1
00:00:02,520 --> 00:00:07,040
Speaker 1: Bloomberg Audio Studios, Podcasts, Radio News.

2
00:00:11,119 --> 00:00:14,400
Speaker 2: Welcome to the Bloomberg Daybreak Asia podcast. I'm Doug Chrisner.

3
00:00:14,720 --> 00:00:17,040
Speaker 2: On today's episode, we'll be taking a look at the

4
00:00:17,079 --> 00:00:20,000
Speaker 2: global macro landscape. In a moment, we'll be chatting with

5
00:00:20,120 --> 00:00:24,400
Speaker 2: David Spell, co CIO at Mount Lucas Management. Plus a

6
00:00:24,480 --> 00:00:27,360
Speaker 2: discussion on the fed's path ahead with Bill Adams. He

7
00:00:27,440 --> 00:00:30,560
Speaker 2: is the chief economist at Comerica Bank. But we begin

8
00:00:30,640 --> 00:00:34,239
Speaker 2: in Tokyo. Joining us now is Katherine Thorbeck. She is

9
00:00:34,400 --> 00:00:38,479
Speaker 2: Asia tech columnist for Bloomberg Opinion. She's been very busy

10
00:00:38,520 --> 00:00:41,560
Speaker 2: this week writing about the story on a Deep Seek,

11
00:00:41,920 --> 00:00:45,160
Speaker 2: the Chinese AI startup. Catherine, thank you for making time

12
00:00:45,159 --> 00:00:46,800
Speaker 2: to chat with us. I know it's been a busy

13
00:00:46,800 --> 00:00:49,320
Speaker 2: week for you. What I want to begin with the

14
00:00:49,440 --> 00:00:52,760
Speaker 2: story that just broke late in the day US time.

15
00:00:53,000 --> 00:00:58,960
Speaker 2: American officials are investigating whether Deep Seek essentially circumvented restrictions

16
00:00:59,040 --> 00:01:03,520
Speaker 2: on advanced semiconductors from Nvidia. Now we know that the

17
00:01:03,520 --> 00:01:07,000
Speaker 2: Biden administration cut off China's access to a range of

18
00:01:07,040 --> 00:01:11,399
Speaker 2: some of Nvidia's most powerful products. Now Sands seemed to

19
00:01:11,400 --> 00:01:13,560
Speaker 2: be shifting a little bit. Can you fill us in

20
00:01:13,560 --> 00:01:15,160
Speaker 2: on what you understand the story to.

21
00:01:15,120 --> 00:01:18,679
Speaker 3: Be, right. So this news just came out, as you mentioned,

22
00:01:19,360 --> 00:01:21,360
Speaker 3: just a few hours ago, and I don't think it

23
00:01:21,400 --> 00:01:24,320
Speaker 3: really caught anybody by surprise that the US would launch

24
00:01:24,319 --> 00:01:27,640
Speaker 3: a probe into, you know, what sort of chips Deep

25
00:01:27,680 --> 00:01:29,560
Speaker 3: Seek was using to train its models and whether it

26
00:01:29,640 --> 00:01:33,480
Speaker 3: was able to circumvent export controls. And it's too soon

27
00:01:33,560 --> 00:01:37,160
Speaker 3: to sort of know the outcome of that investigation, but honestly,

28
00:01:37,200 --> 00:01:39,960
Speaker 3: it wouldn't entirely surprise me if they were able to

29
00:01:40,000 --> 00:01:42,280
Speaker 3: get their hands on some Nvidia chips, some of the

30
00:01:42,319 --> 00:01:44,640
Speaker 3: more advanced chips that have been cut off to China.

31
00:01:45,360 --> 00:01:49,440
Speaker 3: You know, these export controls have proven pretty porous in

32
00:01:49,480 --> 00:01:53,280
Speaker 3: a number of instances. That said, we don't know at

33
00:01:53,280 --> 00:01:57,240
Speaker 3: this point in time, and deep seek has it is

34
00:01:57,280 --> 00:01:59,200
Speaker 3: out there that Deep Seek was hoarding some of the

35
00:01:59,240 --> 00:02:02,280
Speaker 3: older in video chips before these export controls came in,

36
00:02:02,320 --> 00:02:04,120
Speaker 3: and whether they were able to get their hands on

37
00:02:04,120 --> 00:02:06,520
Speaker 3: the more advanced models, that's sort of the question now.

38
00:02:07,760 --> 00:02:09,280
Speaker 3: And I think a lot of people in the US,

39
00:02:09,320 --> 00:02:12,240
Speaker 3: you know, are just very curious how they were able

40
00:02:12,240 --> 00:02:15,119
Speaker 3: to create these AI models with the technology that they had.

41
00:02:15,200 --> 00:02:18,200
Speaker 3: So it makes sense that the US would launch this investigation. Now,

42
00:02:18,600 --> 00:02:20,840
Speaker 3: it wouldn't entirely surprise me if they were able to

43
00:02:20,880 --> 00:02:23,760
Speaker 3: obtain some of these more advanced chips. I'm not sure

44
00:02:23,760 --> 00:02:26,839
Speaker 3: that would necessarily change the narrative about how deep seak

45
00:02:26,880 --> 00:02:29,560
Speaker 3: has sort of upended big tech and BAI race. Right now,

46
00:02:29,560 --> 00:02:32,040
Speaker 3: I still think that they were able to prove that they,

47
00:02:32,520 --> 00:02:34,880
Speaker 3: you know, are able to come up with AI breakthroughs

48
00:02:35,200 --> 00:02:37,600
Speaker 3: despite all of these restrictions, and I think that that

49
00:02:37,800 --> 00:02:41,040
Speaker 3: still is very much top of mind for big tech

50
00:02:41,120 --> 00:02:41,520
Speaker 3: right now.

51
00:02:41,600 --> 00:02:44,880
Speaker 2: So our reporting indicates when it comes to the chip story,

52
00:02:44,919 --> 00:02:47,840
Speaker 2: that American officials are looking at whether they were acquired

53
00:02:48,120 --> 00:02:50,920
Speaker 2: these Nvidia chips through a third party or a third

54
00:02:50,960 --> 00:02:54,400
Speaker 2: parties plural in Singapore. But there are a number of

55
00:02:54,480 --> 00:02:58,760
Speaker 2: other investigations going on in regards to deep seek, and

56
00:02:58,800 --> 00:03:02,200
Speaker 2: that would include Microsoft often open Ai looking at whether

57
00:03:02,240 --> 00:03:05,960
Speaker 2: open aiyes model was somehow used in training deep seek.

