1
00:00:00,040 --> 00:00:11,080
Speaker 1: Bloomberg Audio Studios, Podcasts, radio News. Welcome to the Daybreak

2
00:00:11,080 --> 00:00:14,920
Speaker 1: Asia podcast. I'm Doug Chrisner. The appetite for risk assets

3
00:00:14,960 --> 00:00:17,880
Speaker 1: has improved this morning in the Asia Pacific. A couple

4
00:00:17,960 --> 00:00:20,239
Speaker 1: of things at work here. First, we are told US

5
00:00:20,239 --> 00:00:23,880
Speaker 1: officials were holding early talks on whether to allow Nvidia

6
00:00:23,960 --> 00:00:27,120
Speaker 1: to sell its H two hundred AI chips to China.

7
00:00:27,800 --> 00:00:29,760
Speaker 1: And last Friday we heard from the head of the

8
00:00:29,800 --> 00:00:32,839
Speaker 1: New York Fed, John Williams, and he seemed to suggest

9
00:00:32,920 --> 00:00:37,159
Speaker 1: a near term rate cut remains a possibility. Let's take

10
00:00:37,159 --> 00:00:39,440
Speaker 1: a look at market action with our guest, Helen ju.

11
00:00:39,880 --> 00:00:43,320
Speaker 1: Helen is managing partner also the CIO of the Family

12
00:00:43,400 --> 00:00:47,280
Speaker 1: Office n F Trinity. Helen joins us from Hong Kong.

13
00:00:47,400 --> 00:00:49,199
Speaker 1: Thank you so much for making time to chat with me.

14
00:00:49,520 --> 00:00:52,960
Speaker 1: Let's begin by looking at this unwinding that we saw

15
00:00:53,080 --> 00:00:55,480
Speaker 1: last week of the AI trade, not just here in

16
00:00:55,520 --> 00:00:58,000
Speaker 1: the States, but in the APAC as well. I think

17
00:00:58,040 --> 00:01:01,080
Speaker 1: for all of last week the MSCIS Pacific Index was

18
00:01:01,160 --> 00:01:04,920
Speaker 1: down nearly four percent. How do you understand or make

19
00:01:05,080 --> 00:01:07,119
Speaker 1: sense of what we have been seeing.

20
00:01:08,760 --> 00:01:12,240
Speaker 2: Well, it's one big trade on a combined basis, because

21
00:01:12,280 --> 00:01:15,280
Speaker 2: it's a global ecosystem and value chain, right, so it's

22
00:01:15,319 --> 00:01:17,680
Speaker 2: not as surprise that the US and Asia would fall

23
00:01:17,760 --> 00:01:20,400
Speaker 2: in tandem or go up in tandem as well. What

24
00:01:20,440 --> 00:01:23,759
Speaker 2: we saw in the past few quarters is really, you know,

25
00:01:24,200 --> 00:01:29,640
Speaker 2: one after another, major capex hikes for AI companies in

26
00:01:29,720 --> 00:01:32,040
Speaker 2: terms of twenty twenty six and maybe even beyond in

27
00:01:32,120 --> 00:01:35,360
Speaker 2: terms of expectations. And also obviously in the private market

28
00:01:35,400 --> 00:01:39,119
Speaker 2: we saw huge valuation jumps for some of the leading companies.

29
00:01:39,120 --> 00:01:42,000
Speaker 2: So it was very much of virtuous feedback loop. So

30
00:01:42,280 --> 00:01:45,280
Speaker 2: as valuations went up, then companies that were in fear

31
00:01:45,360 --> 00:01:48,000
Speaker 2: of not being able to fund their capex or their

32
00:01:48,040 --> 00:01:51,000
Speaker 2: businesses got funded more easily, and so on and so forth,

33
00:01:51,080 --> 00:01:53,880
Speaker 2: so positively reinforcing. What happened I think in the last

34
00:01:53,920 --> 00:01:57,000
Speaker 2: couple of weeks is really a couple of things. One

35
00:01:57,080 --> 00:02:00,720
Speaker 2: is that we have some concerns about, you know, despite

36
00:02:00,760 --> 00:02:03,000
Speaker 2: the willingness to spend on AI, whether there is going

37
00:02:03,040 --> 00:02:05,280
Speaker 2: to be some supply side constraints. There is a lot

38
00:02:05,280 --> 00:02:08,800
Speaker 2: more talk now about power constraints, about labor constraints, about

39
00:02:09,280 --> 00:02:11,200
Speaker 2: core weaves, that they had to push back their capex

40
00:02:11,240 --> 00:02:13,720
Speaker 2: by a couple of quarters because of data center shell.

41
00:02:14,080 --> 00:02:16,240
Speaker 2: So some of this noise I think makes people concern

42
00:02:16,360 --> 00:02:19,200
Speaker 2: that maybe the spend and the progress and pace will

43
00:02:19,600 --> 00:02:23,400
Speaker 2: potentially miss versus what's already very very elevated expectations.

44
00:02:23,760 --> 00:02:26,799
Speaker 1: What about circular financing some of these deals, the way

45
00:02:26,840 --> 00:02:30,799
Speaker 1: that funding is being provided, and then there's the issue

46
00:02:30,840 --> 00:02:33,200
Speaker 1: of debt issuance when it comes to financing some of

47
00:02:33,200 --> 00:02:36,520
Speaker 1: the capecs. Are they together kind of troubling for you?

