1 00:00:02,720 --> 00:00:10,560 Speaker 1: Bloomberg Audio Studios, Podcasts, radio news. You're listening to the 2 00:00:10,560 --> 00:00:14,520 Speaker 1: Bloomberg Intelligence Podcast. Catch us live weekdays at ten am 3 00:00:14,560 --> 00:00:18,479 Speaker 1: Eastern on Applecarplay and Android Auto with the Bloomberg Business App. 4 00:00:18,600 --> 00:00:21,840 Speaker 1: Listen on demand wherever you get your podcasts, or watch 5 00:00:21,920 --> 00:00:23,040 Speaker 1: us live on YouTube. 6 00:00:23,320 --> 00:00:25,439 Speaker 2: Let's get back to the trade story, which remains front 7 00:00:25,440 --> 00:00:27,200 Speaker 2: and center here. It seems like we're in a period 8 00:00:27,240 --> 00:00:30,480 Speaker 2: where negotiations are happening between the Trump administration and a 9 00:00:31,400 --> 00:00:35,240 Speaker 2: number of different countries over a number of different teriff 10 00:00:35,280 --> 00:00:37,879 Speaker 2: measures here. So it's important to try to stay on 11 00:00:37,920 --> 00:00:39,280 Speaker 2: top of kind of where we are, and we have 12 00:00:39,320 --> 00:00:42,000 Speaker 2: a good team doing that. Brenda Murray joins US Global 13 00:00:42,120 --> 00:00:46,400 Speaker 2: Trade editor for Bloomberg News. He's in London, Brendan, it 14 00:00:46,479 --> 00:00:50,560 Speaker 2: seems like the president over the next several weeks, is 15 00:00:50,600 --> 00:00:52,839 Speaker 2: it fair to expect that we'll get some announcements on 16 00:00:52,920 --> 00:00:56,400 Speaker 2: trade deals with some of our major trading partners. 17 00:00:57,400 --> 00:00:59,200 Speaker 3: Yeah, well, it depends on what you mean by a 18 00:00:59,280 --> 00:01:02,160 Speaker 3: deal to say that we're likely to get a number 19 00:01:02,200 --> 00:01:05,760 Speaker 3: of announcements laying out the path for talks for an 20 00:01:05,760 --> 00:01:10,399 Speaker 3: eventual deal. Trade deals are very complicated. They take a 21 00:01:10,440 --> 00:01:13,720 Speaker 3: long time to hammer out and to get anything meaningful, 22 00:01:13,840 --> 00:01:15,360 Speaker 3: it's going to take a lot of time. But what 23 00:01:15,480 --> 00:01:19,360 Speaker 3: you could see are some sort of interim proposals, interim 24 00:01:19,800 --> 00:01:23,399 Speaker 3: agreements that would would set the US and the trading 25 00:01:23,440 --> 00:01:26,720 Speaker 3: partner on that course. Some of those who are sort 26 00:01:26,720 --> 00:01:31,280 Speaker 3: of have an early lead would be India, South Korea, Japan. 27 00:01:31,400 --> 00:01:34,920 Speaker 3: These are big export economies that the US wants to 28 00:01:36,080 --> 00:01:39,560 Speaker 3: trade more with to reduce the tariff and non tariff 29 00:01:39,560 --> 00:01:42,840 Speaker 3: barriers that they have with the US economy. So we 30 00:01:42,880 --> 00:01:45,240 Speaker 3: could see we could see some action along those lines. 31 00:01:45,280 --> 00:01:49,920 Speaker 3: But again, to expect anything major, anything fundamentally changing the 32 00:01:49,960 --> 00:01:53,480 Speaker 3: picture of the US trade imbalances like Donald Trump would 33 00:01:53,480 --> 00:01:55,840 Speaker 3: like to see, is probably a bit of wishful thinking. 34 00:01:56,160 --> 00:01:58,480 Speaker 4: Now, Bertie, you said Treasury Secretary Scott bet And said, 35 00:01:58,520 --> 00:02:01,000 Speaker 4: the administration working on them by lateral trade deal with 36 00:02:01,080 --> 00:02:05,000 Speaker 4: seventeen key partners, but not including China. So where does 37 00:02:05,240 --> 00:02:06,160 Speaker 4: China stand in all this? 38 00:02:07,400 --> 00:02:08,840 Speaker 3: Yeah, well this is the big you know, this is 39 00:02:08,880 --> 00:02:11,639 Speaker 3: the big This is the big prize, right, is some 40 00:02:11,680 --> 00:02:14,480 Speaker 3: sort of deal with China. And if if the US 41 00:02:14,560 --> 00:02:18,720 Speaker 3: and China aren't even talking and by all accounts according 42 00:02:18,720 --> 00:02:22,160 Speaker 3: to that they've not really having any sort of formal 43 00:02:22,160 --> 00:02:26,359 Speaker 3: discussions that would lead in the right direction toward a 44 00:02:26,600 --> 00:02:30,799 Speaker 3: formal sit down discussion that you know, you're leaving out 45 00:02:30,800 --> 00:02:33,520 Speaker 3: a big part of the imbalance, the big, you know, 46 00:02:33,560 --> 00:02:36,639 Speaker 3: the biggest imbalance that the US has. So you can 47 00:02:36,639 --> 00:02:39,720 Speaker 3: talk trade deals with Japan and South Korea and India 48 00:02:39,919 --> 00:02:44,000 Speaker 3: and other countries, but the real prize is that Donald 49 00:02:44,040 --> 00:02:45,920 Speaker 3: Trump wants is a trade deal with China, and so 50 00:02:46,000 --> 00:02:47,000 Speaker 3: far they're going nowhere. 51 00:02:47,000 --> 00:02:50,040 Speaker 2: I'm that, you know, David Rosenberg, a frequent guest on 52 00:02:50,040 --> 00:02:54,400 Speaker 2: Bloomberg Surveillance formerly Merrill Lynch. He's and he's a Canadian, 53 00:02:54,440 --> 00:02:57,520 Speaker 2: and out with a tweet saying basically, hey, everybody, I 54 00:02:57,560 --> 00:02:59,800 Speaker 2: know you're focused on China, but you need to figure 55 00:02:59,840 --> 00:03:03,000 Speaker 2: out something with Canada because Canada is the big trading 56 00:03:03,040 --> 00:03:05,560 Speaker 2: partner with the US, as is Mexico. 