58
00:03:06,080 --> 00:03:10,359
Speaker 3: Is that right, that's correct? And so right now Microsoft

59
00:03:10,400 --> 00:03:14,280
Speaker 3: is probing whether deep seek used outputs from open AI's

60
00:03:14,360 --> 00:03:17,240
Speaker 3: models to train their own model, which would technically be

61
00:03:17,400 --> 00:03:19,799
Speaker 3: a breach of the terms of service for open using

62
00:03:19,840 --> 00:03:23,320
Speaker 3: open AI's models. But to me, this this really reeked

63
00:03:23,360 --> 00:03:25,840
Speaker 3: of a lot of irony. You know, open ai has

64
00:03:25,880 --> 00:03:29,080
Speaker 3: trained its models by basically scraping writing and art from

65
00:03:29,120 --> 00:03:33,359
Speaker 3: the entire internet, you know, without really getting meaningful consent

66
00:03:33,440 --> 00:03:36,280
Speaker 3: from artists and writers to do that. So it did

67
00:03:36,320 --> 00:03:37,880
Speaker 3: seem a little bit odd and it has rubbed a

68
00:03:37,880 --> 00:03:39,440
Speaker 3: lot of people sort of the wrong way. A lot

69
00:03:39,440 --> 00:03:41,640
Speaker 3: of jokes have been made about Oh now open a

70
00:03:41,920 --> 00:03:44,600
Speaker 3: open ai all the sudden cares about, you know, intellectual

71
00:03:44,640 --> 00:03:48,560
Speaker 3: property rights. You know, whether deep Seak obtained this data

72
00:03:48,560 --> 00:03:51,360
Speaker 3: improperly or not is still sort of the subject of investigation.

73
00:03:51,440 --> 00:03:53,360
Speaker 3: But I think it does put open ai in a

74
00:03:53,400 --> 00:03:55,240
Speaker 3: little bit of an awkward spot right now.

75
00:03:55,480 --> 00:03:57,920
Speaker 2: So what does the deep Seek story tell us or

76
00:03:58,680 --> 00:04:02,400
Speaker 2: allow us to understand about the evolution of the AI

77
00:04:02,560 --> 00:04:03,640
Speaker 2: industry in China?

78
00:04:04,400 --> 00:04:07,120
Speaker 3: Right So, I think deep seek really caught the West

79
00:04:07,160 --> 00:04:10,040
Speaker 3: by surprise when it released its most recent model on

80
00:04:10,080 --> 00:04:13,560
Speaker 3: January twentieth, And I don't think it necessarily had to

81
00:04:13,600 --> 00:04:16,640
Speaker 3: catch so many people entirely off guard, and you know,

82
00:04:16,880 --> 00:04:21,000
Speaker 3: caused this multi billion dollar stock market sort of route,

83
00:04:21,720 --> 00:04:23,760
Speaker 3: and some of those losses have been paired back over

84
00:04:23,880 --> 00:04:26,600
Speaker 3: over the week. But you know, I first wrote about

85
00:04:26,600 --> 00:04:28,839
Speaker 3: deep Seek back in June more than six months ago

86
00:04:28,880 --> 00:04:31,440
Speaker 3: when it released its V two model, one of its

87
00:04:31,480 --> 00:04:34,520
Speaker 3: earlier AI models, and I was just saying that this

88
00:04:34,640 --> 00:04:36,960
Speaker 3: is actually a very impressive AI model. You know, for

89
00:04:37,000 --> 00:04:40,160
Speaker 3: a long time, the West and Silicon Valley has sort

90
00:04:40,200 --> 00:04:43,320
Speaker 3: of claimed dominance in the AI race, and they've thought

91
00:04:43,320 --> 00:04:46,640
Speaker 3: there were years ahead of China, and I think policymakers

92
00:04:46,640 --> 00:04:48,760
Speaker 3: in Washington have thought, you know, the export controls, the

93
00:04:49,240 --> 00:04:53,359
Speaker 3: restrictions on chips that they've been putting towards China that

94
00:04:53,400 --> 00:04:56,160
Speaker 3: would really hold China back, and Deep Seek really up

95
00:04:56,240 --> 00:04:59,080
Speaker 3: ended that narrative. You know, they showed that Chinese AI,

96
00:04:59,520 --> 00:05:02,080
Speaker 3: Chinese AI startups are actually really able to innovate and

97
00:05:02,120 --> 00:05:04,200
Speaker 3: are able to do it at a fraction of the

98
00:05:04,240 --> 00:05:07,680
Speaker 3: cost that these Silicon Valley tech giants have been doing.

99
00:05:08,120 --> 00:05:10,400
Speaker 3: So it really sort of I think people were really

100
00:05:10,400 --> 00:05:12,640
Speaker 3: really impressed by this R one model that they put

101
00:05:12,680 --> 00:05:17,120
Speaker 3: out on January twentieth, And this R one model, it

102
00:05:17,160 --> 00:05:20,240
Speaker 3: can really it's a reasoning model, so it can really

103
00:05:20,320 --> 00:05:22,760
Speaker 3: sort of think through questions the way you know a

104
00:05:22,839 --> 00:05:26,640
Speaker 3: human would think through questions. It's been on par with

105
00:05:26,839 --> 00:05:29,960
Speaker 3: you know, open AIS models on a number of industry benchmarks,

106
00:05:31,000 --> 00:05:34,039
Speaker 3: and it really I think, you know, caught the sort

107
00:05:34,040 --> 00:05:36,760
Speaker 3: of tech billionaires in the US, some of these very

108
00:05:36,760 --> 00:05:39,040
Speaker 3: powerful companies totally off guard this week.

109
00:05:39,200 --> 00:05:42,279
Speaker 2: To what extent do you believe there is an entrenched

110
00:05:42,360 --> 00:05:46,400
Speaker 2: bias that China doesn't innovate, that it merely copies.

