1 00:00:02,480 --> 00:00:07,000 Speaker 1: Bloomberg Audio Studios, podcasts, radio news. 2 00:00:11,320 --> 00:00:14,760 Speaker 2: Welcome to the Daybreak Asia podcast. I'm Doug Krisner. The 3 00:00:14,920 --> 00:00:19,360 Speaker 2: US is accusing China of engaging in unfair trade practices 4 00:00:19,440 --> 00:00:22,920 Speaker 2: in semiconductors. Now. This is the result of a year's 5 00:00:22,960 --> 00:00:26,960 Speaker 2: long inquiry. It focused on China's production of those older 6 00:00:27,040 --> 00:00:34,040 Speaker 2: model chips widely used in devices like smartphones, automobiles, home appliances, weaponry, 7 00:00:34,240 --> 00:00:39,400 Speaker 2: even telecom networks. Now, the USTR found China employed increasingly 8 00:00:39,440 --> 00:00:44,280 Speaker 2: aggressive and sweeping non market policies to bolster at semiconductor industry. 9 00:00:44,680 --> 00:00:47,240 Speaker 2: And on top of that, the USTR found the China 10 00:00:47,280 --> 00:00:50,600 Speaker 2: move to create foreign dependency on its products in a 11 00:00:50,600 --> 00:00:54,720 Speaker 2: way that disadvantaged US commerce. Even so, the US Trade 12 00:00:54,720 --> 00:00:59,320 Speaker 2: rep is declining to impose additional tariffs on Chinese imports 13 00:00:59,400 --> 00:01:02,920 Speaker 2: at least till mid twenty twenty seven, perhaps given the 14 00:01:02,920 --> 00:01:07,199 Speaker 2: trade truth between Washington and Beijing. For a closer look 15 00:01:07,240 --> 00:01:11,520 Speaker 2: now at US China relations Visa v Technology. I'm joined 16 00:01:11,520 --> 00:01:16,520 Speaker 2: by Tiffany Shao, portfolio manager at Matthew's International Capital Management. 17 00:01:16,880 --> 00:01:19,920 Speaker 2: Tiffany joins us from San Francisco. Thank you so much 18 00:01:19,920 --> 00:01:22,479 Speaker 2: for being here, so as I understand you just got 19 00:01:22,520 --> 00:01:25,280 Speaker 2: back from Asia. Can you lay out for me what 20 00:01:25,360 --> 00:01:28,800 Speaker 2: you see right now as the tension when it comes 21 00:01:28,800 --> 00:01:30,880 Speaker 2: to high tech between the US and China. 22 00:01:32,319 --> 00:01:34,800 Speaker 3: No, typically as you head into your end, people are 23 00:01:34,800 --> 00:01:39,720 Speaker 3: ready for vacation. This year, everyone is preparing for an 24 00:01:39,720 --> 00:01:44,000 Speaker 3: acceleration in the deployment of artificial intelligence heading into twenty 25 00:01:44,040 --> 00:01:48,640 Speaker 3: twenty six. And you know, in the risk management business 26 00:01:48,720 --> 00:01:52,440 Speaker 3: and investment management business, we always have to consider worst 27 00:01:52,480 --> 00:01:56,000 Speaker 3: case scenarios, and one of those scenarios that we map 28 00:01:56,000 --> 00:01:59,240 Speaker 3: out is, you know, a continued, you know, heightened tension 29 00:01:59,440 --> 00:02:04,200 Speaker 3: between US in China. And in that scenario, which is 30 00:02:04,640 --> 00:02:08,160 Speaker 3: what we actually see companies start to prepare for, is 31 00:02:08,160 --> 00:02:13,080 Speaker 3: that there will be a parallel universe built for AI. 32 00:02:13,320 --> 00:02:16,919 Speaker 3: So there will be one AI ecosystem within China where 33 00:02:17,000 --> 00:02:20,680 Speaker 3: they don't want to rely on foreign sources, and there 34 00:02:20,720 --> 00:02:25,080 Speaker 3: will be an ecosystem outside of China led by the 35 00:02:25,240 --> 00:02:28,320 Speaker 3: US where we're trying to build up our own capabilities 36 00:02:28,360 --> 00:02:30,359 Speaker 3: as well. So it's really interesting to see and it's 37 00:02:30,400 --> 00:02:33,080 Speaker 3: keeping both sides very, very busy into the end of 38 00:02:33,080 --> 00:02:33,839 Speaker 3: twenty twenty five. 39 00:02:34,040 --> 00:02:37,000 Speaker 2: So as I'm listening, I'm wondering whether China will be 40 00:02:37,120 --> 00:02:41,600 Speaker 2: less interested in those advanced chips from Nvidia and become 41 00:02:41,760 --> 00:02:44,560 Speaker 2: maybe a little bit more reliant when it comes to 42 00:02:44,600 --> 00:02:48,760 Speaker 2: training AI models on chips that are domestically produced in China, 43 00:02:48,800 --> 00:02:50,760 Speaker 2: maybe something from the likes of Huawei. 