1 00:00:02,520 --> 00:00:11,480 Speaker 1: Bloomberg Audio Studios, Podcasts, radio News. Welcome to the Bloomberg 2 00:00:11,520 --> 00:00:15,120 Speaker 1: Daybreak Asia Podcast. I'm Doug Krisner. So Wall Street is 3 00:00:15,160 --> 00:00:18,840 Speaker 1: gearing up for earnings from some megacap companies. Tomorrow. After 4 00:00:18,880 --> 00:00:21,800 Speaker 1: the bell, we'll have results from Alphabet and Tesla, and 5 00:00:21,840 --> 00:00:24,119 Speaker 1: in a moment we'll get the tech story from the 6 00:00:24,160 --> 00:00:27,560 Speaker 1: Asian perspective. I'll be joined by Stephanie Lyung. She is 7 00:00:27,600 --> 00:00:31,120 Speaker 1: the chief investment officer at Stashaway. But we begin this 8 00:00:31,280 --> 00:00:34,559 Speaker 1: morning with breaking news on trade, President Trump saying the 9 00:00:34,680 --> 00:00:38,160 Speaker 1: US has completed a deal with Japan. In a post 10 00:00:38,200 --> 00:00:40,640 Speaker 1: on truth social Trump said that taro freight would be 11 00:00:40,720 --> 00:00:43,519 Speaker 1: set at fifteen percent. Here is Trump. 12 00:00:44,000 --> 00:00:46,120 Speaker 2: We worked on it long and hard, and it's a 13 00:00:46,159 --> 00:00:48,479 Speaker 2: great deal for everybody. I always say it has to 14 00:00:48,520 --> 00:00:51,360 Speaker 2: be great for everybody. It's a great deal. A lot 15 00:00:51,440 --> 00:00:53,760 Speaker 2: different from the deals in the past. I can tell 16 00:00:53,800 --> 00:00:54,040 Speaker 2: you that. 17 00:00:54,520 --> 00:00:57,280 Speaker 1: Trump also said Japan will be opening its markets to 18 00:00:57,480 --> 00:01:01,880 Speaker 1: US products, including cars and trucks, rice, and certain other 19 00:01:02,000 --> 00:01:05,679 Speaker 1: US agricultural products. And at the same time, Japan will 20 00:01:05,720 --> 00:01:08,520 Speaker 1: be investing five hundred and fifty billion dollars into the 21 00:01:08,600 --> 00:01:11,640 Speaker 1: United States. Earlier, Trump announced a new trade deal with 22 00:01:11,680 --> 00:01:15,000 Speaker 1: the Philippines a tariff right in that case of nineteen percent, 23 00:01:15,480 --> 00:01:19,800 Speaker 1: and earlier Trump touted a major deal with Indonesia estimating 24 00:01:19,880 --> 00:01:24,039 Speaker 1: fifty billion dollars in added US market access. Joining me 25 00:01:24,080 --> 00:01:27,680 Speaker 1: now is David Aspell, partner and co CIO at Mount 26 00:01:27,760 --> 00:01:32,080 Speaker 1: Lucas Management. David joining from just north of Philadelphia. Thank 27 00:01:32,120 --> 00:01:34,080 Speaker 1: you so much for making time to chat with me. David, 28 00:01:34,160 --> 00:01:37,520 Speaker 1: to what extent now do you believe the market will 29 00:01:37,560 --> 00:01:40,600 Speaker 1: be confident that we're closing in on the end of 30 00:01:40,640 --> 00:01:41,360 Speaker 1: this trade war? 31 00:01:43,280 --> 00:01:46,120 Speaker 3: Yeah, I think it is starting to express confidence. You're 32 00:01:46,120 --> 00:01:48,720 Speaker 3: starting to see some trade deals come through. I think 33 00:01:48,840 --> 00:01:51,640 Speaker 3: you're starting to see some more clarity around what the 34 00:01:51,680 --> 00:01:54,720 Speaker 3: world post Liberation Day is going to look like. It 35 00:01:54,720 --> 00:01:58,560 Speaker 3: looked as if Liberation Day was, you know, maybe some 36 00:01:58,600 --> 00:02:01,080 Speaker 3: of the tariff rates in the way it calculated, it 37 00:02:01,120 --> 00:02:05,160 Speaker 3: seemed very high and a little difficult to accomplish their goals. 38 00:02:05,200 --> 00:02:08,280 Speaker 3: And that seems like they walked that back. And now 39 00:02:08,720 --> 00:02:11,320 Speaker 3: that we're on a more sound of footing, I think 40 00:02:11,760 --> 00:02:13,880 Speaker 3: and it's easier to see what we're going to look like, 41 00:02:14,200 --> 00:02:16,640 Speaker 3: a blended tariff rate for the country ten to twenty 42 00:02:16,639 --> 00:02:20,160 Speaker 3: percent low allies, higher for folks that we're not so 43 00:02:20,280 --> 00:02:23,040 Speaker 3: friendly with, and we're still trying to change people's approach 44 00:02:23,280 --> 00:02:25,400 Speaker 3: to trade to make it more balanced and fair and 45 00:02:25,520 --> 00:02:28,840 Speaker 3: open things up to US goods and services. I think 46 00:02:28,919 --> 00:02:31,600 Speaker 3: Secretary Best has been real clear that that's what they 47 00:02:31,680 --> 00:02:33,160 Speaker 3: want to do. They did that when they were talking 48 00:02:33,200 --> 00:02:35,560 Speaker 3: with China about China as well, that what they want 49 00:02:35,639 --> 00:02:38,600 Speaker 3: is China to spend more and to become more open 50 00:02:38,639 --> 00:02:40,120 Speaker 3: to the US. And if they can do that, I 51 00:02:40,120 --> 00:02:42,720 Speaker 3: think it's a game changing win for the administration. 