1 00:00:00,080 --> 00:00:02,520 Speaker 1: Hey, we know investors certainly watching what's happening on the 2 00:00:02,720 --> 00:00:05,320 Speaker 1: campaign trail audience. We've heard a lot in the last 3 00:00:05,360 --> 00:00:08,160 Speaker 1: couple of weeks from some of investing in markets. Guess 4 00:00:08,160 --> 00:00:11,720 Speaker 1: how they and their clients waiting election? What possibly mean 5 00:00:16,360 --> 00:00:19,560 Speaker 1: on the so called and the prediction markets. I gotta 6 00:00:19,600 --> 00:00:20,160 Speaker 1: tell you. 7 00:00:20,680 --> 00:00:23,239 Speaker 2: On Friday, but I was watching the prediction market and 8 00:00:23,280 --> 00:00:27,280 Speaker 2: Jim stat actor from and they were moving very quickly 9 00:00:27,680 --> 00:00:31,520 Speaker 2: away from this clear Trump victory over Harris and emailed 10 00:00:31,560 --> 00:00:34,120 Speaker 2: John Authors. I was like, have you seen what's happening here? 11 00:00:34,400 --> 00:00:37,400 Speaker 2: And sure enough, yeah, he'd been watching it too. We 12 00:00:37,520 --> 00:00:41,360 Speaker 2: got John Authors with also joining us Bloomberg News markets 13 00:00:41,360 --> 00:00:44,279 Speaker 2: reporter Justina Lee. She writes about the election gambling facing. Uh, 14 00:00:44,320 --> 00:00:47,159 Speaker 2: it's a moment of truth. John, Justina, Welcome to the program. 15 00:00:47,200 --> 00:00:49,840 Speaker 2: Both of you writing about the prediction markets. Uh, Justina, 16 00:00:49,880 --> 00:00:51,720 Speaker 2: I do want to start with you, though, because remind 17 00:00:51,760 --> 00:00:54,480 Speaker 2: everyone what exactly we're talking about here. I think for 18 00:00:54,560 --> 00:00:56,480 Speaker 2: a lot of people, this is the first election where 19 00:00:56,480 --> 00:00:57,680 Speaker 2: they're hearing about this stuff. 20 00:00:58,120 --> 00:00:58,320 Speaker 3: Yeah. 21 00:00:58,360 --> 00:01:02,000 Speaker 4: What's really interesting is just before the start of this election, 22 00:01:02,160 --> 00:01:05,160 Speaker 4: I mean, we were we had kind of a judge 23 00:01:05,200 --> 00:01:11,399 Speaker 4: overturned this ban on a US legal kind of exchange 24 00:01:11,440 --> 00:01:14,640 Speaker 4: that is going to offer contracts on the election. And 25 00:01:14,680 --> 00:01:18,240 Speaker 4: because of this, there's more attention on election betting than ever. 26 00:01:18,520 --> 00:01:21,520 Speaker 4: And also there's also this crypto exchange off tour that's 27 00:01:21,560 --> 00:01:25,600 Speaker 4: been seeing really large volumes and kind of electoral betting, 28 00:01:25,720 --> 00:01:27,640 Speaker 4: and I think because of this, there's been a lot 29 00:01:27,680 --> 00:01:31,000 Speaker 4: of attention on those odds, and in particular because over 30 00:01:31,040 --> 00:01:33,880 Speaker 4: the past month they've they've shown like a way higher 31 00:01:33,959 --> 00:01:37,280 Speaker 4: probability for Trump than we're seeing in you know, forecast 32 00:01:37,319 --> 00:01:39,520 Speaker 4: models like five thirty eight or Nate Silver. 33 00:01:39,560 --> 00:01:41,320 Speaker 3: John come on in on this. You've got to calum 34 00:01:41,400 --> 00:01:43,640 Speaker 3: out noting that the prediction markets are giving now Donald 35 00:01:43,640 --> 00:01:47,400 Speaker 3: Trumps November surprise, not necessarily a good one. 36 00:01:47,920 --> 00:01:51,280 Speaker 5: Not necessarily a good one for Trump at all. I mean, 37 00:01:51,560 --> 00:01:54,080 Speaker 5: with prediction markets, you've always got to remember there is 38 00:01:54,120 --> 00:01:57,960 Speaker 5: an issue with them. Garbage and garbage out to the 39 00:01:58,640 --> 00:02:05,240 Speaker 5: and Zel sip Iowa poll at face value, if it's accurate, 40 00:02:05,400 --> 00:02:07,720 Speaker 5: means CAML Harris has won the election. 41 00:02:08,480 --> 00:02:10,000 Speaker 3: What does garbage in garbage out mean? 42 00:02:10,400 --> 00:02:12,560 Speaker 5: Gub it's it's it's a computer term. If that, if 43 00:02:12,560 --> 00:02:15,920 Speaker 5: the data you're putting into the prediction market is bad data, right, 44 00:02:16,120 --> 00:02:19,520 Speaker 5: there's no reason to produce to expect it to produce 45 00:02:19,560 --> 00:02:20,240 Speaker 5: a good outcome. 46 00:02:20,400 --> 00:02:22,880 Speaker 3: So I get that. So with the predicted prediction markets, 47 00:02:22,919 --> 00:02:25,000 Speaker 3: does that mean sometimes there's good data coming in, sometimes 48 00:02:25,040 --> 00:02:26,079 Speaker 3: there's not, or is. 49 00:02:26,840 --> 00:02:30,480 Speaker 5: I think it's been true of any market that you know, 50 00:02:31,320 --> 00:02:33,519 Speaker 5: if you got bad data from Enron and you thought 51 00:02:33,560 --> 00:02:36,000 Speaker 5: it was an absolutely fantastic for company for a long time, 52 00:02:36,040 --> 00:02:38,639 Speaker 5: and then you realized it wasn't right, And amazingly I 53 00:02:38,680 --> 00:02:40,200 Speaker 5: looked up yesterday it was replaced in the S and 54 00:02:40,240 --> 00:02:41,360 Speaker 5: P five hundred my own video. 55 00:02:42,040 --> 00:02:42,280 Speaker 6: Wow. 56 00:02:42,560 --> 00:02:47,519 Speaker 1: Okay, that's yes, yes, But that's that's why John, I 57 00:02:47,560 --> 00:02:49,040 Speaker 1: think it was. I think it might have been exactly 58 00:02:49,080 --> 00:02:50,720 Speaker 1: a week ago you sat in this chair. You'd written 59 00:02:50,720 --> 00:02:53,800 Speaker 1: another column that talked about how the Trump trade was on, 60 00:02:53,919 --> 00:02:56,640 Speaker 1: and it looked like it gave the former president about 61 00:02:56,639 --> 00:02:59,600 Speaker 1: a two thirds chance. Do you do you want to 62 00:02:59,680 --> 00:03:01,280 Speaker 1: update that prediction ahead of tomorrow? 63 00:03:02,320 --> 00:03:07,040 Speaker 5: The current prediction is that it gives him. I'm inclined 64 00:03:07,080 --> 00:03:09,640 Speaker 5: not to trust polymarkets as much as the others because 65 00:03:09,720 --> 00:03:14,440 Speaker 5: there does seem to be an oddly determined positive gloss 66 00:03:14,200 --> 00:03:17,280 Speaker 5: on the on the Republican chances. The others suggest that 67 00:03:17,480 --> 00:03:20,840 Speaker 5: he still has a chance, a better chance than Kamala Harris, 68 00:03:20,840 --> 00:03:23,800 Speaker 5: but it's a much narrow one, like three fifty four percent. 69 00:03:25,400 --> 00:03:30,880 Speaker 5: That sounds broadly accurate to me, simply because we don't 70 00:03:31,040 --> 00:03:34,000 Speaker 5: know what the narratives are that here that are going 71 00:03:34,040 --> 00:03:37,920 Speaker 5: to decide things. It's possible Madison Square Garden Rally and 72 00:03:37,960 --> 00:03:42,120 Speaker 5: everything around it really may decided a lot of people 73 00:03:42,120 --> 00:03:44,160 Speaker 5: that know they weren't going to go vote for this guy. 74 00:03:44,320 --> 00:03:45,960 Speaker 5: We don't know yet. We will know soon. 75 00:03:46,040 --> 00:03:48,320 Speaker 3: And if I recall, was it twenty sixteen that you 76 00:03:48,400 --> 00:03:53,520 Speaker 3: said that initially it was the markets in favor of Hillary. Yes, 77 00:03:53,760 --> 00:03:57,160 Speaker 3: And obviously we know Donald Trump exactly well. 78 00:03:57,160 --> 00:04:00,840 Speaker 5: We also and the markets will convince the prediction. Markets 79 00:04:00,880 --> 00:04:03,560 Speaker 5: were convinced in Britain that Brexit was not going to 80 00:04:03,600 --> 00:04:07,000 Speaker 5: succeed in the referendum earlier that year, and that one 81 00:04:07,080 --> 00:04:09,640 Speaker 5: wasn't That one wasn't right either. I mean, the other 82 00:04:09,720 --> 00:04:12,800 Speaker 5: thing you've got to be very careful with in real 83 00:04:12,840 --> 00:04:16,440 Speaker 5: markets with capital at stake. I did just check up 84 00:04:16,480 --> 00:04:19,600 Speaker 5: that S and P E mini futures were down more 85 00:04:19,640 --> 00:04:24,400 Speaker 5: than five percent in the immediate wake of the network's 86 00:04:24,480 --> 00:04:26,480 Speaker 5: calling twenty sixteen for Donald Trump. 