44 00:02:51,200 --> 00:02:53,480 Speaker 3: So the Chinese are very practical. As you may know, 45 00:02:54,160 --> 00:02:59,280 Speaker 3: they will still procure semiconductor based on their needs. So 46 00:02:59,520 --> 00:03:04,000 Speaker 3: there is from video chips in China and various AA applications, 47 00:03:04,360 --> 00:03:08,519 Speaker 3: but there is definitely a bigger emphasis for the domestic 48 00:03:08,720 --> 00:03:14,040 Speaker 3: ecosystem to develop and to support the domestic ecosystem, whether 49 00:03:14,080 --> 00:03:18,760 Speaker 3: it's the semiconductors itself or building of data centers, ramping 50 00:03:18,800 --> 00:03:22,720 Speaker 3: up their power infrastructure, which is incredibly robust. So those 51 00:03:22,760 --> 00:03:25,480 Speaker 3: are ongoing activities that we see on the ground. 52 00:03:25,960 --> 00:03:28,440 Speaker 2: That's interesting that you mentioned the power angle to the 53 00:03:28,480 --> 00:03:32,639 Speaker 2: AI story, because from what we know, China has really 54 00:03:32,720 --> 00:03:37,040 Speaker 2: done very well in ramping up capacity to produce electricity, 55 00:03:37,160 --> 00:03:39,880 Speaker 2: maybe more so than the US. And at the end 56 00:03:39,960 --> 00:03:42,720 Speaker 2: of the day, because those AI data centers are so 57 00:03:43,400 --> 00:03:47,760 Speaker 2: heavily reliant on electricity, I'm wondering whether China is in 58 00:03:47,880 --> 00:03:49,840 Speaker 2: a much more advantageous place. 59 00:03:51,800 --> 00:03:56,280 Speaker 3: You're absolutely right. AI is very power hungry and China 60 00:03:56,480 --> 00:03:59,880 Speaker 3: is very well equipped to handle the power crisis. They 61 00:04:00,240 --> 00:04:05,960 Speaker 3: have been fortifying their power infrastructure for decades now, so 62 00:04:06,280 --> 00:04:09,640 Speaker 3: that's also an opportunity for outside of China, for our 63 00:04:09,720 --> 00:04:14,560 Speaker 3: companies in Asia that actually are now helping the US 64 00:04:14,640 --> 00:04:19,200 Speaker 3: fortify its power infrastructure. So we see opportunities across Asia 65 00:04:19,400 --> 00:04:23,760 Speaker 3: that really help both sides of the AI race. 66 00:04:24,040 --> 00:04:26,799 Speaker 2: In the early part of the trade tension story between 67 00:04:26,839 --> 00:04:29,760 Speaker 2: the US and China, the US was trying to limit 68 00:04:29,880 --> 00:04:33,839 Speaker 2: Chinese access to technology from other countries, whether it was 69 00:04:33,920 --> 00:04:39,320 Speaker 2: Japan or South Korea. I'm thinking of also ASML in 70 00:04:39,560 --> 00:04:42,840 Speaker 2: the Netherlands. Is this something that China has been able 71 00:04:42,839 --> 00:04:45,760 Speaker 2: to kind of work around or compensate for. 72 00:04:47,520 --> 00:04:51,680 Speaker 3: Absolutely, so they have figured out ways to do more 73 00:04:51,760 --> 00:04:56,080 Speaker 3: with less, and that means, you know, they are using 74 00:04:56,360 --> 00:05:01,080 Speaker 3: lagging edge technology, so typically around two nodes behind the 75 00:05:01,080 --> 00:05:06,279 Speaker 3: world leader, which is TSMC and Taiwan, but using more 76 00:05:06,400 --> 00:05:10,120 Speaker 3: creative ways of linking together these lagging edge chips. So 77 00:05:10,680 --> 00:05:14,599 Speaker 3: that's where we see opportunity. For example and optical communications. 