1 00:00:03,120 --> 00:00:11,280 Speaker 1: Bloomberg Audio Studios, podcasts, radio news. The election is only 2 00:00:11,360 --> 00:00:14,680 Speaker 1: about a week away, and while most major polls, including 3 00:00:14,720 --> 00:00:18,040 Speaker 1: the latest Bloomberg Morning Console poll, show Vice President Harris 4 00:00:18,079 --> 00:00:21,239 Speaker 1: and former President Trump are running neck and neck, Wall 5 00:00:21,239 --> 00:00:25,279 Speaker 1: Street has become increasingly convinced Trump is going to win, 6 00:00:26,040 --> 00:00:29,280 Speaker 1: and that conviction is manifesting itself in what's come to 7 00:00:29,320 --> 00:00:30,920 Speaker 1: be called the Trump. 8 00:00:30,640 --> 00:00:33,559 Speaker 2: Trade, the Trump trade, as some have been calling it, 9 00:00:33,720 --> 00:00:34,760 Speaker 2: the so called Trump trade. 10 00:00:34,840 --> 00:00:36,839 Speaker 1: We see those games from the Trump trades, who are 11 00:00:36,840 --> 00:00:39,800 Speaker 1: the winners and who are the loser? Investors are effectively 12 00:00:39,800 --> 00:00:42,720 Speaker 1: betting on a Trump win in the stock market, in 13 00:00:42,760 --> 00:00:46,960 Speaker 1: the bond market, in currencies, in crypto Bloomberg Opinions, John 14 00:00:46,960 --> 00:00:50,320 Speaker 1: Author says he's never seen anything like it. Wall Street 15 00:00:50,360 --> 00:00:54,280 Speaker 1: paying such close attention to a presidential election. He compared 16 00:00:54,280 --> 00:00:56,680 Speaker 1: to what's happening now to his first election he covered 17 00:00:56,720 --> 00:00:59,520 Speaker 1: in the US, that was Dole versus Clinton in nineteen 18 00:00:59,560 --> 00:01:00,000 Speaker 1: ninety seven. 19 00:01:00,520 --> 00:01:02,960 Speaker 2: I actually spoke to somebody in one of the large 20 00:01:02,960 --> 00:01:08,480 Speaker 2: firms two days later who said, did Clinton win? And 21 00:01:09,480 --> 00:01:12,920 Speaker 2: wasn't embarrassing? Yes he did? I mean that there was 22 00:01:13,840 --> 00:01:19,480 Speaker 2: You couldn't tell anything about that election from prices before 23 00:01:19,520 --> 00:01:22,760 Speaker 2: it happened or after. This is so different from. 24 00:01:22,560 --> 00:01:26,200 Speaker 1: That, it's hard to overstate John says how much things 25 00:01:26,200 --> 00:01:27,280 Speaker 1: have changed since then. 26 00:01:27,680 --> 00:01:33,360 Speaker 2: It's a very interesting, difficult, flammable situation. The level of 27 00:01:33,400 --> 00:01:36,600 Speaker 2: interest is unusual, and it's pretty extreme. 28 00:01:40,080 --> 00:01:42,039 Speaker 1: I'm David Gura, and this is the big take from 29 00:01:42,040 --> 00:01:45,680 Speaker 1: Bloomberg News today on the show, The Trump Trade and 30 00:01:45,720 --> 00:01:48,320 Speaker 1: what it tells us about how Wall Street sees this 31 00:01:48,400 --> 00:01:56,920 Speaker 1: election and the future of the economy. What is the 32 00:01:56,960 --> 00:01:59,720 Speaker 1: Trump trade? What exactly is Wall Street betting on? Okay, 33 00:02:00,120 --> 00:02:01,200 Speaker 1: Trump trade? 34 00:02:01,960 --> 00:02:08,200 Speaker 2: Very broadly, it's positive, bullish on stocks and negative bearish 35 00:02:08,440 --> 00:02:12,880 Speaker 2: on bonds. At present, it seems to be predicated on 36 00:02:12,919 --> 00:02:16,360 Speaker 2: the belief that even though a Trump presidency will be 37 00:02:16,400 --> 00:02:18,880 Speaker 2: negative for bonds, it won't be so negative. It won't 38 00:02:18,960 --> 00:02:22,639 Speaker 2: push up yields so much that it derails the stock market. 39 00:02:23,320 --> 00:02:27,520 Speaker 2: So that's basically the Trump trade, a belief that Trump 40 00:02:27,560 --> 00:02:31,040 Speaker 2: is going to win and that what he does will 41 00:02:31,080 --> 00:02:34,080 Speaker 2: be expansionary and that it's also going to boost growth 42 00:02:34,120 --> 00:02:35,440 Speaker 2: and help the stock market. 