1 00:00:02,480 --> 00:00:10,480 Speaker 1: Bloomberg Audio Studios, podcasts, radio news. This is the Bloomberg 2 00:00:10,520 --> 00:00:13,720 Speaker 1: Daybreak Asia podcast. I'm Doug Prisner. You can join Brian 3 00:00:13,800 --> 00:00:16,640 Speaker 1: Curtis and myself for the stories, making news and moving 4 00:00:16,680 --> 00:00:19,560 Speaker 1: markets in the APAC region. You can subscribe to the 5 00:00:19,600 --> 00:00:23,080 Speaker 1: show anywhere you get your podcast and always on Bloomberg Radio, 6 00:00:23,320 --> 00:00:26,120 Speaker 1: the Bloomberg Terminal, and the Bloomberg Business app. 7 00:00:27,240 --> 00:00:30,240 Speaker 2: Let's get to our guest, Joe Doe, Bloomberg Metals and 8 00:00:30,280 --> 00:00:33,960 Speaker 2: Mining reporter, to discuss this a little bit further. This 9 00:00:34,120 --> 00:00:37,159 Speaker 2: is just yet another obstacle along the way, isn't it. 10 00:00:37,200 --> 00:00:40,279 Speaker 3: Joe, Yeah, it really is. I think the market has 11 00:00:40,320 --> 00:00:43,640 Speaker 3: been so focused on the scipious review of the review 12 00:00:43,720 --> 00:00:48,519 Speaker 3: by the inter government agency that determines whether or not 13 00:00:48,560 --> 00:00:52,239 Speaker 3: a foreign company is okay to buy a domestic company. 14 00:00:52,280 --> 00:00:57,160 Speaker 3: But our sources today telling us that the administration is 15 00:00:57,200 --> 00:01:01,480 Speaker 3: looking at the exposure that Nimpon had to China, specifically 16 00:01:01,560 --> 00:01:05,280 Speaker 3: these nine facilities that they have in China and the 17 00:01:05,319 --> 00:01:07,840 Speaker 3: three point six million tons of capacity that they have 18 00:01:08,760 --> 00:01:11,240 Speaker 3: the ability to produce there. So I think that has 19 00:01:11,280 --> 00:01:16,119 Speaker 3: come up as another thing that investors maybe are probably 20 00:01:16,160 --> 00:01:18,720 Speaker 3: going to be looking a little bit closer at Joe. 21 00:01:18,760 --> 00:01:21,319 Speaker 1: Is this basic steel production when you talk about the 22 00:01:21,360 --> 00:01:23,600 Speaker 1: facilities in China, is it, you know, kind of the 23 00:01:23,680 --> 00:01:27,319 Speaker 1: old school you melt down the iron or you add 24 00:01:27,360 --> 00:01:29,840 Speaker 1: the coal and the limestone, or is it something that 25 00:01:29,920 --> 00:01:33,360 Speaker 1: is more contemporary when I'm thinking of recycled steel and 26 00:01:33,400 --> 00:01:36,200 Speaker 1: metal being put through an electric furnace, is it the 27 00:01:36,200 --> 00:01:38,360 Speaker 1: old school approach that's being used in China. 28 00:01:39,000 --> 00:01:41,759 Speaker 4: So it's actually neither, and it's good that you're nailing 29 00:01:41,760 --> 00:01:45,039 Speaker 4: down into this. It's these downstream products, right, It's like 30 00:01:45,280 --> 00:01:47,440 Speaker 4: bar and hype and tube. 31 00:01:47,600 --> 00:01:51,400 Speaker 3: These are things that that end users buy and they 32 00:01:51,400 --> 00:01:54,400 Speaker 3: put into you know, things like oil, you know, oil 33 00:01:54,400 --> 00:01:58,680 Speaker 3: pipelines or to roads for like the wire rod. So 34 00:01:58,800 --> 00:02:01,600 Speaker 3: it's not like traditional raw steel making as you think 35 00:02:01,600 --> 00:02:03,600 Speaker 3: of it. And I think that's another reason that it 36 00:02:03,800 --> 00:02:06,840 Speaker 3: may raise some eyebrows for folks, right, It's it's not 37 00:02:06,920 --> 00:02:09,680 Speaker 3: the kind that a New Core or US Steel or 38 00:02:09,840 --> 00:02:13,080 Speaker 3: Cleveland Cliffs has traditionally complained about in the past with 39 00:02:13,200 --> 00:02:16,480 Speaker 3: trade tariffs, you know, of dumping. But you know, listen, 40 00:02:16,560 --> 00:02:19,480 Speaker 3: we know how the political climate has been specifically around 41 00:02:19,560 --> 00:02:22,359 Speaker 3: China for many years now. And for steel, I mean 42 00:02:22,360 --> 00:02:25,040 Speaker 3: it goes back for the past twenty years, right. I 43 00:02:25,040 --> 00:02:26,480 Speaker 3: mean that's one of the things that we pointed out 44 00:02:26,520 --> 00:02:28,680 Speaker 3: in our store. There's long history intertwined here. 45 00:02:29,600 --> 00:02:31,880 Speaker 2: It gets really complicated because we don't know all that 46 00:02:31,960 --> 00:02:35,919 Speaker 2: much about these nine sites that Nippon has there in China, 47 00:02:36,040 --> 00:02:38,600 Speaker 2: although with just what was put in a note to 48 00:02:38,639 --> 00:02:43,919 Speaker 2: shareholders that these are part of its global output, you know, plans. 49 00:02:44,760 --> 00:02:48,240 Speaker 2: But it also raises a very tricky question of if 50 00:02:48,240 --> 00:02:50,880 Speaker 2: it is it Nippon steel, then is it Chinese produced 51 00:02:50,880 --> 00:02:54,600 Speaker 2: to steel? You know, is the iPhone that selled elsewhere elsewhere? 