1 00:00:02,520 --> 00:00:11,879 Speaker 1: Bloomberg Audio Studios, Podcasts, radio News. Welcome to the Bloomberg 2 00:00:11,920 --> 00:00:15,520 Speaker 1: Daybreak Asia podcast. I'm Doug Chrisner, and today it's all 3 00:00:15,560 --> 00:00:18,400 Speaker 1: about Nvidia. After the close in New York, the company 4 00:00:18,440 --> 00:00:21,440 Speaker 1: delivered a bullish forecast for revenue in the current quarter. 5 00:00:21,720 --> 00:00:25,680 Speaker 1: This seemed to reassure the market that spending on artificial 6 00:00:25,720 --> 00:00:30,240 Speaker 1: intelligence computing remains strong now. Heading into this report, analyst 7 00:00:30,360 --> 00:00:33,760 Speaker 1: questioned whether supply constraints as well as a shift to 8 00:00:33,800 --> 00:00:38,920 Speaker 1: the latest GPU design, Blackwell, with slow growth for Nvidia. Blackwell, 9 00:00:38,960 --> 00:00:42,400 Speaker 1: you see, is a more sophisticated GPU, It's had some 10 00:00:42,440 --> 00:00:46,640 Speaker 1: manufacturing challenges. And then on the earnings call, CEO Jensen 11 00:00:46,720 --> 00:00:49,400 Speaker 1: Wong gave an upbeat view on Blackwell. 12 00:00:49,600 --> 00:00:52,960 Speaker 2: Blackwell is going to be incredible across the board. And 13 00:00:53,000 --> 00:00:56,640 Speaker 2: when you have a data center that allows you to 14 00:00:56,680 --> 00:01:00,680 Speaker 2: configure and use your data center based on are you 15 00:01:00,840 --> 00:01:04,679 Speaker 2: doing more pre training now, post training now, or scaling 16 00:01:04,720 --> 00:01:09,360 Speaker 2: out your inference. Our architecture is pungible and easy to 17 00:01:09,520 --> 00:01:11,720 Speaker 2: use in all of those different ways. 18 00:01:11,840 --> 00:01:15,360 Speaker 1: Jensen Wong there the CEO of Nvidia. For a little 19 00:01:15,360 --> 00:01:18,200 Speaker 1: more on the Nvidia story, we turned to Angelo Zeno. 20 00:01:18,319 --> 00:01:23,240 Speaker 1: Angelo is the vice president of Equity Research at CFRA Angelo. 21 00:01:23,319 --> 00:01:25,320 Speaker 1: It's always a pleasure to have a chance to visit 22 00:01:25,360 --> 00:01:27,720 Speaker 1: with you on Nvidia earnings day. What did you make 23 00:01:27,800 --> 00:01:29,240 Speaker 1: of the latest results. 24 00:01:29,840 --> 00:01:33,240 Speaker 3: We were actually pretty optimistic about the results, So, you know, overall, 25 00:01:33,319 --> 00:01:35,920 Speaker 3: when we kind of think about the actual numbers that 26 00:01:35,959 --> 00:01:39,520 Speaker 3: were posted, numbers implied or we sort of top line 27 00:01:39,560 --> 00:01:43,520 Speaker 3: growth of about seventy eight percent, and that was slightly 28 00:01:43,600 --> 00:01:48,800 Speaker 3: better than expected. The implied kind of April quarter number 29 00:01:48,920 --> 00:01:51,920 Speaker 3: of revenue figure of forty three billion, which is kind 30 00:01:51,920 --> 00:01:54,840 Speaker 3: of what everybody was eyeing was that April quarter guidance 31 00:01:55,200 --> 00:01:58,120 Speaker 3: consensus was looking at forty two billions, so they got 32 00:01:58,120 --> 00:02:00,840 Speaker 3: it about a billion above the street again applies a 33 00:02:00,840 --> 00:02:03,919 Speaker 3: fairly kind of robust growth piece of north of sixty 34 00:02:03,960 --> 00:02:07,080 Speaker 3: percent on a year of a year basis, And you know, 35 00:02:07,200 --> 00:02:08,640 Speaker 3: at the end of the day, I think kind of 36 00:02:08,680 --> 00:02:11,720 Speaker 3: going into the numbers, there was some concern about the 37 00:02:11,760 --> 00:02:14,959 Speaker 3: Blackwell ramp out there, and when you kind of look 38 00:02:15,000 --> 00:02:17,520 Speaker 3: at maybe what the most important data point out there 39 00:02:17,720 --> 00:02:21,040 Speaker 3: was that in Vidia provided it was the eleven billion 40 00:02:21,200 --> 00:02:23,160 Speaker 3: in Blackwell revenue in. 41 00:02:23,040 --> 00:02:24,640 Speaker 4: The January quarter. 