1 00:00:02,640 --> 00:00:05,320 Speaker 1: Welcome to the Bloomberg Penl podcast on Paul Swing You. 2 00:00:05,360 --> 00:00:07,680 Speaker 1: Along with my co host Lisa Brahma Waits, each day 3 00:00:07,720 --> 00:00:10,240 Speaker 1: we bring you the most noteworthy and useful interviews for 4 00:00:10,280 --> 00:00:12,520 Speaker 1: you and your money, whether at the grocery store or 5 00:00:12,560 --> 00:00:15,480 Speaker 1: the trading floor. Find a Bloomberg Penl podcast on Apple 6 00:00:15,520 --> 00:00:17,960 Speaker 1: podcast or wherever you listen to podcasts, as well as 7 00:00:17,960 --> 00:00:22,919 Speaker 1: at Bloomberg dot com. Ford announced that it will eliminate 8 00:00:22,960 --> 00:00:28,160 Speaker 1: about twenty percent of its workforce across Europe, closing six factories, 9 00:00:28,640 --> 00:00:31,960 Speaker 1: with some in Germany. The shares of the company up 10 00:00:32,120 --> 00:00:36,519 Speaker 1: two point two percent. UH, sort of showing how markets 11 00:00:36,520 --> 00:00:40,200 Speaker 1: are viewing this cut jobs as you try to streamline 12 00:00:40,200 --> 00:00:42,839 Speaker 1: your business, and they've been dealing with a host of 13 00:00:42,840 --> 00:00:45,519 Speaker 1: issues in Europe in particular. Joining us now to get 14 00:00:45,520 --> 00:00:49,360 Speaker 1: a sense of the implications of this announcement. David Kudla, 15 00:00:49,600 --> 00:00:53,479 Speaker 1: chief executive officer and chief investment strategist at Mainstay Capital 16 00:00:53,520 --> 00:00:57,240 Speaker 1: Management with two and a half billion dollars under management, UH, 17 00:00:57,440 --> 00:01:01,400 Speaker 1: sailing from Michigan, where for is based. Thank you so 18 00:01:01,480 --> 00:01:03,440 Speaker 1: much for being with us. David. We love having you on. 19 00:01:03,720 --> 00:01:06,119 Speaker 1: So let's just start with what was your initial knee 20 00:01:06,160 --> 00:01:09,440 Speaker 1: jerk reaction to Ford's announcement this morning about the job cuts. 21 00:01:10,360 --> 00:01:13,560 Speaker 1: Good morning, Lisa, Well we expected this, we knew this 22 00:01:13,640 --> 00:01:18,399 Speaker 1: was coming. We've seen forward U continued to streamline, streamline 23 00:01:18,440 --> 00:01:23,839 Speaker 1: operations in Europe. The market there is weak overall, and 24 00:01:24,640 --> 00:01:31,720 Speaker 1: uh Ford, like GM, has UH the problem of working 25 00:01:31,720 --> 00:01:35,480 Speaker 1: in that middle market, selling in that middle market with 26 00:01:35,520 --> 00:01:38,520 Speaker 1: a lot of their products. There's a weak market overall. 27 00:01:39,120 --> 00:01:42,440 Speaker 1: UH they have strength in commercial vehicles, but they're not 28 00:01:42,520 --> 00:01:45,320 Speaker 1: in the luxury car market where the money is made 29 00:01:45,319 --> 00:01:48,360 Speaker 1: in Europe, and that's the problem they suffer from. And 30 00:01:48,400 --> 00:01:52,920 Speaker 1: so where General Motors decided finally to just exit by 31 00:01:52,920 --> 00:01:56,559 Speaker 1: selling their Opal unit, uh Ford is trying to stay there, 32 00:01:56,640 --> 00:01:58,040 Speaker 1: and the only way they can stay there is to 33 00:01:58,120 --> 00:02:01,640 Speaker 1: continue to restructure, restructure, structure, and we're seeing another big, 34 00:02:01,680 --> 00:02:04,080 Speaker 1: big step in that direction. It's interesting, Dave, that you 35 00:02:04,080 --> 00:02:07,200 Speaker 1: mentioned GM and OPAL and I look at the stock 36 00:02:07,240 --> 00:02:09,919 Speaker 1: today and I'm sure you know stock called does clearly 37 00:02:10,360 --> 00:02:13,919 Speaker 1: like this move here. Do you think Ford is considering 38 00:02:14,240 --> 00:02:16,440 Speaker 1: doing a GM and just kind of getting out of 39 00:02:16,480 --> 00:02:18,880 Speaker 1: the European market just seems so brutal to make a 40 00:02:18,880 --> 00:02:22,359 Speaker 1: profit there. It is brutal to make a profit there. 