1 00:00:00,240 --> 00:00:03,280 Speaker 1: This is Bloomberg Business Week. I'm Carol Masser. Every day 2 00:00:03,279 --> 00:00:05,200 Speaker 1: we're bringing you the latest news from the world's of 3 00:00:05,200 --> 00:00:08,920 Speaker 1: business and finance, plus technology, politics. So much going on 4 00:00:08,960 --> 00:00:12,160 Speaker 1: in the world of politics, economics, and it's all harnessing 5 00:00:12,160 --> 00:00:14,840 Speaker 1: the power of Business Week reporters and editors. If you 6 00:00:14,840 --> 00:00:18,280 Speaker 1: can download Bloomberg Business Week on iTunes, SoundCloud, or Bloomberg 7 00:00:18,320 --> 00:00:20,480 Speaker 1: dot com. If you can also listen to our radio 8 00:00:20,560 --> 00:00:23,439 Speaker 1: show at two pm Eastern on Bloomberg Radio and be 9 00:00:23,440 --> 00:00:26,280 Speaker 1: sure to watch us too on YouTube by searching Bloomberg 10 00:00:26,360 --> 00:00:29,160 Speaker 1: Global News. Well, Kayleie, we've got a lot of headlines 11 00:00:29,280 --> 00:00:32,080 Speaker 1: right when it comes to the virus. Today, the ECB 12 00:00:32,200 --> 00:00:35,360 Speaker 1: coming out and they kind of indicated Christine Lagarde that 13 00:00:35,400 --> 00:00:38,400 Speaker 1: there could be some more stimulus coming because of rising 14 00:00:38,479 --> 00:00:41,560 Speaker 1: infections and more lockdowns. We did have the U S 15 00:00:41,600 --> 00:00:44,080 Speaker 1: economy bounce back, but as we heard from Elena, you know, 16 00:00:44,080 --> 00:00:46,640 Speaker 1: everybody's kind of cautioning that, you know, we're still amid 17 00:00:46,920 --> 00:00:49,440 Speaker 1: the virus and still kind of waiting on some more stimulus. 18 00:00:49,560 --> 00:00:51,280 Speaker 1: I want to throw out one number, the Institute for 19 00:00:51,320 --> 00:00:55,000 Speaker 1: Health Metrics and Evaluation. It's a pretty influential modeling group. 20 00:00:55,160 --> 00:00:58,240 Speaker 1: They projected a higher US death toll about four hundred 21 00:00:58,320 --> 00:01:01,360 Speaker 1: five thousand COVID nineteen foot palities and that is by 22 00:01:01,360 --> 00:01:04,480 Speaker 1: February first, So uh yeah, we feel like we definitely 23 00:01:04,520 --> 00:01:07,600 Speaker 1: feel like a second wave here. Dr Cyber Klein is 24 00:01:07,640 --> 00:01:11,160 Speaker 1: Professor of molecular microbiology and Immunology at the Johns Hopkins 25 00:01:11,200 --> 00:01:15,200 Speaker 1: Bloomberg School of Public Health. Her research really focuses on 26 00:01:15,240 --> 00:01:18,200 Speaker 1: how males and females differ in their immune responses to 27 00:01:18,319 --> 00:01:21,640 Speaker 1: viral infection and vaccination. The Johns Hopkins Bloomberg School of 28 00:01:21,680 --> 00:01:24,399 Speaker 1: Public Health, of course supported by Michael R. Bloomberg, founder 29 00:01:24,440 --> 00:01:28,199 Speaker 1: Bloomberg LP and Bloomberg Philanthropies. Dr Klein on the phone 30 00:01:28,240 --> 00:01:31,160 Speaker 1: in Baltimore. Dr Klein, great to have you here with 31 00:01:31,280 --> 00:01:35,640 Speaker 1: Kelly and myself. So you see these virus heads that 32 00:01:35,680 --> 00:01:38,720 Speaker 1: are coming out. Is it a second wave? Is it 33 00:01:38,800 --> 00:01:42,000 Speaker 1: a third wave? What are your expectations for the coming 34 00:01:42,080 --> 00:01:46,400 Speaker 1: months around the globe and here specifically in the United States? Well, 35 00:01:46,480 --> 00:01:49,800 Speaker 1: thank you. Um, I think we are in the midst 36 00:01:49,880 --> 00:01:54,200 Speaker 1: of seeing the second wave hit, and it's it's likely 37 00:01:54,200 --> 00:01:56,960 Speaker 1: going to be a tough time that we're going to 38 00:01:57,040 --> 00:02:01,120 Speaker 1: experience as we all move indoors. Um and and I 39 00:02:01,160 --> 00:02:04,600 Speaker 1: think the combination of moving indoors where air circulation is 40 00:02:04,600 --> 00:02:07,720 Speaker 1: obviously not as good as when we can all be outdoors, 41 00:02:08,200 --> 00:02:12,200 Speaker 1: combined with pandemic fatigue which has been setting in and 42 00:02:12,440 --> 00:02:14,960 Speaker 1: especially as we enter into the holidays and people want 43 00:02:15,000 --> 00:02:18,080 Speaker 1: to be with families UM, and we're going to see 44 00:02:18,200 --> 00:02:22,280 Speaker 1: more movement of people, UM, which will contribute to increasing 45 00:02:22,320 --> 00:02:25,680 Speaker 1: the likelihood of exposures right well, and sober I just 46 00:02:25,800 --> 00:02:28,920 Speaker 1: look at Europe countries like Germany and France going back 47 00:02:28,960 --> 00:02:32,840 Speaker 1: to these restrictive measures because cases are so high, and 48 00:02:32,880 --> 00:02:34,840 Speaker 1: I think back to the first wave of the virus 49 00:02:34,840 --> 00:02:36,880 Speaker 1: in the spring, Europe was ahead of us here in 50 00:02:36,919 --> 00:02:39,000 Speaker 1: the US, and then it hit us about six to 51 00:02:39,040 --> 00:02:41,079 Speaker 1: eight weeks later. I mean, is that what we're heading for? 52 00:02:41,919 --> 00:02:45,600 Speaker 1: I think that's what um, That's exactly what we're predicting. Yes, 53 00:02:46,200 --> 00:02:49,600 Speaker 1: that we should be looking to Europe and the experiences 54 00:02:49,680 --> 00:02:52,240 Speaker 1: that they are having to give us an indication of 55 00:02:52,240 --> 00:02:56,920 Speaker 1: where we are headed. So is it increases in cases, 56 00:02:56,960 --> 00:03:01,120 Speaker 1: increases in hospitalizations, but the death the death count or 57 00:03:01,160 --> 00:03:03,360 Speaker 1: the rise in deaths isn't as bad because we have 58 00:03:03,520 --> 00:03:07,480 Speaker 1: figured out treatments, UH, in terms of dealing with some 59 00:03:07,560 --> 00:03:09,919 Speaker 1: of the most severe cases so that it doesn't lead 60 00:03:09,919 --> 00:03:13,919 Speaker 1: to a fatality. Absolutely, So I think your interpretation is 61 00:03:14,880 --> 00:03:19,919 Speaker 1: absolutely correct. We are seeing more cases, we're seeing more hospitalization. 62 00:03:20,200 --> 00:03:23,399 Speaker 1: I think people are more well educated, and they're seeking 63 00:03:23,800 --> 00:03:28,799 Speaker 1: um to be tested and or treated, probably earlier than 64 00:03:28,840 --> 00:03:31,640 Speaker 1: what we were seeing in the first wave. I think 65 00:03:31,800 --> 00:03:36,560 Speaker 1: our our biggest concern is that as cases rise and 66 00:03:36,680 --> 00:03:42,000 Speaker 1: as hospitalizations rise UM. While we do have a better 67 00:03:42,040 --> 00:03:45,360 Speaker 1: sense going into the second wave of how to treat 68 00:03:45,480 --> 00:03:50,040 Speaker 1: patients and the diversities of how we can treat patients, 69 00:03:50,200 --> 00:03:52,600 Speaker 1: I mean, it's much better than it was when we 70 00:03:52,680 --> 00:03:55,280 Speaker 1: when we had to go through the shutdown in the spring. 71 00:03:56,200 --> 00:04:00,720 Speaker 1: But I think the big concern is if we exhaust 72 00:04:01,080 --> 00:04:06,600 Speaker 1: hospitals and we exceed the limits of our health care system, 73 00:04:06,680 --> 00:04:11,160 Speaker 1: we will start to see the increases occur in satalities 74 00:04:11,200 --> 00:04:14,040 Speaker 1: because we just may not have the beds and the 75 00:04:14,080 --> 00:04:18,360 Speaker 1: facilities to treat people. That's just infrastructure, right, That's infrastructure. 