48
00:02:38,120 --> 00:02:40,640
Speaker 2: I think the fact that there's debt financing involved by

49
00:02:40,680 --> 00:02:43,840
Speaker 2: itself is not necessarily troubling, because there's usually a significant

50
00:02:43,880 --> 00:02:47,960
Speaker 2: amount of debt in any large infrastructural project. I think

51
00:02:48,040 --> 00:02:51,239
Speaker 2: what's more concerning to the overall market is that it's

52
00:02:51,280 --> 00:02:55,400
Speaker 2: basically company A investing into company B, company b's share

53
00:02:55,440 --> 00:02:58,120
Speaker 2: price going up, or company BE raising money in order

54
00:02:58,160 --> 00:03:01,400
Speaker 2: to buy products from company A. So that in itself

55
00:03:01,600 --> 00:03:04,880
Speaker 2: is what people find to be a little bit, you know, disconcerting.

56
00:03:05,280 --> 00:03:07,720
Speaker 2: But that said, you know, this is we're talking about

57
00:03:07,880 --> 00:03:12,200
Speaker 2: multi year projects and multi year investment and revenue. So

58
00:03:12,639 --> 00:03:15,280
Speaker 2: the risk of unraveling in the near term seems to

59
00:03:15,280 --> 00:03:18,400
Speaker 2: be relatively low, especially given that most of the CAPEC

60
00:03:18,440 --> 00:03:20,840
Speaker 2: spend in twenty twenty five and twenty twenty six by

61
00:03:20,840 --> 00:03:23,959
Speaker 2: the hyperscalers is not expected to have any meaningful cash

62
00:03:23,960 --> 00:03:27,320
Speaker 2: flow generation or major ROI. Basically, all those guys have

63
00:03:27,400 --> 00:03:30,400
Speaker 2: fully committed to the spend irrespective of near term ROI.

64
00:03:30,480 --> 00:03:32,880
Speaker 2: So it is an implicit you know, risk over the

65
00:03:32,919 --> 00:03:35,520
Speaker 2: medium to longer term, but not necessarily immediate.

66
00:03:35,720 --> 00:03:38,480
Speaker 1: So I want to try to understand adoption of AI,

67
00:03:38,640 --> 00:03:41,760
Speaker 1: maybe a little anecdotally. Can you give me a sense

68
00:03:41,800 --> 00:03:44,840
Speaker 1: of how your firm, NF Trinity is using AI?

69
00:03:46,120 --> 00:03:49,440
Speaker 2: Of course, I think we actually see that AI tools

70
00:03:49,440 --> 00:03:51,880
Speaker 2: are becoming more and more prevalent, and every month we

71
00:03:52,000 --> 00:03:55,720
Speaker 2: have new tools, you know, coming out. So for example,

72
00:03:55,840 --> 00:04:00,120
Speaker 2: now instead of downloading research reports one by one on

73
00:04:00,280 --> 00:04:03,160
Speaker 2: scanning them through with the naked eye looking for references

74
00:04:03,200 --> 00:04:05,040
Speaker 2: to the key points that we want, all we have

75
00:04:05,080 --> 00:04:07,640
Speaker 2: to do is go into some specific app and ask

76
00:04:07,760 --> 00:04:10,640
Speaker 2: it to search for us exactly what we're looking for,

77
00:04:11,080 --> 00:04:14,000
Speaker 2: and they will produce it for us and give us

78
00:04:14,040 --> 00:04:16,240
Speaker 2: links to the source so that we can click in

79
00:04:16,279 --> 00:04:20,600
Speaker 2: and follow through. So that would be one relatively rudimentary way.

80
00:04:20,800 --> 00:04:22,880
Speaker 2: Another way would be, you know, for example, if you

81
00:04:22,880 --> 00:04:26,359
Speaker 2: think about it, previously, we have loads of databases that

82
00:04:26,400 --> 00:04:29,760
Speaker 2: are all separate. Now actually we can take a lot

83
00:04:29,760 --> 00:04:31,800
Speaker 2: of the raw data and dump it into a large

84
00:04:31,839 --> 00:04:35,520
Speaker 2: language model and ask it to produce certain results and

85
00:04:35,600 --> 00:04:37,919
Speaker 2: search up specific things for us. So all of the

86
00:04:37,920 --> 00:04:41,480
Speaker 2: stuff is improving our efficiency by leaps and bounds, for sure.

87
00:04:41,839 --> 00:04:43,760
Speaker 1: I'd like to look at a little bit of the

88
00:04:43,880 --> 00:04:47,120
Speaker 1: rivalry when it comes to artificial intelligence between the US

89
00:04:47,160 --> 00:04:50,520
Speaker 1: and China. The Trump administration, we are told, is considering

90
00:04:50,560 --> 00:04:54,800
Speaker 1: some options to ease restrictions on exports of certain chips

91
00:04:54,839 --> 00:04:57,640
Speaker 1: to the Chinese market, namely those from Nvidia, and I

92
00:04:57,680 --> 00:05:00,560
Speaker 1: think the H two hundred chip is really one of

93
00:05:00,880 --> 00:05:03,440
Speaker 1: the focal points here. We are told that the US

94
00:05:03,480 --> 00:05:06,280
Speaker 1: officials have had some early discussions as to whether or

95
00:05:06,320 --> 00:05:08,600
Speaker 1: not to allow these H two hundred chips into the

96
00:05:08,680 --> 00:05:11,800
Speaker 1: Chinese market. How do you view this rivalry right now?