78 00:05:14,680 --> 00:05:17,320 Speaker 3: So if your chips are slower, well you link them 79 00:05:17,360 --> 00:05:21,039 Speaker 3: up into a bigger chip and through optical communication it 80 00:05:21,080 --> 00:05:25,880 Speaker 3: would communicate faster than copper which is what Nvidia predominantly 81 00:05:25,960 --> 00:05:26,520 Speaker 3: uses at this. 82 00:05:26,520 --> 00:05:28,640 Speaker 2: Moment, I'm going to change gears and talk a little 83 00:05:28,680 --> 00:05:31,520 Speaker 2: bit about robotics. I'm curious to get your take on 84 00:05:31,560 --> 00:05:35,400 Speaker 2: what you saw when you were in Asia relative to 85 00:05:35,480 --> 00:05:36,880 Speaker 2: the robotics industry. 86 00:05:38,720 --> 00:05:38,920 Speaker 1: Yeah. 87 00:05:38,960 --> 00:05:43,200 Speaker 3: So robotics, what we often joke about is that in 88 00:05:43,320 --> 00:05:46,919 Speaker 3: China we call it a red sea industry, meaning it 89 00:05:47,000 --> 00:05:51,000 Speaker 3: has already gone through a cycle where now there's over competition, 90 00:05:51,440 --> 00:05:56,880 Speaker 3: there are thousands of suppliers and you know, you see 91 00:05:57,360 --> 00:06:00,919 Speaker 3: like it was in China earlier. This also just for 92 00:06:01,040 --> 00:06:04,360 Speaker 3: personal vacation and when you stay in a hotel room, 93 00:06:04,400 --> 00:06:06,320 Speaker 3: you just talk to the room to tell it you 94 00:06:06,400 --> 00:06:09,240 Speaker 3: need food, and robot actually shows up and delivers your food. 95 00:06:09,279 --> 00:06:12,760 Speaker 3: So they're at that level which is unimaginable here in 96 00:06:12,800 --> 00:06:15,760 Speaker 3: the US. So I would say in a lot of 97 00:06:15,839 --> 00:06:19,760 Speaker 3: areas within robotics, the US is lagging behind. But there's 98 00:06:19,760 --> 00:06:21,640 Speaker 3: an opportunity for the US to catch up. But it 99 00:06:21,640 --> 00:06:24,840 Speaker 3: has to go hand in hand with the re establishment 100 00:06:24,839 --> 00:06:28,480 Speaker 3: of the manufacturing base, because that's going to be a 101 00:06:28,640 --> 00:06:33,640 Speaker 3: more reliable way for US companies to trial and air 102 00:06:33,720 --> 00:06:35,719 Speaker 3: and fortify their product line. 103 00:06:36,040 --> 00:06:39,640 Speaker 2: Is there any concern in Asia about certain parts of 104 00:06:39,720 --> 00:06:43,560 Speaker 2: the AI trade being over extended. I hesitate to use 105 00:06:43,640 --> 00:06:45,840 Speaker 2: the term bubble, but that's been thrown around for the 106 00:06:45,920 --> 00:06:48,919 Speaker 2: last several months. Lately, it seems like it's no longer 107 00:06:48,960 --> 00:06:52,360 Speaker 2: really relevant because the market is continuing to move higher. 108 00:06:52,440 --> 00:06:55,359 Speaker 2: But is there concern here that some of these stock 109 00:06:55,440 --> 00:06:56,800 Speaker 2: prices are overextended? 110 00:06:58,600 --> 00:07:04,360 Speaker 3: Absolutely? I think, you know, in every stage of you know, 111 00:07:04,400 --> 00:07:08,000 Speaker 3: a large secular growth trend. As people always say, people 112 00:07:08,360 --> 00:07:11,360 Speaker 3: underestimate the long term, but overestimate the short term, and 113 00:07:11,400 --> 00:07:16,040 Speaker 3: I think in parts of the technology ecosystem you do 114 00:07:16,120 --> 00:07:20,320 Speaker 3: see that, right. And you know, I often tell investors 115 00:07:20,920 --> 00:07:27,440 Speaker 3: that we've never seen a brand new technology ramp up 116 00:07:27,560 --> 00:07:32,480 Speaker 3: at this scale with this speed. So, you know, the US, 117 00:07:32,560 --> 00:07:36,080 Speaker 3: just the US cloud service providers alone, in twenty twenty six, 118 00:07:36,560 --> 00:07:40,080 Speaker 3: we estimate they will spend about six hundred billion US dollars. 