41 00:02:22,760 --> 00:02:26,280 Speaker 1: If you look, you know the the economic situation, the 42 00:02:26,280 --> 00:02:31,960 Speaker 1: political environment, regulatory environment in Europe, the the the current 43 00:02:32,280 --> 00:02:35,400 Speaker 1: economic environment in Europe, and you know the trouble that 44 00:02:35,440 --> 00:02:39,360 Speaker 1: American automakers have had competing there. It's a very different 45 00:02:39,360 --> 00:02:42,839 Speaker 1: market from the US. And the strength of American automakers 46 00:02:43,040 --> 00:02:48,240 Speaker 1: is um in in trucks UH and subs large trucks 47 00:02:48,600 --> 00:02:51,280 Speaker 1: which don't which don't sell there. They're not they're not made, 48 00:02:51,320 --> 00:02:55,360 Speaker 1: they're not popular in Europe, and so UH. You know, 49 00:02:55,440 --> 00:02:58,080 Speaker 1: the money that's made in Europe is in luxury cars 50 00:02:58,639 --> 00:03:03,440 Speaker 1: and in commercial vehicles. Now Ford has strength and commercial vehicles. 51 00:03:03,440 --> 00:03:06,079 Speaker 1: They have a partnership with BW that they're they're doing 52 00:03:06,160 --> 00:03:09,600 Speaker 1: quite well with, but not really in the luxury vehicle 53 00:03:09,680 --> 00:03:13,200 Speaker 1: segment that belongs to the luxury brands there in Europe, 54 00:03:13,240 --> 00:03:16,320 Speaker 1: and and some some others that are imported UH. In 55 00:03:16,360 --> 00:03:19,239 Speaker 1: that middle market that that's where you can struggle. But 56 00:03:19,360 --> 00:03:22,560 Speaker 1: they do in the suv market, the Kuga that's sold 57 00:03:22,639 --> 00:03:25,720 Speaker 1: over hundred fifty thou units last year at the Ecosport 58 00:03:25,760 --> 00:03:28,200 Speaker 1: over a hundred thousand units last year. They have some 59 00:03:28,240 --> 00:03:33,280 Speaker 1: strength there. So the way they're streamlining now with the 60 00:03:33,320 --> 00:03:36,120 Speaker 1: three divisions are going from there talking about maybe bringing 61 00:03:36,160 --> 00:03:39,440 Speaker 1: in some you know, an iconic brand with the Mustang. 62 00:03:40,040 --> 00:03:43,120 Speaker 1: There might be some opportunity there, small opportunity in niche market, 63 00:03:43,160 --> 00:03:47,000 Speaker 1: but the uh, this streamlining I think has some potential, 64 00:03:47,040 --> 00:03:49,480 Speaker 1: but it's it's just a difficult market, I think for 65 00:03:49,480 --> 00:03:52,400 Speaker 1: an American automaker, how do we sort of view the 66 00:03:52,440 --> 00:03:56,000 Speaker 1: difficulties in the European auto market and lou in light 67 00:03:56,040 --> 00:03:58,600 Speaker 1: of some of the trade tensions and the global slow 68 00:03:58,680 --> 00:04:01,600 Speaker 1: down in growth up more generally, I mean, is this 69 00:04:01,720 --> 00:04:05,200 Speaker 1: a part of that story or is this idiosyncratic having 70 00:04:05,200 --> 00:04:08,120 Speaker 1: to do with the models that are popular and regulations 71 00:04:08,240 --> 00:04:12,040 Speaker 1: and just the sort of entrenchment of local companies there. 