76 00:04:18,520 --> 00:04:23,400 Speaker 1: That's exactly well. So you're a professor of immunology, so 77 00:04:23,480 --> 00:04:27,000 Speaker 1: let's talk about the vaccine. We heard Dr Anthony Fauci 78 00:04:27,040 --> 00:04:29,920 Speaker 1: say yesterday that we could have one by January at 79 00:04:29,920 --> 00:04:34,279 Speaker 1: the earliest. Does that timeline scene realistic to you. I 80 00:04:34,320 --> 00:04:38,800 Speaker 1: think that timeline is absolutely realistic. I think what is 81 00:04:38,880 --> 00:04:45,000 Speaker 1: going to be UM challenging for the public to UM 82 00:04:45,200 --> 00:04:49,880 Speaker 1: appreciate is that while a vaccine maybe available as early 83 00:04:49,920 --> 00:04:54,479 Speaker 1: as January, the rollout is going to probably take a 84 00:04:54,560 --> 00:04:58,600 Speaker 1: longer duration of time, and so who has access to 85 00:04:58,800 --> 00:05:03,160 Speaker 1: the vaccine as it initially has rolled out, It's obviously 86 00:05:03,200 --> 00:05:06,080 Speaker 1: going to be limited. With a lot of recommendations from 87 00:05:06,160 --> 00:05:09,920 Speaker 1: many organizations who've been thinking long and hard about this, 88 00:05:10,680 --> 00:05:13,840 Speaker 1: that it would be health care workers, people UM at 89 00:05:13,880 --> 00:05:17,400 Speaker 1: our front lines from there moving to people who are 90 00:05:17,440 --> 00:05:22,440 Speaker 1: at greatest risk UM, and then slowly but surely making 91 00:05:22,480 --> 00:05:25,520 Speaker 1: its way out to the rest of us UM. So, 92 00:05:25,760 --> 00:05:28,000 Speaker 1: you know, I think I think it's going to be 93 00:05:28,080 --> 00:05:35,680 Speaker 1: challenging for our communities as we hear a vaccine has 94 00:05:35,760 --> 00:05:39,880 Speaker 1: been developed and as being rolled out, and when people 95 00:05:39,920 --> 00:05:43,159 Speaker 1: don't see that coming to their neighborhood drug store or 96 00:05:43,279 --> 00:05:48,080 Speaker 1: to their primary care physician pediatrician right away, I think 97 00:05:48,120 --> 00:05:51,039 Speaker 1: there's just going to probably be a little frustration, but 98 00:05:51,200 --> 00:05:53,520 Speaker 1: it's going to take some time. When we talk about 99 00:05:53,600 --> 00:05:56,960 Speaker 1: millions and millions of doses, and if you know, these 100 00:05:57,040 --> 00:06:02,360 Speaker 1: vaccines require UM special handle in conditions being kept at 101 00:06:02,480 --> 00:06:07,160 Speaker 1: older temperature. Things that are just going to require ensuring 102 00:06:07,240 --> 00:06:10,760 Speaker 1: that again that infrastructure that you mentioned is in place. Sobber, 103 00:06:10,839 --> 00:06:12,840 Speaker 1: I want to get to the difference between women and men, 104 00:06:12,920 --> 00:06:15,080 Speaker 1: but I want to ask you first more broadly about 105 00:06:15,080 --> 00:06:18,680 Speaker 1: the vaccine. Once we get one, what would you need 106 00:06:18,720 --> 00:06:21,599 Speaker 1: to hear, given you study this to be confident in 107 00:06:21,640 --> 00:06:27,040 Speaker 1: taking it. So I'm already confident enough in taking it 108 00:06:27,120 --> 00:06:30,000 Speaker 1: that I was able to get my husband enrolled in 109 00:06:30,360 --> 00:06:37,040 Speaker 1: one of the trials, which trial, which trials, the Fiser trial. Okay, okay, 110 00:06:37,200 --> 00:06:42,120 Speaker 1: So that's how confident. And he was, you know, patient 111 00:06:42,320 --> 00:06:46,400 Speaker 1: eighties seven, so he was a part of that number. 112 00:06:46,440 --> 00:06:50,000 Speaker 1: Should tell you that when you're talking about tens of thousands, 113 00:06:50,520 --> 00:06:54,599 Speaker 1: he was in a very early phase two trial doing great. 114 00:06:55,000 --> 00:06:57,080 Speaker 1: So what so give us some guidance though for those 115 00:06:57,120 --> 00:07:00,320 Speaker 1: of us who are normal Joe's engines and you know, 116 00:07:00,320 --> 00:07:02,640 Speaker 1: are just seeing a ton of vaccines being developed for 117 00:07:02,760 --> 00:07:05,839 Speaker 1: hearing the conflicting things we're seeing the polls, you know, 118 00:07:06,200 --> 00:07:09,520 Speaker 1: what would be your guiding words to everyone? So my 119 00:07:09,560 --> 00:07:14,040 Speaker 1: guiding words, I think what's really tough is the public 120 00:07:14,160 --> 00:07:18,640 Speaker 1: is having to watch science um at work and in 121 00:07:18,760 --> 00:07:22,640 Speaker 1: real time and sometimes you know, it's not all perfect, 122 00:07:23,000 --> 00:07:25,920 Speaker 1: and we're going to have we do have setbacks, and 123 00:07:26,000 --> 00:07:31,400 Speaker 1: that is a part of the scientific process at work. UM. 124 00:07:31,440 --> 00:07:34,520 Speaker 1: I think that that's a good thing. But I think 125 00:07:34,520 --> 00:07:41,240 Speaker 1: it also for the public creates concern, wariness, UM questions 126 00:07:41,280 --> 00:07:45,080 Speaker 1: about things like safety as well as even how effective 127 00:07:45,760 --> 00:07:49,760 Speaker 1: UM these vaccines will be. Nothing is going to be 128 00:07:49,840 --> 00:07:54,800 Speaker 1: put out there until it is completely determined independent, but 129 00:07:55,000 --> 00:07:57,320 Speaker 1: you know by the FDA in the United States and 130 00:07:57,320 --> 00:08:01,400 Speaker 1: by other groups around the world to be safe as 131 00:08:01,440 --> 00:08:03,600 Speaker 1: well as effective. It's so true. Think about you take 132 00:08:03,600 --> 00:08:06,040 Speaker 1: a medication. You don't think twice about it. Your doctor prescribed, 133 00:08:06,040 --> 00:08:07,520 Speaker 1: but you don't go and look at like, well, what 134 00:08:07,600 --> 00:08:09,280 Speaker 1: kind of trials were done and what were they you 135 00:08:09,320 --> 00:08:13,080 Speaker 1: know exactly, you didn't see that at play And at 136 00:08:13,120 --> 00:08:16,280 Speaker 1: times it probably wasn't pretty and at times they may 137 00:08:16,320 --> 00:08:20,880 Speaker 1: have had to stop trials to manage an unusual occurrence. 138 00:08:21,400 --> 00:08:25,720 Speaker 1: These are not unusual. What's unusual is we are having 139 00:08:25,760 --> 00:08:29,720 Speaker 1: to do our work and have you and the rest 140 00:08:29,760 --> 00:08:33,319 Speaker 1: of the public see us do our work in real time. 141 00:08:34,240 --> 00:08:39,000 Speaker 1: And you know, and and and so I want to 142 00:08:39,040 --> 00:08:41,080 Speaker 1: jump in, want we want to jump in because we 143 00:08:41,120 --> 00:08:43,800 Speaker 1: are interested. We've been teasing that you have been studying 144 00:08:43,800 --> 00:08:46,920 Speaker 1: the differences between men and women and their immune responses. 145 00:08:47,000 --> 00:08:49,160 Speaker 1: What are we seeing maybe when it is when it 146 00:08:49,200 --> 00:08:51,880 Speaker 1: comes to COVID. Yes, so when it comes to COVID, 147 00:08:52,000 --> 00:08:56,920 Speaker 1: just as as as you announced, Um, women are doing better, 148 00:08:57,200 --> 00:09:02,079 Speaker 1: and this is true across diverse adult ages. We're seeing this, 149 00:09:02,559 --> 00:09:05,679 Speaker 1: um in people who are getting sick as young as 150 00:09:05,760 --> 00:09:10,760 Speaker 1: twenty and as old in their hundreds. Um. While for 151 00:09:10,880 --> 00:09:13,720 Speaker 1: both men and women, we do see an increase in 152 00:09:13,800 --> 00:09:17,400 Speaker 1: severity of COVID nineteen with age, So that is not 153 00:09:17,520 --> 00:09:20,360 Speaker 1: to say that women are completely in the clear. There 154 00:09:20,559 --> 00:09:25,760 Speaker 1: is an increase in the likelihood of hospitalization, intensive care 155 00:09:25,960 --> 00:09:29,160 Speaker 1: unit admission, as well as even death for both men 156 00:09:29,200 --> 00:09:33,320 Speaker 1: and women, but in all adult ages it's consistently about 157 00:09:33,360 --> 00:09:38,120 Speaker 1: two times higher for men. Yeah, I mean, and it's 158 00:09:38,160 --> 00:09:41,560 Speaker 1: around the world. I think that's another important point. So 159 00:09:41,640 --> 00:09:46,080 Speaker 1: it cuts across maybe some of the diversity that we 160 00:09:46,200 --> 00:09:48,960 Speaker 1: might have and some of the social and cultural norms 161 00:09:49,679 --> 00:09:55,680 Speaker 1: in just in our behaviors, in our lifestyles. Yeah, it's fascinating, 162 00:09:55,679 --> 00:09:57,240 Speaker 1: and that we just keep learning more and more about 163 00:09:57,800 --> 00:10:01,400 Speaker 1: this virus and the differences and then maybe similarities. UM. 164 00:10:01,400 --> 00:10:04,200 Speaker 1: Thank you so much. Dr Sabercline. She's Professor of Molecular 165 00:10:04,240 --> 00:10:07,600 Speaker 1: microbiology and Immunology at the Johns Hopkins Bloomberg School of 166 00:10:07,600 --> 00:10:10,319 Speaker 1: Public Health. The Johns Hopkins Bloomberg School of Public Health, 167 00:10:10,320 --> 00:10:13,360 Speaker 1: of course, supported by Michael R. Bloomberg, Founder up, Bloomberg 168 00:10:13,360 --> 00:10:16,400 Speaker 1: GAUP and Bloomberg Philanthropies. On the phone in Baltimore. I 169 00:10:16,440 --> 00:10:18,679 Speaker 1: just love when we keep kind of just learning more 170 00:10:18,679 --> 00:10:22,480 Speaker 1: and more, right, Yeah, exactly. This is Bloomberg Business Week 171 00:10:22,640 --> 00:10:25,719 Speaker 1: with Carol Messer from Bloomberg Radio. And we know we 172 00:10:25,800 --> 00:10:29,000 Speaker 1: heard from Dr Anthony Fauci yesterday he said vaccines at 173 00:10:29,080 --> 00:10:31,640 Speaker 1: least in the US won't be available until January the earliest. 