1
00:00:01,360 --> 00:00:04,120
Speaker 1: Welcome to the Bloomberg Markets Podcast. I'm Paul Sweeney. Along

2
00:00:04,120 --> 00:00:06,200
Speaker 1: with my co host of Bonnie Quinn. Every business day

3
00:00:06,240 --> 00:00:10,320
Speaker 1: we bring you interviews from CEO, market pros and Bloomberg experts,

4
00:00:10,400 --> 00:00:13,600
Speaker 1: along with essential market moving news. Find the Bloomberg Markets

5
00:00:13,600 --> 00:00:17,000
Speaker 1: Podcast on Apple Podcasts or wherever you listen to podcasts,

6
00:00:17,000 --> 00:00:21,120
Speaker 1: and on Bloomberg dot com. What a market it's been

7
00:00:21,280 --> 00:00:25,680
Speaker 1: so far in obviously that huge sell off when the

8
00:00:25,680 --> 00:00:30,240
Speaker 1: pandemic hit, but then a arguably equally impressive rebound off

9
00:00:30,240 --> 00:00:32,720
Speaker 1: of the bottom, leaving a lot of investors to say, Okay,

10
00:00:33,120 --> 00:00:35,519
Speaker 1: now what as we look forward? We certainly have somebody

11
00:00:35,560 --> 00:00:37,920
Speaker 1: here who can help us answer that question. We have

12
00:00:37,960 --> 00:00:41,280
Speaker 1: Phil Orlando, chief equity market strategist and head of Client

13
00:00:41,320 --> 00:00:45,199
Speaker 1: portfolio Management at Federated at Hermes UH sixty eight billion

14
00:00:45,240 --> 00:00:49,080
Speaker 1: dollars in equity under management about six hundred billion firm

15
00:00:49,280 --> 00:00:52,400
Speaker 1: wide across all assets, joining us on the phone. Phil,

16
00:00:52,440 --> 00:00:55,000
Speaker 1: thanks so much for joining us here again on the

17
00:00:55,080 --> 00:01:01,680
Speaker 1: back of the another challenging and disappointing jobs number today.

18
00:01:02,200 --> 00:01:04,720
Speaker 1: You know, the bears out there as it relates to

19
00:01:04,720 --> 00:01:08,080
Speaker 1: the economic recovery have some more ammunition. What do you think, UH,

20
00:01:08,319 --> 00:01:11,880
Speaker 1: the equity markets are looking at at this moment, Well,

21
00:01:11,920 --> 00:01:15,160
Speaker 1: the equity markets are actually rallying a little bit in

22
00:01:15,160 --> 00:01:18,000
Speaker 1: the last fifteen minutes. And let me let me put

23
00:01:18,120 --> 00:01:21,039
Speaker 1: your your just your left comment there in some context.

24
00:01:21,080 --> 00:01:23,639
Speaker 1: So today's data was a bit of a mixed bag.

25
00:01:24,120 --> 00:01:26,720
Speaker 1: The Philly Set index was a bit of a disappointment.

26
00:01:27,040 --> 00:01:30,200
Speaker 1: You looked at the claims on the surface, the initial

27
00:01:30,280 --> 00:01:32,560
Speaker 1: claims were higher than we expected, but that was a

28
00:01:32,640 --> 00:01:37,120
Speaker 1: seasonally adjusted number. If you looked at the raw unseasonably

29
00:01:37,160 --> 00:01:41,400
Speaker 1: adjusted number, that number was down around which which was

30
00:01:41,600 --> 00:01:45,720
Speaker 1: what we were looking for. The continuing claims have continued

31
00:01:45,760 --> 00:01:48,600
Speaker 1: to come down. That's good news. And and just at

32
00:01:48,640 --> 00:01:51,080
Speaker 1: ten o'clock we got a blowout number out of the

33
00:01:51,200 --> 00:01:55,200
Speaker 1: l EI, the Leading Economic Index. The June reading was

34
00:01:55,240 --> 00:01:58,400
Speaker 1: revised up from a two percent gain to a three

35
00:01:58,400 --> 00:02:01,920
Speaker 1: percent gain and I came in stronger than expected at

36
00:02:01,920 --> 00:02:05,640
Speaker 1: one point four percent. So the bears will certainly look

37
00:02:05,640 --> 00:02:09,000
Speaker 1: at the fact that the initial weekly claims number was

38
00:02:09,000 --> 00:02:11,480
Speaker 1: was not where we wanted it to be, but there

39
00:02:11,480 --> 00:02:15,320
Speaker 1: are some other issues around that that. On balanced, today's

40
00:02:15,360 --> 00:02:18,520
Speaker 1: data dump wasn't that bad and the market is rallying

41
00:02:18,560 --> 00:02:21,760
Speaker 1: in the last fifteen minutes or so after we got

42
00:02:21,800 --> 00:02:24,799
Speaker 1: this l e I number. So, Phil, what do you

43
00:02:24,840 --> 00:02:26,560
Speaker 1: do on a day like today? Do you try and

44
00:02:26,600 --> 00:02:29,000
Speaker 1: do some some day trades or do you stick with

45
00:02:29,040 --> 00:02:32,280
Speaker 1: the plan to may and hold. No, you just you

46
00:02:32,960 --> 00:02:36,079
Speaker 1: you'd get you drive yourself crazy if you're trying to

47
00:02:36,200 --> 00:02:40,720
Speaker 1: day trade this market. Just focus upon the bigger trends.

48
00:02:40,760 --> 00:02:43,160
Speaker 1: And I think Paul laid this out beautifully. At the

49
00:02:43,240 --> 00:02:48,160
Speaker 1: very beginning, we had the sharpest decline from a record

50
00:02:48,240 --> 00:02:51,760
Speaker 1: hid to a bear market in history, down thirty from

51
00:02:52,000 --> 00:02:54,680
Speaker 1: mid February to mid March, and then over the last

52
00:02:54,720 --> 00:02:59,280
Speaker 1: five months the market's up. We've had the most powerful

53
00:03:00,120 --> 00:03:04,440
Speaker 1: rebound from a bear market to an all time record

54
00:03:04,520 --> 00:03:08,000
Speaker 1: high in history. Um, we still think that our our

55
00:03:08,040 --> 00:03:11,400
Speaker 1: target of the SMP this ue was thirty. We're a

56
00:03:11,440 --> 00:03:14,600
Speaker 1: little bit under the thirty four hundred level right now.

