1 00:00:01,400 --> 00:00:04,120 Speaker 1: Welcome to the Bloomberg Markets Podcast. I'm Paul Sweeney. Along 2 00:00:04,120 --> 00:00:06,240 Speaker 1: with my co host of Bonnie Quinn. Every business day 3 00:00:06,240 --> 00:00:10,400 Speaker 1: we bring you interviews from CEOs, market pros, and Bloomberg experts, 4 00:00:10,440 --> 00:00:13,600 Speaker 1: along with essential market moving news kind the Bloomberg Markets 5 00:00:13,600 --> 00:00:17,000 Speaker 1: Podcast on Apple Podcasts or wherever you listen to podcasts, 6 00:00:17,000 --> 00:00:21,160 Speaker 1: and on Bloomberg dot com. Well as more and more 7 00:00:21,239 --> 00:00:25,279 Speaker 1: people work from home for longer and longer period the 8 00:00:25,360 --> 00:00:28,880 Speaker 1: question is what does that mean for corporate real estate 9 00:00:29,000 --> 00:00:32,000 Speaker 1: office space in some major urban cities. To get a 10 00:00:32,000 --> 00:00:34,560 Speaker 1: sense of kind of the future, here, uh, we welcome 11 00:00:34,640 --> 00:00:38,559 Speaker 1: Rebecca Rocky, global head of forecasting for Cushman and Wakefield 12 00:00:38,640 --> 00:00:41,080 Speaker 1: located in New York City. Rebecca, thanks so much for 13 00:00:41,159 --> 00:00:42,640 Speaker 1: joining us. You know, I was in the city a 14 00:00:42,640 --> 00:00:45,640 Speaker 1: couple of weeks ago, back in the office for day, 15 00:00:45,840 --> 00:00:48,159 Speaker 1: and you know, I was, you know, kind of shocked 16 00:00:48,159 --> 00:00:52,080 Speaker 1: to see the the fewer people on the street, and 17 00:00:52,120 --> 00:00:55,480 Speaker 1: that suggested to me fewer people, uh in the office buildings. 18 00:00:55,760 --> 00:00:57,640 Speaker 1: Give us a sense of kind of where we are 19 00:00:58,120 --> 00:01:01,400 Speaker 1: kind of in the global work worse in the office space, 20 00:01:01,480 --> 00:01:04,839 Speaker 1: and how you guys are thinking about it. Sure well, 21 00:01:04,880 --> 00:01:08,760 Speaker 1: first of all, thank you so much for having me today. UM. 22 00:01:08,800 --> 00:01:11,640 Speaker 1: You know, clearly we have a number of things going 23 00:01:11,680 --> 00:01:14,920 Speaker 1: on in the office sector, in particular, not the least 24 00:01:14,920 --> 00:01:18,040 Speaker 1: of which is dealing with the damage that's been done 25 00:01:18,120 --> 00:01:20,920 Speaker 1: in the economy and the labor market. UM. As it 26 00:01:20,959 --> 00:01:23,680 Speaker 1: relates to the return to the office, there are also 27 00:01:23,760 --> 00:01:28,760 Speaker 1: a number of trends emerging and most offices are operating 28 00:01:29,160 --> 00:01:33,000 Speaker 1: well below capacity right all over the country and really 29 00:01:33,080 --> 00:01:35,520 Speaker 1: in most of the parts of the world. We're seeing 30 00:01:35,560 --> 00:01:39,280 Speaker 1: that office utilization is below where it was and in 31 00:01:39,319 --> 00:01:44,320 Speaker 1: some cases significantly. UM. And you know, fortunately office companies 32 00:01:44,360 --> 00:01:48,680 Speaker 1: have been more resilient when you think about the damage 33 00:01:48,720 --> 00:01:52,360 Speaker 1: that's been done to different industries. Office employment has fared 34 00:01:52,800 --> 00:01:57,080 Speaker 1: disproportionately better, and there is somewhat of a an ability 35 00:01:57,360 --> 00:02:00,880 Speaker 1: to work remotely, to get through the times, to continue 36 00:02:00,880 --> 00:02:04,040 Speaker 1: to work, just not in the office right now. So 37 00:02:04,120 --> 00:02:07,840 Speaker 1: that's really what we're seeing take place, and are some 38 00:02:07,920 --> 00:02:11,080 Speaker 1: of the things that we talk about in this report. Yeah, Rebecca, 39 00:02:11,160 --> 00:02:14,120 Speaker 1: you did a global office impact study and found that 40 00:02:14,560 --> 00:02:19,760 Speaker 1: office leasing will stay below pre COVID levels until twenty five, which, 41 00:02:19,800 --> 00:02:21,800 Speaker 1: when you think about it, sort of makes sense. What 42 00:02:21,960 --> 00:02:24,720 Speaker 1: does that mean for the likes of Cashman and Wakefield 43 00:02:24,720 --> 00:02:28,240 Speaker 1: and others like you. Well, I think it was a 44 00:02:28,280 --> 00:02:31,760 Speaker 1: lot of opportunity to add value to our clients and 45 00:02:31,840 --> 00:02:36,160 Speaker 1: helping them think about this new world that we're facing. Right. So, 46 00:02:36,240 --> 00:02:39,520 Speaker 1: we believe that the office is a critical part of 47 00:02:39,560 --> 00:02:44,160 Speaker 1: how companies do business, how they create value in particular, 48 00:02:44,680 --> 00:02:49,080 Speaker 1: and so we fundamentally think there's intrinsic value to the 49 00:02:49,160 --> 00:02:52,440 Speaker 1: office place. Really, the question is what are the kinds 50 00:02:52,440 --> 00:02:55,160 Speaker 1: of things we're doing in the office and how does 51 00:02:55,320 --> 00:02:59,200 Speaker 1: behavior change from a leasing perspective as we go into 52 00:02:59,240 --> 00:03:02,520 Speaker 1: this new normal. Um. The fact that we're finding that 53 00:03:02,680 --> 00:03:07,000 Speaker 1: despite some of the structural changes we anticipate, such as 54 00:03:07,040 --> 00:03:11,120 Speaker 1: work from home to emerge, that the office sector does 55 00:03:11,200 --> 00:03:13,960 Speaker 1: recover from a demand perspective, to me was a really 56 00:03:14,000 --> 00:03:18,000 Speaker 1: strong finding and indicative of the fact that many companies 57 00:03:18,080 --> 00:03:22,240 Speaker 1: view office as part of the broader ecosystem that will 58 00:03:22,320 --> 00:03:25,680 Speaker 1: allow them to achieve the goals that they have as company. 59 00:03:26,040 --> 00:03:27,919 Speaker 1: But it's interesting, you know, we've we've heard a lot 60 00:03:27,919 --> 00:03:31,880 Speaker 1: of corporate leaders in New York City calling for companies 61 00:03:31,919 --> 00:03:35,560 Speaker 1: that bring their employers back, open up the city again. 