,240 Speaker 6: these collaborations also even you know, they'll have some events. 174 00:09:06,800 --> 00:09:09,439 Speaker 7: But all of that is is certainly drawing. 175 00:09:09,200 --> 00:09:12,480 Speaker 6: In new customers and I think Macy's nameplate could certainly 176 00:09:12,520 --> 00:09:15,760 Speaker 6: do more on that end. They had their first collab 177 00:09:15,800 --> 00:09:18,680 Speaker 6: with their on thirty fourth brand this year, but we 178 00:09:18,720 --> 00:09:20,800 Speaker 6: think we're going to see more next year because if 179 00:09:20,840 --> 00:09:23,320 Speaker 6: you look at what Dillard's has been doing over the 180 00:09:23,360 --> 00:09:27,280 Speaker 6: last few years, and they have a different business model 181 00:09:27,320 --> 00:09:30,800 Speaker 6: than Macy's does. They're not really promotional. For example, for 182 00:09:31,160 --> 00:09:34,280 Speaker 6: Black Friday, they just had clearance sales and it was 183 00:09:34,440 --> 00:09:37,520 Speaker 6: pretty comparable to last year, so that didn't mean that 184 00:09:37,559 --> 00:09:39,520 Speaker 6: the rest of the merchandise was on sale. 185 00:09:39,559 --> 00:09:43,000 Speaker 7: Macy's the you know, is far more promotional. 186 00:09:43,360 --> 00:09:47,880 Speaker 6: But by doing collaborations, you know, by getting celebrities involved. 187 00:09:47,960 --> 00:09:50,840 Speaker 6: So for example, for the holiday, they have Jennifer Hudson 188 00:09:51,960 --> 00:09:56,120 Speaker 6: that's you know, fronting their campaign for the holiday, and 189 00:09:56,120 --> 00:10:01,320 Speaker 6: they're also engaging with social influencers. Yes, all of that 190 00:10:01,440 --> 00:10:04,400 Speaker 6: is resonating. We're seeing it with other brands, like for 191 00:10:04,440 --> 00:10:08,520 Speaker 6: example with American Eagle, which just tapped Martha Stewart and 192 00:10:08,559 --> 00:10:10,400 Speaker 6: that that's appealing to gen Z. 193 00:10:11,360 --> 00:10:13,320 Speaker 3: Oh wow, so one. 194 00:10:14,520 --> 00:10:18,679 Speaker 6: Yeah, so these bold campaigns that these brands are doing, 195 00:10:18,800 --> 00:10:22,880 Speaker 6: Macy's is also getting involved there and they're dipping there 196 00:10:22,880 --> 00:10:24,720 Speaker 6: to I would say, they're dipping their toe in the water. 197 00:10:24,760 --> 00:10:27,880 Speaker 6: But I think we're going to see that increase, you know, 198 00:10:27,960 --> 00:10:31,320 Speaker 6: and build as we get into twenty twenty six. And 199 00:10:31,360 --> 00:10:33,760 Speaker 6: when you talk about the digital business, because of course 200 00:10:33,760 --> 00:10:37,600 Speaker 6: you're always hearing let's say, stronger growth on digital. For example, 201 00:10:37,640 --> 00:10:40,719 Speaker 6: when we looked at Black Friday, you know, over the 202 00:10:40,760 --> 00:10:44,880 Speaker 6: weekend through Cyber Monday, the sales strength was really led 203 00:10:45,120 --> 00:10:48,720 Speaker 6: by digital. Digital was up double digits versus you know, 204 00:10:48,840 --> 00:10:51,080 Speaker 6: load to mid single digits for in store. 205 00:10:51,600 --> 00:10:55,760 Speaker 7: So I think that's really positive there. 206 00:10:55,840 --> 00:10:57,760 Speaker 6: But so when we look at Macy's, a third of 207 00:10:57,800 --> 00:11:00,920 Speaker 6: their sales come from digital, so still in the store 208 00:11:01,320 --> 00:11:04,440 Speaker 6: is very big, but it's also omni channel well, the 209 00:11:04,480 --> 00:11:07,520 Speaker 6: ability to buy online, take back in store, or buy 210 00:11:07,559 --> 00:11:08,840 Speaker 6: online pickup in store. 211 00:11:09,480 --> 00:11:11,840 Speaker 2: Just real quick, thirty seconds, what's macy saying about the 212 00:11:11,840 --> 00:11:12,680 Speaker 2: consumer out there. 213 00:11:13,480 --> 00:11:16,240 Speaker 6: Yeah, So they're saying that the lower end consumer is 214 00:11:16,360 --> 00:11:20,280 Speaker 6: really feeling pinched, and that's where they're seeing some challenges 215 00:11:20,320 --> 00:11:22,440 Speaker 6: on some of the price increases on their lower price 216 00:11:22,480 --> 00:11:26,520 Speaker 6: point items. But the higher middle income, in the higher 217 00:11:26,559 --> 00:11:31,800 Speaker 6: income consumer is resilient and they haven't flashed or batter 218 00:11:31,840 --> 00:11:35,560 Speaker 6: DENI with higher prices that they took to offset tariffs, 219 00:11:35,559 --> 00:11:36,520 Speaker 6: and they're still buying. 220 00:11:37,120 --> 00:11:40,320 Speaker 2: Thanks to Mary Ross Gilbert Bloomberg Intelligence, senior equity analyst 221 00:11:40,360 --> 00:11:41,000 Speaker 2: covering retail. 222 00:11:41,240 --> 00:11:43,120 Speaker 3: Coming up, we continue in the retail space and look 223 00:11:43,160 --> 00:11:45,319 Speaker 3: at earnings from the discout retailer dollar. 224 00:11:45,080 --> 00:11:49,320 Speaker 2: Tree listening to Bloomberg Intelligence on Bloomberg Radio, providing research 225 00:11:49,360 --> 00:11:51,240 Speaker 2: and data on two thousand companies and one hundred and 226 00:11:51,280 --> 00:11:51,960 Speaker 2: thirty industries. 227 00:11:52,120 --> 00:11:54,520 Speaker 3: You can access Bloomberg Intelligence via b I go on 228 00:11:54,600 --> 00:11:56,959 Speaker 3: the terminal. I'm normal Linda, and I'm Paul. 229 00:11:56,800 --> 00:11:58,320 Speaker 2: Sweeney, and this is Bloomberg. 230 00:12:02,679 --> 00:12:07,199 Speaker 1: This is Bloomberg Intelligence with Scarlett Foo and Paul Sweeney 231 00:12:07,520 --> 00:12:08,840 Speaker 1: on Bloomberg Radio. 232 00:12:09,600 --> 00:12:11,720 Speaker 3: I'm Paul Sweeney and I'm normal Linda, filling in for 233 00:12:11,720 --> 00:12:12,280 Speaker 3: Scarlet Foo. 234 00:12:12,640 --> 00:12:15,680 Speaker 2: We continue into retail space. This week, dollar Tree reported 235 00:12:15,679 --> 00:12:18,600 Speaker 2: better than expected profit and raised its full year outlook. 236 00:12:18,840 --> 00:12:21,079 Speaker 3: It's a sign that the discount retailer is capturing more 237 00:12:21,080 --> 00:12:23,719 Speaker 3: spending from stretched shoppers. For more of this, Paul and 238 00:12:23,760 --> 00:12:26,559 Speaker 3: I were joined by Lilly Meyer, Bloomberg Retail reporter. 