97
00:05:11,800 --> 00:05:14,240
Speaker 1: And anecdotally, maybe you can give me a sense of

98
00:05:14,680 --> 00:05:18,200
Speaker 1: what you're hearing from companies on the mainland and how

99
00:05:18,279 --> 00:05:21,320
Speaker 1: well they are progressing to kind of meet what is

100
00:05:21,760 --> 00:05:24,880
Speaker 1: up until this point been an advantage to the US.

101
00:05:25,120 --> 00:05:30,359
Speaker 2: Based on our more recent research, certainly the mainland semi

102
00:05:30,480 --> 00:05:34,240
Speaker 2: and foundry space remains lagging versus the US by quite

103
00:05:34,240 --> 00:05:36,680
Speaker 2: a bit, so that is why there's still some demand

104
00:05:36,720 --> 00:05:39,920
Speaker 2: for the Age twenty, which is a quite outdated model

105
00:05:40,000 --> 00:05:43,000
Speaker 2: of Nvidia that has been was banned for a while

106
00:05:43,000 --> 00:05:46,160
Speaker 2: but is now allowed for export to China. The H

107
00:05:46,360 --> 00:05:49,200
Speaker 2: one hundred is what was previously banned, so if the

108
00:05:49,400 --> 00:05:52,480
Speaker 2: H two hundred is actually also allowed, that would actually

109
00:05:52,480 --> 00:05:56,479
Speaker 2: be a huge positive surprise for China. I don't actually

110
00:05:56,520 --> 00:05:59,640
Speaker 2: agree that by sending these chips to China that is

111
00:05:59,680 --> 00:06:03,320
Speaker 2: going to meaningfully stalled China's progress. I actually think that

112
00:06:03,440 --> 00:06:06,360
Speaker 2: China is all in into semi irrespective and it will

113
00:06:06,400 --> 00:06:09,640
Speaker 2: try its very best to make progress on the most

114
00:06:09,640 --> 00:06:12,479
Speaker 2: advanced node, whether they have the H two hundred, the

115
00:06:12,560 --> 00:06:15,480
Speaker 2: H one hundred or not. But certainly having more chips

116
00:06:15,520 --> 00:06:17,760
Speaker 2: for training and inference in the near term is going

117
00:06:17,800 --> 00:06:20,479
Speaker 2: to be very helpful to China. AI also helpful to

118
00:06:20,560 --> 00:06:23,960
Speaker 2: Nvidia and the US supply chain, although not necessarily aligned

119
00:06:23,960 --> 00:06:27,680
Speaker 2: with US's interests over the medium to longer term.

120
00:06:28,080 --> 00:06:31,159
Speaker 1: So we're approaching the holiday shopping season. We talk a

121
00:06:31,200 --> 00:06:33,359
Speaker 1: lot in the States about the wealth effect and the

122
00:06:33,400 --> 00:06:37,240
Speaker 1: degree to which a higher equity market has allowed certain

123
00:06:37,279 --> 00:06:41,120
Speaker 1: consumers to tap in to their gains and fund more

124
00:06:41,120 --> 00:06:44,000
Speaker 1: in the way of consumer spending. Is there a lot

125
00:06:44,080 --> 00:06:45,360
Speaker 1: in the way of the wealth effect.

126
00:06:45,400 --> 00:06:50,360
Speaker 2: In the Asia Pacific, I think there is a certain extent.

127
00:06:50,400 --> 00:06:52,360
Speaker 2: I think in Hong Kong, for example, you can feel

128
00:06:52,360 --> 00:06:55,680
Speaker 2: it more than a year ago, for sure. I think

129
00:06:55,720 --> 00:06:59,200
Speaker 2: elsewhere it really depends, right, So certain markets like Taiwan

130
00:06:59,279 --> 00:07:03,160
Speaker 2: have done better. In China, I would say it's more

131
00:07:03,440 --> 00:07:05,600
Speaker 2: very much the high end has helped a little bit

132
00:07:05,640 --> 00:07:08,839
Speaker 2: in terms of the stock market rally, although the continuous

133
00:07:08,880 --> 00:07:12,320
Speaker 2: decline in property prices has certainly offset that to some extent.

134
00:07:12,600 --> 00:07:14,680
Speaker 2: In the US is very much a K shaped consumer,

135
00:07:14,760 --> 00:07:17,000
Speaker 2: So the high end guys are doing relatively well, but

136
00:07:17,040 --> 00:07:20,360
Speaker 2: the low end consumer is definitely being squeezed meaningfully by

137
00:07:20,400 --> 00:07:23,120
Speaker 2: the inflationary pressures of the past couple of years.

138
00:07:23,200 --> 00:07:25,680
Speaker 1: What about this prevalence of by the dip that whole

139
00:07:25,720 --> 00:07:29,560
Speaker 1: mentality is that primarily a retail phenomenon as you understand it.