57
00:03:15,160 --> 00:03:17,480
Speaker 1: I think the market is going to continue to grind

58
00:03:17,600 --> 00:03:20,040
Speaker 1: up over the course of the next couple of months. Look,

59
00:03:20,320 --> 00:03:22,519
Speaker 1: the easy money has been made. We're not going to

60
00:03:22,600 --> 00:03:25,280
Speaker 1: be up another fifty in between now and the end

61
00:03:25,320 --> 00:03:28,000
Speaker 1: of the year. But I think the bias is higher

62
00:03:28,680 --> 00:03:31,120
Speaker 1: based upon the fact that the trough of the cycle

63
00:03:31,720 --> 00:03:34,120
Speaker 1: was you know, back in March and April, and the

64
00:03:34,200 --> 00:03:38,160
Speaker 1: numbers are getting you know, better over time, alright, So Phil,

65
00:03:38,240 --> 00:03:42,440
Speaker 1: if there's numbers getting better, the economy is slowly coming

66
00:03:42,480 --> 00:03:45,680
Speaker 1: out of that funk we had, that sharp contraction we

67
00:03:45,720 --> 00:03:48,160
Speaker 1: had with the pandemic initially hit. What are some of

68
00:03:48,160 --> 00:03:50,840
Speaker 1: the sectors that investors perhaps should be looking at here,

69
00:03:51,240 --> 00:03:53,119
Speaker 1: you know, let's let's assume they don't own the big

70
00:03:53,160 --> 00:03:56,120
Speaker 1: six or seven tech names. So one of the things

71
00:03:56,120 --> 00:03:59,160
Speaker 1: that that we did as a firm had federated Hermes

72
00:03:59,680 --> 00:04:04,440
Speaker 1: again about two weeks ago, was we're still two percent

73
00:04:04,680 --> 00:04:09,680
Speaker 1: overweight stocks overall in our balanced delecation model, but we

74
00:04:09,760 --> 00:04:14,200
Speaker 1: took a percentage point out of domestic large cap growth

75
00:04:14,240 --> 00:04:19,160
Speaker 1: and added it to domestic large cap value. Value has

76
00:04:19,360 --> 00:04:24,920
Speaker 1: underperformed growth by twenty one percentage points since the bottom

77
00:04:24,920 --> 00:04:28,400
Speaker 1: of the cycle on Marche. We think that gap is

78
00:04:28,440 --> 00:04:30,800
Speaker 1: going to close over the course of the next say,

79
00:04:30,880 --> 00:04:34,480
Speaker 1: twelve to eighteen months. So so we still like technology,

80
00:04:34,680 --> 00:04:36,839
Speaker 1: but just not the things. There are a lot of

81
00:04:36,839 --> 00:04:39,880
Speaker 1: other technology stocks that are still doing well. We still

82
00:04:39,880 --> 00:04:44,560
Speaker 1: like healthcare, but we think that financial services and industrials

83
00:04:44,600 --> 00:04:47,880
Speaker 1: and consumer discretionary are going to get some love here

84
00:04:48,080 --> 00:04:51,960
Speaker 1: as as the market begins to look at what doesn't

85
00:04:52,040 --> 00:04:56,159
Speaker 1: have a name like Apple and Amazon and Microsoft and

86
00:04:56,240 --> 00:05:00,760
Speaker 1: Netflix and Google and and maybe hasn't had a valuation

87
00:05:00,839 --> 00:05:04,000
Speaker 1: completely exploited. So give me a good reason as to

88
00:05:04,240 --> 00:05:08,280
Speaker 1: why it should, because Phil, it feels like, well, I mean,

89
00:05:08,279 --> 00:05:10,159
Speaker 1: the value investors at the very least that I've been

90
00:05:10,160 --> 00:05:11,880
Speaker 1: speaking to over the last six months to a year

91
00:05:11,920 --> 00:05:15,719
Speaker 1: or two more have been waiting for that moment, but

92
00:05:15,720 --> 00:05:18,000
Speaker 1: it hasn't come yet. Well, and I think that moment

93
00:05:18,080 --> 00:05:21,760
Speaker 1: is now because the reality is that that the five

94
00:05:21,839 --> 00:05:25,480
Speaker 1: or six Fang stocks, which now account for something like

95
00:05:26,600 --> 00:05:28,840
Speaker 1: the market cap of the S and P, have had

96
00:05:28,880 --> 00:05:32,960
Speaker 1: a phenomenal move. Those stocks have all doubled um. You know,

97
00:05:33,040 --> 00:05:35,680
Speaker 1: we have not seen anywhere near that kind of a

98
00:05:35,720 --> 00:05:39,240
Speaker 1: rebound in these other sectors that we talked about yet

99
00:05:39,279 --> 00:05:43,360
Speaker 1: from an underlying fundamental standpoint, we've got v bottom recoveries

100
00:05:43,880 --> 00:05:46,600
Speaker 1: in the housing market and in the auto market. We've

101
00:05:46,640 --> 00:05:50,359
Speaker 1: got powerful recoveries we're seeing with a lot of the

102
00:05:50,400 --> 00:05:53,880
Speaker 1: financial service companies, a lot of the consumer discretionary companies,

103
00:05:54,000 --> 00:05:56,920
Speaker 1: but that's not fully reflected in their share prices. So

104
00:05:57,000 --> 00:05:59,760
Speaker 1: investors are are going to be sifting through the rubble

105
00:05:59,839 --> 00:06:03,839
Speaker 1: here and saying, okay, so maybe the worst the coronavirus

106
00:06:03,960 --> 00:06:08,720
Speaker 1: is behind us UH and and where there's still some

107
00:06:08,800 --> 00:06:12,720
Speaker 1: attractive valuations left. And I think we've got to conclude

108
00:06:12,720 --> 00:06:15,359
Speaker 1: that the thanks stocks have done really well, but those

109
00:06:15,400 --> 00:06:18,520
Speaker 1: five or six stocks are not the entire stock market.

110
00:06:18,560 --> 00:06:21,560
Speaker 1: There are other companies that deserve to get back to

111
00:06:21,800 --> 00:06:25,279
Speaker 1: normal valuation levels over the course of the next twelve

112
00:06:25,320 --> 00:06:28,640
Speaker 1: to eighteen months. Phil, it's always a pleasure of speaking

113
00:06:28,640 --> 00:06:32,159
Speaker 1: to you, and don't go completely crazy watching this market today,

114
00:06:32,279 --> 00:06:37,039
Speaker 1: Phil Orlando federated Herme's investors. I hear him though, Paul,

115
00:06:37,120 --> 00:06:39,280
Speaker 1: it's a difficult market to trade, you know. I mean

116
00:06:39,279 --> 00:06:41,640
Speaker 1: you just you watch the same type of trade happened

117
00:06:41,720 --> 00:06:43,280
Speaker 1: day after day after day, and you have there's so

118
00:06:43,360 --> 00:06:48,920
Speaker 1: much uncertainty out there. Well, today i'm Eastern Migualte leading

119
00:06:48,960 --> 00:06:51,640
Speaker 1: index of Economic Indicators and it was better than anticipated

120
00:06:51,680 --> 00:06:54,560
Speaker 1: in July, coming in at positive one point four percent.