52 00:02:43,280 --> 00:02:46,560 Speaker 1: We had some new data today showing that American businesses 53 00:02:46,800 --> 00:02:49,560 Speaker 1: and consumers are paying for these tariffs. If you look 54 00:02:49,560 --> 00:02:53,760 Speaker 1: at import prices excluding fuel, those prices were up notably 55 00:02:53,800 --> 00:02:58,560 Speaker 1: in June, and George Saravellos from Deutsche Bank was saying 56 00:02:58,600 --> 00:03:02,840 Speaker 1: today the top down macro evidence seems clear Americans are 57 00:03:02,880 --> 00:03:05,440 Speaker 1: mostly paying for these tariffs, and a pair of economists 58 00:03:05,440 --> 00:03:09,639 Speaker 1: over at Wells Fargo saying today that domestic firms are 59 00:03:09,680 --> 00:03:13,320 Speaker 1: stomaching the cost of these higher tariffs and starting to 60 00:03:13,360 --> 00:03:16,800 Speaker 1: pass them on to consumers. So if we can accept 61 00:03:16,800 --> 00:03:20,440 Speaker 1: the reality that these costs are ultimately going to be 62 00:03:20,520 --> 00:03:25,240 Speaker 1: borne by American businesses and consumers, talk to me about 63 00:03:25,240 --> 00:03:29,160 Speaker 1: your expectations for the drag that that could potentially have 64 00:03:29,280 --> 00:03:30,240 Speaker 1: on USGDP. 65 00:03:31,240 --> 00:03:33,600 Speaker 3: Yeah, it could be a drag. It's hard to say. 66 00:03:33,720 --> 00:03:36,560 Speaker 3: I think currently who's paying for it and how much? 67 00:03:36,600 --> 00:03:38,440 Speaker 3: I mean, I think there's a blend of things going on, 68 00:03:38,480 --> 00:03:40,960 Speaker 3: and it depends on the type of product, It depends 69 00:03:40,960 --> 00:03:43,280 Speaker 3: on the mix, and depends how much it's going to 70 00:03:43,280 --> 00:03:46,880 Speaker 3: be offset by, you know, by margins and the like. 71 00:03:46,920 --> 00:03:48,800 Speaker 3: It's a little hard to think. It looks currently as 72 00:03:48,840 --> 00:03:51,320 Speaker 3: if thirty to fifty percent of it or so is 73 00:03:51,360 --> 00:03:55,120 Speaker 3: being passed on, But again it's a little hard. You know, 74 00:03:55,160 --> 00:03:57,720 Speaker 3: we're still quite in the early days of this, so 75 00:03:58,160 --> 00:04:00,400 Speaker 3: I'm not quite sure I know how it's going to 76 00:04:00,400 --> 00:04:03,480 Speaker 3: play out. It does look like US companies and are 77 00:04:03,480 --> 00:04:05,720 Speaker 3: going to be paying for certainly some of it, and 78 00:04:05,760 --> 00:04:07,360 Speaker 3: they're going to pass that on, and is that going 79 00:04:07,400 --> 00:04:09,560 Speaker 3: to be a drag? I think it works out as 80 00:04:09,600 --> 00:04:12,640 Speaker 3: something of a tax rise, But then there's other taxes 81 00:04:12,720 --> 00:04:15,120 Speaker 3: through the fiscal package that look as if they're offsetting 82 00:04:15,200 --> 00:04:17,200 Speaker 3: some of that. So it's a little hard to know 83 00:04:17,279 --> 00:04:18,120 Speaker 3: how it shakes out. 84 00:04:18,160 --> 00:04:18,520 Speaker 2: I think. 85 00:04:19,000 --> 00:04:21,000 Speaker 1: So we're in the midst of earning season here in 86 00:04:21,040 --> 00:04:23,919 Speaker 1: the US Bloomberg Intelligence was saying today that if you 87 00:04:23,920 --> 00:04:26,880 Speaker 1: look at the MAG seven companies, they're expected to post 88 00:04:26,920 --> 00:04:31,400 Speaker 1: a combined gain in second quarter profits of around fourteen percent, 89 00:04:31,480 --> 00:04:34,359 Speaker 1: But if you look at earnings for the remainder of 90 00:04:34,360 --> 00:04:38,320 Speaker 1: the S and P, they're predicted to be essentially flat. 91 00:04:38,680 --> 00:04:42,600 Speaker 1: How are you viewing the overall equity market right now? 92 00:04:42,040 --> 00:04:44,840 Speaker 3: I VI the equity market. I think it's clear to 93 00:04:44,839 --> 00:04:47,400 Speaker 3: you say, what you're doing is splitting out the MAG 94 00:04:47,480 --> 00:04:49,200 Speaker 3: seven stocks so that they're they're in a class of 95 00:04:49,240 --> 00:04:53,160 Speaker 3: their own. They're fairly expensive, but they are fabulous businesses, 96 00:04:53,680 --> 00:04:55,960 Speaker 3: they really are. That they're bringing in money from all 97 00:04:56,000 --> 00:04:59,960 Speaker 3: over the world. They're largely dominant in their respective space. 