62 00:03:36,200 --> 00:03:39,520 Speaker 1: Yet it just seems like, you know, just the people 63 00:03:39,640 --> 00:03:43,000 Speaker 1: I talked to, they say Okay, maybe I'll go back 64 00:03:43,040 --> 00:03:45,360 Speaker 1: into the city, but it ain't gonna be five days 65 00:03:45,400 --> 00:03:48,360 Speaker 1: a week. This work at home from thing works just fine. 66 00:03:48,800 --> 00:03:50,880 Speaker 1: So is it going to be a sense that there 67 00:03:50,880 --> 00:03:55,760 Speaker 1: will be some permanent change. Absolutely absolutely. And you know, 68 00:03:55,840 --> 00:03:58,000 Speaker 1: in the right now we're in what I call the 69 00:03:58,040 --> 00:04:02,160 Speaker 1: adrenaline Russias COVID nineteen right, so we're dealing with competing 70 00:04:02,240 --> 00:04:05,520 Speaker 1: forces of trying to figure out what's going on with 71 00:04:05,600 --> 00:04:08,600 Speaker 1: schools and folks who need to maybe take care of 72 00:04:08,640 --> 00:04:11,720 Speaker 1: their their parents. Right. A huge concern is I need 73 00:04:11,760 --> 00:04:14,600 Speaker 1: to go take um groceries on the weekend and I 74 00:04:14,600 --> 00:04:17,440 Speaker 1: don't want to be exposed and put purt risk. So 75 00:04:17,520 --> 00:04:20,120 Speaker 1: we have a lot of that going on. And this 76 00:04:20,160 --> 00:04:23,880 Speaker 1: report really looked at different scenarios where we do find 77 00:04:23,920 --> 00:04:27,040 Speaker 1: ourselves in a post COVID world, defined as a world 78 00:04:27,080 --> 00:04:30,480 Speaker 1: where we have a medical solution such that we can 79 00:04:30,640 --> 00:04:33,960 Speaker 1: really subside in terms of the level of fear of 80 00:04:34,000 --> 00:04:38,120 Speaker 1: the virus. But to your point, we absolutely believe there 81 00:04:38,160 --> 00:04:41,440 Speaker 1: will be long term changes and a majority of those 82 00:04:41,480 --> 00:04:44,760 Speaker 1: are in the evolution of what we call agile working 83 00:04:44,960 --> 00:04:48,360 Speaker 1: or part time at home, part time in third places, 84 00:04:48,400 --> 00:04:51,760 Speaker 1: and part time in the office. We we think a 85 00:04:51,839 --> 00:04:55,240 Speaker 1: minority of the folks who work from home will ultimately 86 00:04:55,279 --> 00:04:58,679 Speaker 1: be permanently there. Most people want to be in the office. 87 00:04:59,120 --> 00:05:00,960 Speaker 1: Most people want to be in the office a few 88 00:05:01,040 --> 00:05:04,240 Speaker 1: days a week. So it's really that evolution that we 89 00:05:04,320 --> 00:05:07,479 Speaker 1: expect to be long lasting in nature, and which we 90 00:05:07,520 --> 00:05:10,680 Speaker 1: tried to quantify in this report. Here are two statistics 91 00:05:10,760 --> 00:05:13,520 Speaker 1: that really jumped out at me. Rebecca, US office vacancy 92 00:05:13,600 --> 00:05:17,080 Speaker 1: is expected to rise steadily and peak at seventeen point 93 00:05:17,160 --> 00:05:20,880 Speaker 1: six percent. But get this by mid twenty two, so 94 00:05:21,000 --> 00:05:24,239 Speaker 1: not even next year, but presumably well after we already 95 00:05:24,240 --> 00:05:27,440 Speaker 1: have a vaccine. And you also found that asking rents 96 00:05:27,440 --> 00:05:31,040 Speaker 1: are expected to decline by nine point three peak to twelve. First, 97 00:05:31,240 --> 00:05:33,240 Speaker 1: that doesn't seem like that big of a decline if 98 00:05:33,240 --> 00:05:36,479 Speaker 1: we're looking at nearly a fifth of office space going 99 00:05:36,520 --> 00:05:40,880 Speaker 1: away until mid two. Are these in the major urban 100 00:05:40,920 --> 00:05:44,760 Speaker 1: centers and so on? Sure? Well, I think from the 101 00:05:44,839 --> 00:05:48,400 Speaker 1: vacancy rate perspective, it's important to note that we were 102 00:05:48,440 --> 00:05:51,520 Speaker 1: really at a low point for the cycle at just 103 00:05:51,680 --> 00:05:55,680 Speaker 1: under thirteen percent, So the increase is really relative to 104 00:05:55,920 --> 00:06:00,280 Speaker 1: that which was consistent with prior sort of peas of 105 00:06:00,360 --> 00:06:03,480 Speaker 1: expansions in terms of the pre COVID level of vacancy. 106 00:06:03,880 --> 00:06:08,320 Speaker 1: So we are expecting this shift upwards by about four 107 00:06:08,440 --> 00:06:12,479 Speaker 1: hundred fifty four HERD sixty basis points. And that's really 108 00:06:12,920 --> 00:06:16,239 Speaker 1: that is the increase that is putting the downward pressure 109 00:06:16,680 --> 00:06:21,280 Speaker 1: on rental rates um so that that effect is something 110 00:06:21,320 --> 00:06:24,040 Speaker 1: that we expect to play out differently across cities. One 111 00:06:24,080 --> 00:06:27,479 Speaker 1: of the things we do find is that, and this 112 00:06:27,640 --> 00:06:31,840 Speaker 1: is consistent with history as well, suburban market the rents 113 00:06:31,839 --> 00:06:35,359 Speaker 1: there be less elastic, they tend to move less during 114 00:06:35,400 --> 00:06:39,640 Speaker 1: down cycles, and our our city central city rents do 115 00:06:39,760 --> 00:06:41,640 Speaker 1: tend to move by a little bit more in our 116 00:06:41,680 --> 00:06:45,200 Speaker 1: findings were consistent with that as well. Rebecca, thank you. 117 00:06:45,279 --> 00:06:47,960 Speaker 1: Presumably there'll be more studies like this and we will 118 00:06:47,960 --> 00:06:49,680 Speaker 1: continue to keep in touch with you and here more. 119 00:06:49,680 --> 00:06:54,200 Speaker 1: Rebecca Rocky is Global ahead of Forecasting for Kushman and Wakefield, 120 00:06:54,440 --> 00:07:00,040 Speaker 1: joining us today. As we approach the elections, there's in 121 00:07:00,080 --> 00:07:01,760 Speaker 1: the plomban discussion on the Wall Street don't what a 122 00:07:01,920 --> 00:07:07,320 Speaker 1: possible Joe Biden presidency would mean for economic policy for 123 00:07:07,360 --> 00:07:10,240 Speaker 1: financial markets. To get some answers to those questions, we 124 00:07:10,240 --> 00:07:13,840 Speaker 1: welcome Edmund Phelps. Edmund is a Nobel laureate