57 00:03:06,080 --> 00:03:08,240 Speaker 5: Where do we stand. Do you think with Canada and Mexico? 58 00:03:09,400 --> 00:03:12,160 Speaker 3: Yeah, well, the Canadians don't sound like they're of course 59 00:03:12,200 --> 00:03:13,799 Speaker 3: they're in there. You know, they're in the middle of 60 00:03:13,800 --> 00:03:16,720 Speaker 3: an election right now, and they don't they don't sound 61 00:03:16,760 --> 00:03:19,000 Speaker 3: like they're in any big hurry to do a deal. 62 00:03:19,880 --> 00:03:23,200 Speaker 3: The Prime Minister Mark Karney said the other day we'd 63 00:03:23,320 --> 00:03:26,720 Speaker 3: rather have a good deal rather than a fast deal. 64 00:03:26,840 --> 00:03:29,720 Speaker 3: So we'll see how that election plays out. That could 65 00:03:30,040 --> 00:03:33,720 Speaker 3: that could dictate the course of of of any negotiations. 66 00:03:33,760 --> 00:03:36,640 Speaker 3: But you know, in the meantime, the Canadian economy is 67 00:03:36,680 --> 00:03:40,000 Speaker 3: going to suffer. American auto companies are going to suffer 68 00:03:40,040 --> 00:03:43,280 Speaker 3: because they rely so much on Canadian suppliers. So you 69 00:03:43,320 --> 00:03:46,280 Speaker 3: could look for a lot more disruption the longer that 70 00:03:46,400 --> 00:03:49,640 Speaker 3: drags out with the cloud of uncertainty hanging over it, 71 00:03:49,800 --> 00:03:51,120 Speaker 3: as it has for several weeks. 72 00:03:51,440 --> 00:03:54,280 Speaker 4: And but what about the big company. Let's say Walmarts 73 00:03:54,280 --> 00:03:57,280 Speaker 4: and Targets are retailers. They have to replenish their inventories. 74 00:03:57,320 --> 00:03:58,400 Speaker 4: Where do they stand in all this? 75 00:03:59,600 --> 00:04:01,400 Speaker 3: Yeah, so this is a big story we have out 76 00:04:01,400 --> 00:04:05,480 Speaker 3: today is that retailers like Walmart and Target, the big 77 00:04:05,480 --> 00:04:09,400 Speaker 3: ones and small companies are looking at those one hundred 78 00:04:09,440 --> 00:04:12,600 Speaker 3: and forty five percent tariffs on goods from China and saying, 79 00:04:12,840 --> 00:04:15,000 Speaker 3: we can't do that, we can't afford that. That's twice, 80 00:04:15,200 --> 00:04:17,200 Speaker 3: well more than twice what we could pay. So we're 81 00:04:17,240 --> 00:04:19,799 Speaker 3: just canceling orders from China. And so what we're seeing 82 00:04:20,279 --> 00:04:23,560 Speaker 3: is in a couple of weeks when those orders would 83 00:04:23,600 --> 00:04:26,960 Speaker 3: have already gotten here. We're going to see volumes through 84 00:04:27,120 --> 00:04:29,720 Speaker 3: US ports go down. We're going to see inventories through 85 00:04:29,839 --> 00:04:33,400 Speaker 3: warehouses go down, and in the big retailers have even 86 00:04:33,440 --> 00:04:36,480 Speaker 3: said privately to President Trump, according to our reporting, that 87 00:04:36,680 --> 00:04:39,200 Speaker 3: you know, this could be this could mean shortages and 88 00:04:39,279 --> 00:04:44,760 Speaker 3: price hikes. So the wave of decoupling that is underway 89 00:04:44,839 --> 00:04:48,200 Speaker 3: between China and the US hasn't really hit the real economy. 90 00:04:48,279 --> 00:04:52,120 Speaker 3: Right now, we hear the administration say, oh, well, you know, 91 00:04:52,360 --> 00:04:54,120 Speaker 3: Wall Street has had a good run. It's time for 92 00:04:54,200 --> 00:04:56,839 Speaker 3: us to focus on Main Street. We'll main streets about 93 00:04:56,880 --> 00:04:59,960 Speaker 3: ready to get hit with some of this, and unless 94 00:05:00,120 --> 00:05:03,800 Speaker 3: things change fast, then we're going to start seeing it 95 00:05:04,279 --> 00:05:07,160 Speaker 3: in in a lot of in some layoffs in in 96 00:05:07,160 --> 00:05:11,839 Speaker 3: industries like trucking and logistics and warehousing where really the 97 00:05:12,000 --> 00:05:15,400 Speaker 3: rubber meets the road between trade and the US economy. 98 00:05:16,000 --> 00:05:17,720 Speaker 5: Are we past the point of no return? 99 00:05:17,760 --> 00:05:20,480 Speaker 2: Brendan, in terms of some of the economic damage that 100 00:05:20,560 --> 00:05:24,479 Speaker 2: could be done, you know, in terms of supply chain 101 00:05:24,560 --> 00:05:27,839 Speaker 2: not getting the stuff that we typically get. 102 00:05:28,720 --> 00:05:30,800 Speaker 5: Well in the short in the short run. 103 00:05:31,120 --> 00:05:34,560 Speaker 3: If President Trump announced later today that which nobody would 104 00:05:34,600 --> 00:05:37,400 Speaker 3: expect this, that he was he was freezing all tariffs 105 00:05:37,440 --> 00:05:39,240 Speaker 3: and we were gonna this was gonna be he was 106 00:05:39,279 --> 00:05:40,720 Speaker 3: going to try to do this another way. If he 107 00:05:40,800 --> 00:05:44,920 Speaker 3: kind of backpedaled on everything, we'd still have a supply whiplash. 108 00:05:44,960 --> 00:05:48,000 Speaker 3: All those canceled orders would be placed again, and we 109 00:05:48,040 --> 00:05:52,239 Speaker 3: would have, you know, the volumes surging through US ports. 