98 00:05:00,160 --> 00:05:02,839 Speaker 3: And clearly the AI trade, the hyperscale and nature of 99 00:05:02,880 --> 00:05:05,680 Speaker 3: it is what's driving that. 100 00:05:05,920 --> 00:05:06,080 Speaker 2: Now. 101 00:05:06,120 --> 00:05:09,640 Speaker 3: I think what you're going to see is that this 102 00:05:09,800 --> 00:05:13,920 Speaker 3: last year or so, the AI boom has a crued 103 00:05:14,000 --> 00:05:16,080 Speaker 3: to those companies, the people that are building it out 104 00:05:16,160 --> 00:05:18,760 Speaker 3: and buying the chips and spending lots and lots of 105 00:05:18,800 --> 00:05:21,279 Speaker 3: money to try and bring AI, you know, into the 106 00:05:21,320 --> 00:05:23,640 Speaker 3: real economy. And I think over the next couple of 107 00:05:23,720 --> 00:05:26,960 Speaker 3: years you're going to see the rest of the S 108 00:05:27,000 --> 00:05:29,920 Speaker 3: and P start to become users of that AI technology 109 00:05:29,920 --> 00:05:32,440 Speaker 3: and that productivity boost, and you're going to start to 110 00:05:32,480 --> 00:05:34,480 Speaker 3: see in a lumpy fashion, I think, where it will 111 00:05:34,520 --> 00:05:37,719 Speaker 3: be different for different companies as they start to adopt it. 112 00:05:37,800 --> 00:05:39,560 Speaker 3: But I think you're going to see some real use 113 00:05:39,600 --> 00:05:43,640 Speaker 3: cases of companies that are making use of that AI 114 00:05:43,960 --> 00:05:50,039 Speaker 3: and seeing strange, unpredictable earnings jumps as they're using it 115 00:05:50,080 --> 00:05:52,440 Speaker 3: better in margins go up. And I think that that's 116 00:05:52,480 --> 00:05:54,040 Speaker 3: how I'm viewing it that the last year or so 117 00:05:54,160 --> 00:05:56,080 Speaker 3: you've seen the hyperscalers and the Max seven do real 118 00:05:56,120 --> 00:05:59,560 Speaker 3: well on the AI trade, and the next couple of 119 00:05:59,640 --> 00:06:02,960 Speaker 3: years going to see that those gains be actually used 120 00:06:04,000 --> 00:06:07,240 Speaker 3: in companies and you'll start to see that benefit broadened 121 00:06:07,240 --> 00:06:08,240 Speaker 3: out to other companies. 122 00:06:08,360 --> 00:06:11,440 Speaker 1: At the risk of using a cliche to what extent 123 00:06:11,600 --> 00:06:15,440 Speaker 1: is the market right now price to perfection and by extension, 124 00:06:15,600 --> 00:06:18,960 Speaker 1: if we get the slightest disappointment from a name like 125 00:06:19,120 --> 00:06:23,520 Speaker 1: Alphabet tomorrow, could that create huge negative consequence? 126 00:06:24,640 --> 00:06:24,880 Speaker 2: Yeah? 127 00:06:24,920 --> 00:06:27,080 Speaker 3: I think so. I mean, it depends on the scale 128 00:06:27,120 --> 00:06:28,800 Speaker 3: of it. I think one of the things that's wonderful 129 00:06:28,839 --> 00:06:33,000 Speaker 3: about about AI is it really does live in the future, though, 130 00:06:33,120 --> 00:06:35,120 Speaker 3: which means you can continue to kind of believe in 131 00:06:35,160 --> 00:06:38,360 Speaker 3: the story. So I think what you'd most likely see 132 00:06:38,360 --> 00:06:40,520 Speaker 3: in that situation, I guess it could come in two ways. 133 00:06:40,520 --> 00:06:43,360 Speaker 3: It could either be that the CAPEX build out is 134 00:06:43,480 --> 00:06:48,040 Speaker 3: incredibly expensive and that shocks people and that could cause 135 00:06:48,040 --> 00:06:51,480 Speaker 3: a disappointment. Or you could see for individual companies, particularly 136 00:06:51,480 --> 00:06:54,160 Speaker 3: like someone like Google, where they're on the receiving end 137 00:06:54,200 --> 00:06:58,960 Speaker 3: of challenges because of AI. I think in the former case, 138 00:06:58,960 --> 00:07:02,240 Speaker 3: where you saw that the that the build out was expensive, 139 00:07:02,400 --> 00:07:04,479 Speaker 3: it'd be easier to look through it because you could 140 00:07:04,480 --> 00:07:07,440 Speaker 3: see that although it's