1 00:00:05,800 --> 00:00:08,720 Speaker 1: Welcome to the Bloomberg p m L Podcast. I'm pim Fox. 2 00:00:08,760 --> 00:00:11,560 Speaker 1: Along with my co host Lisa Abramowitz. Each day we 3 00:00:11,640 --> 00:00:15,120 Speaker 1: bring you the most important, noteworthy, and useful interviews for 4 00:00:15,200 --> 00:00:17,840 Speaker 1: you and your money, whether you're at the grocery store 5 00:00:17,960 --> 00:00:20,720 Speaker 1: or the trading floor. Find the Bloomberg p m L 6 00:00:20,840 --> 00:00:31,800 Speaker 1: Podcast on Apple Podcasts, SoundCloud, and Bloomberg dot Com. Earlier today, 7 00:00:31,880 --> 00:00:35,640 Speaker 1: President Donald Trump said tariffs have put the United States 8 00:00:35,640 --> 00:00:39,400 Speaker 1: in a very strong bargaining position, with billions of dollars 9 00:00:39,400 --> 00:00:43,640 Speaker 1: and jobs flowing into our country, and yet cost increases 10 00:00:43,680 --> 00:00:47,919 Speaker 1: have thus far been almost unnoticeable. If countries will not 11 00:00:48,040 --> 00:00:51,720 Speaker 1: make fair deals with US, they will be tariff That's 12 00:00:51,720 --> 00:00:56,320 Speaker 1: according to President Donald Trump's tweet earlier today. Here to 13 00:00:56,360 --> 00:00:59,400 Speaker 1: help us understand this issue is Brad Setser. He is 14 00:00:59,600 --> 00:01:04,040 Speaker 1: the Senior Fellow for International Economics the Council of Foreign Relations, 15 00:01:04,040 --> 00:01:07,679 Speaker 1: and he joins us now, Brad, do tariffs put the 16 00:01:07,760 --> 00:01:11,640 Speaker 1: United States in a stronger bargaining position. Let's say visavi 17 00:01:11,760 --> 00:01:16,800 Speaker 1: the Chinese, so they present China. They present China with 18 00:01:16,840 --> 00:01:22,000 Speaker 1: a choice. China will, if it wants to avoid Trump's concessions, 19 00:01:22,080 --> 00:01:26,200 Speaker 1: have to make some concessions of its own. I think 20 00:01:26,240 --> 00:01:29,360 Speaker 1: the difficulty is that it is from the Chinese point 21 00:01:29,360 --> 00:01:31,080 Speaker 1: of view, and I think from the point of view 22 00:01:31,120 --> 00:01:35,160 Speaker 1: of most outside observers a little unclear precisely what Trump 23 00:01:35,200 --> 00:01:39,400 Speaker 1: wants from China. So in that sense, uh, the US 24 00:01:39,480 --> 00:01:44,680 Speaker 1: bargaining position is weakened by the lack of clarity about 25 00:01:44,760 --> 00:01:50,960 Speaker 1: US negotiating goals. Right your expertise laws in balance of payments, 26 00:01:51,200 --> 00:01:54,200 Speaker 1: and right now I'm struck by the fact that markets 27 00:01:54,240 --> 00:01:58,960 Speaker 1: are really not responding to these potential additional two hundillion 28 00:01:58,960 --> 00:02:02,640 Speaker 1: dollars of tariffs. What would the practical effect of them be. 29 00:02:06,040 --> 00:02:12,080 Speaker 1: I mean, they would be a significant friction to about 30 00:02:12,240 --> 00:02:17,280 Speaker 1: half of US trade with China, so total, you know, 31 00:02:17,520 --> 00:02:21,120 Speaker 1: looking back last year, total US mports from China were 32 00:02:21,120 --> 00:02:26,640 Speaker 1: about we've put tariffs on fifty billion already. You add 33 00:02:26,840 --> 00:02:30,000 Speaker 1: two billion to that, and you've careft about half of 34 00:02:30,120 --> 00:02:34,560 Speaker 1: trade with China. The tariff level though that has been 35 00:02:34,600 --> 00:02:40,160 Speaker 1: floated on the two is and it's hard to get 36 00:02:40,800 --> 00:02:44,959 Speaker 1: a major shock out of a ten taraff on two billion. 37 00:02:45,040 --> 00:02:48,480 Speaker 1: You just work through the math. If everybody pays it, 38 00:02:48,480 --> 00:02:52,520 Speaker 1: it's about a twenty billion dollar tax that goes to 39 00:02:52,560 --> 00:02:57,000 Speaker 1: the U. S. Treasury presumably paid for by some combination 40 00:02:57,040 --> 00:03:01,200 Speaker 1: of US consumers and US businesses. Uh. And that's just 41 00:03:01,639 --> 00:03:07,440 Speaker 1: not on a scale large enough to generate major macroeconomic shocks. 42 00:03:07,880 --> 00:03:12,760 Speaker 1: There certainly will be some sectoral complications, and I suspect 43 00:03:13,080 --> 00:03:16,720 Speaker 1: that there may be more pain associated with the coming 44 00:03:16,800 --> 00:03:21,799 Speaker 1: Chinese retaliation. Brad. If let's say that Chinese negotiators were 45 00:03:21,800 --> 00:03:26,240 Speaker 1: to call Brad Setzer and ask him, what do you 46 00:03:26,280 --> 00:03:30,400 Speaker 1: really believe the administration wants from these trade talks? How 47 00:03:30,400 --> 00:03:36,120 Speaker 1: would you respond? I would say that there are there 48 00:03:36,160 --> 00:03:40,400 Speaker 1: seemed to be at least three schools of camp within 49 00:03:40,440 --> 00:03:43,520 Speaker 1: the Trump administration. I think there's a camp within the 50 00:03:43,520 --> 00:03:50,080 Speaker 1: Trump administration that believes the tariffs are preferable to almost 51 00:03:50,120 --> 00:03:54,760 Speaker 1: any plausible deal. They want to put a tariff on 52 00:03:54,880 --> 00:03:59,400 Speaker 1: trade with China to encourage US firms to to relocate 53 00:03:59,440 --> 00:04:03,360 Speaker 1: their supply chains, reorganize their supply chains, and become less 54 00:04:03,400 --> 00:04:07,560 Speaker 1: dependent on China. So the goal, in some sense is 55 00:04:07,720 --> 00:04:11,840 Speaker 1: less to change Chinese behavior and more to convince US 56 00:04:11,960 --> 00:04:16,880 Speaker 1: firms to restructure their supply chains and at least move 57 00:04:16,960 --> 00:04:19,960 Speaker 1: them out of China, if not move them to the US. 58 00:04:20,120 --> 00:04:22,279 Speaker 1: I think there's a second school of thought within the 59 00:04:22,320 --> 00:04:28,000 Speaker 1: administration that wants to see substantive changes to the policies 60 00:04:28,000 --> 00:04:35,719 Speaker 1: known as China China's industrial policy, it's tech transfer policies, 61 00:04:36,040 --> 00:04:39,920 Speaker 1: the set of techniques that China is using to build 62 00:04:39,960 --> 00:04:46,039 Speaker 1: out advanced manufacturing industries like aircraft, like semiconductors, like high 63 00:04:46,160 --> 00:04:50,360 Speaker 1: end medical equipment, And they want meaningful changes there, although 64 00:04:50,360 --> 00:04:54,760 Speaker 1: they haven't articulated precisely what kind of changes would be enough. 65 00:04:55,279 --> 00:04:57,240 Speaker 1: And then I think there's a third camp that just 66 00:04:57,279 --> 00:05:01,080 Speaker 1: wants a deal, that doesn't want h tariffs and is 67 00:05:01,160 --> 00:05:08,280 Speaker 1: looking to in some sense come up within an optical victory. Yeah, Brad, 68 00:05:08,400 --> 00:05:12,840 Speaker 1: you said that probably the bigger impact on businesses will 69 00:05:12,880 --> 00:05:18,720 Speaker 1: come from China's potential retaliatory moves. What would those be, Well, 70 00:05:18,800 --> 00:05:23,280 Speaker 1: China's threaten China's already put white substantial tariffs on US 71 00:05:23,279 --> 00:05:27,800 Speaker 1: slating exports UH in response to the to the first round, 72 00:05:27,839 --> 00:05:32,240 Speaker 1: to the fifty billion in tariffs, China has threatened sixty 73 00:05:32,240 --> 00:05:36,560 Speaker 1: billion and additional tariffs if the US goes ahead with 74 00:05:36,640 --> 00:05:42,039 Speaker 1: the UH. The sixty billion presumably would be at a 75 00:05:42,080 --> 00:05:44,320 Speaker 1: slight you know, at the ten percent rate, that was 76 00:05:44,360 --> 00:05:47,920 Speaker 1: probably not prohibitive. And I would guess my sense at 77 00:05:47,960 --> 00:05:51,360 Speaker 1: least is that China's best targets were included in the 78 00:05:51,480 --> 00:05:55,680 Speaker 1: fifty billion initial list. But nonetheless there's going to be 79 00:05:57,000 --> 00:06:02,440 Speaker 1: a likely tariffs on most inputs that the usls to China, 80 00:06:03,000 --> 00:06:06,680 Speaker 1: and that at the margin, if possible, creates an intentive 81 00:06:06,760 --> 00:06:11,279 Speaker 1: to substitute away from US make goods. Brad Setzer, thank 82 00:06:11,320 --> 00:06:13,520 Speaker 1: you so much for being with us. Really a pleasure 83 00:06:13,520 --> 00:06:16,160 Speaker 1: having you as always. Broad Setser is the Steven A. 84 00:06:16,279 --> 00:06:19,040 Speaker 1: Tannenbaum Senior Fellow for International Economics of the Council of 85 00:06:19,080 --> 00:06:23,240 Speaker 1: Foreign Relations. He also is the former Deputy Assistant Secretary 86 00:06:23,279 --> 00:06:26,880 Speaker 1: for International Economic Analysis in the U. S. Treasury Department 87 00:06:26,920 --> 00:06:30,320 Speaker 1: from two thousand and eleven to two thousand and fifteen. 88 00:06:42,200 --> 00:06:45,479 Speaker 1: How do you put together a market outlook that takes 89 00:06:45,560 --> 00:06:51,600 Speaker 1: into into consequence the efforts of trade negotiators, the change 90 00:06:51,600 --> 00:06:55,240 Speaker 1: in interest rates, and also changes in the valuation of 91 00:06:55,279 --> 00:06:57,680 Speaker 1: different equity sectors. Well, one thing you do is you 92 00:06:57,800 --> 00:07:01,039 Speaker 1: turn to Denise Chisholm, the sector strategy just in portfolio 93 00:07:01,080 --> 00:07:05,800 Speaker 1: manager for for Fidelity Investments based in Boston, but joins 94 00:07:05,839 --> 00:07:08,000 Speaker 1: us here in our eleven trio studios. Den He's thanks 95 00:07:08,000 --> 00:07:11,720 Speaker 1: for coming in. Much appreciated. Now, Um I was thinking 96 00:07:11,760 --> 00:07:15,160 Speaker 1: about your approach and I thought, wow, okay, So here's 97 00:07:15,160 --> 00:07:19,240 Speaker 1: like a checklist. You take a variety of different measures 98 00:07:19,680 --> 00:07:22,160 Speaker 1: and you put them all together to try to get 99 00:07:22,200 --> 00:07:25,560 Speaker 1: some kind of holistic vision of the market, and then 100 00:07:25,720 --> 00:07:29,840 Speaker 1: from that you extract what you believe to be tradeable ideas. 101 00:07:29,960 --> 00:07:32,119 Speaker 1: And if you could just explain some of the things 102 00:07:32,120 --> 00:07:34,200 Speaker 1: that go into your thinking, yeah, I think to boil 103 00:07:34,240 --> 00:07:38,240 Speaker 1: it down, I do historical probability analysis on data, right, 104 00:07:38,280 --> 00:07:41,960 Speaker 1: so constantly asking the question, hey, whatever theory you have, 105 00:07:42,120 --> 00:07:46,280 Speaker 1: whatever thesis you have, is that really true historically? And 106 00:07:46,320 --> 00:07:48,720 Speaker 1: if you ask that enough times and you do the 107 00:07:48,760 --> 00:07:51,880 Speaker 1: work enough times, that can actually inform your investment opinion 108 00:07:52,120 --> 00:07:55,120 Speaker 1: only you overall market and then on individual equity sectors. 109 00:07:55,200 --> 00:07:57,440 Speaker 1: All right, So let's get down to what's going on today. 