72 00:04:13,320 --> 00:04:16,440 Speaker 1: Well that you know, that's the other part of it. Uh. 73 00:04:16,520 --> 00:04:19,080 Speaker 1: You know, one of the the announcements with this is 74 00:04:19,120 --> 00:04:23,920 Speaker 1: that they that that four expects to more than triple 75 00:04:24,000 --> 00:04:30,000 Speaker 1: their passenger vehicle imports into Europe annually by And if 76 00:04:30,000 --> 00:04:33,160 Speaker 1: you're going to triple your passenger vehicle imports into Europe annually, 77 00:04:34,760 --> 00:04:37,680 Speaker 1: you need a favorable trade environment to do that, and 78 00:04:38,120 --> 00:04:43,120 Speaker 1: the current administration is made at quite difficult. So, uh, 79 00:04:43,160 --> 00:04:46,920 Speaker 1: you know, you have entrenched brands there that are are 80 00:04:47,279 --> 00:04:50,640 Speaker 1: there is a lot of brand loyalty on that continent. UH, 81 00:04:50,680 --> 00:04:53,120 Speaker 1: and I think that's where there's been difficulty with you know, 82 00:04:53,160 --> 00:04:55,159 Speaker 1: some of the brands that import there. But now you 83 00:04:55,200 --> 00:04:58,880 Speaker 1: have these artificial barriers or let's call them real barriers, 84 00:04:59,040 --> 00:05:03,240 Speaker 1: barriers with uh, the the trade wars that are coming 85 00:05:03,279 --> 00:05:05,320 Speaker 1: up in the tariffs that that keep popping their head up, 86 00:05:05,400 --> 00:05:08,240 Speaker 1: or threats of terrorists that keep popping their head up. So, David, 87 00:05:08,279 --> 00:05:11,240 Speaker 1: I know in the States there's a growing discussion about 88 00:05:11,279 --> 00:05:15,360 Speaker 1: whether we have reached a peak auto in the US 89 00:05:15,520 --> 00:05:19,719 Speaker 1: art there's similar discussions in Europe like that. There's similar 90 00:05:19,720 --> 00:05:24,000 Speaker 1: discussions like that. But the concern in in in Europe 91 00:05:24,080 --> 00:05:27,479 Speaker 1: is is that is that auto sales have just been 92 00:05:27,920 --> 00:05:30,719 Speaker 1: stagnant really for for quite some time because of the 93 00:05:30,760 --> 00:05:35,440 Speaker 1: economic conditions. And for you know, GM before this and 94 00:05:35,640 --> 00:05:38,480 Speaker 1: Ford for years have just been operating at a loss. 95 00:05:38,520 --> 00:05:41,600 Speaker 1: They've had very few years over many years where they've 96 00:05:41,600 --> 00:05:45,800 Speaker 1: had a profit. Ford had a four million dollar loss 97 00:05:45,880 --> 00:05:50,520 Speaker 1: last year. And in Europe and we'll probably again this year, 98 00:05:51,120 --> 00:05:54,680 Speaker 1: UH with this restructuring. UH. As we get you know, 99 00:05:54,800 --> 00:05:57,120 Speaker 1: down the road, that may help, but it is just 100 00:05:57,200 --> 00:05:59,760 Speaker 1: a market where there have been more years in recent 101 00:05:59,839 --> 00:06:03,160 Speaker 1: year years many more years have lost than profit, and 102 00:06:03,240 --> 00:06:05,279 Speaker 1: you know, how many do you sustain that? And I 103 00:06:05,320 --> 00:06:08,680 Speaker 1: think that's why GM finally decided to cut the cord 104 00:06:08,760 --> 00:06:11,840 Speaker 1: with their Oval unit. David Couldla, thank you so much. 105 00:06:11,920 --> 00:06:15,240 Speaker 1: David is the chief executive officer and chief investment strategist 106 00:06:15,279 --> 00:06:18,400 Speaker 1: at main Stake Capital Management based in Michigan, and we 107 00:06:18,560 --> 00:06:20,600 Speaker 1: love to have him on talking about the auto industry. 108 00:06:20,600 --> 00:06:22,839 Speaker 1: He's really plugged in there and it's just a big, 109 00:06:22,880 --> 00:06:38,240 Speaker 1: big issue for the US automakers. In Europe, we have 110 00:06:38,480 --> 00:06:42,039 Speaker 1: the Democratic debates underway. Tonight is the second night of 111 00:06:42,240 --> 00:06:46,320 Speaker 1: a to night extravaganza with twenty candidates at meeting, joining 112 00:06:46,360 --> 00:06:47,960 Speaker 1: us down to talk about what we heard last night. 