52 00:02:54,639 --> 00:02:56,760 Speaker 2: Is that a China product or is it an Apple product? 53 00:02:56,800 --> 00:02:58,639 Speaker 2: And you know, how do we put all this stuff together? 54 00:02:59,400 --> 00:02:59,560 Speaker 4: Right? 55 00:02:59,600 --> 00:03:01,840 Speaker 3: I mean, Nippon did get back to us, and they 56 00:03:01,880 --> 00:03:03,560 Speaker 3: did give us a statement which I should point out 57 00:03:03,600 --> 00:03:06,639 Speaker 3: that they said, you know, our operations in China, including 58 00:03:06,639 --> 00:03:10,120 Speaker 3: any joint ventures they have with Chinese partners, have no 59 00:03:10,240 --> 00:03:14,840 Speaker 3: control over their operations or business decisions made outside of China. 60 00:03:14,600 --> 00:03:15,600 Speaker 4: Including in the US. 61 00:03:16,040 --> 00:03:18,200 Speaker 3: So you know, I think I think that's an interesting point. 62 00:03:18,240 --> 00:03:21,880 Speaker 3: I think another interesting point is it's three point six 63 00:03:22,000 --> 00:03:26,520 Speaker 3: million tons of capacity in out of the sixty six 64 00:03:26,840 --> 00:03:30,840 Speaker 3: million tons of capacity that that Nipon has globally right, 65 00:03:30,880 --> 00:03:33,560 Speaker 3: So it's a it's a thin percentage of it. 66 00:03:35,080 --> 00:03:36,920 Speaker 4: So I think just just. 67 00:03:37,600 --> 00:03:40,080 Speaker 3: Just looking at the numbers, it's not immediately obvious that 68 00:03:40,160 --> 00:03:42,840 Speaker 3: this is necessarily some sort of threat. But I guess 69 00:03:42,880 --> 00:03:45,440 Speaker 3: this is why the administration is looking at it, right. 70 00:03:45,480 --> 00:03:47,400 Speaker 3: They're wanting to look further into it to see if 71 00:03:47,400 --> 00:03:50,120 Speaker 3: maybe it does post some sort of threat or is 72 00:03:50,120 --> 00:03:52,040 Speaker 3: some sort of issue that they should address. 73 00:03:52,240 --> 00:03:52,400 Speaker 2: Well. 74 00:03:52,440 --> 00:03:54,880 Speaker 1: At the same time, I think we have to recognize 75 00:03:54,920 --> 00:03:57,440 Speaker 1: it is in an election year. Donald Trump is already 76 00:03:57,480 --> 00:04:00,800 Speaker 1: weighed in on this deal, saying that he would scrap it, 77 00:04:01,320 --> 00:04:04,160 Speaker 1: and I'm sure that the Biden administration or the Biden 78 00:04:04,240 --> 00:04:07,440 Speaker 1: campaign would very much like the endorsement from the United 79 00:04:07,480 --> 00:04:08,520 Speaker 1: steel Workers. 80 00:04:08,240 --> 00:04:09,640 Speaker 4: Right exactly. 81 00:04:09,720 --> 00:04:13,400 Speaker 3: This boils down to one very big political issue, which 82 00:04:13,440 --> 00:04:17,000 Speaker 3: is blue collar workers. The United steel Workers have made 83 00:04:17,000 --> 00:04:19,800 Speaker 3: it clear that they do not support nipon Steel in 84 00:04:19,880 --> 00:04:23,640 Speaker 3: this deal. The United steel Workers themselves aren't It's not 85 00:04:23,680 --> 00:04:25,599 Speaker 3: like they're the big voting block, right that's going to 86 00:04:25,600 --> 00:04:27,479 Speaker 3: get one or the other over the finish line, but 87 00:04:27,520 --> 00:04:30,440 Speaker 3: they represent a very important type of voter in the 88 00:04:30,520 --> 00:04:34,279 Speaker 3: United States, the blue collar industrial worker. They are also 89 00:04:34,320 --> 00:04:37,960 Speaker 3: in a battleground state, right Pennsylvania is the headquarters of 90 00:04:38,120 --> 00:04:41,080 Speaker 3: US Steel. This is a massive state that helped get 91 00:04:41,120 --> 00:04:43,520 Speaker 3: Biden over the line in twenty twenty, and the steel 92 00:04:43,560 --> 00:04:45,599 Speaker 3: workers and many people like them got Trump over the 93 00:04:45,600 --> 00:04:49,080 Speaker 3: line in twenty sixteen. Both of these guys know what's 94 00:04:49,200 --> 00:04:52,760 Speaker 3: at stake here, and that's obviously why US Steel being 95 00:04:52,800 --> 00:04:55,479 Speaker 3: bought by a Japanese company has been thrust into the 96 00:04:55,480 --> 00:04:57,240 Speaker 3: center of this political dialogue. 97 00:04:58,080 --> 00:05:00,960 Speaker 2: You mentioned that the Nippon steel out in China from 98 00:05:01,000 --> 00:05:04,520 Speaker 2: these nine plants is reasonably small three point six million tons, 99 00:05:04,560 --> 00:05:07,680 Speaker 2: I think you said, compared to you know, a massive 100 00:05:07,680 --> 00:05:08,520 Speaker 2: total globally. 101 00:05:09,080 --> 00:05:09,760 Speaker 5: So is that the. 102 00:05:09,760 --> 00:05:14,000 Speaker 2: Type of of of kind of profile where Nippon Steel 103 00:05:14,040 --> 00:05:17,359 Speaker 2: would either sell them or dispose of them in some 104 00:05:17,520 --> 00:05:19,360 Speaker 2: other way in order to get this deal through? 105 00:05:20,400 --> 00:05:20,839 Speaker 4: Unclear? 