1
00:00:01,800 --> 00:00:04,400
Speaker 1: This is Bloomberg Business Week. I'm Carol Masser and I'm

2
00:00:04,440 --> 00:00:07,280
Speaker 1: Bloomberg Quick Takes Tim Stanivk. We're here every day bringing

3
00:00:07,280 --> 00:00:09,799
Speaker 1: you the latest news from the world of business and finance,

4
00:00:09,840 --> 00:00:13,640
Speaker 1: plus technology, politics, economics, all partnising the power of Business

5
00:00:13,640 --> 00:00:17,119
Speaker 1: Week reporters and editors, not to mention our journalists and

6
00:00:17,160 --> 00:00:20,000
Speaker 1: analyst in more than one twenty countries. You can download

7
00:00:20,000 --> 00:00:23,239
Speaker 1: Bloomberg Business Week and iTunes, SoundCloud, or Bloomberg dot Com.

8
00:00:23,400 --> 00:00:25,160
Speaker 1: You can also listen to our radio show at two

9
00:00:25,160 --> 00:00:27,840
Speaker 1: pm Eastern Time on Bloomberg Radio or watch us on

10
00:00:27,880 --> 00:00:33,280
Speaker 1: YouTube search Bloomberg Global News. We are certainly seeing stocks

11
00:00:33,320 --> 00:00:36,680
Speaker 1: really across the board trade hired today in a significant way.

12
00:00:36,880 --> 00:00:39,680
Speaker 1: Not participating as much though in that rally is shares

13
00:00:39,720 --> 00:00:41,720
Speaker 1: of Apple. They were down as much as four point

14
00:00:41,720 --> 00:00:44,800
Speaker 1: six percent at their lows today, still off those lows,

15
00:00:44,800 --> 00:00:47,239
Speaker 1: but still down about one point four And this has

16
00:00:47,240 --> 00:00:50,600
Speaker 1: to do with the Bloomberg exclusive, a story about Apple

17
00:00:50,600 --> 00:00:53,400
Speaker 1: backing off plans to increase production of its new iPhones

18
00:00:53,720 --> 00:00:56,040
Speaker 1: UH this year. This is according to folks in the nose.

19
00:00:56,080 --> 00:00:58,320
Speaker 1: So let's get to it with our Bloomberg News West

20
00:00:58,320 --> 00:01:01,480
Speaker 1: Coast correspondent Ludlow normally on the West coast, like for us,

21
00:01:01,520 --> 00:01:03,080
Speaker 1: he's on the East coast and is here in our

22
00:01:03,160 --> 00:01:06,160
Speaker 1: sto here's another one. I don't think we'll let go

23
00:01:06,160 --> 00:01:09,720
Speaker 1: back your stack, baby, what a treat. So what's going

24
00:01:09,760 --> 00:01:13,000
Speaker 1: on here? What do we know? And it's complicated in nuance,

25
00:01:13,120 --> 00:01:16,160
Speaker 1: but you know, sources tell us that just before the

26
00:01:16,160 --> 00:01:19,360
Speaker 1: iPhone four teen was announced, they went to supplies and said,

27
00:01:19,440 --> 00:01:22,200
Speaker 1: let's boost production by around six million units. We were

28
00:01:22,240 --> 00:01:24,720
Speaker 1: thinking it would be ninety million this year for the iPhone,

29
00:01:24,920 --> 00:01:27,800
Speaker 1: which was in line with last year. They requested the

30
00:01:27,920 --> 00:01:30,920
Speaker 1: supplies braced for an additional six million, and according to

31
00:01:30,959 --> 00:01:34,120
Speaker 1: our reporting, overnight they walked that back. And the concern

32
00:01:34,280 --> 00:01:36,720
Speaker 1: is that that great demand for this new handset that

33
00:01:36,760 --> 00:01:39,600
Speaker 1: they thought would be there actually didn't materialize. And we've

34
00:01:39,600 --> 00:01:41,720
Speaker 1: already had some evidence of that in the pre ordered numbers.

35
00:01:41,760 --> 00:01:44,399
Speaker 1: Two So when I look at Apple shares, they fell

36
00:01:44,440 --> 00:01:46,520
Speaker 1: as much as four point six percent, but they've been

37
00:01:46,520 --> 00:01:49,760
Speaker 1: steadily pairing their losses. And this doesn't sound like a

38
00:01:49,760 --> 00:01:53,480
Speaker 1: good story for Apple right, less demand for its highest

39
00:01:53,520 --> 00:01:56,360
Speaker 1: priced iPhones or for those super expensive high marking phones.

40
00:01:56,800 --> 00:01:59,559
Speaker 1: Yet it's not as bad as you might think either.

41
00:01:59,720 --> 00:02:02,840
Speaker 1: So the Cell side in particular is sanguine because most

42
00:02:02,920 --> 00:02:05,400
Speaker 1: of them were modeling for ninety million units anyway, So

43
00:02:05,440 --> 00:02:07,200
Speaker 1: they look at this report and they go, well, it

44
00:02:07,240 --> 00:02:10,280
Speaker 1: hasn't really changed anything for us. It's still ninety million.

45
00:02:10,720 --> 00:02:13,200
Speaker 1: There there are some specific pieces of reporting that's so

46
00:02:13,240 --> 00:02:17,360
Speaker 1: important that there's evidence that the consumer, particularly in China,

47
00:02:17,480 --> 00:02:19,919
Speaker 1: is going for that higher end model that the fourteen

48
00:02:20,040 --> 00:02:24,560
Speaker 1: pro Okay, So while there might be concerned about overall volume,

49
00:02:24,800 --> 00:02:26,920
Speaker 1: they are selling the more expensive hand set, and so

50
00:02:26,960 --> 00:02:29,200
Speaker 1: if they stick to that original ninety million goal, which

51
00:02:29,240 --> 00:02:31,799
Speaker 1: was modeled by the Street, then maybe those higher A

52
00:02:31,960 --> 00:02:34,640
Speaker 1: sps can boost the top line, even if just a little,

53
00:02:34,760 --> 00:02:37,080
Speaker 1: because they're selling more of them are more expensive. What

54
00:02:37,120 --> 00:02:38,800
Speaker 1: I thought was interesting, and I bet you picked up

55
00:02:38,800 --> 00:02:41,640
Speaker 1: on this our Bloomberg intelligence team, Ana Grana, you know,

56
00:02:41,680 --> 00:02:45,760
Speaker 1: reminding us um because this was about, oh, I guess

57
00:02:45,760 --> 00:02:47,960
Speaker 1: the belief that there was, as you said, China demand,

58
00:02:48,320 --> 00:02:51,000
Speaker 1: European demand weak. And he reminded us that those two

59
00:02:51,040 --> 00:02:55,400
Speaker 1: regions are about Apple's total sales eat. I mean that's massive, right,

60
00:02:55,400 --> 00:02:58,680
Speaker 1: So we need to think about macro stories here, right, Yeah,

61
00:02:58,720 --> 00:03:00,960
Speaker 1: this is the why do we care about this? And

62
00:03:01,000 --> 00:03:04,200
Speaker 1: it's the rich people buy iPhones, and even in a recession,

63
00:03:04,480 --> 00:03:07,160
Speaker 1: they still buy iPhones. What we're looking for is the

64
00:03:07,240 --> 00:03:09,720
Speaker 1: kind of bigger picture effect. We know that the smartphone

65
00:03:09,720 --> 00:03:13,760
Speaker 1: market is soft, particularly in China. The preorder data report

66
00:03:13,760 --> 00:03:16,960
Speaker 1: from Jeffreys this Monday showed wasn't great in China, but

67
00:03:17,040 --> 00:03:19,840
Speaker 1: good for the higher price models. We need some lens

68
00:03:19,960 --> 00:03:21,960
Speaker 1: with We know what the FED is doing, we know

69
00:03:22,040 --> 00:03:24,840
Speaker 1: about the outlook for recessions around the world and inflation.