and director 125 00:07:13,920 --> 00:07:17,200 Speaker 1: of the Center on Capitalism in Society at Columbia University, 126 00:07:17,200 --> 00:07:19,600 Speaker 1: Professor Phelps, Thanks so much for joining us. What do 127 00:07:19,680 --> 00:07:23,160 Speaker 1: you What are your thoughts here? Should former Vice President 128 00:07:23,200 --> 00:07:26,880 Speaker 1: Joe Biden win the election, Well, certainly hope you will 129 00:07:26,880 --> 00:07:30,920 Speaker 1: win the election. I think the economy really depends on it. 130 00:07:31,880 --> 00:07:36,160 Speaker 1: I've just been um very disturbed over over these past 131 00:07:36,240 --> 00:07:42,560 Speaker 1: years to see uh Trump's attempts to to guide to 132 00:07:42,560 --> 00:07:47,160 Speaker 1: guide the economy, to intervene right and left. This creates 133 00:07:47,400 --> 00:07:53,160 Speaker 1: enormous uncertainty. That's very bad for investment, and it's very 134 00:07:53,200 --> 00:07:58,840 Speaker 1: bad for innovation. And innovation has already been suffering for 135 00:07:58,920 --> 00:08:03,480 Speaker 1: quite a few decades. But with innovators won't get a 136 00:08:03,560 --> 00:08:08,160 Speaker 1: chance to breathe. So I think I think it's very 137 00:08:08,240 --> 00:08:15,480 Speaker 1: important that we vote out the Trump administration and give 138 00:08:15,800 --> 00:08:18,600 Speaker 1: a new group a chance. So that I first saw 139 00:08:18,800 --> 00:08:22,080 Speaker 1: your article in The Guardian, the editorial and the Guardian 140 00:08:22,160 --> 00:08:25,720 Speaker 1: and then later on a sort of a paper almost 141 00:08:25,720 --> 00:08:28,080 Speaker 1: if you like, in Project to Syndicate, and you basically 142 00:08:28,280 --> 00:08:34,880 Speaker 1: start off by excoriating President Trump's policy, you know, quote 143 00:08:34,920 --> 00:08:38,560 Speaker 1: unquote economic policy, because, as you say, he practices Mussolini's 144 00:08:38,600 --> 00:08:41,840 Speaker 1: doctrine of corporatism, the government as poppet master pulling the 145 00:08:41,840 --> 00:08:45,040 Speaker 1: strings of poppet companies. You also go on to talk 146 00:08:45,080 --> 00:08:47,920 Speaker 1: about as populist rhetoric not translating into better pay for 147 00:08:48,040 --> 00:08:51,800 Speaker 1: less advantage workers or victims of discrimination. And you have 148 00:08:51,800 --> 00:08:55,440 Speaker 1: a whole sort of takedown of President's Trump's economic plans 149 00:08:55,559 --> 00:08:59,640 Speaker 1: or actions. But why aren't we hearing more from Biden 150 00:08:59,720 --> 00:09:02,080 Speaker 1: about what he would do? So, yes, we know that 151 00:09:02,160 --> 00:09:04,680 Speaker 1: he's offering pell grounds to everybody and so on, but 152 00:09:04,760 --> 00:09:08,920 Speaker 1: we're not getting a really developed economic platform as far 153 00:09:09,000 --> 00:09:16,200 Speaker 1: as I can see. Well, I think that Biden has 154 00:09:15,640 --> 00:09:21,840 Speaker 1: h shown an interest in, um doing something about the 155 00:09:21,880 --> 00:09:25,720 Speaker 1: wages at the bottom in this country, which have been 156 00:09:25,760 --> 00:09:30,240 Speaker 1: a have continued to be a terrible problem for decades. 157 00:09:30,800 --> 00:09:35,080 Speaker 1: I think I think he has shown interest in addressing 158 00:09:35,440 --> 00:09:40,679 Speaker 1: the poor, core rewards going to to the least advantage 159 00:09:41,240 --> 00:09:45,200 Speaker 1: in the country. And um, I think maybe your question 160 00:09:45,400 --> 00:09:49,360 Speaker 1: is pointed to what do we hear from Biden about 161 00:09:49,600 --> 00:09:54,000 Speaker 1: investment and innovation? Well, I think I think he's I 162 00:09:54,040 --> 00:10:00,920 Speaker 1: think he's shown some definitely shown some awareness of the 163 00:10:01,080 --> 00:10:06,840 Speaker 1: need for picking up innovation. And of course, in the 164 00:10:06,920 --> 00:10:11,400 Speaker 1: long term, you can't have sustained high investment if you 165 00:10:11,440 --> 00:10:16,760 Speaker 1: don't have underlying innovation going on. So I think it's 166 00:10:16,800 --> 00:10:21,560 Speaker 1: fair to say that Biden grown up in his his 167 00:10:21,800 --> 00:10:25,520 Speaker 1: seventy something years. He's grown up in the economy, and 168 00:10:25,600 --> 00:10:29,080 Speaker 1: he understands what's going on. He understands the weakness of 169 00:10:29,120 --> 00:10:33,880 Speaker 1: the economy, he understand slow growth, and uh, you know, 170 00:10:34,160 --> 00:10:35,960 Speaker 1: there have been a hundred things that he's had to 171 00:10:36,000 --> 00:10:40,240 Speaker 1: talk about, and maybe he's not not talked enough about 172 00:10:41,160 --> 00:10:47,080 Speaker 1: investment innovation, but he has done some talking on economic justice, 173 00:10:47,160 --> 00:10:51,560 Speaker 1: which is the other grand theme of mine. Yes, and 174 00:10:51,760 --> 00:10:54,560 Speaker 1: I understand that, and I appreciate that you say that 175 00:10:54,640 --> 00:10:57,280 Speaker 1: he displays an awareness. But the month has been a 176 00:10:57,280 --> 00:11:02,560 Speaker 1: politician his entire life, and surely he has ideas for 177 00:11:02,640 --> 00:11:06,160 Speaker 1: what he would do to redirect funds in the economy, 178 00:11:06,679 --> 00:11:09,679 Speaker 1: and not just on the corporate innovation side, but also, 179 00:11:09,760 --> 00:11:15,320 Speaker 1: as you say, to translate you know, current politics in 180 00:11:15,320 --> 00:11:19,199 Speaker 1: the situation into better pay for less advantage workers, victims, discrimination, 181 00:11:19,559 --> 00:11:23,800 Speaker 1: erase economic justice injustices and so on. He's not coming 182 00:11:23,800 --> 00:11:26,080 Speaker 1: out with any of that. Is he too scared that 183 00:11:26,080 --> 00:11:31,240 Speaker 1: that will alienate some of the demographics that he might need. Uh, 184 00:11:32,040 --> 00:11:35,319 Speaker 1: I'm not a politician. I'm not even a political scientist. 