140
00:07:30,560 --> 00:07:34,600
Speaker 2: I think the US market has become increasingly retail driven,

141
00:07:35,040 --> 00:07:38,040
Speaker 2: and so yes, by the dip has actually for sure

142
00:07:38,240 --> 00:07:40,680
Speaker 2: been kind of the key moo in the last three

143
00:07:40,680 --> 00:07:45,240
Speaker 2: to five years. I would say that it's you know,

144
00:07:45,320 --> 00:07:48,640
Speaker 2: some market neutral hedge funds as well as US retail

145
00:07:49,280 --> 00:07:52,080
Speaker 2: that have been the key pricemakers in the US market.

146
00:07:52,720 --> 00:07:54,200
Speaker 2: You know, in the recent period.

147
00:07:54,320 --> 00:07:57,200
Speaker 1: Are you seeing evidence at all that there is leverage

148
00:07:57,200 --> 00:07:59,480
Speaker 1: that has been built up in the system that maybe

149
00:07:59,520 --> 00:08:00,120
Speaker 1: a little.

150
00:08:01,320 --> 00:08:04,320
Speaker 2: Of course, there's leverage in the system. Clearly there has

151
00:08:04,360 --> 00:08:09,080
Speaker 2: been a period of very significant quantitative easying post COVID

152
00:08:09,160 --> 00:08:12,720
Speaker 2: as well as fiscal stimulus. UH, the various parts of

153
00:08:12,760 --> 00:08:16,080
Speaker 2: the credit market have been booming, for example, private credit

154
00:08:16,200 --> 00:08:20,040
Speaker 2: et cetera. UH. The massive supply of credit has resulted

155
00:08:20,120 --> 00:08:25,160
Speaker 2: in very thin credit spreads versus history, and that's you know,

156
00:08:25,240 --> 00:08:28,320
Speaker 2: that makes credit probably a little bit less attractive versus

157
00:08:28,520 --> 00:08:31,120
Speaker 2: some other periods, although the base rate is still relatively

158
00:08:31,160 --> 00:08:34,040
Speaker 2: high and could actually come off a bit. I think

159
00:08:34,080 --> 00:08:36,200
Speaker 2: the key thing that one needs to watch out for

160
00:08:36,400 --> 00:08:40,480
Speaker 2: is really whether there is any you know, major issue

161
00:08:40,520 --> 00:08:43,199
Speaker 2: that results in a lot of stress on the private

162
00:08:43,240 --> 00:08:47,280
Speaker 2: credit side, especially given that many private credit funds may

163
00:08:47,280 --> 00:08:52,040
Speaker 2: have outsized exposures to sectors like software, some of which

164
00:08:52,160 --> 00:08:55,280
Speaker 2: may have you know, disruption over the medium term from

165
00:08:55,360 --> 00:08:58,679
Speaker 2: AI related progress. So that's something to keep a very

166
00:08:58,679 --> 00:08:59,400
Speaker 2: close eye on you.

167
00:08:59,520 --> 00:09:02,280
Speaker 1: When we talk about the appetite for risk, a lot

168
00:09:02,320 --> 00:09:04,680
Speaker 1: of people like to focus on the cryptocurrency market, and

169
00:09:04,720 --> 00:09:09,120
Speaker 1: then we've seen a pretty dramatic downdraft in the bitcoin

170
00:09:09,280 --> 00:09:11,600
Speaker 1: just to mention one, how do you feel about that

171
00:09:11,640 --> 00:09:14,360
Speaker 1: as an indicator for the appetite for risk assets?

172
00:09:14,679 --> 00:09:20,120
Speaker 2: Crypto is indeed a high beta indicator for risk assets.

173
00:09:20,800 --> 00:09:23,000
Speaker 2: People say that it's for hedging, but I think it's

174
00:09:23,080 --> 00:09:26,600
Speaker 2: much more for just basically risk on risk off market

175
00:09:26,679 --> 00:09:30,319
Speaker 2: beta in essence. So it is an indication, and it's

176
00:09:30,320 --> 00:09:34,480
Speaker 2: correlated with AI trade unraveling recently, right, So I think,

177
00:09:34,640 --> 00:09:37,480
Speaker 2: you know, we'll continue to see ups and downs in

178
00:09:37,520 --> 00:09:41,360
Speaker 2: crypto in alignment with overall market and liquidity sentiment.

179
00:09:41,880 --> 00:09:45,199
Speaker 1: Where you focus these days as you look for opportunity, well,

180
00:09:45,240 --> 00:09:45,520
Speaker 1: we have.

181
00:09:45,480 --> 00:09:48,000
Speaker 2: To be focused everywhere. The most important things to watch

182
00:09:48,080 --> 00:09:51,400
Speaker 2: out for are really whether you know there is an

183
00:09:51,440 --> 00:09:55,480
Speaker 2: AI bubble or not, and whether there's a private credit bubble.

184
00:09:55,760 --> 00:09:58,160
Speaker 2: We think that neither of which is likely to have

185
00:09:58,240 --> 00:10:02,040
Speaker 2: a significant you know, bursts in the short term at least,

186
00:10:02,200 --> 00:10:04,080
Speaker 2: but that's something to keep a very close eye on.