239 00:12:26,480 --> 00:12:29,360 Speaker 2: First ass Lily to break down Dollar Tree's most recent quarter. 240 00:12:29,600 --> 00:12:29,800 Speaker 8: Yeah. 241 00:12:29,800 --> 00:12:33,079 Speaker 9: So Dollar Tree did well this quarter at matt expectations 242 00:12:33,160 --> 00:12:36,880 Speaker 9: on revenue and same store sales, and it raised its 243 00:12:37,200 --> 00:12:40,600 Speaker 9: profit outlook for the year. I think they really have 244 00:12:40,720 --> 00:12:44,160 Speaker 9: hit a niche in being able to capture consumers, both 245 00:12:44,160 --> 00:12:47,640 Speaker 9: lower end consumers who need cheaper goods and then high 246 00:12:47,720 --> 00:12:49,840 Speaker 9: income consumers who are looking to trade down. 247 00:12:50,360 --> 00:12:52,800 Speaker 3: So, I mean, what do we think about elasticity of 248 00:12:52,880 --> 00:12:54,960 Speaker 3: the lower end consumer right now? Because I mean, if 249 00:12:55,000 --> 00:12:56,760 Speaker 3: you think about Walmart, I used to think of this 250 00:12:56,800 --> 00:12:59,680 Speaker 3: as a company that you know, was a cheaper place 251 00:12:59,679 --> 00:13:01,360 Speaker 3: to show, but it seems as though it's appealing to 252 00:13:01,480 --> 00:13:04,439 Speaker 3: multiple consumer types. But it seems as a dollar Tree 253 00:13:04,480 --> 00:13:06,720 Speaker 3: really is a great place for the lower end consumer. 254 00:13:07,040 --> 00:13:09,760 Speaker 9: Yeah, and actually recently dollar Tree has been looking to 255 00:13:09,840 --> 00:13:12,720 Speaker 9: kind of break into that higher income shopper as well. 256 00:13:12,800 --> 00:13:16,200 Speaker 9: So it has this pricing strategy, so it has some 257 00:13:16,480 --> 00:13:19,360 Speaker 9: products that are still cheaper, but then it has some 258 00:13:19,520 --> 00:13:22,480 Speaker 9: it's getting more products that are more expensive. 259 00:13:23,440 --> 00:13:27,920 Speaker 2: What is Dollar Tree saying about its core consumer out there? 260 00:13:28,520 --> 00:13:30,319 Speaker 2: Who is that core consumer and how are they behaving? 261 00:13:30,679 --> 00:13:32,960 Speaker 9: Yeah, so I think it's core consumer is still a 262 00:13:33,040 --> 00:13:35,960 Speaker 9: lower income shopper. Eighty five percent of their products are 263 00:13:36,000 --> 00:13:38,560 Speaker 9: two dollars an under, so they really still have a 264 00:13:38,559 --> 00:13:39,200 Speaker 9: lot of value. 265 00:13:39,280 --> 00:13:40,239 Speaker 3: So they're seeing. 266 00:13:39,960 --> 00:13:43,200 Speaker 9: Those shoppers continue to go in. But this quarter they 267 00:13:43,200 --> 00:13:46,680 Speaker 9: saw traffic down and they attributed that to tariff increases. 268 00:13:46,920 --> 00:13:48,720 Speaker 3: But what's the takeaway in terms of the outlook. I mean, 269 00:13:48,760 --> 00:13:50,880 Speaker 3: you talked about tariff still being a drag here. 270 00:13:51,240 --> 00:13:53,680 Speaker 9: Yeah, so tariffs will really dragged this quarter. They said 271 00:13:53,679 --> 00:13:55,679 Speaker 9: that's going to lessen, So I think this was the 272 00:13:55,760 --> 00:13:59,160 Speaker 9: quarter where we're really seeing the biggest tariff impact. It'll 273 00:13:59,200 --> 00:14:02,760 Speaker 9: be really interesting to see what they predict for consumers 274 00:14:02,960 --> 00:14:06,400 Speaker 9: next year. I'm interested to hear about that and also 275 00:14:06,440 --> 00:14:08,440 Speaker 9: what they see for holiday if they continue to see 276 00:14:08,480 --> 00:14:10,760 Speaker 9: hire income shoppers trading down for gifts. 277 00:14:11,000 --> 00:14:14,920 Speaker 2: Is the dollar stores do they see a surgeon sales 278 00:14:15,240 --> 00:14:17,760 Speaker 2: seasonal surge and sales from holiday sales that Do they 279 00:14:17,800 --> 00:14:19,760 Speaker 2: see that like a department store would. 280 00:14:20,080 --> 00:14:22,080 Speaker 9: Yeah, I don't know if it's the same surge, but 281 00:14:22,240 --> 00:14:24,120 Speaker 9: you know, they sell a lot of gift wrapping and 282 00:14:24,240 --> 00:14:27,360 Speaker 9: gift bags and some of those smaller gifts stocking stuffer, 283 00:14:27,440 --> 00:14:29,000 Speaker 9: so I think they see a lot of that around 284 00:14:29,040 --> 00:14:29,680 Speaker 9: the holidays. 285 00:14:30,160 --> 00:14:31,880 Speaker 3: So what are we seeing in terms of just the 286 00:14:31,880 --> 00:14:34,120 Speaker 3: broader read on the retail space? This kind of gives 287 00:14:34,200 --> 00:14:35,880 Speaker 3: us a picture of the lower end consumer, But what 288 00:14:35,920 --> 00:14:37,040 Speaker 3: are you seeing across the board? 289 00:14:37,400 --> 00:14:40,440 Speaker 9: So broadly, we're really still seeing consumer spend, So there 290 00:14:40,440 --> 00:14:43,000 Speaker 9: hasn't been that massive pullback that I think some of 291 00:14:43,040 --> 00:14:46,280 Speaker 9: us were imagining might happen. We're still seeing consumer spend, 292 00:14:46,320 --> 00:14:48,640 Speaker 9: but they're really value driven, so they're looking for the 293 00:14:48,640 --> 00:14:51,800 Speaker 9: best deals they can get. They're trading down when they 294 00:14:51,840 --> 00:14:53,920 Speaker 9: need to, They're stocking up on essentials. 295 00:14:54,880 --> 00:14:59,440 Speaker 2: How promotional are retailers right now? Because I'm in I know, 296 00:14:59,760 --> 00:15:02,840 Speaker 2: talk to Punham Gooile, the retail analyst Bloomberg Intelligence. She says, 297 00:15:02,880 --> 00:15:05,160 Speaker 2: you know, the more promotions you see out there, that's 298 00:15:05,200 --> 00:15:07,000 Speaker 2: going to be that goes right to the margins, the 299 00:15:07,000 --> 00:15:10,040 Speaker 2: profit margins of some of these retailers. What are we 300 00:15:10,080 --> 00:15:10,760 Speaker 2: seeing this season? 301 00:15:11,000 --> 00:15:13,200 Speaker 9: That's a good question. So this season, we've actually seen 302 00:15:13,280 --> 00:15:16,480 Speaker 9: some retailers pull back on deals to protect their margin. 