1 00:00:00,720 --> 00:00:03,720 Speaker 1: This is Bloomberg Business Week. I'm Carol Masser and I'm 2 00:00:03,800 --> 00:00:06,320 Speaker 1: Jason Kelly. We're right here every day bringing you the 3 00:00:06,400 --> 00:00:11,160 Speaker 1: latest news from the world's of business and finance, plus technology, politics, economics, 4 00:00:11,240 --> 00:00:14,280 Speaker 1: all harnessing the power of Business Week reporters and editors. 5 00:00:14,440 --> 00:00:16,439 Speaker 1: And of course Carol that's part of a team of 6 00:00:16,520 --> 00:00:20,439 Speaker 1: twenty seven hundred journalists and analysts more than a hundred 7 00:00:20,480 --> 00:00:23,280 Speaker 1: and twenty countries and Jason. You can download Bloomberg Business 8 00:00:23,280 --> 00:00:26,239 Speaker 1: Week on iTunes, SoundCloud, al Bloomberg dot com. You can 9 00:00:26,280 --> 00:00:28,640 Speaker 1: also listen to our radio show at two pm Eastern 10 00:00:28,680 --> 00:00:31,560 Speaker 1: on Bloomberg Radio every weekday, or watch us on YouTube 11 00:00:31,600 --> 00:00:36,080 Speaker 1: by searching Bloomberg Global News. So we got to set 12 00:00:36,080 --> 00:00:39,519 Speaker 1: this Business Week agenda, Carol, with these FED minutes, Yeah, totally, 13 00:00:39,560 --> 00:00:41,639 Speaker 1: And I gotta say I just opened them up off 14 00:00:41,680 --> 00:00:44,479 Speaker 1: the FED website, so we're all kind of reading in 15 00:00:44,520 --> 00:00:47,600 Speaker 1: real time at the same time. Here's one headline, FED 16 00:00:47,640 --> 00:00:50,520 Speaker 1: officials reviewing the policies trate to Dane July. Well, yeah, 17 00:00:50,560 --> 00:00:54,200 Speaker 1: that's what they did. So looking back at it, let's 18 00:00:54,200 --> 00:00:56,520 Speaker 1: get into it with people who are far smarter than 19 00:00:56,520 --> 00:00:58,360 Speaker 1: me when it comes to the Fed. Kathleen Hayes is 20 00:00:58,400 --> 00:01:01,120 Speaker 1: with US Global Economics and Policy editor Bloomberg News. She's 21 00:01:01,120 --> 00:01:04,040 Speaker 1: on our access line. And Dave Wilson also on the 22 00:01:04,080 --> 00:01:07,000 Speaker 1: remote access. He's in New Jersey. He's our stocks editor. 23 00:01:07,040 --> 00:01:09,240 Speaker 1: But Kathleen, let's start with you. Like I said, we 24 00:01:09,319 --> 00:01:11,520 Speaker 1: all are opening this up at the same time in 25 00:01:11,640 --> 00:01:14,960 Speaker 1: real time. Let's just tell stumping out for you. Yeah, 26 00:01:15,200 --> 00:01:17,160 Speaker 1: first of all, this is you. They're usually about fifteen 27 00:01:17,240 --> 00:01:19,720 Speaker 1: or sixteen pages, you know, and and they're not necessarily 28 00:01:20,200 --> 00:01:21,760 Speaker 1: there's a lot in there for anybody. So I know 29 00:01:21,800 --> 00:01:25,440 Speaker 1: our FED team in Washington is uh looking over very quickly. 30 00:01:25,440 --> 00:01:29,760 Speaker 1: They're saying refining the statement could help improve transparency. So 31 00:01:29,840 --> 00:01:32,720 Speaker 1: let's put this in perspective. They're reviewing their policy strategy 32 00:01:32,760 --> 00:01:35,880 Speaker 1: at the July meeting. Maybe if they refine the statement 33 00:01:35,880 --> 00:01:40,200 Speaker 1: itself can prove in transparency. Now, everybody who knows, and 34 00:01:40,240 --> 00:01:43,400 Speaker 1: if you don't, the policy statement is about five paragraphs. 35 00:01:43,400 --> 00:01:45,880 Speaker 1: It's kind of boilerplate. They use certain phrases to mean 36 00:01:45,920 --> 00:01:47,800 Speaker 1: certain things. They change a word here or there, and 37 00:01:47,840 --> 00:01:49,840 Speaker 1: I think it leaves a lot of people glad. Number one, 38 00:01:49,880 --> 00:01:52,800 Speaker 1: the FED chair J Powell comes out and explains what 39 00:01:52,880 --> 00:01:55,640 Speaker 1: they did and why and takes tons of questions from reporters. 40 00:01:55,920 --> 00:01:58,120 Speaker 1: At the same time, I think people feel, couldn't you 41 00:01:58,160 --> 00:02:01,080 Speaker 1: write something longer if you gave us more information about 42 00:02:01,120 --> 00:02:04,040 Speaker 1: what you're thinking and and how it may be something conditional. 43 00:02:04,120 --> 00:02:05,800 Speaker 1: You know, you don't think you're going to raise interest 44 00:02:05,880 --> 00:02:08,200 Speaker 1: rates for a long time unless right, we don't see 45 00:02:08,200 --> 00:02:10,120 Speaker 1: it now, And maybe that's what they're referring to. And 46 00:02:10,160 --> 00:02:12,919 Speaker 1: I remember, of course they've had just almost a year 47 00:02:13,000 --> 00:02:16,800 Speaker 1: long policy review, the FED listening miss meetings all over 48 00:02:16,880 --> 00:02:21,280 Speaker 1: the country, and in September they are widely expected to 49 00:02:21,440 --> 00:02:24,320 Speaker 1: put put their their conclusions out. And one of the 50 00:02:24,360 --> 00:02:25,760 Speaker 1: other things I think we're gonna look for in the 51 00:02:25,800 --> 00:02:31,320 Speaker 1: minutes is anything they said about the inflation target and 52 00:02:31,400 --> 00:02:33,720 Speaker 1: moving from we're gonna keep it at two percent or 53 00:02:33,880 --> 00:02:36,560 Speaker 1: try to get it to two percent recently, and then 54 00:02:36,600 --> 00:02:39,000 Speaker 1: we get there, it's a ceiling and we stop. That's 55 00:02:39,000 --> 00:02:40,720 Speaker 1: what people have assumed, And there's a lot of the 56 00:02:40,800 --> 00:02:43,280 Speaker 1: officials saying, no, what we're gonna say is two percent 57 00:02:43,400 --> 00:02:45,560 Speaker 1: is our target. But when we've been way below the 58 00:02:45,600 --> 00:02:49,840 Speaker 1: target for years, it's okay to go above for a 59 00:02:49,919 --> 00:02:52,040 Speaker 1: while to to get it kind of straightened out. The 60 00:02:52,120 --> 00:02:54,880 Speaker 1: question is how far above and how long above. That's 61 00:02:54,880 --> 00:02:56,760 Speaker 1: the kind of thing. But there's the VET can't really 62 00:02:56,840 --> 00:02:59,680 Speaker 1: change his policy right now. Right virus is still there, 63 00:03:00,000 --> 00:03:02,840 Speaker 1: economy still weak. There's no reason for them to hint 64 00:03:02,880 --> 00:03:07,080 Speaker 1: at anything different. But I think these other questions that 65 00:03:07,080 --> 00:03:09,000 Speaker 1: people are waiting to hear more about it very important. 66 00:03:09,200 --> 00:03:11,840 Speaker 1: I just want to say, in terms of um market reaction, 67 00:03:12,040 --> 00:03:14,560 Speaker 1: seems like from our our fed blog that we're doing 68 00:03:14,560 --> 00:03:16,560 Speaker 1: our live blog, not much reaction yet in the markets. 69 00:03:16,600 --> 00:03:18,440 Speaker 1: If I look at the equity markets, they're pretty much 70 00:03:18,480 --> 00:03:21,200 Speaker 1: where they were prior to the release of the minutes. Uh. 71 00:03:21,240 --> 00:03:22,880 Speaker 1: They are pointing out that the long end of the 72 00:03:22,880 --> 00:03:26,360 Speaker 1: treasury market, those yields turning a little higher, thirty year 73 00:03:26,400 --> 00:03:29,359 Speaker 1: yield at a session peak of one point. But let's 74 00:03:29,520 --> 00:03:31,519 Speaker 1: let's tuck a bit about the equity trade. Dave Wilson 75 00:03:31,560 --> 00:03:33,760 Speaker 1: come on in on that. Well, you have the SMP 76 00:03:33,919 --> 00:03:36,120 Speaker 1: five near its highs of the day, but you haven't 77 00:03:36,160 --> 00:03:39,480 Speaker 1: seen a whole lot of movement. Uh three tents of 78 00:03:39,680 --> 00:03:42,800 Speaker 1: percent gain at most, and and we're approaching that at 79 00:03:42,800 --> 00:03:45,200 Speaker 1: this point. But really the story of the day is 80 00:03:45,280 --> 00:03:49,120 Speaker 1: Apple poking its head above two trillion dollars in market value. 81 00:03:49,400 --> 00:03:52,680 Speaker 1: First US company ever to do that. You know, Saudia 82 00:03:52,800 --> 00:03:55,600 Speaker 1: Ramco when they went public was just above two trillion 83 00:03:55,640 --> 00:03:59,680 Speaker 1: when the shares started trading. So that's perhaps the next milestone. 