87 00:04:26,560 --> 00:04:28,200 Speaker 3: Remember that, I remember watching. 88 00:04:27,880 --> 00:04:31,000 Speaker 5: It, and they's pretty deep up by the time they 89 00:04:31,320 --> 00:04:37,120 Speaker 5: markets actually opened the following day. So you know, there 90 00:04:37,120 --> 00:04:39,640 Speaker 5: are some fairly clear things. You would imagine Bond yields 91 00:04:39,640 --> 00:04:42,320 Speaker 5: would go up a lot, and that stocks would gain 92 00:04:42,360 --> 00:04:46,080 Speaker 5: a lot with a with a comfortable Trump victory tomorrow night, 93 00:04:46,120 --> 00:04:48,919 Speaker 5: you don't necessarily assume that that will hold on for 94 00:04:48,960 --> 00:04:52,680 Speaker 5: a terribly long time once people can begin to think 95 00:04:52,720 --> 00:04:54,960 Speaker 5: about this without the uncertainty surrounding it. 96 00:04:55,120 --> 00:04:57,479 Speaker 3: Just in a polls versus we've talked a lot about 97 00:04:57,520 --> 00:05:00,400 Speaker 3: the polling. Bloomberg has been involved in polling poll versus 98 00:05:00,480 --> 00:05:04,600 Speaker 3: prediction markets. What do investors in Wall Street respect as 99 00:05:04,600 --> 00:05:05,720 Speaker 3: we go through this process. 100 00:05:06,120 --> 00:05:08,680 Speaker 4: Yeah, what's been really interesting lately is that we've seen 101 00:05:08,720 --> 00:05:11,840 Speaker 4: a lot of cell sized strategies, in particular citing the 102 00:05:12,480 --> 00:05:16,000 Speaker 4: betting odds rather than the poles based forecast. And I 103 00:05:16,040 --> 00:05:18,719 Speaker 4: think one edge that the betting ods definitely have is 104 00:05:18,760 --> 00:05:21,080 Speaker 4: that you know, as people trade, they can more quickly 105 00:05:21,160 --> 00:05:23,960 Speaker 4: in corporate you know, every new drip of information or 106 00:05:24,000 --> 00:05:26,520 Speaker 4: whatever kind of you know, the vibe shifts. That might 107 00:05:26,560 --> 00:05:29,120 Speaker 4: be a bit harder for a model to quantify. But 108 00:05:29,200 --> 00:05:30,760 Speaker 4: I think that the flip side of that is that 109 00:05:30,800 --> 00:05:33,560 Speaker 4: you can more easily have kind of a hurting mentality, 110 00:05:33,720 --> 00:05:36,760 Speaker 4: or maybe it's more easily affected by one sided bets, 111 00:05:37,000 --> 00:05:39,680 Speaker 4: whereas I guess like the poles based forecasts are more 112 00:05:39,800 --> 00:05:42,960 Speaker 4: grounded on data, but you really need sort of the 113 00:05:43,040 --> 00:05:47,239 Speaker 4: trends to be roughly similar to history for that poles 114 00:05:47,279 --> 00:05:49,440 Speaker 4: based forecast to really have any insight. 115 00:05:50,720 --> 00:05:53,680 Speaker 3: I love this. We've got a listener saying, can Americans 116 00:05:53,720 --> 00:05:55,720 Speaker 3: bet on the winner? How does someone do it? 117 00:05:55,839 --> 00:05:59,560 Speaker 5: Yes, Justina can tell you more bets can let you 118 00:05:59,600 --> 00:06:02,480 Speaker 5: do it. We are in the interactive Brocus studio. 119 00:06:02,200 --> 00:06:02,599 Speaker 6: Are we not? 120 00:06:02,839 --> 00:06:05,960 Speaker 5: Are you can not the time necessarily saying you should? 121 00:06:06,000 --> 00:06:08,120 Speaker 5: But you can bet on it's only attractive breakase if 122 00:06:08,120 --> 00:06:12,320 Speaker 5: you like and robin Hood. Thanks to the CFTC's loss 123 00:06:12,440 --> 00:06:15,840 Speaker 5: in court, a number of people will will let you 124 00:06:15,960 --> 00:06:20,000 Speaker 5: do it legally, even without getting a VPN and pretending 125 00:06:20,080 --> 00:06:20,760 Speaker 5: not to be American. 126 00:06:20,920 --> 00:06:23,040 Speaker 3: Well that's why, Justina. You know in your story you 127 00:06:23,200 --> 00:06:26,039 Speaker 3: note that the prediction markets have entered the big leagues 128 00:06:26,080 --> 00:06:29,280 Speaker 3: with the twenty twenty four presidential vote. I mean this 129 00:06:29,480 --> 00:06:33,800 Speaker 3: is kind of new territory for everyone, for investors, for betting, 130 00:06:33,880 --> 00:06:36,280 Speaker 3: for the betting public here in America. 131 00:06:36,640 --> 00:06:39,640 Speaker 4: Yeah, that's right. I mean, we're seeing really large volumes, 132 00:06:39,720 --> 00:06:42,400 Speaker 4: especially compared to before. And one thing that I think 133 00:06:42,480 --> 00:06:44,240 Speaker 4: is really interesting is, you know, when it comes to 134 00:06:44,320 --> 00:06:47,360 Speaker 4: financial markets, we always think the moral liquidity the better, 135 00:06:47,520 --> 00:06:49,680 Speaker 4: and so kind of by that logic, I mean, this 136 00:06:49,880 --> 00:06:53,640 Speaker 4: year's all should be especially informative. But at the same time, 137 00:06:53,720 --> 00:06:55,720 Speaker 4: it's kind of funny because I spoke to an expert, 138 00:06:55,839 --> 00:06:58,560 Speaker 4: you know, on Friday, and he was saying, maybe pay 139 00:06:58,600 --> 00:07:01,640 Speaker 4: attention to the smallest market of all, which is predicted, 140 00:07:02,000 --> 00:07:05,440 Speaker 4: because predicted kind of limits the sizes of your positions 141 00:07:05,600 --> 00:07:07,560 Speaker 4: and so you don't really get kind of any of 142 00:07:07,640 --> 00:07:09,920 Speaker 4: these big whale traits, so you get on the polymarket. 143 00:07:10,360 --> 00:07:13,000 Speaker 4: And of course that's kind of a really interesting question 144 00:07:13,120 --> 00:07:17,320 Speaker 4: now because Predicted is the one platform that's giving even 145 00:07:17,360 --> 00:07:19,600 Speaker 4: odds to the two candidates at this moment. 146 00:07:19,960 --> 00:07:22,880 Speaker 5: And it also if you look back to the summer, 147 00:07:23,600 --> 00:07:27,440 Speaker 5: Predicted saw Kamala Harris coming a long way before the 148 00:07:27,520 --> 00:07:32,280 Speaker 5: other prediction markets that were out there. It saw the 149 00:07:32,400 --> 00:07:37,040 Speaker 5: chance that I presumably because the often the academics who 150 00:07:37,040 --> 00:07:39,440 Speaker 5: are betting on Predicted are fairly well plugged in the 151 00:07:39,520 --> 00:07:42,640 Speaker 5: democratic politics, they got that Joe Biden was likely to 152 00:07:42,760 --> 00:07:45,920 Speaker 5: have to stand down, and that Kamala Harris would be 153 00:07:46,480 --> 00:07:49,480 Speaker 5: nigh on unstoppable if he did to get the nomination 154 00:07:50,320 --> 00:07:55,680 Speaker 5: far before Polymarket did. So they're not dumb. The other 155 00:07:55,880 --> 00:08:01,040 Speaker 5: thing that is, if you're trying to produce a prediction, 156 00:08:01,200 --> 00:08:03,640 Speaker 5: if you're not hedging your bets, if you're not trying 157 00:08:03,720 --> 00:08:06,400 Speaker 5: to make money, but you're looking for the public, get 158 00:08:06,520 --> 00:08:11,800 Speaker 5: better of a good prediction on predicted everybody, including you 159 00:08:12,880 --> 00:08:15,440 Speaker 5: students who are just finishing their PhDs, is worth as 160 00:08:15,520 --> 00:08:16,280 Speaker 5: much as elon musk. 161 00:08:16,600 --> 00:08:19,320 Speaker 3: You guys, thank you so much. A great round the 162 00:08:19,360 --> 00:08:22,600 Speaker 3: table on that. John authors of Bloomberg Markets and Bloomberg Opinion, 163 00:08:22,720 --> 00:08:24,760 Speaker 3: just in the lead Markets are put her up Bloomber. 