187
00:10:04,320 --> 00:10:06,800
Speaker 2: The dollar has rebounded a little bit versus the bottom

188
00:10:06,840 --> 00:10:09,000
Speaker 2: a couple of months ago. We still think that there

189
00:10:09,040 --> 00:10:13,000
Speaker 2: are some opportunities in some of the emerging markets selectively,

190
00:10:13,360 --> 00:10:16,800
Speaker 2: like we like Korea, you know, even excluding the tech sector,

191
00:10:17,280 --> 00:10:20,199
Speaker 2: which has done phenomenally well. We like parts of Taiwan

192
00:10:20,240 --> 00:10:22,600
Speaker 2: where the Ai trade is, you know, lagging versus their

193
00:10:22,640 --> 00:10:26,000
Speaker 2: counterparts in the US, we still like certain parts of

194
00:10:26,120 --> 00:10:29,000
Speaker 2: Latin et cetera. For China, we would be a bit

195
00:10:29,040 --> 00:10:32,480
Speaker 2: more selective, given the market has rallied quite significantly this

196
00:10:32,559 --> 00:10:36,040
Speaker 2: year and the macroeconomic momentum has been slowing.

197
00:10:35,760 --> 00:10:38,640
Speaker 1: And given the level of volatility that we have seen lately,

198
00:10:38,679 --> 00:10:42,080
Speaker 1: I'm curious about how you're putting new cash to work.

199
00:10:42,120 --> 00:10:44,240
Speaker 1: Are you holding on to a little bit of dry

200
00:10:44,320 --> 00:10:46,720
Speaker 1: powder right now looking for better entry points.

201
00:10:48,040 --> 00:10:51,080
Speaker 2: I think most people are waiting for better entry points

202
00:10:51,120 --> 00:10:54,840
Speaker 2: at the moment. But of course keep in mind that,

203
00:10:54,960 --> 00:10:57,440
Speaker 2: you know, there are other things that one can put

204
00:10:57,640 --> 00:11:00,480
Speaker 2: money into that are not as risky, you know, for example,

205
00:11:00,559 --> 00:11:03,400
Speaker 2: on the fix income side, or our rates, or other

206
00:11:03,440 --> 00:11:05,760
Speaker 2: aspects not necessarily just equities.

207
00:11:05,880 --> 00:11:08,040
Speaker 1: Okay, we'll leave it there, Helen, Thank you so very much.

208
00:11:08,200 --> 00:11:11,880
Speaker 1: Helen Ju managing partner and CIO at the Family Office

209
00:11:11,960 --> 00:11:14,520
Speaker 1: and f Trinity in Hong Kong, joining us here on

210
00:11:14,520 --> 00:11:24,800
Speaker 1: the Daybreak Asia podcast. Welcome back to the Daybreak Asia Podcast.

211
00:11:24,880 --> 00:11:28,400
Speaker 1: I'm deg Krisner. It is a holiday shortened week. Stateside,

212
00:11:28,480 --> 00:11:32,480
Speaker 1: markets will be closed Thursday for the Thanksgiving holiday and

213
00:11:32,640 --> 00:11:35,560
Speaker 1: the next day Black Friday, you know well as the

214
00:11:35,559 --> 00:11:38,480
Speaker 1: biggest day of the year for retailers. Also in the

215
00:11:38,520 --> 00:11:40,720
Speaker 1: week ahead, the government will be releasing more of that

216
00:11:40,800 --> 00:11:44,080
Speaker 1: economic data that had been delayed by the shutdown, So

217
00:11:44,120 --> 00:11:47,320
Speaker 1: we're looking for September numbers on retail sales along with

218
00:11:47,360 --> 00:11:52,000
Speaker 1: producer prices and durable goods orders. And then on Wednesday,

219
00:11:52,000 --> 00:11:55,840
Speaker 1: the Fed will be releasing its Beije book survey for

220
00:11:55,920 --> 00:11:58,480
Speaker 1: a closer look at what the week ahead means for markets.

221
00:11:58,520 --> 00:12:02,439
Speaker 1: I'm joined by Grace Blackner of Sharp Investments. Grace is

222
00:12:02,480 --> 00:12:05,280
Speaker 1: on the investment team at Sharf. Thank you for making

223
00:12:05,280 --> 00:12:07,640
Speaker 1: time to chat with me. If we can begin, Grace

224
00:12:07,679 --> 00:12:10,600
Speaker 1: by looking at this consumer I was struck by the

225
00:12:10,800 --> 00:12:14,760
Speaker 1: erosion in consumer centiment last week reported by the University

226
00:12:14,760 --> 00:12:17,920
Speaker 1: of Michigan. What is your sense in terms of how

227
00:12:17,960 --> 00:12:20,040
Speaker 1: well the American consumer is holding up?

228
00:12:20,559 --> 00:12:23,240
Speaker 3: Yeah, I think we are facing some near term headwinds. Right,

229
00:12:23,240 --> 00:12:26,959
Speaker 3: We're going into the holiday season with low consumer sentiment

230
00:12:27,040 --> 00:12:30,560
Speaker 3: that you touched on, but ultimately we could see some

231
00:12:30,679 --> 00:12:34,360
Speaker 3: of that reverse come the beginning of next year. We'll

232
00:12:34,360 --> 00:12:37,880
Speaker 3: be getting tax rebates for consumers. But ultimately, when you

233
00:12:37,960 --> 00:12:42,319
Speaker 3: think deeply of what the consumer is looking like right now,

234
00:12:42,520 --> 00:12:44,840
Speaker 3: we have lowing consumers that have really been in a

235
00:12:44,880 --> 00:12:48,000
Speaker 3: recession for a number of months. We have Gen Z

236
00:12:48,080 --> 00:12:51,360
Speaker 3: and millennials within unemployment levels in the high single digits.