119 00:07:40,440 --> 00:07:45,040 Speaker 3: That's about the same size of the entire handset ecosystem, 120 00:07:45,200 --> 00:07:48,360 Speaker 3: which took decades to build up and now ships one 121 00:07:48,400 --> 00:07:52,160 Speaker 3: point three billion units a year. So you created a 122 00:07:52,320 --> 00:07:55,200 Speaker 3: brand new tech industry within two and a half years 123 00:07:55,360 --> 00:07:58,720 Speaker 3: that basically is the same size as the largest technology 124 00:07:58,720 --> 00:08:02,120 Speaker 3: product that we had known prior to AI. So at 125 00:08:02,120 --> 00:08:04,840 Speaker 3: that speed, you're going to create a lot of shortages, 126 00:08:04,920 --> 00:08:08,640 Speaker 3: a lot of artificial demand because people are trying to 127 00:08:08,640 --> 00:08:12,600 Speaker 3: double book. So I actually think that, you know, if 128 00:08:12,600 --> 00:08:15,200 Speaker 3: the whole industry just slows down and we actually do 129 00:08:15,240 --> 00:08:18,720 Speaker 3: things properly, that might be a healthier outcome. So from 130 00:08:18,720 --> 00:08:21,800 Speaker 3: that standpoint, I think, you know, slower is better, and 131 00:08:21,840 --> 00:08:24,760 Speaker 3: we'll eventually get to the type of AI that we 132 00:08:24,760 --> 00:08:26,280 Speaker 3: think will be very productive. 133 00:08:26,600 --> 00:08:30,400 Speaker 2: So you have an interesting perspective, vast experience in Asia 134 00:08:31,120 --> 00:08:35,280 Speaker 2: and your home base is San Francisco. Can you quickly 135 00:08:35,400 --> 00:08:41,400 Speaker 2: compare and contrast what you're seeing in Silicon Valley versus 136 00:08:41,480 --> 00:08:45,120 Speaker 2: China as it relates to some of these advanced technologies. 137 00:08:46,640 --> 00:08:48,920 Speaker 3: Yeah, I think, you know, the most interesting part is 138 00:08:48,960 --> 00:08:52,839 Speaker 3: an AI that we've been discussing. So the US companies 139 00:08:52,920 --> 00:08:58,439 Speaker 3: have a very grandiose goal of creating artificial general intelligence, 140 00:08:59,080 --> 00:09:02,880 Speaker 3: whereas in and across most of Asia, they're just trying 141 00:09:02,920 --> 00:09:06,040 Speaker 3: to infuse AI and using AI as a way to 142 00:09:06,080 --> 00:09:09,840 Speaker 3: boost productivity and solve one problem at a time. So 143 00:09:09,920 --> 00:09:12,439 Speaker 3: I often describe it as, you know, the Americans are 144 00:09:12,440 --> 00:09:15,840 Speaker 3: trying to build a spacecraft here to Mars, whereas in 145 00:09:15,880 --> 00:09:18,040 Speaker 3: Asia we're just trying to build planes to go from 146 00:09:18,080 --> 00:09:21,080 Speaker 3: one city to another. So in the very near term, 147 00:09:21,200 --> 00:09:23,640 Speaker 3: the result is that you're probably going to see the 148 00:09:23,679 --> 00:09:26,920 Speaker 3: Asian AI companies make money first because they're taking a 149 00:09:26,920 --> 00:09:30,679 Speaker 3: more pragmatic commercial approach. But over the long run, if 150 00:09:30,720 --> 00:09:34,440 Speaker 3: the US can really get to AGI, I think, yeah, 151 00:09:34,480 --> 00:09:37,599 Speaker 3: there's just so much more opportunities ahead. So it's a 152 00:09:37,679 --> 00:09:42,079 Speaker 3: very different approach, but it's really interesting to see the contrast. 153 00:09:41,920 --> 00:09:44,360 Speaker 2: And interesting to talk to you, Tiffany. Thank you so 154 00:09:44,480 --> 00:09:50,040 Speaker 2: very much. Tiffany Shao, portfolio manager at Matthew's International Capital Management, 155 00:09:50,120 --> 00:09:53,199 Speaker 2: joining from San Francisco here on the Daybreak Asia podcast. 156 00:10:00,120 --> 00:10:02,959 Speaker 2: Welcome back to the Daybreak Asia Podcast. I'm Dog Krisner. 