42 00:02:24,720 --> 00:02:27,120 Speaker 3: We were looking for something closer to seven to nine billion, 43 00:02:27,440 --> 00:02:30,040 Speaker 3: and that number is going to accelerate here over the 44 00:02:30,080 --> 00:02:34,359 Speaker 3: next couple of quarters, and that improved visibility. The lack 45 00:02:34,400 --> 00:02:37,320 Speaker 3: of the easing of some of the supply constraints out there, 46 00:02:37,440 --> 00:02:39,519 Speaker 3: I think east some of the concerns that may have 47 00:02:39,600 --> 00:02:42,320 Speaker 3: been out there for some in Vidia investors. 48 00:02:42,480 --> 00:02:44,440 Speaker 1: I think it's fair to say that one concern for 49 00:02:44,639 --> 00:02:47,920 Speaker 1: the current quarter may have been gross margin. In Vidia 50 00:02:48,200 --> 00:02:52,000 Speaker 1: is predicting non gap gross margin of around seventy one percent. 51 00:02:52,080 --> 00:02:54,920 Speaker 1: That seems pretty high, but it was less than forecast. 52 00:02:55,160 --> 00:02:57,560 Speaker 1: Are you concerned at all about that figure? 53 00:02:58,240 --> 00:03:01,040 Speaker 3: Yeah, I mean the gross margin number was probably the 54 00:03:01,040 --> 00:03:04,320 Speaker 3: one black eye as far as where we kind of 55 00:03:04,400 --> 00:03:06,920 Speaker 3: were looking at the guidance side of things. It was 56 00:03:07,160 --> 00:03:10,080 Speaker 3: definitely a disappointment. I think when you kind of especially 57 00:03:10,120 --> 00:03:12,760 Speaker 3: look at the trajectory of gross margins over the last 58 00:03:12,760 --> 00:03:14,880 Speaker 3: couple of quarters, it kind of hit a peak run 59 00:03:14,960 --> 00:03:17,440 Speaker 3: rate of about seventy eight percent in the first half 60 00:03:17,520 --> 00:03:21,760 Speaker 3: of calendar twenty twenty four. So the margins continue to 61 00:03:21,800 --> 00:03:25,040 Speaker 3: compress here going into the April quarter. The good news 62 00:03:25,120 --> 00:03:27,560 Speaker 3: is we do expect that to essentially be the trough 63 00:03:27,600 --> 00:03:30,600 Speaker 3: of the cycle here in the April quarter, and then 64 00:03:30,639 --> 00:03:33,120 Speaker 3: what we do expect is an improvement on the margin 65 00:03:33,160 --> 00:03:35,280 Speaker 3: side of things. The company a couple of months ago 66 00:03:35,560 --> 00:03:38,600 Speaker 3: did guide to the fact that as Blackwell ramps, you 67 00:03:38,680 --> 00:03:41,680 Speaker 3: are going to see margin pressures. That's what you're seeing now. 68 00:03:41,880 --> 00:03:45,480 Speaker 3: The company reiterated the fact that they expect mid seventies 69 00:03:45,600 --> 00:03:48,200 Speaker 3: margins as we kind of go into second half of 70 00:03:48,280 --> 00:03:50,720 Speaker 3: calendar twenty twenty five. And the fact that they did 71 00:03:50,760 --> 00:03:54,160 Speaker 3: reiterate that, I think kind of is allowing some investors 72 00:03:54,200 --> 00:03:56,440 Speaker 3: out there to at least look past some of the 73 00:03:56,920 --> 00:03:58,600 Speaker 3: disappointment on the margin side of things. 74 00:03:58,760 --> 00:04:03,520 Speaker 1: Nvidia stock is still below the pre Deep Seek level, 75 00:04:03,640 --> 00:04:06,440 Speaker 1: and I'm wondering whether or not this has changed the 76 00:04:06,480 --> 00:04:09,680 Speaker 1: deep Seek story I'm referring to, has changed anything on 77 00:04:09,720 --> 00:04:10,840 Speaker 1: the story with Nvidia. 78 00:04:11,520 --> 00:04:13,000 Speaker 4: Well, you know, I think that's a good question. 79 00:04:13,080 --> 00:04:15,840 Speaker 3: I think it's something that all investors kind of have 80 00:04:15,880 --> 00:04:18,680 Speaker 3: a close eye on and we're kind of debating as 81 00:04:18,680 --> 00:04:21,480 Speaker 3: we were kind of going into the print here and 82 00:04:21,839 --> 00:04:24,799 Speaker 3: as we expect it. Actually, Jensen was very bullish about 83 00:04:24,800 --> 00:04:27,960 Speaker 3: the demand landscape in a post deep Seek environment and 84 00:04:28,240 --> 00:04:30,640 Speaker 3: essentially kind of talked about the belief for a lot 85 00:04:30,640 --> 00:04:33,520 Speaker 3: of these kind of next generation reasoning models out there 86 00:04:33,839 --> 00:04:36,480 Speaker 3: to require a lot more compute out there, as much 87 00:04:36,480 --> 00:04:39,120 Speaker 3: as one hundred times the amount of compute that you're 88 00:04:39,160 --> 00:04:42,360 