237
00:12:51,480 --> 00:12:54,080
Speaker 3: So it's not a strong consumer picture, but in the

238
00:12:54,080 --> 00:12:56,480
Speaker 3: near term we could see some benefits beginning of next

239
00:12:56,559 --> 00:12:57,800
Speaker 3: year when we get tax refunds.

240
00:12:57,960 --> 00:13:00,360
Speaker 1: So we talk a lot about the wealth of fact

241
00:13:00,480 --> 00:13:04,480
Speaker 1: that the equity market has produced and how maybe higher

242
00:13:04,679 --> 00:13:08,480
Speaker 1: income earners or those that have more direct exposure to

243
00:13:08,520 --> 00:13:12,040
Speaker 1: the equity market have been able to spend more than

244
00:13:12,080 --> 00:13:14,880
Speaker 1: those who don't have exposure to the equity space. Do

245
00:13:14,920 --> 00:13:17,160
Speaker 1: you think that's an important distinction that we need to

246
00:13:17,160 --> 00:13:17,880
Speaker 1: tease out a bit?

247
00:13:18,480 --> 00:13:21,360
Speaker 3: Absolutely. The k economy has been a key factor in

248
00:13:21,400 --> 00:13:24,880
Speaker 3: the markets, and we've seen that with companies like Walmart

249
00:13:24,960 --> 00:13:27,839
Speaker 3: doing extremely well able to gain share. This is generally

250
00:13:27,880 --> 00:13:30,160
Speaker 3: in a market where they would do really well right

251
00:13:30,679 --> 00:13:32,840
Speaker 3: when that lower income consumer is hurting and even the

252
00:13:32,840 --> 00:13:36,240
Speaker 3: middle income consumer is not feeling extremely strong. The concern

253
00:13:36,320 --> 00:13:39,760
Speaker 3: is when you have equity markets behaving in a volatile manner,

254
00:13:39,800 --> 00:13:42,840
Speaker 3: as we've seen over the past couple of weeks, you

255
00:13:42,960 --> 00:13:46,040
Speaker 3: start to see that higher income consumer who's been feeling

256
00:13:46,200 --> 00:13:49,720
Speaker 3: very strongly start to feel a little bit more concern

257
00:13:49,840 --> 00:13:50,960
Speaker 3: and have a little more on ease.

258
00:13:51,400 --> 00:13:53,880
Speaker 1: We have seen a lot of volatility, are absolutely right

259
00:13:53,960 --> 00:13:57,600
Speaker 1: to particularly as it's related to the AI trade. Where

260
00:13:57,600 --> 00:14:00,440
Speaker 1: are you right now with this theme of artificial intel leigence.

261
00:14:01,080 --> 00:14:04,160
Speaker 3: Yeah, it's an interesting point that we're at right now.

262
00:14:04,760 --> 00:14:07,280
Speaker 3: What you saw last week with the launch of Gemini

263
00:14:07,360 --> 00:14:10,000
Speaker 3: three showed us a number of things, the first being

264
00:14:10,040 --> 00:14:13,240
Speaker 3: that open AI is no longer kind of the end

265
00:14:13,320 --> 00:14:17,960
Speaker 3: all be all in terms of functionality or accessibility for

266
00:14:18,160 --> 00:14:21,760
Speaker 3: these AI models, and that training can be done at

267
00:14:21,760 --> 00:14:24,920
Speaker 3: the highest levels without Nvidia GPUs because gem and I

268
00:14:24,960 --> 00:14:29,080
Speaker 3: didn't use GPUs for training the Gemini three model. So

269
00:14:29,400 --> 00:14:33,600
Speaker 3: in the end, in the stocks reflected what you saw

270
00:14:33,960 --> 00:14:36,920
Speaker 3: was Google performing extremely well, in other AI companies not

271
00:14:37,040 --> 00:14:38,960
Speaker 3: holding up as well over the course of the week,

272
00:14:39,360 --> 00:14:41,880
Speaker 3: and so we may be entering an era where not

273
00:14:41,960 --> 00:14:45,360
Speaker 3: all AI related companies are moving together anymore. And this

274
00:14:45,400 --> 00:14:48,480
Speaker 3: is going to be extremely important when you think about

275
00:14:48,800 --> 00:14:50,280
Speaker 3: how this trend evolves.

276
00:14:50,560 --> 00:14:52,800
Speaker 1: So what are you inclined to do in a situation

277
00:14:52,960 --> 00:14:54,440
Speaker 1: like that do you want to take some money off

278
00:14:54,480 --> 00:14:57,800
Speaker 1: the table, particularly in some of those high flying names

279
00:14:57,800 --> 00:14:59,160
Speaker 1: that have done remarkably well.