303 00:15:17,080 --> 00:15:19,200 Speaker 9: So some companies are doing that as part of a 304 00:15:19,200 --> 00:15:21,480 Speaker 9: broader strategy, and then some are having to do that 305 00:15:21,560 --> 00:15:24,440 Speaker 9: because of tariff. So, you know, for Black Friday, typically 306 00:15:24,520 --> 00:15:27,200 Speaker 9: they'd offer big discounts and some are pulling back or 307 00:15:27,240 --> 00:15:28,680 Speaker 9: not offering discounts at all. 308 00:15:29,360 --> 00:15:32,480 Speaker 3: So consumers have still been broadly spending in the retail space. 309 00:15:32,600 --> 00:15:34,880 Speaker 3: What are they spending on? Is it? You know, are 310 00:15:34,880 --> 00:15:39,920 Speaker 3: we spending money on essentials right now? Skipping this lurging? Yeah, yeah, 311 00:15:39,960 --> 00:15:40,960 Speaker 3: that's exactly it. 312 00:15:41,040 --> 00:15:43,240 Speaker 9: So Black Friday, we talked to a lot of folks 313 00:15:43,280 --> 00:15:45,960 Speaker 9: who were saying they're going to just get essentials this 314 00:15:46,080 --> 00:15:49,440 Speaker 9: Black Friday. So instead of buying, you know, a Lake Crusette, 315 00:15:49,520 --> 00:15:52,600 Speaker 9: Dutch oven, they were We talked to someone who instead 316 00:15:52,680 --> 00:15:55,040 Speaker 9: was going to buy like three bags of forty pounds 317 00:15:55,080 --> 00:15:55,680 Speaker 9: dog food. 318 00:15:55,880 --> 00:15:57,480 Speaker 2: Oh that sounds okay. 319 00:15:57,640 --> 00:15:58,960 Speaker 7: Yeah, So really. 320 00:15:58,720 --> 00:16:01,400 Speaker 9: Using you know, deals to get things that they need 321 00:16:01,440 --> 00:16:04,280 Speaker 9: for themselves rather than getting that big ticket item they 322 00:16:04,320 --> 00:16:04,800 Speaker 9: waited for. 323 00:16:05,360 --> 00:16:08,480 Speaker 2: What I learned from talking to retail folks is omni 324 00:16:08,760 --> 00:16:12,920 Speaker 2: channel retail, which is you use both the online and 325 00:16:13,000 --> 00:16:15,760 Speaker 2: the bricks and mortar, and maybe you look at something online, 326 00:16:16,040 --> 00:16:17,440 Speaker 2: then you want to go touch and feel it, or 327 00:16:17,440 --> 00:16:18,800 Speaker 2: maybe you order it then you pick it up at 328 00:16:18,800 --> 00:16:21,320 Speaker 2: the store. Omni channels that still a thing. 329 00:16:21,800 --> 00:16:24,360 Speaker 9: Yeah, Yeah, So we were out there on Black Friday 330 00:16:24,360 --> 00:16:26,240 Speaker 9: and some of the stores, and you know, while a 331 00:16:26,320 --> 00:16:29,120 Speaker 9: lot of people have switched their holiday shopping to be online, 332 00:16:29,160 --> 00:16:32,000 Speaker 9: we still saw a ton of people in stores, especially 333 00:16:32,040 --> 00:16:34,680 Speaker 9: at stores with really good deals and stores that have 334 00:16:34,800 --> 00:16:38,520 Speaker 9: appealed to young shoppers. So brands like Addicted and Princess 335 00:16:38,560 --> 00:16:41,520 Speaker 9: Paul that are in malls were really flooded with young people. 336 00:16:41,840 --> 00:16:45,040 Speaker 3: Our thanks to Lily Meyer, Bloomberg Retail reporter, move next. 337 00:16:44,960 --> 00:16:48,080 Speaker 2: To quarterly earnings from the cloud based software company Salesforce. 338 00:16:48,200 --> 00:16:50,600 Speaker 3: This week, the company reported third quarter earnings that beat 339 00:16:50,640 --> 00:16:54,160 Speaker 3: analyst expectations. Salesforce also gave an outlook for revenue in 340 00:16:54,160 --> 00:16:56,440 Speaker 3: the current quarter that topped Wall Street estimates. 341 00:16:56,640 --> 00:16:59,640 Speaker 2: This suggests that the software company is persuading customers to 342 00:16:59,680 --> 00:17:02,520 Speaker 2: buy it AI tools. For more on this, Nornite were 343 00:17:02,600 --> 00:17:05,560 Speaker 2: joined by anarag Rana, Bloomberg Intelligence technology analyst. 344 00:17:05,800 --> 00:17:07,800 Speaker 3: We first asked Aniog for his take on the most 345 00:17:07,840 --> 00:17:09,480 Speaker 3: recent earnings report from Salesforce. 346 00:17:09,840 --> 00:17:10,400 Speaker 10: Yeah, the sack. 347 00:17:10,640 --> 00:17:12,880 Speaker 11: The results did come in, I mean almost in line 348 00:17:12,920 --> 00:17:14,760 Speaker 11: with how we were looking at it in terms of 349 00:17:15,119 --> 00:17:17,840 Speaker 11: that the core business is still struggling. But when it 350 00:17:17,880 --> 00:17:19,960 Speaker 11: comes to some of their AI products that has started 351 00:17:20,000 --> 00:17:22,920 Speaker 11: to do well, they've gained momentum. But when you look 352 00:17:22,960 --> 00:17:25,160 Speaker 11: at somebody like a salesforce, when you have a revenue 353 00:17:25,160 --> 00:17:28,280 Speaker 11: base of forty one billion dollars, it takes a lot 354 00:17:28,359 --> 00:17:30,800 Speaker 11: to move the needles. So even though these products are 355 00:17:30,880 --> 00:17:34,040 Speaker 11: very small and you know, growing triple digits, but they 356 00:17:34,040 --> 00:17:37,160 Speaker 11: are not you know, right there in order to take 357 00:17:37,240 --> 00:17:39,679 Speaker 11: down what is happening on the core business, which is 358 00:17:39,920 --> 00:17:44,080 Speaker 11: a decline in seat growth or the less addition of 359 00:17:44,200 --> 00:17:48,120 Speaker 11: seats because of macro IT spending, and that is probably 360 00:17:48,119 --> 00:17:51,280 Speaker 11: going to be the story, at least for the near term. 361 00:17:51,560 --> 00:17:54,680 Speaker 3: So it seems as though analysts are still generally positive 362 00:17:54,800 --> 00:17:57,119 Speaker 3: on in terms of AI adoption trends when we think 363 00:17:57,160 --> 00:17:58,280 Speaker 3: about this company though. 364 00:17:59,200 --> 00:18:01,240 Speaker 11: Yes, absolutely, and that's you know, one of the things. 365 00:18:01,280 --> 00:18:04,399 Speaker 11: We saw really good numbers on both the data cloud 366 00:18:04,480 --> 00:18:06,840 Speaker 11: side of it and also the agent force. But when 367 00:18:06,840 --> 00:18:09,320 Speaker 11: you look at the stock reaction and finally people have 368 00:18:09,359 --> 00:18:12,600 Speaker 11: when you really scrape the numbers and see that their 369 00:18:12,920 --> 00:18:16,280 Speaker 11: commercial remaining performance obligations, which is the order book for 370 00:18:16,400 --> 00:18:19,440 Speaker 11: next quarter, which they expect to grow about thirteen percent 371 00:18:19,440 --> 00:18:23,679 Speaker 11: in constant currency four percentage of point of that is informatica. 