70
00:03:25,280 --> 00:03:27,360
Speaker 1: What we do is we look to the company movement

71
00:03:27,400 --> 00:03:29,680
Speaker 1: and action to try and get another kind of read

72
00:03:29,720 --> 00:03:31,560
Speaker 1: on the consumer. And I think a lot of what

73
00:03:31,600 --> 00:03:34,440
Speaker 1: this story did would say things are pretty bad and

74
00:03:34,560 --> 00:03:36,720
Speaker 1: key key markets still they're going to sell a lot.

75
00:03:36,840 --> 00:03:38,640
Speaker 1: I always feel like, I know when you tempered back

76
00:03:38,680 --> 00:03:41,360
Speaker 1: the Apple numbers, but they still kind of blow me away. Yes,

77
00:03:41,400 --> 00:03:43,640
Speaker 1: even the expectations. If if it's a lower number, it's

78
00:03:43,640 --> 00:03:45,800
Speaker 1: still a lot of stuff. I like what Global Equities

79
00:03:45,800 --> 00:03:48,920
Speaker 1: Research said. They called Apple the first casualty of recession

80
00:03:49,200 --> 00:03:51,760
Speaker 1: and said that the collapse demand for these iPhones is

81
00:03:51,800 --> 00:03:54,240
Speaker 1: just a tip of the iceberg. You could see a

82
00:03:54,280 --> 00:03:57,520
Speaker 1: lot of layoffs across and through the Apple supply chain.

83
00:03:57,560 --> 00:04:00,120
Speaker 1: In the months to come yes and take this is

84
00:04:00,160 --> 00:04:02,440
Speaker 1: one part of a whole. The next piece of evidence

85
00:04:02,480 --> 00:04:05,800
Speaker 1: we looked to his Micron earnings Thursday. Why biggest maker

86
00:04:05,840 --> 00:04:08,720
Speaker 1: of memory chips d RAM also a huge supply to

87
00:04:08,760 --> 00:04:11,280
Speaker 1: Apple If their earnings are soft, more evidence that the

88
00:04:11,320 --> 00:04:14,520
Speaker 1: broader market for electronics slowing down. The one thing then

89
00:04:14,560 --> 00:04:16,680
Speaker 1: also intrigued by two when it comes to Apple is

90
00:04:16,680 --> 00:04:18,240
Speaker 1: that they have the ability to just call it. Their

91
00:04:18,240 --> 00:04:20,520
Speaker 1: suppliers say we want six million more and then a

92
00:04:20,520 --> 00:04:22,240
Speaker 1: couple of days or months later say you know what,

93
00:04:22,480 --> 00:04:25,120
Speaker 1: no scrap that we're not doing that anymore. And the

94
00:04:25,120 --> 00:04:28,080
Speaker 1: suppliers just have no not going to say, you're not

95
00:04:28,080 --> 00:04:30,360
Speaker 1: going to say that's fine. Whatever we plan to all

96
00:04:30,360 --> 00:04:32,440
Speaker 1: those people were going to bring in, we're not bring

97
00:04:32,440 --> 00:04:34,800
Speaker 1: them in now. And the equity pain was felt in Asia,

98
00:04:34,880 --> 00:04:37,440
Speaker 1: for those suppliers in Europe, for st micro in here

99
00:04:37,480 --> 00:04:40,160
Speaker 1: in the United States, and they all scrambled. We heard

100
00:04:40,200 --> 00:04:43,520
Speaker 1: from sources one supply completely shifted production to just the

101
00:04:43,520 --> 00:04:45,920
Speaker 1: pro the higher end. Well, what if that doesn't stick

102
00:04:45,960 --> 00:04:48,840
Speaker 1: and people end up wanting the cheaper models. Well, as

103
00:04:48,880 --> 00:04:51,000
Speaker 1: we reach out to Apple and look for some commentary

104
00:04:51,040 --> 00:04:52,920
Speaker 1: or some clarity on this, I mean, what is it,

105
00:04:53,160 --> 00:04:54,760
Speaker 1: you know, top of mind for you, if you're sitting

106
00:04:54,800 --> 00:04:57,000
Speaker 1: down with the CEO of Apple, what would you want

107
00:04:57,040 --> 00:04:58,839
Speaker 1: to be asking them right now other than to confirm

108
00:04:58,880 --> 00:05:01,719
Speaker 1: pla is this true? An Apple spokesperson declined to comment

109
00:05:01,720 --> 00:05:05,080
Speaker 1: for the story. You know, Apple is a company that's

110
00:05:05,080 --> 00:05:08,200
Speaker 1: had tremendous growth, and what we're talking about here is

111
00:05:08,240 --> 00:05:12,120
Speaker 1: flat unit growth ninety million last year this year. That's

112
00:05:12,120 --> 00:05:14,960
Speaker 1: a lot of iPhones. But at the top line, I

113
00:05:15,000 --> 00:05:18,720
Speaker 1: think that the consensus is for two revenue growth. That's

114
00:05:18,720 --> 00:05:20,680
Speaker 1: not what Apple does. You know, we've been through the

115
00:05:20,720 --> 00:05:23,840
Speaker 1: pandemic era cycle, we've been through the five G supercycle.

116
00:05:24,680 --> 00:05:26,599
Speaker 1: What's going to lift them up into that next phase

117
00:05:26,640 --> 00:05:29,719
Speaker 1: of growth? And there's a lot resting on people buying

118
00:05:29,839 --> 00:05:32,000
Speaker 1: the expensive Pro hand set. And that's why there's a

119
00:05:32,040 --> 00:05:33,960
Speaker 1: lot of questions about Tim Cook as well, because he's

120
00:05:34,000 --> 00:05:36,760
Speaker 1: not the visionary that Steve Jobs was. He's an incrementalist, right.

121
00:05:36,880 --> 00:05:40,039
Speaker 1: He makes the iPhones better and improves the guts, but

122
00:05:40,120 --> 00:05:43,000
Speaker 1: maybe not the actual aesthetic of the phone that people

123
00:05:43,000 --> 00:05:45,680
Speaker 1: get excited about. So the iPhone fourteen and the Pro,

124
00:05:45,800 --> 00:05:48,520
Speaker 1: the Pro had fancy camera features, very high speck but

125
00:05:48,600 --> 00:05:51,479
Speaker 1: what was the update. It was satellite enabled capabilities. If

126
00:05:51,520 --> 00:05:53,719
Speaker 1: you're stuck up a mountain or you're in the ocean,

127
00:05:54,080 --> 00:05:57,160
Speaker 1: you can connect via your iPhone. Very rich people. Right,

128
00:05:57,240 --> 00:05:59,599
Speaker 1: there's the thing. Who's that helping? Like? Is that going

129
00:05:59,680 --> 00:06:03,479
Speaker 1: to hiking up? It doesn't matter whether I will I

130
00:06:03,520 --> 00:06:05,560
Speaker 1: will say, like I'm looking to upgrade my phone again,

131
00:06:05,600 --> 00:06:08,240
Speaker 1: but I keep looking for something that's an incremental or

132
00:06:08,360 --> 00:06:11,880
Speaker 1: bigger boost a change. Um, and that that better camera

133
00:06:11,920 --> 00:06:14,320
Speaker 1: in the satellite capability doesn't do it for you. Camera

134
00:06:14,360 --> 00:06:17,120
Speaker 1: that does dishes is a laundry like that kind of thing. No,

135
00:06:17,240 --> 00:06:19,320
Speaker 1: but it's like it's an important stock to watch. But

136
00:06:19,360 --> 00:06:21,200
Speaker 1: I do think you guys are right. You pointed out

137
00:06:21,160 --> 00:06:23,560
Speaker 1: it was down four point six percent. It's lows. It's

138
00:06:23,560 --> 00:06:25,760
Speaker 1: come off of that with the overall rally. But um,

139
00:06:25,880 --> 00:06:28,640
Speaker 1: Redmont gun and stuff. He has all the details very early.

140
00:06:28,720 --> 00:06:30,760
Speaker 1: So yeah, yeah, to see him like a big scoop

141
00:06:30,760 --> 00:06:32,720
Speaker 1: by Bloomberg News, does seem a bit at the company

142
00:06:32,800 --> 00:06:35,440
Speaker 1: or something like he has lots of friends at Apple.