157 00:10:03,360 --> 00:10:06,800 Speaker 2: The American economy expanded in the third quarter at the 158 00:10:06,840 --> 00:10:10,000 Speaker 2: fastest pace in two years. We're talking about GDP at 159 00:10:10,040 --> 00:10:13,560 Speaker 2: an annual growth rate of four point three percent. Now, 160 00:10:13,600 --> 00:10:16,560 Speaker 2: this reading seems to have dampened some bets on further 161 00:10:16,640 --> 00:10:18,679 Speaker 2: rate cuts, at least in the near term. Right now, 162 00:10:18,800 --> 00:10:22,000 Speaker 2: money markets see less than a twenty percent chance of 163 00:10:22,040 --> 00:10:24,760 Speaker 2: a FED rate cut in January. For a closer look, 164 00:10:24,760 --> 00:10:28,319 Speaker 2: I'm joined now by Chris Campitsis. He is managing partner 165 00:10:28,360 --> 00:10:31,480 Speaker 2: at Barnum Financial Group. Chris thank you for joining us. 166 00:10:31,760 --> 00:10:34,559 Speaker 2: How do you make a case for FED rate cuts 167 00:10:34,559 --> 00:10:37,439 Speaker 2: when you have a GDP print of four point three percent. 168 00:10:39,200 --> 00:10:42,640 Speaker 1: It's a challenge to make such a case. I don't 169 00:10:42,640 --> 00:10:47,760 Speaker 1: see it realistically being on the table. As you mentioned, 170 00:10:48,280 --> 00:10:52,559 Speaker 1: predictions are saying a less than twenty percent chance. It 171 00:10:52,600 --> 00:10:59,280 Speaker 1: would be extremely accommodative and potentially inflationary to cut further 172 00:10:59,360 --> 00:11:01,760 Speaker 1: with that type of unexpected GDP growth. 173 00:11:01,920 --> 00:11:04,480 Speaker 2: And yet at the same time, today we have President 174 00:11:04,520 --> 00:11:07,440 Speaker 2: Trump in a post on social media saying that he 175 00:11:07,640 --> 00:11:10,720 Speaker 2: expects his FED share to lower rates even if the 176 00:11:10,760 --> 00:11:14,120 Speaker 2: economy and the markets are doing well, and anyone who 177 00:11:14,200 --> 00:11:18,320 Speaker 2: disagrees with the President will never be FED chairman. Does 178 00:11:18,360 --> 00:11:20,840 Speaker 2: that create a bit of risk going forward? Just the 179 00:11:20,880 --> 00:11:23,839 Speaker 2: way in which the President is framing the discussion. 180 00:11:24,880 --> 00:11:28,080 Speaker 1: The FED needs to maintain its independence, and I think 181 00:11:28,160 --> 00:11:32,000 Speaker 1: most FED officials will will tell you that that's job one. 182 00:11:32,600 --> 00:11:36,800 Speaker 1: And definitely any influence from any presidents on either side 183 00:11:36,800 --> 00:11:39,120 Speaker 1: of the aisle, and we do have a long history 184 00:11:39,640 --> 00:11:43,840 Speaker 1: of presidents who do try to influence the FED. It 185 00:11:43,920 --> 00:11:47,920 Speaker 1: doesn't it doesn't make for great outcome. So you know, 186 00:11:48,160 --> 00:11:51,200 Speaker 1: to your point, if I'm applying for the job, I 187 00:11:51,240 --> 00:11:53,800 Speaker 1: don't want to be disagreeing with the president right now, 188 00:11:54,000 --> 00:11:58,280 Speaker 1: but it's a risky proposition to be cutting rates further. 189 00:11:58,320 --> 00:12:00,880 Speaker 2: Here we did have one data. I guess you could 190 00:12:00,920 --> 00:12:03,840 Speaker 2: make the case that would argue for a cut in 191 00:12:03,840 --> 00:12:07,840 Speaker 2: interest rates. Consumer confidence in the month of December dropping 192 00:12:07,880 --> 00:12:11,400 Speaker 2: for a fifth consecutive month. We've talked a lot about 193 00:12:11,400 --> 00:12:14,760 Speaker 2: this case shaped economy. Is that really what we're trying 194 00:12:14,800 --> 00:12:17,600 Speaker 2: to kind of wrap our arms around that we essentially 195 00:12:17,640 --> 00:12:19,360 Speaker 2: have a bifurcated situation. 