280
00:14:59,720 --> 00:15:03,600
Speaker 3: Yeah, it's interesting because the market has been so focused

281
00:15:03,600 --> 00:15:06,160
Speaker 3: on AI and it's kind of been just you know,

282
00:15:06,520 --> 00:15:09,880
Speaker 3: by now, ask questions later in terms of where the

283
00:15:09,880 --> 00:15:12,400
Speaker 3: market eventually evolves and who ends up having the most

284
00:15:12,400 --> 00:15:15,880
Speaker 3: competitive models, most competitive chips, et cetera. So what we've

285
00:15:15,960 --> 00:15:19,520
Speaker 3: been doing is looking at, Okay, are there quality companies

286
00:15:19,600 --> 00:15:22,400
Speaker 3: outside of the AI space where we don't have to

287
00:15:22,400 --> 00:15:25,120
Speaker 3: make a bet on these technologies that are still very

288
00:15:25,120 --> 00:15:27,520
Speaker 3: early days. It's kind of like betting on who's going

289
00:15:27,560 --> 00:15:30,080
Speaker 3: to be the winner in the Internet in nineteen ninety nine, right,

290
00:15:30,080 --> 00:15:33,600
Speaker 3: you probably would have said Yahoo, AOL, Right, companies that

291
00:15:33,720 --> 00:15:36,600
Speaker 3: ended up not being the strongest in the space. And

292
00:15:36,680 --> 00:15:38,880
Speaker 3: so we're looking for what we look for like steady

293
00:15:38,960 --> 00:15:41,280
Speaker 3: eddies is what we call them. And these are companies

294
00:15:41,280 --> 00:15:46,320
Speaker 3: that are outside of the AI speculation largely and they

295
00:15:46,560 --> 00:15:50,400
Speaker 3: have performed really well in past recessions. They're in sectors

296
00:15:50,480 --> 00:15:53,200
Speaker 3: like healthcare. Healthcare is training at the most attractive levels

297
00:15:53,240 --> 00:15:55,720
Speaker 3: that we've seen in seventy years. It's seen a little

298
00:15:55,760 --> 00:15:57,440
Speaker 3: bit of a bid over the past month or so,

299
00:15:58,040 --> 00:16:01,480
Speaker 3: but largely it's been forgotten and really high quality companies

300
00:16:01,520 --> 00:16:04,360
Speaker 3: that are being missed in this AI ferber So we

301
00:16:04,360 --> 00:16:06,640
Speaker 3: see it as an opportunity to buy some of those

302
00:16:06,680 --> 00:16:07,360
Speaker 3: study at ease.

303
00:16:07,960 --> 00:16:10,240
Speaker 1: It's always the case that the FED is really the

304
00:16:10,280 --> 00:16:12,480
Speaker 1: dominant player when you look at market action, and we

305
00:16:12,560 --> 00:16:15,240
Speaker 1: heard last Friday from the head of the New York FED,

306
00:16:15,280 --> 00:16:19,120
Speaker 1: John Williams, he sees room for a rate cut in

307
00:16:19,240 --> 00:16:23,080
Speaker 1: his words, in the near term, maybe it's December, maybe

308
00:16:23,120 --> 00:16:26,440
Speaker 1: it's some time after the first of the year. How

309
00:16:26,520 --> 00:16:29,680
Speaker 1: important is the FED right now to your outlook and

310
00:16:29,880 --> 00:16:33,440
Speaker 1: trying to remain constructive on the US equity market.

311
00:16:34,200 --> 00:16:36,560
Speaker 3: It all comes down to valuation, right We're now in

312
00:16:36,600 --> 00:16:41,160
Speaker 3: a situation where the market is price for perfection, and

313
00:16:41,200 --> 00:16:45,080
Speaker 3: it sets you up to see this volatility associated with

314
00:16:45,200 --> 00:16:48,640
Speaker 3: any new FED speak that we get. It's actually possible

315
00:16:48,760 --> 00:16:51,280
Speaker 3: that the outlook for twenty twenty six that comes out

316
00:16:51,280 --> 00:16:53,440
Speaker 3: of that December meeting is more important than whether we

317
00:16:53,440 --> 00:16:56,080
Speaker 3: get it cut into summer or not, because people are

318
00:16:56,080 --> 00:17:00,440
Speaker 3: starting to look forward, and so our thought is, let's

319
00:17:00,480 --> 00:17:03,760
Speaker 3: look for companies that are not price wore perfection, and

320
00:17:03,840 --> 00:17:07,879
Speaker 3: that allows us to have some ability for just these

321
00:17:08,359 --> 00:17:12,480
Speaker 3: you know, company specific stories to play out and gives

322
00:17:12,560 --> 00:17:14,639
Speaker 3: us a little bit more peace of mind when it

323
00:17:14,640 --> 00:17:16,320
Speaker 3: comes to these FED announcements.

324
00:17:16,359 --> 00:17:19,120
Speaker 1: So you mentioned healthcare, I'm curious as to how you're

325
00:17:19,119 --> 00:17:21,040
Speaker 1: feeling about the financials these days.

326
00:17:21,600 --> 00:17:24,200
Speaker 3: Yeah, financials are tricky. One you've seen the money center

327
00:17:24,240 --> 00:17:29,919
Speaker 3: banks do extremely well. An area that we like is insurance.

328
00:17:30,800 --> 00:17:34,359
Speaker 3: This is an area that generally performs well in a recession.