164 00:08:31,360 --> 00:08:34,840 Speaker 6: You're listening to the Bloomberg Business Week podcast. Catch us 165 00:08:34,920 --> 00:08:38,120 Speaker 6: live weekday afternoons from two to five pm. Easter Listen 166 00:08:38,200 --> 00:08:40,360 Speaker 6: on Apple card Play and then brod Auto with a 167 00:08:40,400 --> 00:08:43,400 Speaker 6: Bloomberg Business app, or want us live on YouTube. 168 00:08:46,160 --> 00:08:48,120 Speaker 1: All right, from the ground game to the money game, 169 00:08:48,200 --> 00:08:50,480 Speaker 1: we go to Yeah and the eleven thousand political groups 170 00:08:50,520 --> 00:08:53,439 Speaker 1: that have spent nearly fifteen billion dollars to influence the 171 00:08:53,480 --> 00:08:56,080 Speaker 1: twenty twenty four election. It brings us to a great 172 00:08:56,160 --> 00:08:59,280 Speaker 1: deep dive into the money that runs the US political systems. 173 00:08:59,320 --> 00:09:02,280 Speaker 1: It's an interact story. It's best read on the Bloomberg 174 00:09:02,360 --> 00:09:05,079 Speaker 1: terminal or online, so I encourage everybody to do that. 175 00:09:05,160 --> 00:09:08,680 Speaker 1: It's also, Carol one story that's really important understanding who's 176 00:09:08,720 --> 00:09:11,439 Speaker 1: spending to support the process and the candidates. 177 00:09:11,520 --> 00:09:13,520 Speaker 3: You've been talking about this story a lot, and we 178 00:09:13,600 --> 00:09:15,080 Speaker 3: talked about it a lot on our call this morning. 179 00:09:15,160 --> 00:09:17,800 Speaker 3: Let's bring in Bloomberg News campaign finance reporter Bill Allison. 180 00:09:18,080 --> 00:09:20,760 Speaker 3: He is in Washington. We should note that Michael Bloomberg, 181 00:09:20,800 --> 00:09:23,840 Speaker 3: the founder majority owner of Bloomberg News parent company Bloomberg 182 00:09:23,960 --> 00:09:26,720 Speaker 3: LP and Bloomberg Philanthropy is has given money to several 183 00:09:26,760 --> 00:09:30,079 Speaker 3: political groups, including House Majority Pack, Future Forward Pack, and 184 00:09:30,200 --> 00:09:33,480 Speaker 3: every Town for Gun Safety Victory Fund. All right, Bill, 185 00:09:33,520 --> 00:09:36,480 Speaker 3: so let's get to your reporting, great and informative deep 186 00:09:36,559 --> 00:09:39,320 Speaker 3: dive into all the money in the twenty twenty four election. 187 00:09:39,440 --> 00:09:41,839 Speaker 3: Tell us how you went about reporting this story out, 188 00:09:41,960 --> 00:09:44,000 Speaker 3: What you looked at, what you found out. 189 00:09:45,520 --> 00:09:48,360 Speaker 7: Well, first of all, it was wrangling this data was 190 00:09:48,400 --> 00:09:50,200 Speaker 7: one of the hardest things we ever did, in part 191 00:09:50,320 --> 00:09:54,160 Speaker 7: because committees give so much money to each other. I mean, 192 00:09:54,200 --> 00:09:56,880 Speaker 7: there's you know, the if you look at the main 193 00:09:57,040 --> 00:10:00,040 Speaker 7: Senate super PACs that they're spending tons of money, and 194 00:10:00,120 --> 00:10:02,480 Speaker 7: the Senate battlegrounds. You know, there's a group called Win 195 00:10:02,640 --> 00:10:07,120 Speaker 7: Senate which is backing Democrats, but it's actually funded by 196 00:10:07,160 --> 00:10:09,679 Speaker 7: the Senate Majority Pack, which is tied closely to to 197 00:10:09,840 --> 00:10:11,760 Speaker 7: Charles Schumer. So we basically the first thing we did 198 00:10:11,880 --> 00:10:13,439 Speaker 7: was to try to get all of that double counting 199 00:10:13,520 --> 00:10:15,880 Speaker 7: out of the numbers and really just focus on the 200 00:10:15,920 --> 00:10:17,520 Speaker 7: money that was coming in and the money that was 201 00:10:17,600 --> 00:10:20,839 Speaker 7: going out and uh, and what we found is is 202 00:10:20,920 --> 00:10:24,040 Speaker 7: that you know, there's there's a hundred committees that are 203 00:10:24,240 --> 00:10:26,880 Speaker 7: really the most active that are spending you know, close 204 00:10:26,920 --> 00:10:30,839 Speaker 7: to a third of the money in this election. And 205 00:10:32,640 --> 00:10:36,080 Speaker 7: it and you know, the it's just we've just seen 206 00:10:36,160 --> 00:10:38,760 Speaker 7: blockbuster amounts of money being spent. It's going to it's 207 00:10:39,040 --> 00:10:41,839 Speaker 7: most likely going to set the record, it's on track 208 00:10:41,920 --> 00:10:44,679 Speaker 7: to set the record for for the most expensive election ever, 209 00:10:44,840 --> 00:10:47,400 Speaker 7: even more than twenty twenty when you had a huge 210 00:10:47,400 --> 00:10:52,240 Speaker 7: attic field for the primaries and uh for the general election. 211 00:10:53,120 --> 00:10:55,640 Speaker 7: It's there's just the amounts of money that are being spent. 212 00:10:55,600 --> 00:10:56,199 Speaker 6: Or just staggering. 213 00:10:56,400 --> 00:10:59,520 Speaker 1: Yeah, fifteen billion dollars is just a mind boggling number. 214 00:11:00,120 --> 00:11:02,599 Speaker 1: I wonder though, how we got here, Bill, Is this 215 00:11:02,760 --> 00:11:06,320 Speaker 1: all a result of that twenty ten Supreme Court Citizens 216 00:11:06,480 --> 00:11:07,480 Speaker 1: United decision. 217 00:11:08,480 --> 00:11:11,200 Speaker 7: That's a big part of which got rid of soft 218 00:11:11,280 --> 00:11:13,200 Speaker 7: money to the parties. We had things like Swift vet 219 00:11:13,320 --> 00:11:16,839 Speaker 7: Vote Swiss, Swift Vote, Swift Vote Vets, Yeah, which was 220 00:11:16,920 --> 00:11:20,199 Speaker 7: the group that went after John Kerry. We had on 221 00:11:20,280 --> 00:11:22,960 Speaker 7: the left, we had a bunch of different They were 222 00:11:23,000 --> 00:11:26,959 Speaker 7: called Section five twenty seven organizations, and they basically ran 223 00:11:27,120 --> 00:11:30,520 Speaker 7: negative ads without using the words vote for, vote against, 224 00:11:30,559 --> 00:11:33,719 Speaker 7: which was fine under Citizens United. So, you know, I 225 00:11:33,800 --> 00:11:35,800 Speaker 7: think that the amount of money in politics, you know, 226 00:11:36,000 --> 00:11:38,400 Speaker 7: was always going to be I mean, it's there's so 227 00:11:38,559 --> 00:11:40,839 Speaker 7: much at stake in a federal election, whether it's you know, 228 00:11:40,960 --> 00:11:43,719 Speaker 7: control of Congress, control of the House, the Senate, or 229 00:11:43,800 --> 00:11:47,240 Speaker 7: the White House, that you know, interests just pour tons 230 00:11:47,280 --> 00:11:48,040 Speaker 7: and tons of money in. 231 00:11:49,040 --> 00:11:50,520 Speaker 3: One of the things that I always think about, you know, 232 00:11:50,600 --> 00:11:52,439 Speaker 3: on a story like this, Bill is yep, I think 233 00:11:52,480 --> 00:11:55,959 Speaker 3: about you know, the final dollar amount. That's serious, serious money, 234 00:11:56,320 --> 00:11:58,280 Speaker 3: and we all see it in the you know, campaigns 235 00:11:58,320 --> 00:12:00,719 Speaker 3: and ads that have been bombarding us. Having said that, 236 00:12:00,800 --> 00:12:04,280 Speaker 3: I also think about influence, and I do wonder in 237 00:12:04,440 --> 00:12:06,839 Speaker 3: terms of where a lot or the bulk of the 238 00:12:06,960 --> 00:12:11,240 Speaker 3: money came from. What were those entities were it? You know, 239 00:12:11,400 --> 00:12:13,160 Speaker 3: we know about Elon Musk. Can we keep talking about 240 00:12:13,160 --> 00:12:16,000 Speaker 3: the billionaires that are in the election, But where did 241 00:12:16,120 --> 00:12:18,240 Speaker 3: most of the money come from? Where is most of 242 00:12:18,320 --> 00:12:20,680 Speaker 3: the influence coming from in this in this campaign? 