185 00:11:36,160 --> 00:11:38,600 Speaker 1: I really wouldn't venture. I wouldn't want to venture a 186 00:11:38,640 --> 00:11:41,800 Speaker 1: guest on that at all. All right, So so Edmund, 187 00:11:41,840 --> 00:11:43,720 Speaker 1: give us the thoughts just real quickly here. On trade, 188 00:11:43,760 --> 00:11:46,000 Speaker 1: that's been a big issue for President Trump. How do 189 00:11:46,000 --> 00:11:50,079 Speaker 1: you see a Biden prenency as it relates to economic trade? Oh? Well, 190 00:11:50,120 --> 00:11:53,840 Speaker 1: I think it. The Trump's position towards trade has been 191 00:11:54,800 --> 00:12:01,160 Speaker 1: another contributor to um poor economic performance. Being able to 192 00:12:01,200 --> 00:12:04,479 Speaker 1: trade with the rest of the world is awfully helpful 193 00:12:05,720 --> 00:12:11,600 Speaker 1: in developing new products, in finding markets for new investment. 194 00:12:12,840 --> 00:12:17,640 Speaker 1: It's hard to imagine high prosperity in the American economy 195 00:12:17,679 --> 00:12:23,680 Speaker 1: without without very considerable amounts of international trade, foreign trade. 196 00:12:24,720 --> 00:12:27,720 Speaker 1: And of course another thing is that Trump has gotten 197 00:12:27,840 --> 00:12:33,360 Speaker 1: in the way of bringing in highly qualified people to 198 00:12:34,040 --> 00:12:40,240 Speaker 1: engage in uh innovation in the American economy. Silicon Valley 199 00:12:40,480 --> 00:12:45,560 Speaker 1: is being starved of of the of of much of 200 00:12:45,600 --> 00:12:50,360 Speaker 1: the talent that it needs. UM. I saw the other 201 00:12:50,440 --> 00:12:56,040 Speaker 1: day that about trade and immigration, I saw that three 202 00:12:56,120 --> 00:13:01,280 Speaker 1: thousand companies are now suing the White House over the 203 00:13:01,320 --> 00:13:07,640 Speaker 1: tariffs that have been instituted by the Trump administration. So 204 00:13:07,880 --> 00:13:13,079 Speaker 1: that just that just is an indication of how oppressive 205 00:13:13,160 --> 00:13:19,840 Speaker 1: and how retarding uh Trump's influence has been on the economy. Well, professor, 206 00:13:20,160 --> 00:13:22,559 Speaker 1: thank you for that. We definitely hope to hear more 207 00:13:22,679 --> 00:13:25,760 Speaker 1: from Joe Biden. Of course, the first debate is next Tuesday, 208 00:13:25,840 --> 00:13:28,360 Speaker 1: and I imagine that there will be a portion on 209 00:13:28,480 --> 00:13:32,040 Speaker 1: economic plans and for anybody who's interested in this, the 210 00:13:32,080 --> 00:13:36,840 Speaker 1: economic case for Biden by Professor edmund S. Phelps, Nobel 211 00:13:36,960 --> 00:13:40,680 Speaker 1: Laureate and of course from Columbia University as well, Legended 212 00:13:40,720 --> 00:13:45,120 Speaker 1: Our Lifetimes really is both on Project Syndicate and in 213 00:13:45,200 --> 00:13:47,600 Speaker 1: the Guardian and Paul, I think it's important. I think 214 00:13:47,600 --> 00:13:50,200 Speaker 1: we need some details. Were fewer than fourty days away 215 00:13:50,200 --> 00:13:52,400 Speaker 1: from the selection, and both candidates need to step it 216 00:13:52,440 --> 00:13:57,080 Speaker 1: up with the actual concrete proposals. Well, Vonnie, we are 217 00:13:57,120 --> 00:13:59,679 Speaker 1: so fortunate to have on a regular basis of good 218 00:13:59,679 --> 00:14:02,720 Speaker 1: folks of Johns Hopkins University come on and help us 219 00:14:02,760 --> 00:14:07,640 Speaker 1: get a little bit smarter about this virus and potential therapy, 220 00:14:07,880 --> 00:14:10,719 Speaker 1: potential vaccines. Today we're joined by Lauren Sauer at the 221 00:14:10,720 --> 00:14:14,920 Speaker 1: Assistant Professor of Emergency Medicine at Johns Hopkins University. H Lauren, 222 00:14:14,920 --> 00:14:17,000 Speaker 1: thanks so much for joining us here. You know, the 223 00:14:17,080 --> 00:14:20,480 Speaker 1: new story I guess I heard today is something called 224 00:14:20,600 --> 00:14:24,040 Speaker 1: interfere on as a possible new treatment. To educate us 225 00:14:24,040 --> 00:14:27,920 Speaker 1: on kind of what you think this might mean. Yeah, 226 00:14:28,040 --> 00:14:30,720 Speaker 1: the two studies that came out recently on interfere on, 227 00:14:30,760 --> 00:14:34,040 Speaker 1: we're really exciting to see. And I think, um, what 228 00:14:34,120 --> 00:14:36,960 Speaker 1: I had seen, what I've seen briefly is that this 229 00:14:37,080 --> 00:14:40,480 Speaker 1: may The scientists who did the studies feel that this 230 00:14:40,600 --> 00:14:44,680 Speaker 1: may um account for nearly fifteen fourteen or fifteen percent 231 00:14:44,760 --> 00:14:49,600 Speaker 1: of the severe COVID cases. Um. What they're seeing is 232 00:14:49,640 --> 00:14:52,000 Speaker 1: that this sort of lack of interfere on and the 233 00:14:52,040 --> 00:14:55,640 Speaker 1: body is helping to facilitate severe disease. So people are 234 00:14:55,640 --> 00:14:59,400 Speaker 1: getting sicker. Um. The good thing about it is that 235 00:14:59,600 --> 00:15:04,080 Speaker 1: we have used interference, especially synthetic interference, for a long 236 00:15:04,120 --> 00:15:07,160 Speaker 1: time for other diseases, and so UM, if we can 237 00:15:07,200 --> 00:15:09,480 Speaker 1: target these at risk patients and use some of this 238 00:15:09,600 --> 00:15:12,600 Speaker 1: research to identify them early, um, we may be able 239 00:15:12,600 --> 00:15:15,520 Speaker 1: to treat them quickly with therapies that we already have 240 00:15:15,560 --> 00:15:19,800 Speaker 1: in our tool kit for other diseases. And it's particularly 241 00:15:19,840 --> 00:15:22,840 Speaker 1: amazing if it ends up being all true and the 242 00:15:22,880 --> 00:15:25,960 Speaker 1: research proves itself out, because it's the type of thing 243 00:15:25,960 --> 00:15:28,880 Speaker 1: that hits young people. And also it means that it 244 00:15:28,960 --> 00:15:31,320 Speaker 1: might save you from going on respirator, which we all know. 245 00:15:31,440 --> 00:15:34,640 Speaker 1: Then you know, it is a whole other stage in 246 00:15:34,640 --> 00:15:38,760 Speaker 1: this illness. When might we know something about the effectiveness 247 00:15:38,880 --> 00:15:43,160 Speaker 1: of of an interfere on you know, rehabilitation scheme if 248 00:15:43,200 --> 00:15:47,560 Speaker 1: you like. Yeah, so, and the studies that came out 249 00:15:47,600 --> 00:15:50,160 Speaker 1: are already telling us that interfe treatment may be an 250 00:15:50,160 --> 00:15:54,280 Speaker 1: effective option. UM. The new arm of the NIH Adaptive 251 00:15:54,320 --> 00:15:57,520 Speaker 1: Trial Act is also an interfere on study. And I 252 00:15:57,520 --> 00:16:01,000 Speaker 1: would imagine that there's lots of interfere on UM studies 253 00:16:01,320 --> 00:16:05,240 Speaker 1: across the country and possibly across the globe. UM, there's 254 00:16:05,760 --> 00:16:09,320 Speaker 1: I'm just too doing interfere on specific studies, especially when 255 00:16:09,320 --> 00:16:12,480 Speaker 1: you're thinking these studies may target or only enroll people 256 00:16:12,520 --> 00:16:16,880 Speaker 1: with severe disease. UM. We are seeing more outpatients with 257 00:16:17,000 --> 00:16:21,200 Speaker 1: COVID and peer severe disease at least where I am UM, 258 00:16:21,400 --> 00:16:26,320 Speaker 1: and so focusing on enrolling those patients into the clinical 259 00:16:26,360 --> 00:16:29,520 Speaker 1: trials quickly and efficiently, both to hopefully save lives but 260 00:16:29,600 --> 00:16:34,520 Speaker 1: also to really better understand the mechanism is critical right now. So, Lauren, 261 00:16:34,560 --> 00:16:37,600 Speaker 1: it appears the data remains stupornly high in terms of 262 00:16:38,120 --> 00:16:44,560 Speaker 1: new cases. UM, yet perhaps the death rate is declining. 263 00:16:44,880 --> 00:16:47,040 Speaker 1: Is that kind of your understanding some of the data 264 00:16:47,080 --> 00:16:51,160 Speaker 1: we're starting to see more recently. Yeah. I think one 265 00:16:51,160 --> 00:16:54,120 Speaker 1: of the things we're seeing is that, UM, we're we 266 00:16:54,320 --> 00:16:58,840 Speaker 1: are getting patients out of the hospital quicker, which is great, UM, 267 00:16:58,920 --> 00:17:02,120 Speaker 1: and that may be I think we're gonna need a 268 00:17:02,120 --> 00:17:04,520 Speaker 1: lot of long term studies to understand why that's happening. 269 00:17:04,640 --> 00:17:06,760 Speaker 1: But a big piece of it maybe that we're getting 270 00:17:06,760 --> 00:17:09,160 Speaker 1: better at managing these patients because we're learning more about 271 00:17:09,200 --> 00:17:11,760 Speaker 1: the course of illness and the course of disease. So UM, 272 00:17:11,760 --> 00:17:15,480 Speaker 1: we're keeping people from entering into that severe disease state, 273 00:17:15,520 --> 00:17:18,840 Speaker 1: you know, off of ventilator, UM, off of those high 274 00:17:18,880 --> 00:17:22,879 Speaker 1: flow oxygen needs, because we're managing their earlier or or 275 00:17:23,000 --> 00:17:25,960 Speaker 1: we're identifying them earlier and we're managing them better in 276 00:17:26,000 --> 00:17:30,119 Speaker 1: the hospital and getting them not quicker. So, Lauren, we 277 00:17:30,119 --> 00:17:34,199 Speaker 1: were talking yesterday about people in the UK proactively getting 278 00:17:34,720 --> 00:17:38,040 Speaker 1: injected or or infected with coronavirus in order to try 279 00:17:38,119 --> 00:17:41,760 Speaker 1: and help studies these people, I mean, are they risking 280 00:17:41,840 --> 00:17:46,959 Speaker 1: long term consequences? I think they absolutely are. The challenge 281 00:17:47,000 --> 00:17:50,359 Speaker 1: study model that UM talking about that we're seeing in 282 00:17:50,400 --> 00:17:53,080 Speaker 1: the UK. UM is a model that we've used in 283 00:17:53,119 --> 00:17:57,199 Speaker 1: other diseases to better understand UM how vaccines work, so 284 00:17:57,240 --> 00:18:00,480 Speaker 1: that it's a controlled environment and we understand the exposure, 285 00:18:00,840 --> 00:18:03,960 Speaker 1: We understand the course of the disease and exactly where 286 00:18:03,960 --> 00:18:07,080 Speaker 1: in the disease process of patients or the participants get 287 00:18:07,160 --> 00:18:11,359 Speaker 1: the vaccine UM and what their exposure level is after 288 00:18:12,040 --> 00:18:16,080 Speaker 1: getting the vaccine. The hard part in this situation is 289 00:18:16,160 --> 00:18:19,679 Speaker 1: that we don't have a really good therapeutic toolkit, so 290 00:18:19,720 --> 00:18:23,680 Speaker 1: if something goes wrong with these patients UM, we don't 291 00:18:23,760 --> 00:18:28,840 Speaker 1: have a great a series of great options to treat them, 292 00:18:28,960 --> 00:18:31,080 Speaker 1: so that that is a higher risk than than you 293 00:18:31,119 --> 00:18:35,120 Speaker 1: would want in a challenge study. And there's a lot 294 00:18:35,160 --> 00:18:38,960 Speaker 1: of ongoing community transmission in many places across the globe, 295 00:18:39,640 --> 00:18:43,119 Speaker 1: so there are opportunities to do vaccine trials the right 296 00:18:43,160 --> 00:18:47,280 Speaker 1: way in a well controlled environment, understanding community transmission without 297 00:18:47,320 --> 00:18:51,080 Speaker 1: putting people deliberately at risk and exposing them to to 298 00:18:51,240 --> 00:18:55,280 Speaker 1: the coronavirus. So it's a risk that we're taking unnecessarily. 