196 00:12:20,559 --> 00:12:23,720 Speaker 1: It most certainly is you know, the economy and effect 197 00:12:23,800 --> 00:12:28,120 Speaker 1: becomes a tale of two cities, and you have what's 198 00:12:28,200 --> 00:12:33,319 Speaker 1: very interesting is increased with the latest labor numbers, increased 199 00:12:33,360 --> 00:12:37,400 Speaker 1: participation in the labor market, which it caused the unemployment 200 00:12:37,520 --> 00:12:41,319 Speaker 1: rate to go up. However, I think that is actually 201 00:12:41,960 --> 00:12:45,160 Speaker 1: a good sign. We're seeing more people looking to return 202 00:12:45,240 --> 00:12:48,520 Speaker 1: to work, looking to get employed, and I think that's 203 00:12:48,640 --> 00:12:53,440 Speaker 1: really important. Consumer confidence historically has bit of a has 204 00:12:53,480 --> 00:12:57,839 Speaker 1: been a bit of a contrarian indicator. When it goes low, 205 00:12:59,080 --> 00:13:02,600 Speaker 1: you tend to see strong economic numbers in the months 206 00:13:02,640 --> 00:13:08,760 Speaker 1: to follow. So I'm actually not completely concerned about that reading. 207 00:13:09,200 --> 00:13:11,880 Speaker 2: If you look at what happened today in the precious 208 00:13:11,920 --> 00:13:14,880 Speaker 2: metals market, we had gold and silver prices rising to 209 00:13:15,520 --> 00:13:18,280 Speaker 2: fresh all time highs. A lot of this seems to 210 00:13:18,320 --> 00:13:20,959 Speaker 2: be tied to the narrative on more rate cuts from 211 00:13:20,960 --> 00:13:24,200 Speaker 2: the Fed. It looks as though the precious metals market 212 00:13:24,240 --> 00:13:27,079 Speaker 2: is a little concerned about inflation. Is that one way 213 00:13:27,200 --> 00:13:28,240 Speaker 2: in which to read this. 214 00:13:30,040 --> 00:13:32,600 Speaker 1: I think you can view precious metals as in essence 215 00:13:32,640 --> 00:13:36,480 Speaker 1: of potential Canarian the coal mine. It's telling you that, yes, 216 00:13:36,600 --> 00:13:41,080 Speaker 1: there's concern around inflation, and there's concern around the economy 217 00:13:41,120 --> 00:13:44,240 Speaker 1: that is starting to build in the months and quarters ahead. 218 00:13:45,120 --> 00:13:47,640 Speaker 2: Give me some specifics. What are you looking at right now? 219 00:13:47,960 --> 00:13:49,680 Speaker 2: In order to make that conclusion. 220 00:13:50,200 --> 00:13:55,400 Speaker 1: We have a situation where the consumer has been extremely resilient. 221 00:13:55,640 --> 00:13:58,640 Speaker 1: It's spending. I think consumer spending was up three point 222 00:13:58,679 --> 00:14:04,439 Speaker 1: five percent, Business investment relatively strong, up about two point 223 00:14:04,920 --> 00:14:09,040 Speaker 1: eight percent, and corporate profits have been strong. So that's 224 00:14:09,960 --> 00:14:14,080 Speaker 1: the book case. That's the thinking that despite tariffs, despite 225 00:14:14,720 --> 00:14:20,640 Speaker 1: concerns around stock valuations, despite concerns around unemployment, the market 226 00:14:20,680 --> 00:14:24,440 Speaker 1: and the underlying economy are healthy. On the flip side 227 00:14:24,480 --> 00:14:30,080 Speaker 1: of that coin, you're seeing a situation where unemployment is 228 00:14:30,240 --> 00:14:36,680 Speaker 1: ticking up. We're seeing that bifurcation starting to occur in 229 00:14:36,720 --> 00:14:39,960 Speaker 1: the economy. I think the retail data that comes out 230 00:14:39,960 --> 00:14:43,120 Speaker 1: this holiday season is going to be very, very critical 231 00:14:43,600 --> 00:14:47,200 Speaker 1: as to just how resilient the consumer is on a 232 00:14:47,240 --> 00:14:50,640 Speaker 1: go forward basis as we enter into twenty twenty six, 233 00:14:51,440 --> 00:14:55,520 Speaker 1: and then ultimately we have to pay close attention to 234 00:14:55,560 --> 00:14:58,760 Speaker 1: what's happening with inflation, because on the bottom end of 235 00:14:58,760 --> 00:15:03,120 Speaker 1: that bifurcated economy, what you're seeing is, you know, consumers 236 00:15:03,160 --> 00:15:06,160 Speaker 1: are telling us things are just getting two expensive. Debt 237 00:15:06,280 --> 00:15:10,000 Speaker 1: levels