174 00:10:31,679 --> 00:10:33,679 Speaker 1: We just talked about that with our last guest. Well, 175 00:10:33,679 --> 00:10:35,960 Speaker 1: this week's cover story is all about the race for 176 00:10:35,960 --> 00:10:37,800 Speaker 1: a vaccine here in the U s. It's of course, 177 00:10:37,840 --> 00:10:41,000 Speaker 1: called Operation Warp Speed. It's the federal government's mission to 178 00:10:41,040 --> 00:10:44,520 Speaker 1: accelerate development of a COVID nineteen vaccine. This story written 179 00:10:44,520 --> 00:10:47,679 Speaker 1: by Bloomberg News Financial Investigation Senior writer Stephanie Baker and 180 00:10:47,720 --> 00:10:50,720 Speaker 1: Bloomberg News is US healthcare reporter Cynthia Kuh and Stephanie 181 00:10:50,800 --> 00:10:53,360 Speaker 1: joins us on the phone from London. And Bloomberg Business 182 00:10:53,400 --> 00:10:57,360 Speaker 1: Week editor Jel Webber is on the phone in Brooklyn. Joel, 183 00:10:57,480 --> 00:10:59,959 Speaker 1: it's it's all about Operation Warp Speed. It's also around 184 00:11:00,040 --> 00:11:03,040 Speaker 1: about a very specific company that's been involved in all 185 00:11:03,080 --> 00:11:05,920 Speaker 1: of this. Yeah, that's so that, you know, we talked 186 00:11:05,920 --> 00:11:10,080 Speaker 1: about vaccines a lot um in this program, and obviously 187 00:11:10,120 --> 00:11:13,360 Speaker 1: I think it's one of the things that everybody is, 188 00:11:14,280 --> 00:11:17,559 Speaker 1: you know, watching in addition to this, you know, election 189 00:11:17,800 --> 00:11:21,240 Speaker 1: next week. But the you know, obviously the big thing 190 00:11:21,400 --> 00:11:24,880 Speaker 1: here with the vaccine is, you know, how do we 191 00:11:24,960 --> 00:11:27,720 Speaker 1: get to a viable vaccine and then how do you 192 00:11:27,760 --> 00:11:31,120 Speaker 1: distribute it? And one of the big unknowns sort of 193 00:11:31,120 --> 00:11:35,400 Speaker 1: in our coverage has been what role Operation Warp Speed 194 00:11:35,480 --> 00:11:38,120 Speaker 1: actually plays in this And that was sort of the 195 00:11:38,160 --> 00:11:41,559 Speaker 1: mission that we put Um, Stephanie and Cynthia on with 196 00:11:41,600 --> 00:11:44,000 Speaker 1: this story. And what we what we learned in the 197 00:11:44,000 --> 00:11:47,680 Speaker 1: process is Um is really told and they told the 198 00:11:47,720 --> 00:11:51,920 Speaker 1: story through a company called uh Emergent, which is in Baltimore. 199 00:11:52,160 --> 00:11:54,320 Speaker 1: That's a company I've never heard of, and yet they're 200 00:11:54,360 --> 00:11:57,240 Speaker 1: one of the many players that are sort of in 201 00:11:57,360 --> 00:12:01,440 Speaker 1: the Operation Warp Speed ecosystem. So so, Stephanie, what what 202 00:12:01,600 --> 00:12:05,480 Speaker 1: is that company? Emergent tell us about Operation Warps feeds 203 00:12:05,520 --> 00:12:11,920 Speaker 1: approach in the vaccine development. Yes, well, you know, Operation 204 00:12:11,960 --> 00:12:15,360 Speaker 1: Warp Speed turned to Emergent when they were looking for 205 00:12:15,520 --> 00:12:20,319 Speaker 1: surge capacity to make vaccines. Emergent had been a supplier 206 00:12:20,440 --> 00:12:25,840 Speaker 1: to the US government for years, uh making vaccines against 207 00:12:25,840 --> 00:12:30,040 Speaker 1: anthrax and smallpox, and so they were in a prime 208 00:12:30,080 --> 00:12:32,480 Speaker 1: position to be able to sort of set that aside 209 00:12:33,280 --> 00:12:37,560 Speaker 1: and start making COVID nineteen vaccines and had this sort 210 00:12:37,559 --> 00:12:42,360 Speaker 1: of the manufacturing suites and the technology, and it turned 211 00:12:42,400 --> 00:12:44,960 Speaker 1: up that there now they had worked with three of 212 00:12:45,000 --> 00:12:48,920 Speaker 1: the six vaccine developers that Operation Warp Speed had has 213 00:12:49,000 --> 00:12:54,199 Speaker 1: publicly backed um and you know, really turned themselves into 214 00:12:54,240 --> 00:12:58,079 Speaker 1: a sort of key node of production for COVID vaccines 215 00:12:58,240 --> 00:13:02,240 Speaker 1: and are gearing up in the process of making what 216 00:13:02,320 --> 00:13:05,520 Speaker 1: will eventually be you know, hundreds of millions of doses 217 00:13:06,120 --> 00:13:10,160 Speaker 1: of vaccines of various candidates. Now, obviously there are two 218 00:13:10,200 --> 00:13:14,160 Speaker 1: things here. There's one is which vaccines will get approved, 219 00:13:14,960 --> 00:13:18,040 Speaker 1: and then there's manufacturing them and making sure there's enough 220 00:13:18,400 --> 00:13:21,920 Speaker 1: supply when that approval does come. And I think that's 221 00:13:21,960 --> 00:13:24,600 Speaker 1: what Operation Warps who's really focused on, is making sure 222 00:13:24,640 --> 00:13:28,560 Speaker 1: that the supply chain is there, that the all the 223 00:13:28,600 --> 00:13:32,000 Speaker 1: manufacturers have what they need and can use, for instance, 224 00:13:32,000 --> 00:13:36,360 Speaker 1: the Defense Production Act to gain priority in in in 225 00:13:36,400 --> 00:13:38,480 Speaker 1: the supply chain to make sure that those doses are 226 00:13:38,520 --> 00:13:43,839 Speaker 1: available if and when an approval does come right. Something 227 00:13:43,840 --> 00:13:45,760 Speaker 1: that surprised me. I don't know whether it should have, 228 00:13:45,880 --> 00:13:49,600 Speaker 1: considering they are intending to have this process happen at 229 00:13:49,600 --> 00:13:51,960 Speaker 1: warp speed, but they say their goal is to start 230 00:13:52,000 --> 00:13:54,880 Speaker 1: delivering a vaccine within twenty four hours of its approval. 231 00:13:55,320 --> 00:13:59,520 Speaker 1: That's a really quick turnaround. Have they succeeded in kind 232 00:13:59,559 --> 00:14:02,880 Speaker 1: of doing having that infrastructure set up for when a 233 00:14:02,960 --> 00:14:07,280 Speaker 1: vaccine is ultimately approved. Well, they are trying to prepare 234 00:14:07,320 --> 00:14:10,920 Speaker 1: the groundwork by doing things like building an integrated computer 235 00:14:10,960 --> 00:14:15,320 Speaker 1: system to track where every dose goes. UM they've outsourced 236 00:14:15,400 --> 00:14:19,720 Speaker 1: distribution to a company UM that has historically worked with 237 00:14:19,800 --> 00:14:23,560 Speaker 1: the Centers for Disease Control on vaccine distribution. But of 238 00:14:23,600 --> 00:14:28,040 Speaker 1: course this all depends on which vaccine gets approved and when, 239 00:14:28,680 --> 00:14:32,520 Speaker 1: and there's just so many uncertainties around that. And you know, 240 00:14:32,600 --> 00:14:36,440 Speaker 1: one of the front runners fiser Um, which is developing 241 00:14:36,480 --> 00:14:40,560 Speaker 1: a vaccine together with Germany's BioNTech UM. You know, it 242 00:14:40,640 --> 00:14:44,800 Speaker 1: has very challenging UH storage requirements. It needs to be 243 00:14:44,880 --> 00:14:47,960 Speaker 1: kept at minus seventy five degrees celsius, which is I 244 00:14:47,960 --> 00:14:52,280 Speaker 1: think as a hundred and twelve degrees fahrenheit. And you 245 00:14:52,280 --> 00:14:56,200 Speaker 1: know that just creates huge challenges in terms of trying 246 00:14:56,240 --> 00:15:01,120 Speaker 1: to farm those doses out across the country. And so 247 00:15:01,160 --> 00:15:05,760 Speaker 1: I think you know they're they're working with individual states 248 00:15:05,800 --> 00:15:07,520 Speaker 1: to try to come up with a plan. I think 249 00:15:07,560 --> 00:15:10,320 Speaker 1: some of the states have pushed back saying, you know, 250 00:15:10,520 --> 00:15:14,760 Speaker 1: you guys, you haven't provided enough detail on things like 251 00:15:14,840 --> 00:15:17,640 Speaker 1: storage or funding. I think there are a lot of 252 00:15:17,760 --> 00:15:23,480 Speaker 1: unanswered questions. So you get some bullish predictions from the 253 00:15:23,520 --> 00:15:27,480 Speaker 1: people working within Operation Warp Speed UM, and it's it's 254 00:15:27,560 --> 00:15:31,360 Speaker 1: unclear until the time comes come January you know whether 255 00:15:31,440 --> 00:15:34,800 Speaker 1: or not they will be able to effectively farm this out. Um. 256 00:15:34,880 --> 00:15:38,840 Speaker 1: It is a massive challenge, Stephanie. One of the big 257 00:15:38,920 --> 00:15:41,760 Speaker 1: numbers in the