43 00:02:35,440 --> 00:02:37,280 Speaker 1: Could I ask you how people are playing this in 44 00:02:37,400 --> 00:02:39,799 Speaker 1: a few different outset classes as you mentioned Starks, Yes, 45 00:02:40,160 --> 00:02:42,680 Speaker 1: I would guess that there would be people who think oh, 46 00:02:42,720 --> 00:02:44,960 Speaker 1: this is going to be good for energy stocks, for instance, 47 00:02:45,120 --> 00:02:47,760 Speaker 1: or financials. Perhaps there'll be less regulation. 48 00:02:48,080 --> 00:02:51,880 Speaker 2: Yeah, companies that are deemed to be very benefited by 49 00:02:52,400 --> 00:02:56,800 Speaker 2: logistics by globalization have a problem. If you were interested 50 00:02:56,840 --> 00:03:02,120 Speaker 2: in FedEx, for example, that's plainly doesn't do well when 51 00:03:02,200 --> 00:03:07,040 Speaker 2: Trump's numbers are seen to improve. But yes, overall a 52 00:03:07,040 --> 00:03:10,519 Speaker 2: Trump win is seen to be good for classic cyclical 53 00:03:11,000 --> 00:03:18,079 Speaker 2: companies and it's not so great for classic defensive, staple 54 00:03:18,200 --> 00:03:19,400 Speaker 2: type companies. 55 00:03:19,520 --> 00:03:20,840 Speaker 1: How about in the bar market. 56 00:03:20,919 --> 00:03:24,959 Speaker 2: Bond market generally there are two animating features here. One 57 00:03:25,000 --> 00:03:27,160 Speaker 2: is it's a cliche, but it is true that bond 58 00:03:27,160 --> 00:03:31,520 Speaker 2: markets prefer gridlock. When you have gridlock when one party 59 00:03:31,639 --> 00:03:34,960 Speaker 2: in Congress actors a check on the presidency, generally speaking, 60 00:03:35,600 --> 00:03:37,760 Speaker 2: the deficity is less likely to get out of control, 61 00:03:37,920 --> 00:03:41,200 Speaker 2: Supply is less likely to be too heavy, and so 62 00:03:41,360 --> 00:03:46,800 Speaker 2: that keeps yields lower. The assumption, which I think is 63 00:03:47,040 --> 00:03:51,160 Speaker 2: probably correct, is that if Trump pulls off the presidency, 64 00:03:51,200 --> 00:03:53,680 Speaker 2: the chances of overwhelmingly strong that he wins the Senate 65 00:03:53,680 --> 00:03:58,480 Speaker 2: as well, and probably also holds onto the House. So 66 00:03:58,760 --> 00:04:04,240 Speaker 2: if you have unified government, that's bad for bonds. 67 00:04:04,640 --> 00:04:08,400 Speaker 1: John says fixed income investors like Most are not typically 68 00:04:08,440 --> 00:04:12,240 Speaker 1: motivated by ideology. They just want to make money, and 69 00:04:12,320 --> 00:04:14,760 Speaker 1: some are trying to bet on what a Trump presidency 70 00:04:14,840 --> 00:04:17,800 Speaker 1: might mean for inflation in both the short term and 71 00:04:17,839 --> 00:04:18,599 Speaker 1: the long term. 72 00:04:19,120 --> 00:04:23,039 Speaker 2: It will absolutely, undoubtedly be terrible for inflation in the 73 00:04:23,080 --> 00:04:28,080 Speaker 2: short term. The total burden on the amount of tariff 74 00:04:28,120 --> 00:04:31,839 Speaker 2: that will be paid. This is Barclay's research. I'm going 75 00:04:31,880 --> 00:04:37,919 Speaker 2: from not anything to hyper liberal. The twenty eighteen tariffs 76 00:04:38,000 --> 00:04:41,600 Speaker 2: added about two percentage points onto the cost of the importans. 77 00:04:41,760 --> 00:04:43,840 Speaker 2: The tarfity is talking about now, if he really goes 78 00:04:43,839 --> 00:04:48,000 Speaker 2: through with it, will add seventeen percentage points. So this 79 00:04:48,120 --> 00:04:52,200 Speaker 2: is protectionism on a scale not seen since the Great Depression. 