110 00:07:57,640 --> 00:08:01,000 Speaker 1: We see a little bit of softness light of the 111 00:08:01,040 --> 00:08:04,320 Speaker 1: headline saying that President Trump is set to impose tem 112 00:08:04,360 --> 00:08:07,440 Speaker 1: percent tariffs and two billion dollars additional goods from China. 113 00:08:07,880 --> 00:08:10,880 Speaker 1: The markets aren't down nearly as much as I would expect, 114 00:08:10,960 --> 00:08:14,320 Speaker 1: given the fact that that seems like a lot. It's 115 00:08:14,560 --> 00:08:17,320 Speaker 1: take again, like using historical data to inform a view 116 00:08:17,400 --> 00:08:20,080 Speaker 1: rather than just giving you my opinion, this is fascinating. 117 00:08:20,160 --> 00:08:23,480 Speaker 1: So if you plot world trade and nominal dollars and 118 00:08:23,520 --> 00:08:25,000 Speaker 1: you look at it on a year in your basis, 119 00:08:25,000 --> 00:08:28,080 Speaker 1: we have that data going back to publicly available data, 120 00:08:28,280 --> 00:08:31,360 Speaker 1: and you said, I have perfect foresight and I know 121 00:08:31,480 --> 00:08:34,000 Speaker 1: that it's going to contract, which is a bottom quartile event. 122 00:08:34,360 --> 00:08:36,600 Speaker 1: You would be shocked to see that if I quartile 123 00:08:36,679 --> 00:08:39,760 Speaker 1: that out, that's actually the highest probability of an advancing 124 00:08:39,800 --> 00:08:43,040 Speaker 1: equity market with the highest average returns. So that to 125 00:08:43,160 --> 00:08:46,320 Speaker 1: me means one of two things. One is that the 126 00:08:46,320 --> 00:08:51,720 Speaker 1: equity market actually discounts this in advance, or two that 127 00:08:51,840 --> 00:08:56,160 Speaker 1: the backdrop is actually more important and can overwhelm the 128 00:08:56,240 --> 00:09:00,319 Speaker 1: individual univariate variable of global trade, which I think we 129 00:09:00,400 --> 00:09:04,520 Speaker 1: have both situations going on currently. When you said backdrop, 130 00:09:04,960 --> 00:09:07,520 Speaker 1: what do you mean by that? That backdrop, now that's 131 00:09:07,520 --> 00:09:10,840 Speaker 1: a great question. By backdrop, I mean the corporate profit recovery. 132 00:09:11,120 --> 00:09:13,760 Speaker 1: So I think we are in year two of what 133 00:09:13,880 --> 00:09:16,720 Speaker 1: could be a four to six year long durable profit 134 00:09:16,760 --> 00:09:19,400 Speaker 1: recovery because we had a contraction on a global earning 135 00:09:19,440 --> 00:09:23,920 Speaker 1: basis in and you're seeing now estimates do something that 136 00:09:23,960 --> 00:09:27,040 Speaker 1: they rarely do historically, which usually as you start the year, 137 00:09:27,120 --> 00:09:29,360 Speaker 1: they start out very optimistic and then over the course 138 00:09:29,400 --> 00:09:32,000 Speaker 1: of the year they come down. You're seeing something that 139 00:09:32,080 --> 00:09:34,920 Speaker 1: you're seeing them do a hook up, right, So that 140 00:09:34,960 --> 00:09:38,240 Speaker 1: tells you two things. One is that analysts are underestimating 141 00:09:38,280 --> 00:09:41,800 Speaker 1: the durability this recovery and underestimating earnings. And to it 142 00:09:41,840 --> 00:09:45,440 Speaker 1: means the valuation levels that we're seeing all those forward 143 00:09:45,520 --> 00:09:48,920 Speaker 1: numbers are actually more solidified, meaning that now at sixteen 144 00:09:49,040 --> 00:09:53,000 Speaker 1: times next year's earnings were at bottom quartile valuation levels. 145 00:09:53,000 --> 00:09:56,360 Speaker 1: Since when you look at historical data, how much do 146 00:09:56,400 --> 00:09:59,720 Speaker 1: you factor in other countries and what's going on with 147 00:10:00,080 --> 00:10:03,280 Speaker 1: um other than just the United States? Because there's been 148 00:10:03,320 --> 00:10:06,880 Speaker 1: this existential question hanging over the markets, how much longer 149 00:10:06,920 --> 00:10:09,280 Speaker 1: can the US diverge from the rest of the world. 150 00:10:09,280 --> 00:10:11,559 Speaker 1: It seems to be in a worse position. No, I 151 00:10:11,600 --> 00:10:14,000 Speaker 1: think that that's definitely true. So I do look on 152 00:10:14,000 --> 00:10:16,319 Speaker 1: a global basis, right, So I look at Europe, I 153 00:10:16,360 --> 00:10:18,679 Speaker 1: look at Japan, and I look at emerging markets and 154 00:10:18,679 --> 00:10:21,080 Speaker 1: what you see historically and again it can always be 155 00:10:21,200 --> 00:10:23,640 Speaker 1: that this time is different. But what you see historically 156 00:10:23,720 --> 00:10:27,120 Speaker 1: is that the US being strong drags other countries and 157 00:10:27,200 --> 00:10:31,640 Speaker 1: regions up, meaning it lowers the probability of a crisis 158 00:10:31,679 --> 00:10:34,200 Speaker 1: that comes back to the U S stock market. So 159 00:10:34,240 --> 00:10:37,560 Speaker 1: you can actually see this divergence on a relative basis 160 00:10:37,600 --> 00:10:40,200 Speaker 1: for quite some time. Speak a little bit more if 161 00:10:40,200 --> 00:10:43,960 Speaker 1: you can about corporate profits. So if you look at 162 00:10:44,000 --> 00:10:47,480 Speaker 1: that recession that we saw in two thousand sixteen, right, 163 00:10:48,760 --> 00:10:51,400 Speaker 1: what I think fascinates me is that most people think, oh, 164 00:10:51,440 --> 00:10:53,600 Speaker 1: it wasn't that big of a deal. It was just 165 00:10:53,720 --> 00:10:56,199 Speaker 1: really energy and materials. And then actually when you look 166 00:10:56,240 --> 00:10:58,480 Speaker 1: at the data, that wasn't the case. At the