84 00:03:59,720 --> 00:04:04,120 Speaker 1: Four are Apple in terms of their evaluation that you know, 85 00:04:04,560 --> 00:04:08,440 Speaker 1: Apple at least one big reason why you know, stocks 86 00:04:08,440 --> 00:04:10,560 Speaker 1: are moving up at this point. And then you can 87 00:04:10,600 --> 00:04:13,760 Speaker 1: point the target which had earnings out that we're pretty 88 00:04:13,800 --> 00:04:16,760 Speaker 1: well received and those shares up twelve percent leading to 89 00:04:16,920 --> 00:04:20,360 Speaker 1: SMP fire. Yeah. I do want to say the market though, 90 00:04:20,520 --> 00:04:23,719 Speaker 1: coming down a little bit. Yeah, just in the last 91 00:04:23,760 --> 00:04:27,040 Speaker 1: couple of seconds, and it must be to somebody found 92 00:04:27,120 --> 00:04:30,160 Speaker 1: something they didn't like or you know, we're getting close 93 00:04:30,200 --> 00:04:31,680 Speaker 1: to the highs of the day, and of course you're 94 00:04:31,960 --> 00:04:35,000 Speaker 1: at record levels for the SMP five hundred above where 95 00:04:35,040 --> 00:04:37,960 Speaker 1: we were yesterday when we broke the February high. So 96 00:04:38,360 --> 00:04:40,760 Speaker 1: you know, it's understandable perhaps people might want to pull 97 00:04:40,800 --> 00:04:43,240 Speaker 1: back a bit. And so, Kathleen, what is top of 98 00:04:43,279 --> 00:04:46,040 Speaker 1: mind for the Fed right now in this moment, because 99 00:04:46,040 --> 00:04:48,080 Speaker 1: you know, this is a little bit backward looking in 100 00:04:48,200 --> 00:04:49,760 Speaker 1: terms of you know, sort of figuring out what they 101 00:04:49,760 --> 00:04:53,960 Speaker 1: were thinking. We know that this is fast moving economically, medically, 102 00:04:54,000 --> 00:04:56,120 Speaker 1: all of these things. You're talking to people all the 103 00:04:56,120 --> 00:04:58,560 Speaker 1: time in and around the FED. What are they thinking 104 00:04:58,560 --> 00:05:02,040 Speaker 1: about right now? Well, they're thinking about the fact that 105 00:05:02,400 --> 00:05:06,280 Speaker 1: they have done things to support the economy that have helped, 106 00:05:07,080 --> 00:05:08,800 Speaker 1: you know, so support it. You know, there are a 107 00:05:08,839 --> 00:05:11,720 Speaker 1: lot of businesses that have been able to stay on 108 00:05:11,760 --> 00:05:15,080 Speaker 1: there on their feet because the FED provided lots of liquidity. 109 00:05:15,600 --> 00:05:19,040 Speaker 1: They've done everything they can to stabilize markets, and they 110 00:05:19,200 --> 00:05:22,560 Speaker 1: every time somebody talks, sometimes whether they're asked or not, 111 00:05:22,760 --> 00:05:25,479 Speaker 1: they say, and we have done what we can do 112 00:05:25,520 --> 00:05:28,239 Speaker 1: with monetary policy. As J. Powell has said, the FED 113 00:05:28,600 --> 00:05:32,559 Speaker 1: can lend, but it cannot spend money. Right that goes 114 00:05:32,600 --> 00:05:35,440 Speaker 1: to Congress. That's where the action has to come next. 115 00:05:35,480 --> 00:05:38,039 Speaker 1: I think they're probably watching these stalled stimulus talks as 116 00:05:38,120 --> 00:05:41,039 Speaker 1: much as anything else. They've got to be watching virus numbers. 117 00:05:41,200 --> 00:05:44,560 Speaker 1: We've got a great chart on the Bloomberg it's virus hotspots. 118 00:05:44,839 --> 00:05:47,240 Speaker 1: The top line is the US and those numbers have 119 00:05:47,360 --> 00:05:49,640 Speaker 1: come way down compared to the peak in July six 120 00:05:50,240 --> 00:05:52,600 Speaker 1: less than half of the what they were seventy eight 121 00:05:52,640 --> 00:05:56,000 Speaker 1: thousand new cases being is a total where was then 122 00:05:56,040 --> 00:05:59,120 Speaker 1: our new ones daily whatever it was um and it's 123 00:05:59,160 --> 00:06:01,600 Speaker 1: down to half. It's in half and the Fed is 124 00:06:01,720 --> 00:06:04,400 Speaker 1: that all along? You want to determine what the economy does? 125 00:06:04,760 --> 00:06:07,040 Speaker 1: Watch the virus night. There was just a guest on 126 00:06:07,160 --> 00:06:09,640 Speaker 1: with David Weston from the Attorney General from North Carolina. 127 00:06:09,720 --> 00:06:11,680 Speaker 1: Wasn't it saying, you know, they sent their kids back 128 00:06:11,680 --> 00:06:13,920 Speaker 1: to school and now they got to send him home. Uh. 129 00:06:14,160 --> 00:06:15,680 Speaker 1: That's the kind of thing that you get, get a 130 00:06:15,680 --> 00:06:17,760 Speaker 1: little momentum going maybe and then it gets it gets 131 00:06:17,800 --> 00:06:20,599 Speaker 1: hobbled again. Yeah, all right, guys, thank you so much. 132 00:06:20,720 --> 00:06:24,240 Speaker 1: Kathleen Hayes Apple, Bloomberg News, Global Economics and Policy Theater, 133 00:06:24,360 --> 00:06:27,560 Speaker 1: Dave Wilson, stocks Are, Bloomberg News. This is Bloomberg Business 134 00:06:27,600 --> 00:06:31,599 Speaker 1: Week with Carol Masser and Jason Kelly on Bloomberg Radio. 135 00:06:31,880 --> 00:06:35,360 Speaker 1: Let's talk a little bit about schools reopening, the medical 136 00:06:35,400 --> 00:06:38,359 Speaker 1: side of that, the social side of it. And it 137 00:06:38,480 --> 00:06:42,680 Speaker 1: is a complicated issue, Carol, because not everyone has the 138 00:06:42,720 --> 00:06:45,839 Speaker 1: same access to healthcare, not everyone has the same sort 139 00:06:45,880 --> 00:06:48,800 Speaker 1: of job. We have to worry about the most vulnerable 140 00:06:49,360 --> 00:06:52,240 Speaker 1: among us. And that's exactly what Dr Ramon Tilladge does. 141 00:06:52,279 --> 00:06:54,600 Speaker 1: He's the founder and chairman of some most community. Here 142 00:06:54,680 --> 00:06:57,800 Speaker 1: joining us on the phone from New York City. Dr Todge, 143 00:06:57,839 --> 00:07:00,640 Speaker 1: really nice to have you here with Carolin myself. I'm 144 00:07:00,800 --> 00:07:02,679 Speaker 1: thank you for you to help me with you. Please. 145 00:07:03,600 --> 00:07:07,520 Speaker 1: So we are talking so much about reopening schools, especially 146 00:07:07,560 --> 00:07:10,800 Speaker 1: in New York City. Is the world's the nations, excuse me, 147 00:07:10,840 --> 00:07:14,080 Speaker 1: the largest school system. What needs to happen for it 148 00:07:14,160 --> 00:07:17,320 Speaker 1: to be safe? Well, in order for me to be saved, 149 00:07:17,640 --> 00:07:20,560 Speaker 1: it should be a discussion between all the people, especially 150 00:07:20,600 --> 00:07:25,240 Speaker 1: the partents with the children's, the school teachers, the doctors, 151 00:07:25,240 --> 00:07:28,280 Speaker 1: obviously the authorities. Well, at this point, I don't see 152 00:07:28,320 --> 00:07:31,720 Speaker 1: that happen. We've been trying for that to happen, especially 153 00:07:31,760 --> 00:07:35,000 Speaker 1: as the doctor to talk and be part of the conversation. 154 00:07:35,120 --> 00:07:39,080 Speaker 1: But we been the one and the I say, in 155 00:07:39,120 --> 00:07:41,160 Speaker 1: the front of the battle from the beginnings as much 156 00:07:41,200 --> 00:07:44,600 Speaker 1: we've been doing this testing education, and I don't think 157 00:07:44,600 --> 00:07:47,600 Speaker 1: we're ready and to open the school because nothing has 158 00:07:47,680 --> 00:07:51,120 Speaker 1: changed as much. What do you mean nothing has changed 159 00:07:51,120 --> 00:07:54,520 Speaker 1: since March? Well, yeah, well let me ask you a question. 