113 00:06:48,040 --> 00:06:51,360 Speaker 1: Chris Leu, former Deputy Secretary of Labor under President Obama 114 00:06:51,600 --> 00:06:55,120 Speaker 1: and senior fellow at the University of Virginia's Miller Center. Chris, 115 00:06:55,200 --> 00:06:57,640 Speaker 1: thank you so much for being with us. First of all, 116 00:06:57,680 --> 00:06:59,919 Speaker 1: i'd love to get your impression of last night's debate. 117 00:07:00,000 --> 00:07:02,720 Speaker 1: What was your thought? Well, you know, it's pretty much 118 00:07:02,760 --> 00:07:05,400 Speaker 1: what I expected. And it is one of the challenges 119 00:07:05,440 --> 00:07:07,839 Speaker 1: with the format of having ten people on stage trying 120 00:07:07,880 --> 00:07:10,200 Speaker 1: to share two hours. You know, if you look at 121 00:07:10,200 --> 00:07:13,440 Speaker 1: the recent path of debates, they really don't have a 122 00:07:13,440 --> 00:07:16,600 Speaker 1: big effect. We'll talk about them for about twenty four hours, 123 00:07:16,600 --> 00:07:19,840 Speaker 1: but short of somebody making a major gaff and I 124 00:07:19,880 --> 00:07:23,280 Speaker 1: didn't see that last night. Um you know, it's some 125 00:07:23,360 --> 00:07:25,480 Speaker 1: candidates will move up, some will move down a little bit, 126 00:07:25,520 --> 00:07:28,160 Speaker 1: but I think it's sort of status quo. Obviously. I 127 00:07:28,200 --> 00:07:31,080 Speaker 1: think Julian Castor did have a very nice night last night, 128 00:07:31,280 --> 00:07:33,760 Speaker 1: and I think it will cause people to look at 129 00:07:33,800 --> 00:07:36,360 Speaker 1: him a little differently. I was also frankly surprised by 130 00:07:36,400 --> 00:07:39,160 Speaker 1: mare de Blasio, who came out very strong, and you know, 131 00:07:39,200 --> 00:07:41,520 Speaker 1: he hasn't really had much traction in his race as well. 132 00:07:42,160 --> 00:07:46,400 Speaker 1: I also thought, um uh, Centator Warned did well as also. 133 00:07:46,800 --> 00:07:49,000 Speaker 1: The challenge, however, is that you know, in this twenty 134 00:07:49,040 --> 00:07:51,960 Speaker 1: four hour period, from less than twenty four before the 135 00:07:52,040 --> 00:07:54,360 Speaker 1: end of one debate to the start of another debate, 136 00:07:54,680 --> 00:07:57,000 Speaker 1: there's not much time and then by tomorrow we'll be 137 00:07:57,000 --> 00:08:00,520 Speaker 1: talking about date debate number two. So, Chris, were you 138 00:08:00,560 --> 00:08:04,240 Speaker 1: surprised at all that the candidates generally last night did 139 00:08:04,280 --> 00:08:07,800 Speaker 1: not go after Senator Elizabeth Warren, who, at least on 140 00:08:07,880 --> 00:08:11,400 Speaker 1: that stage, was the front runner. You know, I am 141 00:08:11,400 --> 00:08:14,040 Speaker 1: a little surprised by that, and you saw and there 142 00:08:14,120 --> 00:08:17,120 Speaker 1: was a place I think certainly to do that. Um, 143 00:08:17,440 --> 00:08:20,440 Speaker 1: that moment when the moderators asked them to to raise 144 00:08:20,480 --> 00:08:24,160 Speaker 1: their hands whether they would eliminate private insurance of health insurance, 145 00:08:24,200 --> 00:08:27,320 Speaker 1: you saw, Um, you saw Congressman Delaney a little bit 146 00:08:27,400 --> 00:08:30,360 Speaker 1: kind of go after that. But I think by and large, 147 00:08:30,440 --> 00:08:33,640 Speaker 1: you know, the unfortunate thing about the format, um, you know, 148 00:08:33,760 --> 00:08:36,560 Speaker 1: at at about halfway through the people start cutting in 149 00:08:36,600 --> 00:08:38,640 Speaker 1: on each other. But by and large, for that first 150 00:08:38,679 --> 00:08:40,840 Speaker 1: period of time when she was doing most of the speaking, 151 00:08:41,600 --> 00:08:44,440 Speaker 1: the contenders are really just kind of waiting to be 152 00:08:44,480 --> 00:08:46,640 Speaker 1: asked questions, So it didn't really lend itself to kind 153 00:08:46,679 --> 00:08:49,199 Speaker 1: of a lot of back and forth. So you're a 154 00:08:49,280 --> 00:08:53,080 Speaker 1: d n C Democratic National Committee super delegate, so you're 155 00:08:53,120 --> 00:08:57,840 Speaker 1: intimately connected with the Democratic Party. And there is sort 156 00:08:57,880 --> 00:09:01,680 Speaker 1: of a very big question here embedded in these debates, 157 00:09:01,720 --> 00:09:04,559 Speaker 1: and that is can any of these candidates beat President Trump? 158 00:09:04,559 --> 00:09:06,560 Speaker 1: And from what you heard last night, did you feel 159 00:09:06,600 --> 00:09:10,680 Speaker 1: more confident or less confident of that? I'm not sure 160 00:09:10,679 --> 00:09:12,960 Speaker 1: I felt more or less confident, As I said, you know, 161 00:09:13,000 --> 00:09:16,000 Speaker 1: I think look, um, I was with President or Senator 162 00:09:16,040 --> 00:09:18,240 Speaker 1: about my back at two thousand and seven, we went 163 00:09:18,240 --> 00:09:20,960 Speaker 1: through an endless series of debates and uh, you know, 164 00:09:21,000 --> 00:09:23,000 Speaker 1: if you go back and read the press accounts of 165 00:09:23,000 --> 00:09:26,720 Speaker 1: that first debate, Senator Obama was pretty underwhelming at the time. 166 00:09:26,720 --> 00:09:30,319 Speaker 1: And so look, it's early in the process. Um, candidates, 167 00:09:30,360 --> 00:09:32,199 Speaker 1: you get better, and I frankly what I think is 168 00:09:32,240 --> 00:09:34,520 Speaker 1: going to be more interesting for many of these candidates. 169 00:09:34,840 --> 00:09:37,120 Speaker 1: They're gonna have to post their second courter of fundraising 170 00:09:37,200 --> 00:09:40,800 Speaker 1: numbers at the end of June. It'll be interesting to 171 00:09:40,840 --> 00:09:42,600 Speaker 1: see because that you know, it is not cheap to 172 00:09:42,679 --> 00:09:45,800 Speaker 1: run some of these campaigns, and uh, some of them 173 00:09:45,840 --> 00:09:48,120 Speaker 1: have had a challenge raising money in this crowded field. 174 00:09:48,160 --> 00:09:50,880 Speaker 1: So you know, look, I think last night we heard 175 00:09:51,280 --> 00:09:55,120 Speaker 1: a lot of substantive debates. It was largely free of insults. Uh, 176 00:09:55,120 --> 00:09:56,959 Speaker 1: it was completely free of insults. And that's kind of 177 00:09:56,960 --> 00:09:58,480 Speaker 1: a mark change from I think what we saw in 178 00:09:58,520 --> 00:10:03,640 Speaker 1: the Republican bates with than candidate Trump. So, Chris, I 179 00:10:03,640 --> 00:10:07,360 Speaker 1: also noticed last night that the candidates didn't really attack 180 00:10:07,480 --> 00:10:11,320 Speaker 1: Trump's character or maybe some of those questionable policies and 181 00:10:11,400 --> 00:10:13,920 Speaker 1: actions and tweets. Do you think the sticking to the 182 00:10:14,000 --> 00:10:18,559 Speaker 1: policies strategy will work against Trump? You know, look, I 183 00:10:18,840 --> 00:10:22,120 Speaker 1: think I think I think they need to do both. Um. 184 00:10:22,160 --> 00:10:26,920 Speaker 1: I think it's highlighting um what UM Trump's policies, his 185 00:10:26,920 --> 00:10:29,800 Speaker 1: his demeanor in office. But I think it's also UM 186 00:10:29,840 --> 00:10:33,360 Speaker 1: putting forward an affirmative, positive agenda of what they're going 187 00:10:33,400 --> 00:10:37,800 Speaker 1: to do on things like healthcare, education, or immigration. Largely 188 00:10:37,840 --> 00:10:40,080 Speaker 1: the kind of anti Trump