372 00:18:23,760 --> 00:18:26,240 Speaker 11: So when you strip that out, you will see that 373 00:18:26,240 --> 00:18:29,520 Speaker 11: that particular backlock number goes from eleven percent this quarter 374 00:18:29,760 --> 00:18:31,840 Speaker 11: to let's say nine or ten percent. So the core 375 00:18:31,880 --> 00:18:34,280 Speaker 11: is still declining or the core is still under pressure. 376 00:18:35,200 --> 00:18:37,640 Speaker 2: So the stock down twenty seven percent year to date 377 00:18:37,840 --> 00:18:40,280 Speaker 2: on a rock that does that reflect the fact that 378 00:18:40,520 --> 00:18:44,479 Speaker 2: it's just it budgets are tight, or that AI poses 379 00:18:44,480 --> 00:18:48,760 Speaker 2: an existential threat to certain providers like a Salesforce. 380 00:18:50,200 --> 00:18:52,399 Speaker 11: I don't think that's the case, because it's going to 381 00:18:52,400 --> 00:18:56,040 Speaker 11: be very difficult for an established Fortune two thousand company 382 00:18:56,240 --> 00:18:58,760 Speaker 11: to get rid of their core system of record, you know, 383 00:18:58,800 --> 00:19:02,359 Speaker 11: whether that's an HRS sales customer service and just deploy 384 00:19:02,400 --> 00:19:04,680 Speaker 11: a model in there. At least we are not there yet. 385 00:19:04,680 --> 00:19:06,840 Speaker 11: Maybe you know, five years down the road we may 386 00:19:06,880 --> 00:19:09,760 Speaker 11: see a scenario like this. But that's not really why 387 00:19:09,840 --> 00:19:13,160 Speaker 11: Salesforce is struggling. It is basically, we are the largest 388 00:19:13,160 --> 00:19:16,760 Speaker 11: provider of sales automation tool and customer service tool to 389 00:19:16,840 --> 00:19:20,000 Speaker 11: Fortune two thousand companies. It's those companies that are not 390 00:19:20,200 --> 00:19:23,080 Speaker 11: hiding at that same rate that they used to because 391 00:19:23,240 --> 00:19:26,680 Speaker 11: outside of AI and AI infrastructure, everything else is still 392 00:19:26,720 --> 00:19:27,320 Speaker 11: weak at this. 393 00:19:27,240 --> 00:19:31,400 Speaker 2: Point our thanks to anaag Rana Bloomberg Intelligence technology analysts, we. 394 00:19:31,320 --> 00:19:33,520 Speaker 3: Move to some news in the aerospace sector. 395 00:19:33,880 --> 00:19:36,920 Speaker 2: This week's shares of the aerospace company Airbus plunged after 396 00:19:36,960 --> 00:19:40,000 Speaker 2: revealed a quality issue on some fuselage panels of its 397 00:19:40,080 --> 00:19:42,640 Speaker 2: A three to twenty airliner. This came just days after 398 00:19:42,640 --> 00:19:45,840 Speaker 2: Airbus flagged a software glitch on about six thousand jets. 399 00:19:46,160 --> 00:19:48,880 Speaker 3: As a result, Airbus must inspect hundreds of its best 400 00:19:48,880 --> 00:19:51,560 Speaker 3: selling A three twenty jets for potential quality flaws in 401 00:19:51,600 --> 00:19:54,199 Speaker 3: the aircraft's body, and this could risk slowing down delivery 402 00:19:54,200 --> 00:19:55,360 Speaker 3: of newly produced jets. 403 00:19:55,520 --> 00:19:57,520 Speaker 2: For more on this guest host Alex Semonova and I 404 00:19:57,520 --> 00:20:01,240 Speaker 2: were joined by George ferguson Bloomberg Intelligence. Your aerospace, defense 405 00:20:01,280 --> 00:20:03,919 Speaker 2: and airlines analysts first asked George to talk to us 406 00:20:03,960 --> 00:20:06,919 Speaker 2: about why it seems Airbus has been able to fly 407 00:20:07,119 --> 00:20:08,720 Speaker 2: under the radar until just recently. 408 00:20:08,960 --> 00:20:12,040 Speaker 8: I think they've also had their challenges in the supply 409 00:20:12,160 --> 00:20:15,560 Speaker 8: chain along the way, just throwing challenges were so much 410 00:20:15,600 --> 00:20:19,679 Speaker 8: greater that they stole the spotlight, if you will. But 411 00:20:19,760 --> 00:20:22,640 Speaker 8: I mean, look, the aerospace supply chain is a bit 412 00:20:22,720 --> 00:20:24,960 Speaker 8: thin right, It doesn't have the same redundancy as like 413 00:20:25,000 --> 00:20:28,360 Speaker 8: you'd get in an auto supply chain, and so when 414 00:20:28,400 --> 00:20:30,840 Speaker 8: you just have some little problem at one of your suppliers, 415 00:20:31,920 --> 00:20:34,480 Speaker 8: you know, it can really interrupt your ability to deliver airplanes. 416 00:20:34,480 --> 00:20:37,359 Speaker 8: And I think right now what you're seeing is that 417 00:20:37,520 --> 00:20:41,040 Speaker 8: Airbus already has a really tall order to meet the 418 00:20:41,200 --> 00:20:45,960 Speaker 8: something like eight hundred and twenty airplane guidance or delivery 419 00:20:45,960 --> 00:20:48,760 Speaker 8: guidance they've got for this year. We don't think they're 420 00:20:48,800 --> 00:20:51,840 Speaker 8: gonna make it. I think they need seventy plus a 421 00:20:52,000 --> 00:20:54,560 Speaker 8: three twenties in the last two months of the year 422 00:20:54,560 --> 00:20:57,800 Speaker 8: in November December. We think that's pretty hard given they've 423 00:20:58,080 --> 00:21:02,119 Speaker 8: kind of delivered fifty five ish most months of in 424 00:21:02,160 --> 00:21:06,080 Speaker 8: the last couple, you know, for months, and so I 425 00:21:06,119 --> 00:21:10,879 Speaker 8: think a quality problem here probably really places in doubt 426 00:21:10,920 --> 00:21:14,040 Speaker 8: their ability to make that guidance, and that's going to 427 00:21:14,119 --> 00:21:15,480 Speaker 8: hurt their profitability for the year. 428 00:21:15,960 --> 00:21:19,720 Speaker 4: George, you mentioned that really ambitious target for eight hundred 429 00:21:19,760 --> 00:21:22,280 Speaker 4: and twenty aircraft deliveries by the end of this year. 430 00:21:22,359 --> 00:21:25,440 Speaker 4: How disappointed could investors get if it fails to meet 431 00:21:25,440 --> 00:21:28,720 Speaker 4: that target. On top of the headwinds that this company 432 00:21:28,760 --> 00:21:30,720 Speaker 4: is