Speaker 3: seeing now from these kind of reasoning models. And essentially 89 00:04:42,440 --> 00:04:45,160 Speaker 3: kind of his belief is this is concept known as 90 00:04:45,200 --> 00:04:48,040 Speaker 3: model distillation out there, which is what Deep Seek is 91 00:04:48,160 --> 00:04:52,200 Speaker 3: essentially leveraging, and that's kind of basically taking a lot 92 00:04:52,240 --> 00:04:55,200 Speaker 3: of the learnings from some of these larger language models 93 00:04:55,240 --> 00:04:57,760 Speaker 3: out there and leveraging it in their own models. And 94 00:04:57,760 --> 00:05:00,520 Speaker 3: that requires again on in videos lot of things to 95 00:05:00,600 --> 00:05:03,480 Speaker 3: tell they've said it requires a lot more compute than 96 00:05:03,560 --> 00:05:07,160 Speaker 3: just pre training alone. So they again talked up kind 97 00:05:07,200 --> 00:05:10,479 Speaker 3: of a very positive story post Deep Seek. It remains 98 00:05:10,480 --> 00:05:12,760 Speaker 3: to be seen exactly how this all plays out. I 99 00:05:12,760 --> 00:05:15,159 Speaker 3: will say this as far as these large language models 100 00:05:15,200 --> 00:05:17,800 Speaker 3: are concerned, who essentially have this kind of race to 101 00:05:17,839 --> 00:05:20,440 Speaker 3: the bottom at this point in times in terms of 102 00:05:21,400 --> 00:05:24,080 Speaker 3: you know, pricing a lot of China new competitors out there, 103 00:05:24,160 --> 00:05:27,920 Speaker 3: China competitors coming out there, and that's going to kind 104 00:05:27,960 --> 00:05:31,480 Speaker 3: of commoditize the larger language model side of things. So 105 00:05:31,520 --> 00:05:33,159 Speaker 3: that is going to have an impact in terms of 106 00:05:33,240 --> 00:05:36,840 Speaker 3: AI monetization as far as large language models are concerned. 107 00:05:36,960 --> 00:05:38,880 Speaker 3: And as a result of that, we think it's going 108 00:05:38,920 --> 00:05:41,760 Speaker 3: to be more relevant for investors to start looking at 109 00:05:41,880 --> 00:05:45,400 Speaker 3: the monetization from these AI agents out there, and eventually 110 00:05:45,480 --> 00:05:48,120 Speaker 3: as you move to a physical AI world. So I 111 00:05:48,120 --> 00:05:50,520 Speaker 3: think this is an evolving landscape out there. I think 112 00:05:50,560 --> 00:05:54,400 Speaker 3: stay tuned, But as far as Jensen is concerned, post 113 00:05:54,480 --> 00:05:57,279 Speaker 3: deep seek looks better at least long term for the 114 00:05:57,320 --> 00:05:59,680 Speaker 3: compute the evolution of compute. 115 00:05:59,720 --> 00:06:02,560 Speaker 1: And there's the geopolitics. I think we have to talk 116 00:06:02,600 --> 00:06:05,400 Speaker 1: a little bit about what the Trump administration is intending 117 00:06:05,440 --> 00:06:08,520 Speaker 1: to do. Recently we learned that the administration is sketching 118 00:06:08,520 --> 00:06:12,320 Speaker 1: out tougher versions of US semiconductor curbs for China. Do 119 00:06:12,360 --> 00:06:17,040 Speaker 1: you think that that necessarily will negatively impact nvidio and 120 00:06:17,120 --> 00:06:19,120 Speaker 1: that narrative in a significant way. 121 00:06:20,360 --> 00:06:23,200 Speaker 3: If the Trump administration goes ahead and actually kind of 122 00:06:23,520 --> 00:06:27,279 Speaker 3: implements let's call its more harsh stance on some of 123 00:06:27,279 --> 00:06:31,160 Speaker 3: these kind of export restrictions, especially tied to GPUs, and 124 00:06:31,200 --> 00:06:33,000 Speaker 3: I think kind of the fear out there is a 125 00:06:33,000 --> 00:06:36,920 Speaker 3: potential all out beIN of these GPUs and that would 126 00:06:36,920 --> 00:06:39,640 Speaker 3: include I guess their most popular seller, which would be 127 00:06:39,680 --> 00:06:41,440 Speaker 3: the Age twenty out in China. 128 00:06:41,520 --> 00:06:44,160 Speaker 4: And if that were to happen, I mean that potentially. 