110 00:05:52,240 --> 00:05:55,279 Speaker 3: And we saw during the pandemic what happens when when 111 00:05:55,560 --> 00:05:59,920 Speaker 3: the the nodes of of supply change get bogged down. 112 00:06:00,440 --> 00:06:02,760 Speaker 3: Is we had one hundred and twenty ships parked outside 113 00:06:02,760 --> 00:06:06,599 Speaker 3: the port of Long Beach in Los Angeles. So that's 114 00:06:06,600 --> 00:06:08,400 Speaker 3: the kind of thing. Most people don't think it's going 115 00:06:08,440 --> 00:06:11,560 Speaker 3: to happen on that kind of scale, but the system 116 00:06:11,680 --> 00:06:16,680 Speaker 3: can't handle big declines or surges in volumes, and that's 117 00:06:16,800 --> 00:06:19,600 Speaker 3: what we're looking at over the next several weeks or 118 00:06:19,600 --> 00:06:20,360 Speaker 3: a few months. 119 00:06:20,600 --> 00:06:22,800 Speaker 2: All right, Brendan, thank you so much for joining us Avius. 120 00:06:22,839 --> 00:06:26,440 Speaker 2: Appreciate getting your reporting. That's Brendan Murray, a Global trade 121 00:06:26,520 --> 00:06:29,360 Speaker 2: editor for Bloomberg News joining us from London. And again 122 00:06:29,400 --> 00:06:32,279 Speaker 2: there's some reporting out of Bloomberg and others over the weekend, 123 00:06:32,400 --> 00:06:37,360 Speaker 2: just simply the volume of ships leaving Chinese ports setting 124 00:06:37,400 --> 00:06:40,440 Speaker 2: sail for presumably the west coast of the US, and 125 00:06:40,440 --> 00:06:42,920 Speaker 2: we often talk to Gene Soroca, who runs the Port 126 00:06:43,279 --> 00:06:46,840 Speaker 2: of Los Angeles on Long Beach. We'll search to get 127 00:06:46,880 --> 00:06:48,320 Speaker 2: back in touch with them in the next couple of days. 128 00:06:48,360 --> 00:06:50,839 Speaker 2: But some of those sailings have declined dramatically just in 129 00:06:50,839 --> 00:06:53,120 Speaker 2: the last couple of weeks. So perhaps that's reflecting what 130 00:06:53,120 --> 00:06:56,479 Speaker 2: was Brendan was suggesting, was maybe some canceled orders from 131 00:06:56,520 --> 00:06:58,560 Speaker 2: some US wholesalers and retailers. 132 00:06:58,560 --> 00:06:59,960 Speaker 5: Will stay on top of that story. 133 00:07:01,760 --> 00:07:05,440 Speaker 1: You're listening to the Bloomberg Intelligence podcast. Catch us live 134 00:07:05,520 --> 00:07:08,919 Speaker 1: weekdays at ten am Eastern on Applecarclay, and Android Auto 135 00:07:09,000 --> 00:07:12,080 Speaker 1: with the Bloomberg Business app. Listen on demand wherever you 136 00:07:12,120 --> 00:07:15,120 Speaker 1: get your podcasts, or watch us live on YouTube. 137 00:07:15,560 --> 00:07:17,400 Speaker 2: All right, big earnings week out there for the S 138 00:07:17,440 --> 00:07:20,080 Speaker 2: ANDP five hundred. We have twenty trillion dollars in market cap. 139 00:07:20,480 --> 00:07:22,440 Speaker 5: It's going to report earnings this week. That is big. 140 00:07:22,440 --> 00:07:23,920 Speaker 5: We had about eleven billion last week. 141 00:07:23,920 --> 00:07:25,800 Speaker 2: And some of the big companies that can report and 142 00:07:25,800 --> 00:07:27,720 Speaker 2: are the technology companies, and you really want to get 143 00:07:27,760 --> 00:07:29,120 Speaker 2: a handle on kind of how they're. 144 00:07:29,000 --> 00:07:30,800 Speaker 5: Viewing the world these days. So we asked a couple 145 00:07:30,840 --> 00:07:32,520 Speaker 5: of the smart folks that we know to to join 146 00:07:32,600 --> 00:07:32,840 Speaker 5: us here. 147 00:07:32,880 --> 00:07:36,360 Speaker 2: Anurag Rana Man Deep singing their senior technology channels for 148 00:07:36,440 --> 00:07:40,040 Speaker 2: Bloomberg Intelligence. Honra joins us from Chicago, and Mandeep is 149 00:07:40,040 --> 00:07:42,680 Speaker 2: in our Bloomberg Interactive Brokers studio Man Deal. 150 00:07:43,000 --> 00:07:43,920 Speaker 5: Let me start with you here. 151 00:07:43,960 --> 00:07:45,840 Speaker 2: I mean, just given what you've heard so far from 152 00:07:45,840 --> 00:07:48,280 Speaker 2: some of the big tech companies and what you expect 153 00:07:48,440 --> 00:07:51,360 Speaker 2: this week, how is how are some of the companies, 154 00:07:51,360 --> 00:07:53,760 Speaker 2: these big technology companies, which had been real drivers for 155 00:07:53,840 --> 00:07:56,560 Speaker 2: the stock market, how are they kind of saying they're 156 00:07:56,600 --> 00:07:58,000 Speaker 2: seeing the world out there these days? 157 00:07:58,480 --> 00:07:58,680 Speaker 6: Yeah? 158 00:07:58,760 --> 00:08:01,880 Speaker 7: I think in the case of Meta, I mean clearly 159 00:08:02,560 --> 00:08:07,560 Speaker 7: they are exposed to the deminimous rule where companies in 160 00:08:07,640 --> 00:08:12,440 Speaker 7: China can't really ship any products below eight hundred dollars anymore. 161 00:08:12,760 --> 00:08:15,560 Speaker 7: And that was a big driver of ad spending from 162 00:08:15,680 --> 00:08:19,440 Speaker 7: Timu and Chain and some of these advertisers. So that's 163 00:08:19,480 --> 00:08:23,920 Speaker 7: going to impact Meta. We saw in the case of Alphabet, 164 00:08:24,160 --> 00:08:28,920 Speaker 7: the click ads grew only two percent, the pricing was 165 00:08:29,000 --> 00:08:32,520 Speaker 7: relatively stable. So I think in the case of Meta, 166 00:08:32,600 --> 00:08:35,800 Speaker 7: the ad pricing may come under more pressure compared to 167 00:08:36,040 --> 00:08:40,559 Speaker 7: an alphabet, and the ad impressions may be better than alphabet. 