80 00:04:53,200 --> 00:04:56,560 Speaker 2: And if you are a company, you will pass that 81 00:04:56,680 --> 00:04:59,000 Speaker 2: on or pass as much of it as you can on, 82 00:04:59,320 --> 00:05:02,359 Speaker 2: because otherwise you're shareholders won't be very pleased with you. 83 00:05:03,480 --> 00:05:06,599 Speaker 2: So it is directly inflationary in the short term. I 84 00:05:06,600 --> 00:05:12,440 Speaker 2: don't see any arguments against that. If Donald Trump persuades 85 00:05:13,000 --> 00:05:16,080 Speaker 2: more production to come to the States, if he persuades 86 00:05:16,240 --> 00:05:21,559 Speaker 2: companies currently operating in China to move their production facilities here, 87 00:05:22,600 --> 00:05:25,920 Speaker 2: in the long term, that will definitely be good. But 88 00:05:26,120 --> 00:05:30,320 Speaker 2: it takes far longer to build a factory than it 89 00:05:30,360 --> 00:05:33,679 Speaker 2: does to raise a price, and so there is still 90 00:05:33,720 --> 00:05:36,159 Speaker 2: no way that you avoid an inflationary spike if he 91 00:05:36,200 --> 00:05:38,400 Speaker 2: really goes through with this, and that will be bad 92 00:05:38,400 --> 00:05:39,119 Speaker 2: for the bond market. 93 00:05:39,400 --> 00:05:43,040 Speaker 1: Currency traders are also focusing on what former President Trump 94 00:05:43,120 --> 00:05:44,560 Speaker 1: has been saying about tariffs. 95 00:05:44,720 --> 00:05:48,680 Speaker 2: The currency traders take it as an absolute given that, 96 00:05:49,200 --> 00:05:51,919 Speaker 2: particularly if he goes through with those tariffs, that it 97 00:05:51,960 --> 00:05:55,880 Speaker 2: will be very bullish for the dollar. If the Trump 98 00:05:55,880 --> 00:05:58,960 Speaker 2: proposals are accurate, that he's really going to try to 99 00:05:59,040 --> 00:06:02,880 Speaker 2: deter near suring as well and really try to force 100 00:06:02,920 --> 00:06:06,719 Speaker 2: people to bring production back to the US, this will 101 00:06:06,720 --> 00:06:10,360 Speaker 2: mean a very strong dollar. You then get into the issue, 102 00:06:10,480 --> 00:06:13,560 Speaker 2: as is so often the case, you need to start 103 00:06:13,600 --> 00:06:15,599 Speaker 2: thinking in terms of a chess player and what the 104 00:06:15,640 --> 00:06:18,880 Speaker 2: next moves will be. If, as is likely, you get 105 00:06:18,920 --> 00:06:22,440 Speaker 2: a startling strengthening of the dollar, which makes it that 106 00:06:22,600 --> 00:06:28,119 Speaker 2: much harder for US exporters, presumably the next response either 107 00:06:28,200 --> 00:06:30,880 Speaker 2: will be okay, maybe these tariff's answers to a great idea, 108 00:06:31,360 --> 00:06:35,559 Speaker 2: or what can we do to push the dollar lower? Now? 109 00:06:35,960 --> 00:06:41,200 Speaker 2: One possibility which is not particularly positive for the markets 110 00:06:41,480 --> 00:06:43,880 Speaker 2: is that we then have a President Trump trying to 111 00:06:43,880 --> 00:06:48,160 Speaker 2: impinge upon the Fed's independence to get rates down when 112 00:06:48,200 --> 00:06:52,120 Speaker 2: they would otherwise rise and weaken the dollar, which for 113 00:06:52,160 --> 00:06:57,480 Speaker 2: any number of reasons would really terrify people. The other possibility, 114 00:06:57,720 --> 00:06:59,680 Speaker 2: given that Trump at least put his name to a 115 00:06:59,680 --> 00:07:02,599 Speaker 2: book of the deal, is that you could try to 116 00:07:02,680 --> 00:07:06,960 Speaker 2: have a grand deal two weeken the dullo. 