106 00:05:20,960 --> 00:05:25,479 Speaker 3: I mean Nippon hasn't said anything about that specifically. I mean, 107 00:05:25,640 --> 00:05:27,960 Speaker 3: if you dig deep into the weeds of all the 108 00:05:28,000 --> 00:05:30,480 Speaker 3: different documents that have been put out since the deals announced, 109 00:05:30,800 --> 00:05:36,600 Speaker 3: you know it does mention that, you know, the company 110 00:05:36,600 --> 00:05:38,839 Speaker 3: will do what it takes to get this deal closed. 111 00:05:38,960 --> 00:05:41,440 Speaker 3: I don't know if they'll be willing to sell assets. 112 00:05:41,800 --> 00:05:43,760 Speaker 3: I mean that that's a that's a question that we 113 00:05:43,960 --> 00:05:46,599 Speaker 3: really should find out from them and that they maybe 114 00:05:46,600 --> 00:05:47,680 Speaker 3: should announce. 115 00:05:47,400 --> 00:05:51,240 Speaker 4: To two shareholders. But at this point it's unclear. 116 00:05:51,800 --> 00:05:54,680 Speaker 3: And you know, listen, Nippon gave us the statement that 117 00:05:54,720 --> 00:05:57,480 Speaker 3: they gave us, but it's also not even clear if 118 00:05:57,520 --> 00:06:00,480 Speaker 3: they've had a conversation with the. 119 00:06:00,240 --> 00:06:01,839 Speaker 4: White House abouts stuff like this. 120 00:06:02,000 --> 00:06:04,159 Speaker 3: So there's a lot still going on behind the scenes 121 00:06:04,200 --> 00:06:05,640 Speaker 3: that I just I think we just don't know. 122 00:06:06,040 --> 00:06:09,120 Speaker 1: Yeah, I'm wondering about you know, when you mentioned national security. 123 00:06:09,200 --> 00:06:12,880 Speaker 1: Let's just hypothetically say that there is a scenario where 124 00:06:13,360 --> 00:06:16,279 Speaker 1: India's Tata Steel were to make a bid for US Steel. 125 00:06:16,360 --> 00:06:20,760 Speaker 1: Do you think it would get the same level of scrutiny. 126 00:06:21,360 --> 00:06:24,320 Speaker 4: I don't know. I think it's US Steel. This is 127 00:06:24,320 --> 00:06:27,240 Speaker 4: the way I look at it. It's United States Steel Corporation. 128 00:06:28,200 --> 00:06:32,400 Speaker 3: And the idea that a company that is not American, 129 00:06:32,880 --> 00:06:35,599 Speaker 3: or any company for that matter, buying United States Steel. 130 00:06:35,760 --> 00:06:39,400 Speaker 4: I think Harry is a certain symbolic weight with it. 131 00:06:40,000 --> 00:06:42,680 Speaker 3: And if you tell a bunch of guys who are 132 00:06:42,680 --> 00:06:45,760 Speaker 3: living just outside of Pittsburgh that the buyer of a 133 00:06:45,800 --> 00:06:47,920 Speaker 3: company that they've worked at, their fathers worked at, their 134 00:06:47,960 --> 00:06:51,000 Speaker 3: grandfathers worked at, and more, it's going to be snapped 135 00:06:51,080 --> 00:06:54,520 Speaker 3: up by a Japanese company. You know, their reaction probably 136 00:06:54,640 --> 00:06:57,159 Speaker 3: is like whoa, okay, wow, how did we get here? 137 00:06:57,279 --> 00:06:59,480 Speaker 4: Right? And so I think even if you said it 138 00:06:59,520 --> 00:07:00,440 Speaker 4: was a you know. 139 00:07:00,480 --> 00:07:03,920 Speaker 3: A European company which we've seen, you know, arceler Mittel 140 00:07:03,920 --> 00:07:07,640 Speaker 3: bought a lot of American steel mills, I just think 141 00:07:07,640 --> 00:07:10,760 Speaker 3: it comes with a feeling, right, And a feeling isn't 142 00:07:10,800 --> 00:07:13,680 Speaker 3: something that we can capture in numbers or something that 143 00:07:13,720 --> 00:07:15,960 Speaker 3: we can capture in data in the Bloomberg terminal. It 144 00:07:16,080 --> 00:07:19,280 Speaker 3: is something that we have to capture through stories and 145 00:07:19,360 --> 00:07:20,840 Speaker 3: telling the voice of those people. 146 00:07:21,560 --> 00:07:23,800 Speaker 2: In the old days, it could be political. The Democrats 147 00:07:23,840 --> 00:07:27,280 Speaker 2: would have supported it and the Republicans would have or 148 00:07:27,280 --> 00:07:29,760 Speaker 2: the Republicans would have supported it and the Democrats might 149 00:07:29,760 --> 00:07:32,320 Speaker 2: have rejected it because they're worried about jobs. It's all 150 00:07:32,320 --> 00:07:35,640 Speaker 2: different now, everything's completely different. Can we expect similar action 151 00:07:35,720 --> 00:07:36,880 Speaker 2: on aluminum coming soon? 152 00:07:38,560 --> 00:07:38,840 Speaker 6: Well? 153 00:07:40,400 --> 00:07:42,240 Speaker 4: Other companies buying aluminum companies? 154 00:07:42,600 --> 00:07:45,040 Speaker 5: Yeah, I mean I don't know. 155 00:07:46,120 --> 00:07:48,400 Speaker 3: You know, co Ha's got its own issues right now 156 00:07:49,600 --> 00:07:52,520 Speaker 3: in Western Australia on their box side minds and getting 157 00:07:52,560 --> 00:07:55,240 Speaker 3: approval and licenses for those that they had expect. I mean, 158 00:07:56,000 --> 00:07:59,360 Speaker 3: they didn't ever expect to have trouble with I haven't 159 00:07:59,400 --> 00:08:02,000 Speaker 3: heard talk of that, but listen, everything is up for 160 00:08:02,040 --> 00:08:04,920 Speaker 3: sale at all times, right, especially commies. 