expensive, they're doing it for a reason, 141 00:07:07,520 --> 00:07:10,360 Speaker 3: and that companies will get a benefit from this. They're 142 00:07:10,400 --> 00:07:12,600 Speaker 3: not wasting money. I think if you saw it the 143 00:07:12,640 --> 00:07:15,280 Speaker 3: other way around, for Google in particular, that they were 144 00:07:15,720 --> 00:07:18,640 Speaker 3: really starting to lose ground because of the core search 145 00:07:18,680 --> 00:07:21,800 Speaker 3: engine business, and that things like chat, GPT and some 146 00:07:21,880 --> 00:07:25,120 Speaker 3: of the other AI businesses were really encroaching in Google 147 00:07:25,160 --> 00:07:28,240 Speaker 3: in particular space, I think that would cause problems for 148 00:07:28,560 --> 00:07:29,320 Speaker 3: Google certainly. 149 00:07:29,560 --> 00:07:31,120 Speaker 1: So we have a FED meeting at the end of 150 00:07:31,120 --> 00:07:33,920 Speaker 1: the month. We know there's been a lot of controversy 151 00:07:34,000 --> 00:07:36,200 Speaker 1: around the fact that the FED has been unwilling at 152 00:07:36,320 --> 00:07:39,960 Speaker 1: least at this point, to cut infrastrates again. Right now, 153 00:07:40,000 --> 00:07:43,120 Speaker 1: the market's convinced that September is the next meeting where 154 00:07:43,160 --> 00:07:46,240 Speaker 1: that twenty five basis point cut is likely. How are 155 00:07:46,280 --> 00:07:49,680 Speaker 1: you viewing FED policy right now? And if you could 156 00:07:49,720 --> 00:07:52,280 Speaker 1: put that kind of in the context of a lot 157 00:07:52,280 --> 00:07:55,600 Speaker 1: of the tension that seems to exist between let's say 158 00:07:55,600 --> 00:07:57,520 Speaker 1: the White House and the Fed. 159 00:07:58,320 --> 00:08:00,800 Speaker 3: Yeah, there's a lot of political pressure put on Powell 160 00:08:01,600 --> 00:08:05,080 Speaker 3: and the rest of the FOMC for lower rates. Powell 161 00:08:05,200 --> 00:08:07,760 Speaker 3: is clearly bearing a brunt of it. Obviously Trump did 162 00:08:07,800 --> 00:08:11,560 Speaker 3: appoint them because it's a slightly strange I think there's 163 00:08:11,600 --> 00:08:13,720 Speaker 3: a good case. I don't think Trump's completely wrong here 164 00:08:13,760 --> 00:08:17,440 Speaker 3: that the FED should cut rates. I don't think they're 165 00:08:17,440 --> 00:08:19,960 Speaker 3: particularly slow in doing so. But I think at this 166 00:08:20,000 --> 00:08:24,160 Speaker 3: point it's fairly clear. I think that things are slowing 167 00:08:24,280 --> 00:08:27,920 Speaker 3: somewhat and that the inflationary dynamics that you saw a 168 00:08:27,960 --> 00:08:30,560 Speaker 3: couple of years ago aren't really there. You can really 169 00:08:30,560 --> 00:08:32,640 Speaker 3: see that in house prices and some of the very 170 00:08:32,640 --> 00:08:34,880 Speaker 3: interest rates that sensitive sector of the economy look as 171 00:08:34,920 --> 00:08:37,640 Speaker 3: if they're slowing. So I'm not particularly worried about inflation 172 00:08:37,720 --> 00:08:39,920 Speaker 3: picking up again. And I think that when you've got 173 00:08:40,000 --> 00:08:41,880 Speaker 3: a FED rate that is what four p thirty three 174 00:08:41,960 --> 00:08:45,480 Speaker 3: or four point three currently that is notably above where 175 00:08:45,480 --> 00:08:48,760 Speaker 3: I think inflation ends up, particularly be adjust for the 176 00:08:48,800 --> 00:08:52,320 Speaker 3: housing issue. I think Trump is likely right. I mean, 177 00:08:52,360 --> 00:08:53,640 Speaker 3: I don't think we need to be cutting rates by 178 00:08:53,679 --> 00:08:55,360 Speaker 3: two hundred basis points. That I think is a bit 179 00:08:55,400 --> 00:08:59,760 Speaker 3: extreme there. But should the FED be cutting in July 180 00:08:59,840 --> 00:09:02,240 Speaker 3: and septem berming, Yes, I think so. I mean, you 181 00:09:02,240 --> 00:09:04,480 Speaker 3: could get rates down fifty to seventy five basis points, 182 00:09:04,480 --> 00:09:06,480 Speaker 3: and I think that would be I don't think that 183 00:09:06,520 --> 00:09:08,760 Speaker 3: would be unreasonable all. I don't think it's right that 184 00:09:08,800 --> 00:09:10,760 Speaker 3: they're putting quite so much pressure on them. I don't 185 00:09:10,760 --> 00:09:14,280 Speaker 3: think that's particularly helpful. And if you do end up 186 00:09:14,320 --> 00:09:18,240 