143
00:06:35,560 --> 00:06:38,679
Speaker 1: Oh my god, alright, folks, we gotta run low. Bloomberg

144
00:06:38,720 --> 00:06:41,280
Speaker 1: News West Coast correspondent. He is here on the East

145
00:06:41,320 --> 00:06:43,440
Speaker 1: Coast for a bit, joining us here in our interactive

146
00:06:43,440 --> 00:06:48,720
Speaker 1: broker studio. This is Bloomberg. This is Bloomberg Business Week

147
00:06:48,880 --> 00:06:52,880
Speaker 1: with Carol Masser and Bloomberg Quick Takes Tim Stinovic on

148
00:06:53,000 --> 00:06:56,039
Speaker 1: Bloomberg Radio. It's a story we covered big time yesterday

149
00:06:56,080 --> 00:06:58,680
Speaker 1: about what was up with using what's app that led

150
00:06:58,680 --> 00:07:01,239
Speaker 1: to surveillance failures across Wall Street. More than two billion

151
00:07:01,279 --> 00:07:04,719
Speaker 1: in fines already levied to a roster of firms including

152
00:07:04,720 --> 00:07:08,080
Speaker 1: b of A City, Goldman, Morgan Stanley, eleven Wall Street

153
00:07:08,080 --> 00:07:11,600
Speaker 1: banks in total prevailing to stop staff from using unauthorized

154
00:07:11,600 --> 00:07:14,040
Speaker 1: messaging platforms. Scarlett, this is one of our most read

155
00:07:14,080 --> 00:07:15,880
Speaker 1: stories on the Bloomberg today. I'm just looking at some

156
00:07:15,920 --> 00:07:17,480
Speaker 1: of the bank's named. It's hard to find a bank

157
00:07:17,600 --> 00:07:20,360
Speaker 1: that we know that's not included in this list. Hannah

158
00:07:20,400 --> 00:07:23,240
Speaker 1: Lovett has been following this story from the beginning and

159
00:07:23,360 --> 00:07:25,560
Speaker 1: she joins us. Now, Hannah, there's been more than two

160
00:07:25,560 --> 00:07:27,680
Speaker 1: billion dollars and finds levied so far, as Carol was

161
00:07:27,760 --> 00:07:30,600
Speaker 1: just saying, but the banks are now taking action in

162
00:07:30,640 --> 00:07:33,240
Speaker 1: a different way as well. They just opened the vault

163
00:07:33,240 --> 00:07:37,760
Speaker 1: to let her in and welcome um. What kind of

164
00:07:37,760 --> 00:07:42,000
Speaker 1: compliance steps of regulatory measures? Regulatory solutions are these banks

165
00:07:42,000 --> 00:07:44,960
Speaker 1: coming up with. Yeah, So beyond the fines that came

166
00:07:44,960 --> 00:07:48,640
Speaker 1: out in the orders yesterday, they agreed to um hire

167
00:07:49,200 --> 00:07:53,160
Speaker 1: compliance consultants to make sure that they're you know, monitoring

168
00:07:53,760 --> 00:07:57,200
Speaker 1: and preserving these messages lay, Yeah, to the extent that

169
00:07:57,200 --> 00:08:00,360
Speaker 1: they're supposed to be. And you know that the these

170
00:08:00,400 --> 00:08:03,280
Speaker 1: firms are required by law to do this. And that

171
00:08:03,360 --> 00:08:07,000
Speaker 1: was already um you know, becoming an issue just because

172
00:08:07,000 --> 00:08:09,680
Speaker 1: of the proliferation of these messaging apps UM you know

173
00:08:09,720 --> 00:08:12,600
Speaker 1: what's up signal you name it UM. So that was

174
00:08:12,600 --> 00:08:15,400
Speaker 1: already a thing pre COVID. And then if you think about,

175
00:08:15,440 --> 00:08:18,960
Speaker 1: you know, what happened in early when everyone was working

176
00:08:18,960 --> 00:08:22,040
Speaker 1: from home and like you know, you you went from

177
00:08:22,040 --> 00:08:24,080
Speaker 1: saying something to your colleague next to you to maybe

178
00:08:24,080 --> 00:08:26,640
Speaker 1: like tapping out a message. So that wasn't what started this,

179
00:08:26,680 --> 00:08:29,520
Speaker 1: but that definitely made it a bigger deal. I do

180
00:08:29,560 --> 00:08:31,120
Speaker 1: feel like it's part of our world, right, we were

181
00:08:31,120 --> 00:08:32,920
Speaker 1: talking before we got going. I mean, how often do

182
00:08:33,040 --> 00:08:36,200
Speaker 1: I like send myself to my Gmail or something something

183
00:08:36,240 --> 00:08:37,920
Speaker 1: I want to do for work or just a memory.

184
00:08:37,960 --> 00:08:41,000
Speaker 1: It's kind of what's fun about We're not fun? What's

185
00:08:41,000 --> 00:08:43,000
Speaker 1: interesting about the stories? We get more and more details.

186
00:08:43,160 --> 00:08:45,200
Speaker 1: Is we're finding out about the worst offenders. So what

187
00:08:45,240 --> 00:08:47,880
Speaker 1: do we know about them and what level and what

188
00:08:47,960 --> 00:08:49,280
Speaker 1: kinds of things they were doing? And do we know

189
00:08:49,440 --> 00:08:52,360
Speaker 1: names totally? Um, well, we don't know names. We don't

190
00:08:52,400 --> 00:08:55,200
Speaker 1: know names. Why not because they did not name them

191
00:08:55,240 --> 00:08:57,960
Speaker 1: in the orders. Okay. My suspicion is if they start

192
00:08:58,000 --> 00:09:00,400
Speaker 1: to name people, you'd get people the high at the

193
00:09:00,440 --> 00:09:02,600
Speaker 1: highest level, as you get all kinds of people like

194
00:09:02,640 --> 00:09:04,640
Speaker 1: who would not be ensnared in this right? I mean,

195
00:09:04,720 --> 00:09:07,200
Speaker 1: I think, you know, as demonstrated by like you said,

196
00:09:07,240 --> 00:09:10,320
Speaker 1: it was like virtually every major bank yesterday. And you know,

197
00:09:10,360 --> 00:09:13,080
Speaker 1: they said that the investigations on going, so there could

198
00:09:13,120 --> 00:09:18,160
Speaker 1: be more, but like you know, it was everywhere. I

199
00:09:18,200 --> 00:09:21,000
Speaker 1: think that was a general conclusion, um, And they did

200
00:09:21,000 --> 00:09:22,440
Speaker 1: this whole thing. You know, we had a story earlier

201
00:09:22,480 --> 00:09:25,680
Speaker 1: this year about how the US was mandating this look

202
00:09:25,800 --> 00:09:30,400
Speaker 1: this like strategic look across the board into you know,

203
00:09:30,520 --> 00:09:35,320
Speaker 1: thirty thirty five phones at each firm, um, and that

204
00:09:35,360 --> 00:09:37,000
Speaker 1: was mandated to kind of get a sense of the

205
00:09:37,040 --> 00:09:40,000
Speaker 1: magnitude of this and how much was happening. And clearly,

206
00:09:40,280 --> 00:09:42,520
Speaker 1: you know, they all ended up getting fined around the

207
00:09:42,559 --> 00:09:44,440
Speaker 1: same thing, like that's it's like, oh, you're all doing

208
00:09:44,440 --> 00:09:46,440
Speaker 1: it drilled down though, Like there's like tell us about

209
00:09:46,480 --> 00:09:48,280
Speaker 1: be of A and what we found out for you

210
00:09:48,400 --> 00:09:50,760
Speaker 1: because because the specifics to me are kind of interesting,

211
00:09:50,800 --> 00:09:52,839
Speaker 1: so we have an idea. Right. Also, they disclosed to

212
00:09:52,920 --> 00:09:55,640
Speaker 1: most and penalties as well. Right, they definitely the most

213
00:09:55,840 --> 00:09:58,040
Speaker 1: um they did, but they did by the CFCC, so

214
00:09:58,080 --> 00:10:00,480
Speaker 1: they their sec fine was the same everyone else and