121
00:06:54,720 --> 00:06:58,320
Speaker 1: JUNS reading was revised up to three percent from two percent,

122
00:06:58,480 --> 00:07:02,599
Speaker 1: so all told, not too shabby. Let's bring in somebody

123
00:07:02,640 --> 00:07:05,560
Speaker 1: from the Conference Board. Atomana Zildrim a Senior director of

124
00:07:05,600 --> 00:07:08,920
Speaker 1: Economics and Global Research at the Conference Board and you

125
00:07:08,960 --> 00:07:11,600
Speaker 1: can tell us a little bit more about the subcomponents, Adoman,

126
00:07:11,680 --> 00:07:14,400
Speaker 1: Thanks for joining. Was there anything in the leading index

127
00:07:14,480 --> 00:07:18,240
Speaker 1: that set off alarm bells for you? Hi, good morning,

128
00:07:18,480 --> 00:07:21,600
Speaker 1: Thanks for having me on the program. Um. Well, you know,

129
00:07:21,640 --> 00:07:25,520
Speaker 1: when you look at the leading index, it is encouraging

130
00:07:25,560 --> 00:07:28,200
Speaker 1: news that you know, we've got a third consecutive month

131
00:07:28,280 --> 00:07:32,240
Speaker 1: of increase, but that increases coming in at a slower

132
00:07:32,280 --> 00:07:35,200
Speaker 1: pace than the sharp increases that we saw in the

133
00:07:35,240 --> 00:07:41,000
Speaker 1: previous two months. So that might suggest that the recovery

134
00:07:41,400 --> 00:07:44,680
Speaker 1: is going to be losing steam going forward. So we

135
00:07:44,760 --> 00:07:49,480
Speaker 1: haven't seen sort of the same momentum continuing in the

136
00:07:49,560 --> 00:07:53,280
Speaker 1: leading indicators. All right, So, Automan, we also had today,

137
00:07:53,520 --> 00:07:56,040
Speaker 1: I had some jobless numbers come in. Uh you know,

138
00:07:56,120 --> 00:07:59,920
Speaker 1: still uh north of a million jobless claims here. Talk

139
00:08:00,040 --> 00:08:04,480
Speaker 1: just about kind of your view of the labor market here. Yeah,

140
00:08:04,520 --> 00:08:07,600
Speaker 1: so the labor markets are obviously the the part of

141
00:08:07,640 --> 00:08:11,800
Speaker 1: the economy that are uh showing the most pick up

142
00:08:11,880 --> 00:08:18,800
Speaker 1: in leading indicators. Great contributions there, um, but there's still uh,

143
00:08:18,840 --> 00:08:22,120
Speaker 1: you know, a lot of fragility in those labor markets

144
00:08:22,480 --> 00:08:27,640
Speaker 1: really depending on the measures to contain the pandemic. Um.

145
00:08:27,760 --> 00:08:30,560
Speaker 1: You know, when you look at UH. We've done some

146
00:08:30,600 --> 00:08:35,000
Speaker 1: analysis across all fifties states. UH. And you know, the

147
00:08:35,040 --> 00:08:38,959
Speaker 1: infection rates in about fifteen of those states UM are

148
00:08:39,040 --> 00:08:42,559
Speaker 1: in the green zone. They've come down, but the rest

149
00:08:42,600 --> 00:08:46,680
Speaker 1: of them are still showing a spreading virus. And those

150
00:08:46,720 --> 00:08:51,400
Speaker 1: amounts to about of economic output produced by those states

151
00:08:51,440 --> 00:08:54,920
Speaker 1: when you put them all together. UM. So that does

152
00:08:55,000 --> 00:08:59,280
Speaker 1: pose a major risk for having to have more furloughs

153
00:08:59,320 --> 00:09:03,000
Speaker 1: and layoffs and a fragile states for the labor markets. Yeah.

154
00:09:03,040 --> 00:09:05,280
Speaker 1: And of course we already saw the initial doubles claims

155
00:09:05,320 --> 00:09:09,080
Speaker 1: take up last week. So there are ten components to

156
00:09:09,280 --> 00:09:13,200
Speaker 1: the Leading Economic Index, including things like average weekly hours

157
00:09:13,200 --> 00:09:17,000
Speaker 1: from manufacturing, you know, manufacturers, new orders, and then other

158
00:09:17,040 --> 00:09:20,400
Speaker 1: things like the leading credit Index. Give us a clue

159
00:09:20,559 --> 00:09:24,599
Speaker 1: as to where you're spotting the most fragilities in the subcomponents.

160
00:09:26,120 --> 00:09:29,280
Speaker 1: Right in the latest months, UM, the sort of negative

161
00:09:29,320 --> 00:09:33,640
Speaker 1: contributions are coming from UM, you know, some of those

162
00:09:34,040 --> 00:09:39,720
Speaker 1: indicators of financial conditions UM, and also from new orders

163
00:09:39,720 --> 00:09:45,760
Speaker 1: and manufacturing UM. But maybe most importantly is consumers outlook

164
00:09:46,480 --> 00:09:50,520
Speaker 1: for business conditions UH. And consumers are really affected by

165
00:09:50,600 --> 00:09:54,160
Speaker 1: what's going on in the labor markets of high unemployment

166
00:09:54,280 --> 00:09:58,520
Speaker 1: rates and that keeps their confidence level low. And uh,

167
00:09:58,559 --> 00:10:01,000
Speaker 1: and that's why you know, at the confer Sport, we're

168
00:10:01,080 --> 00:10:05,840
Speaker 1: thinking that the the final months of the year is

169
00:10:05,960 --> 00:10:10,000
Speaker 1: going to see a recovery that's losing steam and maybe

170
00:10:10,040 --> 00:10:16,120
Speaker 1: even we might see UH negative GDP growth rates continuing. Alright,

171
00:10:16,160 --> 00:10:20,200
Speaker 1: So so Automan, I guess the question for a lot

172
00:10:20,200 --> 00:10:22,199
Speaker 1: of people is are we still in a recession or

173
00:10:22,200 --> 00:10:25,320
Speaker 1: are we in the early stages of a recovery? And

174
00:10:25,320 --> 00:10:28,840
Speaker 1: how fragile is that recovery? I guess yeah, Well, as

175
00:10:28,880 --> 00:10:33,360
Speaker 1: you know, the recession started in in February, UM, and

176
00:10:33,640 --> 00:10:38,000
Speaker 1: when you look at the coincident indicators, which are kind

177
00:10:38,000 --> 00:10:40,400
Speaker 1: of the indicative of whether we're in a recession or not,

178
00:10:40,880 --> 00:10:45,400
Speaker 1: we see the same type of rebound in those UM,

179
00:10:45,480 --> 00:10:49,120
Speaker 1: but they're still showing an economy that's in a deep hole.