Speaker 3: with a powel that was fired, I don't quite know 187 00:09:18,280 --> 00:09:20,840 Speaker 3: how that would play out. I imagine you'd see a 188 00:09:20,880 --> 00:09:23,719 Speaker 3: steeper curve because you'd a price that rates would get 189 00:09:23,720 --> 00:09:26,320 Speaker 3: cut more drastically, and then you might price that you'd 190 00:09:26,320 --> 00:09:30,120 Speaker 3: lose somewhat lose some control of the back end of 191 00:09:30,160 --> 00:09:33,280 Speaker 3: the curve. But you know, it's a staggered a committee 192 00:09:33,679 --> 00:09:37,760 Speaker 3: with staggered appointments. So I think there's plenty of other 193 00:09:37,760 --> 00:09:40,680 Speaker 3: people on the FED that will continue with the monetary 194 00:09:40,720 --> 00:09:42,880 Speaker 3: policy in the manner of which they've been doing it 195 00:09:42,920 --> 00:09:43,240 Speaker 3: so far. 196 00:09:43,520 --> 00:09:45,440 Speaker 1: David will leave it there, always a pleasure. Thank you 197 00:09:45,480 --> 00:09:48,960 Speaker 1: so very much. David Espell, partner co CIO at Mount 198 00:09:49,000 --> 00:09:52,520 Speaker 1: Lucas Management, joining from just outside Philadelphia here on the 199 00:09:52,600 --> 00:10:06,079 Speaker 1: Daybreak as your podcast. Welcome back to the Daybreak Asia podcast. 200 00:10:06,160 --> 00:10:10,240 Speaker 1: I'm Doug Chrisner. Markets are now looking ahead to megacap tech. 201 00:10:10,280 --> 00:10:13,599 Speaker 1: Earnings from both Alphabet and Tesla companies are set to 202 00:10:13,679 --> 00:10:17,000 Speaker 1: report in under twenty four hours. Let's take a closer 203 00:10:17,040 --> 00:10:19,959 Speaker 1: look now. I'm joined by Stephanie Leung. She is the 204 00:10:20,080 --> 00:10:23,920 Speaker 1: chief investment officer at Stashaway. Stephanie joins us from our 205 00:10:23,960 --> 00:10:26,800 Speaker 1: studios in Hong Kong. Thank you so much for making 206 00:10:26,840 --> 00:10:28,640 Speaker 1: time to chat with me. I'm going to play to 207 00:10:28,720 --> 00:10:34,200 Speaker 1: one of your strengths, technology and particularly artificial intelligence. On 208 00:10:34,280 --> 00:10:36,240 Speaker 1: Wednesday here in the States. After the bell, we're going 209 00:10:36,320 --> 00:10:38,800 Speaker 1: to hear from Alphabet, and I think the market's going 210 00:10:38,840 --> 00:10:41,880 Speaker 1: to be very curious not only on spending when it 211 00:10:41,920 --> 00:10:46,240 Speaker 1: comes to AI, but what some analysts have expressed concern 212 00:10:46,480 --> 00:10:49,000 Speaker 1: over in the past, which is how AI may be 213 00:10:49,360 --> 00:10:54,400 Speaker 1: impacting the company's core search business. How do you understand 214 00:10:54,679 --> 00:10:58,760 Speaker 1: the risk of some of these AI back chatbots posing 215 00:10:58,800 --> 00:11:01,040 Speaker 1: some sort of risk to a business, even for bay 216 00:11:01,120 --> 00:11:03,599 Speaker 1: Do in China, which has around seventy percent of the 217 00:11:03,640 --> 00:11:08,000 Speaker 1: search market. Is AI a way for this to be reimagined, 218 00:11:08,000 --> 00:11:10,319 Speaker 1: do you think, and maybe does it represent a near 219 00:11:10,440 --> 00:11:10,920 Speaker 1: term risk? 220 00:11:11,760 --> 00:11:13,720 Speaker 4: Yeah? I think, I mean you bring a very very 221 00:11:13,760 --> 00:11:16,319 Speaker 4: good point, right in the sense that, of course, if 222 00:11:16,360 --> 00:11:19,199 Speaker 4: you think about the Internet era, search was a very 223 00:11:19,280 --> 00:11:23,000 Speaker 4: very profitable business and Google by do pretty much have 224 00:11:23,240 --> 00:11:27,079 Speaker 4: like a dominance or monopoly in these businesses. However, if 225 00:11:27,120 --> 00:11:29,520 Speaker 4: we enter the AI era, if you think about kind 226 00:11:29,559 --> 00:11:33,000 Speaker 4: of just what people go to search engines to do, 227 00:11:33,080 --> 00:11:36,240 Speaker 4: they're basically asking questions, and you can ask these questions 228 00:11:36,320 --> 00:11:39,600 Speaker 4: much more directly and get much better answers by going 229 00:11:39,640 --> 00:11:44,560 Speaker 4: to the LM chat bots to ask the same questions, 230 00:11:44,920 --> 00:11:47,400 Speaker 4: and they will give you a much more comprehensive answer 231 00:11:47,480 --> 00:11:51,000 Speaker 4: rather than just the templu links that that Google would provide. 