215
00:10:00,480 --> 00:10:03,240
Speaker 1: the gosh a little more CFCC. But there's so so

216
00:10:03,280 --> 00:10:05,800
Speaker 1: basically the way that these things were structured was that

217
00:10:05,840 --> 00:10:07,480
Speaker 1: it was in order for each firm and there was

218
00:10:07,520 --> 00:10:09,880
Speaker 1: an area of like a couple of paragraphs where it

219
00:10:09,920 --> 00:10:12,040
Speaker 1: was the specifics for each firm. So be avail I'll

220
00:10:12,080 --> 00:10:14,880
Speaker 1: just look at it. Um a managing director at the

221
00:10:14,920 --> 00:10:17,600
Speaker 1: investment bank with the US wide role sent and received

222
00:10:17,640 --> 00:10:22,120
Speaker 1: thousands of messages including the colleagues, clients and personnelity other firms,

223
00:10:22,240 --> 00:10:25,400
Speaker 1: and then the head of an equity's trading desk texted

224
00:10:25,400 --> 00:10:27,520
Speaker 1: with more than fifty colleagues and numerous people outside the

225
00:10:27,520 --> 00:10:29,600
Speaker 1: firm and like so that was what be eviated. You

226
00:10:29,640 --> 00:10:32,280
Speaker 1: can go down the list and truly it was like

227
00:10:32,320 --> 00:10:34,240
Speaker 1: you know, this m D and this part of the

228
00:10:34,240 --> 00:10:37,680
Speaker 1: bank did you know send this many thousand messages to

229
00:10:37,880 --> 00:10:40,920
Speaker 1: these people and and it really was just every Yeah,

230
00:10:40,920 --> 00:10:44,200
Speaker 1: it was like copy and paste, you know. And you

231
00:10:44,280 --> 00:10:46,079
Speaker 1: guys reporting because you say when you're talking about be

232
00:10:46,320 --> 00:10:47,880
Speaker 1: and forgive me for singling it out, because if you

233
00:10:47,920 --> 00:10:52,560
Speaker 1: could pick a Scarlett said, uh Stanley, no, mora Ubs

234
00:10:52,880 --> 00:10:56,120
Speaker 1: City credit suite, it covers No, She's right, she covers

235
00:10:56,160 --> 00:11:00,199
Speaker 1: all ahead of a trading desk told brokers at others

236
00:11:00,240 --> 00:11:03,160
Speaker 1: to delete message they messages they had exchanged on personal

237
00:11:03,160 --> 00:11:05,560
Speaker 1: devices and to switch to signal, which, as we know,

238
00:11:05,679 --> 00:11:08,720
Speaker 1: is encrypted according to the CFTC. So is it just

239
00:11:08,800 --> 00:11:10,720
Speaker 1: a case of we were just kind of talking to

240
00:11:10,760 --> 00:11:13,400
Speaker 1: each other, we weren't trying to hide anything, or is

241
00:11:13,440 --> 00:11:15,959
Speaker 1: it something deeper? And that's why it's worries. I think

242
00:11:15,960 --> 00:11:17,920
Speaker 1: that's one of the things that TVD about this whole

243
00:11:17,960 --> 00:11:20,640
Speaker 1: investigation is like, you know, at this stage they're not

244
00:11:20,720 --> 00:11:24,160
Speaker 1: calling out wrongdoing, they're like found within the messages. They're

245
00:11:24,200 --> 00:11:26,880
Speaker 1: calling out the wrongdoing that is that these messages were

246
00:11:26,880 --> 00:11:29,319
Speaker 1: happening in the first place. But you know, when the

247
00:11:29,400 --> 00:11:31,800
Speaker 1: JPM order came out in December and again yesterday when

248
00:11:31,800 --> 00:11:34,839
Speaker 1: these came out, like it clearly states that the investigation

249
00:11:34,880 --> 00:11:36,520
Speaker 1: is ongoing, So I think that will be you know,

250
00:11:36,600 --> 00:11:39,680
Speaker 1: something that I will certainly be paying attention to going

251
00:11:39,720 --> 00:11:41,960
Speaker 1: forward is is what else might come out of this?

252
00:11:42,240 --> 00:11:44,560
Speaker 1: So when we say that the investigation is ongoing, do

253
00:11:44,640 --> 00:11:46,640
Speaker 1: we think do we suspect that there will be more

254
00:11:46,720 --> 00:11:49,840
Speaker 1: fines levied or will it be a case of the

255
00:11:49,880 --> 00:11:51,920
Speaker 1: banks will say yeah, yeah, yeah, we get that there's

256
00:11:51,960 --> 00:11:54,560
Speaker 1: a lot of wrongdoing. Let us figure out what we

257
00:11:54,600 --> 00:11:56,200
Speaker 1: need to do and come up with our own solutions.

258
00:11:56,440 --> 00:11:57,920
Speaker 1: That's a good question. You feel like what else? That

259
00:11:57,960 --> 00:12:01,280
Speaker 1: is a good question. I mean, I wouldn't necessarily rule

260
00:12:01,320 --> 00:12:04,280
Speaker 1: out any of that. I think that you know, a

261
00:12:04,320 --> 00:12:08,600
Speaker 1: lot of banks were named yesterday, some weren't, So we could,

262
00:12:08,679 --> 00:12:11,600
Speaker 1: you know, if if it's indeed ubiquitous a quad across

263
00:12:11,679 --> 00:12:13,880
Speaker 1: the industry as it as it seems, we might be

264
00:12:13,920 --> 00:12:16,720
Speaker 1: able to look there um and then beyond that. Yet

265
00:12:16,760 --> 00:12:19,920
Speaker 1: anything in the underlying messages that they would find, uh,

266
00:12:20,080 --> 00:12:21,720
Speaker 1: that would be a case of wrongdoing. But we haven't

267
00:12:21,720 --> 00:12:23,280
Speaker 1: gotten there that. I have a quick question, how can

268
00:12:23,320 --> 00:12:26,520
Speaker 1: you communicate with clients or colleagues then if you need

269
00:12:26,559 --> 00:12:29,720
Speaker 1: to use your device and just kind of about twenty seconds, Yeah, um,

270
00:12:29,760 --> 00:12:32,160
Speaker 1: I mean email. I think they have like an app

271
00:12:32,200 --> 00:12:34,760
Speaker 1: installed now that does the tracking so they can use that,

272
00:12:34,960 --> 00:12:38,199
Speaker 1: or like a company issued phone. Yes, so much just

273
00:12:38,240 --> 00:12:40,520
Speaker 1: put in place after the financial crisis. Will people be fired?

274
00:12:40,640 --> 00:12:42,480
Speaker 1: Do you think after this they were at drap Morgan

275
00:12:43,320 --> 00:12:45,800
Speaker 1: TBD or to come kind of levet you and the

276
00:12:45,800 --> 00:12:47,560
Speaker 1: team and the reporting has been really great on this

277
00:12:47,600 --> 00:12:50,439
Speaker 1: and we really appreciate getting an update. Or Hannah Levit,

278
00:12:50,440 --> 00:12:53,440
Speaker 1: she is financial reporter at Bloomberg News, joining us in

279
00:12:53,480 --> 00:12:59,000
Speaker 1: our interactive Broker studio. You're listening to Bloomberg Business Week

280
00:12:59,200 --> 00:13:02,600
Speaker 1: with Carol mass Her and Bloomberg Quick Takes Tim Stinovic

281
00:13:03,040 --> 00:13:05,880
Speaker 1: on Bloomberg Radio. Well, on a day where we are

282
00:13:05,920 --> 00:13:09,160
Speaker 1: focusing so much on Biogen and the very promising results

283
00:13:09,200 --> 00:13:12,280
Speaker 1: of that company's Alzheimer's drug, we are reminded once again

284
00:13:12,760 --> 00:13:15,640
Speaker 1: about those big biotech and big farmer names that continue

285
00:13:15,640 --> 00:13:17,960
Speaker 1: to work on better treatments, are new ones to tap

286
00:13:18,000 --> 00:13:20,720
Speaker 1: some of our major medical ailments. So that brings us

287
00:13:20,720 --> 00:13:22,280
Speaker 1: to a story in the upcoming a new issue of

288
00:13:22,360 --> 00:13:25,679
Speaker 1: Bloomberg Business Week. That's story already online at Bloomberg dot

289
00:13:25,720 --> 00:13:28,400
Speaker 1: com Slash business Week, and of course on the Bloomberg Terminal.