243 00:12:22,600 --> 00:12:22,840 Speaker 6: Boy? 244 00:12:23,000 --> 00:12:26,800 Speaker 7: That's you know, there's there's a huge base of small 245 00:12:26,840 --> 00:12:30,040 Speaker 7: dollar donors that are giving, you know, that are accounting 246 00:12:30,080 --> 00:12:32,520 Speaker 7: for you know, billions of dollars the amount of the total. 247 00:12:33,080 --> 00:12:35,520 Speaker 7: And those folks really aren't you know, they're much more 248 00:12:35,559 --> 00:12:38,679 Speaker 7: ideological givers. And I think at the upper end of 249 00:12:38,760 --> 00:12:40,640 Speaker 7: the spectrum too. And it's kind of funny that you 250 00:12:40,720 --> 00:12:44,080 Speaker 7: mentioned Elon Musk when you're talking to Ted Man. He's 251 00:12:44,440 --> 00:12:47,120 Speaker 7: he started as a very transactional giver. He gave to 252 00:12:47,160 --> 00:12:51,240 Speaker 7: the Obama campaign, but relatively small amounts for him, certainly, 253 00:12:51,360 --> 00:12:53,200 Speaker 7: like fifty thousand dollars I think was what he gave 254 00:12:53,280 --> 00:12:55,240 Speaker 7: to the Obama Victory Fund in two thousand and eight. 255 00:12:55,679 --> 00:12:58,600 Speaker 7: And he gave to politicians who could help his business estress, 256 00:12:58,640 --> 00:13:01,880 Speaker 7: whether it was SpaceX or ESLA. And now he's become 257 00:13:02,080 --> 00:13:04,960 Speaker 7: kind of much more of an ideological giver. The way 258 00:13:05,040 --> 00:13:08,439 Speaker 7: he talks about politics. You know, it's it's and I 259 00:13:08,520 --> 00:13:10,520 Speaker 7: think you see this kind of across the board. You know, 260 00:13:10,600 --> 00:13:13,839 Speaker 7: we did the story earlier on fair Shake the Crypto Superpack, 261 00:13:14,520 --> 00:13:18,599 Speaker 7: and you know it's supporting Democrats and Republicans based on 262 00:13:18,679 --> 00:13:21,120 Speaker 7: where you stand on Crypto. And one of the big 263 00:13:21,240 --> 00:13:25,880 Speaker 7: donors to that to Fairshake was a big Democratic donor 264 00:13:26,240 --> 00:13:29,640 Speaker 7: who got very angry when he found out that they 265 00:13:29,720 --> 00:13:31,800 Speaker 7: were going against Shared Brown because he says that the 266 00:13:31,840 --> 00:13:34,760 Speaker 7: cher Brown has to win his seat to hold the Senate, 267 00:13:34,840 --> 00:13:37,160 Speaker 7: and he stopped giving to the super pac. And I 268 00:13:37,200 --> 00:13:40,600 Speaker 7: think this kind of really shows how ideological and how 269 00:13:40,840 --> 00:13:43,920 Speaker 7: Democrat versus Republican and just kind of in the same 270 00:13:43,960 --> 00:13:47,760 Speaker 7: way that the country is really starkly divided, donors are 271 00:13:47,800 --> 00:13:50,840 Speaker 7: starkly divided between, you know, the visions for the country. 272 00:13:51,280 --> 00:13:54,280 Speaker 1: Bill big money versus small money. What's the story there? 273 00:13:54,600 --> 00:13:57,040 Speaker 1: Certainly the big money from folks like Elon Musk and 274 00:13:57,440 --> 00:14:01,360 Speaker 1: the Light get a lot of attention, But small money 275 00:14:01,440 --> 00:14:05,439 Speaker 1: donations have powered the Trump campaign in the past. How 276 00:14:05,520 --> 00:14:07,640 Speaker 1: did do this year and how did Harris' campaign do 277 00:14:07,720 --> 00:14:08,640 Speaker 1: with small money donors? 278 00:14:09,720 --> 00:14:12,800 Speaker 7: Actually, Harris's campaign is doing better, I mean with with Trump. 279 00:14:12,920 --> 00:14:16,079 Speaker 7: You know, in the past, he got much more support 280 00:14:16,160 --> 00:14:18,400 Speaker 7: from small dollar donors. I was giving less than two 281 00:14:18,480 --> 00:14:21,360 Speaker 7: hundred dollars in aggregate for the election. Maybe, you know, 282 00:14:21,480 --> 00:14:23,760 Speaker 7: it's not just people. If you give like ten dollars 283 00:14:24,200 --> 00:14:27,040 Speaker 7: twenty one times, you're a you're an itemized donor. So 284 00:14:27,120 --> 00:14:29,000 Speaker 7: he's gotten like a ton of support from people who 285 00:14:29,000 --> 00:14:32,440 Speaker 7: don't didn't give very much in both twenty sixteen and 286 00:14:32,600 --> 00:14:36,280 Speaker 7: twenty twenty, and much more from from millionaires this year. 287 00:14:36,400 --> 00:14:38,680 Speaker 7: It's it's the millionaires or people making donations of a 288 00:14:38,760 --> 00:14:41,120 Speaker 7: million dollars or more. Cause a lot of more billionaires 289 00:14:41,160 --> 00:14:44,040 Speaker 7: we're doing that. They're the ones who are really fueling 290 00:14:44,680 --> 00:14:48,920 Speaker 7: his campaign. He's his outside money. There's about I think 291 00:14:48,920 --> 00:14:52,200 Speaker 7: it's close to seven hundred million dollar dollars that are 292 00:14:52,240 --> 00:14:55,080 Speaker 7: in outside money going to super packs compared to about 293 00:14:55,080 --> 00:14:57,440 Speaker 7: three hundred and fifty million that he's raised for his campaign. 294 00:14:57,600 --> 00:15:01,400 Speaker 7: So he's doing much better now with wealth donors than 295 00:15:01,440 --> 00:15:04,080 Speaker 7: he is with the small dollar donors. Part of that 296 00:15:04,200 --> 00:15:07,760 Speaker 7: might be inflation that's hit his donor base, and part 297 00:15:07,800 --> 00:15:09,760 Speaker 7: of it might be that just you know, the appeal 298 00:15:09,880 --> 00:15:12,400 Speaker 7: isn't the same. You know, he's been hitting these people 299 00:15:12,680 --> 00:15:15,720 Speaker 7: up in the same people since, you know, since he 300 00:15:15,800 --> 00:15:18,720 Speaker 7: won the nomination in twenty sixteen. Yeah, and you know, 301 00:15:18,760 --> 00:15:20,280 Speaker 7: you wonder if he's gone to the well one too 302 00:15:20,320 --> 00:15:20,880 Speaker 7: many times. 303 00:15:21,760 --> 00:15:24,880 Speaker 3: Great stuff, Bill, Thank you, Thank you so much. Bill Allison, 304 00:15:24,920 --> 00:15:29,160 Speaker 3: Bloomberg News Campaign Finance reporter, joining us there from Washington, 305 00:15:29,280 --> 00:15:29,560 Speaker 3: d C. 306 00:15:31,400 --> 00:15:35,200 Speaker 6: You're listening to the Bloomberg Business Week podcast. Listen live 307 00:15:35,360 --> 00:15:37,960 Speaker 6: each weekday. He's starting at two pm Eastern on Apple 308 00:15:38,040 --> 00:15:40,920 Speaker 6: car Play and Android Auto with the Bloomberg Business Ad. 309 00:15:41,160 --> 00:15:44,000 Speaker 6: You can also listen live on Amazon Alexa from our 310 00:15:44,040 --> 00:15:48,360 Speaker 6: flagship New York station, Just say Alexa Play Bloomberg eleven thirty. 