232 00:11:51,320 --> 00:11:53,960 Speaker 4: And I think that actually creates a sort of a 233 00:11:54,000 --> 00:11:56,959 Speaker 4: dilemma for companies like Google in the sense that I 234 00:11:57,000 --> 00:11:59,880 Speaker 4: mean they know that that's the direction that things are going. However, 235 00:12:00,080 --> 00:12:02,960 Speaker 4: of course they have existing sort of earnings to try 236 00:12:03,000 --> 00:12:05,680 Speaker 4: to protect, so they need to. I mean, they are 237 00:12:05,720 --> 00:12:08,920 Speaker 4: trying to actually strike a balance between like kind of 238 00:12:08,960 --> 00:12:13,640 Speaker 4: not cannibalizing the existing business, but meanwhile making efforts to 239 00:12:13,679 --> 00:12:16,280 Speaker 4: make sure that they don't get this kind of extinct 240 00:12:16,760 --> 00:12:19,760 Speaker 4: in the in the new AI era. So, for example AI, 241 00:12:20,000 --> 00:12:21,840 Speaker 4: if you go to Google Search right now, you see 242 00:12:21,880 --> 00:12:26,600 Speaker 4: that they will provide a AI generated search summary. Uh, 243 00:12:26,679 --> 00:12:29,800 Speaker 4: and that's sort of some of the efforts to help 244 00:12:30,400 --> 00:12:33,680 Speaker 4: the company that migrates. Of course, I think if you 245 00:12:33,679 --> 00:12:36,400 Speaker 4: look at the share price and also valuation, I mean 246 00:12:36,400 --> 00:12:39,160 Speaker 4: that concern seems to me to be quite well understood 247 00:12:39,160 --> 00:12:41,079 Speaker 4: by the market in the sense that if you kind 248 00:12:41,080 --> 00:12:44,240 Speaker 4: of kind of compare Google's valuation versus others in the 249 00:12:44,320 --> 00:12:46,640 Speaker 4: Max seven, I mean, they are the lowest, and they're 250 00:12:46,679 --> 00:12:50,320 Speaker 4: also trading at the lowest kind of price earnings valuation 251 00:12:50,520 --> 00:12:54,560 Speaker 4: compared to its own history. So I think if you 252 00:12:54,640 --> 00:12:57,200 Speaker 4: just kind of look at Google's kind of whole business, 253 00:12:57,520 --> 00:12:59,560 Speaker 4: of course, search is a very very important part. 254 00:12:59,600 --> 00:13:01,080 Speaker 5: However, there are other businesses. 255 00:13:01,120 --> 00:13:05,040 Speaker 4: For example, Weimo is making some very good progress in 256 00:13:05,120 --> 00:13:06,440 Speaker 4: terms of autonomous driving. 257 00:13:06,480 --> 00:13:07,800 Speaker 5: That's also AI driven. 258 00:13:08,280 --> 00:13:08,520 Speaker 2: Uh. 259 00:13:08,559 --> 00:13:11,760 Speaker 5: If you look at kind of YouTube, it's also doing well. 260 00:13:12,440 --> 00:13:13,320 Speaker 5: That's uh. 261 00:13:13,440 --> 00:13:17,280 Speaker 4: There's also kind of AI enabled kind of algorithms that 262 00:13:17,400 --> 00:13:22,680 Speaker 4: help them to sort of promote relevant videos and velephant contents. 263 00:13:23,040 --> 00:13:25,520 Speaker 4: So I do think that there are actually, of course, 264 00:13:26,000 --> 00:13:28,319 Speaker 4: there are other levers that googleg and pull, and one 265 00:13:28,320 --> 00:13:30,240 Speaker 4: of which is of course, like if you and I 266 00:13:30,400 --> 00:13:33,920 Speaker 4: kind of look at war is the most popular mail 267 00:13:34,920 --> 00:13:37,360 Speaker 4: protocol and mail program out there. I mean there's still 268 00:13:37,360 --> 00:13:40,720 Speaker 4: a Gmail, right, So I think there are optionalities. It's 269 00:13:40,760 --> 00:13:43,120 Speaker 4: about just kind of in the intim period, how to 270 00:13:43,240 --> 00:13:46,000 Speaker 4: balance kind of the the search business with it. 271 00:13:46,200 --> 00:13:48,960 Speaker 1: So if you're looking at opportunities in AI in China, 272 00:13:49,000 --> 00:13:52,319 Speaker 1: are you more focused on the software side or are 273 00:13:52,320 --> 00:13:55,679 Speaker 1: you looking at the hardware story and maybe semiconductors, how 274 00:13:55,679 --> 00:13:56,240 Speaker 1: do you play it? 275 00:13:57,080 --> 00:13:57,559 Speaker 5: I think. 