161 00:08:05,120 --> 00:08:07,200 Speaker 2: And everything's up in the air. And Joe, we appreciate 162 00:08:07,240 --> 00:08:10,000 Speaker 2: coming in and spending some time with us, even when 163 00:08:10,040 --> 00:08:12,440 Speaker 2: we don't know, you know, all of these questions and 164 00:08:12,640 --> 00:08:15,320 Speaker 2: exactly where they're going. Joe Doe there with us Bloomberg 165 00:08:15,360 --> 00:08:16,640 Speaker 2: Metal and Mining Report. 166 00:08:16,800 --> 00:08:17,600 Speaker 5: This is Bloombern. 167 00:08:25,200 --> 00:08:27,920 Speaker 2: Fred Newman joins us here in our studios in Hong Kong, 168 00:08:28,360 --> 00:08:31,080 Speaker 2: Chief Asia Economist and co head of Global Research for 169 00:08:31,200 --> 00:08:35,000 Speaker 2: Asia at HSBC. Fred, thanks very much for coming in. 170 00:08:35,440 --> 00:08:38,600 Speaker 2: You know, we cover macro conditions a lot on this program, 171 00:08:38,880 --> 00:08:42,160 Speaker 2: but on a daylight today and yesterday, the FED and 172 00:08:42,240 --> 00:08:45,839 Speaker 2: interest rates in China, geopolitics, all that sort of gets 173 00:08:45,840 --> 00:08:50,880 Speaker 2: pushed to the back burner. The earnings from Nvidia and 174 00:08:51,200 --> 00:08:54,760 Speaker 2: how it projects to other companies. How does that sit 175 00:08:54,920 --> 00:08:58,200 Speaker 2: in the overall environment for growth, Let's say, starting in 176 00:08:58,200 --> 00:08:58,959 Speaker 2: the US. 177 00:08:59,360 --> 00:09:02,440 Speaker 7: Well, that we still have booming sectors. It's not all 178 00:09:02,559 --> 00:09:04,679 Speaker 7: doom and gloom that you might sometimes think you have 179 00:09:04,920 --> 00:09:08,080 Speaker 7: clearly investment needs in the AI space, but we should 180 00:09:08,200 --> 00:09:11,280 Speaker 7: remember that's very narrowly focused. So we think about the 181 00:09:11,320 --> 00:09:15,199 Speaker 7: Asian tech supply chain, for example, it's very specific companies 182 00:09:15,440 --> 00:09:18,800 Speaker 7: in very specific segments that benefit. If you look at 183 00:09:18,840 --> 00:09:22,600 Speaker 7: the overall electronics sector, actually it hasn't really lifted just 184 00:09:22,640 --> 00:09:25,560 Speaker 7: as much. If you look, for example, at global new 185 00:09:25,720 --> 00:09:29,560 Speaker 7: orders for consumer electronics, there's still down the smartphone sector, 186 00:09:29,679 --> 00:09:33,040 Speaker 7: the laptop sector for example, not really coming up. It's 187 00:09:33,120 --> 00:09:36,600 Speaker 7: very specific that AI related investment and as of course, 188 00:09:36,800 --> 00:09:40,000 Speaker 7: and video benefits and other companies in supply chain. But 189 00:09:40,640 --> 00:09:44,240 Speaker 7: for broader growth in Asia, for Asian exports, one third 190 00:09:44,280 --> 00:09:47,080 Speaker 7: of which are electronics, to lift, we need more broader 191 00:09:47,120 --> 00:09:48,000 Speaker 7: demand to come through. 192 00:09:48,160 --> 00:09:51,400 Speaker 1: So I'm going to get a little philosophical here. Broadly speaking, Fred, 193 00:09:51,400 --> 00:09:57,680 Speaker 1: do you believe artificial intelligence has the potential to create disinflation? 194 00:10:00,200 --> 00:10:04,600 Speaker 7: It has potentially, yes, and that's not necessarily all positive. 195 00:10:04,880 --> 00:10:07,040 Speaker 7: So we know there's more investment coming in. We know 196 00:10:07,080 --> 00:10:10,280 Speaker 7: there's no servers being installed at the other side, and 197 00:10:10,280 --> 00:10:12,880 Speaker 7: we still need to see that. To what extent is 198 00:10:13,000 --> 00:10:16,800 Speaker 7: AI starting to slow down the hiring of workers that 199 00:10:16,840 --> 00:10:20,160 Speaker 7: would originally have been used in AI, for example, Right, 200 00:10:20,200 --> 00:10:22,440 Speaker 7: So that's an open question. I don't know the answer. 201 00:10:22,679 --> 00:10:25,800 Speaker 7: There's certainly productivity gains a long term technology is there, 202 00:10:25,840 --> 00:10:29,200 Speaker 7: you can't really prevent progress. But sometimes these introduction of 203 00:10:29,240 --> 00:10:31,960 Speaker 7: new technologies can be quite disruptive for the labor market, 204 00:10:32,040 --> 00:10:35,920 Speaker 7: and that obviously introduces uncertainties as well as opportunities, and 205 00:10:36,000 --> 00:10:40,240 Speaker 7: potentially then in the next few years might actually curb 206 00:10:40,400 --> 00:10:41,640 Speaker 7: job wage growth. 207 00:10:41,640 --> 00:10:42,120 Speaker 5: For example. 208 00:10:42,240 --> 00:10:45,080 Speaker 2: Yeah, some of the most dour people I know are economists, right, 209 00:10:45,120 --> 00:10:49,640 Speaker 2: and you're fitting that highlighting the negatives would not become economists, 210 00:10:49,640 --> 00:10:50,000 Speaker 2: it wasn't. 211 00:10:50,760 --> 00:10:51,480 Speaker 5: Yeah, exactly. 