then 167 00:10:59,320 --> 00:11:01,840 Speaker 1: ten gigs sectors that we saw at the time, you 168 00:11:01,920 --> 00:11:05,480 Speaker 1: had a median stock earning this contraction in seven out 169 00:11:05,520 --> 00:11:08,480 Speaker 1: of those ten sectors. So it was very diffuse, and 170 00:11:08,520 --> 00:11:11,200 Speaker 1: actually on a diffusion basis, it was as much of 171 00:11:11,240 --> 00:11:16,480 Speaker 1: a contraction as we saw in the recession of So 172 00:11:16,520 --> 00:11:18,760 Speaker 1: if you just step back and say, forget the corporate 173 00:11:18,760 --> 00:11:21,480 Speaker 1: tax reform that we put in place, let's just look 174 00:11:21,480 --> 00:11:24,559 Speaker 1: at what an average corporate profit recovery looks like. You 175 00:11:24,679 --> 00:11:27,440 Speaker 1: actually see that it lasts four years. Now, the range 176 00:11:27,480 --> 00:11:29,560 Speaker 1: is pretty wide. It goes between two and six. But 177 00:11:29,640 --> 00:11:32,200 Speaker 1: then of the forty five variables I looked at, and 178 00:11:32,200 --> 00:11:33,760 Speaker 1: it's not all the variables in the world, but it's 179 00:11:33,760 --> 00:11:35,600 Speaker 1: the forty five one. It doesn't correlate to the FED 180 00:11:35,679 --> 00:11:39,199 Speaker 1: raising interest rates. It actually correlates to the starting point 181 00:11:39,240 --> 00:11:42,760 Speaker 1: in bank credit, and that's delinquencies a percentaive overall loans 182 00:11:43,040 --> 00:11:45,480 Speaker 1: bad bad assets as a percentage of assets. However you'd 183 00:11:45,520 --> 00:11:48,920 Speaker 1: like to to quantify it just thirty seconds. I'm curious 184 00:11:48,920 --> 00:11:52,000 Speaker 1: from your perspective, do you think that the tax reform 185 00:11:52,040 --> 00:11:55,520 Speaker 1: brought forward profits and that they're likely to dwindle out 186 00:11:55,559 --> 00:11:57,440 Speaker 1: and that this could be a different period of time 187 00:11:57,440 --> 00:12:00,760 Speaker 1: than the past because of that. So again, there's not 188 00:12:00,840 --> 00:12:03,400 Speaker 1: much data on this. We have six instances in history, right, 189 00:12:03,440 --> 00:12:07,160 Speaker 1: but what you see is exactly history saying confirming what 190 00:12:07,240 --> 00:12:09,440 Speaker 1: we have seen, which is corporate profits turned the year 191 00:12:09,520 --> 00:12:14,240 Speaker 1: before corporate tax reform hits because of that investor optimism 192 00:12:14,360 --> 00:12:18,040 Speaker 1: or I should say that CEO optimism, and it becomes sticky. Right, 193 00:12:18,080 --> 00:12:21,000 Speaker 1: So in history you don't historically see the dwindling, it 194 00:12:21,000 --> 00:12:24,160 Speaker 1: actually sticks really really interesting. Thank you so much for 195 00:12:24,200 --> 00:12:26,960 Speaker 1: being with us, Thanks for having me. Denise Chisholm. She 196 00:12:27,200 --> 00:12:29,679 Speaker 1: is a sector at strategist at Fidelity. Taking a look 197 00:12:29,720 --> 00:12:32,800 Speaker 1: at those historical data points and putting them all together 198 00:12:33,040 --> 00:12:37,079 Speaker 1: saying that perhaps analysts are underestimating just how strong it's 199 00:12:37,120 --> 00:12:40,160 Speaker 1: recovery will be and how long it will last. Him 200 00:12:40,160 --> 00:12:43,839 Speaker 1: really interesting. Yes, that's a bulk case for stocks. Yeah, 201 00:12:43,880 --> 00:12:46,439 Speaker 1: despite the calls for a recession from a number of 202 00:12:46,480 --> 00:13:02,680 Speaker 1: different firms, I want to turn our focus to self 203 00:13:02,880 --> 00:13:05,040 Speaker 1: driving cars. A lot of people thought that this would 204 00:13:05,080 --> 00:13:09,400 Speaker 1: be the future of driving and the car sharing economy. 205 00:13:09,480 --> 00:13:12,920 Speaker 1: But there's a major problem. They can't handle rain or 206 00:13:13,000 --> 00:13:16,360 Speaker 1: sleet or snow. Joining us now, Kyle Stock, Senior correspondent 207 00:13:16,400 --> 00:13:19,320 Speaker 1: for Bloomberg News. I thought your story was fascinating, Kyle, 208 00:13:19,640 --> 00:13:22,280 Speaker 1: thank you so much for joining us. So, just how 209 00:13:23,240 --> 00:13:28,560 Speaker 1: enable unable are these cars able to handle weather? Yeah, 210 00:13:28,679 --> 00:13:33,520 Speaker 1: it's it's tricky. They're making very slow progress on this front. Um, 211 00:13:33,559 --> 00:13:37,120 Speaker 1: there's other things that people thought were going to be 212 00:13:37,200 --> 00:13:42,120 Speaker 1: major stumbling blocks, like epics or other human drivers or algorithms. Um, 213 00:13:42,240 --> 00:13:44,840 Speaker 1: those are all approving a little bit more easy to 214 00:13:44,920 --> 00:13:48,920 Speaker 1: deal with. So, Kyle, let's get this straight. When the 215 00:13:48,960 --> 00:13:54,440 Speaker 1: weather is perfect and there's no traffic, driverless automobiles might 216 00:13:54,480 --> 00:13:59,920 Speaker 1: actually work just fine. But at those moments when it's cloudy, rain, 217 00:14:00,000 --> 00:14:03,080 Speaker 1: any snowy, or there's a lot of traffic or a 218 00:14:03,080 --> 00:14:07,760 Speaker 1: lot of congestion, that's when there might be trouble exactly. 