117 00:07:07,360 --> 00:07:10,720 Speaker 1: That's happened before when Ronald Reagan was the president, But 118 00:07:10,800 --> 00:07:13,680 Speaker 1: the world has changed a lot since then, and John 119 00:07:13,720 --> 00:07:15,560 Speaker 1: says it would be hard for Trump to broke were 120 00:07:15,520 --> 00:07:19,200 Speaker 1: in agreement like that today. Coming up, how the Trump 121 00:07:19,240 --> 00:07:22,440 Speaker 1: trade has evolved, how it's playing out in prediction markets, 122 00:07:22,680 --> 00:07:24,960 Speaker 1: and what happens to the Trump trade when we find 123 00:07:24,960 --> 00:07:37,680 Speaker 1: out the outcome of the election. That's next. Another place 124 00:07:37,680 --> 00:07:40,080 Speaker 1: where you can see investors betting on a Trump win 125 00:07:40,480 --> 00:07:43,680 Speaker 1: is in the prediction markets. Today. They exist on sites 126 00:07:43,760 --> 00:07:47,480 Speaker 1: like Predicted and the Iowa Electronic Markets where people can 127 00:07:47,520 --> 00:07:50,760 Speaker 1: bet on the outcome of the election. But Bloomberg opinion 128 00:07:50,760 --> 00:07:54,520 Speaker 1: columnist John Authors says prediction markets have a long history. 129 00:07:54,800 --> 00:07:57,360 Speaker 2: Prediction markets have been around for an extremely long time. 130 00:07:57,920 --> 00:08:02,080 Speaker 2: They used to be thriving prediction markets in papal conclaves 131 00:08:02,920 --> 00:08:05,600 Speaker 2: in the fifteenth and sixteenth century. 132 00:08:05,960 --> 00:08:07,239 Speaker 1: Who's going to be the next pope? 133 00:08:07,320 --> 00:08:10,160 Speaker 2: Who is going to be the next pope? Cardinals would 134 00:08:10,240 --> 00:08:14,240 Speaker 2: tell their attendants who was leading, and they would rush 135 00:08:14,240 --> 00:08:16,520 Speaker 2: out and put bets on it with the traders out 136 00:08:16,560 --> 00:08:19,600 Speaker 2: there on the streets of Rome, and the betting markets 137 00:08:19,680 --> 00:08:24,400 Speaker 2: could be surprisingly accurate, and the money that was involved 138 00:08:24,560 --> 00:08:30,120 Speaker 2: was multi millions in today's today's terms, because obviously in 139 00:08:30,200 --> 00:08:32,800 Speaker 2: Renaissance Rome, who is going to be the next pope? 140 00:08:33,080 --> 00:08:37,000 Speaker 2: Really about it, and there were prediction markets writing on 141 00:08:37,880 --> 00:08:41,120 Speaker 2: the floor of the New York Stock Exchange for many 142 00:08:41,160 --> 00:08:43,480 Speaker 2: decades at the beginning of the twentieth century. 143 00:08:43,679 --> 00:08:47,680 Speaker 1: Today, another one of these prediction markets is called poly Market. 144 00:08:48,000 --> 00:08:53,880 Speaker 2: It's a big and liquid market. Officially, Americans can't trade there, 145 00:08:54,320 --> 00:08:57,040 Speaker 2: which ought to be a very big red flag sign. 146 00:08:57,679 --> 00:09:01,439 Speaker 2: There can be some extra dispassion attitude that can come 147 00:09:01,480 --> 00:09:02,880 Speaker 2: from not actually being American. 148 00:09:03,080 --> 00:09:06,200 Speaker 1: In recent days, a polymarket user who goes by Freddy 149 00:09:06,320 --> 00:09:09,600 Speaker 1: nine nine on the site has bet more than forty 150 00:09:09,640 --> 00:09:13,719 Speaker 1: five million dollars on a Republican victory. He's been identified 151 00:09:13,760 --> 00:09:17,560 Speaker 1: as a French national with extensive trading experience and the 152 00:09:17,600 --> 00:09:22,040 Speaker 1: financial services background, according to Polymarket, and John says one 153 00:09:22,080 --> 00:09:26,240 Speaker 1: thing that sets polymarket apart is that, unlike other prediction markets, 154 00:09:26,440 --> 00:09:28,560 Speaker 1: there is no limit on what you can bet. 155 00:09:28,880 --> 00:09:33,280 Speaker 2: It's a more liquid market. You can also express your 156 00:09:33,960 --> 00:09:38,760 Speaker 2: conviction more easily because you can bet more. Polymarkets like 157 00:09:38,840 --> 00:09:41,320 Speaker 2: any markets, if somebody enters with a really big bait, 158 00:09:41,440 --> 00:09:43,800 Speaker 2: it will move, which is what's happened after Eaton Musk 159 00:09:43,960 --> 00:09:46,720 Speaker 2: told everybody, look at polymarketing, isn't it wonderful? 