212 00:10:51,520 --> 00:10:53,760 Speaker 2: Well, it's good to have a sober mind in our 213 00:10:53,800 --> 00:10:57,120 Speaker 2: midst because sometimes things run a little crazy. We talked 214 00:10:57,160 --> 00:11:00,000 Speaker 2: about the huge expansion and in videos market cap today 215 00:11:00,160 --> 00:11:02,920 Speaker 2: being one and a half times Intel. I still find 216 00:11:02,920 --> 00:11:05,560 Speaker 2: that very hard to get my head around. But on 217 00:11:05,600 --> 00:11:08,040 Speaker 2: the positive side, and I think that's what really the 218 00:11:08,080 --> 00:11:12,000 Speaker 2: market's responding to is some of those productivity gains. How 219 00:11:12,000 --> 00:11:16,320 Speaker 2: AI has the potential to change the way we do business, 220 00:11:17,000 --> 00:11:20,319 Speaker 2: and it's very hard to actually compute that at the moment. 221 00:11:21,000 --> 00:11:23,160 Speaker 7: That's right, we don't know it, but the potential is 222 00:11:23,160 --> 00:11:26,679 Speaker 7: there's absolutely breathtaking. And ultimately that's what gets even Dow 223 00:11:26,800 --> 00:11:30,440 Speaker 7: economists excited when you talk about productivity gains, and you 224 00:11:30,440 --> 00:11:33,440 Speaker 7: know they're Ultimately, human prosperity is driven by productivity, and 225 00:11:33,480 --> 00:11:36,160 Speaker 7: if we have new technology that drives that, that of 226 00:11:36,240 --> 00:11:38,840 Speaker 7: course raises uspective the next ten years we might see 227 00:11:39,000 --> 00:11:41,719 Speaker 7: niomous gains and economic growth driven. 228 00:11:41,440 --> 00:11:43,480 Speaker 5: By the application of AI. And there's other good stuff 229 00:11:43,480 --> 00:11:44,560 Speaker 5: happening in the world as well. 230 00:11:44,600 --> 00:11:47,439 Speaker 7: If you look at self driving cars, if you look 231 00:11:47,480 --> 00:11:51,200 Speaker 7: at buy technology, for example, We're not at a standstill. 232 00:11:51,240 --> 00:11:54,240 Speaker 7: This is not the end of global growth as we 233 00:11:54,320 --> 00:11:57,079 Speaker 7: know it, because we have these breakthroughs and technology. However, 234 00:11:57,679 --> 00:12:00,240 Speaker 7: it can be disruptive. One is being introduced, and I 235 00:12:00,240 --> 00:12:04,119 Speaker 7: think managing those social consequences, making sure that the technology 236 00:12:04,200 --> 00:12:07,160 Speaker 7: is safe is very important, and I think that's a 237 00:12:07,160 --> 00:12:09,760 Speaker 7: broader public interest. I think to make sure that we 238 00:12:09,880 --> 00:12:12,800 Speaker 7: developed these powerful technologies in the safest way possible. 239 00:12:12,920 --> 00:12:14,360 Speaker 1: I was looking at a story just now in the 240 00:12:14,400 --> 00:12:18,400 Speaker 1: Bloomberg terminal. A money manager at Fidelity International has sold 241 00:12:18,440 --> 00:12:21,960 Speaker 1: the vast maturity of his holdings in US treasuries from 242 00:12:22,000 --> 00:12:25,800 Speaker 1: the funds that he oversees because he believes that the 243 00:12:26,120 --> 00:12:28,360 Speaker 1: economy still has a lot of room to grow. I 244 00:12:28,360 --> 00:12:30,880 Speaker 1: think he's primarily thinking here of the US, But when 245 00:12:30,920 --> 00:12:33,360 Speaker 1: you think about where we're headed in the rates environment 246 00:12:33,440 --> 00:12:35,920 Speaker 1: right now. We had at least four FED officials today 247 00:12:36,040 --> 00:12:39,760 Speaker 1: urging patrons when you start to talk about rate cuts. 248 00:12:39,760 --> 00:12:42,400 Speaker 1: Where are you right now in terms of growth vis 249 00:12:42,400 --> 00:12:43,960 Speaker 1: a vis FED rate cuts? 250 00:12:45,240 --> 00:12:48,199 Speaker 7: Well, you know, we've said for quite some time it's 251 00:12:48,320 --> 00:12:50,280 Speaker 7: the FED may ease, but it may be a much 252 00:12:50,320 --> 00:12:53,439 Speaker 7: more shallow easing cycle than the market had expected even 253 00:12:53,480 --> 00:12:56,560 Speaker 7: a few weeks ago. And if you look at growth 254 00:12:56,600 --> 00:12:58,720 Speaker 7: in the US, it looks like it's going down perhaps 255 00:12:58,800 --> 00:13:03,800 Speaker 7: to trend. Still pretty strong growth overall. We were to 256 00:13:03,800 --> 00:13:05,679 Speaker 7: point out, for example, not only with a data over 257 00:13:05,760 --> 00:13:08,520 Speaker 7: not pretty strong initial claims down again for example, but 258 00:13:08,600 --> 00:13:12,600 Speaker 7: also US households are still sitting on very large wealth gains. 259 00:13:12,640 --> 00:13:15,160 Speaker 7: If you look at what's happening with Nvidia with a 260 00:13:15,200 --> 00:13:18,040 Speaker 7: stock market overall, that's a big tail when still for 261 00:13:18,200 --> 00:13:21,959 Speaker 7: US consumption, and so it's not entirely clear that really 262 00:13:22,000 --> 00:13:25,040 Speaker 7: heading to that heart landing and whether it's really the 263 00:13:25,240 --> 00:13:27,280 Speaker 7: all clear and inflation, I think we need to be 264 00:13:27,400 --> 00:13:30,520 Speaker 7: very careful in this. Fortunately, markets wound back its expectation. 