message I don't think really 189 00:10:40,120 --> 00:10:42,720 Speaker 1: needs to be made. It's being made here in Washington 190 00:10:42,760 --> 00:10:45,280 Speaker 1: every day, is being made on the cable news networks. UM. 191 00:10:45,320 --> 00:10:46,520 Speaker 1: You know, I just got back from I was in 192 00:10:46,559 --> 00:10:49,240 Speaker 1: Iowa yesterday meeting with some voters, and they really want 193 00:10:49,240 --> 00:10:51,920 Speaker 1: to hear about the issues that are affecting in their lives, 194 00:10:51,960 --> 00:10:55,360 Speaker 1: and so, UM, I don't know that they necessarily the 195 00:10:55,400 --> 00:10:57,760 Speaker 1: candidates nests that I need to draw that distinction, because 196 00:10:57,760 --> 00:11:00,360 Speaker 1: it really is being made for them. You know, you 197 00:11:00,400 --> 00:11:04,160 Speaker 1: started out talking about the limitations of this debate format. 198 00:11:04,280 --> 00:11:06,200 Speaker 1: Is there a way that it could have been done 199 00:11:06,240 --> 00:11:08,800 Speaker 1: that would have been more effective? Uh, it's sort of 200 00:11:08,880 --> 00:11:11,240 Speaker 1: lesson learned for next time, not to have two nights 201 00:11:11,240 --> 00:11:13,760 Speaker 1: of ten different candidates on the stage, each having about 202 00:11:13,800 --> 00:11:17,200 Speaker 1: thirty seconds to talk. Yeah, you know, it's unfortunate because 203 00:11:17,200 --> 00:11:20,160 Speaker 1: the Democratic National Committee I think was trying to address 204 00:11:20,200 --> 00:11:23,200 Speaker 1: the concerns that came out of sixteen that they may have, 205 00:11:23,600 --> 00:11:25,560 Speaker 1: you know, put their thumb on the scale, and so 206 00:11:25,600 --> 00:11:28,040 Speaker 1: what they wanted to do very early on is create 207 00:11:28,120 --> 00:11:30,760 Speaker 1: these objective criterias that everyone knew what they were, and 208 00:11:30,880 --> 00:11:33,640 Speaker 1: to try to meet them. In hindsight, they probably set 209 00:11:33,640 --> 00:11:35,680 Speaker 1: the criteria a little bit too low, this idea that 210 00:11:35,760 --> 00:11:38,960 Speaker 1: sixty five thousand donations could get you in UH. In 211 00:11:39,000 --> 00:11:41,440 Speaker 1: this day and age, it's relatively easy to do that, 212 00:11:41,520 --> 00:11:43,439 Speaker 1: and you can game it in a bunch of different ways. 213 00:11:43,679 --> 00:11:45,640 Speaker 1: I think the real interesting challenge will be when they 214 00:11:45,679 --> 00:11:49,439 Speaker 1: get this September, because then the donation threshold goes to 215 00:11:49,480 --> 00:11:52,240 Speaker 1: a hundred and thirty thousand UH. It's also a two 216 00:11:52,240 --> 00:11:55,720 Speaker 1: percent polling threshold, so I think you may likely see 217 00:11:55,800 --> 00:11:59,079 Speaker 1: only you know, a dozen candidates on the debate stage 218 00:11:59,200 --> 00:12:02,720 Speaker 1: up come September. So, Chris, tonight, we have the second 219 00:12:02,800 --> 00:12:05,360 Speaker 1: night of debates, and of course um uh from a 220 00:12:05,440 --> 00:12:09,160 Speaker 1: vice president Joe Biden and Bernie Sanders as well the 221 00:12:09,160 --> 00:12:12,079 Speaker 1: front runners. What do you expect tonight? Well, I think 222 00:12:12,080 --> 00:12:14,040 Speaker 1: tonight is gonna be a fascinating contrast. I'm gonna be 223 00:12:14,120 --> 00:12:18,040 Speaker 1: looking at whether um uh, Senator Sanders and Vice President 224 00:12:18,080 --> 00:12:20,560 Speaker 1: Biden go after each other. I suspect they won't, but 225 00:12:20,640 --> 00:12:22,160 Speaker 1: I think what you will see is this kind of 226 00:12:22,200 --> 00:12:28,280 Speaker 1: interesting um gender