219 00:14:08,000 --> 00:14:11,079 Speaker 1: I mean, there's a reason why they're testing all these 220 00:14:11,120 --> 00:14:14,560 Speaker 1: things in Phoenix for the most Partum, it's pretty sunny 221 00:14:14,559 --> 00:14:18,600 Speaker 1: most of the time. Oh my goodness. I mean, honestly, 222 00:14:18,920 --> 00:14:21,560 Speaker 1: on one hand, it's sort of shocking that this is 223 00:14:21,600 --> 00:14:23,480 Speaker 1: such a big obstacle at a time when so many 224 00:14:23,480 --> 00:14:26,600 Speaker 1: people are considering in a very serious way a mass 225 00:14:26,640 --> 00:14:29,080 Speaker 1: adoption of self driving vehicles and a lot of money 226 00:14:29,120 --> 00:14:31,960 Speaker 1: being thrown at this topic. Absolutely, I want to talk 227 00:14:32,000 --> 00:14:35,320 Speaker 1: about where the opportunities are given that this problem is 228 00:14:35,720 --> 00:14:38,160 Speaker 1: definitely being worked on by a lot of startups with 229 00:14:38,200 --> 00:14:41,360 Speaker 1: a lot of sensor companies that are looking for ways 230 00:14:41,440 --> 00:14:44,320 Speaker 1: to address it. Can you can you talk to that please? Yeah. 231 00:14:44,360 --> 00:14:46,560 Speaker 1: I mean there's there's definitely a hardware play and a 232 00:14:46,600 --> 00:14:49,800 Speaker 1: software play, so you know, the engineers are tuning the 233 00:14:49,840 --> 00:14:53,840 Speaker 1: software to sort of help help the sensors make better 234 00:14:53,880 --> 00:14:57,960 Speaker 1: sense of the world when there's rain or fog or snow. Um. 235 00:14:58,080 --> 00:15:01,200 Speaker 1: But then they're also you know, building these these sensors. 236 00:15:02,000 --> 00:15:06,760 Speaker 1: Way Moo, the leading self driving company, is build its 237 00:15:06,800 --> 00:15:10,280 Speaker 1: own sensors. So they say they're iterating every time they 238 00:15:10,360 --> 00:15:13,040 Speaker 1: make a new version of the product. And one of 239 00:15:13,080 --> 00:15:14,720 Speaker 1: the companies I talked to is out of m i 240 00:15:14,800 --> 00:15:19,040 Speaker 1: T called Waves Sense, and they have an entirely new approach. 241 00:15:19,080 --> 00:15:25,560 Speaker 1: They're doing a ground penetrating radar literally looking under the road, um, 242 00:15:25,600 --> 00:15:29,120 Speaker 1: to keep the car on track so they don't need 243 00:15:29,160 --> 00:15:31,480 Speaker 1: to worry about whatever is happening on top of the 244 00:15:31,520 --> 00:15:35,760 Speaker 1: road in terms of weather. Kyle disabused me of my 245 00:15:35,920 --> 00:15:38,040 Speaker 1: idea here, But I don't think the issue has to 246 00:15:38,120 --> 00:15:40,720 Speaker 1: do with driverless automobiles. It has to do with traffic. 247 00:15:41,400 --> 00:15:43,360 Speaker 1: If you're if they if you're able to drive in 248 00:15:43,440 --> 00:15:47,560 Speaker 1: traffic free conditions, driving is kind of fun, isn't it. 249 00:15:48,080 --> 00:15:50,920 Speaker 1: It sure is? Yeah, And well, the other interesting thing 250 00:15:51,040 --> 00:15:54,560 Speaker 1: is I think we're almost holding sort of these robot 251 00:15:54,640 --> 00:15:58,640 Speaker 1: vehicles to a higher standard. We expect them to be 252 00:15:58,640 --> 00:16:01,760 Speaker 1: better than human drivers. And there's a lot of weather 253 00:16:01,840 --> 00:16:05,280 Speaker 1: when I'm not comfortable driving. I won't speak for you, Pim, 254 00:16:05,320 --> 00:16:08,320 Speaker 1: but um, we want them to get us there, and 255 00:16:08,520 --> 00:16:11,840 Speaker 1: you know, yeah, right, And the idea is, you know, 256 00:16:11,880 --> 00:16:15,240 Speaker 1: when it's inclement weather, slow down. Well, hold on a second, 257 00:16:15,360 --> 00:16:17,280 Speaker 1: I take a step back here, because your story said 258 00:16:17,280 --> 00:16:19,400 Speaker 1: that even a dusting of snow would be a problem, 259 00:16:19,440 --> 00:16:22,040 Speaker 1: and anything more than that, So I think that that 260 00:16:22,080 --> 00:16:23,920 Speaker 1: would be just fine for you, Pim, to go out 261 00:16:24,000 --> 00:16:26,200 Speaker 1: driving in a little bit more than a dusting of snow. 262 00:16:26,760 --> 00:16:29,480 Speaker 1: But I do want to talk about the incredible investment, 263 00:16:29,520 --> 00:16:32,040 Speaker 1: as Pim mentioned earlier that a lot of major car 264 00:16:32,120 --> 00:16:35,920 Speaker 1: companies are making in autonomous vehicles. If you have such 265 00:16:35,960 --> 00:16:38,880 Speaker 1: fundamental problems as this at a time when people do 266 00:16:39,040 --> 00:16:42,160 Speaker 1: hold robots at a higher standard, does it suggest that 267 00:16:42,200 --> 00:16:44,640 Speaker 1: perhaps our hopes are a little bit further along than 268 00:16:44,680 --> 00:16:47,960 Speaker 1: the actuality when it comes to these cars. Yeah, I 269 00:16:47,960 --> 00:16:50,560 Speaker 1: think that's fair to say. But it's just the opportunity 270 00:16:50,600 --> 00:16:54,040 Speaker 1: to market is so huge. Um, you know the ride 271 00:16:54,320 --> 00:16:59,120 Speaker 1: they're talking about a seven trillion dollar rideshare business that. Um, 272 00:16:59,200 --> 00:17:01,720 Speaker 1: you know, these company Ace and the the investors behind 273 00:17:01,760 --> 00:17:05,240 Speaker 1: them are dreaming big. So even if they're just even 274 00:17:05,280 --> 00:17:08,760 Speaker 1: if they can operate only in a perfect sunny day, 275 00:17:08,800 --> 00:17:12,679 Speaker 1: it still makes sense to really be be charging for this. 276 00:17:12,840 --> 00:17:19,080 Speaker 1: If you're a company like Ford or Uber or Weymo. Um, Kyle, 277 00:17:19,119 --> 00:17:21,920 Speaker 1: I would just say all people who have been stuck 278 00:17:22,119 --> 00:17:25,359 Speaker 1: in one of those automated people movers at an airport, 279 00:17:25,440 --> 