111
00:05:47,000 --> 00:05:49,200
Speaker 3: So I think we've seen this narrative for a while,

112
00:05:49,480 --> 00:05:52,839
Speaker 3: and I think that there's a number of reasons why

113
00:05:52,880 --> 00:05:54,680
Speaker 3: this comes up over and over again and why we're

114
00:05:54,680 --> 00:05:59,279
Speaker 3: continually shocked by China's tech breakthroughs. And you know, some

115
00:05:59,360 --> 00:06:01,480
Speaker 3: of these, I think, you know, a language barrier, separate

116
00:06:01,520 --> 00:06:04,920
Speaker 3: social media ecosystems, and sort of a shrinking number of

117
00:06:04,920 --> 00:06:07,800
Speaker 3: foreign reporters actually in China give the US very little

118
00:06:07,880 --> 00:06:10,960
Speaker 3: visibility into some of the more exciting sort of developments

119
00:06:11,000 --> 00:06:14,280
Speaker 3: in China's tech sector right now. And I also think

120
00:06:14,400 --> 00:06:17,040
Speaker 3: that there's sort of an insular mindset in the US

121
00:06:17,160 --> 00:06:20,120
Speaker 3: that you know, Silicon Valley and sort of these the

122
00:06:20,240 --> 00:06:22,640
Speaker 3: Silicon Valley leaders, a lot of them seem to think

123
00:06:22,680 --> 00:06:24,240
Speaker 3: that they're the only ones who can really lead the

124
00:06:24,320 --> 00:06:27,240
Speaker 3: charge here, and I think it leaves huge blind spots

125
00:06:27,279 --> 00:06:29,240
Speaker 3: to what's going on in China. A lot of sort

126
00:06:29,240 --> 00:06:30,720
Speaker 3: of the coverage of China that we read in the

127
00:06:30,800 --> 00:06:34,120
Speaker 3: US is very focused on geopolitical rivalries and a lot

128
00:06:34,160 --> 00:06:36,880
Speaker 3: of you know, voices in Washington see any sort of

129
00:06:36,880 --> 00:06:38,840
Speaker 3: tech breakthroughs in China as you know, a threat to

130
00:06:38,880 --> 00:06:42,400
Speaker 3: democracy everywhere. And whether or not that's true, I think

131
00:06:42,440 --> 00:06:45,359
Speaker 3: it does create these big blind spots to some of

132
00:06:45,360 --> 00:06:48,159
Speaker 3: the sort of actual people working in China, and you know,

133
00:06:48,200 --> 00:06:50,200
Speaker 3: the more than one billion people that live there and

134
00:06:50,240 --> 00:06:52,200
Speaker 3: a lot of times are innovating and sort of driving

135
00:06:52,240 --> 00:06:55,800
Speaker 3: tech forward despite their government and not because of it.

136
00:06:56,320 --> 00:06:58,359
Speaker 2: I know, the TikTok story is something that you and

137
00:06:58,440 --> 00:07:02,320
Speaker 2: I have discussed in the past, and the proprietary nature

138
00:07:02,360 --> 00:07:05,560
Speaker 2: of that algorithm something that Chinese would like to protect.

139
00:07:06,040 --> 00:07:09,479
Speaker 2: I found it curious that in the case of deep Seek,

140
00:07:10,160 --> 00:07:14,440
Speaker 2: the developers opted for kind of an open system. Did

141
00:07:14,440 --> 00:07:15,960
Speaker 2: that surprise you at all?

142
00:07:16,800 --> 00:07:19,440
Speaker 3: It didn't entirely surprise me. I think that they were

143
00:07:19,480 --> 00:07:21,680
Speaker 3: sort of working with what they've got, and you know,

144
00:07:21,760 --> 00:07:25,480
Speaker 3: open source models you can sort of tweak and a

145
00:07:25,480 --> 00:07:27,040
Speaker 3: lot of people can work on them at once, and

146
00:07:27,080 --> 00:07:30,120
Speaker 3: you can sort of they're they're a little bit cheaper

147
00:07:30,160 --> 00:07:32,800
Speaker 3: to run than sort of what open ai is doing,

148
00:07:32,800 --> 00:07:36,239
Speaker 3: which is just training bigger and bigger and bigger proprietary models,

149
00:07:36,520 --> 00:07:38,520
Speaker 3: So it didn't totally surprise me that they did this.

150
00:07:40,080 --> 00:07:42,440
Speaker 3: I think it does sort of raise larger questions of

151
00:07:43,080 --> 00:07:45,480
Speaker 3: sort of the future direction of the AI sector and

152
00:07:45,520 --> 00:07:48,520
Speaker 3: whether it will be you know, dominated by these like

153
00:07:48,600 --> 00:07:52,320
Speaker 3: smaller startups that are really perfecting and tweaking these open

154
00:07:52,320 --> 00:07:56,200
Speaker 3: source models, or whether sort of the open AI route,

155
00:07:56,200 --> 00:07:58,120
Speaker 3: which is just you know, creating bigger and bigger and

156
00:07:58,160 --> 00:08:01,600
Speaker 3: bigger models and spending more and building out these models,

157
00:08:02,040 --> 00:08:04,480
Speaker 3: whether that will sort of prove superior and we'll have

158
00:08:04,520 --> 00:08:06,240
Speaker 3: to see how it does play out in the long run.

159
00:08:06,520 --> 00:08:08,800
Speaker 2: So we were talking a moment ago about open ai,

160
00:08:08,960 --> 00:08:12,040
Speaker 2: and you reference the fact that open ai essentially was

161
00:08:12,080 --> 00:08:15,920
Speaker 2: trained using the US intranet, and I'm wondering, from the

162
00:08:15,960 --> 00:08:19,280
Speaker 2: point of view of deep seek, do we know much

163
00:08:19,400 --> 00:08:21,640
Speaker 2: about how this model was trained at all?

164
00:08:22,240 --> 00:08:25,080
Speaker 3: So I think it's interesting. I think when it comes

165
00:08:25,080 --> 00:08:27,720
Speaker 3: to deep Seek. One of the big issues that sort

166
00:08:27,760 --> 00:08:30,400
Speaker 3: of as the swarm of American and international users have

167
00:08:30,480 --> 00:08:33,840
Speaker 3: discovered as they've logged on and you know, downloaded this

168
00:08:33,880 --> 00:08:35,640
Speaker 3: app and it's you know, shot up to the top

169
00:08:35,679 --> 00:08:38,040
Speaker 3: of Apple's app store this week. One of the things

170
00:08:38,040 --> 00:08:41,480
Speaker 3: that they've discovered, is you know what's off limits behind

171
00:08:41,600 --> 00:08:44,439
Speaker 3: China's Great Firewall and whether that's you know, talking about Shijinping,

172
00:08:44,600 --> 00:08:48,960
Speaker 3: talking about China's human rights record in Shinjong, where you know,

173
00:08:49,240 --> 00:08:53,079
Speaker 3: there have been documented human rights abuses of weager Muslim minorities,

174
00:08:53,559 --> 00:08:56,120
Speaker 3: and right now, when you chat with deep seek about that,

175
00:08:56,320 --> 00:08:59,120
Speaker 3: you know it'll initially say, let's change the subject, let's

176
00:08:59,160 --> 00:09:02,360
Speaker 3: talk about something else. There are sort of workarounds that

177
00:09:02,440 --> 00:09:04,320
Speaker 3: I was able to play around with this week where

178
00:09:04,360 --> 00:09:08,000
Speaker 3: I did get it to say and sort of encode.