265 00:13:30,559 --> 00:13:32,680 Speaker 7: We're now to June instead of March. I think that 266 00:13:32,800 --> 00:13:33,640 Speaker 7: sounds about right. 267 00:13:34,400 --> 00:13:36,160 Speaker 5: June, right, we are June as well? 268 00:13:36,240 --> 00:13:38,880 Speaker 7: Yeah, but look I mean some some, you know, when 269 00:13:38,880 --> 00:13:41,400 Speaker 7: we talk to clients, some people are now asking could 270 00:13:41,400 --> 00:13:45,040 Speaker 7: have had even high grades. Again, it's not entirely and conceivable, it's. 271 00:13:44,960 --> 00:13:45,720 Speaker 5: Not our base, Katy. 272 00:13:45,840 --> 00:13:48,040 Speaker 2: Slightly more likely is they just don't move this year. 273 00:13:48,320 --> 00:13:51,040 Speaker 2: What do you think of that probability. 274 00:13:50,440 --> 00:13:52,120 Speaker 5: That it could be as well? 275 00:13:52,160 --> 00:13:55,679 Speaker 7: I think the the right now the data flow suggests 276 00:13:55,800 --> 00:13:59,240 Speaker 7: less rather than more and so more we have one 277 00:13:59,280 --> 00:14:01,600 Speaker 7: more month of strong data, one more months of sticky 278 00:14:01,600 --> 00:14:05,960 Speaker 7: inflation coming in. Why would the Fed necessarily rush into 279 00:14:06,040 --> 00:14:08,200 Speaker 7: raycuts so far things are going well, then we have 280 00:14:08,200 --> 00:14:10,040 Speaker 7: the US election coming in as well, and they may 281 00:14:10,080 --> 00:14:12,320 Speaker 7: not want to move too closely before that as well. 282 00:14:12,520 --> 00:14:15,080 Speaker 1: Ten seconds, last question. The big gains that we were 283 00:14:15,080 --> 00:14:17,600 Speaker 1: seeing in the equity market suggest that there is still 284 00:14:17,640 --> 00:14:20,280 Speaker 1: too much liquidity in the system. 285 00:14:21,040 --> 00:14:24,480 Speaker 7: Well, there is still liquidity in the system, but the 286 00:14:24,600 --> 00:14:26,680 Speaker 7: body is in the eye of the beholder. Quit is 287 00:14:26,680 --> 00:14:28,960 Speaker 7: a state of mind. I don't know whether you know 288 00:14:29,040 --> 00:14:31,240 Speaker 7: that's that's one of my professors said, it's a state 289 00:14:31,280 --> 00:14:31,680 Speaker 7: of mind. 290 00:14:31,760 --> 00:14:33,720 Speaker 5: If if and then the state of mind is bullish 291 00:14:33,800 --> 00:14:35,480 Speaker 5: right now. So there you go. You got liquidity. 292 00:14:35,520 --> 00:14:36,640 Speaker 2: But can I sleep well tonight? 293 00:14:37,280 --> 00:14:40,000 Speaker 5: You can sleep well? Yes, it's Friday night, okay for the. 294 00:14:40,000 --> 00:14:42,920 Speaker 2: Moment, yeah, eight, the weekend approaches, Frederick, thank you very 295 00:14:43,000 --> 00:14:44,280 Speaker 2: much for being with us, Frederick. 296 00:14:44,080 --> 00:14:45,320 Speaker 1: Human HSPC. 297 00:14:45,680 --> 00:14:46,560 Speaker 5: This is one broke. 298 00:14:53,760 --> 00:14:53,880 Speaker 6: Well. 299 00:14:53,920 --> 00:14:56,280 Speaker 2: A huge trove of documents has turned up at the 300 00:14:56,320 --> 00:15:00,440 Speaker 2: Global Security side Gethub, owned by Microsoft. The documents appear 301 00:15:00,520 --> 00:15:04,720 Speaker 2: to outline China's state sponsored cyber attacks on foreign governments. 302 00:15:05,120 --> 00:15:07,720 Speaker 2: Joining us now to discuss this in detail is Sarah 303 00:15:07,800 --> 00:15:11,960 Speaker 2: Jung Bloomberg, China Technology Reporter. So there are so many 304 00:15:12,000 --> 00:15:15,120 Speaker 2: interesting angles to this, Sarah, one of which is that 305 00:15:15,560 --> 00:15:18,640 Speaker 2: this vendor i Soon from which a lot of these 306 00:15:18,640 --> 00:15:22,680 Speaker 2: files emanated, is just one of many, many different vendors 307 00:15:23,320 --> 00:15:26,600 Speaker 2: that take part in this selected program exactly. 308 00:15:26,680 --> 00:15:30,800 Speaker 6: I think that exact point is why the global cybersecurity 309 00:15:30,880 --> 00:15:33,440 Speaker 6: community has been so excited about this kind of leak, 310 00:15:33,760 --> 00:15:36,440 Speaker 6: because it's the first major leak from this type of 311 00:15:36,800 --> 00:15:39,000 Speaker 6: Chinese cyber vendor, and it gives us a little bit 312 00:15:39,000 --> 00:15:42,840 Speaker 6: of a glimpse into this broader ecosystem of vendors in 313 00:15:42,920 --> 00:15:46,640 Speaker 6: China that work with government clients and procure this kind 314 00:15:46,680 --> 00:15:50,440 Speaker 6: of data potentially from foreign government targets, and provides that 315 00:15:50,480 --> 00:15:51,480 Speaker 6: for the Chinese government. 