00:17:28,479 Speaker 1: please raise your hand at one point or other, listening 280 00:17:28,520 --> 00:17:33,040 Speaker 1: to the to the music play over and over again. Yeah, 281 00:17:33,280 --> 00:17:35,680 Speaker 1: this is is Do you feel that there's gonna be 282 00:17:35,720 --> 00:17:37,600 Speaker 1: a shakeout from this? I mean, you can use a 283 00:17:37,600 --> 00:17:40,760 Speaker 1: lot of the technology in cars that are driven by 284 00:17:40,840 --> 00:17:44,040 Speaker 1: human beings, of course, whether that's blind spot warning or 285 00:17:44,760 --> 00:17:48,280 Speaker 1: you know, breaking technology, which is all great, But I mean, 286 00:17:48,280 --> 00:17:49,679 Speaker 1: do you think that people are going to sort of, 287 00:17:49,720 --> 00:17:51,679 Speaker 1: as Leasa said, kind of pair back a little of 288 00:17:51,720 --> 00:17:56,560 Speaker 1: this science fiction. I think the timeline will be adjusted. Um. 289 00:17:56,600 --> 00:17:59,520 Speaker 1: I think rather than a shakeout, though, what you're going 290 00:17:59,560 --> 00:18:01,800 Speaker 1: to see this is not something we've talked about a lot, 291 00:18:02,320 --> 00:18:06,880 Speaker 1: is a rollout based on geography. So the irony here 292 00:18:06,960 --> 00:18:08,879 Speaker 1: is that some of the tech centers of the world, 293 00:18:09,359 --> 00:18:13,600 Speaker 1: San Francisco and Seattle specifically, might be the last places 294 00:18:13,640 --> 00:18:16,960 Speaker 1: to get self driving vehicles. You're going to see them 295 00:18:17,000 --> 00:18:20,639 Speaker 1: in the Sunbelt, You're gonna see him in Florida. Um. 296 00:18:20,720 --> 00:18:24,120 Speaker 1: One of the analysts I spoke with said, basically, when 297 00:18:24,119 --> 00:18:27,040 Speaker 1: they these cars do show up in a place like Boston, 298 00:18:27,160 --> 00:18:31,040 Speaker 1: they'll be bespoke versions, so they'll have twice as many sensors, 299 00:18:31,160 --> 00:18:35,199 Speaker 1: will be totally over over engineered just to deal with 300 00:18:35,240 --> 00:18:38,840 Speaker 1: the heavy weather in a way that they won't be um, 301 00:18:38,960 --> 00:18:42,720 Speaker 1: you know in uh in Georgia. Right, all right, well, 302 00:18:42,720 --> 00:18:45,520 Speaker 1: we gotta leave it there, but thanks very much. Kyle Stock, 303 00:18:45,560 --> 00:18:49,320 Speaker 1: our senior correspondent for Bloomberg News, talking about self driving 304 00:18:49,359 --> 00:18:52,240 Speaker 1: automobiles and whether they can really handle the rain, the 305 00:18:52,359 --> 00:19:08,399 Speaker 1: sleet or the snow. Will find out. Oil prices have 306 00:19:08,600 --> 00:19:14,240 Speaker 1: been rather stable considering the backdrop of hurricanes and typhoons 307 00:19:14,280 --> 00:19:18,119 Speaker 1: and other situations, but perhaps some traitors are not taking 308 00:19:18,160 --> 00:19:22,280 Speaker 1: into account. November four, that is an important date when 309 00:19:22,480 --> 00:19:26,080 Speaker 1: sanctions will go into effect on Iran. Here to talk 310 00:19:26,119 --> 00:19:29,240 Speaker 1: about that, Dr Ellen at Wald, president of Transversal Consulting 311 00:19:29,440 --> 00:19:31,640 Speaker 1: and a non residency your fellow at the Atlantic Council's 312 00:19:31,680 --> 00:19:34,760 Speaker 1: Global Energy Center, as well as Toby Harshaw, editor at 313 00:19:34,880 --> 00:19:39,320 Speaker 1: Bloomberg Opinion. Uh. Dr Wald, let's start with you. Why 314 00:19:39,440 --> 00:19:43,199 Speaker 1: is November four such an important date? November four is 315 00:19:43,359 --> 00:19:46,080 Speaker 1: d date at which these sanctions are going to go 316 00:19:46,160 --> 00:19:49,119 Speaker 1: into effect, and now that it's the middle of September, 317 00:19:49,640 --> 00:19:52,320 Speaker 1: we are really looking to see how the dominoes are 318 00:19:52,320 --> 00:19:55,040 Speaker 1: going to fall when it comes to the sanctions. Which 319 00:19:55,040 --> 00:19:58,920 Speaker 1: countries are actually going to stop importing Iranian oil and 320 00:19:59,080 --> 00:20:02,080 Speaker 1: which countries are planning to continue and right now it 321 00:20:02,160 --> 00:20:06,240 Speaker 1: looks like China, India, and Turkey are still importing lots 322 00:20:06,240 --> 00:20:09,600 Speaker 1: of Iranian oil. But also surprisingly we now have data 323 00:20:09,680 --> 00:20:14,280 Speaker 1: that shows that Italy and Spain and possibly even Greece 324 00:20:14,520 --> 00:20:18,760 Speaker 1: are still importing oil from Iran even though it's now 325 00:20:18,840 --> 00:20:22,399 Speaker 1: the middle of September. Toby Harshaw, I want you to 326 00:20:22,440 --> 00:20:24,840 Speaker 1: come in on this topic of Iran, but ed in 327 00:20:25,280 --> 00:20:28,560 Speaker 1: what's going on with their economy. About six of the 328 00:20:28,560 --> 00:20:33,359 Speaker 1: Iranian economy is centrally planned. It's basically dominated by the 329 00:20:33,400 --> 00:20:37,719 Speaker 1: oil and gas industry. Yeah, and it's dominated by UH 330 00:20:38,720 --> 00:20:44,000 Speaker 1: UH the Iranian Guards, which are supposedly a military force, 331 00:20:44,040 --> 00:20:47,280 Speaker 1: but they become the most dominant force in the economy. UM. 332 00:20:47,359 --> 00:20:52,200 Speaker 1: There's no overestimating the effect that oil has on their economy. 