276 00:13:58,880 --> 00:14:01,199 Speaker 4: If you look at the semiconduct to our hardware side, 277 00:14:02,120 --> 00:14:05,680 Speaker 4: it's very very focused in a few kind of companies 278 00:14:05,679 --> 00:14:08,360 Speaker 4: that have the technology. So by that I mean, for example, 279 00:14:08,440 --> 00:14:10,920 Speaker 4: n video, Nvidia has the chips that are kind of 280 00:14:10,960 --> 00:14:13,760 Speaker 4: ways ahead. And if you look at all the recent 281 00:14:13,880 --> 00:14:17,319 Speaker 4: kind of announcements from big big tech companies like for example, 282 00:14:17,920 --> 00:14:20,800 Speaker 4: Matters big announcement of their data centers, I mean they 283 00:14:20,800 --> 00:14:24,880 Speaker 4: are still predominantly using UH in video technology. UH if 284 00:14:24,920 --> 00:14:29,040 Speaker 4: you look at kind of in China. Of course, recently, uh, 285 00:14:29,080 --> 00:14:33,360 Speaker 4: President Trump lifted the restriction to export H twenty chips 286 00:14:33,400 --> 00:14:36,520 Speaker 4: to China, and I mean Nvidia is receiving a lot 287 00:14:36,560 --> 00:14:39,600 Speaker 4: of orders and I mean the citing supply shortages. 288 00:14:40,040 --> 00:14:42,480 Speaker 5: So still Nvidia is the kind of the. 289 00:14:42,400 --> 00:14:46,920 Speaker 4: Dominant player in the infrastructure layer. Of course, like companies 290 00:14:46,920 --> 00:14:50,200 Speaker 4: like Huawei are catching up, but I think they are 291 00:14:50,240 --> 00:14:53,800 Speaker 4: still kind of somewhat behind on the application side. I 292 00:14:53,800 --> 00:14:56,200 Speaker 4: think that's where it gets more interesting, right, because it's 293 00:14:56,240 --> 00:15:01,160 Speaker 4: not it's not that kind of u dominated by one 294 00:15:01,240 --> 00:15:03,440 Speaker 4: or two players. I think in the application side, you 295 00:15:03,440 --> 00:15:06,920 Speaker 4: can see a lot of very creative uses of the 296 00:15:07,040 --> 00:15:11,920 Speaker 4: underlying technology in terms of driving usage, driving revenue, or 297 00:15:11,960 --> 00:15:14,640 Speaker 4: cutting costs. And here I think you can see that 298 00:15:14,760 --> 00:15:17,600 Speaker 4: in the US there are different companies in different verticals 299 00:15:18,600 --> 00:15:23,160 Speaker 4: kind of I guess making big strides. And also in China, right, 300 00:15:23,480 --> 00:15:25,800 Speaker 4: if you look at kind of the software companies, I 301 00:15:25,840 --> 00:15:28,040 Speaker 4: think they are one of the first to benefit from 302 00:15:28,160 --> 00:15:31,560 Speaker 4: these AI coding agents, for example, and these actually benefit 303 00:15:32,040 --> 00:15:34,720 Speaker 4: a lot more companies than just the infrastructure. 304 00:15:34,800 --> 00:15:38,360 Speaker 1: Later, you touched on autonomous driving in China a moment ago, 305 00:15:38,440 --> 00:15:42,880 Speaker 1: and I'm curious how is that progressing? Are there developments 306 00:15:42,920 --> 00:15:45,080 Speaker 1: that look promising at this point where you want to 307 00:15:45,080 --> 00:15:47,400 Speaker 1: be invested in those companies? 308 00:15:48,480 --> 00:15:52,040 Speaker 4: I think in China is developing very very quickly, but 309 00:15:52,120 --> 00:15:54,480 Speaker 4: still if you look at kind of the where their 310 00:15:54,520 --> 00:15:57,760 Speaker 4: technology is in the forefront is still in the US 311 00:15:57,880 --> 00:16:01,600 Speaker 4: right Tesla is leading the effort in developing some of 312 00:16:01,600 --> 00:16:06,560 Speaker 4: the more advanced AI driven kind of I guess automis 313 00:16:06,680 --> 00:16:10,440 Speaker 4: driving technologies. As I mentioned, Weimo is also making some 314 00:16:10,560 --> 00:16:13,800 Speaker 4: very vaguer good progresses. So these are companies that are 315 00:16:13,840 --> 00:16:16,600 Speaker 4: at the forefront. I think in China is where the 316 00:16:16,640 --> 00:16:21,360 Speaker 4: application of these technologies may actually surprise on the upside 317 00:16:21,600 --> 00:16:24,360 Speaker 4: in the sense that I think if you look at 318 00:16:24,440 --> 00:16:27,880 Speaker 4: kind of how China can deploy these technologies, it tends 319 00:16:27,920 --> 00:16:31,240 Speaker 4: to be a lot more efficient. So I think that's 320 00:16:31,280 --> 00:16:33,920 Speaker 4: sort of at the again, it's at the application layer 321 00:16:33,960 --> 00:16:36,240 Speaker 4: where some of these companies can benefit. 