168 00:08:40,679 --> 00:08:45,760 Speaker 7: So because of the FTC case against Meta and similarly 169 00:08:45,800 --> 00:08:49,160 Speaker 7: for Alphabet. These companies have regulatory pressures as well, but 170 00:08:49,200 --> 00:08:51,960 Speaker 7: there is no doubt that the macro environment has changed 171 00:08:51,960 --> 00:08:55,360 Speaker 7: for the worse. And I don't see, you know, even 172 00:08:55,400 --> 00:08:57,640 Speaker 7: though the impact would show up more in two Q, 173 00:08:58,200 --> 00:09:01,080 Speaker 7: I don't see how they guide better than they did 174 00:09:01,160 --> 00:09:02,360 Speaker 7: in the fourth quarter. 175 00:09:02,600 --> 00:09:04,840 Speaker 4: What about AI spend? How much of an impact is 176 00:09:04,880 --> 00:09:06,920 Speaker 4: that going to have? Are the investors going to be 177 00:09:06,960 --> 00:09:07,559 Speaker 4: looking to that? 178 00:09:08,640 --> 00:09:11,840 Speaker 7: So Meta raised their CAPEX the last time they reported 179 00:09:12,000 --> 00:09:14,640 Speaker 7: to sixty five billion, and in between there was news 180 00:09:14,679 --> 00:09:18,160 Speaker 7: that Meta is looking for an Amazon and Microsoft to 181 00:09:18,280 --> 00:09:21,800 Speaker 7: share some of that capex because they have an open 182 00:09:21,880 --> 00:09:26,400 Speaker 7: source model. So I think they're under pressure to kind 183 00:09:26,440 --> 00:09:29,959 Speaker 7: of cut back on the CAPEX or the reality lab spend. 184 00:09:30,360 --> 00:09:33,000 Speaker 7: But so far no one has pulled back on AI 185 00:09:33,160 --> 00:09:36,280 Speaker 7: capex given you are still in a supply constrained environment 186 00:09:36,280 --> 00:09:39,800 Speaker 7: when it comes to the GPUs and overall AI infrastructure. 187 00:09:39,840 --> 00:09:41,840 Speaker 7: So it'll be interesting to see what they end up doing. 188 00:09:41,920 --> 00:09:44,560 Speaker 2: Hey, Anurag, you know, I kind of think with even 189 00:09:44,600 --> 00:09:47,200 Speaker 2: within technology, which is such a great growth story and 190 00:09:47,960 --> 00:09:50,800 Speaker 2: can batter some slowdowns, I think of the software companies 191 00:09:50,800 --> 00:09:52,240 Speaker 2: that you cover is kind of maybe one of the 192 00:09:52,320 --> 00:09:55,520 Speaker 2: safer places to be within technology. What do you expect 193 00:09:55,520 --> 00:09:57,400 Speaker 2: to hear from the Microsoft's of the world. 194 00:09:59,440 --> 00:10:02,000 Speaker 6: Yes, you know, on a relative basis, I think you're 195 00:10:02,080 --> 00:10:04,640 Speaker 6: right about that. But at the same time, they do 196 00:10:04,760 --> 00:10:07,640 Speaker 6: have an impact on the second degree demand. If the 197 00:10:08,080 --> 00:10:10,800 Speaker 6: enterprise text spending starts to cut down, you know, that 198 00:10:10,880 --> 00:10:13,760 Speaker 6: has an impact on software space as well. So so 199 00:10:13,880 --> 00:10:15,960 Speaker 6: that's the something we will be looking for. But I 200 00:10:15,960 --> 00:10:18,680 Speaker 6: would agree with Mandib that we are not anticipating a 201 00:10:18,760 --> 00:10:23,760 Speaker 6: drop in capex either from Microsoft or AWS later this week, 202 00:10:23,800 --> 00:10:26,360 Speaker 6: because that those are the names that dictate a lot 203 00:10:26,440 --> 00:10:28,800 Speaker 6: in terms of, you know, how AI spend will shape 204 00:10:28,840 --> 00:10:30,880 Speaker 6: up over the next twelve months. 205 00:10:31,480 --> 00:10:34,079 Speaker 2: Where within the text act on a route do you 206 00:10:34,080 --> 00:10:36,800 Speaker 2: think you could see maybe some of the biggest exposure 207 00:10:36,840 --> 00:10:40,240 Speaker 2: to I guess just tariffs and maybe a slowing global economy. 208 00:10:41,080 --> 00:10:43,120 Speaker 6: Yeah, so Apple is going to be in front and 209 00:10:43,200 --> 00:10:46,080 Speaker 6: center over there. There's so much news about you know, 210 00:10:46,120 --> 00:10:49,000 Speaker 6: their ability to move the supply chain that's not that easy. 211 00:10:49,360 --> 00:10:52,720 Speaker 6: We do anticipate some pull forward and demand for them. 212 00:10:52,800 --> 00:10:55,319 Speaker 6: We know the you know, Apple stores were really crowded 213 00:10:55,920 --> 00:10:58,320 Speaker 6: before the tariff date, and you know that that will 214 00:10:58,320 --> 00:11:00,480 Speaker 6: show up in some of the numbers. But the question 215 00:11:00,559 --> 00:11:02,360 Speaker 6: is going to be what kind of guidance can they give, 216 00:11:02,400 --> 00:11:04,360 Speaker 6: and in fact, if they can even give guidance at 217 00:11:04,400 --> 00:11:06,720 Speaker 6: this point, and you know, how if there is a 218 00:11:06,760 --> 00:11:09,080 Speaker 6: big number that goes up on tatifs can they even 219 00:11:09,160 --> 00:11:10,920 Speaker 6: fulfill the demand. So there's going to be a lot 220 00:11:10,920 --> 00:11:14,000 Speaker 6: of noise around that supply chain and what they're doing 221 00:11:14,040 --> 00:11:16,439 Speaker 6: to offset that, both in the near term and in 222 00:11:16,480 --> 00:11:17,200 Speaker 6: the long term. 223 00:11:17,600 --> 00:11:19,720 Speaker 4: And the other big story for today IBM planning to 224 00:11:19,720 --> 00:11:21,600 Speaker 4: invest one hundred and fifty billion in the US over 225 00:11:21,600 --> 00:11:23,880 Speaker 4: the next five years. Mandy, can you break it down 226 00:11:23,920 --> 00:11:26,120 Speaker 4: for us? What does that include? That's a pretty big number. 