333 00:20:52,280 --> 00:20:55,080 Speaker 1: The question is with their exports, how much of that 334 00:20:55,160 --> 00:20:58,439 Speaker 1: money they can bring back UH. Last time, with the 335 00:20:58,480 --> 00:21:02,040 Speaker 1: sanctions UH, the money was held in escrow by countries 336 00:21:02,080 --> 00:21:05,159 Speaker 1: like India and China, and Iran could only use the 337 00:21:05,160 --> 00:21:08,840 Speaker 1: money to to buy products in those countries and have 338 00:21:08,920 --> 00:21:11,439 Speaker 1: them sent back. And they were actually buying products in 339 00:21:11,520 --> 00:21:14,560 Speaker 1: China that they didn't even really need. So as Allen 340 00:21:14,600 --> 00:21:16,840 Speaker 1: will tell us that's one of the big questions about 341 00:21:16,880 --> 00:21:20,320 Speaker 1: how these sanctions are reinstated this time around. So Ellen 342 00:21:20,560 --> 00:21:22,879 Speaker 1: just to talk a little bit about plugging the holes 343 00:21:22,920 --> 00:21:26,840 Speaker 1: and sort of creating a more airtight system of sanctions. 344 00:21:27,240 --> 00:21:31,480 Speaker 1: I'm wondering if the US administration can do that successfully, 345 00:21:31,520 --> 00:21:34,159 Speaker 1: what would the effect be on the oil market, on 346 00:21:34,200 --> 00:21:36,640 Speaker 1: the price of crude in a way that perhaps people 347 00:21:36,680 --> 00:21:40,080 Speaker 1: aren't factoring in right now. Well, if the US can 348 00:21:40,240 --> 00:21:44,240 Speaker 1: really enforce these sanctions to the maximum to plug these holes. 349 00:21:44,280 --> 00:21:48,600 Speaker 1: There have been holes in terms of Iran's exporting of 350 00:21:48,800 --> 00:21:51,160 Speaker 1: content thates, which is a very light type of crude 351 00:21:51,160 --> 00:21:55,560 Speaker 1: oil that some people see as or or classify as 352 00:21:55,560 --> 00:21:58,439 Speaker 1: crude oil and other people don't technically classify it as 353 00:21:58,440 --> 00:22:01,119 Speaker 1: crude oil. But if they can ug all of these holes, 354 00:22:01,160 --> 00:22:05,320 Speaker 1: if they can really get the Iranian exports down, I 355 00:22:05,320 --> 00:22:08,600 Speaker 1: would say, buy one point five million barrels wave they 356 00:22:08,600 --> 00:22:11,000 Speaker 1: can eliminate that from the market, then we could really 357 00:22:11,040 --> 00:22:14,439 Speaker 1: be in for some serious tightening in the oil market, 358 00:22:14,680 --> 00:22:17,480 Speaker 1: mostly because at the same time we're also seeing continued 359 00:22:17,560 --> 00:22:22,119 Speaker 1: drops from Venezuela. US production isn't increasing at quite the 360 00:22:22,240 --> 00:22:24,040 Speaker 1: rate that we thought it was going to be and 361 00:22:24,080 --> 00:22:27,560 Speaker 1: so the question is really can Russia and Saudi Arabia, 362 00:22:27,640 --> 00:22:30,119 Speaker 1: the two countries that have the most spare capacity, can 363 00:22:30,160 --> 00:22:34,520 Speaker 1: they really increase to combat these drops. And then the 364 00:22:34,560 --> 00:22:37,480 Speaker 1: other question is if they can, will they And that's 365 00:22:37,480 --> 00:22:42,000 Speaker 1: all going to come down to that December three Opeque meeting. 366 00:22:42,680 --> 00:22:44,439 Speaker 1: So in other words, if they don't, that means the 367 00:22:44,480 --> 00:22:48,720 Speaker 1: price of crude could rise substantially. It could rise substantially, 368 00:22:48,720 --> 00:22:52,240 Speaker 1: But there's there's also the speculation effect. So even if 369 00:22:52,280 --> 00:22:55,439 Speaker 1: we we do have enough crude oil to go around, 370 00:22:55,720 --> 00:22:58,960 Speaker 1: there's always this effect of people thinking that we don't 371 00:22:59,000 --> 00:23:01,920 Speaker 1: necessarily have an enough and that can push the prices up. 372 00:23:02,080 --> 00:23:04,560 Speaker 1: There's also the matter of the right type of crude oil. 373 00:23:04,800 --> 00:23:08,240 Speaker 1: Do we have enough heavy crude coming in? That's really 374 00:23:08,320 --> 00:23:10,840 Speaker 1: kind of a hot commodity now because there's so much 375 00:23:11,320 --> 00:23:13,680 Speaker 1: there's kind of an overflow of light crude coming out 376 00:23:13,800 --> 00:23:17,000 Speaker 1: from the US and and from from fracking, So we 377 00:23:17,040 --> 00:23:18,879 Speaker 1: need to have the right type of crude. So crude 378 00:23:19,119 --> 00:23:22,119 Speaker 1: quality matters, as people like to say, But there's also 379 00:23:22,200 --> 00:23:25,840 Speaker 1: the issue of um demand and what one of the 380 00:23:25,880 --> 00:23:29,960 Speaker 1: interesting things on the horizon is that OPEC has recently 381 00:23:30,000 --> 00:23:33,720 Speaker 1: revised its demand figures, So they think that demand is 382 00:23:33,720 --> 00:23:36,760 Speaker 1: actually going to um to be less than they thought 383 00:23:36,920 --> 00:23:41,040 Speaker 1: in en and that could actually kind of arrest some 384 00:23:41,200 --> 00:23:44,840 Speaker 1: of the higher crew prices. Toby, maybe just to add 385 00:23:44,880 --> 00:23:48,360 Speaker 1: your thoughts about what's happening to the Iranian economy as 386 00:23:48,400 --> 00:23:53,240 Speaker 1: a result of these UH sanctions and additional sanctions, I 387 00:23:53,320 --> 00:23:56,359 Speaker 1: just want to note it's about eight two million people, 388 00:23:56,640 --> 00:24:02,160 Speaker 1: that's the population of Iran and unemployment. If you look 389 00:24:02,160 --> 00:24:05,800 Speaker 1: at unemployment levels, maybe fifteen to twenty nine, about a 390 00:24:05,960 --> 00:24:09,960 Speaker 1: quarter of the potential workforce is out of work. Yeah, 391 00:24:10,000 --> 00:24:14,400 