160 00:07:55,200 --> 00:07:58,040 Speaker 1: In March, why do we close the school? We've closer 161 00:07:58,120 --> 00:08:01,720 Speaker 1: because the bigger skill, there's no vaccine, there's no treatment 162 00:08:02,280 --> 00:08:04,400 Speaker 1: anything of those things have changed. I don't think so, 163 00:08:06,640 --> 00:08:10,720 Speaker 1: and so why So why then do you think people 164 00:08:10,760 --> 00:08:13,200 Speaker 1: are rushing so much to open schools? Is it an 165 00:08:13,200 --> 00:08:16,920 Speaker 1: economic question? Is it that? I mean, we talked about 166 00:08:16,920 --> 00:08:19,200 Speaker 1: this all the time, that people, you know, need their 167 00:08:19,280 --> 00:08:21,200 Speaker 1: kids to go back to school so that they can 168 00:08:21,200 --> 00:08:24,160 Speaker 1: continue to work. I know this is something you think 169 00:08:24,200 --> 00:08:27,600 Speaker 1: a lot about. So why why is the pressure there? Well, 170 00:08:27,640 --> 00:08:30,080 Speaker 1: there's no one answer for when you dealing with the 171 00:08:30,120 --> 00:08:33,600 Speaker 1: pandemic that nobody knew about it. Nobody has a hundred 172 00:08:33,679 --> 00:08:36,679 Speaker 1: years and most of our scholars has failed to tell 173 00:08:36,720 --> 00:08:39,120 Speaker 1: us the truth of these virus. But we on there 174 00:08:39,120 --> 00:08:42,160 Speaker 1: forth from being since March telling us what's going on 175 00:08:42,280 --> 00:08:46,160 Speaker 1: right now? We know this for two in our neighborhoods 176 00:08:46,559 --> 00:08:49,079 Speaker 1: how tested positive in our tests that we do. We 177 00:08:49,240 --> 00:08:53,439 Speaker 1: ins almost two thousand doctors or those one more than 178 00:08:53,480 --> 00:08:57,679 Speaker 1: two hundred hundred family practices will take care of two 179 00:08:57,720 --> 00:09:01,400 Speaker 1: hundred kids, which is almost goes to a four fifth 180 00:09:01,880 --> 00:09:04,120 Speaker 1: the faith for all the kids in New York City 181 00:09:04,440 --> 00:09:08,160 Speaker 1: we've been testing. Then forty two our neighbors are positive. 182 00:09:08,440 --> 00:09:10,960 Speaker 1: Let's the average between the four main border that we 183 00:09:10,960 --> 00:09:14,400 Speaker 1: are on. Then it that's true. I mean the fifth 184 00:09:14,640 --> 00:09:17,719 Speaker 1: percent has not seen the virus yet. You opened the 185 00:09:17,760 --> 00:09:20,760 Speaker 1: school and the numbers that the mayor or the government 186 00:09:20,760 --> 00:09:23,560 Speaker 1: has given us one to two percent. That mean for 187 00:09:23,640 --> 00:09:29,000 Speaker 1: every every thousand kids twenty to ten really positive, you're 188 00:09:29,600 --> 00:09:31,679 Speaker 1: join the other one who are negative. So you're saying, 189 00:09:31,800 --> 00:09:35,160 Speaker 1: you guys have testing kids in communities and you represent 190 00:09:35,559 --> 00:09:38,600 Speaker 1: largely many of certainly the public school systems in New 191 00:09:38,679 --> 00:09:42,400 Speaker 1: York City. Of those kids are positive, I'm guessing a 192 00:09:42,440 --> 00:09:45,800 Speaker 1: fair manner asymptomatic. And the concern is that they're going 193 00:09:45,840 --> 00:09:49,480 Speaker 1: to be in the community and there will be spread. No, 194 00:09:49,679 --> 00:09:52,520 Speaker 1: let me tell you forty two percent positive in blood tests, 195 00:09:52,840 --> 00:09:56,800 Speaker 1: I mean they already had the disease. That means the 196 00:09:56,960 --> 00:10:02,480 Speaker 1: fifty percent and haven't seen virus. Therefore, those one will 197 00:10:02,520 --> 00:10:05,079 Speaker 1: be supposed in the school with the ten with the 198 00:10:05,120 --> 00:10:07,520 Speaker 1: one or two percent that it is estimated that they 199 00:10:07,520 --> 00:10:11,280 Speaker 1: say is positively. Now, therefore, for each thousand kids ten 200 00:10:11,400 --> 00:10:15,040 Speaker 1: to twenty went to the school we positive, then the 201 00:10:15,080 --> 00:10:19,120 Speaker 1: other one will get infected. The majority will never have symptoms, 202 00:10:19,160 --> 00:10:21,760 Speaker 1: but they going back to the houses. Who's gonna get infected? 203 00:10:22,080 --> 00:10:25,720 Speaker 1: Their partients and their grandparents, the people who are the 204 00:10:25,800 --> 00:10:28,880 Speaker 1: most need. They have to find the food day today. 205 00:10:29,240 --> 00:10:31,040 Speaker 1: They don't have a steady job. They lost their job, 206 00:10:31,360 --> 00:10:33,520 Speaker 1: they couldn't find medication, they had no in students. We've 207 00:10:33,520 --> 00:10:35,760 Speaker 1: been hitting very home. But you don't think with New 208 00:10:35,800 --> 00:10:38,120 Speaker 1: York City. We talked about this before we started this 209 00:10:38,160 --> 00:10:40,760 Speaker 1: interview for a New York audience. You don't think um 210 00:10:40,840 --> 00:10:44,000 Speaker 1: Dr Tillage. We talked about the city's positive COVID nineteen 211 00:10:44,000 --> 00:10:46,440 Speaker 1: tests rate, you know, to the lowest since the pandemic 212 00:10:46,480 --> 00:10:49,199 Speaker 1: began in March. I mean the numbers have come way down. 213 00:10:49,320 --> 00:10:53,680 Speaker 1: You don't think that's strong enough, good enough, safe enough 214 00:10:53,800 --> 00:10:56,480 Speaker 1: for kids to go back. I just give you the example. 215 00:10:56,880 --> 00:10:59,000 Speaker 1: I gotta ask your kids. Will you just send it 216 00:10:59,640 --> 00:11:02,800 Speaker 1: knowing that if you have one percent and the school 217 00:11:02,880 --> 00:11:06,280 Speaker 1: has a thousand kids then will be positive. That's one percent. Then, 218 00:11:07,240 --> 00:11:10,000 Speaker 1: I mean those things we jump around kids are kids 219 00:11:10,520 --> 00:11:14,240 Speaker 1: in the school with in our neighborhoods are still negative 220 00:11:14,720 --> 00:11:17,440 Speaker 1: and they will getting affected. There's no one answer. And 221 00:11:17,480 --> 00:11:19,800 Speaker 1: then you asked me about what happened to stay at home? 222 00:11:19,960 --> 00:11:22,679 Speaker 1: Who's gonna take care of them? The motherity to work, 223 00:11:22,720 --> 00:11:24,640 Speaker 1: the father need to work, or the way they can survive. 224 00:11:25,120 --> 00:11:27,280 Speaker 1: They lose their job if they find a job to do, 225 00:11:27,520 --> 00:11:29,920 Speaker 1: if they do the jog Hando Insurance there's no one 226 00:11:29,960 --> 00:11:33,640 Speaker 1: clear answer, but whichever is the answer has to be 227 00:11:33,720 --> 00:11:37,360 Speaker 1: done between all the past, talking together, the teachers, the parents, 228 00:11:37,400 --> 00:11:41,520 Speaker 1: obviously the doctors in the community. We are willing to 229 00:11:41,559 --> 00:11:44,960 Speaker 1: give five computers if they're going to open. We want 230 00:11:45,000 --> 00:11:48,000 Speaker 1: the nurses in the school, yes, we need them and 231 00:11:48,520 --> 00:11:50,839 Speaker 1: want them to be attached to the primary care. There 232 00:11:50,920 --> 00:11:54,319 Speaker 1: is interchange of information according to all the hip a compliance, 233 00:11:54,600 --> 00:11:58,000 Speaker 1: but we could tell them not only the vaccine that 234 00:11:58,080 --> 00:12:03,080 Speaker 1: could happen at some point, how who and when they 235 00:12:03,120 --> 00:12:05,880 Speaker 1: were in fact, how many are infected and what kind 236 00:12:05,920 --> 00:12:08,319 Speaker 1: of our scene they need for all the diseases, the 237 00:12:08,400 --> 00:12:13,240 Speaker 1: one within the pandemic. So Dr Talaj, what does a 238 00:12:13,400 --> 00:12:16,120 Speaker 1: good plan look like? What do we need to do 239 00:12:16,240 --> 00:12:18,320 Speaker 1: at this point? Do we just need to wait for 240 00:12:18,360 --> 00:12:22,080 Speaker 1: a vaccine? There's no question, there is no one answer 241 00:12:22,160 --> 00:12:25,760 Speaker 1: for that. I agree totally with the Teachers Association. We 242 00:12:25,800 --> 00:12:28,600 Speaker 1: had to wait, We had to implement songs in that 243 00:12:28,640 --> 00:12:31,240 Speaker 1: we all coinsolution and know it's going to be painful. 