329
00:17:34,440 --> 00:17:38,840
Speaker 3: You still have to for the most part, maintain whether

330
00:17:38,880 --> 00:17:42,960
Speaker 3: it's your home insurance or your auto insurance. And they're

331
00:17:43,119 --> 00:17:46,800
Speaker 3: they're trading at a very attractive valuations and so that

332
00:17:46,840 --> 00:17:49,399
Speaker 3: would be another area that we would highlight within financials.

333
00:17:49,440 --> 00:17:51,760
Speaker 3: I think it's it's tough in an error in a

334
00:17:51,840 --> 00:17:54,600
Speaker 3: time of AI to look at, you know, the regional

335
00:17:54,600 --> 00:17:56,800
Speaker 3: banks where you know, are they going to be able

336
00:17:56,840 --> 00:18:00,680
Speaker 3: to compete with these larger institutions and and that's been

337
00:18:00,720 --> 00:18:03,280
Speaker 3: part of the concern in addition to the credit concerns

338
00:18:03,320 --> 00:18:04,160
Speaker 3: that they've had as well.

339
00:18:04,240 --> 00:18:05,880
Speaker 1: So what's your outlook for the new year.

340
00:18:06,400 --> 00:18:12,560
Speaker 3: We are cautiously optimistic for the steady eddy companies. I

341
00:18:12,560 --> 00:18:15,119
Speaker 3: think it's going to be could it could be another

342
00:18:15,240 --> 00:18:18,400
Speaker 3: stock pickers market? Right? What we saw in twenty twenty five.

343
00:18:18,640 --> 00:18:22,199
Speaker 3: The setup has been that AI really drove returns, It

344
00:18:22,359 --> 00:18:26,560
Speaker 3: drove the earnings growth into twenty twenty five. But what

345
00:18:26,640 --> 00:18:30,920
Speaker 3: that did is it allowed opportunities and companies that still

346
00:18:30,960 --> 00:18:34,199
Speaker 3: have strong earnings growth double digit earnings growth irrespective of

347
00:18:34,200 --> 00:18:37,639
Speaker 3: market cycles, and they're training at low valuation. So we

348
00:18:37,680 --> 00:18:40,160
Speaker 3: see an opportunity for those companies to outperform in twenty

349
00:18:40,200 --> 00:18:43,760
Speaker 3: twenty six because they do have that valuation support and

350
00:18:44,400 --> 00:18:46,720
Speaker 3: potentially could see a mean reversion where some of these

351
00:18:47,040 --> 00:18:51,399
Speaker 3: valuations in twenty twenty six from tech AI companies that

352
00:18:51,480 --> 00:18:54,560
Speaker 3: are deemed to be not winners for the near term.

353
00:18:54,680 --> 00:18:56,160
Speaker 3: It's tough to say how it's going to play out

354
00:18:56,160 --> 00:18:59,400
Speaker 3: longer term, but right now, that's how the market's viewing. It.

355
00:18:59,440 --> 00:19:01,879
Speaker 3: Could see their valuations come in and you could see

356
00:19:02,160 --> 00:19:05,080
Speaker 3: that AI, those AI dollars drive to just a few

357
00:19:05,119 --> 00:19:06,960
Speaker 3: companies that are our view to be winners.

358
00:19:07,040 --> 00:19:10,080
Speaker 1: Do you want to be diversified offshore right now globally

359
00:19:10,160 --> 00:19:12,600
Speaker 1: or are you looking at other markets outside the US?

360
00:19:13,000 --> 00:19:16,240
Speaker 3: The global equity market is very attractive right It's still

361
00:19:16,280 --> 00:19:17,720
Speaker 3: trading even though we saw a little bit of a

362
00:19:18,320 --> 00:19:20,199
Speaker 3: run earlier in the year. It's still trading at more

363
00:19:20,200 --> 00:19:23,000
Speaker 3: attract evaluations than we have in the US. The key

364
00:19:23,040 --> 00:19:25,640
Speaker 3: there is to make sure that you're finding quality companies

365
00:19:25,920 --> 00:19:28,239
Speaker 3: with really strong earnings growth, and you can get them

366
00:19:28,280 --> 00:19:30,760
Speaker 3: at a discount, so what you'd get in the US.

367
00:19:31,359 --> 00:19:33,560
Speaker 1: Okay, Grace, we'll leave it there. Thank you so very much.

368
00:19:34,000 --> 00:19:37,280
Speaker 1: Grace Glockner is with Sharf Investments. Joining us here on

369
00:19:37,280 --> 00:19:42,359
Speaker 1: the Daybreak Asia Podcast. Thanks for listening to today's episode

370
00:19:42,440 --> 00:19:46,439
Speaker 1: of the Bloomberg Daybreak Asia Edition podcast. Each weekday, we

371
00:19:46,480 --> 00:19:50,359
Speaker 1: look at the story shaping markets, finance, and geopolitics in

372
00:19:50,400 --> 00:19:53,560
Speaker 1: the Asia Pacific. You can find us on Apple, Spotify,

373
00:19:53,680 --> 00:19:57,200
Speaker 1: the Bloomberg Podcast YouTube channel, or anywhere else you listen.

374
00:19:57,600 --> 00:20:00,520
Speaker 1: Join us again tomorrow for insight on the market moves

375
00:20:00,560 --> 00:20:05,120
Speaker 1: from Hong Kong to Singapore and Australia. I'm Doug Prisoner

376
00:20:05,280 --> 00:20:06,639
Speaker 1: and this is Bloomberg