311 00:15:50,120 --> 00:15:52,520 Speaker 3: The other thing that is, you know, thinking about the election, 312 00:15:52,840 --> 00:15:54,360 Speaker 3: and I feel like it's safe to say that it's 313 00:15:54,360 --> 00:15:57,760 Speaker 3: been a big piece of the election, whether it's concerns 314 00:15:57,840 --> 00:16:01,720 Speaker 3: or actuality of it. Is just our own Bloomberg News 315 00:16:01,800 --> 00:16:05,680 Speaker 3: team reporting out how it has been permeating the US 316 00:16:05,760 --> 00:16:09,760 Speaker 3: presidential election on an unprecedented scale, with online instigators escalating 317 00:16:09,840 --> 00:16:13,120 Speaker 3: doubts about the integrity of the electoral process as millions 318 00:16:13,160 --> 00:16:15,800 Speaker 3: of Americans have been casting their ballots. So there's been 319 00:16:15,840 --> 00:16:18,880 Speaker 3: a big question tim about can you trust the vote? 320 00:16:19,080 --> 00:16:22,440 Speaker 1: And that's exactly that Bloomberg News technology reporter Austin Carr 321 00:16:23,160 --> 00:16:25,880 Speaker 1: tried to answer. He's set to figure it out. It's 322 00:16:25,920 --> 00:16:28,640 Speaker 1: all in his Bloomberg BusinessWeek story about how US voting 323 00:16:28,720 --> 00:16:31,920 Speaker 1: machines became safer than ever. Austin joins us from the 324 00:16:31,920 --> 00:16:35,600 Speaker 1: Bloomberg News bureau in Boston. Austin tell us about Chip 325 00:16:35,680 --> 00:16:40,600 Speaker 1: Troutbridge and the Clear Ballot Group. So Clear Ballot is 326 00:16:40,760 --> 00:16:43,480 Speaker 1: a startup that's based in Boston. It's about a decade 327 00:16:43,520 --> 00:16:46,200 Speaker 1: holl It's backed by Best Summer Ventures, and it's one 328 00:16:46,200 --> 00:16:49,160 Speaker 1: of the companies that's trying to compete with Dominion, the 329 00:16:49,280 --> 00:16:52,640 Speaker 1: sort of larger incumbent in the space, which you would 330 00:16:52,680 --> 00:16:55,920 Speaker 1: think would make them a very tech forward sort of 331 00:16:56,000 --> 00:16:58,960 Speaker 1: player in the voting machines. But it actually turns out 332 00:16:59,000 --> 00:17:00,720 Speaker 1: that I spent some time with the team. They're both 333 00:17:00,840 --> 00:17:03,320 Speaker 1: their office in Boston as well as their factory in 334 00:17:03,400 --> 00:17:05,639 Speaker 1: New Hampshire, and it turns out they're really pushing a 335 00:17:05,760 --> 00:17:09,440 Speaker 1: paper centric approach, just as a lot of election vendors 336 00:17:09,840 --> 00:17:13,040 Speaker 1: are doing themselves. It's actually turns out that paper marking 337 00:17:13,080 --> 00:17:15,960 Speaker 1: things physically and keeping an audit trail is incredibly safe, 338 00:17:16,119 --> 00:17:18,080 Speaker 1: and so a lot of the technology that's being invested 339 00:17:18,119 --> 00:17:21,280 Speaker 1: into this industry is really around tabulating votes rather than 340 00:17:21,359 --> 00:17:23,640 Speaker 1: changing actually how we're marking them in a very old 341 00:17:23,680 --> 00:17:26,080 Speaker 1: school way with pens and paper, so meaning that we 342 00:17:26,160 --> 00:17:28,919 Speaker 1: are going to be using paper ballots for the foreseeable future. 343 00:17:29,760 --> 00:17:30,080 Speaker 5: Correct. 344 00:17:30,160 --> 00:17:33,280 Speaker 8: I mean, it's really funny you hear. You hear a 345 00:17:33,320 --> 00:17:35,760 Speaker 8: lot of noise from you know, people like Elon Musk 346 00:17:35,840 --> 00:17:39,399 Speaker 8: saying that, you know, voting machines are super vulnerable to 347 00:17:39,440 --> 00:17:41,439 Speaker 8: hacking and connected to the Internet, and we should move 348 00:17:41,480 --> 00:17:43,520 Speaker 8: back to paper, and a lot of people I talk 349 00:17:43,560 --> 00:17:45,120 Speaker 8: to you say, you know what I mean, These voting 350 00:17:45,200 --> 00:17:48,040 Speaker 8: machines are, for the majority of them, are not connected 351 00:17:48,040 --> 00:17:50,359 Speaker 8: to the Internet, and about ninety eight percent of ballots 352 00:17:50,400 --> 00:17:53,200 Speaker 8: will be cast on paper tomorrow. So it's actually a 353 00:17:53,320 --> 00:17:56,200 Speaker 8: very paper centric approach, which I think sort of cuts 354 00:17:56,240 --> 00:17:57,760 Speaker 8: against a lot of the noise you hear around how 355 00:17:57,840 --> 00:18:01,600 Speaker 8: much hacking and manipulation and all these that are apparently 356 00:18:01,640 --> 00:18:03,879 Speaker 8: going to corrupt the election, just as they did in 357 00:18:03,960 --> 00:18:06,640 Speaker 8: twenty twenty from some of the more conspiratorial voices we heard. 358 00:18:06,680 --> 00:18:08,600 Speaker 3: All Right, so I'm just playing Devil's advocate. Why do 359 00:18:08,680 --> 00:18:10,840 Speaker 3: we care what Chip has to say? And what Clear 360 00:18:10,960 --> 00:18:13,680 Speaker 3: Ballot group has to say as we think about how 361 00:18:13,800 --> 00:18:15,399 Speaker 3: safe our voting process is. 362 00:18:16,400 --> 00:18:20,960 Speaker 8: So Chip Troutbridge is the CTO of Clear Ballot. He 363 00:18:21,080 --> 00:18:23,400 Speaker 8: came from a company called in Deco, which was later 364 00:18:23,440 --> 00:18:26,879 Speaker 8: acquired by Oracle. They're very good at data analytics, and 365 00:18:26,920 --> 00:18:30,000 Speaker 8: in fact Clear Ballot got it start auditing elections. What 366 00:18:30,080 --> 00:18:32,840 Speaker 8: their technology originally does is sort of scan all the 367 00:18:32,840 --> 00:18:35,440 Speaker 8: paper ballots. You know, when you get to a voting 368 00:18:35,480 --> 00:18:37,280 Speaker 8: booth and you mark it down with a sharpie and 369 00:18:37,280 --> 00:18:39,040 Speaker 8: a kind of gleat bleach to the paper. Maybe you 370 00:18:39,160 --> 00:18:41,399 Speaker 8: just check it off, maybe you scribble, maybe you're a 371 00:18:41,560 --> 00:18:45,120 Speaker 8: person who inadvertently circles the choice of the candidate you want. Well, 372 00:18:45,160 --> 00:18:48,200 Speaker 8: this technology scans all those ballots and provides a visualization 373 00:18:48,320 --> 00:18:50,200 Speaker 8: of all of them digitally, so if there are votes 374 00:18:50,240 --> 00:18:52,160 Speaker 8: that are a little bit less clear, they can actually 375 00:18:52,240 --> 00:18:54,320 Speaker 8: view them on a computer. But it's just sort of 376 00:18:55,000 --> 00:18:58,399 Speaker 8: a corresponding sort of representation, a digital image of the 377 00:18:58,480 --> 00:19:01,720 Speaker 8: physical paper ballot. That's just helping to speed up the 378 00:19:01,800 --> 00:19:03,879 Speaker 8: process so there aren't long delays when they have to 379 00:19:03,960 --> 00:19:06,320 Speaker 8: do recounts or post election audits. 380 00:19:07,680 --> 00:19:10,000 Speaker 3: No no, no, yes, and forgive me go ahead, please? 381 00:19:11,080 --> 00:19:14,680 Speaker 8: Oh just so the longer there is between sort of 382 00:19:14,920 --> 00:19:17,560 Speaker 8: the time that votes are cast and when election results 383 00:19:17,560 --> 00:19:20,320 Speaker 8: are given, that's what a lot of conspiracies fill that void. 384 00:19:20,400 --> 00:19:24,000 Speaker 8: People start thinking something must be nefarious happening when actuality 385 00:19:24,080 --> 00:19:26,080 Speaker 8: is just there's a lot of bureaucracy and slow moving 386 00:19:26,840 --> 00:19:29,920 Speaker 8: of mechanisms that keep canvassing very slow. So this technology 387 00:19:29,960 --> 00:19:31,320 Speaker 8: is designed to speed it up and make it a 388 00:19:31,359 --> 00:19:33,960 Speaker 8: lot faster. But again it's still fundamentally a paper based 389 00:19:34,440 --> 00:19:35,119 Speaker 8: voting system. 390 00:19:35,200 --> 00:19:37,480 Speaker 3: So if paper based is the thing, I mean the idea, 391 00:19:38,440 --> 00:19:40,760 Speaker 3: is hanging chads something that we have to be worried 392 00:19:40,760 --> 00:19:42,800 Speaker 3: about in the future. We all remember or not everybody 393 00:19:42,840 --> 00:19:45,360 Speaker 3: maybe remembers, right, it's twenty twenty four. That was back 394 00:19:45,400 --> 00:19:49,440 Speaker 3: in two thousand, but that was quite a fiasco, unexpected 395 00:19:50,520 --> 00:19:53,960 Speaker 3: and some say we it played out differently, we might 396 00:19:54,000 --> 00:19:55,480 Speaker 3: have had a different president in the White House. But 397 00:19:55,880 --> 00:19:58,200 Speaker 3: do we have to be worried about something like hanging chads? Though? 398 00:19:59,119 --> 00:20:03,440 Speaker 8: No, so that actually after the two thousand Florida fiasco. 