322 00:16:36,760 --> 00:16:39,600 Speaker 1: We know the trade negotiators from the European Union and 323 00:16:39,760 --> 00:16:42,160 Speaker 1: the US will be meeting again this week for more 324 00:16:42,200 --> 00:16:45,560 Speaker 1: trade talks. So whether we're talking about the European Union 325 00:16:45,800 --> 00:16:48,480 Speaker 1: or China, we do have this August deadline in front 326 00:16:48,520 --> 00:16:51,480 Speaker 1: of us. But I'm curious, are you optimistic that we're 327 00:16:51,520 --> 00:16:53,720 Speaker 1: going to be able to kind of turn the page 328 00:16:53,720 --> 00:16:54,960 Speaker 1: on this tariff story soon. 329 00:16:55,600 --> 00:16:59,280 Speaker 4: So I think if you look at Trump's policy, it's 330 00:16:59,320 --> 00:17:02,920 Speaker 4: been kind of kicking the can down the road. And 331 00:17:03,240 --> 00:17:07,199 Speaker 4: if you listen to the latest Bestent interview, what he 332 00:17:07,280 --> 00:17:10,399 Speaker 4: mentioned was actually quite telling, right he said, it's about 333 00:17:10,400 --> 00:17:12,879 Speaker 4: the quality of the outcome, not the timing of the outcome. 334 00:17:12,960 --> 00:17:16,400 Speaker 4: So I think again, the next kind of deadline that's 335 00:17:16,440 --> 00:17:19,040 Speaker 4: coming up and is first of August, which is kind 336 00:17:19,040 --> 00:17:22,720 Speaker 4: of a few days from from today, but I do 337 00:17:22,800 --> 00:17:25,440 Speaker 4: suspect that they will try to kick the can down 338 00:17:25,440 --> 00:17:29,280 Speaker 4: the road again, which I think it's it's sort of 339 00:17:30,080 --> 00:17:33,720 Speaker 4: expected or digested by the market. And if you look 340 00:17:33,720 --> 00:17:37,080 Speaker 4: at kind of the current level of actual tariffs that 341 00:17:37,320 --> 00:17:39,720 Speaker 4: are being imposed, they are sort of in ten to 342 00:17:39,760 --> 00:17:42,840 Speaker 4: twenty percent range. And I think if you look at 343 00:17:42,960 --> 00:17:46,200 Speaker 4: the where it like the level of the level of 344 00:17:46,280 --> 00:17:49,320 Speaker 4: tariff really hit US economy, if it goes up to 345 00:17:49,440 --> 00:17:53,399 Speaker 4: about thirty percent, then that's when things get much challenged, 346 00:17:53,440 --> 00:17:56,359 Speaker 4: much more challenging. So I mean, we'll have to see 347 00:17:56,359 --> 00:17:59,320 Speaker 4: what the outcome is, But I mean I think if 348 00:17:59,320 --> 00:18:02,160 Speaker 4: you look at kind of the summer months August September 349 00:18:02,200 --> 00:18:02,920 Speaker 4: tends to be. 350 00:18:02,960 --> 00:18:05,400 Speaker 5: Like the worst months in terms of seasonality. 351 00:18:05,760 --> 00:18:08,840 Speaker 4: I mean, liquidity is quite thin, and I mean we've 352 00:18:08,840 --> 00:18:11,720 Speaker 4: had a market that has rally like twenty something thirty 353 00:18:11,720 --> 00:18:15,080 Speaker 4: percent from as bottom. So I wouldn't be surprised if 354 00:18:15,200 --> 00:18:17,440 Speaker 4: in the summer we see some headlines coming out from 355 00:18:17,440 --> 00:18:21,119 Speaker 4: these trade talks that could rattle markets and create I 356 00:18:21,119 --> 00:18:23,639 Speaker 4: mean five to ten percent correction. However, the fundamentals are 357 00:18:23,640 --> 00:18:26,399 Speaker 4: still quite solid, so I think those are kind of 358 00:18:26,400 --> 00:18:28,879 Speaker 4: good opportunity for people to still I mean, add to 359 00:18:28,920 --> 00:18:29,280 Speaker 4: the risk. 360 00:18:29,720 --> 00:18:31,840 Speaker 1: Stephanie will leave it there. It's always a pleasure. Thank 361 00:18:31,840 --> 00:18:34,440 Speaker 1: you so very much, Stephanie Jung. She is the chief 362 00:18:34,480 --> 00:18:38,760 Speaker 1: investment officer at Stashaway. Joining from our Hong Kong studios 363 00:18:38,760 --> 00:18:43,760 Speaker 1: here on the Daybreak Asia Podcast. Thanks for listening to 364 00:18:43,760 --> 00:18:48,760 Speaker 1: today's episode of the Bloomberg Daybreak Asia Edition podcast. Each weekday, 365 00:18:48,800 --> 00:18:52,720 Speaker 1: we look at the story shaping markets, finance, and geopolitics 366 00:18:52,720 --> 00:18:56,000 Speaker 1: in the Asia Pacific. You can find us on Apple, Spotify, 367 00:18:56,119 --> 00:18:59,639 Speaker 1: the Bloomberg Podcast YouTube channel, or anywhere else you listen. 368 00:19:00,080 --> 00:19:02,960 Speaker 1: Join us again tomorrow for insight on the market moves 369 00:19:03,000 --> 00:19:07,560 Speaker 1: from Hong Kong to Singapore and Australia. I'm Doug prisoner 370 00:19:07,720 --> 00:19:09,119 Speaker 1: and this is Bloomberg