179
00:09:08,240 --> 00:09:11,360
Speaker 3: You know that Xi Jinping has faced international criticism for

180
00:09:11,400 --> 00:09:14,720
Speaker 3: his treatment of Hong Kong protesters and political dissidents. So

181
00:09:14,760 --> 00:09:17,600
Speaker 3: it does show that deep Seek was trained on data

182
00:09:17,679 --> 00:09:20,200
Speaker 3: beyond the Great Firewall, and I'm sure that's going to

183
00:09:20,200 --> 00:09:23,040
Speaker 3: cause a headache for deep Seek. You know, I don't

184
00:09:23,040 --> 00:09:25,080
Speaker 3: think Chinese authorities are going to crack down on this

185
00:09:25,160 --> 00:09:28,319
Speaker 3: tool that you know has brought such a positive international

186
00:09:28,400 --> 00:09:32,520
Speaker 3: spotlight to its tech sector and tech capabilities. But what

187
00:09:32,600 --> 00:09:34,880
Speaker 3: I do think that this all shows is that there's

188
00:09:34,920 --> 00:09:37,720
Speaker 3: a lot more at stake in this global race for

189
00:09:37,800 --> 00:09:40,439
Speaker 3: AI dominance between the US and China. You know, as

190
00:09:40,440 --> 00:09:43,440
Speaker 3: more people turn to these tools for research, for homework help.

191
00:09:44,000 --> 00:09:46,679
Speaker 3: They could also be used to sort of covertly influence

192
00:09:47,000 --> 00:09:50,640
Speaker 3: our ideas and influence our ideologies, whether that's from Beijing

193
00:09:50,840 --> 00:09:53,040
Speaker 3: or from the US. So I think that, you know,

194
00:09:53,120 --> 00:09:55,360
Speaker 3: there's obviously a lot of money in stock market value

195
00:09:55,360 --> 00:09:58,280
Speaker 3: at stake here, but these tools are also very powerful

196
00:09:58,320 --> 00:10:01,040
Speaker 3: and they have the power to really influence people. And

197
00:10:01,080 --> 00:10:02,480
Speaker 3: I think that that we're going to see more of

198
00:10:02,480 --> 00:10:04,680
Speaker 3: that sort of play now in the long run.

199
00:10:04,880 --> 00:10:07,480
Speaker 2: Catherine will leave it there always a pleasure. Katherine Thorbeck,

200
00:10:07,600 --> 00:10:11,360
Speaker 2: Asia tech columnist for Bloomberg Opinion, joining us here on

201
00:10:11,400 --> 00:10:22,600
Speaker 2: the Daybreak Asia podcast. Welcome back to the Daybreak Asia Podcast.

202
00:10:22,640 --> 00:10:25,880
Speaker 2: I'm Doug Chrisner. There was certainly volatility in the currency

203
00:10:25,920 --> 00:10:29,000
Speaker 2: markets in late New York trading today and the catalyst

204
00:10:29,080 --> 00:10:32,199
Speaker 2: was President Trump. He said that he will follow through

205
00:10:32,320 --> 00:10:34,920
Speaker 2: on his threat to impose twenty five percent tariffs on

206
00:10:35,040 --> 00:10:39,080
Speaker 2: imports from Canada and Mexico this Saturday. For a closer

207
00:10:39,120 --> 00:10:42,400
Speaker 2: look now at how these tariffs might affect the macro outlook,

208
00:10:42,760 --> 00:10:45,520
Speaker 2: I'm joined by David Aspell. He is partner also co

209
00:10:45,640 --> 00:10:50,439
Speaker 2: CIO at Mount Lucas Management, joining us from just outside Philadelphia.

210
00:10:50,960 --> 00:10:52,800
Speaker 2: Thank you for making time to chat with us. David,

211
00:10:52,840 --> 00:10:55,480
Speaker 2: do you have a sense of what the tariff threat

212
00:10:55,559 --> 00:10:58,439
Speaker 2: may mean to global markets generally speaking?

213
00:10:59,240 --> 00:11:01,360
Speaker 1: I mean, there's a lot of uncertainty, doesn't it.

214
00:11:01,360 --> 00:11:04,240
Speaker 4: You know, we've got a new administration that's just come

215
00:11:04,280 --> 00:11:07,720
Speaker 4: in that you know, it's clearly sees volatility as a feature,

216
00:11:07,880 --> 00:11:11,079
Speaker 4: not a bug. And you know they're using tariffs, amongst

217
00:11:11,080 --> 00:11:16,080
Speaker 4: other things, for negotiating leverage to try and push through

218
00:11:16,120 --> 00:11:20,520
Speaker 4: some pretty large macro policy goals. And these policy goals

219
00:11:20,600 --> 00:11:24,800
Speaker 4: run directly through currency markets, through bond yields, and they're

220
00:11:24,800 --> 00:11:26,800
Speaker 4: going to have large impacts on economies everywhere.

221
00:11:26,840 --> 00:11:28,480
Speaker 1: It's going to be a fascinating four years.

222
00:11:28,480 --> 00:11:31,359
Speaker 2: I think, yeah, definitely, the dollar has been a big beneficiary.

223
00:11:31,600 --> 00:11:33,880
Speaker 2: We can talk about FED policy in a moment. But

224
00:11:33,960 --> 00:11:37,240
Speaker 2: do you expect the dollar to remain very strong here

225
00:11:37,280 --> 00:11:38,120
Speaker 2: against the matures?

226
00:11:38,960 --> 00:11:40,600
Speaker 1: I think it's hard to say.

227
00:11:40,679 --> 00:11:42,400
Speaker 4: I think what's going on is that, you know, we've

228
00:11:42,400 --> 00:11:45,320
Speaker 4: gone through a period of US exceptionalism over the past

229
00:11:45,840 --> 00:11:50,240
Speaker 4: few years, where the US economy has been stronger than others,

230
00:11:50,480 --> 00:11:53,440
Speaker 4: and so that's why you've seen it particularly against Japan

231
00:11:53,600 --> 00:11:56,319
Speaker 4: or against the Euro. You know, the euro has been

232
00:11:56,440 --> 00:11:58,160
Speaker 4: weak because the European economy has been weak.