already facing well. 433 00:21:30,600 --> 00:21:32,720 Speaker 8: I mean, so I think you're starting to see, you know, 434 00:21:32,760 --> 00:21:37,280 Speaker 8: the disappointment here. Again, I'd be surprised if most investors 435 00:21:37,800 --> 00:21:41,800 Speaker 8: weren't already concerned that the target was too high. I 436 00:21:41,840 --> 00:21:44,080 Speaker 8: think Airbus has really put out a bunch of very 437 00:21:44,119 --> 00:21:48,880 Speaker 8: ambitious build rate targets right the I think our latest 438 00:21:48,920 --> 00:21:50,480 Speaker 8: number in A three twenty is that we would be 439 00:21:50,520 --> 00:21:54,400 Speaker 8: going to something like seventy five a month, and that's 440 00:21:54,440 --> 00:21:58,040 Speaker 8: consistently throughout the entire year, right by the end of 441 00:21:58,080 --> 00:22:01,480 Speaker 8: twenty twenty six, which to us just seems far too high. 442 00:22:01,520 --> 00:22:04,560 Speaker 8: And I feel like Airbus keeps trying to lead the 443 00:22:04,640 --> 00:22:08,720 Speaker 8: supplier base by pushing these higher numbers out and trying 444 00:22:08,760 --> 00:22:11,760 Speaker 8: to pull the supplier base along, and then over time 445 00:22:11,880 --> 00:22:15,399 Speaker 8: lowers some of these expectations. So look, I think anything 446 00:22:15,400 --> 00:22:18,760 Speaker 8: they miss now isn't going away. It gets pushed into 447 00:22:18,800 --> 00:22:21,119 Speaker 8: the next year and the next year, and again, I 448 00:22:21,160 --> 00:22:25,119 Speaker 8: think the bigger challenge here is investors have to ask themselves, 449 00:22:25,480 --> 00:22:28,280 Speaker 8: are a lot of these Airbus targets for delivery rates? 450 00:22:28,359 --> 00:22:30,840 Speaker 8: Are they just too ambitious? And don't we have to 451 00:22:30,840 --> 00:22:33,600 Speaker 8: sort of knock them down when we build our consensus 452 00:22:33,600 --> 00:22:34,960 Speaker 8: for what we think the company's going to be able 453 00:22:34,960 --> 00:22:35,320 Speaker 8: to do. 454 00:22:35,440 --> 00:22:38,639 Speaker 2: Because George, I mean a number like seventy seems really 455 00:22:38,720 --> 00:22:41,560 Speaker 2: high to me because when we talk about Boeing, it's like, Gee, 456 00:22:41,560 --> 00:22:44,080 Speaker 2: I hope they can get the forty maybe to fifty. 457 00:22:44,800 --> 00:22:47,639 Speaker 2: Is that does Boeing typically run that far behind on 458 00:22:47,680 --> 00:22:50,280 Speaker 2: a production schedule than a Airbus. 459 00:22:51,119 --> 00:22:53,800 Speaker 8: So I would say that if you would consider normal 460 00:22:54,440 --> 00:22:57,040 Speaker 8: the end of the last decade when both were building 461 00:22:57,119 --> 00:23:01,480 Speaker 8: and Boeing wasn't having the problems with mcas Airbus was 462 00:23:02,119 --> 00:23:04,840 Speaker 8: up in the higher sixties and Boeing was in the 463 00:23:04,920 --> 00:23:09,280 Speaker 8: higher fifties, and so we have traditionally seen Airbus be 464 00:23:09,280 --> 00:23:12,960 Speaker 8: able to put out more airplanes than Boeing. I think 465 00:23:13,000 --> 00:23:16,080 Speaker 8: their supply base maybe a little bit more robust, and 466 00:23:16,119 --> 00:23:20,360 Speaker 8: I think they have sort of multiple final assembly areas 467 00:23:20,880 --> 00:23:23,600 Speaker 8: around the world. I think those are some of the 468 00:23:23,640 --> 00:23:27,120 Speaker 8: reasons why Airbus can just has the infrastructure to put 469 00:23:27,160 --> 00:23:30,359 Speaker 8: out more airplanes, more narrowbody airplanes per month. 470 00:23:30,520 --> 00:23:33,480 Speaker 2: Our thanks to George Ferguson Bloomberg Intelligence senior Aerospace, Defense 471 00:23:33,520 --> 00:23:34,520 Speaker 2: and Airlines analysts. 472 00:23:34,560 --> 00:23:36,679 Speaker 3: Coming up, we'll take a look at US data centered 473 00:23:36,720 --> 00:23:39,680 Speaker 3: power demand and just how quickly the sector is expanding. 474 00:23:39,280 --> 00:23:42,040 Speaker 2: You're listening to Bloomberg Intelligence on Bloomberg Radio, providing in 475 00:23:42,080 --> 00:23:44,199 Speaker 2: depth research and data on two thousand companies and one 476 00:23:44,280 --> 00:23:45,360 Speaker 2: hundred and thirty industries. 477 00:23:45,440 --> 00:23:47,320 Speaker 3: You can access Bloomberg Intelligence be a B I go 478 00:23:47,560 --> 00:23:49,400 Speaker 3: on the terminal. I'm normal Inda, and. 479 00:23:49,359 --> 00:23:51,360 Speaker 2: I'm Paul Sweeney, and this is Bloomberg. 480 00:23:57,280 --> 00:24:01,800 Speaker 1: This is Bloomberg Intelligence with Scarlet Foo and Paul Sweeney 481 00:24:02,160 --> 00:24:03,480 Speaker 1: on Bloomberg Radio. 482 00:24:04,320 --> 00:24:07,160 Speaker 3: On Paul Sweeney and I'm normal Linda filling in for Scarlettfoo. 483 00:24:07,400 --> 00:24:09,920 Speaker 2: We move next to the real estate Space nor Nite. 484 00:24:09,920 --> 00:24:12,919 Speaker 2: We're joined by Jeff Langbaum. This week, Bloomberg Intelligence Senior 485 00:24:13,119 --> 00:24:14,640 Speaker 2: US REET analyst. 486 00:24:14,520 --> 00:24:17,520 Speaker 3: Jeff discussed research on real estate investment trusts or reads 487 00:24:17,600 --> 00:24:19,840 Speaker 3: as his outlook for them. In twenty twenty six. 488 00:24:19,680 --> 00:24:23,400 Speaker 2: We first asked Jeff how reads have been performing this year. 489 00:24:23,920 --> 00:24:26,800 Speaker 12: They haven't performed well in twenty twenty five, that's for sure. 490 00:24:28,280 --> 00:24:30,320 Speaker 12: I mean, basically, you know, kind of flats to slightly 491 00:24:30,359 --> 00:24:34,200 Speaker 12: down on an aggregate basis, but relative to the S 492 00:24:34,280 --> 00:24:39,159 Speaker 12: and P underperformed significantly. And that's going on three years now. Obviously, 493 00:24:39,320 --> 00:24:41,720 Speaker 12: you know, you had the rising rate cycle that was 494 00:24:42,280 --> 00:24:46,560 Speaker 12: pretty damaging. You had some difficulties especially in the office sector. 