180
00:10:49,280 --> 00:10:51,600
Speaker 1: There's still a long way to climb out of that.

181
00:10:52,360 --> 00:10:55,280
Speaker 1: UM and Uh, I think it it remains to be seen,

182
00:10:55,400 --> 00:10:57,880
Speaker 1: you know, when we come out of that recession, recession

183
00:10:57,920 --> 00:11:02,400
Speaker 1: back into you know, fully posited this uh growth rates.

184
00:11:02,400 --> 00:11:05,319
Speaker 1: How much of the answers to all of those questions,

185
00:11:05,320 --> 00:11:13,440
Speaker 1: Ottoman depend on stimulus further simulus UM, Well, uh, we

186
00:11:13,480 --> 00:11:17,040
Speaker 1: are seeing sort of the the earlier rounds of stimulus

187
00:11:17,480 --> 00:11:23,120
Speaker 1: waning and looking ahead, you know, unless uh more stimulus

188
00:11:23,160 --> 00:11:29,160
Speaker 1: comes to households to keep their uh spending sustained. UM,

189
00:11:29,440 --> 00:11:32,640
Speaker 1: I think it will figure in into uh the risk

190
00:11:32,960 --> 00:11:37,520
Speaker 1: about this outlook going forward, and I would say, uh

191
00:11:37,600 --> 00:11:40,199
Speaker 1: quite a bit depends on the stimulus as well as

192
00:11:40,240 --> 00:11:43,680
Speaker 1: how how the pandemic kind of fair is going forward

193
00:11:43,679 --> 00:11:47,520
Speaker 1: into the next few months. Automan, just quickly about thirty seconds,

194
00:11:47,520 --> 00:11:52,960
Speaker 1: what is the conference boards GDP call here for? Yeah,

195
00:11:53,040 --> 00:11:57,600
Speaker 1: so for on an annual basis, for UM, we're estimating

196
00:11:57,640 --> 00:12:02,320
Speaker 1: about almost uh five sent decline in the economy over

197
00:12:02,400 --> 00:12:09,320
Speaker 1: twenty UM and going into one UM the economy can

198
00:12:09,400 --> 00:12:13,160
Speaker 1: recover back into about its long term growth, which we

199
00:12:13,320 --> 00:12:16,600
Speaker 1: estimate to be about about two percent, so slightly below

200
00:12:17,000 --> 00:12:21,120
Speaker 1: that long term potential growth UM and uh again, you

201
00:12:21,160 --> 00:12:23,480
Speaker 1: know a lot of that really depends on, you know,

202
00:12:23,520 --> 00:12:28,880
Speaker 1: how the pandemic continues, whether we get a resurgence, sustained

203
00:12:28,960 --> 00:12:33,400
Speaker 1: resurgence that leads so lockdown or not. Automan, thanks so much,

204
00:12:33,880 --> 00:12:37,120
Speaker 1: as always, always appreciate you giving us your opinions and

205
00:12:37,360 --> 00:12:40,839
Speaker 1: sharing the data from the conference board. Automan also DRUM

206
00:12:40,880 --> 00:12:44,680
Speaker 1: Director of Economic Research and Global Research chair for the

207
00:12:44,720 --> 00:12:47,840
Speaker 1: Conference Board joining us on the field better than expected

208
00:12:47,920 --> 00:12:51,840
Speaker 1: numbers four July Annie, but some caution for their mainer. Yeah,

209
00:12:51,840 --> 00:12:53,720
Speaker 1: you're hearing it from all the economis out there. We

210
00:12:53,800 --> 00:12:58,080
Speaker 1: came off such low levels that even you know, beating

211
00:12:58,120 --> 00:13:00,559
Speaker 1: these estimates really doesn't mean all that much. And if

212
00:13:00,559 --> 00:13:03,319
Speaker 1: you look at pre pandemic numbers or year over year number,

213
00:13:03,360 --> 00:13:07,360
Speaker 1: is it's really almost you know, almost apprising. Yeah, it's interesting.

214
00:13:07,400 --> 00:13:11,600
Speaker 1: So again it is that create more pressure for fiscal

215
00:13:11,640 --> 00:13:17,240
Speaker 1: studias out of Washington. One of the most read stories

216
00:13:17,280 --> 00:13:21,200
Speaker 1: on the Bloomberg terminal today is about New York City

217
00:13:21,320 --> 00:13:25,360
Speaker 1: landlords aggressively calling tenants in the financial industry and other

218
00:13:25,400 --> 00:13:28,640
Speaker 1: initiaties saying, hey, get your people back to work. It's

219
00:13:28,640 --> 00:13:31,080
Speaker 1: a fascinating story. It's a Bloomberg exclusive, and we have

220
00:13:31,440 --> 00:13:35,000
Speaker 1: one of the reporters with us. Natalie wong Us, commercial

221
00:13:35,080 --> 00:13:38,200
Speaker 1: real estate reporter for Bloomberg News joins us. So not likely,

222
00:13:38,280 --> 00:13:40,840
Speaker 1: just a fascinating story. Here, give us kind of the

223
00:13:40,640 --> 00:13:44,320
Speaker 1: the the key takeaways that you uh and shree not rodging,

224
00:13:44,360 --> 00:13:48,880
Speaker 1: your co author. Other reporter on the story reported, Hi,

225
00:13:49,040 --> 00:13:51,920
Speaker 1: thanks for having me. Um. Yeah, so we've been making

226
00:13:51,960 --> 00:13:55,040
Speaker 1: some calls in the past few weeks basically to top

227
00:13:55,080 --> 00:13:58,000
Speaker 1: New York City real estate landlords and to you know,

228
00:13:58,080 --> 00:14:01,480
Speaker 1: some of the finance executives and lots of people in

229
00:14:01,520 --> 00:14:03,320
Speaker 1: the city who are kind of counting on a return

230
00:14:03,400 --> 00:14:05,440
Speaker 1: to the offices. And what we're hearing is that even

231
00:14:05,440 --> 00:14:09,560
Speaker 1: though the offices have been opened for quite some time now,

232
00:14:09,679 --> 00:14:12,880
Speaker 1: a lot of them are still quite empty. Um And

233
00:14:12,920 --> 00:14:15,560
Speaker 1: basically the argument that a lot of these landlords are

234
00:14:15,600 --> 00:14:19,560
Speaker 1: making is that it's basic pacific duty to have these

235
00:14:19,760 --> 00:14:22,440
Speaker 1: big companies start to bring the back their workers in

236
00:14:22,480 --> 00:14:25,160
Speaker 1: a more aggressive way because a the buildings are safe.