160 00:09:47,080 --> 00:09:49,720 Speaker 1: John is talking about a post Musk made on x 161 00:09:49,800 --> 00:09:53,319 Speaker 1: in early October in which he praised prediction markets as 162 00:09:53,360 --> 00:09:56,959 Speaker 1: being quote more accurate than polls, as actual money is 163 00:09:57,000 --> 00:09:57,600 Speaker 1: on the line. 164 00:09:57,760 --> 00:09:59,400 Speaker 2: The last time I checked, when we were recording this, 165 00:09:59,480 --> 00:10:01,440 Speaker 2: I think polyma market put the odds on Trump winning 166 00:10:01,440 --> 00:10:04,280 Speaker 2: at sixty two percent. That's more than a one in 167 00:10:04,320 --> 00:10:06,680 Speaker 2: three chance that Kamala Harris is the next president. According 168 00:10:06,720 --> 00:10:09,920 Speaker 2: to polymarket. You wouldn't bet your life on this. And 169 00:10:10,240 --> 00:10:13,840 Speaker 2: that's to some extent the point of where a prediction 170 00:10:14,000 --> 00:10:17,480 Speaker 2: market has its advantage. You see the price and then 171 00:10:17,520 --> 00:10:20,240 Speaker 2: you think, well, I do think Donald Trump is probably 172 00:10:20,320 --> 00:10:23,280 Speaker 2: going to win. But do I really know that the 173 00:10:23,320 --> 00:10:26,320 Speaker 2: Democrats don't have a better ground game they did last time? 174 00:10:26,400 --> 00:10:28,920 Speaker 2: Do I really know that the polls aren't just missing 175 00:10:29,760 --> 00:10:33,360 Speaker 2: lots of very motivated, angry young women who weren't voting 176 00:10:33,520 --> 00:10:35,880 Speaker 2: last time because of the abortion issue. Actually, no, I 177 00:10:35,920 --> 00:10:40,440 Speaker 2: don't know that. So am I really confident enough to 178 00:10:40,520 --> 00:10:44,600 Speaker 2: bet much more than that. No, Actually, we'll leave it 179 00:10:44,640 --> 00:10:47,880 Speaker 2: at only about a sixty percent chance. That is the 180 00:10:47,920 --> 00:10:51,440 Speaker 2: benefit of prediction markets that they do capture that, But 181 00:10:51,520 --> 00:10:54,480 Speaker 2: it's not the same. There's there are certainly people who 182 00:10:54,520 --> 00:10:57,000 Speaker 2: think that polymarket at sixty two percent for Trump means 183 00:10:57,040 --> 00:10:58,920 Speaker 2: they think Donald Trump will get sixty two percent of 184 00:10:58,960 --> 00:11:04,560 Speaker 2: the votes, which be an absolutely monstrous, historic landslide. No, 185 00:11:04,679 --> 00:11:06,720 Speaker 2: it doesn't mean that that isn't going to happen. 186 00:11:07,080 --> 00:11:09,600 Speaker 1: I wonder what happens on election day. Say Trump wins, 187 00:11:10,080 --> 00:11:12,880 Speaker 1: what does that mean for people who have bet on 188 00:11:12,880 --> 00:11:15,120 Speaker 1: this Trump trade? If he loses, what does that mean. 189 00:11:15,280 --> 00:11:18,160 Speaker 2: In terms of the bond markets. I imagine you would 190 00:11:18,320 --> 00:11:21,920 Speaker 2: see a big relief rally into bonds and you would 191 00:11:21,960 --> 00:11:24,640 Speaker 2: probably see some degree of a sell off in stocks 192 00:11:25,040 --> 00:11:28,720 Speaker 2: if you have a Kamala Harris presidency. If and I 193 00:11:28,760 --> 00:11:31,840 Speaker 2: think it's very unlikely, but if if somehow or other 194 00:11:32,200 --> 00:11:36,840 Speaker 2: John Tester wins in Montana or Ted Cruz loses in Texas, 195 00:11:37,280 --> 00:11:39,640 Speaker 2: which would make a lot of people in this country 196 00:11:39,800 --> 00:11:43,520 Speaker 2: extremely happy. But I still don't quite imagine it happening. 