244 00:12:31,720 --> 00:12:34,280 Speaker 1: But if we open right now the way it is, 245 00:12:34,400 --> 00:12:37,920 Speaker 1: there's no different from March. Still, people are positive out 246 00:12:37,960 --> 00:12:40,120 Speaker 1: there and then we come to the school and the 247 00:12:40,200 --> 00:12:42,880 Speaker 1: kids doesn't see the virus will get effected, and then 248 00:12:42,920 --> 00:12:46,720 Speaker 1: we're bringing home and elderly and parents are gonna die. 249 00:12:47,120 --> 00:12:49,439 Speaker 1: They're gonna be very sick. And we don't want to 250 00:12:49,480 --> 00:12:52,080 Speaker 1: see the same way it happened before in New York City. 251 00:12:52,240 --> 00:12:54,719 Speaker 1: We don't. So I do what and if and if 252 00:12:54,720 --> 00:12:57,320 Speaker 1: they open, I don't see. I don't want to see 253 00:12:57,360 --> 00:13:00,000 Speaker 1: one of my kids going to public hopital to get 254 00:13:00,040 --> 00:13:05,880 Speaker 1: That's it. That's preposterous, petricians or in the school? Well 255 00:13:07,840 --> 00:13:10,360 Speaker 1: is that how I mean? A vaccine is not around 256 00:13:10,400 --> 00:13:12,600 Speaker 1: the corner. We may not even get something before the 257 00:13:12,679 --> 00:13:15,440 Speaker 1: end of the year, and some say maybe it'll be 258 00:13:15,559 --> 00:13:17,680 Speaker 1: a year from now before we really have something that's 259 00:13:17,840 --> 00:13:21,880 Speaker 1: very successful in terms of the immunity it creates, creates 260 00:13:21,880 --> 00:13:25,479 Speaker 1: an individuals. But I do wonder Dr Talaj. In the meantime, 261 00:13:25,800 --> 00:13:28,040 Speaker 1: there is pressure to get kids back to school because 262 00:13:28,440 --> 00:13:31,320 Speaker 1: there are those who, as you know, can hire private 263 00:13:31,320 --> 00:13:35,559 Speaker 1: tutors or you know, learn from home successfully, and so 264 00:13:35,640 --> 00:13:37,720 Speaker 1: we are worried about who gets left behind as a 265 00:13:37,760 --> 00:13:41,520 Speaker 1: result of this. If we could have rapid testing in 266 00:13:41,640 --> 00:13:47,520 Speaker 1: schools and administered by medical professional, would that make it 267 00:13:47,679 --> 00:13:52,560 Speaker 1: safer significantly? Would your opinion change about the safetiness of 268 00:13:52,679 --> 00:13:55,280 Speaker 1: our the safety of having kids back at school. Let 269 00:13:55,320 --> 00:13:56,840 Speaker 1: me ask you a question. Are you talking about to 270 00:13:56,840 --> 00:14:01,240 Speaker 1: do one point one million every three days? I guess 271 00:14:01,320 --> 00:14:04,680 Speaker 1: I guess that's not realistic. Certainly not to that. Let's 272 00:14:04,760 --> 00:14:08,520 Speaker 1: let's start that way. We are. You know, we have physicians, 273 00:14:08,880 --> 00:14:12,400 Speaker 1: We believe in science. Besides that, I'm very trusting in 274 00:14:12,480 --> 00:14:15,880 Speaker 1: God and Christian and tratolly. But I'm telling you right 275 00:14:15,920 --> 00:14:18,440 Speaker 1: now it Cattaby is some kind of business if they 276 00:14:18,440 --> 00:14:20,280 Speaker 1: want to open the school the way we're talking about. 277 00:14:20,400 --> 00:14:22,840 Speaker 1: Nothing has changed this March, and we've been in the 278 00:14:22,880 --> 00:14:24,960 Speaker 1: fourth Front, and we we were the first one to 279 00:14:25,000 --> 00:14:28,040 Speaker 1: get the alert at the beginning of March. I'm being 280 00:14:28,040 --> 00:14:30,960 Speaker 1: sorry they. You know, March we told them seventy of 281 00:14:31,000 --> 00:14:34,680 Speaker 1: the people and queens are positive. Stop we need to isolation. 282 00:14:34,800 --> 00:14:37,560 Speaker 1: They were looking for ventilators. We know what we're saying. 283 00:14:37,760 --> 00:14:41,280 Speaker 1: We don't have the answer yet. There's no science answer 284 00:14:41,440 --> 00:14:46,200 Speaker 1: about this vible. Certainly we know that the vaccine that 285 00:14:46,200 --> 00:14:47,920 Speaker 1: I produced, they want to produce it because they want 286 00:14:47,960 --> 00:14:50,600 Speaker 1: to create antibody and the kids. Now we know the 287 00:14:50,680 --> 00:14:54,480 Speaker 1: forty two of our kids has antibody. That's an average. 288 00:14:54,880 --> 00:14:59,960 Speaker 1: Our neighbor therefore is the most important number. Those are negative, 289 00:15:00,040 --> 00:15:03,400 Speaker 1: they haven't seen the virus. Those we get infected. Here 290 00:15:03,440 --> 00:15:06,480 Speaker 1: we go again, Here we go again, and most of 291 00:15:06,520 --> 00:15:10,280 Speaker 1: the time cheater does not have symptoms. So then do 292 00:15:10,360 --> 00:15:13,720 Speaker 1: we just need to wait for her immunity. Then, well, 293 00:15:13,880 --> 00:15:17,240 Speaker 1: I just tell you what the facts are. Now, we 294 00:15:17,320 --> 00:15:21,880 Speaker 1: sit down together on the teachers, the parents, the stakeholders 295 00:15:21,920 --> 00:15:24,880 Speaker 1: decide this is the way we go single go wrong, 296 00:15:25,400 --> 00:15:28,640 Speaker 1: to go right, it will be casualties. That's probably what's 297 00:15:28,680 --> 00:15:31,680 Speaker 1: not to happen. This is really we're dealing here with this. 298 00:15:32,040 --> 00:15:35,280 Speaker 1: We call it the SOLIDU virus because people are dying alone, 299 00:15:35,760 --> 00:15:38,000 Speaker 1: they cannot even see their family. I don't want to 300 00:15:38,040 --> 00:15:41,800 Speaker 1: see another round the same way we saw it a 301 00:15:41,800 --> 00:15:44,560 Speaker 1: few months ago, when so many people die in our neighborhood. 302 00:15:44,800 --> 00:15:47,520 Speaker 1: Those are the same one who has no computers. Their 303 00:15:47,520 --> 00:15:49,600 Speaker 1: farthing had no computers. I want to take the kids 304 00:15:49,960 --> 00:15:52,480 Speaker 1: they know, they don't know that have WiFi. All of 305 00:15:52,480 --> 00:15:54,800 Speaker 1: the things you have to put in consideraction. But there's 306 00:15:54,840 --> 00:15:58,960 Speaker 1: no one answer. One thing is an answer. This virus 307 00:15:58,960 --> 00:16:03,960 Speaker 1: still killed the saying. So bottom line, you would say, 308 00:16:04,000 --> 00:16:06,560 Speaker 1: no school's open come September. In New York City just 309 00:16:06,680 --> 00:16:09,400 Speaker 1: quickly just got about thirty seconds they do, we will 310 00:16:09,400 --> 00:16:14,480 Speaker 1: be supposed all right, Well, we're gonna leave it there. 311 00:16:14,520 --> 00:16:16,040 Speaker 1: Thank you so much. We look forward to keeping in 312 00:16:16,080 --> 00:16:18,880 Speaker 1: touch with you. Dr Ramon to Lodge, founder chairman of 313 00:16:18,920 --> 00:16:23,120 Speaker 1: some most Community Care. It is a network of independent 314 00:16:23,360 --> 00:16:30,600 Speaker 1: physicians more than healthcare providers involved, serving predominantly Latino and 315 00:16:30,640 --> 00:16:35,000 Speaker 1: immigrant communities. This is Bloomberg Business Week with Carol Masser 316 00:16:35,120 --> 00:16:38,880 Speaker 1: and Jason Kelly on Bloomberg Radio. Check out this Bloomberg 317 00:16:38,920 --> 00:16:44,000 Speaker 1: Business Week story because let's not forget with Despite everything 318 00:16:44,040 --> 00:16:47,680 Speaker 1: going on, hackers never let up this story at Business 319 00:16:47,720 --> 00:16:51,360 Speaker 1: Week about how hackers bled one eighteen bitcoins out of 320 00:16:51,360 --> 00:16:54,000 Speaker 1: COVID researchers in the United States. So, yeah, there is 321 00:16:54,040 --> 00:16:57,760 Speaker 1: a virus angle here. Carter ke Marotra is cybersecurity reporter 322 00:16:57,800 --> 00:17:01,600 Speaker 1: at Bloomberg News, joins us on the phone from sam Francisco. Cardike. 323 00:17:02,080 --> 00:17:07,000 Speaker 1: Interesting story, tell us what's going on. So in early June, 324 00:17:07,560 --> 00:17:14,199 Speaker 1: um attackers, cyber attackers from a cybergang broke into the 325 00:17:14,280 --> 00:17:18,359 Speaker 1: Department of Epidemiology and Biostatistics at the University of California 326 00:17:18,400 --> 00:17:22,639 Speaker 1: San Francisco. UCSF is uh famous for its med school 327 00:17:22,680 --> 00:17:25,440 Speaker 1: and its teaching hospital and was was in the midst 328 00:17:25,560 --> 00:17:29,520 Speaker 1: of some COVID related research. They were looking into UM 329 00:17:29,560 --> 00:17:32,800 Speaker 1: at the time, we were still wondering whether hydroxy chloroquinn 330 00:17:32,880 --> 00:17:36,359 Speaker 1: could could offer any redeeming value as as treatment. They 331 00:17:36,359 --> 00:17:40,000 Speaker 1: were looking into contact tracing programs. They wanted to know 332 00:17:40,119 --> 00:17:43,760 Speaker 1: who was adversely affected most by COVID and UH. In 333 00:17:43,760 --> 00:17:47,439 Speaker 1: that first week of June, hackers locked up seven of 334 00:17:47,480 --> 00:17:52,000 Speaker 1: their servers UM and UH and demanded three million dollars 335 00:17:52,040 --> 00:17:56,040 Speaker 1: in ransom. It took about a week. UCSF hired a 336 00:17:56,080 --> 00:17:59,080 Speaker 1: negotiator and some lawyers to to help them see their 337 00:17:59,080 --> 00:18:02,280 Speaker 1: way through this, and over the course of a week, UM, 338 00:18:02,480 --> 00:18:05,000 Speaker 1: we we got a glimpse into what it takes to 339 00:18:05,040 --> 00:18:08,280 Speaker 1: get out of this very very messy situation. Yeah. So 340 00:18:08,440 --> 00:18:13,800 Speaker 1: you saw basically the communication between the operator and you. 341 00:18:14,000 --> 00:18:16,960 Speaker 1: C SF tell us what was in there, because the 342 00:18:17,000 --> 00:18:20,879 Speaker 1: back and forth is fascinating. It's really strange. UH. So 343 00:18:21,440 --> 00:18:25,320 Speaker 1: you've got one side that that is, you know, objectively 344 00:18:25,320 --> 00:18:28,640 Speaker 1: a criminal, right and in a real world situation, there's 345 00:18:28,680 --> 00:18:34,040 Speaker 1: no way you you offer legitimacy too to their business model, 346 00:18:34,080 --> 00:18:37,560 Speaker 1: which is holding you hostage. But in a cyber realm, 347 00:18:37,600 --> 00:18:41,239 Speaker 1: there's no chance of or very little chance of at 348 00:18:41,280 --> 00:18:44,520 Speaker 1: least immediately catching these bad guys. You have to take 349 00:18:44,600 --> 00:18:48,040 Speaker 1: them seriously. And that's what this negotiator did, was was 350 00:18:48,119 --> 00:18:53,000 Speaker 1: provide them with the respect they needed. They demanded respect um, 351 00:18:53,280 --> 00:18:55,639 Speaker 1: and so the negotiator had to provide them with that 352 00:18:55,760 --> 00:18:58,560 Speaker 1: sort of certainty that we are taking you seriously. We 353 00:18:58,560 --> 00:19:00,800 Speaker 1: we know that this is your business model and and 354 00:19:00,840 --> 00:19:03,600 Speaker 1: you're just here to do your job. And so UM 355 00:19:03,720 --> 00:19:07,000 Speaker 1: UCSF really had to sort of buy into that. And 356 00:19:07,000 --> 00:19:09,439 Speaker 1: and so the back and forth over weeks was but 357 00:19:09,560 --> 00:19:14,359 Speaker 1: at times comical, almost like amateur drama. Ish um. But 358 00:19:14,920 --> 00:19:17,880 Speaker 1: you know, car, I want to do a reading around 359 00:19:17,920 --> 00:19:20,199 Speaker 1: the table with the lines back and forth here because 360 00:19:20,520 --> 00:19:23,840 Speaker 1: you say, the guys uh at u c SF UM, 361 00:19:23,960 --> 00:19:26,120 Speaker 1: we're saying to the hackers, we've poured almost all our 362 00:19:26,160 --> 00:19:29,080 Speaker 1: funds into COVID nineteen research to help cure this disease. 363 00:19:29,720 --> 00:19:31,240 Speaker 1: Um that on top of all the cuts due to 364 00:19:31,280 --> 00:19:33,199 Speaker 1: classes being canceled as put a serious drain in the 365 00:19:33,200 --> 00:19:35,359 Speaker 1: whole school. You know, they're like, we don't have the 366 00:19:35,359 --> 00:19:38,760 Speaker 1: money basically, and then the operator was like, wait a minute. 367 00:19:38,840 --> 00:19:40,919 Speaker 1: You know the school, you know, you collect more than 368 00:19:40,960 --> 00:19:43,399 Speaker 1: seven billion in revenue each year. You've got lawyers, you 369 00:19:43,480 --> 00:19:46,240 Speaker 1: got security consultants. We think you should be good for 370 00:19:46,280 --> 00:19:49,080 Speaker 1: a few mil. Yeah, they just weren't buying it right. 371 00:19:49,480 --> 00:19:53,280 Speaker 1: They saw this as a massive institution that spend billions 372 00:19:53,320 --> 00:19:55,960 Speaker 1: every year. Uh, and they should have a couple of 373 00:19:56,000 --> 00:20:00,720 Speaker 1: mill to toss around to get their system back online. Unfortunately. 374 00:20:00,880 --> 00:20:04,160 Speaker 1: Or UCSFS contention was that, look, we're in the middle 375 00:20:04,160 --> 00:20:06,359 Speaker 1: of a pandemic. We don't know if our students are 376 00:20:06,359 --> 00:20:08,200 Speaker 1: coming back and if anybody's going to be paying their 377 00:20:08,200 --> 00:20:11,240 Speaker 1: bills to us this fall. Um, we're trying to research 378 00:20:11,320 --> 00:20:14,640 Speaker 1: a cure for this this disease. We just don't have 379 00:20:14,680 --> 00:20:17,520 Speaker 1: that kind of cash laying around. So their initial offer 380 00:20:18,040 --> 00:20:24,200 Speaker 1: was three dollars um and and the operator scoffed at it. 381 00:20:24,280 --> 00:20:26,800 Speaker 1: He just he or she just didn't didn't see it 382 00:20:26,840 --> 00:20:29,880 Speaker 1: as a reasonable offer because they obviously have a job 383 00:20:29,920 --> 00:20:33,119 Speaker 1: to do as well, and you know, like any salesperson, 384 00:20:33,240 --> 00:20:35,520 Speaker 1: they have a boss as well. Uh. And they were 385 00:20:35,520 --> 00:20:38,160 Speaker 1: afraid of taking three to their boss in the first place. 386 00:20:38,160 --> 00:20:40,800 Speaker 1: They said, look, you have to do better than that. Well, 387 00:20:40,840 --> 00:20:43,600 Speaker 1: and you know, down lower in this story, and I 388 00:20:43,680 --> 00:20:46,199 Speaker 1: encourage everybody to read this because it does take some 389 00:20:46,240 --> 00:20:50,160 Speaker 1: twists and turns and you're reminded that as cinematic as 390 00:20:50,200 --> 00:20:52,160 Speaker 1: this is, and I couldn't help thinking if they made 391 00:20:52,160 --> 00:20:54,879 Speaker 1: the big Lebowski now it would have to involve some 392 00:20:54,880 --> 00:20:59,080 Speaker 1: some bitcoin. Um. But you know, you do have some 393 00:20:59,119 --> 00:21:03,600 Speaker 1: really interesting moments where the representative from UCSF basically is like, 394 00:21:03,880 --> 00:21:06,439 Speaker 1: look man like as you say, like my jobs on 395 00:21:06,480 --> 00:21:09,399 Speaker 1: the line. Here people are essentially making fun of me. 396 00:21:09,480 --> 00:21:12,760 Speaker 1: They think I totally messed this up. And you have 397 00:21:12,760 --> 00:21:14,520 Speaker 1: the operator coming back and be like, it's really not 398 00:21:14,560 --> 00:21:16,359 Speaker 1: your fault. We could do this to anyone. I mean, 399 00:21:16,400 --> 00:21:19,000 Speaker 1: it's chilling in a lot of ways, and it's it's 400 00:21:19,000 --> 00:21:22,480 Speaker 1: really true. Um. And so the most important aspect of 401 00:21:22,480 --> 00:21:25,040 Speaker 1: that is it's it's unimportant to understand. I guess that 402 00:21:25,359 --> 00:21:27,879 Speaker 1: this is a negotiation tactic as much as it is 403 00:21:27,880 --> 00:21:30,679 Speaker 1: a reflection of what's going on at UCSU. So it 404 00:21:30,760 --> 00:21:33,760 Speaker 1: is entirely possible that this individual was being blamed for 405 00:21:33,800 --> 00:21:37,200 Speaker 1: the hack. And you know, victims of ransomware attacks typically 406 00:21:37,240 --> 00:21:39,560 Speaker 1: don't want to talk about this in public because being 407 00:21:39,640 --> 00:21:44,520 Speaker 1: victimized can be Uh, there's there's a notion that it's embarrassing, right, 408 00:21:44,600 --> 00:21:49,639 Speaker 1: but here, um, you know this, Sorry, the negotiator Um 409 00:21:49,680 --> 00:21:53,359 Speaker 1: presented that look, I am UM being held at fault 410 00:21:53,359 --> 00:21:56,200 Speaker 1: here and there's no way out of this unless you 411 00:21:56,240 --> 00:21:59,040 Speaker 1: help me get through this. So will you please, um, 412 00:21:59,080 --> 00:22:01,879 Speaker 1: you know, help find us solution one that's reasonable? Uh, 413 00:22:01,960 --> 00:22:05,480 Speaker 1: and that I think really UM sort of appealed to 414 00:22:05,480 --> 00:22:08,080 Speaker 1: to the operator because they saw, look, this is a 415 00:22:08,119 --> 00:22:10,680 Speaker 1: person who's taking us seriously, who was willing to work 416 00:22:10,720 --> 00:22:12,959 Speaker 1: with us. I will I will make money off of 417 00:22:12,960 --> 00:22:14,960 Speaker 1: this one way or another. And it did help. I 418 00:22:15,040 --> 00:22:17,760 Speaker 1: told you it needs a table reading, right, Jason, you 419 00:22:17,800 --> 00:22:23,040 Speaker 1: play You play the hacker, I'll play one of the negotiators. Cardigan, Cardigate. 420 00:22:23,119 --> 00:22:25,040 Speaker 1: You can like kind of you know, be the narrator. 