233
00:11:58,160 --> 00:12:00,520
Speaker 1: It's the same with the UK. And if you think

234
00:12:00,559 --> 00:12:01,200
Speaker 1: why that.

235
00:12:01,200 --> 00:12:04,040
Speaker 4: Is, it's because the US has had has higher rates

236
00:12:04,080 --> 00:12:07,560
Speaker 4: currently and it can survive higher rates because it's got

237
00:12:07,600 --> 00:12:11,360
Speaker 4: a slightly different type of economy where mortgage rates don't

238
00:12:11,360 --> 00:12:13,600
Speaker 4: feed through in quite the same way. And now you've

239
00:12:13,600 --> 00:12:17,600
Speaker 4: got an administration that seems like it's unleashing some animal spirits.

240
00:12:17,640 --> 00:12:19,760
Speaker 4: So as long as that continues and the US does

241
00:12:19,800 --> 00:12:22,600
Speaker 4: better than others, then yeah, I think the US dollar

242
00:12:22,679 --> 00:12:24,800
Speaker 4: can stay can stay fairly well bid.

243
00:12:25,000 --> 00:12:27,240
Speaker 2: There's been some debate in Washington as whether or not

244
00:12:27,320 --> 00:12:30,160
Speaker 2: these policies regarding tariffs are inflationary. Do you have a

245
00:12:30,240 --> 00:12:30,640
Speaker 2: view on that.

246
00:12:31,240 --> 00:12:32,240
Speaker 1: I don't think they are.

247
00:12:32,880 --> 00:12:34,880
Speaker 4: I think they might be for a short period of

248
00:12:34,960 --> 00:12:37,280
Speaker 4: time as a macro trader, and how I look at inflation,

249
00:12:37,400 --> 00:12:40,000
Speaker 4: how I think the FED looks at inflation is maybe

250
00:12:40,000 --> 00:12:42,200
Speaker 4: a little different to how people on main street see it.

251
00:12:43,120 --> 00:12:45,600
Speaker 1: What inflation to me is.

252
00:12:45,120 --> 00:12:48,480
Speaker 4: Is an ongoing process of higher prices for a period

253
00:12:48,520 --> 00:12:50,400
Speaker 4: of time, whereas tariffs to me are a one off

254
00:12:50,440 --> 00:12:53,199
Speaker 4: price shock. Now it could be that they get embedded,

255
00:12:53,240 --> 00:12:55,480
Speaker 4: particularly at a time when people are nervous about inflation,

256
00:12:55,880 --> 00:12:59,960
Speaker 4: but I think that the negatives of inflation will take

257
00:13:00,240 --> 00:13:02,720
Speaker 4: you know, as they slow down the economy in some places,

258
00:13:03,000 --> 00:13:05,440
Speaker 4: if people are nervous about them, will take the edge

259
00:13:05,440 --> 00:13:07,640
Speaker 4: off them. And I think generally if the inflation part

260
00:13:07,679 --> 00:13:10,679
Speaker 4: of me seems quite well set over the next few years,

261
00:13:10,720 --> 00:13:11,800
Speaker 4: partly because of housing.

262
00:13:12,200 --> 00:13:14,320
Speaker 2: Just a few weeks ago, the debate in the bond

263
00:13:14,360 --> 00:13:16,240
Speaker 2: market was whether or not we were going to see

264
00:13:16,280 --> 00:13:18,559
Speaker 2: a five percent yield on the tenure. I'm looking at

265
00:13:18,559 --> 00:13:21,120
Speaker 2: something now that's closer to four and a half percent.

266
00:13:21,400 --> 00:13:23,640
Speaker 2: What's your view on yields going forward?

267
00:13:24,000 --> 00:13:27,400
Speaker 4: Unless something goes very wry in inflation, which is possible

268
00:13:27,400 --> 00:13:28,199
Speaker 4: but seems unlikely.

269
00:13:28,240 --> 00:13:30,679
Speaker 1: I think we've seen the peak and yields. I think

270
00:13:30,760 --> 00:13:32,120
Speaker 1: the economy can survive them.

271
00:13:32,160 --> 00:13:34,360
Speaker 4: But I think you've got a FED that wants to

272
00:13:34,440 --> 00:13:37,199
Speaker 4: reduce rates and is able to reduce rates over time.

273
00:13:37,679 --> 00:13:39,640
Speaker 4: If you look at where the FED projections were at

274
00:13:39,679 --> 00:13:41,360
Speaker 4: the end of the year, you know they thought that

275
00:13:41,360 --> 00:13:44,439
Speaker 4: with a two point five percent core PC at the

276
00:13:44,559 --> 00:13:47,679
Speaker 4: end of this year, they would have rates down at

277
00:13:47,720 --> 00:13:50,480
Speaker 4: three point nine, which to me seems like they're making

278
00:13:50,600 --> 00:13:53,800
Speaker 4: an easier bar to cut rates rather than a higher bar.

279
00:13:53,720 --> 00:13:55,560
Speaker 1: So I think they offer good value.

280
00:13:55,760 --> 00:13:59,680
Speaker 4: It seems that they're useful in a portfolio context currently

281
00:14:00,080 --> 00:14:02,160
Speaker 4: because if the economy slows down, the FED is able

282
00:14:02,200 --> 00:14:03,360
Speaker 4: to cut which I think.

283
00:14:03,280 --> 00:14:03,959
Speaker 1: Is real helpful.

284
00:14:04,360 --> 00:14:06,840
Speaker 2: In terms of the story across the Asia Pacific, it's

285
00:14:06,880 --> 00:14:10,840
Speaker 2: mainly been about weak domestic demand in China and sluggishness

286
00:14:11,040 --> 00:14:13,760
Speaker 2: in the industrial economy. Do you have a sense of

287
00:14:13,800 --> 00:14:16,320
Speaker 2: what China is going through, where we are now in

288
00:14:16,360 --> 00:14:19,000
Speaker 2: this cycle, and whether or not things are beginning to improve.

289
00:14:19,400 --> 00:14:19,600
Speaker 1: Yeah.

290
00:14:19,640 --> 00:14:21,760
Speaker 4: I think that that's been one of the major stories

291
00:14:21,800 --> 00:14:24,000
Speaker 4: in the global economy over the past few years. The

292
00:14:24,040 --> 00:14:26,360
Speaker 4: extent to which China has been slowing. They've clearly got

293
00:14:26,800 --> 00:14:30,600
Speaker 4: a consumption problem. That their economy is incredibly unbalanced. They

294
00:14:30,720 --> 00:14:33,680
Speaker 4: run very large surpluses and rely on other people to

295
00:14:33,760 --> 00:14:35,120
Speaker 4: soak up those surpluses, and.