299 00:18:56,560 --> 00:18:58,960 Speaker 1: So Lauren, again I'm just going to ask us to 300 00:18:59,000 --> 00:19:01,919 Speaker 1: try to triangulate around timing. Is it still fair to 301 00:19:02,440 --> 00:19:05,400 Speaker 1: suspect that we will that some series of vaccines will 302 00:19:05,400 --> 00:19:08,320 Speaker 1: be available sometime early next year, maybe late this year, 303 00:19:08,640 --> 00:19:10,199 Speaker 1: but it will take time after that to kind of 304 00:19:10,200 --> 00:19:12,280 Speaker 1: figure out what's most effective. Is that's still the way 305 00:19:12,280 --> 00:19:15,840 Speaker 1: to think about it. Yeah, I think that early next 306 00:19:15,920 --> 00:19:19,560 Speaker 1: year is probably on target for a few of these vaccines. UM. 307 00:19:19,680 --> 00:19:22,360 Speaker 1: We're seeing the Phase three trials happen right now, We're 308 00:19:22,359 --> 00:19:25,240 Speaker 1: seeing good data come in. I think the challenges that 309 00:19:25,359 --> 00:19:28,480 Speaker 1: scale up piece so UM. Once a vaccine can it 310 00:19:28,560 --> 00:19:31,360 Speaker 1: goes through the process, we still have the regulatory environment 311 00:19:31,400 --> 00:19:34,760 Speaker 1: for getting that approval from the FDA. For example. UM. 312 00:19:34,800 --> 00:19:37,880 Speaker 1: There is discussion of you of using the Emergency used 313 00:19:37,960 --> 00:19:42,760 Speaker 1: authorization in the interim space between UM or preliminary data 314 00:19:42,800 --> 00:19:45,919 Speaker 1: from the Phase three trials and getting approval from the 315 00:19:46,720 --> 00:19:49,439 Speaker 1: UM for the vaccine to roll out more broadly. But 316 00:19:49,480 --> 00:19:53,360 Speaker 1: we also have to consider scale up of manufacturing, distribution plans, 317 00:19:53,560 --> 00:19:56,720 Speaker 1: prioritizing the people who will receive it, what are the 318 00:19:56,760 --> 00:20:00,720 Speaker 1: most important populations UM, And so there's a lot of 319 00:20:00,760 --> 00:20:02,879 Speaker 1: things that have to happen between now and a massive 320 00:20:02,960 --> 00:20:06,000 Speaker 1: rollout of the vaccine trial. And I think mid to 321 00:20:06,240 --> 00:20:08,760 Speaker 1: late and mid to the end of next year is 322 00:20:08,800 --> 00:20:12,160 Speaker 1: probably reasonable for large scale rollout. Lawrence, thank you as 323 00:20:12,200 --> 00:20:15,800 Speaker 1: always absolutely love getting your updates straight from you know, 324 00:20:15,840 --> 00:20:18,840 Speaker 1: the epicenter of where all the research is happening. Lawrence 325 00:20:18,840 --> 00:20:22,040 Speaker 1: Hower is the system Professor of Emergency Medicine at Johns 326 00:20:22,040 --> 00:20:25,000 Speaker 1: Hopkins School of Medicine and of course the Bloomberg School 327 00:20:25,000 --> 00:20:27,119 Speaker 1: of Public Health. Is supported by MICHAELAR Bloomberg, founder of 328 00:20:27,160 --> 00:20:32,800 Speaker 1: Bloomberg LP and Bloomberg Philanthropies and Bloomberg Markets. Is brought 329 00:20:32,920 --> 00:20:36,480 Speaker 1: team by with him forward thinking advisory and accounting firm 330 00:20:36,480 --> 00:20:38,600 Speaker 1: helping hiens to be in a position of strength and 331 00:20:38,680 --> 00:20:42,159 Speaker 1: the new reality of business learn about their innovative solutions 332 00:20:42,160 --> 00:20:46,399 Speaker 1: by visiting with them dot com. So it's time to 333 00:20:46,440 --> 00:20:50,160 Speaker 1: talk commodities. Some are seeing good news, some are not 334 00:20:50,200 --> 00:20:52,360 Speaker 1: seeing so much good news. Let's bring in Mike McGlone, 335 00:20:52,440 --> 00:20:55,359 Speaker 1: who knows all about the precious metals and also precious 336 00:20:55,400 --> 00:20:58,080 Speaker 1: metals and every other commodity out there. He's commodity strategist 337 00:20:58,080 --> 00:21:01,120 Speaker 1: for Bloomberg Intelligence. Mike, we haven't talked too much about 338 00:21:01,160 --> 00:21:04,760 Speaker 1: China recently, mainly because apart from TikTok and ouricle and 339 00:21:04,760 --> 00:21:08,119 Speaker 1: so on, there haven't been many trade developments. But at 340 00:21:08,119 --> 00:21:12,600 Speaker 1: the same time, underlying commodities are moving still because of this. 341 00:21:12,800 --> 00:21:16,119 Speaker 1: For example, China went on a buying spree and so 342 00:21:16,200 --> 00:21:19,480 Speaker 1: that seems to have revived export profits for some top 343 00:21:19,520 --> 00:21:22,400 Speaker 1: crop traders. So that's good news, right, Are we seeing 344 00:21:22,440 --> 00:21:25,760 Speaker 1: prices reflect that? Oh? Certainly in soybeans tiganium, Yes, so 345 00:21:25,800 --> 00:21:27,399 Speaker 1: I means that ten dollars a bush, so they're up 346 00:21:27,400 --> 00:21:29,600 Speaker 1: about five percent in the year they got about ten thirty. 347 00:21:29,960 --> 00:21:32,719 Speaker 1: That's been a good sign. It's almost completely on exports 348 00:21:32,720 --> 00:21:35,040 Speaker 1: because it's a big crop this year, not really swabeans, 349 00:21:35,080 --> 00:21:37,119 Speaker 1: but corn, so that's a big deal. And also the 350 00:21:37,119 --> 00:21:39,879 Speaker 1: market's anticipating the potential peak in the dollar, and the 351 00:21:39,960 --> 00:21:43,879 Speaker 1: US now exports about swabeans, so the value of the dollar, 352 00:21:44,240 --> 00:21:46,200 Speaker 1: the value of the Brazilian real is a big thing. 353 00:21:46,280 --> 00:21:48,040 Speaker 1: Just the fact that the China has been back in 354 00:21:48,080 --> 00:21:51,560 Speaker 1: has been good in crops, it's really better take taking 355 00:21:51,600 --> 00:21:54,280 Speaker 1: them off the bottom. But for new highs to really 356 00:21:54,280 --> 00:21:58,200 Speaker 1: go up for more strength, eggs need a peak dollar, 357 00:22:00,080 --> 00:22:02,440 Speaker 1: all right. So but also look at the dollar index 358 00:22:02,480 --> 00:22:05,199 Speaker 1: here at ninety four. That's not peaked. Dollar isn't no 359 00:22:05,400 --> 00:22:07,800 Speaker 1: hit all um, And it's really and from from the 360 00:22:07,800 --> 00:22:10,320 Speaker 1: egg standpoint, we watched the trade weighted broad dollar because 361 00:22:10,359 --> 00:22:13,960 Speaker 1: the dollar index is six almost two thirds Euro trade 362 00:22:13,960 --> 00:22:17,440 Speaker 1: weighted broad is mostly China's China. It doesn't take every day, 363 00:22:17,600 --> 00:22:19,760 Speaker 1: but gives you a good indication. The key thing is 364 00:22:19,800 --> 00:22:22,160 Speaker 1: what's been really driving that strong dollar the last ten 365 00:22:22,240 --> 00:22:25,240 Speaker 1: years ago, so is the out performance the US stock market. 