316 00:15:51,720 --> 00:15:53,880 Speaker 1: So from what I'm reading in the Bloomberg piece the 317 00:15:53,920 --> 00:15:56,520 Speaker 1: origin of the files are unclear, but experts do believe 318 00:15:56,560 --> 00:16:00,160 Speaker 1: they are authentic. Have we or has there been any 319 00:16:00,240 --> 00:16:02,040 Speaker 1: reaction from Beijing at this point? 320 00:16:03,320 --> 00:16:07,320 Speaker 6: So far, there hasn't been. We've had reporters asking the 321 00:16:07,400 --> 00:16:10,200 Speaker 6: Chinese warn Ministry at their regular briefings, and they claim 322 00:16:10,240 --> 00:16:12,080 Speaker 6: that they're not aware of this, and they say that 323 00:16:12,160 --> 00:16:16,080 Speaker 6: they oppose all types of cyber attacks. In the past, 324 00:16:16,120 --> 00:16:19,440 Speaker 6: we've seen the Chinese government be increasingly vocal about how 325 00:16:19,520 --> 00:16:22,640 Speaker 6: they are actually a victim of Western hacking and deny 326 00:16:22,840 --> 00:16:27,440 Speaker 6: all state sponsored hacking. But we are looking to see 327 00:16:27,520 --> 00:16:31,400 Speaker 6: as this gains more attention and traction among the named 328 00:16:32,240 --> 00:16:34,480 Speaker 6: governments and companies in this league, whether or not the 329 00:16:34,560 --> 00:16:37,040 Speaker 6: Chinese government will will come out with more of an 330 00:16:37,040 --> 00:16:37,840 Speaker 6: official reaction. 331 00:16:38,320 --> 00:16:42,600 Speaker 2: One of the other interesting aspects is the widely diverse targets, 332 00:16:42,920 --> 00:16:45,760 Speaker 2: the different types of targets that are brought up in 333 00:16:45,760 --> 00:16:46,720 Speaker 2: some of these files. 334 00:16:47,000 --> 00:16:49,800 Speaker 6: Yeah, exactly, so, a bunch of colleagues, you know, we 335 00:16:49,880 --> 00:16:52,600 Speaker 6: were going through hundreds of files, almost six hundred files, 336 00:16:52,600 --> 00:16:55,280 Speaker 6: I think if I recall, and there are a bunch 337 00:16:55,320 --> 00:16:58,360 Speaker 6: of different targets named. It's very diverse. A lot of 338 00:16:58,440 --> 00:17:02,560 Speaker 6: high profile government targets, including even the NATO Secretary General. 339 00:17:03,360 --> 00:17:07,720 Speaker 6: We saw the UK FOURG ministry named the Royal Taie Army, 340 00:17:07,840 --> 00:17:11,320 Speaker 6: a bunch of different governments and including companies as well. 341 00:17:12,160 --> 00:17:14,639 Speaker 1: So I'm wondering when you get away from the relation 342 00:17:14,800 --> 00:17:18,399 Speaker 1: with Washington, DC and you're involving other entities like NATO 343 00:17:18,560 --> 00:17:21,320 Speaker 1: or even the Thai Army, I mean, they're really in 344 00:17:21,400 --> 00:17:26,320 Speaker 1: terms of damage control, there's a lot to push back against, definitely. 345 00:17:26,400 --> 00:17:29,000 Speaker 6: I mean, I think what is interesting is that no 346 00:17:29,040 --> 00:17:33,120 Speaker 6: one is particularly surprised that governments or state actors are 347 00:17:33,280 --> 00:17:35,880 Speaker 6: targeting other governments. I mean, I think that's something that's 348 00:17:36,359 --> 00:17:41,080 Speaker 6: generally understood, but in this case, we are seeing specific 349 00:17:41,160 --> 00:17:46,280 Speaker 6: details laid out about how these researchers are actually engaging 350 00:17:46,280 --> 00:17:48,879 Speaker 6: in the targeting, a little bit of information about how 351 00:17:48,960 --> 00:17:53,000 Speaker 6: much they're selling it for, and just laying out in 352 00:17:53,320 --> 00:17:56,160 Speaker 6: very clear terms that we are procuring this data and 353 00:17:56,200 --> 00:17:58,919 Speaker 6: providing it to the government, so something that we already 354 00:17:59,080 --> 00:18:01,720 Speaker 6: kind of would guess is happening and having it be 355 00:18:01,800 --> 00:18:02,600 Speaker 6: brought to the fore. 356 00:18:03,000 --> 00:18:05,040 Speaker 2: And what are some of the interesting comments that we're 357 00:18:05,040 --> 00:18:10,800 Speaker 2: hearing from cybersecurity experts who we've contacted to come in 358 00:18:10,840 --> 00:18:11,320 Speaker 2: on the story. 359 00:18:11,720 --> 00:18:12,360 Speaker 7: I think what's. 360 00:18:12,200 --> 00:18:14,439 Speaker 6: Interesting is that this is the first major leak of 361 00:18:14,440 --> 00:18:17,560 Speaker 6: this kind from a cyber vendor that does this kind 362 00:18:17,560 --> 00:18:20,720 Speaker 6: of attacking. So they are pointing out quite interesting things 363 00:18:20,760 --> 00:18:24,280 Speaker 6: about what this shows about the operations of this particular 364 00:18:24,359 --> 00:18:27,440 Speaker 6: vendor and maybe what it reveals about this broader market 365 00:18:28,119 --> 00:18:31,080 Speaker 6: just for this kind of data inside of China. And 366 00:18:31,119 --> 00:18:33,240 Speaker 6: there are also you know, a lot of speculation about 367 00:18:33,320 --> 00:18:36,000 Speaker 6: the origins of this, you know, what the person who 368 00:18:36,000 --> 00:18:39,560 Speaker 6: had leaked this data is intending to do, and then 369 00:18:39,600 --> 00:18:42,920 Speaker 6: potentially what this could mean for the Chinese government. Will 370 00:18:42,920 --> 00:18:45,359 Speaker 6: they have to answer for it, will other governments that 371 00:18:45,400 --> 00:18:47,760 Speaker 6: were named in this leak come out and pressure them 372 00:18:47,760 --> 00:18:48,120 Speaker 6: as well. 373 00:18:48,280 --> 00:18:52,239 Speaker 1: So you talked about visibility into pricing, how expensive or 374 00:18:52,280 --> 00:18:55,200 Speaker 1: how inexpensive is it for this type of behavior. 