290
00:13:28,600 --> 00:13:30,480
Speaker 1: So let's get to it. It's about how big Pharma

291
00:13:30,640 --> 00:13:33,679
Speaker 1: is chasing a fifty five billion dollar prize of safer

292
00:13:33,720 --> 00:13:37,280
Speaker 1: blood thinners. The story from Bloomberg News healthcare reporter Angelica

293
00:13:37,480 --> 00:13:41,520
Speaker 1: Angelica Peebles. She's on the phone in San Diego. Hey, Angelica,

294
00:13:41,800 --> 00:13:44,000
Speaker 1: nice to have you here with Scarlet Food and myself.

295
00:13:44,040 --> 00:13:47,320
Speaker 1: So tell us about your story and what you set

296
00:13:47,320 --> 00:13:52,160
Speaker 1: out to do. Big Pharma is really searching for new

297
00:13:52,160 --> 00:13:54,880
Speaker 1: treatments for blood clots, and that's because we have some

298
00:13:55,000 --> 00:13:58,720
Speaker 1: really good treatments right now, namely Eloquence and z Arelto.

299
00:13:58,840 --> 00:14:01,080
Speaker 1: They are some of the best selling drugs in the world,

300
00:14:01,440 --> 00:14:05,199
Speaker 1: but they also carry some pretty big risks um namely bleeding.

301
00:14:05,320 --> 00:14:07,840
Speaker 1: It can take a variety of forms, whether that's just

302
00:14:08,000 --> 00:14:11,520
Speaker 1: bruising a little bit more easily, or in rare cases,

303
00:14:11,840 --> 00:14:14,920
Speaker 1: turning into brain bleeding, which can of course be lethal.

304
00:14:15,360 --> 00:14:18,280
Speaker 1: So it's just a really big prize out there for

305
00:14:18,320 --> 00:14:21,680
Speaker 1: these companies to create something that's just as effective as

306
00:14:21,680 --> 00:14:25,160
Speaker 1: the treatments we have now, but safer. And that's how

307
00:14:25,200 --> 00:14:28,960
Speaker 1: the companies landed on a different enzyme. It's called factor

308
00:14:29,000 --> 00:14:33,320
Speaker 1: eleven A, and basically there's this whole chain plotting system

309
00:14:33,360 --> 00:14:35,640
Speaker 1: in your body. We won't have We don't get into

310
00:14:35,640 --> 00:14:39,160
Speaker 1: all the details. But right now the main drugs target

311
00:14:39,200 --> 00:14:42,360
Speaker 1: one enzyme and now they're going after another, and it's

312
00:14:42,360 --> 00:14:47,800
Speaker 1: still relatively early. We just have um more recent data

313
00:14:48,080 --> 00:14:50,960
Speaker 1: and the companies still have to do these really big

314
00:14:51,000 --> 00:14:53,440
Speaker 1: trials to prove that they work. But if they do

315
00:14:53,920 --> 00:14:56,200
Speaker 1: UM it could mean a lot of companies and of

316
00:14:56,200 --> 00:14:59,040
Speaker 1: course for patients. So when we say big farmah, which

317
00:14:59,040 --> 00:15:02,000
Speaker 1: companies are doing the chasing hair, Which ones are investing

318
00:15:02,040 --> 00:15:04,880
Speaker 1: a lot of time and money into this. There are

319
00:15:04,880 --> 00:15:07,360
Speaker 1: a lot of companies in this game, but the biggest

320
00:15:07,400 --> 00:15:10,360
Speaker 1: ones that we're focusing on right now are Bristol Myers,

321
00:15:10,400 --> 00:15:13,400
Speaker 1: squib Johnson and Johnson and those two of our partners.

322
00:15:13,760 --> 00:15:16,640
Speaker 1: And then there which is of course the German company

323
00:15:16,680 --> 00:15:20,680
Speaker 1: behind Asprin, and those are the ones that are going

324
00:15:20,720 --> 00:15:24,440
Speaker 1: into these big trials UM and are. They're both working

325
00:15:24,440 --> 00:15:27,560
Speaker 1: on pills that you can take. There's another company called

326
00:15:27,600 --> 00:15:31,480
Speaker 1: Antos and they are spin out from nov Artists and

327
00:15:31,720 --> 00:15:35,440
Speaker 1: they are using UM biologic drugs, so it would be

328
00:15:35,720 --> 00:15:38,720
Speaker 1: infused or injected. I mean some of these names A

329
00:15:38,800 --> 00:15:41,240
Speaker 1: Delica are already bringing in some money for these big

330
00:15:41,240 --> 00:15:45,160
Speaker 1: farmer names, aren't they yeah, eloquence and are relative or

331
00:15:45,360 --> 00:15:49,280
Speaker 1: huge money makers, And they will lose their patent exclusivity

332
00:15:49,680 --> 00:15:51,960
Speaker 1: um within the next few years, and that means that

333
00:15:52,160 --> 00:15:54,760
Speaker 1: generic treatments will be able to come onto the market,

334
00:15:55,160 --> 00:15:59,480
Speaker 1: presumably undercutting the price, and that poses a big question

335
00:15:59,600 --> 00:16:02,880
Speaker 1: for those companies on how they'll replace that money, and

336
00:16:02,960 --> 00:16:06,200
Speaker 1: so they see these new drugs as a way to

337
00:16:06,240 --> 00:16:09,720
Speaker 1: fill that whole. Of course, um they'll have to compete

338
00:16:09,800 --> 00:16:13,000
Speaker 1: against the now the cheaper drugs that are already on

339
00:16:13,040 --> 00:16:15,760
Speaker 1: the market. But that's why it's so important to show

340
00:16:16,120 --> 00:16:19,400
Speaker 1: that these drugs are much safer, because if that's the case,

341
00:16:19,880 --> 00:16:23,120
Speaker 1: then they can treat far more patients people who right

342
00:16:23,160 --> 00:16:25,880
Speaker 1: now either can't or don't want to take a drug

343
00:16:26,000 --> 00:16:28,560
Speaker 1: that might um cause them to bleed out. God's a

344
00:16:28,640 --> 00:16:31,680
Speaker 1: bit if they cut themselves, cut themselves shaving, or something

345
00:16:31,720 --> 00:16:35,440
Speaker 1: along those lines, so it could expand the market for them.

346
00:16:35,480 --> 00:16:38,040
Speaker 1: It's interesting that big farms chasing this because we know

347
00:16:38,160 --> 00:16:40,560
Speaker 1: that in a lot of ailments UM it's often the

348
00:16:40,640 --> 00:16:43,040
Speaker 1: smaller biotech companies that are doing a lot of the

349
00:16:43,240 --> 00:16:47,920
Speaker 1: investing in some kind of new medical solution or some

350
00:16:48,000 --> 00:16:52,720
Speaker 1: kind of farmers pharmacist pharmacological solution to ems. Yeah, but

351
00:16:52,920 --> 00:16:55,240
Speaker 1: the fact that big farmers in here shows that the

352
00:16:55,240 --> 00:16:58,160
Speaker 1: potential to make money here is massive. Are there smaller

353
00:16:58,160 --> 00:17:01,200
Speaker 1: companies that are perhaps making headway doing anything interesting in

354
00:17:01,200 --> 00:17:05,760
Speaker 1: this space? There are smaller companies, Anthos being one of them.