197 00:11:43,920 --> 00:11:46,920 Speaker 2: If somehow or other you get a clean sweep for 198 00:11:47,000 --> 00:11:52,320 Speaker 2: Kamala Harris rather than a checked Kamala Harris, then I 199 00:11:52,320 --> 00:11:56,960 Speaker 2: imagine the sell off in bonds would continue and the 200 00:11:56,960 --> 00:11:59,520 Speaker 2: stock market would probably not like that very much either. 201 00:12:00,640 --> 00:12:05,679 Speaker 2: I think the best outcome, probably for most asset classes, 202 00:12:05,760 --> 00:12:09,400 Speaker 2: is Kamela checked by the Senate. Possibly Camela checked by 203 00:12:09,440 --> 00:12:12,600 Speaker 2: the Senate and the House. That would not have any 204 00:12:12,640 --> 00:12:15,800 Speaker 2: great negative response. I don't think. 205 00:12:15,880 --> 00:12:18,120 Speaker 1: How good is Wall streeted predicted the outcome of elections 206 00:12:18,120 --> 00:12:18,840 Speaker 1: if you look at. 207 00:12:18,720 --> 00:12:22,400 Speaker 2: History, Oh, the number of times. 208 00:12:22,160 --> 00:12:24,760 Speaker 1: As good as the cardinals. 209 00:12:24,920 --> 00:12:30,640 Speaker 2: Yes, I mean the over history twenty sixteen, the polls 210 00:12:30,640 --> 00:12:33,840 Speaker 2: were wrong. Answer with the prediction markets. It was one 211 00:12:33,720 --> 00:12:37,640 Speaker 2: where for whatever reason, people just didn't catch what was happening. 212 00:12:38,640 --> 00:12:42,920 Speaker 2: Over history, the various prediction markets that were available were 213 00:12:42,920 --> 00:12:46,880 Speaker 2: better than the gallop pole over a series of elections, 214 00:12:47,720 --> 00:12:52,640 Speaker 2: So prediction markets generally are pretty good over history. The 215 00:12:52,720 --> 00:12:57,319 Speaker 2: number of examples of really big sell offs or booms 216 00:12:57,360 --> 00:13:01,080 Speaker 2: in response to an election result is pretty minimal, which 217 00:13:01,120 --> 00:13:05,000 Speaker 2: means that Wall Street is generally not surprised by the results, 218 00:13:05,920 --> 00:13:11,200 Speaker 2: twenty sixteen being the big, glaring exception to that. I 219 00:13:11,200 --> 00:13:16,360 Speaker 2: think one of the things that's very difficult is again 220 00:13:16,400 --> 00:13:19,199 Speaker 2: that you need to know about the chess moves ahead. 221 00:13:19,679 --> 00:13:22,920 Speaker 2: Like from what we know now, you can say various 222 00:13:22,960 --> 00:13:26,440 Speaker 2: things about Harris versus a Trump foreign policy, domestic policy, 223 00:13:26,480 --> 00:13:29,719 Speaker 2: but broadly speaking, it's not that obvious how different things 224 00:13:29,760 --> 00:13:30,120 Speaker 2: would be. 225 00:13:33,880 --> 00:13:36,480 Speaker 1: This is the Big Take from Bloomberg News. I'm David Gura. 226 00:13:36,760 --> 00:13:39,839 Speaker 1: This episode was produced by David Fox. It was edited 227 00:13:39,880 --> 00:13:43,040 Speaker 1: by Caitlin Kenny and Sid Verma, and mixed by Alex Sagura. 228 00:13:43,559 --> 00:13:46,640 Speaker 1: It was fact checked by Adriana Tapia. Our senior producer 229 00:13:46,679 --> 00:13:50,400 Speaker 1: is Naomi Shaven. Our senior editor is Elizabeth Ponso. Our 230 00:13:50,440 --> 00:13:54,119 Speaker 1: executive producer is Nicole Beemster Boor Sage Bauman is Bloomberg's 231 00:13:54,160 --> 00:13:57,040 Speaker 1: head of Podcasts. If you liked this episode, make sure 232 00:13:57,080 --> 00:13:59,480 Speaker 1: you subscribe and review The Big Take wherever you listen 233 00:13:59,520 --> 00:14:03,120 Speaker 1: to podcasts. It helps people find the show. Thanks for listening. 234 00:14:03,360 --> 00:14:14,760 Speaker 1: We'll be back tomorrow. Hey, everyone, Bloomberg wants to hear 235 00:14:14,800 --> 00:14:17,319 Speaker 1: from you. 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