296
00:14:35,160 --> 00:14:37,440
Speaker 1: The rest of the world has decided that rightly.

297
00:14:37,480 --> 00:14:39,360
Speaker 4: I think that it's not going They're not willing to

298
00:14:39,400 --> 00:14:43,240
Speaker 4: absorb those surpluses, which has led to some slow down

299
00:14:43,240 --> 00:14:47,960
Speaker 4: in China. I think what they're doing is slowly they

300
00:14:48,000 --> 00:14:52,360
Speaker 4: are trying to rebalance, and I thought that the stimulus

301
00:14:52,400 --> 00:14:56,720
Speaker 4: policies they put in around rates and the other loosenings

302
00:14:56,720 --> 00:14:58,600
Speaker 4: and the cleaning up a balance sheets. I thought they

303
00:14:58,600 --> 00:15:02,240
Speaker 4: were quite powerful. Just about now starting to see those,

304
00:15:02,920 --> 00:15:04,880
Speaker 4: to see those come to fruition. The data seems like

305
00:15:04,920 --> 00:15:07,359
Speaker 4: it's starting to turn up. It seems like the stimulus

306
00:15:07,440 --> 00:15:08,840
Speaker 4: was powerful around the consumer.

307
00:15:09,560 --> 00:15:10,920
Speaker 1: It's just I worry that it's.

308
00:15:10,840 --> 00:15:15,040
Speaker 4: Going to run into a buzzsaw of the new administration

309
00:15:15,120 --> 00:15:16,480
Speaker 4: and tariffs, and I hope that we can get a

310
00:15:16,520 --> 00:15:21,000
Speaker 4: deal done that rebalances their economy and means that we

311
00:15:21,040 --> 00:15:22,440
Speaker 4: don't have to the rest of the world doesn't have

312
00:15:22,480 --> 00:15:25,400
Speaker 4: to soak up their surpluses without too much collateral damage.

313
00:15:25,600 --> 00:15:29,760
Speaker 2: I'm curious about whether you're finding any value across markets

314
00:15:29,760 --> 00:15:33,560
Speaker 2: in Asia. Now, Chinese assets may be inexpensive on a

315
00:15:33,640 --> 00:15:36,480
Speaker 2: relative basis, we can go there, but I'm also curious

316
00:15:36,480 --> 00:15:37,840
Speaker 2: about what you're seeing in Japan.

317
00:15:38,880 --> 00:15:42,200
Speaker 4: I would say that we generally do systematic trend following,

318
00:15:42,240 --> 00:15:44,600
Speaker 4: So what we're doing is just following prices. If things

319
00:15:44,640 --> 00:15:47,440
Speaker 4: are going up, we're along them. If things are going down,

320
00:15:47,480 --> 00:15:49,400
Speaker 4: with short them, which means you know, we've been in

321
00:15:49,480 --> 00:15:51,600
Speaker 4: the in the yen trade for a long period of time.

322
00:15:52,040 --> 00:15:54,440
Speaker 4: We have been long dollars and short yeah, and that's

323
00:15:54,480 --> 00:15:56,320
Speaker 4: been good. I think that trade can continue because of

324
00:15:56,360 --> 00:16:00,600
Speaker 4: the interest rate differential. Alongside on the discretion side where

325
00:16:00,600 --> 00:16:03,720
Speaker 4: we run macro strategies, I think the Chinese equity market

326
00:16:03,960 --> 00:16:05,400
Speaker 4: is incredibly cheap.

327
00:16:05,240 --> 00:16:06,880
Speaker 1: As long as it can do the things.

328
00:16:07,080 --> 00:16:09,440
Speaker 4: It just needs to be able to do the rebalancing

329
00:16:09,720 --> 00:16:11,960
Speaker 4: to get through this period and come to a trade

330
00:16:11,960 --> 00:16:15,600
Speaker 4: agreement and operate in a much more normal way as

331
00:16:15,880 --> 00:16:20,520
Speaker 4: something closer to a regular emerging market economy. If it

332
00:16:20,560 --> 00:16:22,920
Speaker 4: can do that, then the equity market there is incredibly cheap.

333
00:16:23,120 --> 00:16:25,560
Speaker 4: If it cannot do that, then I think we'll end

334
00:16:25,640 --> 00:16:27,440
Speaker 4: up this will be another false down of which you've

335
00:16:27,440 --> 00:16:30,160
Speaker 4: had a few over the past years. But I'm pretty

336
00:16:30,160 --> 00:16:32,680
Speaker 4: hopeful that the new administration is able to do a

337
00:16:32,720 --> 00:16:35,800
Speaker 4: trade deal and we see some brighter times ahead in Asia.

338
00:16:35,920 --> 00:16:38,320
Speaker 2: David, we'll leave it there, Thanks so much. David Spell,

339
00:16:38,400 --> 00:16:42,120
Speaker 2: partner co CIO at Mount Lucas Management, joining us here

340
00:16:42,160 --> 00:16:46,640
Speaker 2: on the Daybreak Aasia podcast. So let's turn our attention

341
00:16:46,720 --> 00:16:49,920
Speaker 2: now to the US economy. Today, we learn that economic

342
00:16:49,960 --> 00:16:53,000
Speaker 2: growth expanded at a solid pace in the fourth quarter,

343
00:16:53,160 --> 00:16:57,840
Speaker 2: albeit a little less than forecast. Fourth quarter GDP growing

344
00:16:57,880 --> 00:16:59,960
Speaker 2: at a rate of two point three percent, and can

345
00:17:00,000 --> 00:17:03,720
Speaker 2: consumer spending advancing at an annual rate of four point

346
00:17:03,760 --> 00:17:07,040
Speaker 2: two percent. Let's take a closer look now with Bill Adams.

347
00:17:07,119 --> 00:17:10,040
Speaker 2: He is the chief economist at Comerica Bank. Bill, thanks

348
00:17:10,040 --> 00:17:12,399
Speaker 2: for making time to chat with us. Give me your

349
00:17:12,480 --> 00:17:15,159
Speaker 2: overall impression of this GDP print. What do you think

350
00:17:15,240 --> 00:17:15,880
Speaker 2: it tells us?

351
00:17:16,600 --> 00:17:20,480
Speaker 5: So the headline was a slowdown, but the details were strong.