355
00:17:05,800 --> 00:17:07,840
Speaker 1: Of course they came from a big barma company, but

356
00:17:07,880 --> 00:17:10,880
Speaker 1: they're doing it alone now, and there are more. But

357
00:17:11,040 --> 00:17:14,399
Speaker 1: really this is a perfect um perfect disease, a perfect

358
00:17:14,400 --> 00:17:18,560
Speaker 1: indication if you will, for big pharma because so many

359
00:17:18,640 --> 00:17:22,359
Speaker 1: people um experience blood clots. In fact, blood clots are

360
00:17:22,400 --> 00:17:26,320
Speaker 1: responsible um for an estimated one in four deaths worldwide,

361
00:17:26,359 --> 00:17:29,399
Speaker 1: which I was shocked to hear, And so that really

362
00:17:29,480 --> 00:17:32,880
Speaker 1: suits itself well for a big company to go after

363
00:17:33,080 --> 00:17:36,720
Speaker 1: running these trials will take thousands, if not you know,

364
00:17:36,800 --> 00:17:40,160
Speaker 1: many more patients around the world, and it will take

365
00:17:40,160 --> 00:17:43,159
Speaker 1: a lot of money to actually prove that these works.

366
00:17:43,200 --> 00:17:47,240
Speaker 1: That this is a perfect opportunity for big farma to play. Hey, Angelica,

367
00:17:47,240 --> 00:17:49,520
Speaker 1: is this part of kind of where finally reaping the

368
00:17:49,560 --> 00:17:52,680
Speaker 1: benefits of that huge mapping of the genome and really

369
00:17:52,720 --> 00:17:55,840
Speaker 1: just getting to understand on a much greater, deeper, smarter

370
00:17:56,000 --> 00:18:01,439
Speaker 1: level genetics in terms of creating methodologies or pharma or

371
00:18:01,520 --> 00:18:05,320
Speaker 1: treatments that really can target different individuals who maybe didn't

372
00:18:05,320 --> 00:18:09,280
Speaker 1: respond so well to a previous treatment. Good question, Thank you.

373
00:18:10,200 --> 00:18:14,240
Speaker 1: The way that UM scientists decided to factor or focus

374
00:18:14,280 --> 00:18:17,560
Speaker 1: on factor eleven a, which is that enzyme, is because

375
00:18:17,560 --> 00:18:20,400
Speaker 1: of genetic data, So that is UM. You know, this

376
00:18:20,440 --> 00:18:24,680
Speaker 1: is one example of how genetics are marrying drug development

377
00:18:24,720 --> 00:18:28,160
Speaker 1: and how we're using UM the information that our genetics

378
00:18:28,200 --> 00:18:32,399
Speaker 1: provide to create better drugs. And the scientists found was

379
00:18:32,440 --> 00:18:35,719
Speaker 1: that there were certain people who maybe they've led a

380
00:18:35,720 --> 00:18:37,959
Speaker 1: little bit more than your average person, say if they

381
00:18:37,960 --> 00:18:41,159
Speaker 1: were getting their teeth cleaned, but they didn't bleed as

382
00:18:41,240 --> 00:18:44,080
Speaker 1: much as people with other forms of hemophilia. And at

383
00:18:44,080 --> 00:18:47,240
Speaker 1: the same time, they appeared to be at less risk

384
00:18:47,280 --> 00:18:51,040
Speaker 1: of stroke than the normal population. And so that gave

385
00:18:51,160 --> 00:18:55,159
Speaker 1: scientists a clue that going after this particular enzyme and

386
00:18:55,160 --> 00:18:59,080
Speaker 1: actually blocking it could give you the benefit of, you know,

387
00:18:59,119 --> 00:19:04,680
Speaker 1: preventing blood without this unnecessary this added burden of potentially

388
00:19:05,480 --> 00:19:08,640
Speaker 1: unwanted bleeding. And so that was really how this all

389
00:19:08,680 --> 00:19:10,760
Speaker 1: came about, and we're just going to see more and

390
00:19:10,800 --> 00:19:14,200
Speaker 1: more of this going forward. So Angelica big picture, when

391
00:19:14,200 --> 00:19:16,919
Speaker 1: we talk about treatments for Alzheimer's, for instance, it very

392
00:19:17,000 --> 00:19:19,639
Speaker 1: much feels like one step for two steps for one

393
00:19:19,680 --> 00:19:23,760
Speaker 1: step back. What's the trajectory like for a new safer

394
00:19:23,800 --> 00:19:28,760
Speaker 1: blood than or is it similarly staggered and frustrating? Drug

395
00:19:28,760 --> 00:19:32,600
Speaker 1: development is never perfect, and companies will remind you oftentimes

396
00:19:32,680 --> 00:19:36,280
Speaker 1: that they fail more than they succeed. And what's interesting

397
00:19:36,359 --> 00:19:41,400
Speaker 1: about the Phase two data that Bear, as well as

398
00:19:41,480 --> 00:19:45,879
Speaker 1: the Silmyer, squib and Johnson and Johnson presented last month,

399
00:19:46,200 --> 00:19:51,000
Speaker 1: is that the drugs actually failed in their trial, and

400
00:19:51,680 --> 00:19:54,480
Speaker 1: that caused a lot of concern that maybe these don't

401
00:19:54,560 --> 00:19:57,720
Speaker 1: work as well as these thought they do. The company said, look,

402
00:19:57,840 --> 00:20:00,960
Speaker 1: these studies weren't powered to show just how well the

403
00:20:01,040 --> 00:20:03,600
Speaker 1: drugs work. It was more about finding the right dose

404
00:20:03,720 --> 00:20:06,640
Speaker 1: and making sure that they live up to their promise

405
00:20:06,680 --> 00:20:10,200
Speaker 1: of being safer. Um right now, there's a lot more

406
00:20:10,280 --> 00:20:14,280
Speaker 1: skepticism that they might not be everything that we thought

407
00:20:14,359 --> 00:20:17,840
Speaker 1: they would be. So if their Phase three trials are

408
00:20:17,920 --> 00:20:20,640
Speaker 1: not guaranteed to succeed by any means, and they could

409
00:20:20,720 --> 00:20:23,080
Speaker 1: very well fail, we'll have to see. Yeah, my brother

410
00:20:23,119 --> 00:20:24,720
Speaker 1: who worked in the pharmaceuticals for a long time and

411
00:20:24,800 --> 00:20:27,320
Speaker 1: we had debate about the cost of pharmaceuticals and treatments

412
00:20:27,440 --> 00:20:29,560
Speaker 1: is like, keep in mind that this takes a long

413
00:20:29,600 --> 00:20:31,280
Speaker 1: time to develop stuff, and a lot of stuff doesn't

414
00:20:31,280 --> 00:20:33,480
Speaker 1: pan out, so we'd always go kind of round and round.

415
00:20:33,560 --> 00:20:38,040
Speaker 1: It's like a lottery. Yeah. Bloomberg News healthcare reporter Angelica

416
00:20:38,040 --> 00:20:40,200
Speaker 1: Peoples judging us on the phone from San Diego. That

417
00:20:40,280 --> 00:20:42,320
Speaker 1: story in the upcoming new issue of Bloomberg Business Week

418
00:20:42,320 --> 00:20:45,760
Speaker 1: on newsstands tomorrow. Already online a Bloomberg dot com slash

419
00:20:45,800 --> 00:20:54,080
Speaker 1: Business weekend, of course, on the Bloomberg terminal brom Journal. Yeah,

420
00:20:54,080 --> 00:20:58,359
Speaker 1: but you let me drive? Oh no, no, no Ah

421
00:20:58,440 --> 00:21:04,880
Speaker 1: night please album Bobart Rivals. I want to drive. It's

422
00:21:04,880 --> 00:21:11,240
Speaker 1: a good question. This is good ride to the clothes

423
00:21:12,720 --> 00:21:17,760
Speaker 1: well radio, all right, everybody, just about ten minutes left

424
00:21:17,760 --> 00:21:19,720
Speaker 1: in today's trading session, and man, we are seeing some

425
00:21:19,800 --> 00:21:22,040
Speaker 1: buying here in the last few minutes of trading, as

426
00:21:22,080 --> 00:21:25,480
Speaker 1: Dug mansioned those equity averages well above two percent, two

427
00:21:25,480 --> 00:21:27,800
Speaker 1: point three percent higher on the SNP NAZDAC hired by

428
00:21:27,840 --> 00:21:29,800
Speaker 1: almost two and a half percent. We're pretty much at

429
00:21:29,840 --> 00:21:31,840
Speaker 1: our best levels of the session. This is we've seen

430
00:21:31,920 --> 00:21:34,880
Speaker 1: yields back off, so Let's get to it. Let's get

431
00:21:34,880 --> 00:21:37,359
Speaker 1: to the drive to the close with Doug Cioca, CEO

432
00:21:37,400 --> 00:21:40,000
Speaker 1: and partner at Cavar Capital Partners over a billion in

433
00:21:40,119 --> 00:21:44,280
Speaker 1: assets under management. He joins us on the phone in Leewood, Kansas,

434
00:21:44,600 --> 00:21:46,880
Speaker 1: uh and joins us on the phone from there. How

435
00:21:46,880 --> 00:21:50,080
Speaker 1: are you, Doug. I'm doing very well. How are you doing?