story is eight ten billion, which is 258 00:15:41,760 --> 00:15:45,800 Speaker 1: basically the figure that Operation work Speed has at its 259 00:15:45,880 --> 00:15:51,400 Speaker 1: disposal to invest in incentivize the private sector and the 260 00:15:51,400 --> 00:15:56,280 Speaker 1: farmer companies to help basically get a vaccino. UM. I'm 261 00:15:56,320 --> 00:15:59,000 Speaker 1: wondering when you think about how big that number is 262 00:15:59,040 --> 00:16:03,280 Speaker 1: in the logistical olenge that Operation Warp Speed is ultimately 263 00:16:03,280 --> 00:16:07,000 Speaker 1: facing here is there is there like almost an optimistic 264 00:16:07,080 --> 00:16:09,760 Speaker 1: take on this. I mean here we are like, regardless 265 00:16:09,760 --> 00:16:12,800 Speaker 1: of when the vaccine comes, whether it's three months, six months, 266 00:16:12,800 --> 00:16:15,880 Speaker 1: a year from now, like, we've never seen anything in 267 00:16:15,920 --> 00:16:19,560 Speaker 1: the in this country operate at this velocity. What's your 268 00:16:19,600 --> 00:16:23,760 Speaker 1: take on that? Yeah, you know, when I started this story, 269 00:16:23,960 --> 00:16:26,160 Speaker 1: I thought there you know, there was a lot of 270 00:16:26,200 --> 00:16:29,360 Speaker 1: questions about lack of transparency in whether or not you know, 271 00:16:29,400 --> 00:16:34,360 Speaker 1: this was um wasted taxpayer money. But when you when 272 00:16:34,360 --> 00:16:37,680 Speaker 1: you think about it, the scale of the economic fallout 273 00:16:37,760 --> 00:16:42,120 Speaker 1: is so enormous. Trillions of dollars in a way, billion 274 00:16:42,320 --> 00:16:46,160 Speaker 1: is very little um, and that they ought to be 275 00:16:46,480 --> 00:16:49,120 Speaker 1: throwing more money at it, and we'll probably have to 276 00:16:49,160 --> 00:16:51,680 Speaker 1: throw more money at it in reality when it gets 277 00:16:51,720 --> 00:16:55,280 Speaker 1: down to the distribution. Um, you know, the States are 278 00:16:55,320 --> 00:17:00,240 Speaker 1: demanding you know, more money. Um. You know Trump has 279 00:17:00,280 --> 00:17:05,000 Speaker 1: promised to provide the vaccine for free, so has Joe Biden. Um. 280 00:17:05,080 --> 00:17:09,560 Speaker 1: Joe Biden has announced that he would spend billion on 281 00:17:09,560 --> 00:17:16,600 Speaker 1: on distribution. Uh, you know, additional on on the vaccine effort, 282 00:17:16,640 --> 00:17:21,040 Speaker 1: including distribution. UM. So you know, I actually think that 283 00:17:21,280 --> 00:17:24,080 Speaker 1: it's it is a bargain in a way, if it 284 00:17:24,280 --> 00:17:27,280 Speaker 1: comes up with an effective vaccine, even if it's only one, 285 00:17:27,400 --> 00:17:30,399 Speaker 1: if they're able to produce three million doses, which is 286 00:17:30,440 --> 00:17:33,360 Speaker 1: the target. He's definitely just really quick thirty seconds from 287 00:17:33,400 --> 00:17:36,160 Speaker 1: your reporting and what you found out about Operation Works. 288 00:17:36,359 --> 00:17:38,600 Speaker 1: Do you feel like it's sometimes I think we questioned 289 00:17:38,600 --> 00:17:40,960 Speaker 1: some of the efficiencies in government or lack thereof. Do 290 00:17:40,960 --> 00:17:44,960 Speaker 1: you feel like it's an efficient process? Just quickly yeah. 291 00:17:45,000 --> 00:17:48,040 Speaker 1: I mean we got from the companies that we spoke 292 00:17:48,080 --> 00:17:51,400 Speaker 1: to they felt like they were getting the support um 293 00:17:51,440 --> 00:17:55,719 Speaker 1: that they needed and that they it was surprisingly efficient. Um. 294 00:17:55,800 --> 00:17:58,280 Speaker 1: And I think, you know, it's obviously a mixed picture 295 00:17:58,320 --> 00:18:01,080 Speaker 1: depending on you know, what company you're talking about, but 296 00:18:01,160 --> 00:18:03,840 Speaker 1: in terms of working out supply chain glitches, I think 297 00:18:04,119 --> 00:18:06,880 Speaker 1: it actually has been quite effective. Pretty cool story, Um, 298 00:18:06,920 --> 00:18:10,040 Speaker 1: great stuff. It's the cover story in the magazine. Stephanie Baker, 299 00:18:10,080 --> 00:18:13,040 Speaker 1: thank you so much. Financial Investigation, senior writer at Bloomberg 300 00:18:13,040 --> 00:18:15,400 Speaker 1: News joining us from London. Jill Weber, thank you as well, 301 00:18:15,560 --> 00:18:18,000 Speaker 1: editor at Bloomberg Business Week. You can find that story 302 00:18:18,040 --> 00:18:22,760 Speaker 1: the magazine, hitting news stands, online and on the Bloomberg Carol. 303 00:18:22,880 --> 00:18:28,440 Speaker 1: It is five days to go into actually the official 304 00:18:28,800 --> 00:18:31,680 Speaker 1: voting club because then we're at election day if we're 305 00:18:31,680 --> 00:18:33,919 Speaker 1: playing that game, though the election has already started being 306 00:18:33,960 --> 00:18:36,080 Speaker 1: fair enough. More than half of the people that voted 307 00:18:36,119 --> 00:18:38,359 Speaker 1: in TWENTI have already voted early. So there you go. 308 00:18:38,480 --> 00:18:40,960 Speaker 1: It's pretty wild, right, It's like the numbers that we're seeing. 309 00:18:40,960 --> 00:18:42,800 Speaker 1: I think it's over seventy five million, at least at 310 00:18:42,800 --> 00:18:45,719 Speaker 1: one check um that I looked at. I always look 311 00:18:45,760 --> 00:18:47,840 Speaker 1: forward to talking with our next guest. Bloomberg News political 312 00:18:47,880 --> 00:18:50,560 Speaker 1: contributor I own a college professor of political science, Jeanie 313 00:18:50,640 --> 00:18:53,760 Speaker 1: Zeno is back with us on the phone from New Rochelle, 314 00:18:53,800 --> 00:18:56,800 Speaker 1: New York up in Westchester. Genny, great to have you 315 00:18:56,800 --> 00:18:59,040 Speaker 1: here with Kaylee and myself. I'm not quite sure where 316 00:18:59,080 --> 00:19:00,800 Speaker 1: to start, Like, so you make up in the morning. 317 00:19:01,000 --> 00:19:02,399 Speaker 1: What is it that you want to know when it 318 00:19:02,400 --> 00:19:05,119 Speaker 1: comes to the campaign trial. So good to talk to 319 00:19:05,240 --> 00:19:07,479 Speaker 1: both of you. It's time to believe, as you're just 320 00:19:07,480 --> 00:19:11,280 Speaker 1: saying that, let's get crazy. But um, you know I 321 00:19:11,480 --> 00:19:14,160 Speaker 1: I I do. As a poster, I have to confess 322 00:19:14,280 --> 00:19:17,919 Speaker 1: that I do always look at the polls. We're just 323 00:19:18,000 --> 00:19:20,840 Speaker 1: having this discussion in class, trying to keep in mind 324 00:19:20,960 --> 00:19:24,200 Speaker 1: that these are, you know, based on probabilities. And they're 325 00:19:24,280 --> 00:19:27,439 Speaker 1: fraught with you know, uncertainty at this point. But I 326 00:19:27,520 --> 00:19:29,639 Speaker 1: do look at the polls. I do look at my 327 00:19:29,680 --> 00:19:33,080 Speaker 1: favorite forecasters. I have to admit everybody from five thirty 328 00:19:33,080 --> 00:19:35,720 Speaker 1: eight to Larry Sabato who comes on Bloomberg of course, 329 00:19:35,720 --> 00:19:40,359 Speaker 1: and it's wonderful, and you know, so many of the yes, 330 00:19:40,640 --> 00:19:43,119 Speaker 1: U v A. And Crystal Ball is great and of 331 00:19:43,160 --> 00:19:46,080 Speaker 1: course uh Cook political reports. So there's a lot of 332 00:19:46,080 --> 00:19:48,280 Speaker 1: the forecasters I look at. But I get it right 333 00:19:48,359 --> 00:19:52,440 Speaker 1: last time. Um, you know, they did not necessarily get 334 00:19:52,480 --> 00:19:56,960 Speaker 1: it right overall, but that but but the some of 335 00:19:57,000 --> 00:20:00,240 Speaker 1: them did, but the but you know, the the was 336 00:20:00,280 --> 00:20:01,760 Speaker 1: more of I think a flaw of some of the 337 00:20:01,840 --> 00:20:04,760 Speaker 1: state polls. But again, you know, when you have states 338 00:20:04,840 --> 00:20:10,480 Speaker 1: like Michigan, Wisconsin, UM in Pennsylvania where the president one 339 00:20:10,560 --> 00:20:13,160 Speaker 1: by less than one percent, you know, those are really 340 00:20:13,200 --> 00:20:15,560 Speaker 1: hard to call. So I look at that. But of course, 341 00:20:15,640 --> 00:20:17,639 Speaker 1: like I always pay attention to what's going on in 342 00:20:17,680 --> 00:20:20,000 Speaker 1: the news and of course the economy, like all of 343 00:20:20,040 --> 00:20:22,400 Speaker 1: these things that could sort of change something