237
00:14:25,560 --> 00:14:27,840
Speaker 1: But the most importantly or the argument that they're making

238
00:14:27,920 --> 00:14:31,000
Speaker 1: is that a pacific beauty because if there's no office

239
00:14:31,040 --> 00:14:34,280
Speaker 1: workers and a lot of central business district areas in

240
00:14:34,320 --> 00:14:37,400
Speaker 1: New York City are not going to thrive. And a

241
00:14:37,440 --> 00:14:40,160
Speaker 1: lot of the small businesses that prop up these areas,

242
00:14:40,200 --> 00:14:43,920
Speaker 1: but the retailers and ellis, the coffee shops, etcetera, they're

243
00:14:43,960 --> 00:14:46,000
Speaker 1: not going to survive and they're they're going to die

244
00:14:46,040 --> 00:14:48,040
Speaker 1: and there's gonna be nothing to come back to. So

245
00:14:48,120 --> 00:14:51,240
Speaker 1: it's the main argument that they're making. So these major

246
00:14:51,360 --> 00:14:54,760
Speaker 1: landlords and developers are saying we love our city. They're

247
00:14:54,760 --> 00:14:58,960
Speaker 1: not saying pay us rent again, no, not not not

248
00:14:58,960 --> 00:15:01,800
Speaker 1: not not for this angle. If they're speaking with basically

249
00:15:01,920 --> 00:15:05,320
Speaker 1: their you know friends, some of their biggest tenants, UM,

250
00:15:05,360 --> 00:15:07,640
Speaker 1: the people that have the ability to bring black hundreds,

251
00:15:07,680 --> 00:15:10,000
Speaker 1: if not thousands of workers into the city. We're talking

252
00:15:10,040 --> 00:15:13,360
Speaker 1: about the golden stacks of blackstones, the black rocks, UM.

253
00:15:13,680 --> 00:15:16,600
Speaker 1: And they're basically making a plea to say, listen, if

254
00:15:16,600 --> 00:15:18,480
Speaker 1: you love New York City and we've all done so

255
00:15:18,520 --> 00:15:21,360
Speaker 1: well UM thriving from New York City, then it's kind

256
00:15:21,360 --> 00:15:25,120
Speaker 1: of our reponsibility to come back now, UM, to save

257
00:15:25,200 --> 00:15:29,040
Speaker 1: New York City. So, Natalie, what has what's been a

258
00:15:29,040 --> 00:15:33,080
Speaker 1: sense of the response they're getting. So what I'm hearing

259
00:15:33,200 --> 00:15:35,320
Speaker 1: is that it's a little bit mixed. Some of the

260
00:15:35,400 --> 00:15:39,200
Speaker 1: CEOs that we've talked to UM has said that the

261
00:15:39,320 --> 00:15:41,920
Speaker 1: response has been sort of lukewarm because obviously there's so

262
00:15:42,000 --> 00:15:45,760
Speaker 1: much uncertainty around the virus, around potential surging and even

263
00:15:45,800 --> 00:15:49,040
Speaker 1: schools reopening in the city. UM, So obviously no one

264
00:15:49,120 --> 00:15:51,040
Speaker 1: wants to go out and make a big gold statement

265
00:15:51,040 --> 00:15:53,400
Speaker 1: to bring their workers back when there's no certainty of

266
00:15:53,520 --> 00:15:57,080
Speaker 1: exactly how to do that. UM and on the other

267
00:15:57,120 --> 00:15:59,240
Speaker 1: side of the coin, we're also hearing that some of

268
00:15:59,280 --> 00:16:02,920
Speaker 1: the CEO's are agreeing. We had one of our real

269
00:16:03,040 --> 00:16:07,160
Speaker 1: estate executives say that from the CEOs, he've spoken to you,

270
00:16:07,200 --> 00:16:10,040
Speaker 1: and he's spoken to well over a hundred tenants UM.

271
00:16:10,080 --> 00:16:12,080
Speaker 1: It seems like they're going to be making an aggressive

272
00:16:12,160 --> 00:16:17,239
Speaker 1: push to bring back far more workers between their workforce

273
00:16:17,360 --> 00:16:20,800
Speaker 1: following Labor Day. So we'll have to see if I

274
00:16:20,920 --> 00:16:23,560
Speaker 1: actually follows through. I mean, I can see how CEOs

275
00:16:23,720 --> 00:16:27,280
Speaker 1: want things to be normal. Everybody does. But there's also

276
00:16:27,440 --> 00:16:30,520
Speaker 1: the health aspect, and there's also the mental health aspect.

277
00:16:30,520 --> 00:16:33,200
Speaker 1: If people are more comfortable being out of the office

278
00:16:33,800 --> 00:16:37,200
Speaker 1: and working from home than I also can see why

279
00:16:37,240 --> 00:16:41,360
Speaker 1: CEOs would be okay with that. Ultimately, it's what you prioritize, right, Natalie.

280
00:16:41,400 --> 00:16:45,560
Speaker 1: And developers prioritize the places they develop clearly, and if

281
00:16:45,600 --> 00:16:48,640
Speaker 1: they were developing suburban areas, I'm sure they would be

282
00:16:48,920 --> 00:16:52,040
Speaker 1: making the opposite phone calls to these CEOs and saying, hey, listen,

283
00:16:52,200 --> 00:16:55,360
Speaker 1: great opportunity here to have you know, X y Z

284
00:16:55,840 --> 00:16:59,880
Speaker 1: Town and Upstate New York thrive. But CEOs a bang

285
00:17:00,120 --> 00:17:04,280
Speaker 1: some major firms, they probably prioritize their workforce and profits

286
00:17:04,320 --> 00:17:08,080
Speaker 1: in you know, different orders. All right, I think it's

287
00:17:08,080 --> 00:17:10,239
Speaker 1: a Turkey time for all these different parties. And your

288
00:17:10,280 --> 00:17:12,119
Speaker 1: right sate Land lads do have a lot riding on this.

289
00:17:12,240 --> 00:17:14,240
Speaker 1: I mean, over the past few decades. The one that

290
00:17:14,240 --> 00:17:16,680
Speaker 1: we've spoken to have in buts so much capital into

291
00:17:17,160 --> 00:17:20,160
Speaker 1: big real estate developments in the city that really rely

292
00:17:20,400 --> 00:17:22,840
Speaker 1: on the slow of thousands of office workers touris them

293
00:17:23,080 --> 00:17:25,800
Speaker 1: and the ability of New York City to continue their talent.

294
00:17:25,920 --> 00:17:27,600
Speaker 1: So if people don't have to come back to the

295
00:17:27,640 --> 00:17:30,720
Speaker 1: office and some of these you know, vibrant retailer small

296
00:17:30,720 --> 00:17:33,760
Speaker 1: businesses starts diet, there's a lot less reason for talent

297
00:17:33,840 --> 00:17:36,280
Speaker 1: to want to come into the city at all. Um.