129 00:06:44,160 --> 00:06:46,840 Speaker 3: Puts at risk as much as as much as ten 130 00:06:46,960 --> 00:06:51,520 Speaker 3: to fifteen percent of their revenue, which is tied in 131 00:06:51,600 --> 00:06:53,799 Speaker 3: China at least tied to kind of the data center 132 00:06:53,880 --> 00:06:56,760 Speaker 3: side of things. So yeah, I mean, I think when 133 00:06:56,760 --> 00:07:00,480 Speaker 3: you kind of think about the negative tilt or kind 134 00:07:00,520 --> 00:07:03,240 Speaker 3: of the barecase burned video right now, the biggest near 135 00:07:03,400 --> 00:07:06,440 Speaker 3: term risk out there has to be the geopolitical landscape. 136 00:07:06,480 --> 00:07:08,599 Speaker 3: So hopefully we get some kind of clarity on that 137 00:07:08,680 --> 00:07:11,000 Speaker 3: here over the next couple of months, and hopefully the 138 00:07:11,240 --> 00:07:15,080 Speaker 3: administration doesn't take that harsher stance out there. To be 139 00:07:15,080 --> 00:07:18,200 Speaker 3: honest with you, if you know, if the administration was 140 00:07:18,240 --> 00:07:21,240 Speaker 3: really kind of looking to take a harsh stance on 141 00:07:21,560 --> 00:07:24,600 Speaker 3: China as far as Chips is concerned, we would we 142 00:07:24,640 --> 00:07:26,880 Speaker 3: would say, hey, listen, do an all out ban on 143 00:07:26,920 --> 00:07:28,960 Speaker 3: the semi equip side of things, which would kind of 144 00:07:28,960 --> 00:07:32,640 Speaker 3: be more of kind of a table pounder out there 145 00:07:32,680 --> 00:07:33,120 Speaker 3: than kind. 146 00:07:33,040 --> 00:07:34,560 Speaker 4: Of banning some of these GPUs. 147 00:07:34,600 --> 00:07:37,440 Speaker 3: But it is very possible that we kind of get 148 00:07:37,480 --> 00:07:39,880 Speaker 3: an all out ban on these GPUs, and that would 149 00:07:39,920 --> 00:07:42,400 Speaker 3: be the risk out there for investors of Nvidia. 150 00:07:42,800 --> 00:07:46,280 Speaker 1: These are early days for the adoption of artificial intelligence, 151 00:07:46,320 --> 00:07:48,240 Speaker 1: but can you give me a sense and maybe it's 152 00:07:48,280 --> 00:07:51,200 Speaker 1: too soon to call it a super cycle. Where are 153 00:07:51,240 --> 00:07:54,800 Speaker 1: we right now in terms of the cycle for AI, 154 00:07:55,240 --> 00:07:58,000 Speaker 1: and give me your assessment on how valuations kind of 155 00:07:58,040 --> 00:07:59,320 Speaker 1: factor into that at the moment. 156 00:07:59,720 --> 00:08:01,560 Speaker 4: Yeah, I mean, I think you're right. 157 00:08:01,600 --> 00:08:04,320 Speaker 3: I think this is early days and there's going to 158 00:08:04,360 --> 00:08:05,800 Speaker 3: be a lot of volatility. 159 00:08:05,840 --> 00:08:07,960 Speaker 4: I think, you know, there were hopeful, you know, there was. 160 00:08:07,960 --> 00:08:10,240 Speaker 3: Some help out there from some investors that this is 161 00:08:10,240 --> 00:08:11,800 Speaker 3: going to be kind of up into the right and 162 00:08:11,840 --> 00:08:14,720 Speaker 3: that's not going to be how this all plays out, 163 00:08:14,800 --> 00:08:17,280 Speaker 3: right in terms of the CAPEX spend, in terms of 164 00:08:17,360 --> 00:08:20,240 Speaker 3: the AI monetization of all of this, in terms of 165 00:08:20,280 --> 00:08:23,040 Speaker 3: the cap X cycle is concerned, as far as in 166 00:08:23,080 --> 00:08:26,320 Speaker 3: nvidios GPUs are concerned. We're entering kind of year three 167 00:08:26,800 --> 00:08:28,920 Speaker 3: of this upcycle that really kind of started with the 168 00:08:29,240 --> 00:08:33,200 Speaker 3: Open AI Microsoft partnership in early calendar twenty twenty three. 169 00:08:33,360 --> 00:08:36,199 Speaker 3: So you know, comparisons are obviously going to get a 170 00:08:36,240 --> 00:08:39,199 Speaker 3: lot more difficult as the years go by. The question is, 171 00:08:39,320 --> 00:08:41,280 Speaker 3: you know, how far is the current kind of CAPEX 172 00:08:41,360 --> 00:08:44,320 Speaker 3: cycle going to go. Potentially could go five six years. 173 00:08:44,600 --> 00:08:48,000 Speaker 3: Historically kind of capex cycles on the data center side 174 00:08:48,000 --> 00:08:50,200 Speaker 3: of things last longer than I would say on the 175 00:08:50,200 --> 00:08:52,560 Speaker 3: consumer side of things when we're talking about you know, 176 00:08:52,960 --> 00:08:56,520 Speaker 3: kind of you know, cycles tied to PCs or smartphones 177 00:08:56,600 --> 00:08:57,360 Speaker 3: or something like that. 178 00:08:57,600 --> 00:08:58,280 Speaker 4: But it's important. 