227 00:11:27,000 --> 00:11:29,720 Speaker 7: Yeah, I mean, look in the case of five AM, 228 00:11:29,800 --> 00:11:34,000 Speaker 7: they are not a big spender on AI capex, so clearly, 229 00:11:34,160 --> 00:11:37,880 Speaker 7: you know, they are looking to expand in terms of 230 00:11:37,920 --> 00:11:41,520 Speaker 7: their own investments, whether it's mainframe related or any other 231 00:11:41,600 --> 00:11:45,400 Speaker 7: type of R and D around quantum. But we've heard 232 00:11:45,440 --> 00:11:48,680 Speaker 7: that from Apple, you know, five hundred billion dollars over 233 00:11:48,720 --> 00:11:52,040 Speaker 7: the next four years. So a lot of these tech 234 00:11:52,080 --> 00:11:56,720 Speaker 7: companies are looking to appease the administration, which is keen 235 00:11:56,760 --> 00:12:01,400 Speaker 7: to you know, bring manufacturing back. Interesting to see where 236 00:12:01,520 --> 00:12:06,640 Speaker 7: IBM sort of thinks about investing the one hundred and 237 00:12:06,640 --> 00:12:08,920 Speaker 7: fifty billion dollars because, as I said, they're not a 238 00:12:08,920 --> 00:12:12,360 Speaker 7: big player when it comes to the AI infrastructure play 239 00:12:12,400 --> 00:12:14,400 Speaker 7: that the other hyperscalers are involved in. 240 00:12:14,840 --> 00:12:16,920 Speaker 2: Hey, an er, guessin you remember a lot of the 241 00:12:16,960 --> 00:12:20,280 Speaker 2: CEOs that you and man deep cover making their way 242 00:12:20,280 --> 00:12:23,080 Speaker 2: to Washington, DC over the last three four months having 243 00:12:23,160 --> 00:12:26,439 Speaker 2: meetings with the President members of administration. Is there a 244 00:12:26,520 --> 00:12:29,559 Speaker 2: sense that they're getting the benefit of that or is 245 00:12:29,600 --> 00:12:32,719 Speaker 2: it having any impact because I'm not sure I see that. 246 00:12:34,040 --> 00:12:36,959 Speaker 6: Well. One could argue that, you know, the smartphone exemptions 247 00:12:37,000 --> 00:12:39,400 Speaker 6: that we got or the consumer electronics may have had 248 00:12:39,440 --> 00:12:41,679 Speaker 6: something to do with it. But we'll find out if 249 00:12:41,679 --> 00:12:44,600 Speaker 6: that can continue or not. But you know, frankly speaking, 250 00:12:45,040 --> 00:12:48,600 Speaker 6: these companies are the ones that are really putting us 251 00:12:48,640 --> 00:12:51,480 Speaker 6: at the forefront. I will be very surprised if we 252 00:12:51,559 --> 00:12:55,439 Speaker 6: see a much more hostile behavior against them. The big 253 00:12:55,520 --> 00:12:58,160 Speaker 6: question is Hasmond you mentioned there are a few antitrust 254 00:12:58,200 --> 00:13:00,840 Speaker 6: cases going across them right now. For a bunch of 255 00:13:00,880 --> 00:13:04,600 Speaker 6: these companies, we'll find out how the administration takes over 256 00:13:04,880 --> 00:13:08,520 Speaker 6: or you know, puts their credibility or the backing behind 257 00:13:08,559 --> 00:13:09,160 Speaker 6: those deals. 258 00:13:09,760 --> 00:13:12,480 Speaker 4: Man, if you mentioned before quantum computing when we were 259 00:13:12,480 --> 00:13:14,440 Speaker 4: talking about IBM, I mean, are we going to be 260 00:13:14,520 --> 00:13:18,000 Speaker 4: hearing more and more of that come in the future, 261 00:13:18,000 --> 00:13:19,719 Speaker 4: because we've been hearing so much about AI. But is 262 00:13:19,800 --> 00:13:21,520 Speaker 4: quantum kind of going to move forward? 263 00:13:22,400 --> 00:13:25,200 Speaker 7: I think at this point, you know, given the macro 264 00:13:25,320 --> 00:13:28,320 Speaker 7: environment we are in, I would focus more on what 265 00:13:28,360 --> 00:13:32,400 Speaker 7: the companies think, as you know, monetizable in the near term. 266 00:13:32,640 --> 00:13:35,600 Speaker 7: Quantum would be further out. At the same time, I mean, 267 00:13:35,679 --> 00:13:39,080 Speaker 7: could you know one to two percent of those CAPEX 268 00:13:39,160 --> 00:13:42,360 Speaker 7: dollars go into quantum, Yes, but the big chunk would 269 00:13:42,400 --> 00:13:47,400 Speaker 7: still be allocated towards AI and you know, specifically inferencing, 270 00:13:47,520 --> 00:13:50,839 Speaker 7: because everyone seems to be quite bullish about the type 271 00:13:50,840 --> 00:13:54,200 Speaker 7: of use cases that are emerging around AI agents and 272 00:13:54,240 --> 00:13:56,600 Speaker 7: what it means for the overall enterprises. 