421 00:22:25,480 --> 00:22:28,680 Speaker 1: You'll be the clock. Yeah, totally, you could be the clock, 422 00:22:28,760 --> 00:22:30,159 Speaker 1: like I could see. It's like a kind of a 423 00:22:30,200 --> 00:22:33,640 Speaker 1: one act play. I mean, it's just this is our times, right, 424 00:22:33,680 --> 00:22:35,159 Speaker 1: I mean, this is the kind of stuff that we are. 425 00:22:35,600 --> 00:22:38,280 Speaker 1: Despite to some extent we have better controls, we still 426 00:22:38,280 --> 00:22:39,920 Speaker 1: have to deal with stuff like this. Just got about 427 00:22:40,000 --> 00:22:43,560 Speaker 1: forty seconds here. It's absolutely true and and what the 428 00:22:43,560 --> 00:22:46,520 Speaker 1: operator was saying was in fact the truth. This could 429 00:22:46,520 --> 00:22:49,680 Speaker 1: happen to anyone and it wasn't the fault of UCSF. 430 00:22:49,840 --> 00:22:53,000 Speaker 1: They were a victim, right and and the university had 431 00:22:53,040 --> 00:22:55,040 Speaker 1: to do what it could to to get out of it. 432 00:22:55,080 --> 00:22:58,560 Speaker 1: But it's important to understand that if you are attacked, um, 433 00:22:58,600 --> 00:23:01,280 Speaker 1: talking about it and explain what happened to you will 434 00:23:01,320 --> 00:23:04,920 Speaker 1: help others defend against similar attacks in the future. Yeah, well, 435 00:23:05,000 --> 00:23:07,080 Speaker 1: props to them for sharing this story with you, and 436 00:23:07,400 --> 00:23:09,400 Speaker 1: props to you for telling it so well. We really 437 00:23:09,440 --> 00:23:13,080 Speaker 1: appreciate you joining us. Check it out on the Bloomberg 438 00:23:13,359 --> 00:23:18,320 Speaker 1: and Bloomberg dot Com. Card K Marotra is cybersecurity reporter 439 00:23:18,440 --> 00:23:20,479 Speaker 1: for Bloomberg News. He joined us on the phone from 440 00:23:20,520 --> 00:23:23,840 Speaker 1: San Francisco. You see SF hack shows evolving rest of 441 00:23:23,960 --> 00:23:28,359 Speaker 1: ransomware in the COVID era. This is Bloomberg Business Week 442 00:23:28,520 --> 00:23:32,800 Speaker 1: with Carol Masser and Jason Kelly on Bloomberg Radio. Well, 443 00:23:33,080 --> 00:23:35,800 Speaker 1: for this edition of Bloomberg Green, we turned to one 444 00:23:35,840 --> 00:23:38,800 Speaker 1: of our faves, Noah boom Hire, finance reporter for Bloomberg, 445 00:23:38,880 --> 00:23:42,680 Speaker 1: joining us on the phone from Seattle. And he's looking 446 00:23:42,800 --> 00:23:47,040 Speaker 1: south in this case toward California, where we know those 447 00:23:47,080 --> 00:23:50,560 Speaker 1: wildfires are raging. If it's not one thing, it's another 448 00:23:51,119 --> 00:23:56,560 Speaker 1: there in California climate obviously a huge piece of this 449 00:23:56,840 --> 00:24:01,119 Speaker 1: fire risk. But there's a guy who's got a cure 450 00:24:01,200 --> 00:24:04,119 Speaker 1: of sorts. Noah, this is a phenomenal story. We always 451 00:24:04,119 --> 00:24:06,920 Speaker 1: love talking to you. Everybody has a guy. He's got 452 00:24:06,960 --> 00:24:09,439 Speaker 1: a guy. I mean, this is really something. Tell us 453 00:24:09,480 --> 00:24:14,720 Speaker 1: about what's going on here. Yeah, So this feature, UM, 454 00:24:14,760 --> 00:24:18,480 Speaker 1: I reported about a guy named Jim Moseley. He started 455 00:24:18,680 --> 00:24:23,400 Speaker 1: a company several years back. Uh. The name is Sunfire Defense, 456 00:24:23,760 --> 00:24:30,920 Speaker 1: and basically he's selling a variety of uh wildfire protection 457 00:24:31,880 --> 00:24:36,960 Speaker 1: gear or uh that that homeowners can use to to 458 00:24:37,040 --> 00:24:40,000 Speaker 1: help harden their homes and you know, when a wildfire 459 00:24:40,760 --> 00:24:44,119 Speaker 1: comes through, hopefully will help save the structure. Um. The 460 00:24:44,840 --> 00:24:48,960 Speaker 1: problem is that uh one of his main products, called 461 00:24:49,119 --> 00:24:57,160 Speaker 1: FPF three thousand has uh drawn the attention of uh 462 00:24:57,240 --> 00:25:02,160 Speaker 1: some attorneys in Santa Barbara and the l A City attorney. UM, 463 00:25:02,200 --> 00:25:05,560 Speaker 1: and they're basically alleging that he's made uh, you know, 464 00:25:05,760 --> 00:25:09,439 Speaker 1: falser misleading claims about this product. Um. You know, namely 465 00:25:09,440 --> 00:25:11,800 Speaker 1: that it's not nearly as effective as he says it is, 466 00:25:12,080 --> 00:25:17,280 Speaker 1: and uh, uh that it's toxic, even after he said 467 00:25:17,320 --> 00:25:20,000 Speaker 1: that it was a you know, not harmful to humans 468 00:25:20,080 --> 00:25:22,439 Speaker 1: or animals and that kind of stuff. So tell us 469 00:25:22,480 --> 00:25:28,080 Speaker 1: you actually I believe witnessed it firsthand. Yeah, so in February, 470 00:25:28,119 --> 00:25:31,480 Speaker 1: actually before the pandemic shut everything down, I spent a 471 00:25:31,560 --> 00:25:34,000 Speaker 1: day with him in Los Angeles and got a demonstration 472 00:25:34,000 --> 00:25:37,040 Speaker 1: on the product. And it's, you know, it's pretty compelling. 473 00:25:37,119 --> 00:25:40,000 Speaker 1: He he takes a stick that he says was treated 474 00:25:40,040 --> 00:25:44,959 Speaker 1: with this substance, and uh takes a blowtorch to it, 475 00:25:45,240 --> 00:25:48,520 Speaker 1: and you know, the part of the stick that hasn't 476 00:25:48,520 --> 00:25:52,040 Speaker 1: been treated, UM gets very brittle and breaks, and the 477 00:25:52,160 --> 00:25:56,080 Speaker 1: part uh that is uh gets a nice char on it. 478 00:25:56,119 --> 00:25:57,960 Speaker 1: But then you know, he'll take a key out of 479 00:25:58,000 --> 00:26:00,800 Speaker 1: his pocket or a coin and scratch that off, and 480 00:26:00,880 --> 00:26:03,320 Speaker 1: you see the wood beneath. Can I just mention the 481 00:26:03,359 --> 00:26:06,840 Speaker 1: cost of this? You put your story three dollars fifty 482 00:26:06,840 --> 00:26:09,080 Speaker 1: cents per square foot, which means it costs tens of 483 00:26:09,080 --> 00:26:12,600 Speaker 1: thousands of dollars to cover a large home using SPF 484 00:26:12,640 --> 00:26:15,600 Speaker 1: three thousand. I mean, this isn't I mean, this isn't cheap. Now, 485 00:26:15,640 --> 00:26:18,120 Speaker 1: mind you, if you're saving a multimillion dollar home, it's 486 00:26:18,160 --> 00:26:21,680 Speaker 1: pretty inexpensive, I guess, but I mean it's not. I mean, look, 487 00:26:21,680 --> 00:26:26,919 Speaker 1: that's yeah, that's the value proposition. And you know, uh, Mosley, 488 00:26:26,960 --> 00:26:29,280 Speaker 1: you know has an interesting client lift as a result. 489 00:26:29,320 --> 00:26:33,520 Speaker 1: I mean he has treated parts of the Neverland ranch. 490 00:26:33,640 --> 00:26:38,160 Speaker 1: He uh treated the home of Star Wars actor Mark 491 00:26:38,240 --> 00:26:43,960 Speaker 1: Hamill and Malibu Um Dean Koon's the best selling novelists. Uh. 492 00:26:44,359 --> 00:26:48,160 Speaker 1: He's managed to attract the attention of some well known folks. 493 00:26:49,400 --> 00:26:51,960 Speaker 1: And I mean, how much of this, you know, sort 494 00:26:52,000 --> 00:26:55,280 Speaker 1: of taking a step back, Noah is about the fact 495 00:26:55,359 --> 00:26:58,520 Speaker 1: that especially I mean, as we see these headlines, it's 496 00:26:58,640 --> 00:27:02,920 Speaker 1: just unbelievable the to be reminded of this wildfire risk. 497 00:27:02,920 --> 00:27:05,480 Speaker 1: And I was reading, uh and listening to a story 498 00:27:05,560 --> 00:27:07,919 Speaker 1: recently by actually by a friend of mine out at 499 00:27:07,960 --> 00:27:11,919 Speaker 1: k queed and California talking about the enormous risk of wildfires, 500 00:27:12,000 --> 00:27:16,400 Speaker 1: especially to you know, those most vulnerable and living homes 501 00:27:16,400 --> 00:27:18,760 Speaker 1: and nursing homes. Uh. You should check that out as 502 00:27:18,920 --> 00:27:22,239 Speaker 1: an aside. But um, I mean people will sort of 503 00:27:22,359 --> 00:27:25,400 Speaker 1: do whatever they can in many ways, he's taking advantage 504 00:27:25,400 --> 00:27:29,040 Speaker 1: of people, one could argue, who are desperate for any 505 00:27:29,080 --> 00:27:32,480 Speaker 1: solution here. Well, yeah, I mean that's that's essentially what 506 00:27:32,520 --> 00:27:35,760 Speaker 1: the district attorney and Santa Barbara and the city attorney 507 00:27:35,760 --> 00:27:37,960 Speaker 1: in l A are arguing, is that is that he's 508 00:27:38,040 --> 00:27:40,280 Speaker 1: this is a predatory company that he's praying on people's 509 00:27:40,280 --> 00:27:43,879 Speaker 1: and securities and fears and the you know, very well 510 00:27:44,000 --> 00:27:47,320 Speaker 1: established fact that wildfire risk is high in a lot 511 00:27:47,320 --> 00:27:50,440 Speaker 1: of parts of California and climate change is making it worse. 