179 00:08:58,320 --> 00:09:00,400 Speaker 3: It's impossible to really kind of tell how this all 180 00:09:00,440 --> 00:09:02,839 Speaker 3: plays out. Macro obviously has a big role in all 181 00:09:02,880 --> 00:09:06,200 Speaker 3: of this as well, but the AI monetization is really 182 00:09:06,280 --> 00:09:08,640 Speaker 3: kind of where all eyes should be for investors at 183 00:09:08,640 --> 00:09:12,280 Speaker 3: this point in times. It's take a look at Microsoft, 184 00:09:12,320 --> 00:09:15,280 Speaker 3: take a look at what a company like Salesforce is 185 00:09:15,320 --> 00:09:17,680 Speaker 3: going to do, what they have to say over the 186 00:09:17,720 --> 00:09:20,319 Speaker 3: next couple of quarters in years as far as AI 187 00:09:20,440 --> 00:09:25,439 Speaker 3: monetization is, tie is concerned, tied to AI agents out there. 188 00:09:25,640 --> 00:09:26,679 Speaker 4: If we see kind. 189 00:09:26,480 --> 00:09:29,240 Speaker 3: Of a strong ramp here going into the second half 190 00:09:29,240 --> 00:09:32,320 Speaker 3: of calendar twenty five into twenty six, that bodes well 191 00:09:32,360 --> 00:09:36,080 Speaker 3: in terms of kind of the sentiment and enthusiasm in 192 00:09:36,160 --> 00:09:38,280 Speaker 3: terms of some of the spend net we're seeing. If 193 00:09:38,320 --> 00:09:40,800 Speaker 3: you don't see that AI monetization really kind of ramp 194 00:09:40,880 --> 00:09:42,880 Speaker 3: up the way you know some out there are hoping for, 195 00:09:43,720 --> 00:09:46,640 Speaker 3: there's a very good possibility that some of these these 196 00:09:46,720 --> 00:09:49,720 Speaker 3: hyperscalers maybe kind of level off some of the spend 197 00:09:49,840 --> 00:09:52,080 Speaker 3: as we go into twenty twenty six, as far as 198 00:09:52,160 --> 00:09:56,280 Speaker 3: valuations are concerned across the AI ecosystem, they've definitely kind 199 00:09:56,280 --> 00:09:58,600 Speaker 3: of compressed here over the last kind of nine to 200 00:09:58,640 --> 00:10:01,840 Speaker 3: twelve months. Is kind of tech has kind of really 201 00:10:01,880 --> 00:10:05,120 Speaker 3: been in this kind of you know, flat line situation 202 00:10:05,320 --> 00:10:07,320 Speaker 3: since the summer of last year. In fact, if you 203 00:10:07,400 --> 00:10:10,400 Speaker 3: kind of look at a Nvidia's valuation trading about twenty 204 00:10:10,400 --> 00:10:13,480 Speaker 3: five times on our calendar twenty six estimate, it's come 205 00:10:13,559 --> 00:10:16,439 Speaker 3: down significantly over the last couple of quarters. You can 206 00:10:16,480 --> 00:10:20,439 Speaker 3: also see that, you know, across other type of mag 207 00:10:20,559 --> 00:10:22,800 Speaker 3: seven type names out there, whether it be a name 208 00:10:22,920 --> 00:10:26,960 Speaker 3: like Microsoft trading about twenty six times our calendar twenty 209 00:10:27,000 --> 00:10:30,280 Speaker 3: six estimate and others out there, they're actually trading at 210 00:10:30,280 --> 00:10:33,240 Speaker 3: discounts to historical levels. So it kind of tells you 211 00:10:33,280 --> 00:10:35,640 Speaker 3: that there are investors out there that are kind of 212 00:10:36,400 --> 00:10:39,319 Speaker 3: getting a little bit skittish about kind of this AI 213 00:10:39,440 --> 00:10:40,160 Speaker 3: trade at the moment. 214 00:10:40,320 --> 00:10:43,520 Speaker 1: Yeah, Angelo, thank you so much for the analysis. Great stuff. 215 00:10:43,559 --> 00:10:46,840 Speaker 1: Angelo Zeno there, he is vice president of Equity Research 216 00:10:47,120 --> 00:10:50,600 Speaker 1: at CFR. Joining us here on the Daybreak Asia podcast. 217 00:10:58,920 --> 00:11:02,080 Speaker 1: Welcome back to the Daybreak Asia Podcast. I'm Doug Chrisner. 