273 00:13:57,240 --> 00:13:59,080 Speaker 2: All Right, fellows, thank you so much for joining us. 274 00:13:59,080 --> 00:14:01,600 Speaker 2: Always appreciate getting you guys, particularly when we get you 275 00:14:01,600 --> 00:14:04,760 Speaker 2: guys together on rog Rana. Man deep seeing there to 276 00:14:04,800 --> 00:14:08,360 Speaker 2: two folks that kind of run our global technology research 277 00:14:08,400 --> 00:14:11,640 Speaker 2: effort at Bloomberg Intelligence, and like you have to do. 278 00:14:11,800 --> 00:14:15,920 Speaker 2: Technology is a global business. Therefore you need to have 279 00:14:16,000 --> 00:14:18,600 Speaker 2: expertise on the ground all around the world, and we 280 00:14:18,679 --> 00:14:22,440 Speaker 2: do Asia, Europe, North America. We've got it covered for you, 281 00:14:22,440 --> 00:14:24,920 Speaker 2: and man Deep and on rog run that business for us. 282 00:14:25,000 --> 00:14:27,080 Speaker 2: We appreciate getting a couple of minutes of their time. 283 00:14:27,120 --> 00:14:29,840 Speaker 2: It's gonna be a big week for earnings continued big 284 00:14:29,880 --> 00:14:32,520 Speaker 2: week for technology companies to what extent is their business 285 00:14:32,560 --> 00:14:35,480 Speaker 2: be impacted by some of the economic uncertainty that may 286 00:14:35,480 --> 00:14:37,760 Speaker 2: be building out there as a result of maybe some 287 00:14:37,880 --> 00:14:41,880 Speaker 2: uncertain tariff policy issues. So we'll see how that plays 288 00:14:41,880 --> 00:14:44,720 Speaker 2: out this week when you get more again twenty trillion 289 00:14:44,760 --> 00:14:47,560 Speaker 2: dollars in market cap those companies reporting this week. 290 00:14:49,200 --> 00:14:52,880 Speaker 1: You're listening to the Bloomberg Intelligence Podcast. Catch us live 291 00:14:52,960 --> 00:14:56,440 Speaker 1: weekdays at ten am Eastern on applecarcklay and Android Auto 292 00:14:56,480 --> 00:14:59,480 Speaker 1: with the Bloomberg Business App. Listen on demand wherever you 293 00:14:59,520 --> 00:15:02,760 Speaker 1: get your or watch us live on YouTube. 294 00:15:03,320 --> 00:15:05,720 Speaker 2: And we've got a lot of economic data, and maybe 295 00:15:05,960 --> 00:15:07,520 Speaker 2: the question is when are we can start seeing some 296 00:15:07,600 --> 00:15:10,800 Speaker 2: of the uncertainty in some of the economic data, whether 297 00:15:10,800 --> 00:15:12,520 Speaker 2: it's GDP or inflation. 298 00:15:12,160 --> 00:15:14,040 Speaker 5: And that kind of thing. So we got attention to that. 299 00:15:14,200 --> 00:15:16,640 Speaker 2: So if you're a professional money manager, there's plenty to 300 00:15:16,680 --> 00:15:19,440 Speaker 2: keep you busy. Kim Farest, founder and chief investment officer 301 00:15:19,480 --> 00:15:22,920 Speaker 2: Bouque Capital Partners Joints this year, Kim, kind of with 302 00:15:23,000 --> 00:15:25,440 Speaker 2: that set up, what do you think is driving socks here? 303 00:15:25,440 --> 00:15:29,760 Speaker 2: Do we earnings or some of this bigger I guess 304 00:15:29,800 --> 00:15:33,520 Speaker 2: economic data issues or is it just what comes out 305 00:15:33,560 --> 00:15:37,080 Speaker 2: of the Twitter account or ex account or of a 306 00:15:37,120 --> 00:15:37,840 Speaker 2: certain president. 307 00:15:39,360 --> 00:15:41,840 Speaker 8: I think all of the above. But here's what I've 308 00:15:41,920 --> 00:15:44,520 Speaker 8: learned from doing this for the past. I can't believe 309 00:15:44,560 --> 00:15:48,440 Speaker 8: that twenty six years of looking at markets is in 310 00:15:49,120 --> 00:15:52,320 Speaker 8: a given day they can really only process one or 311 00:15:52,360 --> 00:15:56,000 Speaker 8: two ideas. I kid you not. If you go back 312 00:15:56,480 --> 00:16:00,080 Speaker 8: to what happened on Friday, you can suss out what 313 00:16:00,080 --> 00:16:02,960 Speaker 8: what drove the market? What was and you look at 314 00:16:02,960 --> 00:16:05,320 Speaker 8: the stocks, and you look at the data that comes 315 00:16:05,360 --> 00:16:08,240 Speaker 8: out and you go, Aha, this is what drove the market. 316 00:16:08,560 --> 00:16:11,200 Speaker 8: So I'm going to make a bold prediction that the 317 00:16:11,320 --> 00:16:14,880 Speaker 8: thing that drove the markets last year clearly was in 318 00:16:14,960 --> 00:16:18,280 Speaker 8: Nvidia and the AI trade. And this week we're going 319 00:16:18,360 --> 00:16:20,800 Speaker 8: to get a little bit more information on whether or 320 00:16:20,880 --> 00:16:23,640 Speaker 8: not the AI trade is dead, and I think the 321 00:16:23,680 --> 00:16:26,640 Speaker 8: answer is no, because we got a sneak peek from 322 00:16:26,640 --> 00:16:29,960 Speaker 8: what happened on Thursday. I think it was Thursday. Every 323 00:16:30,040 --> 00:16:35,600 Speaker 8: day seems like a lifetime anyhow with Google, and Google 324 00:16:36,200 --> 00:16:39,840 Speaker 8: reiterated that they are going to continue spending on their 325 00:16:39,880 --> 00:16:44,880 Speaker 8: AI build out, and so we expect Microsoft, Meta, and 326 00:16:45,200 --> 00:16:47,560 Speaker 8: Amazon to all say the same thing. 327 00:16:47,760 --> 00:16:51,520 Speaker 9: It's actually a very good point. And Kim, I've been 328 00:16:51,520 --> 00:16:53,400 Speaker 9: asking the question all morning are we going to see 329 00:16:53,440 --> 00:16:56,800 Speaker 9: more cost cuts? Because there was a story in the 330 00:16:56,840 --> 00:17:03,080 Speaker 9: Wall Street Journal that said corporate CEOs are like saying 331 00:17:03,080 --> 00:17:05,879 Speaker 9: the market version of the serenity prayer right now. Costs 332 00:17:05,880 --> 00:17:08,679 Speaker 9: are the only thing that they can really control, and 333 00:17:08,680 --> 00:17:11,520 Speaker 9: in the face of total uncertainty, that's the lever they're pulling. 