as well. 344 00:20:22,440 --> 00:20:24,719 Speaker 1: It's late for there to be sort of a big 345 00:20:24,840 --> 00:20:27,520 Speaker 1: changing news event, but I do think it can have 346 00:20:27,560 --> 00:20:30,080 Speaker 1: an impact. And one thing I'm curious about now is 347 00:20:30,400 --> 00:20:32,879 Speaker 1: you know, as the prospect of the Democrats taking the 348 00:20:32,920 --> 00:20:37,080 Speaker 1: Senate seems to increase, does that make people at least 349 00:20:37,119 --> 00:20:39,600 Speaker 1: in the middle unwilling to sort of give all of 350 00:20:39,680 --> 00:20:43,399 Speaker 1: Washington to Democrats. I think that's a big question. Well, gee, 351 00:20:43,400 --> 00:20:44,960 Speaker 1: you brought up the Senate, so I want to ask you. 352 00:20:45,000 --> 00:20:47,679 Speaker 1: I was looking at real clear politics right now. They 353 00:20:47,720 --> 00:20:51,600 Speaker 1: see forty five seats going to Democrats Republicans. Nine are 354 00:20:51,680 --> 00:20:55,560 Speaker 1: toss ups. That feels like it really could go either way, 355 00:20:55,600 --> 00:20:58,200 Speaker 1: it really does, you know. I think at this point 356 00:20:58,280 --> 00:21:01,359 Speaker 1: we are thinking that it looks, you know, that the 357 00:21:01,400 --> 00:21:05,000 Speaker 1: Democrats can take this, but we are not sure where 358 00:21:05,040 --> 00:21:07,200 Speaker 1: some of these states are going to come down. And so, 359 00:21:07,760 --> 00:21:09,439 Speaker 1: you know, I think those are going to be some 360 00:21:09,560 --> 00:21:12,520 Speaker 1: of the most interesting races to watch are going to 361 00:21:12,600 --> 00:21:15,159 Speaker 1: be in the Senate this year. And so, you know, 362 00:21:15,359 --> 00:21:18,440 Speaker 1: some of them have been fascinating just listening to the president, 363 00:21:18,840 --> 00:21:22,040 Speaker 1: you know, quickly call up Martha McSally to you know, 364 00:21:22,160 --> 00:21:25,000 Speaker 1: to speak yesterday and just as quickly dismissed her. And 365 00:21:25,080 --> 00:21:26,880 Speaker 1: what's going to happen in the state in the race 366 00:21:26,960 --> 00:21:29,520 Speaker 1: like Arizona, certainly, what's going to happen in the state 367 00:21:29,600 --> 00:21:32,800 Speaker 1: like Colorado, in a state like Michigan. So there are 368 00:21:32,800 --> 00:21:36,359 Speaker 1: so many North Carolina. There's so many fascinating races going 369 00:21:36,400 --> 00:21:39,600 Speaker 1: on around the country that could change this thing either 370 00:21:39,640 --> 00:21:42,040 Speaker 1: way at this point for sure, and with the Senate 371 00:21:42,080 --> 00:21:44,000 Speaker 1: and with the presidential race, I want to ask you 372 00:21:44,080 --> 00:21:47,760 Speaker 1: how stimulus or the lack of getting a stimulus deal 373 00:21:47,840 --> 00:21:49,960 Speaker 1: factors into this. Who does it help, who does it hurt? 374 00:21:49,960 --> 00:21:52,760 Speaker 1: Does it really make a difference. I think it does 375 00:21:52,840 --> 00:21:55,439 Speaker 1: make a difference. I think it is um, you know, 376 00:21:55,760 --> 00:21:59,359 Speaker 1: something that I think it's something that we heard the 377 00:21:59,400 --> 00:22:02,880 Speaker 1: president you know, wanted to do um and they could 378 00:22:02,920 --> 00:22:07,480 Speaker 1: not get it done with the Democrats. Um, I think democrats. 379 00:22:08,160 --> 00:22:11,680 Speaker 1: I think it hurts the Republicans more because I think 380 00:22:11,720 --> 00:22:14,920 Speaker 1: there's a tendency for the American public to blame the 381 00:22:14,960 --> 00:22:17,400 Speaker 1: people who control the White House or what doesn't does 382 00:22:17,440 --> 00:22:20,119 Speaker 1: not come out whether I don't think that's even quite fair, 383 00:22:20,160 --> 00:22:22,320 Speaker 1: but I think we all have a tendency to say 384 00:22:22,480 --> 00:22:24,800 Speaker 1: the president could have made this happen if he or 385 00:22:24,840 --> 00:22:28,040 Speaker 1: she wanted to. So I do think there's a tendency 386 00:22:28,080 --> 00:22:30,280 Speaker 1: for this to hurt the Republicans because they do have 387 00:22:30,440 --> 00:22:33,760 Speaker 1: the Senate and the White House. Um. But but you know, 388 00:22:33,840 --> 00:22:35,800 Speaker 1: I think there's a lot of blame to go around too. 389 00:22:35,840 --> 00:22:38,480 Speaker 1: I think that you know, Democrats could have done more 390 00:22:38,600 --> 00:22:40,720 Speaker 1: to come to an agreement. They did not do that. 391 00:22:41,119 --> 00:22:43,919 Speaker 1: So I do think the stimulus plays a role. And 392 00:22:43,960 --> 00:22:46,840 Speaker 1: I think as people think about, you know, the stock 393 00:22:46,880 --> 00:22:49,760 Speaker 1: market and other things, the stimulus is you know, top 394 00:22:49,760 --> 00:22:51,960 Speaker 1: on their mind in terms of how we go forward. 395 00:22:52,080 --> 00:22:55,480 Speaker 1: And we're hearing Sauci say yesterday that we could be 396 00:22:55,640 --> 00:22:58,080 Speaker 1: in the midst of this pandemic not just through but 397 00:22:58,160 --> 00:23:01,399 Speaker 1: twenty two before life returns to North and so we 398 00:23:01,520 --> 00:23:04,119 Speaker 1: are going to need a stimulus agreement out of Washington 399 00:23:04,280 --> 00:23:06,840 Speaker 1: sooner rather than later. At a conversation with the CEO 400 00:23:07,240 --> 00:23:10,359 Speaker 1: and they earlier today and saying that Cove is going 401 00:23:10,400 --> 00:23:12,760 Speaker 1: to be with us for a few years. Like cases 402 00:23:12,800 --> 00:23:14,600 Speaker 1: will pop up and we just have to kind of 403 00:23:14,600 --> 00:23:17,480 Speaker 1: get used to it and figure out how to kind 404 00:23:17,520 --> 00:23:20,240 Speaker 1: of live with it and stay safe generally. I do 405 00:23:20,359 --> 00:23:24,680 Speaker 1: wonder on the early voting trends, um, is something happening 406 00:23:24,920 --> 00:23:28,760 Speaker 1: in terms of a transformation of politics more than we 407 00:23:28,840 --> 00:23:31,879 Speaker 1: kind of realize right now in the moment, this early 408 00:23:31,960 --> 00:23:34,800 Speaker 1: voting process, Is this going to be the norm going forward? 409 00:23:36,000 --> 00:23:38,879 Speaker 1: That is something I am so curious about. I do 410 00:23:39,160 --> 00:23:41,960 Speaker 1: think that one of the quote unquote silver linings, if 411 00:23:41,960 --> 00:23:44,800 Speaker 1: you will, of the pandemic is that it has pushed 412 00:23:44,840 --> 00:23:48,680 Speaker 1: many states to adjust. Um they're the way that they 413 00:23:48,720 --> 00:23:52,320 Speaker 1: allow their their their voters to vote. And I do 414 00:23:52,440 --> 00:23:54,679 Speaker 1: think it once you get people in the habit of 415 00:23:54,720 --> 00:23:57,800 Speaker 1: allowing them to vote by mail and vote early. Now, 416 00:23:57,840 --> 00:24:00,760 Speaker 1: obviously one election is not a habit, but once you 417 00:24:00,840 --> 00:24:03,640 Speaker 1: give people that option, I think it's tougher to pull 418 00:24:03,680 --> 00:24:06,000 Speaker 1: that back. So I do think we are going to 419 00:24:06,119 --> 00:24:09,240 Speaker 1: see a movement in this direction. It's been coming for 420 00:24:09,359 --> 00:24:11,840 Speaker 1: some time. People out in the West know this. You know, 421 00:24:11,880 --> 00:24:15,040 Speaker 1: states like Washington, Oregon, they've been great with voting by 422 00:24:15,160 --> 00:24:18,440 Speaker 1: mail and it's increased their turnout tremendously. And so I 423 00:24:18,440 --> 00:24:20,520 Speaker 1: think we start to see more of this as we 424 00:24:20,600 --> 00:24:24,439 Speaker 1: go forward, and you know, consideration of other things like 425 00:24:24,880 --> 00:24:28,480 Speaker 1: should we have weekend voting, um, you know, should we 426 00:24:28,640 --> 00:24:31,920 Speaker 1: make voting in other words easier and more accessible than 427 00:24:32,000 --> 00:24:34,560 Speaker 1: we do. And the problem in the US is always 428 00:24:34,600 --> 00:24:36,840 Speaker 1: because we are a federal system that's sort of a 429 00:24:36,920 --> 00:24:39,800 Speaker 1: state by state decision, So it takes some time to 430 00:24:39,920 --> 00:24:42,040 Speaker 1: wave if you will, across the nation, but I think 431 00:24:42,080 --> 00:24:44,560 Speaker 1: the pandemic is pushing it a bit. Jenny. What do 432 00:24:44,600 --> 00:24:47,280 Speaker 1: you make of kind of the