399 00:20:03,680 --> 00:20:05,800 Speaker 8: Those were based on mechanical levers. So those are the 400 00:20:05,880 --> 00:20:08,640 Speaker 8: punch cards that you have, those hanging chads from physically 401 00:20:08,920 --> 00:20:11,640 Speaker 8: punching in. This is just your marking a ballot. There's 402 00:20:11,680 --> 00:20:14,440 Speaker 8: basically two approaches. You're marking a ballot with a sharpie, 403 00:20:14,600 --> 00:20:16,840 Speaker 8: then you submit it into a scanner. It keeps the paper, 404 00:20:17,080 --> 00:20:19,680 Speaker 8: and then the tabulator just provides a digital image of 405 00:20:19,720 --> 00:20:22,600 Speaker 8: it and just counts it. The other system that Dominion 406 00:20:23,040 --> 00:20:25,680 Speaker 8: has gotten some controversy for is a touch screen. You 407 00:20:25,920 --> 00:20:28,040 Speaker 8: enter your choices and then it prints out the physical 408 00:20:28,080 --> 00:20:31,800 Speaker 8: ballot and that's what you submit. It has your candidates 409 00:20:31,840 --> 00:20:34,720 Speaker 8: that you selected printed out with clear legible texts. You 410 00:20:34,800 --> 00:20:37,119 Speaker 8: can review it. There's a QR code that the scanner 411 00:20:37,160 --> 00:20:39,480 Speaker 8: scans and that's what you submit. So both their paper 412 00:20:39,520 --> 00:20:42,560 Speaker 8: based approaches and that represents about ninety eight percent of voting. 413 00:20:42,800 --> 00:20:45,120 Speaker 8: But again, unless you're really messing with your sharpie, i'd 414 00:20:45,160 --> 00:20:48,480 Speaker 8: say the vast majority of votes are inputed pretty properly. Again, 415 00:20:48,640 --> 00:20:50,440 Speaker 8: I'm not questioning your penmanship. I'm sure you're gonna do 416 00:20:50,480 --> 00:20:54,320 Speaker 8: a great job. But that's the fundamental issue is there's 417 00:20:54,359 --> 00:20:56,560 Speaker 8: no hanging chads. That's going to be the issue. It's 418 00:20:56,640 --> 00:21:01,720 Speaker 8: most likely disinformation registration issues and just sort of larger 419 00:21:01,800 --> 00:21:04,960 Speaker 8: disruption at the pole places themselves than actual hacking of 420 00:21:05,040 --> 00:21:06,840 Speaker 8: these these sort of computer tabulators. 421 00:21:07,320 --> 00:21:07,800 Speaker 3: Well, Austin. 422 00:21:07,840 --> 00:21:10,600 Speaker 1: What about the process of actually keeping track of how 423 00:21:10,680 --> 00:21:13,919 Speaker 1: many votes each candidate gets, because yes, you know, at 424 00:21:13,960 --> 00:21:17,400 Speaker 1: the precinct level, we understand that there are paper ballots, 425 00:21:17,440 --> 00:21:21,000 Speaker 1: but then when they're added up, that number gets sent 426 00:21:21,080 --> 00:21:24,360 Speaker 1: in some sort of format to a bigger place where 427 00:21:24,640 --> 00:21:26,960 Speaker 1: things are being kept tracked, where the stuff is being 428 00:21:27,000 --> 00:21:30,400 Speaker 1: kept track of. Is there any opportunity there for malfeasons? 429 00:21:31,200 --> 00:21:33,840 Speaker 8: Well, I think that the sort of physical safeguards and 430 00:21:34,119 --> 00:21:38,600 Speaker 8: redundancies that are in place make the process very slow 431 00:21:38,680 --> 00:21:41,560 Speaker 8: and hard to change, but also ironically makes it very safe. 432 00:21:42,040 --> 00:21:44,240 Speaker 8: And that's the one thing that I with the clear 433 00:21:44,320 --> 00:21:46,440 Speaker 8: Ballot CTO chip that I spent a lot of time 434 00:21:46,520 --> 00:21:49,880 Speaker 8: talking to just growing through all those mechanisms from sort 435 00:21:49,880 --> 00:21:51,960 Speaker 8: of you know, when they have to open these machines, 436 00:21:52,000 --> 00:21:54,679 Speaker 8: there's people from opposite political parties that have to unlock 437 00:21:54,720 --> 00:21:57,159 Speaker 8: the machines and tear off security seals to Actually, when 438 00:21:57,160 --> 00:22:00,199 Speaker 8: you're talking about transferring the vote counts of the end 439 00:22:00,200 --> 00:22:03,080 Speaker 8: of the night, those are sometimes transferred on a USB stick. 440 00:22:03,359 --> 00:22:07,120 Speaker 8: Now you might think, oh, couldn't that USB stick be switched, Well, again, 441 00:22:07,480 --> 00:22:10,000 Speaker 8: you'd have to. That would be quite a feat just 442 00:22:10,040 --> 00:22:11,639 Speaker 8: to get by all the people who are looking at 443 00:22:11,720 --> 00:22:15,119 Speaker 8: you'd somehow have to replace the USB stick, the logs 444 00:22:15,160 --> 00:22:16,600 Speaker 8: that you plug it in and out of a computer. 445 00:22:16,760 --> 00:22:19,320 Speaker 8: You'd have to change those. And then again, these ballots, 446 00:22:19,720 --> 00:22:23,240 Speaker 8: those are unofficial results. The physical ballots are the official count. 447 00:22:23,560 --> 00:22:27,760 Speaker 8: So even if you did change the sort of somehow 448 00:22:27,840 --> 00:22:30,639 Speaker 8: hacked into a USB stick that was being transferred to 449 00:22:30,720 --> 00:22:33,439 Speaker 8: a central location, I don't know, you'd have to corrupt 450 00:22:33,480 --> 00:22:35,920 Speaker 8: both the scans at the precinct and at a county level. 451 00:22:35,960 --> 00:22:38,400 Speaker 8: You'd have to replace the paper ballots. It's just there's 452 00:22:38,440 --> 00:22:42,720 Speaker 8: a lot of redundancies, analogue offline redundancies in place that 453 00:22:42,840 --> 00:22:45,120 Speaker 8: make it sort of fantastical and really hard to play 454 00:22:45,160 --> 00:22:48,399 Speaker 8: out this sort of scenario. I think we said in 455 00:22:48,480 --> 00:22:50,040 Speaker 8: the piece that it's not so much that you'd have 456 00:22:50,119 --> 00:22:53,600 Speaker 8: to have mission impossible cunning, but really the logistical omnipresence 457 00:22:53,600 --> 00:22:55,840 Speaker 8: of Santa Claus to pull off something like this at scale. 458 00:22:58,400 --> 00:23:01,679 Speaker 3: Yeah, yeah, exactly. Hey, Austin, thank you so much. Austin 459 00:23:01,760 --> 00:23:04,200 Speaker 3: Carr Technology or putter up Bloomberg New's joining us from 460 00:23:04,240 --> 00:23:06,800 Speaker 3: our Boston bureau. You can check out that story at 461 00:23:06,800 --> 00:23:09,840 Speaker 3: Bloomberg BusinessWeek story. You can find out more just head 462 00:23:09,880 --> 00:23:12,040 Speaker 3: to the Bloomberg terminal and at Bloomberg dot com. 463 00:23:18,720 --> 00:23:22,199 Speaker 6: You're listening to the Bloomberg Business Week podcast. Catch us 464 00:23:22,320 --> 00:23:25,520 Speaker 6: live weekday afternoons from two to five pm. Easter Listen 465 00:23:25,560 --> 00:23:28,880 Speaker 6: on Applecarplay and and Broyd Auto with a Bloomberg Business app, 466 00:23:29,040 --> 00:23:31,240 Speaker 6: or watch us live on YouTube. 467 00:23:33,119 --> 00:23:39,200 Speaker 4: Blomarco Journal, Now about you let me drive? 468 00:23:39,480 --> 00:23:40,920 Speaker 8: Oh no, no, no, no, please. 469 00:23:42,560 --> 00:23:46,760 Speaker 6: Honey, please travels, I want to drive. 470 00:23:49,280 --> 00:23:50,160 Speaker 5: The question. 471 00:23:53,720 --> 00:23:57,440 Speaker 6: This is the drive to the clothes? Do we'll buy 472 00:23:57,480 --> 00:23:58,240 Speaker 6: around it? 473 00:23:58,880 --> 00:24:02,439 Speaker 3: On Bloomberg Rady all right, everybody, we've got just about 474 00:24:03,040 --> 00:24:06,440 Speaker 3: eighteen minutes left to go until we wrap up the 475 00:24:06,480 --> 00:24:07,760 Speaker 3: trading day. Ways shaking your head. 476 00:24:07,880 --> 00:24:09,679 Speaker 1: That's time flies when you're having fun. 477 00:24:10,240 --> 00:24:11,359 Speaker 3: It's been a little bit crazy. 