495 00:24:47,119 --> 00:24:49,480 Speaker 12: But as we sit here looking ahead to twenty twenty six, 496 00:24:49,680 --> 00:24:53,040 Speaker 12: the fundamental backdrop looks okay. And especially if you get 497 00:24:53,119 --> 00:24:56,320 Speaker 12: rates falling, if that ten year yield starts to drop, 498 00:24:56,359 --> 00:25:00,119 Speaker 12: and you know, that has cascading effects on evaluations, it 499 00:25:00,119 --> 00:25:04,760 Speaker 12: has cascading effects on cost of capital and and really 500 00:25:04,800 --> 00:25:08,000 Speaker 12: would be a boost for the sector going forward. 501 00:25:08,760 --> 00:25:10,800 Speaker 3: We are you seeing to be some bright spots right 502 00:25:10,840 --> 00:25:14,719 Speaker 3: now in the reat sector, Jeff Senior. 503 00:25:14,720 --> 00:25:19,760 Speaker 12: Housing, That is the that I didn't look at you. 504 00:25:21,320 --> 00:25:24,880 Speaker 12: I'm looking at you, Paul, the I mean, that's that's 505 00:25:24,920 --> 00:25:30,600 Speaker 12: the clear winner right now. The fundamental backdrop, driven by 506 00:25:30,640 --> 00:25:37,160 Speaker 12: demographics is huge and growing. There's an incredible coming need 507 00:25:37,280 --> 00:25:42,600 Speaker 12: for housing for the aging baby boomers, and you know 508 00:25:42,640 --> 00:25:45,800 Speaker 12: there's nothing, nothing being built, so the supply demand uh 509 00:25:45,960 --> 00:25:50,480 Speaker 12: dynamics in that space are incredible. And you know there's 510 00:25:50,520 --> 00:25:52,400 Speaker 12: a couple of roots that play in that space, Well 511 00:25:52,480 --> 00:25:56,240 Speaker 12: Towers the biggest one. They're growing like crazy and the 512 00:25:56,280 --> 00:25:57,640 Speaker 12: stock is reflecting it. 513 00:25:58,720 --> 00:26:04,399 Speaker 2: All right, So what's the aside from folks, you know, 514 00:26:04,400 --> 00:26:06,400 Speaker 2: old folks housing, which is I'm going to say, because 515 00:26:06,480 --> 00:26:09,000 Speaker 2: you know, I'm there, I'm there, I'm in the demo 516 00:26:09,600 --> 00:26:12,639 Speaker 2: what else is working here? What is is it? Is 517 00:26:12,680 --> 00:26:15,520 Speaker 2: there a replay on all this AI data center stuff. 518 00:26:16,720 --> 00:26:19,720 Speaker 12: So the you know, there's there's a couple of different 519 00:26:19,720 --> 00:26:23,399 Speaker 12: ways to answer that. The direct impact of AI on 520 00:26:23,400 --> 00:26:27,760 Speaker 12: on reads is the two big data center reads Equinics 521 00:26:27,760 --> 00:26:29,919 Speaker 12: and Digital Realty, and they are playing in that space 522 00:26:30,720 --> 00:26:33,400 Speaker 12: right now. It's kind of unclear exactly where they fit. 523 00:26:33,800 --> 00:26:37,800 Speaker 12: There should be a significant amount of demand for their space, 524 00:26:38,200 --> 00:26:40,560 Speaker 12: especially for the stuff that they're looking to build, but 525 00:26:40,560 --> 00:26:42,520 Speaker 12: they have to raise a ton of capital in order 526 00:26:42,600 --> 00:26:47,280 Speaker 12: to fund that that that development, you know, and you 527 00:26:47,320 --> 00:26:50,439 Speaker 12: see capex numbers coming out from all the hyperscalers that 528 00:26:50,480 --> 00:26:54,919 Speaker 12: are astronomical, and you know reads, you know, investors in 529 00:26:54,960 --> 00:26:57,680 Speaker 12: reads don't necessarily love the concept of raising a ton 530 00:26:57,720 --> 00:27:00,480 Speaker 12: of money to deploy it in kind of risky assets 531 00:27:00,480 --> 00:27:02,720 Speaker 12: that you need to then go lease up. So the 532 00:27:02,800 --> 00:27:05,679 Speaker 12: demand should clearly be there, but it's going to be 533 00:27:05,680 --> 00:27:07,440 Speaker 12: interesting to see how it plays out over the next 534 00:27:07,440 --> 00:27:09,480 Speaker 12: couple of years as that demand filters through. 535 00:27:09,800 --> 00:27:12,000 Speaker 2: The other issue with AI, though, is there. 536 00:27:11,880 --> 00:27:14,600 Speaker 12: Is a kind of a concern that AI is going 537 00:27:14,600 --> 00:27:17,520 Speaker 12: to impact demand for office space, and you know, as 538 00:27:17,560 --> 00:27:20,000 Speaker 12: companies get more efficient, they need less headcount, they need 539 00:27:20,080 --> 00:27:23,040 Speaker 12: less office space. Haven't really started to see that play 540 00:27:23,080 --> 00:27:27,280 Speaker 12: out yet, but it's definitely a sentiment that is out 541 00:27:27,280 --> 00:27:30,399 Speaker 12: there and is impacting the stocks to a degree. You know, 542 00:27:30,520 --> 00:27:33,480 Speaker 12: just as we got past the whole work from home 543 00:27:33,800 --> 00:27:37,080 Speaker 12: thing and concern over whether offices we're ever going to 544 00:27:37,119 --> 00:27:39,320 Speaker 12: have people back in them, now we have concerned that 545 00:27:39,359 --> 00:27:40,960 Speaker 12: the robots are going to replace the people. 546 00:27:42,359 --> 00:27:43,719 Speaker 3: So of course we do have the income in New 547 00:27:43,760 --> 00:27:46,600 Speaker 3: York City Mayor saying that he wants to freeze rents 548 00:27:46,600 --> 00:27:49,560 Speaker 3: on rent stabilized apartments in New York City. What's the 549 00:27:49,640 --> 00:27:53,000 Speaker 3: latest in terms of the apartment rate space right now? 550 00:27:53,680 --> 00:27:55,840 Speaker 12: Yeah, I mean it's unclear exactly what he's going to 551 00:27:55,880 --> 00:28:01,000 Speaker 12: be able to do on rent stabilization freeze capping rents. 552 00:28:01,520 --> 00:28:04,600 Speaker 12: But the reats that own own residential in New York City, 553 00:28:04,680 --> 00:28:08,480 Speaker 12: names like Avalon Bay Equity Residential, they own stuff that's 554 00:28:08,520 --> 00:28:12,439 Speaker 12: not subject to those caps. It's it's largely newer market 555 00:28:12,480 --> 00:28:15,800 Speaker 12: rate stuff, and so they're not going to be directly impacted. 556 00:28:16,640 --> 00:28:19,240 Speaker 12: And so you know, at the end of the day, 557 00:28:19,720 --> 00:28:24,320 Speaker 12: if there is less new the net result of of 558 00:28:24,400 --> 00:28:26,480 Speaker 12: caps like that is less new stuff, get less stuff 559 00:28:26,480 --> 00:28:29,000 Speaker 12: getting renovated, less stuff getting built, and and that just 560 00:28:29,240 --> 00:28:32,160 Speaker 12: you know, keeps supply down and as long as demands 561 00:28:32,680 --> 00:28:35,159 Speaker 12: stays elevated, then that should flow through to the ability 562 00:28:35,200 --> 00:28:38,080 Speaker 12: to keep buildings full and keep rents rising to a degree. 