298
00:17:36,359 --> 00:17:38,480
Speaker 1: And and that's when that alsman stands to valid. But

299
00:17:38,520 --> 00:17:40,879
Speaker 1: obviously behind all of this is a big pandemic and

300
00:17:41,040 --> 00:17:44,760
Speaker 1: major health list um that kind of underlie the reason

301
00:17:44,800 --> 00:17:47,240
Speaker 1: for many people wanting to stay at home. So what

302
00:17:47,280 --> 00:17:49,159
Speaker 1: we're hearing now is that CEO is still kind of

303
00:17:49,160 --> 00:17:52,040
Speaker 1: taking the time it's in August lower time be here

304
00:17:52,080 --> 00:17:56,119
Speaker 1: to kind of assess exactly how and if they should

305
00:17:56,160 --> 00:18:03,440
Speaker 1: start um bringing people back and behind all these cumber yeah, yeah,

306
00:18:03,600 --> 00:18:05,879
Speaker 1: I mean they're not just talking to the videos to

307
00:18:06,080 --> 00:18:08,680
Speaker 1: They're they're really talking to the Governor's office there, talking

308
00:18:08,760 --> 00:18:12,680
Speaker 1: to a very influential local coalition for top businesses in

309
00:18:12,720 --> 00:18:15,879
Speaker 1: New York City and also pushing uh the Mayor's office

310
00:18:16,320 --> 00:18:20,560
Speaker 1: to really ramp up this return to work, back to business.

311
00:18:20,600 --> 00:18:23,760
Speaker 1: You know, New York's open for business again campaigns um.

312
00:18:23,880 --> 00:18:26,760
Speaker 1: So it's kind of all across the board. These landlords

313
00:18:26,760 --> 00:18:28,960
Speaker 1: are really going out of the way to do that now,

314
00:18:29,080 --> 00:18:31,439
Speaker 1: not just real quickly here. What's your sense is the

315
00:18:31,560 --> 00:18:34,199
Speaker 1: average when people will be coming back is like a

316
00:18:34,280 --> 00:18:37,800
Speaker 1: half by the end of the year, maybe by next year.

317
00:18:37,840 --> 00:18:42,040
Speaker 1: What's kind of the consensus you're hearing. It's really hard

318
00:18:42,080 --> 00:18:45,280
Speaker 1: to tell. Initially we were hearing that more people were

319
00:18:45,320 --> 00:18:47,159
Speaker 1: really going to come back after Labor Day. That's kind

320
00:18:47,160 --> 00:18:49,320
Speaker 1: of what we've heard from that one studeo that I

321
00:18:49,440 --> 00:18:52,320
Speaker 1: spoke to. But according to a recent survey of top

322
00:18:52,400 --> 00:18:54,920
Speaker 1: a hundred poty six companies done in New York City,

323
00:18:55,200 --> 00:18:58,919
Speaker 1: they're estimating that just over a half is expected to

324
00:18:59,000 --> 00:19:03,640
Speaker 1: return by summer. So it seems like that's continually crushed

325
00:19:03,640 --> 00:19:06,280
Speaker 1: back and a lot of people are writing on waiting

326
00:19:06,359 --> 00:19:10,280
Speaker 1: for a vaccine before making that decision. So it seems

327
00:19:10,280 --> 00:19:13,600
Speaker 1: to be considering there's a lot more in certainty India. Yeah, Natalie,

328
00:19:13,600 --> 00:19:15,480
Speaker 1: I mean that's basically what Max Nison said as well.

329
00:19:15,680 --> 00:19:18,919
Speaker 1: He's you know, following all of the vaccine trials and

330
00:19:18,920 --> 00:19:21,960
Speaker 1: so on, and he's preparing for something sort of you know,

331
00:19:22,080 --> 00:19:24,720
Speaker 1: well into next year as well. We shall see though

332
00:19:24,800 --> 00:19:28,280
Speaker 1: there could be some some opening sprouting and perhaps some

333
00:19:28,320 --> 00:19:31,240
Speaker 1: reclosings as well. Not only long, it's a fantastic story

334
00:19:31,320 --> 00:19:35,159
Speaker 1: and a real insight into how these developers and and

335
00:19:35,320 --> 00:19:37,520
Speaker 1: ceo s work and how they think and how they

336
00:19:37,520 --> 00:19:40,080
Speaker 1: communicate with each other. Do check it out on Bloomberg

337
00:19:40,240 --> 00:19:44,040
Speaker 1: dot com. It's time for Bloomberg Opinion. We can do

338
00:19:44,080 --> 00:19:46,760
Speaker 1: that today with Max Knees and biotech, farm and healthcare

339
00:19:46,920 --> 00:19:50,360
Speaker 1: Calumness for Bloomberg Opinion and actually got a fascinating column

340
00:19:50,359 --> 00:19:54,600
Speaker 1: out there. It's about perhaps a newer, better, more effective

341
00:19:54,680 --> 00:19:59,920
Speaker 1: and hopefully fester test for the coronavirus. Tell us about it. Yeah,

342
00:20:00,000 --> 00:20:04,199
Speaker 1: absolutely so. The column was about an effort developed by

343
00:20:04,440 --> 00:20:07,680
Speaker 1: researchers at the Yale School of Public Health. Um, it's

344
00:20:07,680 --> 00:20:10,240
Speaker 1: a saliva test, not not the first one of these.

345
00:20:10,359 --> 00:20:13,200
Speaker 1: That's been developed. But but the one that's the thing

346
00:20:13,240 --> 00:20:16,879
Speaker 1: that's unique about this one is that UM instead of

347
00:20:16,880 --> 00:20:19,840
Speaker 1: requiring a kind of a you know, a complex series

348
00:20:19,880 --> 00:20:25,080
Speaker 1: of steps and UM expensive reagents that's actually run the test,

349
00:20:25,440 --> 00:20:28,399
Speaker 1: all it takes is a widely available chemical and some

350
00:20:28,520 --> 00:20:31,359
Speaker 1: heat UM, and it's it's something that just about any

351
00:20:31,480 --> 00:20:33,840
Speaker 1: lab can run UM as low as it as the

352
00:20:33,840 --> 00:20:37,719
Speaker 1: proper equipment and the researchers are Basically it's it's not

353
00:20:37,800 --> 00:20:40,600
Speaker 1: a test that you have to send to them. It's

354
00:20:40,640 --> 00:20:43,280
Speaker 1: something that they're licensing out for free that that anyone

355
00:20:43,320 --> 00:20:46,200
Speaker 1: can run as long as they get the process right.