478 00:24:11,440 --> 00:24:13,680 Speaker 1: It's been a little crazy. Well, you know, part of 479 00:24:13,760 --> 00:24:15,560 Speaker 1: it is just because things are crazy right now. 480 00:24:15,720 --> 00:24:17,800 Speaker 3: Yeah, it is. I think you can feel, you know, 481 00:24:17,880 --> 00:24:19,920 Speaker 3: it feels like a day before an election. Actually, I 482 00:24:19,960 --> 00:24:22,320 Speaker 3: want to say it feels like a day before a 483 00:24:23,960 --> 00:24:28,040 Speaker 3: very close election based on polling and where things have 484 00:24:28,280 --> 00:24:31,280 Speaker 3: changed dramatically. It's been an unusual election cycle to say 485 00:24:31,320 --> 00:24:34,280 Speaker 3: the least. And so yeah, here we are and a 486 00:24:34,320 --> 00:24:36,639 Speaker 3: market that's been bouncing around. We were just talking with 487 00:24:36,720 --> 00:24:39,160 Speaker 3: our Bill Maloney here about what brought the markets down 488 00:24:39,240 --> 00:24:43,120 Speaker 3: around eleven o'clock or so, and a story I think 489 00:24:43,119 --> 00:24:46,440 Speaker 3: it was in the Wall Street Journal or the Washington Post. No, 490 00:24:46,480 --> 00:24:49,680 Speaker 3: it's the Journal. It was a journal forgive me about 491 00:24:50,440 --> 00:24:56,000 Speaker 3: Russia maybe putting some devices, in sundiary devices into some 492 00:24:56,160 --> 00:24:57,960 Speaker 3: planes coming into the United States. 493 00:24:58,080 --> 00:24:58,240 Speaker 6: Yeah. 494 00:24:58,280 --> 00:25:00,800 Speaker 1: Reading from the journal, Western security officials they believe that too, 495 00:25:00,840 --> 00:25:03,440 Speaker 1: and sendiary devices shipped via DHL. We're part of a 496 00:25:03,560 --> 00:25:06,520 Speaker 1: covert Russian operation that ultimately aimed to start fires aboard 497 00:25:06,560 --> 00:25:09,119 Speaker 1: cargo or passenger aircraft flying to the US and Canada. 498 00:25:09,480 --> 00:25:12,399 Speaker 1: This is Moscow steps up a sabotage campaign against Washington. 499 00:25:12,520 --> 00:25:16,680 Speaker 3: Yeah, the devices ignited DHL logistics hubs in July, one 500 00:25:16,960 --> 00:25:20,639 Speaker 3: in Germany, another in England. The explosion set off a 501 00:25:20,720 --> 00:25:23,639 Speaker 3: multinational race to find the culprits. So just you know, 502 00:25:23,720 --> 00:25:26,280 Speaker 3: stuff going on behind the scenes. And so anyway, that 503 00:25:26,480 --> 00:25:28,600 Speaker 3: was Bill's thinking that would dragged the market. 504 00:25:28,440 --> 00:25:31,360 Speaker 1: Down, not just an election to contend with. So Kara 505 00:25:31,480 --> 00:25:34,720 Speaker 1: Murphy's chief investment officer at Kestra Investment Management. Kara joins 506 00:25:34,800 --> 00:25:38,680 Speaker 1: us from Austin, Texas. Right now, Kara, what are you 507 00:25:38,840 --> 00:25:41,359 Speaker 1: hearing from clients as we get closer and closer to 508 00:25:41,440 --> 00:25:42,080 Speaker 1: election day. 509 00:25:41,960 --> 00:25:45,879 Speaker 9: Tomorrow, there's a lot of hand ringing. And you know, 510 00:25:45,960 --> 00:25:47,600 Speaker 9: when I think back to the beginning of the year, 511 00:25:47,760 --> 00:25:49,680 Speaker 9: we were sort of prepping ourselves to get ready to 512 00:25:49,760 --> 00:25:51,920 Speaker 9: talk a lot about elections, and at that time people 513 00:25:52,000 --> 00:25:54,359 Speaker 9: were like, oh, we're not really focusing on it. But 514 00:25:54,600 --> 00:25:57,399 Speaker 9: over the last couple of months that has very definitely changed. 515 00:25:57,440 --> 00:25:59,480 Speaker 9: There's a lot of concern and it doesn't matter what 516 00:25:59,560 --> 00:26:01,720 Speaker 9: side of the that you're on, and so we've just 517 00:26:01,800 --> 00:26:04,960 Speaker 9: been repeating the mantra that go vote, it's important, but 518 00:26:05,080 --> 00:26:07,119 Speaker 9: it's not necessarily important for your portfolio. 519 00:26:07,760 --> 00:26:11,520 Speaker 3: Well that's interesting. So are you anticipating I don't know 520 00:26:11,600 --> 00:26:13,840 Speaker 3: when we have the election outcome that you're going to 521 00:26:13,880 --> 00:26:16,000 Speaker 3: get a lot of calls of investors saying, hey, now 522 00:26:16,040 --> 00:26:18,159 Speaker 3: we're thinking, all right, we know what's going on, we 523 00:26:18,240 --> 00:26:21,760 Speaker 3: know what the composition of Congress is, We're going to 524 00:26:21,800 --> 00:26:24,320 Speaker 3: start making some changes. Is that what's going to happen 525 00:26:24,440 --> 00:26:25,400 Speaker 3: or not necessarily? 526 00:26:26,760 --> 00:26:28,480 Speaker 9: Well, I think we all look forward to the time 527 00:26:28,560 --> 00:26:30,680 Speaker 9: when we know what the composition of Congress and the 528 00:26:30,720 --> 00:26:33,000 Speaker 9: White House looks like. So we're all excited about when 529 00:26:33,080 --> 00:26:35,560 Speaker 9: that will happen, But I think no, for most people, 530 00:26:35,640 --> 00:26:38,000 Speaker 9: it's really about getting back to that conversation, what are 531 00:26:38,040 --> 00:26:40,800 Speaker 9: your long term goals, what's the long term trajectory of 532 00:26:40,960 --> 00:26:43,280 Speaker 9: the US economy, what's corporate earnings power? 533 00:26:43,440 --> 00:26:43,560 Speaker 1: Right? 534 00:26:43,840 --> 00:26:46,439 Speaker 9: So I think the conversation shifts from what's happening at 535 00:26:46,440 --> 00:26:48,480 Speaker 9: the ballot box to what are those things that are 536 00:26:48,520 --> 00:26:50,320 Speaker 9: really important for stocks and bonds? 537 00:26:51,400 --> 00:26:52,240 Speaker 1: What are those things? 538 00:26:53,480 --> 00:26:56,240 Speaker 9: So earnings, right, that's a big one, and we're in 539 00:26:56,280 --> 00:26:58,480 Speaker 9: the thick of earning season right now. Last week we 540 00:26:58,560 --> 00:27:02,040 Speaker 9: had five of this of the seven reporting, and i'm 541 00:27:02,200 --> 00:27:04,760 Speaker 9: incredibly important for the near term move in the market. 542 00:27:04,840 --> 00:27:07,000 Speaker 9: And what was interesting is that we saw with those 543 00:27:07,160 --> 00:27:11,359 Speaker 9: individual companies pretty good reports on both earnings and revenues, 544 00:27:11,760 --> 00:27:14,560 Speaker 9: but the stocks didn't perform so well. And I think 545 00:27:14,600 --> 00:27:17,480 Speaker 9: that's because what we're seeing right now is the beginning 546 00:27:17,600 --> 00:27:20,800 Speaker 9: of this handoff from the mag seven, which has driven 547 00:27:20,840 --> 00:27:25,040 Speaker 9: the market for the last two ish years to everybody else. 548 00:27:25,520 --> 00:27:27,119 Speaker 9: And we need to start to see some of that 549 00:27:27,280 --> 00:27:29,920 Speaker 9: earnings pick up into next year for some of those 550 00:27:29,960 --> 00:27:32,720 Speaker 9: smaller names in order to be able to sustain this rally, 551 00:27:32,760 --> 00:27:35,119 Speaker 9: which we think will happen. But it's the sort of 552 00:27:35,200 --> 00:27:36,400 Speaker 9: delicate handoff. 553 00:27:36,400 --> 00:27:38,359 Speaker 3: In the meantime, you know, when it comes to something like, 554 00:27:38,520 --> 00:27:42,080 Speaker 3: as you said, earnings fundamentals, these are all important, you know, recession, 555 00:27:42,240 --> 00:27:45,000 Speaker 3: no recession. Do you think it matters who's in the 556 00:27:45,040 --> 00:27:47,480 Speaker 3: White House or do you think something like that For 557 00:27:47,560 --> 00:27:52,119 Speaker 3: the US economy specifically, it doesn't matter who's in the 558 00:27:52,160 --> 00:27:54,720 Speaker 3: White House whether or not we dip into a recession, 559 00:27:54,800 --> 00:27:56,000 Speaker 3: maybe sooner rather than later. 