512 00:27:50,600 --> 00:27:53,719 Speaker 1: I mean, that's that's ultimately why I wanted to do 513 00:27:53,760 --> 00:27:57,119 Speaker 1: this story. Uh there, you know, mostly is not alone. 514 00:27:57,240 --> 00:28:00,560 Speaker 1: There are lots of people and lots of company peddling 515 00:28:00,680 --> 00:28:04,840 Speaker 1: fixes to this problem. But the fact the matter is 516 00:28:05,000 --> 00:28:08,359 Speaker 1: that development patterns and a changing climate have created a 517 00:28:08,400 --> 00:28:11,639 Speaker 1: situation where you've got you know, hundreds of billions of 518 00:28:11,680 --> 00:28:15,000 Speaker 1: dollars of real estate at risk, UM in this state, 519 00:28:15,240 --> 00:28:18,920 Speaker 1: and UM, you know, people who live there are at 520 00:28:18,920 --> 00:28:23,600 Speaker 1: a point that they're willing to just put their hope 521 00:28:23,640 --> 00:28:29,040 Speaker 1: in their faith in unproven or you know, not very 522 00:28:29,040 --> 00:28:32,480 Speaker 1: well tested solutions to the problem. And you know, one 523 00:28:32,480 --> 00:28:34,440 Speaker 1: of the things we tried to highlight this is really 524 00:28:34,520 --> 00:28:38,440 Speaker 1: a story of our moment right now. We're going through 525 00:28:39,240 --> 00:28:43,080 Speaker 1: um a lot right now with the coronavirus, and and 526 00:28:43,080 --> 00:28:46,720 Speaker 1: there are parallels there. People are are are searching for 527 00:28:46,840 --> 00:28:50,080 Speaker 1: cures to that disease, and um, you know, in the 528 00:28:50,160 --> 00:28:55,800 Speaker 1: absence of of a solution and a vaccine, people are 529 00:28:55,840 --> 00:28:58,800 Speaker 1: just grasping for for whatever they can. Now it's a 530 00:28:58,800 --> 00:29:00,760 Speaker 1: really good point. I'm glad you made a parallel because 531 00:29:00,760 --> 00:29:03,000 Speaker 1: it did certainly recur to me as I was reading 532 00:29:03,040 --> 00:29:05,840 Speaker 1: your piece. No Blue Hire, thank you so much. Finance 533 00:29:05,840 --> 00:29:08,440 Speaker 1: reporter for Bloomberg. He joined us on the phone from Seattle. 534 00:29:08,520 --> 00:29:11,640 Speaker 1: Check out his story in wildfire ravage California. A salesman 535 00:29:11,760 --> 00:29:15,840 Speaker 1: is peddling cure. Read that story and more on climate news, science, 536 00:29:15,840 --> 00:29:19,560 Speaker 1: and the environment at bloomberg dot com slash green bro 537 00:29:22,840 --> 00:29:26,760 Speaker 1: a journal. Yeah, but you let me drive? Oh no, no, no, no, 538 00:29:26,800 --> 00:29:32,080 Speaker 1: who's going to drive? Honey? Please, I'll do the right velvet. 539 00:29:32,520 --> 00:29:41,440 Speaker 1: I want to drive ball, just drive baby. The questions trying. 540 00:29:47,880 --> 00:29:51,640 Speaker 1: This is the drive to the globe. Thanks, we'll drive 541 00:29:51,800 --> 00:29:56,680 Speaker 1: us down on Bloomberg Radio. All right, it is time 542 00:29:56,920 --> 00:29:59,480 Speaker 1: for the drive to the clothes. And as we head 543 00:29:59,520 --> 00:30:02,080 Speaker 1: towards that, we're about eleven minutes way, less than eleven 544 00:30:02,120 --> 00:30:04,880 Speaker 1: minutes way. Let's check out with Michael Congino, President and 545 00:30:04,880 --> 00:30:08,840 Speaker 1: portfolio manager for the Permanent Portfolio family of funds. He 546 00:30:08,920 --> 00:30:11,480 Speaker 1: joins on the phone from San Francisco. Michael, how are you? 547 00:30:11,560 --> 00:30:15,040 Speaker 1: How are things in San Francisco? Good? Afternoon, Jason, Uh, 548 00:30:15,240 --> 00:30:18,600 Speaker 1: pretty good, although we've had a few fires, um, you know, 549 00:30:18,720 --> 00:30:21,880 Speaker 1: north and east of the city, um Tahoe area, the 550 00:30:21,920 --> 00:30:24,400 Speaker 1: wine country, which is making the air quality not quite 551 00:30:24,440 --> 00:30:26,720 Speaker 1: as good. We had a lot of dry thunder and 552 00:30:26,840 --> 00:30:29,239 Speaker 1: lightning earlier in the week. Um didn't a mount too 553 00:30:29,320 --> 00:30:31,600 Speaker 1: much rain, but some of that lightning hit the ground 554 00:30:31,600 --> 00:30:33,960 Speaker 1: and cause some fire. So it's it's creating an early 555 00:30:34,000 --> 00:30:37,560 Speaker 1: start to the fire season, which has been difficult. Yeah. Well, 556 00:30:37,640 --> 00:30:39,760 Speaker 1: and on top of you know, California and I know 557 00:30:39,840 --> 00:30:43,280 Speaker 1: northern California and southern California have had uh sort of 558 00:30:43,280 --> 00:30:46,760 Speaker 1: a different experience of late and really throughout the pandemic. 559 00:30:46,880 --> 00:30:49,200 Speaker 1: But um, I tell you, I know it's not getting 560 00:30:49,240 --> 00:30:52,040 Speaker 1: any easier for you guys out there. And yet in 561 00:30:52,080 --> 00:30:54,840 Speaker 1: the midst of all this, we have a market that continues, 562 00:30:54,960 --> 00:30:59,000 Speaker 1: even if we're off our highs today, to grind higher. 563 00:30:59,080 --> 00:31:01,400 Speaker 1: What do you make of if we're asking everybody we 564 00:31:01,480 --> 00:31:05,440 Speaker 1: can talk to about this seeming disconnect between a pretty 565 00:31:05,440 --> 00:31:09,080 Speaker 1: scary underlying economy, a health crisis, and a market that 566 00:31:09,200 --> 00:31:13,360 Speaker 1: is setting records. Well, it's not unusual for the stock 567 00:31:13,440 --> 00:31:17,000 Speaker 1: market to not exactly correlate to the broader economy. I 568 00:31:17,040 --> 00:31:19,080 Speaker 1: mean for the better part of the two thousands. I 569 00:31:19,080 --> 00:31:22,520 Speaker 1: mean you had you know, roughly one to two GDP growth, 570 00:31:22,520 --> 00:31:24,520 Speaker 1: and you had stock market and your returns up in 571 00:31:24,560 --> 00:31:28,280 Speaker 1: the teams to or more. Um So it's nothing unusual. 572 00:31:28,360 --> 00:31:32,320 Speaker 1: The stock market is predicting future economic activity in all likelihood. 573 00:31:32,560 --> 00:31:34,640 Speaker 1: Some of the things that are driving the stock market, 574 00:31:34,920 --> 00:31:36,760 Speaker 1: you know, a lot of the games are centered in 575 00:31:36,880 --> 00:31:41,760 Speaker 1: a few industries like technology UM, information services, communications, UM, 576 00:31:41,880 --> 00:31:44,640 Speaker 1: that are doing very well in this downturn versus other 577 00:31:44,920 --> 00:31:47,640 Speaker 1: broader economy industries that are more cyclical, that are more 578 00:31:48,080 --> 00:31:51,840 Speaker 1: um dependent on human labor, and those sorts of things. 579 00:31:51,920 --> 00:31:55,920 Speaker 1: I have to jump in. Two thousand didn't end so well, no, 580 00:31:56,160 --> 00:31:58,320 Speaker 1: I mean that was the beginning of the two thousand recession. 581 00:31:59,120 --> 00:32:02,440 Speaker 1: Um uh. And you know you had a ten year 582 00:32:02,520 --> 00:32:06,160 Speaker 1: run at that point that h that you know, we're 583 00:32:06,200 --> 00:32:08,960 Speaker 1: talking two thousand, nineteen, we thousand, talking about two thousand 584 00:32:09,040 --> 00:32:11,320 Speaker 1: itself twenty years ago. Well, I'm just saying, you know, 585 00:32:11,360 --> 00:32:14,480 Speaker 1: you said, you know, we've seen market disconnect before from 586 00:32:14,520 --> 00:32:16,360 Speaker 1: kind of what's going on in the real economy, and 587 00:32:16,360 --> 00:32:19,520 Speaker 1: I'm just thinking you mentioned, you know, the two thousand 588 00:32:19,640 --> 00:32:21,520 Speaker 1: run up, and it didn't end so well. And I 589 00:32:21,520 --> 00:32:24,640 Speaker 1: do wonder if you think we're so disconnected. We have 590 00:32:24,720 --> 00:32:26,240 Speaker 1: seen it before, but do you think this isn't going 591 00:32:26,320 --> 00:32:30,120 Speaker 1: to end well? Well? At some point? I mean to me, 592 00:32:30,240 --> 00:32:34,760 Speaker 1: there's a there's a broad, long term corel correlation between 593 00:32:34,840 --> 00:32:38,880 Speaker 1: stock market performance and the economy because stocks are driven 594 00:32:38,920 --> 00:32:41,080 Speaker 1: on the basis of the health of the