Speaker 1: and it always depends who's who's compiling those statistics. Uh. 392 00:24:14,840 --> 00:24:18,080 Speaker 1: If anything, that's probably higher. The inflation statistic put out 393 00:24:18,160 --> 00:24:21,200 Speaker 1: by the Iranian government is an absolute joke. Um, it's 394 00:24:21,359 --> 00:24:24,720 Speaker 1: vastly higher than whatever they're going to say. So the 395 00:24:24,840 --> 00:24:30,920 Speaker 1: combination of high inflation, high unemployment, and now additional sanctions, 396 00:24:31,440 --> 00:24:36,359 Speaker 1: will it have the intended effect on the Iranian government? UM? 397 00:24:36,600 --> 00:24:38,320 Speaker 1: I don't see it as having much of an effect 398 00:24:38,320 --> 00:24:41,400 Speaker 1: at all. Um. I don't think they have much choice 399 00:24:41,800 --> 00:24:45,160 Speaker 1: except to, uh, you know, to bear it, to buckle up, 400 00:24:45,200 --> 00:24:48,119 Speaker 1: and and it's going to happen. Um. The it's a 401 00:24:48,119 --> 00:24:51,800 Speaker 1: political gamble on the part of the government. Um, people 402 00:24:51,800 --> 00:24:55,200 Speaker 1: are unhappy about it, but then um, they can always 403 00:24:55,280 --> 00:24:58,640 Speaker 1: use further hardship as another reason that America is still 404 00:24:58,680 --> 00:25:01,720 Speaker 1: the great Satan um and and you know, appeal to 405 00:25:01,760 --> 00:25:04,960 Speaker 1: patriotism and things like that, Toby. Are there enough people 406 00:25:05,119 --> 00:25:09,720 Speaker 1: in the administration with knowledge of the Iran situation who 407 00:25:09,760 --> 00:25:12,560 Speaker 1: could bridge some of these loopholes and sort of plug 408 00:25:12,600 --> 00:25:15,159 Speaker 1: them up and make it more tight. Yeah. Absolutely. This 409 00:25:15,240 --> 00:25:17,760 Speaker 1: is professional staff for the most part that deals with it. 410 00:25:18,200 --> 00:25:20,440 Speaker 1: It's the Treasury Department that's in charge. There's a lot 411 00:25:20,440 --> 00:25:24,320 Speaker 1: of Treasury lifers, um, long term employees, were very very 412 00:25:24,480 --> 00:25:26,680 Speaker 1: very savvy about this, you know, And this is one 413 00:25:26,680 --> 00:25:29,480 Speaker 1: of those instances in which you know, to my mind anyway, 414 00:25:29,480 --> 00:25:33,199 Speaker 1: the Trump administration is is pretty set on doing the 415 00:25:33,280 --> 00:25:37,040 Speaker 1: right thing, ellen Wald. Are there any examples that you 416 00:25:37,160 --> 00:25:40,640 Speaker 1: can point to that show us that sanctions actually achieve 417 00:25:40,720 --> 00:25:45,360 Speaker 1: their goal? Well, that's that's the big question here. And 418 00:25:45,720 --> 00:25:47,840 Speaker 1: you know, some people will You can always find people 419 00:25:47,840 --> 00:25:49,640 Speaker 1: who will argue that they do, and you can also 420 00:25:49,680 --> 00:25:52,960 Speaker 1: find people who will argue that they won't. And many 421 00:25:52,960 --> 00:25:55,800 Speaker 1: people say that the sanctions did achieve their goal when 422 00:25:55,840 --> 00:25:58,359 Speaker 1: they led to the negotiations for the initial j c 423 00:25:58,480 --> 00:26:01,240 Speaker 1: p O. I at thing though with regard to the 424 00:26:01,280 --> 00:26:04,760 Speaker 1: Iranian economy, and that's the the Iranian economy was not 425 00:26:04,800 --> 00:26:08,200 Speaker 1: doing well even before these sanctions were instituted. They've they've 426 00:26:08,240 --> 00:26:10,439 Speaker 1: really kind of shot themselves in the foot in a 427 00:26:10,480 --> 00:26:15,760 Speaker 1: sense in Iran um politically and economically, particularly with respect 428 00:26:15,760 --> 00:26:19,399 Speaker 1: to the oil industry, because they have very very deep 429 00:26:19,960 --> 00:26:26,280 Speaker 1: and institutionalized um distrust of foreign oil companies that could 430 00:26:26,320 --> 00:26:29,800 Speaker 1: have come in and really helped get their oil industry going. Yes, 431 00:26:29,800 --> 00:26:32,080 Speaker 1: there was a lot of fear on the part of 432 00:26:32,080 --> 00:26:34,359 Speaker 1: foreign oil companies, but there were some who were really 433 00:26:34,359 --> 00:26:36,560 Speaker 1: were willing to come into tal was one, but the 434 00:26:36,600 --> 00:26:40,680 Speaker 1: Iranian UH kind of ideology makes it very very difficult 435 00:26:40,720 --> 00:26:44,040 Speaker 1: for that to happen. So they were going down a 436 00:26:44,119 --> 00:26:47,560 Speaker 1: bad path even before these sanctions. I want to thank 437 00:26:47,600 --> 00:26:50,200 Speaker 1: you both very much for joining us. Dr Ellen Walled 438 00:26:50,320 --> 00:26:54,720 Speaker 1: is the president of Transversal Consulting, a nonresident Senior Fellow 439 00:26:54,800 --> 00:26:58,760 Speaker 1: at the Atlantic Council's Global Energy Center, and our thanks 440 00:26:58,800 --> 00:27:06,040 Speaker 1: also to Toby hart Shaw, editor for Bloomberg Opinion. Thanks 441 00:27:06,080 --> 00:27:08,720 Speaker 1: for listening to the Bloomberg P and L podcast. You 442 00:27:08,760 --> 00:27:12,560 Speaker 1: can subscribe and listen to interviews at Apple Podcasts, SoundCloud, 443 00:27:12,640 --> 00:27:16,120 Speaker 1: or whatever podcast platform you prefer. I'm pim Fox. I'm 444 00:27:16,160 --> 00:27:19,680 Speaker 1: on Twitter at pim Fox. I'm on Twitter at Lisa 445 00:27:19,720 --> 00:27:22,879 Speaker 1: Abramowits one before the podcast. You can always catch us 446 00:27:22,920 --> 00:27:24,480 Speaker 1: worldwide on Bloomberg Radio