334 00:17:11,600 --> 00:17:14,960 Speaker 9: But I was talking with Gargey chow Duri of Blackrock 335 00:17:15,000 --> 00:17:17,959 Speaker 9: this morning and she said, well, you know what, Google 336 00:17:18,000 --> 00:17:21,800 Speaker 9: didn't cut its capex, so maybe we won't see cutting 337 00:17:21,880 --> 00:17:25,080 Speaker 9: capex from the other hyperscalers. And that's really what's driving 338 00:17:26,000 --> 00:17:28,560 Speaker 9: this market, is that AI trade that that you know, 339 00:17:28,600 --> 00:17:32,880 Speaker 9: we obviously saw so big last year. What about other 340 00:17:32,960 --> 00:17:35,119 Speaker 9: companies though, Kim, are you worried that we're going to 341 00:17:35,160 --> 00:17:38,919 Speaker 9: start seeing especially smaller companies start to fire our employees, 342 00:17:39,240 --> 00:17:43,080 Speaker 9: start to you know, close down stores, start to reduce 343 00:17:43,160 --> 00:17:44,320 Speaker 9: costs wherever they can. 344 00:17:46,000 --> 00:17:49,720 Speaker 8: So the answer is always yes, right for the troubled, 345 00:17:50,119 --> 00:17:55,560 Speaker 8: like Macy's is going to close a store in this 346 00:17:55,920 --> 00:17:58,159 Speaker 8: I don't know how big. It was a huge, huge 347 00:17:58,200 --> 00:18:02,280 Speaker 8: mall and there's only three things it now maybe four 348 00:18:02,320 --> 00:18:05,879 Speaker 8: if you consider the collectibles shop that's in there as well. 349 00:18:06,040 --> 00:18:09,200 Speaker 9: That's amazing business. That's like something it really doesn't. 350 00:18:09,240 --> 00:18:12,600 Speaker 8: But that's I'm painting this right. Joanne Fabrics pulled the 351 00:18:12,640 --> 00:18:15,600 Speaker 8: plug there, but we've got Macy's that is now going 352 00:18:15,600 --> 00:18:18,399 Speaker 8: to pull the plug. Dick's Sporting Goods is going to 353 00:18:18,760 --> 00:18:21,360 Speaker 8: pull the plug. But the township of Frasier has its 354 00:18:22,680 --> 00:18:25,840 Speaker 8: township building in that building. But it's massive. It is 355 00:18:25,880 --> 00:18:28,359 Speaker 8: the hugest, most empty building I've ever seen in my 356 00:18:28,520 --> 00:18:32,280 Speaker 8: entire life. But that is what we get is companies 357 00:18:32,280 --> 00:18:35,160 Speaker 8: that aren't succeeding are going to reshuffle the decks. 358 00:18:35,160 --> 00:18:35,800 Speaker 7: Now Dixon is. 359 00:18:35,800 --> 00:18:38,840 Speaker 8: Doing pretty well, but in that mall, nobody's going to 360 00:18:38,880 --> 00:18:41,199 Speaker 8: the mall. They're going to move somewhere else, no kidding. 361 00:18:41,240 --> 00:18:43,840 Speaker 8: So that goes on all the time. But the I 362 00:18:43,880 --> 00:18:47,240 Speaker 8: would even say smaller companies that are successful are not 363 00:18:47,359 --> 00:18:51,520 Speaker 8: going to just indiscriminately higher. What companies do have right 364 00:18:51,560 --> 00:18:54,560 Speaker 8: now is technology that tells them what the pipeline is 365 00:18:54,600 --> 00:18:58,119 Speaker 8: doing in real time. Most even small companies have a 366 00:18:58,200 --> 00:19:01,439 Speaker 8: CRM system where they can see what demand looks like. 367 00:19:01,840 --> 00:19:05,200 Speaker 8: And I think that is going to drive things, not tweets, 368 00:19:05,800 --> 00:19:09,920 Speaker 8: not you know, headlines. It's going to be what's happening 369 00:19:09,960 --> 00:19:12,800 Speaker 8: with our business. And if your business is sick, you're 370 00:19:12,800 --> 00:19:13,400 Speaker 8: going to make some. 371 00:19:13,400 --> 00:19:16,200 Speaker 5: Cuts, Kim. I mean looking at the S and P. 372 00:19:16,640 --> 00:19:18,840 Speaker 2: I made the comment earlier that depends on kind of 373 00:19:18,920 --> 00:19:20,639 Speaker 2: your glass half end to your half full kind of 374 00:19:20,640 --> 00:19:23,639 Speaker 2: person that you know. The the bad news is that 375 00:19:24,040 --> 00:19:26,480 Speaker 2: the S and p's down, you know, ten percent roughly from. 376 00:19:26,320 --> 00:19:27,720 Speaker 5: Its peak earlier this year. 377 00:19:27,880 --> 00:19:29,960 Speaker 2: The good news is that it's up ten percent from 378 00:19:30,320 --> 00:19:32,800 Speaker 2: the bottom. How do you view kind of the what's 379 00:19:32,840 --> 00:19:35,919 Speaker 2: going on out there in the stock market generally, Well. 380 00:19:35,760 --> 00:19:41,080 Speaker 8: Again, I'm kind of a mathematician, that's my basic training 381 00:19:41,440 --> 00:19:43,800 Speaker 8: was That's what I graduated with a degree in that 382 00:19:43,920 --> 00:19:46,840 Speaker 8: and computer science. So I like to take apart the 383 00:19:46,880 --> 00:19:48,800 Speaker 8: pieces of the S and P. And if I look 384 00:19:48,840 --> 00:19:51,520 Speaker 8: at what was driving the S and P last year 385 00:19:51,920 --> 00:19:54,840 Speaker 8: and pretty much through the end of the year was 386 00:19:54,960 --> 00:19:58,520 Speaker 8: the AI trade. So that's the big mag seven. I 387 00:19:58,520 --> 