financial fortunes or lack thereof, 433 00:24:47,520 --> 00:24:53,440 Speaker 1: or diminishing fortunes of the Trump campaign versus the Biden campaign. Yeah, 434 00:24:53,480 --> 00:24:56,080 Speaker 1: I mean it's been a fascinating story. Um. You know, 435 00:24:56,280 --> 00:25:00,320 Speaker 1: he has uh Biden has out raised and they can 436 00:25:00,400 --> 00:25:03,919 Speaker 1: now outspend the Trump campaign. Um. And that is obviously, 437 00:25:03,960 --> 00:25:07,000 Speaker 1: always in our system, a huge benefit. I would just 438 00:25:07,119 --> 00:25:11,679 Speaker 1: caution it's not determinative, of course, because Hillary Clinton spend 439 00:25:11,800 --> 00:25:14,720 Speaker 1: more than Donald Trump did in twenty sixteen, and so 440 00:25:14,800 --> 00:25:18,040 Speaker 1: I think what the Trump campaign, you know, more often 441 00:25:18,040 --> 00:25:20,800 Speaker 1: than not, money is going to translate into votes, um, 442 00:25:20,840 --> 00:25:23,840 Speaker 1: but but it not always. And I think what the 443 00:25:23,840 --> 00:25:27,960 Speaker 1: Trump campaign is hoping is that with these rallies and 444 00:25:28,160 --> 00:25:31,520 Speaker 1: sort of the statements by the President and his surrogates, 445 00:25:31,560 --> 00:25:35,199 Speaker 1: they are able to generate free media, if you will, 446 00:25:35,240 --> 00:25:38,760 Speaker 1: in these battleground states and get attention that way and 447 00:25:38,840 --> 00:25:40,879 Speaker 1: not have to spend I mean, this has been Donald 448 00:25:40,920 --> 00:25:43,520 Speaker 1: Trump's bread and butter. As we know, he says, you know, 449 00:25:43,640 --> 00:25:48,399 Speaker 1: semi controversial, outrageous things or things that get attention and 450 00:25:48,440 --> 00:25:51,000 Speaker 1: he can then not spend as much as his opponents. 451 00:25:51,000 --> 00:25:53,919 Speaker 1: So I don't think this is there, this was necessarily 452 00:25:53,920 --> 00:25:55,880 Speaker 1: a plan. I don't think they wanted to be out, 453 00:25:56,320 --> 00:25:58,879 Speaker 1: you know, be out fundraised um, but this is the 454 00:25:58,920 --> 00:26:02,479 Speaker 1: position there in it is does vote very well for Biden, 455 00:26:02,520 --> 00:26:05,280 Speaker 1: but I don't think it's determinative. But with those rallies 456 00:26:05,320 --> 00:26:08,240 Speaker 1: you mentioned, Jennie, I have to wonder how much that 457 00:26:08,320 --> 00:26:11,000 Speaker 1: really helps him reach beyond his base, because isn't he 458 00:26:11,080 --> 00:26:14,240 Speaker 1: just kind of preach into the choir. Yeah, I agree 459 00:26:14,280 --> 00:26:17,199 Speaker 1: with you. You know, they worked in sixteen, But I 460 00:26:17,200 --> 00:26:21,040 Speaker 1: think the problem has been he's running this campaign as 461 00:26:21,040 --> 00:26:23,480 Speaker 1: if it's sixteen and he's not. For one thing, we're 462 00:26:23,520 --> 00:26:26,359 Speaker 1: in the midst of a pandemic, and so there's a 463 00:26:26,400 --> 00:26:29,400 Speaker 1: school of thought that those rallies actually work against him 464 00:26:29,400 --> 00:26:32,120 Speaker 1: when people turn on the TV, seniors for instance, who 465 00:26:32,119 --> 00:26:35,040 Speaker 1: he needs to vote for him. They turn on TV 466 00:26:35,119 --> 00:26:37,960 Speaker 1: and see all these people close together, unmasked, as if 467 00:26:38,040 --> 00:26:41,520 Speaker 1: the pandemic isn't happening right now. So, you know, I'm 468 00:26:41,520 --> 00:26:45,040 Speaker 1: not certain it works for him to that extent. And then, 469 00:26:45,080 --> 00:26:47,879 Speaker 1: of course, to your point, he is, you know, the 470 00:26:47,920 --> 00:26:51,440 Speaker 1: income and president as opposed to the challenger. This isn't 471 00:26:51,480 --> 00:26:55,480 Speaker 1: twenty sixteen, and he's got to reach independence and moderates, 472 00:26:55,800 --> 00:26:58,399 Speaker 1: and I'm not so sure those rallies are going to 473 00:26:58,440 --> 00:27:00,959 Speaker 1: be able to do that, but they do show that 474 00:27:01,000 --> 00:27:03,600 Speaker 1: he's got energy on the ground, and there is something 475 00:27:03,640 --> 00:27:05,920 Speaker 1: to say for that, you know, But I do wonder too. 476 00:27:05,920 --> 00:27:09,560 Speaker 1: We have a story Jennie a Ryan te Becker back 477 00:27:09,600 --> 00:27:12,960 Speaker 1: with reporting how President Trump isn't heating his aids. Advice 478 00:27:13,000 --> 00:27:15,840 Speaker 1: to focus on the economy like this, You know, if 479 00:27:15,880 --> 00:27:19,720 Speaker 1: there's an election playbook, it's about the economy. And if 480 00:27:19,880 --> 00:27:22,720 Speaker 1: you can point to are you doing better than you were? 481 00:27:22,960 --> 00:27:25,879 Speaker 1: Or have you done well under my administration? You know, 482 00:27:26,080 --> 00:27:28,760 Speaker 1: that will often get people to pull the lever for 483 00:27:28,800 --> 00:27:31,439 Speaker 1: you when they go into the voting booth. Why is 484 00:27:31,480 --> 00:27:35,240 Speaker 1: the president maybe not running on that? These to me 485 00:27:35,440 --> 00:27:38,760 Speaker 1: are this is the most confounding aspect of this campaign 486 00:27:39,080 --> 00:27:41,879 Speaker 1: is that he wins when it comes to the economy. 487 00:27:42,240 --> 00:27:44,840 Speaker 1: People Most people think that they are better off than 488 00:27:44,840 --> 00:27:48,159 Speaker 1: they were before despite the pandemic, which is quite remarkable 489 00:27:48,480 --> 00:27:51,040 Speaker 1: and to his credit, and he can point to the 490 00:27:51,040 --> 00:27:54,480 Speaker 1: economy before the pandemic and say he was the leader 491 00:27:54,560 --> 00:27:58,000 Speaker 1: of a really strong economy. But he hasn't been able 492 00:27:58,040 --> 00:28:00,720 Speaker 1: to sustain making that case. In any time this thing 493 00:28:00,800 --> 00:28:04,480 Speaker 1: refocuses on the pandemic, which is easy to do, it 494 00:28:04,520 --> 00:28:07,840 Speaker 1: turns against him. And so that to me is really 495 00:28:07,880 --> 00:28:10,840 Speaker 1: confounding that he hasn't focused on that. And also I 496 00:28:10,880 --> 00:28:14,080 Speaker 1: think that he hasn't focused on the fact that when 497 00:28:14,119 --> 00:28:18,520 Speaker 1: it comes to economic issues like regulation, taxes, the deficit, 498 00:28:18,680 --> 00:28:22,320 Speaker 1: the debt, trade, all these things that we care about jobs, 499 00:28:22,760 --> 00:28:26,760 Speaker 1: that a democratic, all democratic Washington is not what some 500 00:28:26,880 --> 00:28:29,840 Speaker 1: Americans are going to want when they wake up in January. 501 00:28:30,200 --> 00:28:32,480 Speaker 1: And he you know, if he was to make that 502 00:28:32,600 --> 00:28:35,119 Speaker 1: case and say you may or not like me, but 503 00:28:35,280 --> 00:28:37,479 Speaker 1: I will hold the line as I have before, that 504 00:28:37,480 --> 00:28:39,960 Speaker 1: would be a winning case for many people. He hasn't, 505 00:28:40,120 --> 00:28:42,360 Speaker 1: you know, found the will or the ability or the 506 00:28:42,360 --> 00:28:45,120 Speaker 1: willingness to make it for some reason. Jennie, We're in 507 00:28:45,160 --> 00:28:48,120 Speaker 1: the home stretch for five days or four days, Carol 508 00:28:48,240 --> 00:28:52,040 Speaker 1: out from the election. What can happen? Can anything happen 509 00:28:52,680 --> 00:28:54,560 Speaker 1: in the next four days that is actually going to 510 00:28:54,600 --> 00:28:57,680 Speaker 1: fundamentally change the trajectory of this race? Or have already 511 00:28:57,680 --> 00:29:01,200 Speaker 1: people already made up their minds already people have voted. Therefore, 512 00:29:01,400 --> 00:29:04,000 Speaker 1: you know it's locked in at this point, you know, 513 00:29:04,080 --> 00:29:07,080 Speaker 1: I would. I would normally say, yeah, this is pretty 514 00:29:07,120 --> 00:29:11,120 Speaker 1: much in the back. You know, so much seems to 515 00:29:11,160 --> 00:29:13,560 Speaker 1: happen despite what we say. But you know, the county, 516 00:29:13,960 --> 00:29:17,080 Speaker 1: after all, it's twenty twenty, right, it's crazy, but you know, 517 00:29:17,160 --> 00:29:19,640 Speaker 1: the calendar is getting very narrow for a big shake 518 00:29:19,720 --> 00:29:21,560 Speaker 1: up at this point. They you know, some of this 519 00:29:21,720 --> 00:29:24,080 Speaker 1: was tried with the Hunter Biden release doesn't seem to 520 00:29:24,080 --> 00:29:27,240 Speaker 1: have had much impact, so you know, it's becoming harder. 