436
00:21:50,240 --> 00:21:52,720
Speaker 1: I'm doing okay, I'm doing okay. But I gotta ask

437
00:21:52,760 --> 00:21:55,240
Speaker 1: you something really important to happened here in New York City.

438
00:21:55,240 --> 00:21:57,159
Speaker 1: I don't know if everybody saw it, but our New

439
00:21:57,240 --> 00:22:01,280
Speaker 1: York City Mayor Eric Adams actually making some amends about

440
00:22:01,320 --> 00:22:04,840
Speaker 1: New York versus Kansas. Here's what he had to say.

441
00:22:05,040 --> 00:22:08,440
Speaker 1: New York has a brand and when people see it,

442
00:22:08,440 --> 00:22:11,200
Speaker 1: it means something. You know when we go there. It's

443
00:22:11,200 --> 00:22:19,240
Speaker 1: not Kansas doesn't have a brand when you go there. Okay,

444
00:22:19,240 --> 00:22:24,120
Speaker 1: you from Kansas out New York City Mayor Eric Adams

445
00:22:24,200 --> 00:22:26,520
Speaker 1: um having some fun about branding. But come on, Doug,

446
00:22:26,760 --> 00:22:28,879
Speaker 1: you know you are from Kansas. One of the reasons

447
00:22:28,880 --> 00:22:31,560
Speaker 1: I love talking to people around the country, especially when

448
00:22:31,560 --> 00:22:33,280
Speaker 1: it comes to markets in the economy, is we get

449
00:22:33,280 --> 00:22:37,680
Speaker 1: a different perspective. So come on in. Yeah, we were

450
00:22:37,720 --> 00:22:39,320
Speaker 1: shocked to learn that we were the land of no

451
00:22:39,480 --> 00:22:43,600
Speaker 1: brand the last night. Imagine it made its way around

452
00:22:43,600 --> 00:22:46,879
Speaker 1: our local media circuit, and so it's actually kind of

453
00:22:46,960 --> 00:22:49,480
Speaker 1: kicked up a lot of sort of spontaneous contributions to

454
00:22:49,520 --> 00:22:52,320
Speaker 1: define the brand of Kansas. And I don't know if

455
00:22:52,320 --> 00:22:56,320
Speaker 1: you want to invoke the national basketball champion Kansas Jayhawks

456
00:22:56,359 --> 00:22:59,399
Speaker 1: from this year, our agricultural contribution in the world, grade schools,

457
00:22:59,440 --> 00:23:02,760
Speaker 1: low crime, and lest us never forget the birthplace of

458
00:23:02,760 --> 00:23:06,360
Speaker 1: American treasure had left. So, oh my gosh, Oh that's

459
00:23:06,400 --> 00:23:08,040
Speaker 1: a good point. You know, I got thought of that.

460
00:23:08,160 --> 00:23:11,000
Speaker 1: You make a good point, good, a really good point. Um.

461
00:23:11,119 --> 00:23:13,240
Speaker 1: I gotta say I love the heartland. And like I said,

462
00:23:13,359 --> 00:23:15,240
Speaker 1: I love talking to people, especially when it comes to

463
00:23:15,280 --> 00:23:18,600
Speaker 1: financial markets and trying to get a grasp of what's

464
00:23:18,600 --> 00:23:21,119
Speaker 1: going on in terms of sentiment across the country. And

465
00:23:21,119 --> 00:23:23,240
Speaker 1: when we go to you, Doug, we get that. Tell us,

466
00:23:23,560 --> 00:23:25,200
Speaker 1: how does it feel in Kansas right now? Are you

467
00:23:25,280 --> 00:23:27,080
Speaker 1: guys have freaked out as much as we all are

468
00:23:27,160 --> 00:23:31,600
Speaker 1: about recession, fed moves, higher rates, what's going on overseas?

469
00:23:31,720 --> 00:23:34,680
Speaker 1: Give us give us some perspective here. Yeah, I think

470
00:23:34,720 --> 00:23:36,280
Speaker 1: all of that, I mean, and it is we know

471
00:23:36,359 --> 00:23:38,800
Speaker 1: I mean, being in the Midwest is wonderful and we

472
00:23:38,880 --> 00:23:41,240
Speaker 1: love sort of the set of values in the Midwestern

473
00:23:41,280 --> 00:23:45,160
Speaker 1: mentality and friendliness, but you know that the market is global,

474
00:23:45,240 --> 00:23:47,840
Speaker 1: and we feel as plugged in here is I think

475
00:23:47,880 --> 00:23:49,600
Speaker 1: I probably would if I was sitting in Chicago, New

476
00:23:49,640 --> 00:23:52,560
Speaker 1: York and London. So I think the way information makes

477
00:23:52,440 --> 00:23:54,680
Speaker 1: its way around the universe these days, and we don't

478
00:23:54,720 --> 00:23:58,240
Speaker 1: certainly don't feel disconnected, and the psyche of certainly our

479
00:23:58,320 --> 00:24:02,200
Speaker 1: clients is fragile. I think just the crossed asset class

480
00:24:02,240 --> 00:24:05,359
Speaker 1: correlation that has defined the first nine months of this

481
00:24:05,440 --> 00:24:09,359
Speaker 1: year has been really pronounced. And I think that unfortunately,

482
00:24:09,400 --> 00:24:13,679
Speaker 1: when when you have to go through some um expectation resetting,

483
00:24:14,000 --> 00:24:16,600
Speaker 1: when you get these resets and valuations, and you just

484
00:24:16,640 --> 00:24:19,359
Speaker 1: try to frame perspective on what that can mean well

485
00:24:19,400 --> 00:24:22,280
Speaker 1: into the future, and we're very optimistic, and I think,

486
00:24:22,320 --> 00:24:25,800
Speaker 1: unfortunately you have to plow through this um. It sounds

487
00:24:25,800 --> 00:24:28,320
Speaker 1: silly to be optimistic in the face of perspective recession

488
00:24:28,359 --> 00:24:30,000
Speaker 1: in a bare market, but we can't help but be

489
00:24:30,880 --> 00:24:33,760
Speaker 1: so you have to plow through this. And I wonder

490
00:24:33,840 --> 00:24:37,000
Speaker 1: there's this word disorder that comes up a lot these days. Uh,

491
00:24:37,240 --> 00:24:39,399
Speaker 1: Jenny Yellen says there's no disorder in the markets at

492
00:24:39,440 --> 00:24:42,040
Speaker 1: least stateside. Larry Summer says, yes, there was in the

493
00:24:42,119 --> 00:24:46,480
Speaker 1: UK bond market. Uh, but he sees risks of breakdowns

494
00:24:46,520 --> 00:24:49,919
Speaker 1: to come. How do investors prepare for that possibility of

495
00:24:49,960 --> 00:24:52,480
Speaker 1: breakdowns to come? Do you just sit in cash? You

496
00:24:52,600 --> 00:24:55,639
Speaker 1: move to cash? Do you uh sit tighten, not do anything.