218 00:11:02,400 --> 00:11:04,920 Speaker 1: So we were talking about in Nvidia a moment ago. 219 00:11:05,160 --> 00:11:07,280 Speaker 1: You know, this stock has been down this year on 220 00:11:07,480 --> 00:11:10,640 Speaker 1: concern about the slow down and spending potentially from data 221 00:11:10,679 --> 00:11:13,959 Speaker 1: center operators. Also, we have to bring into the story 222 00:11:14,160 --> 00:11:17,720 Speaker 1: the breakthrough from that Chinese startup, Deep Seek. The company's 223 00:11:17,800 --> 00:11:21,520 Speaker 1: chatbot show that llm's can be developed on the cheap 224 00:11:22,040 --> 00:11:25,920 Speaker 1: and that could reduce the need for Nvidia's powerful AI chips. 225 00:11:26,120 --> 00:11:28,840 Speaker 1: But for the moment, let's turn our attention to Chinese 226 00:11:28,840 --> 00:11:31,640 Speaker 1: tech stocks. They've been on a tear lately. Joining us 227 00:11:31,640 --> 00:11:35,400 Speaker 1: now is Shuly Rent, Bloomberg opinion columnist truly joins from 228 00:11:35,400 --> 00:11:38,440 Speaker 1: our studios in Hong Kong. Suly, it's always a pleasure. 229 00:11:38,520 --> 00:11:41,760 Speaker 1: Thank you so much. How would you describe what's been 230 00:11:41,800 --> 00:11:43,920 Speaker 1: happening with Chinese tech right now? 231 00:11:44,600 --> 00:11:49,120 Speaker 5: Well, Deep Seek really has changed the perception of Chinese investors. 232 00:11:49,320 --> 00:11:51,800 Speaker 5: They do feel, I mean going back, like we know 233 00:11:51,960 --> 00:11:55,160 Speaker 5: that the Hong Kong list issues mostly Chinese companies, right 234 00:11:55,320 --> 00:12:00,280 Speaker 5: they are deep value traps after the Beijing's regular to 235 00:12:00,600 --> 00:12:04,760 Speaker 5: crack down some big tech and the whole property bubble bust, 236 00:12:05,160 --> 00:12:07,960 Speaker 5: Like the Chinese shares are very cheap, but Deep Sea 237 00:12:08,000 --> 00:12:10,880 Speaker 5: basically said that, you know, China is not just a 238 00:12:10,920 --> 00:12:15,040 Speaker 5: manufacturing powerhouse. It's also good with the software and digital stuff, 239 00:12:15,160 --> 00:12:20,000 Speaker 5: right like Deep Sea does a generative AI. And the 240 00:12:20,040 --> 00:12:25,280 Speaker 5: people didn't really expect that China, a small unknown startup 241 00:12:25,800 --> 00:12:28,800 Speaker 5: even to the Chinese until a month ago, could do 242 00:12:28,920 --> 00:12:32,360 Speaker 5: so well despite all the export controls, and that really 243 00:12:32,360 --> 00:12:34,800 Speaker 5: fired up. And then what we are seeing is that 244 00:12:35,000 --> 00:12:37,920 Speaker 5: you know, the tex doogs, the software companies, they're doing very, 245 00:12:38,000 --> 00:12:40,600 Speaker 5: very well, and there is a sense that the China 246 00:12:40,640 --> 00:12:41,920 Speaker 5: can be a growth market. Again. 247 00:12:42,160 --> 00:12:45,240 Speaker 1: In the latest column that you authored for Bloomberg Opinion, 248 00:12:45,280 --> 00:12:49,559 Speaker 1: you write that a Chinese alternative to the Magnificent Seven arrives. 249 00:12:49,559 --> 00:12:52,040 Speaker 1: And I'm wondering whether you're really focused on a lot 250 00:12:52,040 --> 00:12:54,760 Speaker 1: of these e commerce names that we hear so much about, 251 00:12:54,800 --> 00:12:56,360 Speaker 1: like Ali Baba ten Cent. 252 00:12:57,240 --> 00:13:00,880 Speaker 5: Yes. One thing though, is like a lot of it 253 00:13:00,920 --> 00:13:05,319 Speaker 5: is about the positioning, like global asset managers positioning. Coming 254 00:13:05,320 --> 00:13:09,640 Speaker 5: into this year, everyone is overweight on basically the big 255 00:13:09,679 --> 00:13:12,480 Speaker 5: seven tax stocks, right, the so called the notion of 256 00:13:12,520 --> 00:13:17,040 Speaker 5: a US exceptionalism. And everyone agrees that the US store 257 00:13:17,040 --> 00:13:20,680 Speaker 5: market is overvalued because just simply because so much money 258 00:13:20,720 --> 00:13:23,960 Speaker 5: has been coming in and there is this genuine need 259 00:13:24,040 --> 00:13:26,960 Speaker 5: to diversify, and now the question is where do you 260 00:13:27,000 --> 00:13:30,880 Speaker 5: diversify to. Right Like China, tex stock is one story. 261 00:13:31,080 --> 00:13:34,480 Speaker 5: Another story is European stocks. They have been doing quite 262 00:13:34,480 --> 00:13:38,680 Speaker 5: well as well, and there is expectation that the Donald Trump, 263 00:13:38,840 --> 00:13:42,560 Speaker 5: however you like it politically or not, could propel peace 264 00:13:42,840 --> 00:13:46,000 Speaker 5: over Ukraine, which means that it could be good for 265 00:13:46,160 --> 00:13:48,280 Speaker 5: European economies, especially Germany. 