352
00:17:20,600 --> 00:17:23,640
Speaker 5: If you look at my preferred measure of core real

353
00:17:23,680 --> 00:17:27,639
Speaker 5: GDP that's real final sales to private domestic purchasers. That

354
00:17:27,800 --> 00:17:31,280
Speaker 5: tracks GDP's trend by leaving out the effects of inventories,

355
00:17:31,359 --> 00:17:34,120
Speaker 5: leaving out the effects of trade and government spending. That

356
00:17:34,160 --> 00:17:36,879
Speaker 5: grew three point two percent annualized in the fourth quarter.

357
00:17:37,200 --> 00:17:41,679
Speaker 5: So that's good news. The US economy is in good shape.

358
00:17:42,240 --> 00:17:45,320
Speaker 5: Growth momentum is stronger than the headline in the fourth

359
00:17:45,400 --> 00:17:48,880
Speaker 5: quarter and closer to the annual growth rate two point

360
00:17:48,920 --> 00:17:52,400
Speaker 5: eight percent, which is excellent for the US economy.

361
00:17:52,560 --> 00:17:54,880
Speaker 2: So at the same time, today we learned that weekly

362
00:17:54,960 --> 00:17:58,040
Speaker 2: jobless claims came in well below estimates. And I'm wondering

363
00:17:58,080 --> 00:18:00,680
Speaker 2: whether when you look at the claims day on top

364
00:18:00,720 --> 00:18:04,240
Speaker 2: of the GDP data, you come away with a conclusion that, yeah,

365
00:18:04,280 --> 00:18:06,480
Speaker 2: the Fed's going to be on hold for a bit longer.

366
00:18:06,960 --> 00:18:11,040
Speaker 5: It sure looks like it. The labor market data in

367
00:18:11,280 --> 00:18:14,160
Speaker 5: the second half of twenty twenty four, we're worrying the Fed.

368
00:18:15,240 --> 00:18:17,160
Speaker 5: You'll recall that was when we were all talking about

369
00:18:17,160 --> 00:18:20,560
Speaker 5: the Psalm rule, form of FED economist Claudia Sam's observation.

370
00:18:21,240 --> 00:18:23,520
Speaker 5: When the three month moving average of the unemployment rate

371
00:18:23,600 --> 00:18:25,720
Speaker 5: rises by half a percent or more from it's twelve

372
00:18:25,800 --> 00:18:29,720
Speaker 5: month low, typically the economy has been in recession, and

373
00:18:29,800 --> 00:18:32,720
Speaker 5: so that Psalm rule triggered, and I think that was

374
00:18:32,760 --> 00:18:34,800
Speaker 5: one of the big contributors to why the Fed cut

375
00:18:34,840 --> 00:18:38,440
Speaker 5: interest rates a full percentage point between September and December.

376
00:18:39,240 --> 00:18:42,399
Speaker 5: But now we have this solid GDP growth data in hand,

377
00:18:42,600 --> 00:18:46,200
Speaker 5: Labor market data like that claims data like the jobs

378
00:18:46,240 --> 00:18:50,560
Speaker 5: report have stabilized, and that means that the FED is

379
00:18:50,640 --> 00:18:53,640
Speaker 5: less worried about the economic outlook and they can they

380
00:18:53,640 --> 00:18:56,240
Speaker 5: feel they have the latitude to refocus their attention on

381
00:18:56,320 --> 00:18:59,000
Speaker 5: bringing inflation closer to that two percent target.

382
00:18:59,080 --> 00:19:01,520
Speaker 2: So, Bill, I'm curious to get your take on how

383
00:19:01,680 --> 00:19:05,080
Speaker 2: the policies from the Trump administration as they relate to

384
00:19:05,280 --> 00:19:08,240
Speaker 2: deportations may impact the labor market. Do you have a

385
00:19:08,280 --> 00:19:08,800
Speaker 2: sense of that.

386
00:19:09,480 --> 00:19:13,720
Speaker 5: So directionally, if the US labor market has fewer workers,

387
00:19:13,760 --> 00:19:17,400
Speaker 5: that would tend to push the unemployment rate down. That's

388
00:19:17,480 --> 00:19:20,680
Speaker 5: just labor demand is not going to decline as much

389
00:19:20,680 --> 00:19:23,440
Speaker 5: as labor supply would, and so it's a question of

390
00:19:23,680 --> 00:19:27,399
Speaker 5: magnitude how large this effect is going to be. But

391
00:19:28,119 --> 00:19:31,040
Speaker 5: I think the Fed is clearly taking a wait and

392
00:19:31,080 --> 00:19:35,440
Speaker 5: see approach to see how much the change in immigration

393
00:19:35,520 --> 00:19:39,320
Speaker 5: policies affects labor supply over the next twelve months, next

394
00:19:39,359 --> 00:19:42,239
Speaker 5: twenty four months, as well as waiting and see this

395
00:19:42,800 --> 00:19:49,119
Speaker 5: for what exactly happens with tariff policies tax policies. But directionally,

396
00:19:49,160 --> 00:19:52,120
Speaker 5: it all kind of points to either a tighter job

397
00:19:52,160 --> 00:19:57,199
Speaker 5: market with changes in immigration policy, or higher prices for

398
00:19:57,280 --> 00:20:01,399
Speaker 5: consumers and for businesses if teriff rates go up, or

399
00:20:01,440 --> 00:20:04,280
Speaker 5: just an overall hotter economy if we have tax cut

400
00:20:04,840 --> 00:20:07,359
Speaker 5: directed stimulus. So all of that would be reasons for

401
00:20:07,440 --> 00:20:12,119
Speaker 5: the FED to slow the move lower in interest rates

402
00:20:12,480 --> 00:20:15,120
Speaker 5: or to just hold interest rates steady for an extended period.

403
00:20:15,320 --> 00:20:17,160
Speaker 5: That seems to be the theme right now.

404
00:20:17,240 --> 00:20:21,040
Speaker 2: So if you extend that then into the market's response.

405
00:20:21,200 --> 00:20:24,120
Speaker 2: I'm talking about the treasury market here, is it likely

406
00:20:24,200 --> 00:20:27,040
Speaker 2: that that tenure yield could approach five percent this year.