521 00:29:27,560 --> 00:29:30,040 Speaker 1: I think, sure something could happen, it would have to 522 00:29:30,040 --> 00:29:33,400 Speaker 1: be pretty major, you know, something to come out about 523 00:29:33,400 --> 00:29:35,560 Speaker 1: one of the candidates that was just you know, turns 524 00:29:35,600 --> 00:29:38,800 Speaker 1: people who supported them against them. But even so, as 525 00:29:38,800 --> 00:29:41,760 Speaker 1: you said, we've had so many people vote already they 526 00:29:41,760 --> 00:29:44,720 Speaker 1: can't take back their votes. So those kinds of things 527 00:29:44,760 --> 00:29:47,600 Speaker 1: make it increasingly tough to turn this ship around, if 528 00:29:47,600 --> 00:29:50,040 Speaker 1: you will. At this point, does that early voting, you know, 529 00:29:50,080 --> 00:29:52,440 Speaker 1: I think it tends to lean towards Democrats, but I 530 00:29:52,440 --> 00:29:54,240 Speaker 1: don't know if that's true. We just got thirty seconds 531 00:29:54,320 --> 00:29:56,840 Speaker 1: left here. Can you make any assumptions or maybe not. 532 00:29:57,480 --> 00:29:59,880 Speaker 1: It's hard to know because just because you're registered Democrat 533 00:30:00,160 --> 00:30:02,520 Speaker 1: mean you vote Democratic. So that's something to keep in mind. 534 00:30:02,560 --> 00:30:04,760 Speaker 1: All right, good stuff as always, Genie, Genie, thank you 535 00:30:04,800 --> 00:30:05,960 Speaker 1: so much. As we always say, I want to be 536 00:30:06,040 --> 00:30:08,160 Speaker 1: in her policy class. I just do. I just do. 537 00:30:08,400 --> 00:30:12,080 Speaker 1: Genie's political contributor. I hear at Bloomberg News professor, a 538 00:30:12,160 --> 00:30:15,000 Speaker 1: political science at Iona College. Really a great go to 539 00:30:15,120 --> 00:30:17,920 Speaker 1: when it comes to this campaign and the election. On 540 00:30:17,960 --> 00:30:25,840 Speaker 1: the phone from New Rochelle, New York, I'm roc journal. Yeah, 541 00:30:25,920 --> 00:30:30,959 Speaker 1: but you let me drive. Oh no, no, no no, no home, honey, please, 542 00:30:31,040 --> 00:30:34,400 Speaker 1: I'll do the ding Drivelt me. I want to drive, 543 00:30:37,160 --> 00:30:50,240 Speaker 1: just drive, baby, the question try this is the drive 544 00:30:50,320 --> 00:30:54,160 Speaker 1: to the globe. Commun Thanks, We'll drying us down on 545 00:30:54,360 --> 00:30:58,440 Speaker 1: Bloomberg Radio. All right, Carol, we are just about eleven 546 00:30:58,520 --> 00:31:00,959 Speaker 1: minutes to the closing alone. Of course, we've got a 547 00:31:00,960 --> 00:31:04,360 Speaker 1: lot of big tech names, important results in just about 548 00:31:04,360 --> 00:31:07,040 Speaker 1: ten twelve minutes time. Yeah, they we're gonna be crossing 549 00:31:07,360 --> 00:31:10,640 Speaker 1: the Bloomberg terminal fast and furiously. Let's get to the 550 00:31:10,720 --> 00:31:13,080 Speaker 1: drive to the close because with us, as Larry Pittkowski, 551 00:31:13,200 --> 00:31:16,560 Speaker 1: he's managing partner and portfolio manager good Haven Capital Management. 552 00:31:16,880 --> 00:31:19,360 Speaker 1: He's back with us. He's based in Milbourne, New Jersey, 553 00:31:19,360 --> 00:31:22,200 Speaker 1: and that's where we find him on the phone. This Thursday, Larry, 554 00:31:22,240 --> 00:31:24,800 Speaker 1: good to have you here with us, a very different 555 00:31:24,840 --> 00:31:28,200 Speaker 1: tone from what we got from yesterday. And we saw 556 00:31:28,920 --> 00:31:31,240 Speaker 1: UH stocks kind of picking up some momentum in the 557 00:31:31,320 --> 00:31:33,720 Speaker 1: last hour, so so we're kind of bouncing around our 558 00:31:33,800 --> 00:31:37,000 Speaker 1: highs of the day. I don't know what do you 559 00:31:37,600 --> 00:31:40,200 Speaker 1: focus on right now in our world? There's so many 560 00:31:40,240 --> 00:31:42,840 Speaker 1: macro stories out there right now, the big ones, the election, 561 00:31:42,960 --> 00:31:47,360 Speaker 1: the virus, the lack of stimulus, waiting for stimulus. UM, 562 00:31:47,440 --> 00:31:52,600 Speaker 1: what's the most important to you, the most important to us, Carol, 563 00:31:52,680 --> 00:31:56,640 Speaker 1: Or what do we think about our companies and what 564 00:31:56,960 --> 00:31:59,440 Speaker 1: are the few journeyings going to be? And what do 565 00:31:59,480 --> 00:32:01,800 Speaker 1: we think about the future values and what price are 566 00:32:01,840 --> 00:32:05,040 Speaker 1: we paying for them? And that's the most critical thing, 567 00:32:05,080 --> 00:32:08,520 Speaker 1: you know, in investing UH, you have to decide if 568 00:32:08,600 --> 00:32:11,840 Speaker 1: a piece of information is important and is it knowable. 569 00:32:11,840 --> 00:32:13,960 Speaker 1: There's all kinds of things that are important, but they're 570 00:32:13,960 --> 00:32:16,080 Speaker 1: really not knowable. And I think most of the macro 571 00:32:16,240 --> 00:32:20,240 Speaker 1: stuff is not knowable. And I think it's the who's 572 00:32:20,280 --> 00:32:22,760 Speaker 1: an investor of any sort to just try and focus 573 00:32:22,800 --> 00:32:25,000 Speaker 1: on the businesses that you own and what you think 574 00:32:25,000 --> 00:32:28,760 Speaker 1: about their future earnings capabilities are future drivers of value? 575 00:32:28,800 --> 00:32:30,440 Speaker 1: And then try and pay an attractive price. And for 576 00:32:30,520 --> 00:32:34,520 Speaker 1: us at good Haven, we did a little buying yesterday 577 00:32:34,680 --> 00:32:36,640 Speaker 1: and we haven't done any buying today. And I think 578 00:32:36,840 --> 00:32:41,880 Speaker 1: that is consistent with the opportunistic way that I try 579 00:32:41,960 --> 00:32:46,040 Speaker 1: and invest money. It's so funny because everything that was 580 00:32:46,080 --> 00:32:49,280 Speaker 1: true yesterday is true again today. The virus is still spreading, 581 00:32:49,600 --> 00:32:52,480 Speaker 1: there's still no stimulus, there's still a lot of uncertainty 582 00:32:52,960 --> 00:32:55,080 Speaker 1: that's hanging in the air when it comes to the election. 583 00:32:55,680 --> 00:32:58,480 Speaker 1: Um so do you expect this kind of volatility, the 584 00:32:58,680 --> 00:33:04,040 Speaker 1: daily ups and downs to continue. I think that one should. 585 00:33:04,080 --> 00:33:06,000 Speaker 1: I I've written for some time that I think the 586 00:33:06,080 --> 00:33:09,680 Speaker 1: nature of markets, you know, the percentage of market activity 587 00:33:09,720 --> 00:33:13,800 Speaker 1: that's electronic driven, either high frequency trading, quads, passive money 588 00:33:14,160 --> 00:33:16,320 Speaker 1: is a very high percentage. And a lot of those 589 00:33:17,040 --> 00:33:20,080 Speaker 1: strategies to some extent or on autopilot, and a lot 590 00:33:20,120 --> 00:33:22,600 Speaker 1: of it is sell weakness by strength, and so I 591 00:33:22,640 --> 00:33:25,680 Speaker 1: think one should expect more volatility. The key as an 592 00:33:25,720 --> 00:33:29,120 Speaker 1: investor is how do you attempt to take advantage of that? 593 00:33:29,360 --> 00:33:32,920 Speaker 1: You know, for yourself or for your clients of any sort. 594 00:33:32,960 --> 00:33:34,920 Speaker 1: And I think you have to be prepared. I think 595 00:33:34,920 --> 00:33:36,760 Speaker 1: it helps to not be leveraged, and I think you 596 00:33:36,760 --> 00:33:38,600 Speaker 1: need to have some liquidity, and then I think you 597 00:33:38,640 --> 00:33:41,400 Speaker 1: have to have your shopping list and have done your homeworker. 598 00:33:41,800 --> 00:33:44,160 Speaker 1: I don't think the volatility is going away. You know, 599 00:33:44,400 --> 00:33:47,480 Speaker 1: put twenty people in a room, investment guys, gals, you 600 00:33:47,560 --> 00:33:50,280 Speaker 1: name it, and you know, put out a Macro issue 601 00:33:50,280 --> 00:33:51,920 Speaker 1: and you get ten to say one thing and ten 602 00:33:52,000 --> 00:33:53,360 Speaker 1: to say the other. I mean, I feel that way 603 00:33:53,360 --> 00:33:55,120 Speaker 1: about Macro, like you can go kind of a lot 604 00:33:55,120 --> 00:33:57,560 Speaker 1: of different directions. That it is about knowing your companies, 605 00:33:57,600 --> 00:34:00,600 Speaker 1: knowing your investments, knowing the fundamentals, and when to kind 606 00:34:00,600 --> 00:34:03,480 Speaker 1: of pull the lever. So, Larry, let's drill down. You know, 607 00:34:03,760 --> 00:34:05,479 Speaker 1: what are some of the names that are coming up 608 00:34:05,480 --> 00:34:07,400 Speaker 1: on your radar? Where would you commit new money to 609 00:34:07,560 --> 00:34:11,040 Speaker 1: right now? Well, you know, it's it's an interesting question. 