economy and 595 00:32:41,120 --> 00:32:44,520 Speaker 1: the ability to to own the companies that make goods 596 00:32:44,520 --> 00:32:46,960 Speaker 1: and services and that sort of thing. So you do 597 00:32:47,000 --> 00:32:50,120 Speaker 1: have a broad correlation over time, but in shorter periods 598 00:32:50,160 --> 00:32:52,880 Speaker 1: you can have all kinds of anomalies that that make 599 00:32:52,920 --> 00:32:54,920 Speaker 1: it so the stock market has a great year and 600 00:32:54,960 --> 00:32:58,320 Speaker 1: the economy does not, or vice versa. And what I'm 601 00:32:58,360 --> 00:33:00,880 Speaker 1: saying is that in this particular vironment you have one 602 00:33:00,920 --> 00:33:04,720 Speaker 1: of those You have investors anticipating a better economy coming 603 00:33:04,720 --> 00:33:07,240 Speaker 1: out of COVID. You have certain industries that are driving 604 00:33:07,280 --> 00:33:10,000 Speaker 1: of the large majority of the market gains that have 605 00:33:10,120 --> 00:33:13,600 Speaker 1: been doing better than the overall economy during this this 606 00:33:13,680 --> 00:33:16,760 Speaker 1: period of COVID. So therefore the stock prices of those 607 00:33:16,760 --> 00:33:19,840 Speaker 1: companies are going up and maybe giving a warped picture 608 00:33:19,840 --> 00:33:23,200 Speaker 1: of the broader stock market in light of the weaker 609 00:33:23,440 --> 00:33:27,360 Speaker 1: broader economy. So there's a normalies even now that make 610 00:33:27,440 --> 00:33:30,120 Speaker 1: it so that again it's not unusual for the stock 611 00:33:30,160 --> 00:33:33,640 Speaker 1: market to not exactly track the broader economy. Talk to 612 00:33:33,680 --> 00:33:37,239 Speaker 1: me about several silver and gold, Michael, because I know 613 00:33:37,280 --> 00:33:39,200 Speaker 1: that that's something you've taken a look at, and I 614 00:33:39,280 --> 00:33:41,440 Speaker 1: know it's something that's been on the minds of a 615 00:33:41,440 --> 00:33:44,560 Speaker 1: lot of investors out there. How do you factor those 616 00:33:44,800 --> 00:33:48,680 Speaker 1: precious metals into the investment thesis? Well, in our in 617 00:33:48,720 --> 00:33:51,760 Speaker 1: our program, we we believe that you know, owning those 618 00:33:51,800 --> 00:33:54,760 Speaker 1: assets are an integral part of long term wealth building, 619 00:33:54,800 --> 00:33:56,840 Speaker 1: and so a failure to own them leaves a hole 620 00:33:56,880 --> 00:33:59,440 Speaker 1: in your strategy. UM. So our view is to not 621 00:33:59,520 --> 00:34:02,920 Speaker 1: only owned stocks and bonds, but also in commodities, natural resources, 622 00:34:02,960 --> 00:34:06,360 Speaker 1: real estate, and and gold and silver as asset classes. 623 00:34:06,400 --> 00:34:08,560 Speaker 1: So we believe in them long term. And when you 624 00:34:08,600 --> 00:34:12,280 Speaker 1: look at the environment right now, um, with the fedback 625 00:34:12,360 --> 00:34:17,800 Speaker 1: stopping everything, um, with the likelihood of even more stimulus 626 00:34:17,840 --> 00:34:21,000 Speaker 1: than we've already created, with the ability of that stimulus 627 00:34:21,040 --> 00:34:23,359 Speaker 1: to get onto main street, which was not true ten 628 00:34:23,440 --> 00:34:25,800 Speaker 1: to twelve years ago. It stayed mostly in the banking 629 00:34:25,840 --> 00:34:28,799 Speaker 1: system to recap the banks. Um, you know you have 630 00:34:28,840 --> 00:34:33,360 Speaker 1: inflationary pressures or potentially um expected inflationary potential, you know, 631 00:34:33,640 --> 00:34:36,600 Speaker 1: pressures when the economy begins to grow again. Not only that, 632 00:34:36,680 --> 00:34:39,880 Speaker 1: but the uncertainty factor created by COVID. I mean, to me, 633 00:34:39,960 --> 00:34:42,600 Speaker 1: there's still a lot of uncertainty with respect to really 634 00:34:42,600 --> 00:34:45,919 Speaker 1: what's happening I you know, and until that gets solidified, 635 00:34:45,960 --> 00:34:48,160 Speaker 1: I think you could go on a number of directions. 636 00:34:48,160 --> 00:34:50,640 Speaker 1: So when you add all this up, it's not surprising 637 00:34:50,640 --> 00:34:53,280 Speaker 1: that the prices of gold and silver have have gone 638 00:34:53,360 --> 00:34:56,480 Speaker 1: up UM and and we'll likely continue to do so. 639 00:34:56,800 --> 00:34:59,040 Speaker 1: Keep in mind that gold really didn't do much for 640 00:34:59,160 --> 00:35:02,320 Speaker 1: most of the the odds. I mean, it was pretty benign, 641 00:35:02,719 --> 00:35:05,440 Speaker 1: and it's begun to move again, so there's some valuation 642 00:35:05,560 --> 00:35:09,160 Speaker 1: catch up UM. But also the conditions are fertile. Negative 643 00:35:09,160 --> 00:35:12,200 Speaker 1: real interest rates across the curve is another big one UM, 644 00:35:12,239 --> 00:35:14,760 Speaker 1: and I don't see that changing anytime soon. So there's 645 00:35:14,840 --> 00:35:17,640 Speaker 1: there's room for gold to go even further and silver 646 00:35:17,760 --> 00:35:21,239 Speaker 1: as well. If you look at it on a valuation basis, UM. 647 00:35:21,280 --> 00:35:23,520 Speaker 1: You know, the value of an ounce of gold is 648 00:35:23,560 --> 00:35:25,719 Speaker 1: about point six of the value of a share of 649 00:35:25,719 --> 00:35:29,479 Speaker 1: the SMP five index evaluation metric. We haven't seen since 650 00:35:29,520 --> 00:35:32,440 Speaker 1: the middle of the the odds around two oh seven 651 00:35:32,480 --> 00:35:35,640 Speaker 1: to oh eight UM, so it's not overly valued even 652 00:35:35,680 --> 00:35:38,440 Speaker 1: though it's had a big run and uh and again 653 00:35:38,480 --> 00:35:40,760 Speaker 1: it didn't do much for years, so there's a catchup 654 00:35:40,800 --> 00:35:43,840 Speaker 1: period that uh that is factoring in as well, and 655 00:35:43,920 --> 00:35:47,680 Speaker 1: investors are rediscovering it given this overall back stoff, and 656 00:35:47,680 --> 00:35:50,640 Speaker 1: I think that's that's why you've seen the moves you've had. 657 00:35:50,800 --> 00:35:52,920 Speaker 1: I would also say that it's a volatile asset. It 658 00:35:52,960 --> 00:35:55,080 Speaker 1: can go up and down a hundred bucks pretty quickly, 659 00:35:55,320 --> 00:35:58,480 Speaker 1: so investors need to understand that. But generally speaking, if 660 00:35:58,480 --> 00:36:00,399 Speaker 1: you buy it and hold it and you look look 661 00:36:00,480 --> 00:36:03,319 Speaker 1: back years after you bought it, you're generally up. There's 662 00:36:03,320 --> 00:36:06,400 Speaker 1: a strong correlation between the value of gold on a 663 00:36:06,440 --> 00:36:09,760 Speaker 1: long term basis and the creation of of the money 664 00:36:09,760 --> 00:36:11,800 Speaker 1: supply and liquidity and credit and I don't see that 665 00:36:11,920 --> 00:36:14,640 Speaker 1: changing at all. So for long term investor, picking spot 666 00:36:14,680 --> 00:36:17,160 Speaker 1: and definitely you want to hold some well, really really 667 00:36:17,200 --> 00:36:20,640 Speaker 1: thoughtful UM as always, Michael, thank you so much. Michael Codino. 668 00:36:20,760 --> 00:36:23,640 Speaker 1: He's president portfolio manager a Permanent Portfolio family of funds. 669 00:36:23,640 --> 00:36:26,760 Speaker 1: You've got roughly two point two billion in assets under management. 670 00:36:26,840 --> 00:36:29,520 Speaker 1: The Permanent Portfolio fund. By the way, in the nineties 671 00:36:29,760 --> 00:36:32,080 Speaker 1: percentile for funds and its category of the past five 672 00:36:32,160 --> 00:36:35,239 Speaker 1: years is up nearly eight percent annually in each of 673 00:36:35,280 --> 00:36:38,440 Speaker 1: those five years, so he's had quite a run up. 674 00:36:38,680 --> 00:36:41,120 Speaker 1: Thanks so much for listening to Bloomberg Business Week. Download 675 00:36:41,160 --> 00:36:44,080 Speaker 1: the podcast on iTunes, Southcloud, Bloomberg dot com, but wherever 676 00:36:44,200 --> 00:36:46,320 Speaker 1: you get your podcasts, and of course you can always 677 00:36:46,360 --> 00:36:48,440 Speaker 1: listen to our radio show at two pm Eastern on 678 00:36:48,480 --> 00:36:51,680 Speaker 1: Bloomberg Radio or watch us on YouTube by searching Bloomberg 679 00:36:51,719 --> 00:36:52,359 Speaker 1: Global News