are increasing, and there's a lot of concern around 238 00:15:10,040 --> 00:15:10,560 Speaker 1: that as well. 239 00:15:10,880 --> 00:15:13,360 Speaker 2: So everything that you believe right now in terms of 240 00:15:13,400 --> 00:15:16,680 Speaker 2: what you've just kind of captured there, how is that 241 00:15:16,800 --> 00:15:20,800 Speaker 2: leading you to create a strategy for markets in twenty 242 00:15:20,840 --> 00:15:21,440 Speaker 2: twenty six. 243 00:15:23,000 --> 00:15:27,960 Speaker 1: We're taking a Barbelle approach because we understand that ultimately 244 00:15:29,080 --> 00:15:35,640 Speaker 1: technology artificial intelligence that's going to be tremendously expansive, but 245 00:15:35,880 --> 00:15:40,640 Speaker 1: most certainly not in a straight line. We anticipate that sector, 246 00:15:40,680 --> 00:15:43,960 Speaker 1: which is obviously driving the top of the market, to 247 00:15:44,040 --> 00:15:48,840 Speaker 1: be more volatile than ever as more and more investors 248 00:15:48,960 --> 00:15:52,080 Speaker 1: are looking for a reason to sell rather than a 249 00:15:52,160 --> 00:15:55,040 Speaker 1: reason to buy. And you see that with the last 250 00:15:55,080 --> 00:16:00,680 Speaker 1: couple set of earnings on the you know each where 251 00:16:01,440 --> 00:16:07,080 Speaker 1: stocks have reacted really negatively despite really positive earnings reports 252 00:16:07,440 --> 00:16:10,480 Speaker 1: out of these tech companies. On the flip side of 253 00:16:10,520 --> 00:16:14,800 Speaker 1: the coin, you're seeing some increase to the breadth of 254 00:16:14,920 --> 00:16:17,960 Speaker 1: the overall market where sectors that have been out of 255 00:16:18,000 --> 00:16:22,760 Speaker 1: favor for a really long time, healthcare, consumer staples, they're 256 00:16:23,000 --> 00:16:26,640 Speaker 1: starting to show signs of strength and begin to show 257 00:16:26,680 --> 00:16:31,560 Speaker 1: some momentum. So we want to play both value, still 258 00:16:31,600 --> 00:16:34,600 Speaker 1: participate in growth, but not quite as much in terms 259 00:16:34,600 --> 00:16:38,480 Speaker 1: of the overall portfolio allocation as in twenty twenty five, 260 00:16:39,160 --> 00:16:41,280 Speaker 1: and we want to have some dry powder to be 261 00:16:41,360 --> 00:16:45,000 Speaker 1: able to buy those dips because there will certainly be dips. 262 00:16:45,040 --> 00:16:47,160 Speaker 1: We know that going in There's never been a year 263 00:16:47,200 --> 00:16:51,040 Speaker 1: where there hasn't been ups and downs, and so cash 264 00:16:51,080 --> 00:16:54,760 Speaker 1: on the sidelines is critical, and we're seeing that a lot. 265 00:16:54,960 --> 00:16:59,480 Speaker 1: Over these last couple days. There's been an increase in 266 00:16:59,560 --> 00:17:03,720 Speaker 1: tax us harvesting in stocks that have underperformed this year 267 00:17:03,800 --> 00:17:08,439 Speaker 1: being sold and and we're seeing cash on the sidelines 268 00:17:08,480 --> 00:17:10,640 Speaker 1: increasing a little bit. I think that's a wise move 269 00:17:10,680 --> 00:17:11,719 Speaker 1: as we head into the new year. 270 00:17:11,920 --> 00:17:16,800 Speaker 2: What about increasing your exposure to markets offshore, particularly in Asia. 271 00:17:17,320 --> 00:17:19,240 Speaker 2: Does that seem to make sense at this point? 