610 00:34:11,120 --> 00:34:16,640 Speaker 1: You know. Back ind a younger Larry Pittkowski found himself 611 00:34:16,680 --> 00:34:20,200 Speaker 1: managing money during a period where there were excesses in 612 00:34:20,239 --> 00:34:22,440 Speaker 1: certain areas and there were other sectors that had been 613 00:34:22,520 --> 00:34:26,160 Speaker 1: kind of left behind. And at that during that period, 614 00:34:26,400 --> 00:34:28,960 Speaker 1: I happen to have found a bunch of opportunities in 615 00:34:29,000 --> 00:34:33,520 Speaker 1: and around the property and casualty insurance area, which for 616 00:34:33,719 --> 00:34:38,000 Speaker 1: the next eight years or so, uh, you know, proved 617 00:34:38,000 --> 00:34:42,120 Speaker 1: to be a very good place to have investments, while 618 00:34:42,239 --> 00:34:44,920 Speaker 1: other sectors of the market went through a very difficult period. 619 00:34:45,000 --> 00:34:50,760 Speaker 1: So ironically, here is we sit in. I think there 620 00:34:50,760 --> 00:34:54,640 Speaker 1: are a bunch of the sector of things in and 621 00:34:54,680 --> 00:34:57,040 Speaker 1: around the property and casualty insurance area. I think is 622 00:34:57,080 --> 00:35:01,040 Speaker 1: an interesting place to look. And I mentioned that because 623 00:35:01,080 --> 00:35:03,719 Speaker 1: I'm going to read you a a quote from I'm 624 00:35:03,719 --> 00:35:06,200 Speaker 1: not going to tell you the company from an earnings 625 00:35:06,560 --> 00:35:08,719 Speaker 1: report from the other day. A company put out a 626 00:35:08,880 --> 00:35:12,319 Speaker 1: release and they said, by the way, the average price 627 00:35:12,400 --> 00:35:14,480 Speaker 1: increased for our you know, some of our main products, 628 00:35:14,520 --> 00:35:17,200 Speaker 1: and I'm paraphrasing, was fourteen and a half percent, and 629 00:35:17,239 --> 00:35:21,000 Speaker 1: the top line grew eight percent in some areas. So 630 00:35:21,080 --> 00:35:23,440 Speaker 1: that's not a cloud based company. That happens to be 631 00:35:23,600 --> 00:35:25,880 Speaker 1: w war Berkeley, which is a property and casualty insurance 632 00:35:25,880 --> 00:35:29,480 Speaker 1: company that we don't own. But it's a endemic of 633 00:35:29,600 --> 00:35:32,960 Speaker 1: I think some of the positive tail winds happening in 634 00:35:33,000 --> 00:35:37,880 Speaker 1: that industry. Now the sector will have some very material catastrophes. 635 00:35:37,920 --> 00:35:41,920 Speaker 1: For Q three, you've got hurricanes, you've got you've had 636 00:35:42,000 --> 00:35:44,560 Speaker 1: terrible fires, and you still have some COVID claims, but 637 00:35:45,040 --> 00:35:48,800 Speaker 1: I think a good haven. The question that I asked myself, 638 00:35:48,840 --> 00:35:51,719 Speaker 1: and you know i'm assisted here in the portfolio by 639 00:35:52,080 --> 00:35:55,640 Speaker 1: Artie Kak, is where are their sectors that the market 640 00:35:55,760 --> 00:35:59,319 Speaker 1: has potentially not recognized where there might still be bargains. 641 00:35:59,360 --> 00:36:02,600 Speaker 1: Because there's all kinds of interesting sectors that the market 642 00:36:02,680 --> 00:36:05,879 Speaker 1: has recognized them, and you know we own some of those, 643 00:36:05,880 --> 00:36:08,319 Speaker 1: which is fine, But where might there be opportunities? I 644 00:36:08,320 --> 00:36:12,600 Speaker 1: think here are potential opportunities. Well, you say you're looking 645 00:36:12,600 --> 00:36:14,680 Speaker 1: for a bargain. Can I assume that means you're staying 646 00:36:14,719 --> 00:36:18,840 Speaker 1: away from large cap tech? Well, we all we you know, 647 00:36:18,880 --> 00:36:21,879 Speaker 1: we have a material exposure to Alphabet, which we've owned 648 00:36:21,920 --> 00:36:24,040 Speaker 1: for a long time, and we've made an enormous amount 649 00:36:24,040 --> 00:36:27,600 Speaker 1: of money on I and so. And I don't think 650 00:36:27,640 --> 00:36:31,759 Speaker 1: it's priced at a ridiculous level. I think it's you know, 651 00:36:31,840 --> 00:36:37,399 Speaker 1: probably like a mid twenty uh mid twenties pe xtra 652 00:36:37,520 --> 00:36:40,600 Speaker 1: cash to earnings, which you know, for a company of 653 00:36:40,600 --> 00:36:43,839 Speaker 1: that quality, where I think the growth will get back 654 00:36:43,880 --> 00:36:47,160 Speaker 1: to some normal level and it so dominates its world. 655 00:36:47,239 --> 00:36:49,759 Speaker 1: I don't think that's a ridiculous level. There are all 656 00:36:49,840 --> 00:36:53,239 Speaker 1: kinds of other sectors in and around tech where there 657 00:36:53,320 --> 00:36:56,040 Speaker 1: seemed to be some material access is. I don't think, 658 00:36:56,600 --> 00:36:58,480 Speaker 1: you know, Alphabet's one of them, and that's not a 659 00:36:58,480 --> 00:37:00,640 Speaker 1: prediction about what earnings are going to in you know, 660 00:37:00,719 --> 00:37:04,279 Speaker 1: twenty minutes. But there are plenty of obvious areas of 661 00:37:04,760 --> 00:37:08,319 Speaker 1: material access is. But the nice thing about investing, if 662 00:37:08,360 --> 00:37:12,680 Speaker 1: you're managing a portfolio that you know somewhat concentrated and 663 00:37:12,680 --> 00:37:14,480 Speaker 1: you have a lot of flexibilities, you don't have to 664 00:37:14,480 --> 00:37:16,759 Speaker 1: go to where their excesses. You can go instead to 665 00:37:16,800 --> 00:37:20,120 Speaker 1: where you think there are opportunities. What do you say, 666 00:37:20,120 --> 00:37:22,440 Speaker 1: And just got about forty seconds here. I think among 667 00:37:22,440 --> 00:37:25,000 Speaker 1: your top holdings is Berkshire and then you've got Alphabet, 668 00:37:25,040 --> 00:37:29,040 Speaker 1: Like it's an interesting kind of very different companies. Yeah, 669 00:37:29,120 --> 00:37:32,160 Speaker 1: and berke Shure. I feel like it's going through some adjustments, uh, 670 00:37:32,320 --> 00:37:35,320 Speaker 1: you know, in terms of some of its holdings and investments, 671 00:37:35,320 --> 00:37:37,600 Speaker 1: but nonetheless two very different companies. What does that say 672 00:37:37,600 --> 00:37:39,960 Speaker 1: about kind of your thinking? And just got about forty 673 00:37:39,960 --> 00:37:42,720 Speaker 1: seconds here. Very quickly, I think what it says about 674 00:37:43,280 --> 00:37:45,799 Speaker 1: my thinking, good haven thinking is we have an eclectic 675 00:37:45,840 --> 00:37:49,480 Speaker 1: approach to where we may find opportunities. I think it's 676 00:37:49,480 --> 00:37:52,480 Speaker 1: a mistake to just pigeonhole one self and to say 677 00:37:52,600 --> 00:37:54,439 Speaker 1: it has to have a certain metric of some sort. 678 00:37:54,480 --> 00:37:58,279 Speaker 1: We think Berkshire's is now our biggest holding, is very attractive. 679 00:37:58,680 --> 00:38:02,960 Speaker 1: It has material holdings in and aground property and casualty 680 00:38:03,000 --> 00:38:05,680 Speaker 1: insurance and reinsurance which look to have a tail wind. 681 00:38:05,719 --> 00:38:10,160 Speaker 1: And I like the evolution of the uh Rod and 682 00:38:10,280 --> 00:38:14,000 Speaker 1: Ted and the investment portfolio. I think it's a healthy 683 00:38:14,120 --> 00:38:16,520 Speaker 1: thing for the future of the business. All right, Larry, 684 00:38:16,560 --> 00:38:19,440 Speaker 1: take care good to get some thoughts from you. Larry Pitkowsky, 685 00:38:19,480 --> 00:38:22,480 Speaker 1: Imaging Partner, Portfolio managing, good Haven Capital Management, on the 686 00:38:22,520 --> 00:38:25,960 Speaker 1: phone in Milinburgh, New Jersey. Thanks so much for listening 687 00:38:25,960 --> 00:38:29,520 Speaker 1: to Bloomberg Business Week. Download the podcast on iTunes, SoundCloud 688 00:38:29,600 --> 00:38:31,719 Speaker 1: or at Bloomberg dot com, and be sure to check 689 00:38:31,719 --> 00:38:34,040 Speaker 1: out our daily radio show at two pm Eastern on 690 00:38:34,120 --> 00:38:36,600 Speaker 1: Bloomberg Radio. To be sure to watch us too on 691 00:38:36,680 --> 00:38:39,080 Speaker 1: YouTube by searching Bloomberg Global News.