497
00:24:55,720 --> 00:24:57,080
Speaker 1: Look at my four oh one kid, I kind of

498
00:24:57,080 --> 00:24:58,560
Speaker 1: wish I had moved to cash. I'm just gonna put

499
00:24:58,560 --> 00:25:02,040
Speaker 1: that out there. Yeah, I think we we could have

500
00:25:02,119 --> 00:25:04,359
Speaker 1: used an expression for a while and just talking about

501
00:25:04,400 --> 00:25:06,480
Speaker 1: managing for the short term and investing for the long

502
00:25:06,600 --> 00:25:09,000
Speaker 1: term and keeping a certain amount of capital out of

503
00:25:09,000 --> 00:25:12,000
Speaker 1: the path. That's insanity, I think is just prudent um

504
00:25:12,040 --> 00:25:15,399
Speaker 1: asset management. But I think more than anything, And and

505
00:25:15,520 --> 00:25:18,120
Speaker 1: you know, the feed seems to think that um, their

506
00:25:18,160 --> 00:25:21,080
Speaker 1: experimentation is not live. Right. This is not like a

507
00:25:21,160 --> 00:25:23,920
Speaker 1: randomized control trial or only one group of constituents is

508
00:25:23,960 --> 00:25:28,359
Speaker 1: impacted by their actions, right, their direct implications and many

509
00:25:28,359 --> 00:25:32,400
Speaker 1: indirect implications. Where right, no area of a globally intertwined

510
00:25:32,440 --> 00:25:34,040
Speaker 1: economy is going to be immune from some of the

511
00:25:34,040 --> 00:25:37,480
Speaker 1: things they're doing. And I heard an interview with Lizzianne

512
00:25:37,520 --> 00:25:40,320
Speaker 1: Saunders the other day, and she made a really good

513
00:25:40,359 --> 00:25:43,760
Speaker 1: point about the SET trying to differentiate between financial market

514
00:25:43,840 --> 00:25:48,639
Speaker 1: volatility and financial system instability. And I do think the

515
00:25:48,640 --> 00:25:52,879
Speaker 1: FED seems at best apesthetic to the former, but hopefully

516
00:25:53,000 --> 00:25:55,399
Speaker 1: you know not to the ladder, and with taking place

517
00:25:55,480 --> 00:25:58,080
Speaker 1: within the UK is a pretty good example of the ladder. Yeah,

518
00:25:58,160 --> 00:26:01,960
Speaker 1: financial market uh, movement volatility is certainly what we're seeing

519
00:26:02,040 --> 00:26:04,200
Speaker 1: right now. If you were to take a step back,

520
00:26:05,040 --> 00:26:06,960
Speaker 1: what is the what is the tail? What is the

521
00:26:07,000 --> 00:26:11,520
Speaker 1: dog here? What's driving what here? Yeah, it's a great question,

522
00:26:11,640 --> 00:26:13,960
Speaker 1: you know. I think what's interesting when you do take

523
00:26:14,000 --> 00:26:18,080
Speaker 1: the step back, right is if you if you are

524
00:26:18,520 --> 00:26:25,440
Speaker 1: kind of understanding accountability, which for the exercise is beneficial,

525
00:26:25,560 --> 00:26:28,000
Speaker 1: so you can ask your tave a pathway forward and

526
00:26:28,040 --> 00:26:30,959
Speaker 1: then you understand the accountability. Why we have inflation. We

527
00:26:31,040 --> 00:26:33,800
Speaker 1: had a lot on the demand side because coming out

528
00:26:33,800 --> 00:26:35,679
Speaker 1: of the pandemic, we had a bunch of stimulus that

529
00:26:35,760 --> 00:26:39,359
Speaker 1: justifiably came to the economy the bestically and globally and

530
00:26:39,880 --> 00:26:44,800
Speaker 1: likely overstayed uh the necessary point of being retained. And

531
00:26:44,840 --> 00:26:47,119
Speaker 1: then you have some of the externalities, right that have

532
00:26:47,200 --> 00:26:50,760
Speaker 1: taken place because of supply mind disruptions in Russia, Ukraine

533
00:26:50,760 --> 00:26:53,760
Speaker 1: and over in China, and I think what you try

534
00:26:53,800 --> 00:26:58,400
Speaker 1: to do is then find the combination of steps with

535
00:26:58,520 --> 00:27:01,040
Speaker 1: extraction of liquidity, being mindful of the things that are

536
00:27:01,040 --> 00:27:03,359
Speaker 1: out of your control, and then use a term that

537
00:27:03,440 --> 00:27:05,960
Speaker 1: Powell used in his press conference four times but it

538
00:27:06,000 --> 00:27:10,440
Speaker 1: is not actually incorporated into practice, understand that the implementation

539
00:27:10,560 --> 00:27:13,840
Speaker 1: is going to be long and variable, and that would

540
00:27:13,880 --> 00:27:17,360
Speaker 1: require a set of patients to understand the direct impact

541
00:27:17,440 --> 00:27:20,160
Speaker 1: of some of these military policy initiatives. If you had

542
00:27:20,280 --> 00:27:23,520
Speaker 1: that opportunity, I think you take a little the volatility

543
00:27:23,520 --> 00:27:26,560
Speaker 1: out of the system, but you restore much more needed

544
00:27:26,600 --> 00:27:29,960
Speaker 1: stability to this. Hey, Doug, what's a smart metric to

545
00:27:30,040 --> 00:27:31,959
Speaker 1: keep an eye on for investors? Where I feel like

546
00:27:32,280 --> 00:27:34,760
Speaker 1: the metrics is a lot of volatility in them, and

547
00:27:34,760 --> 00:27:37,240
Speaker 1: I'm not quite sure what we should be focusing on

548
00:27:37,280 --> 00:27:41,119
Speaker 1: at this point. You know what's been fascinating curls this week?

549
00:27:41,680 --> 00:27:44,880
Speaker 1: Despite the hawkersh tone of the FED meeting, follow through

550
00:27:44,920 --> 00:27:48,320
Speaker 1: at that FED Lessons event on Friday, and then reinforce

551
00:27:48,400 --> 00:27:52,760
Speaker 1: through harsh language of Mester Cash Carrian Bullard, the terminal

552
00:27:52,880 --> 00:27:56,239
Speaker 1: rate projection has dropped every day this week and now

553
00:27:56,320 --> 00:27:58,600
Speaker 1: from the four point four for March and next year

554
00:27:58,960 --> 00:28:01,879
Speaker 1: because the market thinks this said we'll see the fruits

555
00:28:01,880 --> 00:28:04,359
Speaker 1: of its labor comes through in better cp I PC

556
00:28:04,960 --> 00:28:08,720
Speaker 1: or job reads or the realization of these global ramifications

557
00:28:08,760 --> 00:28:11,120
Speaker 1: courtesy what took place in the UK, and that may

558
00:28:11,240 --> 00:28:13,520
Speaker 1: cause the said to pause, right, maybe a little bit

559
00:28:13,560 --> 00:28:16,080
Speaker 1: ahead of at SCP projections, right. I think that would

560
00:28:16,119 --> 00:28:19,120
Speaker 1: be a really good thanks for them to deliberate about doing.

561
00:28:19,240 --> 00:28:21,800
Speaker 1: That's interesting, which also I keep thinking about what Charlie

562
00:28:21,840 --> 00:28:25,080
Speaker 1: Evans told CNBC in terms of maybe uh FED rate

563
00:28:25,119 --> 00:28:29,680
Speaker 1: moves potentially topping out come March. Doug Cioca, we love you,

564
00:28:29,720 --> 00:28:32,439
Speaker 1: We love Kansas, chief executive officer partner at of Our

565
00:28:32,520 --> 00:28:35,680
Speaker 1: Capital Partners, joining us on the phone from Leewood, Kansas.

566
00:28:35,720 --> 00:28:38,400
Speaker 1: He's got about a billion dollars more than that under

567
00:28:38,480 --> 00:28:42,920
Speaker 1: management at his firm. Thanks for listening to Bloomberg Business Week.

568
00:28:43,040 --> 00:28:46,520
Speaker 1: Download the podcast on iTunes, SoundCloud, or Bloomberg dot com,

569
00:28:46,640 --> 00:28:48,320
Speaker 1: and you can also listen to our radio show at

570
00:28:48,320 --> 00:28:50,920
Speaker 1: two pm Eastern on Bloomberg Radio or watch us on

571
00:28:50,960 --> 00:28:52,960
Speaker 1: YouTube search Bloomberg Global News