272 00:17:20,280 --> 00:17:23,600 Speaker 1: I like Asia absolutely. I also think there's a lot 273 00:17:23,640 --> 00:17:27,639 Speaker 1: to like with Europe. You know, when we think about Europe, 274 00:17:27,720 --> 00:17:32,600 Speaker 1: the valuations of their equity markets stocks are cheaper. Also, 275 00:17:32,640 --> 00:17:37,760 Speaker 1: they're more aggressively cutting rates. The governments there are spending 276 00:17:37,840 --> 00:17:41,119 Speaker 1: more as they feel like they can rely less on 277 00:17:41,680 --> 00:17:46,680 Speaker 1: the other global superpowers and the dollars weeker. So there's 278 00:17:46,720 --> 00:17:50,840 Speaker 1: a lot to like about international markets in general. In particular, 279 00:17:51,119 --> 00:17:52,440 Speaker 1: we like Europe quite a bit. 280 00:17:53,119 --> 00:17:56,200 Speaker 2: I'm wondering about opportunities in the bond market. If you're 281 00:17:56,240 --> 00:18:01,120 Speaker 2: somewhat defensive and you want to be part in some way, 282 00:18:01,600 --> 00:18:03,640 Speaker 2: is the bond market a good option right now? 283 00:18:04,440 --> 00:18:07,520 Speaker 1: If you believe ultimately that in twenty twenty six interest 284 00:18:07,640 --> 00:18:11,280 Speaker 1: rates are going to ultimately be lower rather than higher. 285 00:18:12,119 --> 00:18:15,080 Speaker 1: It tends to lead to say, hey, well, maybe parking 286 00:18:15,119 --> 00:18:18,240 Speaker 1: some money and bonds make sense. You want high credit, 287 00:18:18,320 --> 00:18:22,520 Speaker 1: quality government bonds. I don't think you want to be 288 00:18:22,640 --> 00:18:26,520 Speaker 1: taking tremendous amount of credit exposure here. We're starting to 289 00:18:26,520 --> 00:18:30,200 Speaker 1: see cracks in the private credit story as an example 290 00:18:30,280 --> 00:18:32,440 Speaker 1: of that, So high yield it is going to be 291 00:18:32,480 --> 00:18:37,240 Speaker 1: a little bit riskier, but quality, quality credit quality bonds 292 00:18:37,440 --> 00:18:41,480 Speaker 1: a potential increase to the allocation. That being said, the 293 00:18:41,640 --> 00:18:46,800 Speaker 1: idea of when stocks go down, bonds go up, that 294 00:18:46,880 --> 00:18:50,600 Speaker 1: equation is not quite as true as it used to 295 00:18:50,640 --> 00:18:53,760 Speaker 1: be historically, at least it hasn't been over the last decade. 296 00:18:54,080 --> 00:18:56,240 Speaker 1: So I'm not so sure that one is a certainty 297 00:18:56,280 --> 00:18:57,879 Speaker 1: when the other happens going forward. 298 00:18:57,920 --> 00:18:59,760 Speaker 2: Can you give me a call that you would make 299 00:18:59,840 --> 00:19:03,320 Speaker 2: for the new year that may be a little counterintuitive. 300 00:19:03,760 --> 00:19:05,840 Speaker 1: A call that I would make for the new year 301 00:19:05,920 --> 00:19:09,840 Speaker 1: that would be a little counterintuitive would be number one, 302 00:19:10,480 --> 00:19:15,160 Speaker 1: gold and precious metals may be a little bit overpriced here. 303 00:19:15,600 --> 00:19:20,280 Speaker 1: And number two, you might want to really consider taking 304 00:19:20,359 --> 00:19:23,760 Speaker 1: some of those tech profits off of the table, but 305 00:19:23,920 --> 00:19:26,920 Speaker 1: not being afraid to go back in when you see 306 00:19:26,960 --> 00:19:27,760 Speaker 1: prices adjust. 307 00:19:27,960 --> 00:19:29,920 Speaker 2: Chris will leave it there. Thank you so very much. 308 00:19:30,240 --> 00:19:35,040 Speaker 2: Chris Campittsis is managing partner at Barnum Financial Group. Joining 309 00:19:35,119 --> 00:19:39,159 Speaker 2: us here on the Daybreak Asia Podcast. Thanks for listening 310 00:19:39,240 --> 00:19:43,480 Speaker 2: to today's episode of the Bloomberg Daybreak Asia Edition podcast. 311 00:19:43,800 --> 00:19:46,919 Speaker 2: Each weekday, we look at the story shaping markets, finance, 312 00:19:47,280 --> 00:19:50,359 Speaker 2: and geopolitics in the Asia Pacific. You can find us 313 00:19:50,400 --> 00:19:54,560 Speaker 2: on Apple, Spotify, The Bloomberg Podcast YouTube channel or anywhere 314 00:19:54,600 --> 00:19:57,720 Speaker 2: else you listen. Join us again tomorrow for insight on 315 00:19:57,760 --> 00:20:01,880 Speaker 2: the market moves from Hong Kong to Singapore and Australia. 316 00:20:02,320 --> 00:20:04,800 Speaker 2: I'm Doug Prisoner and this is Bloomberg