and generational contrast with Kamala Harrison stage 227 00:12:28,280 --> 00:12:31,560 Speaker 1: along with Pete Boutigge, who, even if they're not directly 228 00:12:31,679 --> 00:12:35,560 Speaker 1: going after either Sanders or Biden, provide sort of an 229 00:12:35,559 --> 00:12:39,240 Speaker 1: interesting contrast for voters who want either a more diverse 230 00:12:39,280 --> 00:12:41,760 Speaker 1: candidate or a younger candidate. And who do you think 231 00:12:41,840 --> 00:12:44,200 Speaker 1: is winning right now for the quote soul of the 232 00:12:44,200 --> 00:12:47,199 Speaker 1: Democratic Party, the more liberal wing, the sort of further 233 00:12:47,320 --> 00:12:52,080 Speaker 1: left or this interest Well, it's it's interesting that there's 234 00:12:52,120 --> 00:12:54,480 Speaker 1: the contradiction between what we all see on social media 235 00:12:54,480 --> 00:12:57,480 Speaker 1: and Twitter, which is clearly a much more progressive audience 236 00:12:57,520 --> 00:12:59,680 Speaker 1: then and what you certainly see when you're out talking 237 00:12:59,679 --> 00:13:02,560 Speaker 1: to vote and what you see in public opinion polls. UM. 238 00:13:02,600 --> 00:13:04,440 Speaker 1: But I do think which is I think more moderate? 239 00:13:04,480 --> 00:13:06,920 Speaker 1: I do think it's a challenge. I think ultimately when 240 00:13:06,920 --> 00:13:10,120 Speaker 1: you look at these candidates, there are some extremes, but 241 00:13:10,200 --> 00:13:12,520 Speaker 1: by and large they're united in the idea that we 242 00:13:12,559 --> 00:13:15,600 Speaker 1: need to do more to make the economy work for everyone. 243 00:13:15,600 --> 00:13:17,719 Speaker 1: We need to do more to expand healthcare and make 244 00:13:17,760 --> 00:13:20,800 Speaker 1: it um less expensive. We need to do more in 245 00:13:20,880 --> 00:13:23,640 Speaker 1: terms of building up our relationships with allies. I think 246 00:13:23,640 --> 00:13:26,959 Speaker 1: it's gradations on the spectrum at this point. Chris lou 247 00:13:27,160 --> 00:13:29,520 Speaker 1: thank you so much for taking the time today. Uh 248 00:13:29,679 --> 00:13:31,920 Speaker 1: was she the best of luck. Chris lewis Senior Fellow 249 00:13:32,000 --> 00:13:35,880 Speaker 1: at the University of Virginia Miller Center, former Deputy Secretary 250 00:13:35,920 --> 00:13:39,400 Speaker 1: of Labor under President Obama. Also he is a d 251 00:13:39,600 --> 00:13:43,000 Speaker 1: n C super Delegate. Has just been in Iowa talking 252 00:13:43,160 --> 00:14:04,680 Speaker 1: to perspective voters. As Paul Sweeney was talking just minutes ago. 253 00:14:04,720 --> 00:14:06,440 Speaker 1: You might have heard some beeping in the background, and 254 00:14:06,480 --> 00:14:08,680 Speaker 1: that's because I was up against the wall holding a 255 00:14:08,720 --> 00:14:11,240 Speaker 1: smartphone in various places to try to get a size 256 00:14:11,840 --> 00:14:14,280 Speaker 1: of what clothes I should be buying. And that is 257 00:14:14,320 --> 00:14:17,000 Speaker 1: because Ronan Luzon is here with us. He is founder 258 00:14:17,040 --> 00:14:21,080 Speaker 1: and chief executive officer of My Size, based in Israel, 259 00:14:21,120 --> 00:14:23,560 Speaker 1: but joining us here in our Bloomberg Intta Active Broker Studios. 