266 00:13:48,640 --> 00:13:51,680 Speaker 1: You know, Beijin seems to have kind of changed its 267 00:13:51,720 --> 00:13:54,280 Speaker 1: attitude where some of the big tech stories in China 268 00:13:54,280 --> 00:13:56,680 Speaker 1: are concerned. I'm thinking back to the meeting a few 269 00:13:56,720 --> 00:13:59,320 Speaker 1: weeks ago that Chi Jinping had with some of the 270 00:13:59,360 --> 00:14:01,680 Speaker 1: leaders of these big companies that I'm thinking of Jack 271 00:14:01,800 --> 00:14:06,320 Speaker 1: Ma in particular, as Shi Jinping changed his attitude when 272 00:14:06,320 --> 00:14:07,320 Speaker 1: it comes to big tech. 273 00:14:08,320 --> 00:14:12,560 Speaker 5: He has to because, believe it or not, just because 274 00:14:12,880 --> 00:14:16,360 Speaker 5: China's economic out look it's not so good. Right like 275 00:14:17,160 --> 00:14:21,640 Speaker 5: the big tech, the big e commerce platforms political fortunes 276 00:14:21,680 --> 00:14:25,600 Speaker 5: actually are improving because they actually soak up a lot 277 00:14:25,640 --> 00:14:30,040 Speaker 5: of employment. Right like young people. The unemployment rate for 278 00:14:30,160 --> 00:14:33,200 Speaker 5: young people in China is very high, and if young 279 00:14:33,240 --> 00:14:37,160 Speaker 5: people have no jobs, they could become delivery workers unfortunately, 280 00:14:37,520 --> 00:14:40,320 Speaker 5: or like they could be uber drivers in China that 281 00:14:40,360 --> 00:14:42,760 Speaker 5: would be d D. Or they could set up a 282 00:14:42,840 --> 00:14:48,520 Speaker 5: small e commercer shops selling stuff, or they could be influencers. 283 00:14:48,800 --> 00:14:53,440 Speaker 5: And I think Beijing does recognize that these big platforms 284 00:14:53,640 --> 00:14:56,120 Speaker 5: they are job creators and they need to be nice 285 00:14:56,160 --> 00:14:56,480 Speaker 5: to them. 286 00:14:56,680 --> 00:14:59,800 Speaker 1: When you look at valuation, you're a financial analyst by training. 287 00:15:00,120 --> 00:15:02,080 Speaker 1: You see when you look at some of these companies, 288 00:15:02,640 --> 00:15:04,240 Speaker 1: Chinese firms that trade in Hong. 289 00:15:04,200 --> 00:15:08,880 Speaker 5: Kong, everything is relative. I mean Tesla trades at the 290 00:15:09,160 --> 00:15:12,520 Speaker 5: over one hundred times forward earnings shell me and the 291 00:15:12,560 --> 00:15:16,200 Speaker 5: bid they both do evs, they trade at the roughly 292 00:15:16,800 --> 00:15:21,120 Speaker 5: forty to forty and twenty five times, and relatively speaking, 293 00:15:21,240 --> 00:15:25,320 Speaker 5: everyone everyone else is cheap compared to Tesla, right, And 294 00:15:25,440 --> 00:15:28,720 Speaker 5: it's not just that a lot of Chinese feel that 295 00:15:28,800 --> 00:15:32,040 Speaker 5: the Ela musk has been very distracted lately and then 296 00:15:32,160 --> 00:15:35,400 Speaker 5: that he's not paying attention to Tesla's business, and that 297 00:15:35,680 --> 00:15:39,000 Speaker 5: opens a window for Chinese EV makers. And in fact, 298 00:15:39,200 --> 00:15:41,800 Speaker 5: like a lot of EV makers, they are adding like 299 00:15:42,040 --> 00:15:46,640 Speaker 5: a lot of like advanced technology, for instance, auto driving, 300 00:15:47,200 --> 00:15:51,280 Speaker 5: greeting the drivers with their favorite songs, et cetera for free, 301 00:15:51,480 --> 00:15:55,400 Speaker 5: Like basically you are getting the same heart with technolological 302 00:15:55,440 --> 00:15:58,840 Speaker 5: add ons, but you're not paying anymore. And they do 303 00:15:58,880 --> 00:16:02,240 Speaker 5: feel that the Shelby and b White have a lot 304 00:16:02,320 --> 00:16:06,120 Speaker 5: of space in Europe or even in the US. 305 00:16:06,480 --> 00:16:08,480 Speaker 1: So I talked a moment ago about the rally that 306 00:16:08,520 --> 00:16:10,640 Speaker 1: we have seen recently and a lot of these text 307 00:16:10,640 --> 00:16:13,120 Speaker 1: shares in Hong Kong. Do you know whether or not 308 00:16:13,200 --> 00:16:16,240 Speaker 1: most of this buying is on the part of institutions 309 00:16:16,360 --> 00:16:19,400 Speaker 1: or is it the retail crowd that is really stepping 310 00:16:19,480 --> 00:16:21,119 Speaker 1: up and taking smaller positions. 