563 00:28:38,640 --> 00:28:40,360 Speaker 12: So I think that in the in the near term, 564 00:28:40,560 --> 00:28:43,640 Speaker 12: you know, that that should be it should be fine 565 00:28:43,800 --> 00:28:46,200 Speaker 12: for names like like those that play in the in 566 00:28:46,280 --> 00:28:49,840 Speaker 12: the city, you know, the the it's it's those that 567 00:28:49,920 --> 00:28:51,720 Speaker 12: own the kind of the lower tier space that maybe 568 00:28:51,760 --> 00:28:53,880 Speaker 12: are a little bit more exposed are. 569 00:28:53,720 --> 00:28:57,520 Speaker 3: Thanks to Jeff'slingbam Bloomberg Intelligence senior US re analysts. 570 00:28:57,200 --> 00:28:59,800 Speaker 2: On Bloomberg Intelligence, we often look at research from Bloomberg 571 00:28:59,840 --> 00:29:02,560 Speaker 2: and EF previously known as New Energy Finance. 572 00:29:02,680 --> 00:29:04,600 Speaker 3: They have a team at Bloomberg that tracks and analyzes 573 00:29:04,640 --> 00:29:08,400 Speaker 3: the energy transition from commodities to power, transport, industries, buildings, 574 00:29:08,440 --> 00:29:11,160 Speaker 3: and agriculture sectors. This week we took a look at 575 00:29:11,400 --> 00:29:14,080 Speaker 3: US data center powered demand and just how quickly that 576 00:29:14,120 --> 00:29:15,040 Speaker 3: sector is expanding. 577 00:29:15,200 --> 00:29:17,640 Speaker 2: For more on this guest host Alex Semonovan and I 578 00:29:17,640 --> 00:29:20,600 Speaker 2: were joined by Helen co b Nf, head of US 579 00:29:20,640 --> 00:29:23,320 Speaker 2: Power Markets Research. We first asked Helen if we have 580 00:29:23,480 --> 00:29:26,960 Speaker 2: the power necessary to power all the data centers we 581 00:29:27,040 --> 00:29:27,800 Speaker 2: keep hearing about. 582 00:29:28,200 --> 00:29:32,760 Speaker 10: What we're seeing is quite an unprecedented acceleration of data 583 00:29:32,760 --> 00:29:38,240 Speaker 10: center demand, driven largely by AI and at BNF. What 584 00:29:38,440 --> 00:29:41,920 Speaker 10: we see and expect is that data center power demand 585 00:29:42,040 --> 00:29:44,800 Speaker 10: is going to reach roughly one hundred and six gigawatts 586 00:29:44,880 --> 00:29:45,960 Speaker 10: by twenty thirty five. 587 00:29:46,080 --> 00:29:48,120 Speaker 2: Where are we today, just for example. 588 00:29:48,120 --> 00:29:53,040 Speaker 10: Today, we are definitely a lot lower in capacity, so 589 00:29:53,240 --> 00:29:56,600 Speaker 10: roughly half of that right now. What we also know 590 00:29:57,000 --> 00:29:59,880 Speaker 10: is that that one oho six gigawats by twenty thirty five, 591 00:30:00,080 --> 00:30:03,520 Speaker 10: that's thirty six percent higher than our outlook just six 592 00:30:03,560 --> 00:30:07,000 Speaker 10: months ago. So we've increased that forecast quite a lot 593 00:30:08,000 --> 00:30:10,320 Speaker 10: since these last six months. What we've seen is a 594 00:30:10,320 --> 00:30:13,840 Speaker 10: flood of early stage projects getting announced, which results in 595 00:30:13,880 --> 00:30:17,160 Speaker 10: a much larger pipeline, and therefore our forecast has also 596 00:30:17,280 --> 00:30:21,520 Speaker 10: increased quite a bit to power these data centers. What 597 00:30:21,560 --> 00:30:24,120 Speaker 10: we know is that there's a lot of new build 598 00:30:24,400 --> 00:30:28,200 Speaker 10: of power supply coming online to try to reach this 599 00:30:28,320 --> 00:30:29,440 Speaker 10: overall power demand. 600 00:30:30,360 --> 00:30:33,480 Speaker 4: Helen, we're obviously in the early innings of this build 601 00:30:33,520 --> 00:30:36,120 Speaker 4: out of data centers. What signs are you seeing already 602 00:30:36,400 --> 00:30:39,840 Speaker 4: of any kind of strains on resources on electricity? 603 00:30:40,440 --> 00:30:43,160 Speaker 10: What we know is there are certain regions that are 604 00:30:43,560 --> 00:30:46,520 Speaker 10: hitting a tipping point in terms of actually being able 605 00:30:46,520 --> 00:30:50,440 Speaker 10: to power this overall supply. What we know is that 606 00:30:50,680 --> 00:30:54,000 Speaker 10: Northern Virginia is still the largest kind of market for 607 00:30:54,080 --> 00:30:57,880 Speaker 10: data center demand based on our forecast, and we are 608 00:30:57,920 --> 00:31:00,840 Speaker 10: seeing a lot of growing concern in that PEG region. 609 00:31:01,720 --> 00:31:04,720 Speaker 10: What we project in PGM is that data center capacity 610 00:31:04,800 --> 00:31:07,959 Speaker 10: is going to hit roughly thirty one gigawatts by twenty thirty. 611 00:31:09,080 --> 00:31:12,520 Speaker 10: And what we do is when we adjust that overall 612 00:31:12,800 --> 00:31:16,280 Speaker 10: kind of like what power demand looks like in PGM 613 00:31:17,200 --> 00:31:19,960 Speaker 10: relative to supply, what we expect is there might be 614 00:31:20,000 --> 00:31:24,320 Speaker 10: a nine point five gigawatch shortfall of overall power supply 615 00:31:24,520 --> 00:31:26,920 Speaker 10: by the end of the decade if we assume that 616 00:31:27,000 --> 00:31:29,920 Speaker 10: all of this data center demand is going to come online. 617 00:31:30,280 --> 00:31:33,680 Speaker 2: If all this data center demand comes online, obviously the 618 00:31:33,720 --> 00:31:36,720 Speaker 2: need for electricity or power is just extraordinary. I'm a 619 00:31:36,720 --> 00:31:41,400 Speaker 2: big fan of nuclear, A small mobile reactor, modular reactor here, 620 00:31:41,400 --> 00:31:43,840 Speaker 2: there's SMR type things talk to us about that is 621 00:31:44,280 --> 00:31:46,560 Speaker 2: that a viable technology solution at some point. 