560 00:27:56,920 --> 00:27:59,879 Speaker 9: I think it would be rare that a policy does 561 00:28:00,000 --> 00:28:03,520 Speaker 9: decision would trip the whole economy into recession. So certainly 562 00:28:03,560 --> 00:28:06,520 Speaker 9: there are certain economic policies that have a big impact 563 00:28:06,600 --> 00:28:09,360 Speaker 9: on certain areas of the economy. But when you think 564 00:28:09,400 --> 00:28:12,159 Speaker 9: about what's driven you know, the last few recessions, they 565 00:28:12,200 --> 00:28:16,159 Speaker 9: were big, huge macro events that were not driven by policies. 566 00:28:16,240 --> 00:28:20,879 Speaker 9: Think COVID, global financial crisis, bursting of the Internet bubble. 567 00:28:20,960 --> 00:28:23,800 Speaker 9: These are things that had very far reaching effects that 568 00:28:23,920 --> 00:28:25,640 Speaker 9: were not driven by a single individual. 569 00:28:26,119 --> 00:28:28,240 Speaker 3: How about though, if you've got, you know, a candidate 570 00:28:28,720 --> 00:28:31,679 Speaker 3: who might want to tinker with the Federal Reserve. 571 00:28:33,119 --> 00:28:33,760 Speaker 5: So I think the. 572 00:28:33,840 --> 00:28:37,720 Speaker 9: Federal Reserve and the independence of those policy decisions is 573 00:28:38,000 --> 00:28:41,440 Speaker 9: really critical to keeping the economy on solid footing. And 574 00:28:41,520 --> 00:28:43,360 Speaker 9: I often say that, you know, the part of the 575 00:28:43,400 --> 00:28:45,440 Speaker 9: reason why I don't worry so much about who's in 576 00:28:45,520 --> 00:28:48,560 Speaker 9: the White House is because we are very fortunate to 577 00:28:48,680 --> 00:28:52,600 Speaker 9: live in the United States that has very strong political institutions. Now, 578 00:28:52,720 --> 00:28:55,480 Speaker 9: typically the Federal Reserve is not included in those, but 579 00:28:55,600 --> 00:28:58,800 Speaker 9: from an economic perspective, the Federal Reserve and its independence 580 00:28:58,920 --> 00:29:01,640 Speaker 9: is really critical to being able to write the ship 581 00:29:01,760 --> 00:29:04,120 Speaker 9: and be able to help manage the volatility and the 582 00:29:04,160 --> 00:29:05,040 Speaker 9: economic cycle. 583 00:29:05,840 --> 00:29:09,800 Speaker 1: Okay, so help us think past the election, because I 584 00:29:09,840 --> 00:29:11,239 Speaker 1: think a lot of us are focused too. 585 00:29:11,840 --> 00:29:12,040 Speaker 3: Yeah. 586 00:29:12,640 --> 00:29:15,280 Speaker 1: I mean, one thing that we've been hearing from folks 587 00:29:15,400 --> 00:29:18,320 Speaker 1: like you is that, Okay, maybe the risk isn't necessarily 588 00:29:18,920 --> 00:29:23,680 Speaker 1: with the presidential election. It's with who else is elected 589 00:29:23,720 --> 00:29:25,080 Speaker 1: in terms of the House and the Senate and the 590 00:29:25,120 --> 00:29:28,240 Speaker 1: makeup there. But also how long this drags on for 591 00:29:29,000 --> 00:29:31,680 Speaker 1: And I'm wondering what happens to the markets if it 592 00:29:31,760 --> 00:29:32,240 Speaker 1: drags on. 593 00:29:34,520 --> 00:29:34,800 Speaker 3: Again. 594 00:29:34,840 --> 00:29:36,400 Speaker 9: I mean, this gets back to the strength of the 595 00:29:36,520 --> 00:29:39,560 Speaker 9: US institutions. And I was looking back at this earlier today, 596 00:29:39,800 --> 00:29:43,120 Speaker 9: and we've had occasions where we didn't know who the 597 00:29:43,280 --> 00:29:45,960 Speaker 9: official was or what the makeup of Congress was for 598 00:29:46,120 --> 00:29:49,240 Speaker 9: some time. So we can actually manage through those things 599 00:29:49,360 --> 00:29:52,440 Speaker 9: fairly well. And I think you know, even we hear 600 00:29:52,480 --> 00:29:56,480 Speaker 9: a lot about you know, blue sweep or red sweep 601 00:29:56,560 --> 00:29:58,640 Speaker 9: on one side or the other. And I think even 602 00:29:58,680 --> 00:30:01,440 Speaker 9: in those instances where we have one party takes all, 603 00:30:02,040 --> 00:30:04,040 Speaker 9: all of the margins are going to be raised or thin, 604 00:30:04,200 --> 00:30:06,960 Speaker 9: whether it's the White House, House of Representatives, or Senate, 605 00:30:07,400 --> 00:30:10,000 Speaker 9: that even once we get those numbers, there's not all 606 00:30:10,080 --> 00:30:11,680 Speaker 9: that much that's going to be able to get done 607 00:30:11,760 --> 00:30:13,920 Speaker 9: because no party is going to have that strong a 608 00:30:14,000 --> 00:30:16,080 Speaker 9: majority in any one of those institutions. 609 00:30:16,320 --> 00:30:19,040 Speaker 3: Anything interesting that you're noticing in terms of investment flows 610 00:30:19,720 --> 00:30:22,520 Speaker 3: coming in coming out for some of your client base, 611 00:30:24,000 --> 00:30:25,840 Speaker 3: So it's been interesting. 612 00:30:25,920 --> 00:30:27,880 Speaker 9: So there have been some people who have been sort 613 00:30:27,880 --> 00:30:32,000 Speaker 9: of positioning for a really dire situation, right moving more 614 00:30:32,080 --> 00:30:34,360 Speaker 9: into commodities in order to be able to hedge against 615 00:30:34,360 --> 00:30:37,960 Speaker 9: a really sort of volatile outcome coming out of tomorrow. 616 00:30:38,240 --> 00:30:40,440 Speaker 9: But for the most part, what we see is that 617 00:30:40,520 --> 00:30:42,840 Speaker 9: people are able to sort of pick themselves up out 618 00:30:42,880 --> 00:30:45,720 Speaker 9: of the election results tomorrow and look beyond that and 619 00:30:45,760 --> 00:30:47,720 Speaker 9: start thinking about what's right for them and their long 620 00:30:47,800 --> 00:30:48,280 Speaker 9: term goals. 621 00:30:48,360 --> 00:30:52,040 Speaker 3: All right, So I am Tim and I are both 622 00:30:52,120 --> 00:30:55,840 Speaker 3: looking beyond the results, and we're thinking about, Yes, the 623 00:30:55,920 --> 00:30:59,520 Speaker 3: FED meeting very important this week, but also Nvidia earnings 624 00:30:59,560 --> 00:31:01,520 Speaker 3: which come at the end of this month. How big 625 00:31:01,600 --> 00:31:03,400 Speaker 3: a deal is that for you in terms of how 626 00:31:03,440 --> 00:31:06,680 Speaker 3: you think about sentiment, market sentiment and a big investment 627 00:31:06,720 --> 00:31:09,000 Speaker 3: play which has been AI for the last you know, 628 00:31:09,080 --> 00:31:10,880 Speaker 3: we're coming up almost on two years, but easily a 629 00:31:11,000 --> 00:31:13,120 Speaker 3: year and a half. Yeah, for sure. 630 00:31:13,160 --> 00:31:15,320 Speaker 9: I mean, this is one name that has largely carried 631 00:31:15,320 --> 00:31:17,440 Speaker 9: the market for almost two years and has become this 632 00:31:17,600 --> 00:31:20,720 Speaker 9: bellweather as you suggested, for AI and its implications in 633 00:31:20,760 --> 00:31:23,360 Speaker 9: the broader economy. And so I think if last week 634 00:31:23,480 --> 00:31:26,280 Speaker 9: was any lesson it's that Nvidia has to come out 635 00:31:26,400 --> 00:31:30,480 Speaker 9: and not just be positive on revenues and earnings in 636 00:31:30,520 --> 00:31:33,240 Speaker 9: the rearview mirror, but also has to be positive going forward. 637 00:31:33,280 --> 00:31:36,000 Speaker 9: And so certainly all eyes will be on that earnings report. 638 00:31:36,320 --> 00:31:39,080 Speaker 3: All right, good stuff, Thank you so much, Kara, look 639 00:31:39,160 --> 00:31:41,640 Speaker 3: forward to talking to you next time. Kara Murphy, Chief 640 00:31:41,680 --> 00:31:45,800 Speaker 3: investment Officer Kestra Investment Management, joining us from Austin, Texas. 641 00:31:46,440 --> 00:31:49,680 Speaker 6: This is the Bloomberg Business Week Podcast. 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