00:20:01,720 Speaker 8: was going to call them the Big seven mag seven 388 00:20:01,920 --> 00:20:05,159 Speaker 8: and then you know, especially in Vidia. Now Nvidia has 389 00:20:05,200 --> 00:20:11,960 Speaker 8: come down a lot, right, yeah, yeah, so that is 390 00:20:12,119 --> 00:20:14,919 Speaker 8: overweight in the S and P or it was really 391 00:20:14,960 --> 00:20:18,080 Speaker 8: overweight in the S and P five hundred calculation. So 392 00:20:18,160 --> 00:20:19,960 Speaker 8: you have to look at that, and if you look 393 00:20:20,000 --> 00:20:23,200 Speaker 8: at the rest of the S and P five hundred, 394 00:20:23,240 --> 00:20:27,000 Speaker 8: they're really not going all that up or down. Right 395 00:20:27,440 --> 00:20:30,040 Speaker 8: that most of that dip down and dip back up 396 00:20:30,320 --> 00:20:34,200 Speaker 8: was the Magnificent seven and that was the blessing last 397 00:20:34,280 --> 00:20:37,720 Speaker 8: year and it's the curse this year. So you index 398 00:20:37,800 --> 00:20:39,480 Speaker 8: buyers are just going to have to put. 399 00:20:39,400 --> 00:20:39,760 Speaker 5: Up with that. 400 00:20:40,920 --> 00:20:43,720 Speaker 9: It's actually at one point it was down thirty seven percent, 401 00:20:43,840 --> 00:20:47,119 Speaker 9: peaked to trough, you know, with the peak being like 402 00:20:47,359 --> 00:20:50,600 Speaker 9: the very beginning of January and the trough being two 403 00:20:50,680 --> 00:20:54,720 Speaker 9: weeks ago. We've had a pretty powerful rally though over 404 00:20:54,760 --> 00:20:58,479 Speaker 9: the past four days. Today it's you know, looking not 405 00:20:58,520 --> 00:21:00,560 Speaker 9: looking like it's gonna continue. 406 00:21:00,600 --> 00:21:01,720 Speaker 5: But we had. 407 00:21:01,520 --> 00:21:07,760 Speaker 9: The Swig Breadth Thrust indicator triggered for at least the 408 00:21:07,880 --> 00:21:11,480 Speaker 9: eighteenth I've seen three different estimates of how many times 409 00:21:11,520 --> 00:21:13,520 Speaker 9: have been triggered since nineteen forty three, but it's been 410 00:21:13,520 --> 00:21:18,720 Speaker 9: at least eighteen times, and each of those eighteen times, KIM, 411 00:21:18,880 --> 00:21:23,879 Speaker 9: It's resulted in double digit gains on average, like fifteen 412 00:21:23,920 --> 00:21:27,040 Speaker 9: percent six months out and twenty five percent twelve months out. 413 00:21:27,200 --> 00:21:31,600 Speaker 9: Do you put any trust into the swig breadth thrust indicator, 414 00:21:31,640 --> 00:21:38,439 Speaker 9: which basically just says NYC stocks only, I think forty 415 00:21:38,480 --> 00:21:41,960 Speaker 9: percent of them were at new highs, and then within 416 00:21:42,000 --> 00:21:44,440 Speaker 9: ten days sixty one and a half. 417 00:21:44,240 --> 00:21:46,040 Speaker 5: Percent of them were at new hives. Totally clear. 418 00:21:46,280 --> 00:21:49,800 Speaker 8: Yeah, so I'm going to use one of my favorite 419 00:21:49,800 --> 00:21:53,359 Speaker 8: phrases that I think irritate people. That's interesting but irrelevant 420 00:21:53,800 --> 00:22:01,320 Speaker 8: because the truth is a lot. And remember, I'm a 421 00:22:01,359 --> 00:22:03,680 Speaker 8: math person. I used to be an AI person, which 422 00:22:03,720 --> 00:22:08,320 Speaker 8: is math. I love math, but it tells me what 423 00:22:08,400 --> 00:22:10,399 Speaker 8: happened in the past, not what's going to happen in 424 00:22:10,440 --> 00:22:13,480 Speaker 8: the future. And there's so much that can happen in 425 00:22:13,520 --> 00:22:19,719 Speaker 8: the future, like deals, tariff deals signed not signed, wars 426 00:22:19,760 --> 00:22:24,120 Speaker 8: not wars, you know, just everyday life. That doesn't necessarily 427 00:22:24,240 --> 00:22:27,480 Speaker 8: let you with assurance know what's going to happen to 428 00:22:27,560 --> 00:22:32,040 Speaker 8: your stocks in the future. So I'm I'm cheered by this. 429 00:22:32,160 --> 00:22:36,560 Speaker 8: If that happens, go whatever, indicator, But I'm not gonna 430 00:22:36,680 --> 00:22:39,040 Speaker 8: you know, run my money based on it. 431 00:22:39,640 --> 00:22:42,359 Speaker 9: I was excited last week about It's the swig Martin 432 00:22:42,440 --> 00:22:46,000 Speaker 9: Swig and the swag breadth thrust indicators. 433 00:22:46,440 --> 00:22:48,080 Speaker 2: All right, put that out on social media. I'm sure 434 00:22:48,080 --> 00:22:49,600 Speaker 2: that I got a lot of hits. Kim Forrest, thank 435 00:22:49,640 --> 00:22:51,640 Speaker 2: you so much for joining us. Chimis founder and chief 436 00:22:51,640 --> 00:22:53,600 Speaker 2: investment officer of Bouquet Capital Partners. 437 00:22:54,400 --> 00:22:59,080 Speaker 1: This is the Bloomberg Intelligence Podcast, available on Apple, Spotify, 438 00:22:59,280 --> 00:23:02,760 Speaker 1: and anywhere else you get your podcasts. Listen live each 439 00:23:02,760 --> 00:23:06,520 Speaker 1: weekday ten am to noon Eastern on Bloomberg dot com, 440 00:23:06,640 --> 00:23:10,160 Speaker 1: the iHeartRadio app, tune In, and the Bloomberg Business app. 441 00:23:10,600 --> 00:23:13,520 Speaker 1: You can also watch us live every weekday on YouTube 442 00:23:13,920 --> 00:23:16,200 Speaker 1: and always on the Bloomberg terminal.