622 00:31:47,680 --> 00:31:49,680 Speaker 10: So we know that there has been a lot of 623 00:31:49,680 --> 00:31:53,360 Speaker 10: company announcements around small modular nuclear as well as just 624 00:31:53,520 --> 00:31:58,880 Speaker 10: nuclear in general. And there has been several different new 625 00:31:58,920 --> 00:32:03,200 Speaker 10: power purchase agreement and surround nuclear by major hyperscale companies 626 00:32:03,240 --> 00:32:07,320 Speaker 10: as well. What we see within BNF is that in 627 00:32:07,360 --> 00:32:10,280 Speaker 10: the near term what is likely going to power data 628 00:32:10,280 --> 00:32:13,440 Speaker 10: center demand is actually going to be gas, and nuclear 629 00:32:13,600 --> 00:32:17,000 Speaker 10: is a much more longer kind of like long term 630 00:32:17,040 --> 00:32:19,760 Speaker 10: play in terms of how you power data center demand. 631 00:32:20,040 --> 00:32:22,600 Speaker 10: But what we expect is that the major ramp up 632 00:32:22,720 --> 00:32:26,000 Speaker 10: in overall demand is coming over these next three years, 633 00:32:26,200 --> 00:32:29,280 Speaker 10: and gas is likely what's going to meet that overall demand. 634 00:32:30,000 --> 00:32:34,360 Speaker 4: What kind of measures are being taken to limit any 635 00:32:34,440 --> 00:32:38,000 Speaker 4: kind of potential power outages from this build. 636 00:32:37,760 --> 00:32:41,440 Speaker 10: Out, Well, we do see that there's been a lot 637 00:32:41,520 --> 00:32:45,120 Speaker 10: of different regulations that are evolving real time around data 638 00:32:45,160 --> 00:32:49,400 Speaker 10: center demand. What we know is that Georgia adopted new 639 00:32:49,480 --> 00:32:54,720 Speaker 10: rules pushing grid connection costs onto large users like industrial users. 640 00:32:54,880 --> 00:32:57,280 Speaker 10: Ohio now requires data centers to pay for at least 641 00:32:57,280 --> 00:33:00,480 Speaker 10: eighty five percent of the energy they request each month, 642 00:33:01,240 --> 00:33:05,000 Speaker 10: even if it is underutilized, and so policies are kind 643 00:33:05,040 --> 00:33:07,680 Speaker 10: of being put in place to kind of navigate rising 644 00:33:07,720 --> 00:33:08,600 Speaker 10: and growing demand. 645 00:33:09,960 --> 00:33:12,800 Speaker 2: Are we building these data centers too quickly? Is there 646 00:33:12,800 --> 00:33:16,120 Speaker 2: a risk for an overbuild? It just feels like it's 647 00:33:16,200 --> 00:33:19,120 Speaker 2: too much, too fast, but all the projections say we're 648 00:33:19,120 --> 00:33:20,800 Speaker 2: going to need all that compute. 649 00:33:21,160 --> 00:33:24,640 Speaker 10: It's a really great question, something as an analyst I 650 00:33:24,680 --> 00:33:28,960 Speaker 10: think about quite a bit. At BNF. What we've done 651 00:33:29,080 --> 00:33:32,480 Speaker 10: is we've benchmarked our data center forecast relative to a 652 00:33:32,520 --> 00:33:35,840 Speaker 10: whole bunch of other third party forecasts out there, and 653 00:33:35,880 --> 00:33:39,320 Speaker 10: what we see is that our forecast is relatively conservative 654 00:33:39,400 --> 00:33:44,360 Speaker 10: compared to other third parties because our data center forecast 655 00:33:44,520 --> 00:33:49,800 Speaker 10: does include and analyze some of the additional power constraints 656 00:33:50,400 --> 00:33:54,400 Speaker 10: as well as like project development timelines of data center development. 657 00:33:54,640 --> 00:33:57,400 Speaker 10: And what we found is that it roughly takes seven 658 00:33:57,520 --> 00:34:00,880 Speaker 10: years to develop a data center, and even that we're 659 00:34:00,920 --> 00:34:04,840 Speaker 10: seeing quite a bit of new capacity come online. That 660 00:34:05,040 --> 00:34:09,040 Speaker 10: is a result of just fundamentals around AI demand, whether 661 00:34:09,040 --> 00:34:13,960 Speaker 10: that is company announcements of data centers as well as 662 00:34:14,120 --> 00:34:17,120 Speaker 10: just like the underlying growth and trend around AI. 663 00:34:17,800 --> 00:34:22,880 Speaker 4: I can't help but wonder how are data centers addressing sustainability? 664 00:34:22,400 --> 00:34:25,839 Speaker 4: Are they using clean energy? What measures are they taking. 665 00:34:26,600 --> 00:34:29,359 Speaker 10: A lot of these hyperscalers that are building out data 666 00:34:29,360 --> 00:34:35,520 Speaker 10: centers do have sustainability goals and clean energy commitments. However, 667 00:34:36,160 --> 00:34:39,280 Speaker 10: like within the data center's outlook. What we mostly focused 668 00:34:39,280 --> 00:34:43,600 Speaker 10: on is just what is the additional capacity and activity 669 00:34:43,680 --> 00:34:47,160 Speaker 10: around data center demand within the United States, And we 670 00:34:47,239 --> 00:34:51,919 Speaker 10: also did a small analysis on specific markets that are 671 00:34:52,080 --> 00:34:55,920 Speaker 10: likely going to have constraints in the market around power supply, 672 00:34:56,520 --> 00:34:59,880 Speaker 10: and within URCOTT and PGM, which is our two larges 673 00:35:00,160 --> 00:35:03,880 Speaker 10: power market region that expects high data center demand growth, 674 00:35:04,200 --> 00:35:08,359 Speaker 10: what we're seeing is that the likelihood of what's going 675 00:35:08,400 --> 00:35:11,080 Speaker 10: to meet that supply is going to be gas, and 676 00:35:11,160 --> 00:35:18,359 Speaker 10: so we don't specifically look at sustainability commitments, but what 677 00:35:18,440 --> 00:35:21,120 Speaker 10: we know is that a lot of what's supplying data 678 00:35:21,160 --> 00:35:23,120 Speaker 10: centers will be gas in the narature. 679 00:35:23,040 --> 00:35:25,440 Speaker 3: Our thanks to Helen co be Any, head of US 680 00:35:25,520 --> 00:35:26,520 Speaker 3: Power Markets Research. 681 00:35:26,760 --> 00:35:29,439 Speaker 2: That's this week's edition of Bloomberg Intelligence on Bloomberg Radio, 682 00:35:29,560 --> 00:35:31,960 Speaker 2: providing in depth research and data on two thousand companies 683 00:35:32,000 --> 00:35:33,320 Speaker 2: and one hundred and thirty industries. 684 00:35:33,440 --> 00:35:35,920 Speaker 3: And remember you can access Bloomberg Intelligence be a Bigo 685 00:35:36,040 --> 00:35:38,680 Speaker 3: on the terminal. I'm normal Indo and I'm Paul Sweeney. 686 00:35:38,760 --> 00:35:41,640 Speaker 2: Stay with us. Today's top stories and global business headlines 687 00:35:41,680 --> 00:35:44,319 Speaker 2: are coming up right now.