366 00:22:25,520 --> 00:22:27,560 Speaker 1: So we're seeing lately is a bit of a divergence. 367 00:22:27,560 --> 00:22:31,159 Speaker 1: There's been flows into commanities. Commanies are outperforming during this 368 00:22:31,280 --> 00:22:33,960 Speaker 1: last little sloon correction in the stock markets. The key 369 00:22:34,040 --> 00:22:36,480 Speaker 1: is Greggs and Eggs aren't really going to really matter 370 00:22:36,520 --> 00:22:38,440 Speaker 1: to the stock market so much. But in copper, that's 371 00:22:38,440 --> 00:22:40,119 Speaker 1: been a key thing I've been watching. Copper is the 372 00:22:40,200 --> 00:22:42,760 Speaker 1: highest correlation to the stock market ever in a fifty 373 00:22:42,760 --> 00:22:45,600 Speaker 1: two weeks twelve one basis and it's really not and 374 00:22:45,640 --> 00:22:48,520 Speaker 1: it's still hanging around three dollars a pound versus the 375 00:22:48,520 --> 00:22:50,879 Speaker 1: ten percent correction in nansect. That's a good sign that 376 00:22:50,920 --> 00:22:53,080 Speaker 1: maybe we're seeing some divergence. I think people are looking 377 00:22:53,080 --> 00:22:56,720 Speaker 1: more for the physical assets, not just gold, silver, platinum plate, 378 00:22:56,800 --> 00:22:59,439 Speaker 1: and not just sup precious but more the base metals 379 00:22:59,480 --> 00:23:01,439 Speaker 1: like copper. Well, I was going to say, with the 380 00:23:01,480 --> 00:23:04,000 Speaker 1: exception actually of gold, which seems to really have just 381 00:23:04,200 --> 00:23:06,320 Speaker 1: gone and got its cold and left the room, right Mike. 382 00:23:08,320 --> 00:23:10,840 Speaker 1: In the short term, gold still up in the year. 383 00:23:10,840 --> 00:23:15,040 Speaker 1: In the unchanged Bitcoin is up in there. So my 384 00:23:15,160 --> 00:23:17,639 Speaker 1: bias at the beginning here was the quasi currencies gold 385 00:23:17,800 --> 00:23:20,119 Speaker 1: and bitcoin should continue to outperform. I don't see why 386 00:23:20,119 --> 00:23:22,560 Speaker 1: I should change that. The gold just got a little 387 00:23:22,600 --> 00:23:25,160 Speaker 1: bit extended. You know, it was fifty it was well 388 00:23:25,160 --> 00:23:27,040 Speaker 1: above is fifty two eight me and the highest and 389 00:23:27,400 --> 00:23:29,960 Speaker 1: a long time. It's it's it's consolidating the bull market 390 00:23:30,000 --> 00:23:31,480 Speaker 1: that way I see it. Right now. It's going to 391 00:23:31,560 --> 00:23:33,640 Speaker 1: back up in the good sport around eighteen hundred dollars 392 00:23:33,680 --> 00:23:35,560 Speaker 1: and ounced. But if you look at the foundation for 393 00:23:35,640 --> 00:23:39,040 Speaker 1: gold rapidly rise in US debt to the GDP and 394 00:23:39,160 --> 00:23:42,200 Speaker 1: increase in CHEWI on a global SCS scale, it's unprecedented 395 00:23:42,240 --> 00:23:44,760 Speaker 1: goal has a very solid foundation for the next five 396 00:23:44,760 --> 00:23:48,480 Speaker 1: ten years. And just help us revisit the bull case 397 00:23:48,720 --> 00:23:52,159 Speaker 1: for bitcoin. We can talk bitcoin. Vannie doesn't have a 398 00:23:52,200 --> 00:23:56,080 Speaker 1: no bitcoin policy like Tom peen Um. So give us 399 00:23:56,080 --> 00:23:59,800 Speaker 1: that bull case for bitcoin again, Mike. Bottom line very 400 00:24:00,040 --> 00:24:03,760 Speaker 1: and supply actually less potentially less supply than gold. Higher 401 00:24:03,760 --> 00:24:06,200 Speaker 1: prices will not bring on more supply, and then it's 402 00:24:06,200 --> 00:24:08,879 Speaker 1: about demand. So all my indications for demand are higher, 403 00:24:09,119 --> 00:24:12,600 Speaker 1: and bitcoin has been becoming adopted in the space. There's 404 00:24:12,640 --> 00:24:15,560 Speaker 1: more and more people getting in there. The main indications 405 00:24:15,560 --> 00:24:19,720 Speaker 1: are quite positive. Futures open, interest um, exchange traded products 406 00:24:19,880 --> 00:24:24,040 Speaker 1: coming on for and and addresses used and things like that. 407 00:24:24,040 --> 00:24:26,520 Speaker 1: So bitcoins is getting there. The cool thing about bitcoins 408 00:24:26,520 --> 00:24:29,240 Speaker 1: has had a significant correction and it's had a period 409 00:24:29,280 --> 00:24:31,720 Speaker 1: of disdain, and so that's us you a good foundation 410 00:24:31,720 --> 00:24:34,760 Speaker 1: for higher prices. And the correlation between bitcoin and gold 411 00:24:35,160 --> 00:24:37,159 Speaker 1: is the highest ever depending on how you measure it. 412 00:24:37,320 --> 00:24:40,600 Speaker 1: So I see bitcoin is becoming a digital version of gold. 413 00:24:40,600 --> 00:24:42,040 Speaker 1: It's just more of a kind of a baby and 414 00:24:42,080 --> 00:24:45,520 Speaker 1: it's catching up. It's taking baby steps now at the moment. Well, 415 00:24:45,560 --> 00:24:49,200 Speaker 1: I on that note, would like to compare Etherium with bitcoin, 416 00:24:49,480 --> 00:24:51,320 Speaker 1: and so if you look at returns over the last year, 417 00:24:51,320 --> 00:24:56,160 Speaker 1: ethereum is up on Bitcoin, up versus the US dollar. 418 00:24:56,280 --> 00:24:58,119 Speaker 1: Does that just suggest that bitcoin is a little more 419 00:24:58,160 --> 00:25:01,679 Speaker 1: mature as a cryptocurrency. It is, and there's a big difference. 