311 00:16:21,600 --> 00:16:24,600 Speaker 5: I think it's both, but the most of it is 312 00:16:24,640 --> 00:16:29,200 Speaker 5: still Chinese money. You can actually see. So basically mainland 313 00:16:29,280 --> 00:16:32,360 Speaker 5: China and Hong Kong has a stock connect. Mainland investors 314 00:16:32,400 --> 00:16:35,400 Speaker 5: can through the stock connect by Hong Kong list issues, 315 00:16:35,560 --> 00:16:38,120 Speaker 5: and you do see that, you know, whenever the Hong 316 00:16:38,200 --> 00:16:42,480 Speaker 5: Kong stock market is wobbling, like you actually see the 317 00:16:42,520 --> 00:16:45,320 Speaker 5: self bound money coming into Hong Kong. So I do 318 00:16:45,360 --> 00:16:49,120 Speaker 5: think like there is retail money, there is institution money, 319 00:16:49,120 --> 00:16:51,520 Speaker 5: but most of it is still Chinese money. I mean, 320 00:16:51,560 --> 00:16:56,760 Speaker 5: after all, like China has been a big career risk 321 00:16:56,960 --> 00:16:59,960 Speaker 5: for a lot of the global asset managers. They're interest 322 00:17:00,560 --> 00:17:03,200 Speaker 5: but they are still sitting on the sidelines. Although you know, 323 00:17:03,280 --> 00:17:05,840 Speaker 5: if you see like macro funds or hatch funds, they 324 00:17:05,840 --> 00:17:07,840 Speaker 5: are in and out, they do trade. 325 00:17:08,240 --> 00:17:11,159 Speaker 1: So how would you evaluate the conviction? Is there a 326 00:17:11,200 --> 00:17:14,840 Speaker 1: feeling here that this is something more than a one off, 327 00:17:14,880 --> 00:17:17,800 Speaker 1: that there is really something more durable underneath the surface. 328 00:17:18,600 --> 00:17:20,760 Speaker 5: The last week or so, I have checked with a 329 00:17:20,760 --> 00:17:23,959 Speaker 5: lot of asset managers. They feel quite boolish, and I 330 00:17:24,000 --> 00:17:27,520 Speaker 5: do think deep Seak is changing the game, right, Like 331 00:17:27,760 --> 00:17:30,120 Speaker 5: going back to the whole thing. People have a lot 332 00:17:30,119 --> 00:17:34,359 Speaker 5: of confidence in China's manufacturing power, but they don't really 333 00:17:34,400 --> 00:17:37,359 Speaker 5: have that much confidence in China's software power. And the 334 00:17:37,400 --> 00:17:40,520 Speaker 5: deep sea shows otherwise. And that's why, Like if you 335 00:17:40,560 --> 00:17:44,159 Speaker 5: see the Hong Kong listed tech stocks, they wobble a 336 00:17:44,200 --> 00:17:46,679 Speaker 5: little bit when the news flow comes that the trumpet 337 00:17:46,760 --> 00:17:49,879 Speaker 5: is going to increase export chip controls out of China, 338 00:17:50,080 --> 00:17:52,760 Speaker 5: But very quickly you should see people buy on the 339 00:17:52,800 --> 00:17:55,760 Speaker 5: dip because they just think export controls are not working. 340 00:17:56,480 --> 00:17:58,560 Speaker 1: Truly, thank you so much for joining us. It's always 341 00:17:58,560 --> 00:18:02,320 Speaker 1: a pleasure, truly. Ranch He is Bloomberg opinion columnist joining 342 00:18:02,359 --> 00:18:07,080 Speaker 1: us here on the Daybreak Asia podcast. Thanks for listening 343 00:18:07,119 --> 00:18:11,320 Speaker 1: to today's episode of the Bloomberg Daybreak Asia edition podcast. 344 00:18:11,640 --> 00:18:14,800 Speaker 1: Each weekday, we look at the story shaping markets, finance, 345 00:18:15,119 --> 00:18:18,239 Speaker 1: and geopolitics in the Asia Pacific. You can find us 346 00:18:18,240 --> 00:18:22,480 Speaker 1: on Apple, Spotify, the Bloomberg Podcast YouTube channel, or anywhere 347 00:18:22,480 --> 00:18:25,560 Speaker 1: else you listen. Join us again tomorrow for insight on 348 00:18:25,600 --> 00:18:29,760 Speaker 1: the market moves from Hong Kong to Singapore and Australia. 349 00:18:30,200 --> 00:18:32,679 Speaker 1: I'm Doug Chrisner, and this is Bloomberg