407
00:20:27,720 --> 00:20:30,320
Speaker 5: I'm expecting that for most of the year, the ten

408
00:20:30,400 --> 00:20:32,879
Speaker 5: year is probably going to range between four and a

409
00:20:32,960 --> 00:20:35,680
Speaker 5: quarter percent and four and three quarters percent. I think

410
00:20:35,720 --> 00:20:40,280
Speaker 5: a lot of the concerns about upper pressures on inflation,

411
00:20:40,520 --> 00:20:44,159
Speaker 5: or pressures on the labor market, or on the fiscal

412
00:20:44,160 --> 00:20:47,040
Speaker 5: deficit if we have more stimulus, all of that is

413
00:20:47,560 --> 00:20:50,959
Speaker 5: I think pretty clearly reflected in market pricing today.

414
00:20:51,280 --> 00:20:53,320
Speaker 2: What about the knock on effect that it would have

415
00:20:53,520 --> 00:20:54,760
Speaker 2: with the mortgage market.

416
00:20:55,280 --> 00:20:57,640
Speaker 5: I think we'll have less of a recovery of home

417
00:20:57,720 --> 00:21:01,840
Speaker 5: sales than we would have in the absence of these policies,

418
00:21:02,119 --> 00:21:04,919
Speaker 5: but you know that's relative, and if you're comparing to

419
00:21:05,200 --> 00:21:08,719
Speaker 5: twenty twenty four, that was the weakest year since the

420
00:21:08,720 --> 00:21:11,560
Speaker 5: mid nineties for existing home sales, I think the direction,

421
00:21:12,119 --> 00:21:14,600
Speaker 5: even with mortgage rates staying high, is probably a bit

422
00:21:14,680 --> 00:21:17,719
Speaker 5: higher this year. It's just it's going to be a

423
00:21:17,760 --> 00:21:22,040
Speaker 5: more measured recovery for existing home sales than we otherwise

424
00:21:22,080 --> 00:21:24,560
Speaker 5: would have seen. New home sales I think look better

425
00:21:24,640 --> 00:21:29,320
Speaker 5: because there's homebuilders are offering incentives to home buyers, and

426
00:21:29,600 --> 00:21:32,159
Speaker 5: the kind of the absolute number of existing homes that

427
00:21:32,200 --> 00:21:35,399
Speaker 5: are listed right now is still pretty low, and that

428
00:21:35,520 --> 00:21:38,000
Speaker 5: is directing home buyers, the ones who can afford to

429
00:21:38,000 --> 00:21:41,000
Speaker 5: be buying in a market like this, to have a

430
00:21:41,000 --> 00:21:43,240
Speaker 5: look at new construction.

431
00:21:43,440 --> 00:21:46,119
Speaker 2: I mentioned a moment ago, the consumer spending in the

432
00:21:46,160 --> 00:21:48,480
Speaker 2: fourth quarter of last year was very robust at four

433
00:21:48,520 --> 00:21:51,920
Speaker 2: point two percent growth. How do you evaluate the American

434
00:21:51,960 --> 00:21:55,920
Speaker 2: consumer right now? Are things beginning to become less robust

435
00:21:56,000 --> 00:21:56,440
Speaker 2: in a way?

436
00:21:56,520 --> 00:22:01,800
Speaker 5: Perhaps that's a funny question. So on average, the American

437
00:22:01,800 --> 00:22:05,520
Speaker 5: consumer is in great shape, benefiting from the big increases

438
00:22:05,560 --> 00:22:09,600
Speaker 5: in the stock market, big increases in home equity for homeowners,

439
00:22:10,000 --> 00:22:15,359
Speaker 5: and that wealth effect is funding robust spending on discretionary

440
00:22:15,400 --> 00:22:20,159
Speaker 5: categories on new vehicles. New vehicle sales also helped along

441
00:22:20,200 --> 00:22:23,840
Speaker 5: by both fears of higher prices because the tariffs, and

442
00:22:23,880 --> 00:22:27,360
Speaker 5: then also the idea that maybe those incentives for EV

443
00:22:27,480 --> 00:22:31,880
Speaker 5: sales could go away. But in general, the average American

444
00:22:31,920 --> 00:22:35,639
Speaker 5: consumer is performing well. But that average is really being

445
00:22:35,760 --> 00:22:40,119
Speaker 5: held up by high income, high wealth, affluent households. And

446
00:22:40,200 --> 00:22:43,520
Speaker 5: if you look at the typical consumer, the media and consumer,

447
00:22:43,920 --> 00:22:47,000
Speaker 5: they are much more affected by the increase in rents,

448
00:22:47,080 --> 00:22:50,600
Speaker 5: by the increase in the cost of food and other

449
00:22:50,760 --> 00:22:55,720
Speaker 5: essentials and that side of the American consumer is struggling

450
00:22:55,720 --> 00:22:59,000
Speaker 5: to an extent still. I think it's been directionally a

451
00:22:59,040 --> 00:23:02,040
Speaker 5: little bit better over the last six to twelve months,

452
00:23:02,359 --> 00:23:06,440
Speaker 5: but if you look at high frequency measures of food insecurity,

453
00:23:06,520 --> 00:23:09,840
Speaker 5: for example, it does look like you see more stress

454
00:23:09,920 --> 00:23:13,360
Speaker 5: right now than you saw before the pandemic hit and

455
00:23:13,960 --> 00:23:15,720
Speaker 5: transform the US economy.

456
00:23:15,800 --> 00:23:17,399
Speaker 2: Bill will leave it there. Thank you so much for

457
00:23:17,480 --> 00:23:19,600
Speaker 2: joining us today. Bill Adams there. He is the chief

458
00:23:19,640 --> 00:23:22,760
Speaker 2: economist at Comerica Bank. Joining us here on the Daybreak

459
00:23:22,800 --> 00:23:28,600
Speaker 2: Asia Podcast. Thanks for listening to today's episode of the

460
00:23:28,600 --> 00:23:32,760
Speaker 2: Bloomberg Daybreak Asia Edition podcast. Each weekday, we look at

461
00:23:32,760 --> 00:23:37,280
Speaker 2: the story shaping markets, finance, and geopolitics in the Asia Pacific.

462
00:23:37,480 --> 00:23:40,800
Speaker 2: You can find us on Apple, Spotify, the Bloomberg Podcast

463
00:23:40,840 --> 00:23:44,200
Speaker 2: YouTube channel, or anywhere else you listen. Join us again

464
00:23:44,240 --> 00:23:47,560
Speaker 2: tomorrow for insight on the market moves from Hong Kong

465
00:23:47,680 --> 00:23:52,080
Speaker 2: to Singapore and Australia. I'm Doug Chrisner, and this is

466
00:23:52,119 --> 00:23:52,639
Speaker 2: Bloomberg