420 00:25:01,680 --> 00:25:04,280 Speaker 1: Ethereum kind of part of the whole other crypto space, 421 00:25:04,280 --> 00:25:06,760 Speaker 1: and there's seven thousand of them Ethereum is the number 422 00:25:06,840 --> 00:25:09,280 Speaker 1: two cryptocurrency, but if you look at the current trends, 423 00:25:09,560 --> 00:25:11,959 Speaker 1: a theorem will be surpassed next year by the stable 424 00:25:11,960 --> 00:25:14,600 Speaker 1: coin tether. So ethereum has got good and things that 425 00:25:14,640 --> 00:25:18,240 Speaker 1: has going for it is defied decentralized finances finance, and 426 00:25:18,640 --> 00:25:22,880 Speaker 1: the dex is decentralized exchanges. Theorems like the first platform 427 00:25:22,920 --> 00:25:25,760 Speaker 1: for that, but it has a lot of competition. Theorium 428 00:25:25,800 --> 00:25:28,280 Speaker 1: got a little bit expensive around five hundred. It's meeting 429 00:25:28,320 --> 00:25:30,479 Speaker 1: good support around three hundred. But I think their overall 430 00:25:30,520 --> 00:25:33,800 Speaker 1: bias is towards and continued to increase. But Bitcoin should 431 00:25:33,800 --> 00:25:36,560 Speaker 1: continue to outperform the overall broad market. And the problem 432 00:25:36,600 --> 00:25:39,600 Speaker 1: is there's just too much supply in the broad crypto market. 433 00:25:40,440 --> 00:25:42,359 Speaker 1: So Mike, we can't let you go without talking the 434 00:25:42,440 --> 00:25:45,920 Speaker 1: soft commodities, agricultural. Do we have evidence? I mean, is 435 00:25:45,960 --> 00:25:49,920 Speaker 1: this market now just completely driven by China on? China off? 436 00:25:50,040 --> 00:25:51,159 Speaker 1: Is that kind of the only thing we need to 437 00:25:51,160 --> 00:25:54,720 Speaker 1: focus on. It's right now, it is China has really 438 00:25:54,720 --> 00:25:56,359 Speaker 1: helped bring it out of the dull drums, and we 439 00:25:56,560 --> 00:25:58,760 Speaker 1: had multi year lows, lows and corns just a few 440 00:25:58,760 --> 00:26:01,120 Speaker 1: months ago, and soybeans are getting pretty beat up. Yet 441 00:26:01,160 --> 00:26:02,720 Speaker 1: we have a you know, have a pretty good crop. 442 00:26:02,760 --> 00:26:06,159 Speaker 1: But this year, actually the revisions for the U s 443 00:26:06,200 --> 00:26:09,440 Speaker 1: productions actually come down since that August report, so it's 444 00:26:09,440 --> 00:26:12,080 Speaker 1: a good sign it's going that way. But I don't 445 00:26:12,080 --> 00:26:15,560 Speaker 1: see US sauce i e. Corn soy means really having 446 00:26:15,600 --> 00:26:18,520 Speaker 1: a good bullmark until the dollar peaks, because the US 447 00:26:18,680 --> 00:26:21,080 Speaker 1: now exports more than of its soy it means and 448 00:26:21,119 --> 00:26:24,880 Speaker 1: over its wheat. So the dollar really matters there. Well, 449 00:26:24,920 --> 00:26:27,880 Speaker 1: I mean just on the US. You know, how can 450 00:26:27,880 --> 00:26:30,360 Speaker 1: the dollar peak again or even get much stronger when 451 00:26:30,400 --> 00:26:33,800 Speaker 1: the Chinese have the yuan trading around you know, six 452 00:26:33,920 --> 00:26:37,240 Speaker 1: eight at this point and looking to go even lower 453 00:26:37,320 --> 00:26:40,399 Speaker 1: i e. Stronger. Well, so the the un has actually 454 00:26:40,400 --> 00:26:42,480 Speaker 1: been strengthening recently because it's six eight used to be 455 00:26:42,480 --> 00:26:44,960 Speaker 1: seven recently. But the key thing you remember from the 456 00:26:45,040 --> 00:26:50,120 Speaker 1: dollar standpoint is the dollars measured against other other other currencies, 457 00:26:50,119 --> 00:26:52,000 Speaker 1: which are all paper currencies, and that's where you come 458 00:26:52,040 --> 00:26:55,760 Speaker 1: to the physical assets like most notably the medals, the gold, 459 00:26:55,800 --> 00:26:59,200 Speaker 1: the bitcoins of the world. They're rising versus all paper currencies. 460 00:26:59,200 --> 00:27:03,000 Speaker 1: So it's that race for cheaper currencies. Everybody's queueing everybody's 461 00:27:03,040 --> 00:27:06,560 Speaker 1: at zero rates, which means physical assets like copper and 462 00:27:06,640 --> 00:27:08,760 Speaker 1: gold and bitcoin are gaining that value. And that's what 463 00:27:08,800 --> 00:27:10,720 Speaker 1: I see going forward, and hopefully that'll trickle down to 464 00:27:10,720 --> 00:27:12,800 Speaker 1: the other commodities. It's just probably not going to trickle 465 00:27:12,880 --> 00:27:15,040 Speaker 1: up to crude oil because there's too much supply and 466 00:27:15,040 --> 00:27:18,320 Speaker 1: we all know the trend in decarbonization. Really quick, I'm 467 00:27:18,320 --> 00:27:21,719 Speaker 1: gonna slip in a discussion about cattle. What's going on? 468 00:27:21,720 --> 00:27:24,399 Speaker 1: How's the herd look? Yes, sorry, that's one thing I 469 00:27:24,400 --> 00:27:27,520 Speaker 1: don't watch much of cattle, Paul, I'm sorry about that one. 470 00:27:27,600 --> 00:27:29,200 Speaker 1: Just the one thing I've never been able to figure 471 00:27:29,200 --> 00:27:31,960 Speaker 1: out is a good high robust correlations to the price 472 00:27:32,000 --> 00:27:37,040 Speaker 1: of cattle. Alright, I see it's possible to stump Mike mcgloan, 473 00:27:37,080 --> 00:27:40,240 Speaker 1: Michael don't. Thanks so much for joining US commodity strategists 474 00:27:40,440 --> 00:27:45,399 Speaker 1: for Bloomberg Intelligences all over the commodity complex. For ut Vonnie, 475 00:27:45,400 --> 00:27:47,800 Speaker 1: it's great to have my gun. Cattle features don't seem 476 00:27:47,840 --> 00:27:50,040 Speaker 1: to be shifting around much Pole. Of course I looked 477 00:27:50,080 --> 00:27:52,280 Speaker 1: it up. It's LC one. If you want the genericat 478 00:27:52,520 --> 00:27:54,720 Speaker 1: I'm sure every farmer out there would say that no 479 00:27:54,880 --> 00:27:58,800 Speaker 1: cattle is generic they're all individual. Thanks for listening to 480 00:27:58,800 --> 00:28:02,040 Speaker 1: Bloomberg Markets podcast asked. You can subscribe and listen to 481 00:28:02,160 --> 00:28:05,920 Speaker 1: interviews at Apple Podcasts or whatever podcast platform you prefer. 482 00:28:06,160 --> 00:28:09,119 Speaker 1: I'm Bonnie Quinn, I'm on Twitter at Bonnie Quinn. And 483 00:28:09,200 --> 00:28:11,800 Speaker 1: I'm Paul Sweeney. I'm on Twitter at pt Sweeney. Before 484 00:28:11,840 --> 00:28:14,680 Speaker 1: the podcast, you can always catch us worldwide at Bloomberg 485 00:28:14,760 --> 00:28:15,000 Speaker 1: Radio