356
00:20:46,320 --> 00:20:50,600
Speaker 1: So UM, you know, easier on patients, easier to run UH,

357
00:20:50,760 --> 00:20:54,440
Speaker 1: and hopefully one of the many tools needed to get

358
00:20:54,480 --> 00:20:57,800
Speaker 1: to a place where we're testing isn't such a weight

359
00:20:57,840 --> 00:21:01,240
Speaker 1: around the neck of the response and need states. Yeah,

360
00:21:01,359 --> 00:21:03,760
Speaker 1: it's pretty insane that this far into it their states

361
00:21:03,760 --> 00:21:06,840
Speaker 1: out there that aren't even able to test their healthcare

362
00:21:06,960 --> 00:21:12,840
Speaker 1: personnel max. How reliable will this test be? UM? Quite reliable.

363
00:21:12,920 --> 00:21:16,000
Speaker 1: It's still a PCR test, so kind of in the

364
00:21:16,080 --> 00:21:20,840
Speaker 1: more accurate general family and UM, you know, it's probably

365
00:21:20,880 --> 00:21:24,800
Speaker 1: not quite as accurate as sort of the kind of

366
00:21:24,840 --> 00:21:28,000
Speaker 1: standard test you know, swab all the way back, you know,

367
00:21:28,040 --> 00:21:31,920
Speaker 1: halfway through your skull um with that more complicated process.

368
00:21:31,920 --> 00:21:36,040
Speaker 1: But it's close, and it's it's more than reasonable if

369
00:21:36,080 --> 00:21:38,800
Speaker 1: you you know, if you need to do mass testing

370
00:21:38,920 --> 00:21:42,680
Speaker 1: to to accept a little slightly lower potential accuracy, but

371
00:21:42,800 --> 00:21:46,159
Speaker 1: still you know, a good level in order to potentially

372
00:21:47,119 --> 00:21:50,280
Speaker 1: expand the number of tests and and the ease of

373
00:21:50,400 --> 00:21:53,600
Speaker 1: collecting and running them. So you know, they're always trade ups,

374
00:21:53,680 --> 00:21:56,480
Speaker 1: but this, this seems like a good one to me. Max.

375
00:21:56,520 --> 00:21:59,320
Speaker 1: Where are we in terms of getting this test as

376
00:21:59,320 --> 00:22:01,359
Speaker 1: it hasn't been a proved and if so, is this

377
00:22:01,440 --> 00:22:03,639
Speaker 1: something that can be where are we in terms of

378
00:22:03,680 --> 00:22:07,600
Speaker 1: distributing making it available? Um? Yeah, so it's it's it

379
00:22:07,720 --> 00:22:10,760
Speaker 1: got approved over the weekend, and the next step is

380
00:22:10,800 --> 00:22:13,959
Speaker 1: basically for for labs to kind of you know, get

381
00:22:14,040 --> 00:22:16,320
Speaker 1: up and start running it, to talk to the researchers

382
00:22:16,359 --> 00:22:19,760
Speaker 1: and and get their license. Um the license is more

383
00:22:19,840 --> 00:22:22,880
Speaker 1: or less just conditional on them having the right type

384
00:22:22,920 --> 00:22:26,280
Speaker 1: of machine and agreeing to charge a low price. The

385
00:22:26,280 --> 00:22:29,880
Speaker 1: other benefit of this test very very cheap. So it's

386
00:22:29,920 --> 00:22:32,880
Speaker 1: something that at least theoretically labs should be able to

387
00:22:32,880 --> 00:22:37,959
Speaker 1: to get up and running very quickly because it's so simple. Um,

388
00:22:38,040 --> 00:22:40,760
Speaker 1: you know how long that will actually take, we'll see,

389
00:22:40,880 --> 00:22:43,520
Speaker 1: But but there are many barriers in the way of

390
00:22:43,840 --> 00:22:49,040
Speaker 1: it being used, you know, quite broadly, quite soon, hopefully, Max.

391
00:22:49,200 --> 00:22:51,400
Speaker 1: Is anybody in the community talking about what would happen

392
00:22:51,440 --> 00:22:54,159
Speaker 1: if there were to be a change in administration in November,

393
00:22:54,280 --> 00:22:57,280
Speaker 1: because you know, I mean, yes, we would love if

394
00:22:57,320 --> 00:23:00,440
Speaker 1: this all happened sooner, but technically won't a tween months

395
00:23:00,480 --> 00:23:02,960
Speaker 1: away from that day and and sort of six months

396
00:23:02,960 --> 00:23:05,680
Speaker 1: away from January obviously when a new administration would take over,

397
00:23:05,720 --> 00:23:08,240
Speaker 1: if there were to be one, Would it change things materially?

398
00:23:10,160 --> 00:23:15,160
Speaker 1: I think that it's it's quite evident that it would, um,

399
00:23:15,200 --> 00:23:17,840
Speaker 1: you know, in terms of just kind of getting back

400
00:23:17,920 --> 00:23:23,240
Speaker 1: to what I would describe as a more normal response

401
00:23:23,320 --> 00:23:25,639
Speaker 1: to the pandemic, which is to say, one that is

402
00:23:26,359 --> 00:23:31,119
Speaker 1: publicly led by public health authorities, with um, a little

403
00:23:31,119 --> 00:23:35,720
Speaker 1: bit less an injection of politics and and um, you know,

404
00:23:36,240 --> 00:23:42,760
Speaker 1: strange of diversions, you know, affections for particular medicines, um,

405
00:23:42,840 --> 00:23:47,720
Speaker 1: less than consistent regard for scientific evidence. UM. So yeah,

406
00:23:47,720 --> 00:23:49,840
Speaker 1: I think a lot of things will be different on

407
00:23:50,640 --> 00:23:55,119
Speaker 1: you know, both the kind of communication and policy front. Um.

408
00:23:55,160 --> 00:23:58,159
Speaker 1: You know, one would hope that because obviously what's happening

409
00:23:58,200 --> 00:24:02,719
Speaker 1: now isn't going especially Max, give us an update if

410
00:24:02,760 --> 00:24:05,800
Speaker 1: you would on kind of you know where we are

411
00:24:05,840 --> 00:24:07,919
Speaker 1: in terms of vaccines. I know there's you know, roughly

412
00:24:07,920 --> 00:24:11,959
Speaker 1: a dozen entity slash companies groups out there that are

413
00:24:11,960 --> 00:24:15,000
Speaker 1: you know, their stages. Just give us a kind of

414
00:24:15,080 --> 00:24:19,359
Speaker 1: lay of the land right now. Sure, so there are

415
00:24:19,359 --> 00:24:22,919
Speaker 1: a few efforts that are sort of the furthest along,

416
00:24:23,800 --> 00:24:28,720
Speaker 1: those being Fiser and Maderna's RNA vaccines which which started

417
00:24:29,080 --> 00:24:31,480
Speaker 1: UM final stage US trials at the end of July.