375 00:18:55,920 --> 00:18:58,800 Speaker 6: It's actually interesting because what experts are saying is that 376 00:18:58,840 --> 00:19:02,879 Speaker 6: it seems quite inexpensive, especially given the costs that governments 377 00:19:02,880 --> 00:19:06,879 Speaker 6: and companies, major companies would put into cybersecurity defenses. Some 378 00:19:06,960 --> 00:19:10,560 Speaker 6: of these massive databases of personal data were being hawked 379 00:19:10,560 --> 00:19:13,720 Speaker 6: online according to these documents for you know, just tens 380 00:19:13,720 --> 00:19:17,320 Speaker 6: of thousands of R and B, so a huge price differential. 381 00:19:16,920 --> 00:19:18,960 Speaker 2: There, So you referred to it as a leak. We 382 00:19:19,040 --> 00:19:21,800 Speaker 2: actually say in our headline purported leaks. And I said 383 00:19:21,840 --> 00:19:24,200 Speaker 2: earlier that you know, it was unclear that you know, 384 00:19:24,400 --> 00:19:27,000 Speaker 2: maybe this was uncovered by someone, but it seems like 385 00:19:27,040 --> 00:19:29,680 Speaker 2: it is a leak. And then it's really tricky getting 386 00:19:29,720 --> 00:19:31,600 Speaker 2: at the motivation, isn't it Definitely? 387 00:19:31,640 --> 00:19:34,320 Speaker 6: And I think that's a good caveat to mention. We 388 00:19:34,600 --> 00:19:37,280 Speaker 6: have gone through the documents, but we haven't personally been 389 00:19:37,320 --> 00:19:39,879 Speaker 6: able to verify all of the contents. But from what 390 00:19:39,960 --> 00:19:43,359 Speaker 6: cybersecurity experts are saying, they say that it aligns with 391 00:19:43,760 --> 00:19:48,000 Speaker 6: publicly reported information on these types of threat actors. And 392 00:19:48,760 --> 00:19:53,480 Speaker 6: we had Mandient, you know, a really big name in cybersecurity, 393 00:19:53,520 --> 00:19:55,320 Speaker 6: a unit of Google Cloud, coming out and saying that 394 00:19:55,400 --> 00:19:57,720 Speaker 6: they believe it to be authentic as well. 395 00:19:57,920 --> 00:20:00,720 Speaker 1: So the most surprising thing is seems to be how 396 00:20:00,760 --> 00:20:01,920 Speaker 1: inexpensive it is. 397 00:20:02,000 --> 00:20:06,040 Speaker 5: Not the fact that it's going on right, yes, that, and. 398 00:20:06,000 --> 00:20:07,919 Speaker 6: Then just the fact that you know, we're seeing it 399 00:20:08,000 --> 00:20:10,120 Speaker 6: spelled out in black and white, that they have these 400 00:20:10,160 --> 00:20:13,040 Speaker 6: specific targets and that we you know this this could 401 00:20:13,119 --> 00:20:15,080 Speaker 6: be sort of the tip of the iceberg for what 402 00:20:15,200 --> 00:20:18,119 Speaker 6: is actually going on in China and the broader you know, 403 00:20:18,200 --> 00:20:19,399 Speaker 6: cyber attack ecosystem. 404 00:20:19,680 --> 00:20:22,400 Speaker 2: Well, I suppose for you know, the Ministry of State Security, 405 00:20:22,800 --> 00:20:26,240 Speaker 2: you know, with with deep pockets, you know, two hundred 406 00:20:26,280 --> 00:20:28,439 Speaker 2: and seventy eight thousand dollars is not too much, But 407 00:20:28,560 --> 00:20:31,200 Speaker 2: that's one of the charges that we saw, at least 408 00:20:31,440 --> 00:20:34,400 Speaker 2: in one of the stories, Chinese customers getting a trove 409 00:20:34,480 --> 00:20:38,679 Speaker 2: of information behind social media accounts and platforms like Facebook 410 00:20:38,720 --> 00:20:41,960 Speaker 2: and Telegram for a quarter of a million dollars, which 411 00:20:42,320 --> 00:20:45,560 Speaker 2: seems expensive to us, but for governments maybe not so much. 412 00:20:45,760 --> 00:20:48,119 Speaker 5: Sarah, Thanks very much, Sarah Jane. This is Bloomberg. 413 00:20:49,840 --> 00:20:52,800 Speaker 1: This has been the Bloomberg Daybreak Asia podcast, bringing you 414 00:20:52,840 --> 00:20:55,960 Speaker 1: the stories making news and moving markets in the Asia Pacific. 415 00:20:56,480 --> 00:20:59,560 Speaker 1: Visit the Bloomberg Podcast channel on YouTube to get more 416 00:20:59,560 --> 00:21:03,240 Speaker 1: episodes of this and other shows from Bloomberg. Subscribe to 417 00:21:03,280 --> 00:21:07,040 Speaker 1: the podcast on Apple, Spotify, or anywhere else you listen 418 00:21:07,160 --> 00:21:10,240 Speaker 1: and always on Bloomberg Radio, the Bloomberg Terminal, and the 419 00:21:10,240 --> 00:21:11,359 Speaker 1: Bloomberg Business App.