418
00:24:32,280 --> 00:24:36,240
Speaker 1: Unclear exactly when data will come on those, but but

419
00:24:36,320 --> 00:24:39,320
Speaker 1: that's the best hope for for the first um kind

420
00:24:39,359 --> 00:24:41,680
Speaker 1: of read out something that that you know, getting data

421
00:24:41,720 --> 00:24:45,720
Speaker 1: that could eventually lead to to an FDA approval. UM.

422
00:24:45,840 --> 00:24:48,280
Speaker 1: But you know that that could happen in the in

423
00:24:48,320 --> 00:24:50,880
Speaker 1: the autumn probably on the later side. It just depends

424
00:24:50,920 --> 00:24:54,600
Speaker 1: on how quickly they can enroll and how many you know,

425
00:24:54,640 --> 00:24:58,400
Speaker 1: how how the data accrues. But but the cautionary note

426
00:24:58,440 --> 00:25:01,920
Speaker 1: there is, you know, getting that that positive data readout

427
00:25:02,280 --> 00:25:06,560
Speaker 1: doesn't translate to vaccine immediately available UM you know with

428
00:25:06,680 --> 00:25:10,000
Speaker 1: customer if if it works, still have the kind of

429
00:25:10,280 --> 00:25:14,240
Speaker 1: mass manufacturing and distribution piece to figure out, which is

430
00:25:14,560 --> 00:25:17,359
Speaker 1: the substantial effort in its own right on top of

431
00:25:18,040 --> 00:25:20,560
Speaker 1: you know, the remaining risk that that the trial takes

432
00:25:20,600 --> 00:25:23,320
Speaker 1: a while, the vaccine doesn't work. So um, you know,

433
00:25:23,520 --> 00:25:27,080
Speaker 1: very promising progress, but but still a good amount of

434
00:25:27,160 --> 00:25:30,560
Speaker 1: uncertainty and and wait to come. Luckily with so many

435
00:25:30,640 --> 00:25:34,520
Speaker 1: programs and others moving towards those large scale trials, Uh,

436
00:25:34,600 --> 00:25:37,560
Speaker 1: there there's you know, even if something fails, there are

437
00:25:37,560 --> 00:25:41,440
Speaker 1: plenty of backups. Yeah, I mean, how does it impact

438
00:25:41,920 --> 00:25:47,760
Speaker 1: the trials and also then the potential for success of

439
00:25:47,760 --> 00:25:50,439
Speaker 1: one of these vaccine candidates that there will be also

440
00:25:50,480 --> 00:25:54,199
Speaker 1: the flu vaccine going out soon and you know there

441
00:25:54,200 --> 00:25:58,680
Speaker 1: will be more doses than ever being administered this year. Yeah,

442
00:25:58,760 --> 00:26:02,119
Speaker 1: that that's kind of proof. A public health perspective really

443
00:26:02,160 --> 00:26:07,119
Speaker 1: really important. Um, you want to avoid you know, similar symptoms,

444
00:26:07,160 --> 00:26:11,960
Speaker 1: similar vulnerable populations. Let's take suy to create a lot

445
00:26:12,000 --> 00:26:16,440
Speaker 1: of confusion and extra burden on the system. Um. I

446
00:26:16,840 --> 00:26:20,080
Speaker 1: don't think that those efforts should should necessarily interfere with

447
00:26:20,160 --> 00:26:23,000
Speaker 1: trial recruitment. Um. If anything, that that could be a

448
00:26:23,040 --> 00:26:25,240
Speaker 1: good way to you know, people already coming in for

449
00:26:25,280 --> 00:26:28,960
Speaker 1: a shot to try and recruit more directly and especially

450
00:26:29,000 --> 00:26:32,760
Speaker 1: target the populations that that are a little bit kind

451
00:26:32,800 --> 00:26:35,800
Speaker 1: of running behind and recruitment. So I'm hopeful that you

452
00:26:35,800 --> 00:26:38,160
Speaker 1: know that that effort succeeds and that it can be

453
00:26:38,560 --> 00:26:42,960
Speaker 1: parlayed into both you know, good vaccination infrastructure for of

454
00:26:42,960 --> 00:26:46,320
Speaker 1: an eventual COVID vaccine in a way to to maybe

455
00:26:46,960 --> 00:26:50,600
Speaker 1: get an answer faster on multiple vaccines. Max just going

456
00:26:50,640 --> 00:26:52,160
Speaker 1: to put you on the spot, but we won't hold

457
00:26:52,160 --> 00:26:54,240
Speaker 1: you too, as we will never play this again. When

458
00:26:54,240 --> 00:26:56,440
Speaker 1: are you planning for life to return to a quote

459
00:26:56,480 --> 00:27:02,120
Speaker 1: unquote normal with yourself and your own family? Oh, it's

460
00:27:02,160 --> 00:27:07,120
Speaker 1: it's likely to be sometime well into next year. Uh

461
00:27:07,160 --> 00:27:09,640
Speaker 1: And and my my answer comes from kind of two

462
00:27:09,640 --> 00:27:14,520
Speaker 1: specific points. One that you know, having enough vaccine to

463
00:27:14,520 --> 00:27:18,440
Speaker 1: to get some sort of meaningful level of her immunity

464
00:27:18,440 --> 00:27:20,920
Speaker 1: where you'd be confident enough to to sort of fully

465
00:27:20,920 --> 00:27:22,959
Speaker 1: get back to normal, that's just going to take a

466
00:27:22,960 --> 00:27:26,520
Speaker 1: long time because of those manufacturing distribution stuffs. And the

467
00:27:26,600 --> 00:27:30,400
Speaker 1: second is either the high amount of uncertainty about exactly

468
00:27:30,400 --> 00:27:34,440
Speaker 1: how effective the vaccine will be, huge range of potential

469
00:27:34,480 --> 00:27:38,680
Speaker 1: outcomes there if it's only you know, quite modestly effective,

470
00:27:38,720 --> 00:27:42,520
Speaker 1: you know, just clears the FDA. Bar uh Max. Thank you,

471
00:27:42,600 --> 00:27:47,800
Speaker 1: Macnis and Bloomberg. Thanks for listening to Bloomberg Markets podcast.

472
00:27:48,000 --> 00:27:51,359
Speaker 1: You can subscribe and listen to interviews at Apple Podcasts

473
00:27:51,480 --> 00:27:54,720
Speaker 1: or whatever a podcast platform you prefer. I'm Monny Quinn.

474
00:27:54,840 --> 00:27:58,080
Speaker 1: I'm on Twitter at Bonny Quinn swey. I'm on Twitter

475
00:27:58,119 --> 00:28:01,000
Speaker 1: at pt Sweeney. Before the podcast, you can always catch

476
00:28:01,040 --> 00:28:05,639
Speaker 1: us worldwide at Bloomberg Radio m