260 00:14:24,120 --> 00:14:27,160 Speaker 1: Ronan my Size, from what I could tell, is an 261 00:14:27,160 --> 00:14:30,920 Speaker 1: app on your phone that allows you to buy sensors 262 00:14:30,920 --> 00:14:33,000 Speaker 1: by just holding the phone in various places while I'm 263 00:14:33,000 --> 00:14:37,360 Speaker 1: wearing some clothes I'm still wearing clothes to uh just 264 00:14:37,400 --> 00:14:40,200 Speaker 1: tell you exactly what size you'd be in different brands 265 00:14:40,240 --> 00:14:44,000 Speaker 1: to facilitate online shopping. Is that correct? Yeah? That's right? Right? Yeah, 266 00:14:44,240 --> 00:14:48,160 Speaker 1: So how much has this been adopted so far? So? Um, 267 00:14:48,200 --> 00:14:51,120 Speaker 1: the company started two thousand fourteen, and we started as 268 00:14:51,120 --> 00:14:53,440 Speaker 1: a publicly traded company, but we just launched the product 269 00:14:53,560 --> 00:14:55,920 Speaker 1: last September in Fashion Week in New York. So we 270 00:14:55,920 --> 00:14:58,320 Speaker 1: took us about four years to make this thing happen. 271 00:14:58,360 --> 00:15:00,160 Speaker 1: He started as a dream as as a pro when 272 00:15:00,240 --> 00:15:02,440 Speaker 1: that each and everyone of us suffer when we're buying 273 00:15:02,480 --> 00:15:05,800 Speaker 1: things online. We get always the wrong size, well not always, 274 00:15:05,840 --> 00:15:08,400 Speaker 1: but we get sometimes the wrong size. And it took 275 00:15:08,400 --> 00:15:10,800 Speaker 1: four years and we just launched it in last September 276 00:15:10,800 --> 00:15:14,280 Speaker 1: in Fashion Week and was great. Like, retailers are looking 277 00:15:14,320 --> 00:15:16,960 Speaker 1: for a solution because they're suffering for much from the 278 00:15:17,080 --> 00:15:20,200 Speaker 1: online returns in the US alone, as between thirty and 279 00:15:20,200 --> 00:15:23,480 Speaker 1: fifty percent returns almost every second item is being sent back. 280 00:15:23,920 --> 00:15:26,320 Speaker 1: It's an abslute situation for the retailers and for us 281 00:15:26,320 --> 00:15:29,440 Speaker 1: to consumers. So we just now start kicking off. We 282 00:15:29,800 --> 00:15:33,160 Speaker 1: began romping up the the adoption of the technology both 283 00:15:33,200 --> 00:15:37,520 Speaker 1: on retailers and consumers alike, even though our business model 284 00:15:37,640 --> 00:15:40,800 Speaker 1: is B two B. So who's paying for that technology 285 00:15:40,880 --> 00:15:44,640 Speaker 1: is the retailers the consumers completely free for use and 286 00:15:44,800 --> 00:15:47,320 Speaker 1: uh and and try so that everybody can download it. 287 00:15:47,520 --> 00:15:50,040 Speaker 1: But who's paying for that is the retailers. So they're 288 00:15:50,080 --> 00:15:53,680 Speaker 1: paying for every what we call a fit recommendation. Us 289 00:15:53,680 --> 00:15:56,640 Speaker 1: as the users as consumers when we're going online for 290 00:15:56,680 --> 00:15:59,480 Speaker 1: our favorite retailer or a new retailer that we don't 291 00:15:59,480 --> 00:16:01,960 Speaker 1: know ourselves, eyes before we click on the button to 292 00:16:02,000 --> 00:16:04,720 Speaker 1: get our recommended size, and then when we as a 293 00:16:04,760 --> 00:16:08,000 Speaker 1: my size charge to retailer for alright, So talking about 294 00:16:08,040 --> 00:16:11,200 Speaker 1: the technology here again, I was working over here and 295 00:16:11,200 --> 00:16:13,320 Speaker 1: you guys are over there in the corner of the studio. 296 00:16:13,440 --> 00:16:16,640 Speaker 1: He raises his eyebrows. I wasn't working and I heard 297 00:16:16,640 --> 00:16:18,920 Speaker 1: a lot of buzzing and peeping and phones being way 298 00:16:18,960 --> 00:16:23,000 Speaker 1: waved around. How does the technology work? So when I 299 00:16:23,040 --> 00:16:26,320 Speaker 1: started that it's it was because of my my kid, 300 00:16:26,360 --> 00:16:30,040 Speaker 1: now today's fifteen, but he back then was ordering things online, 301 00:16:30,120 --> 00:16:33,880 Speaker 1: especially NBA suits, and it came wrong size, and I 302 00:16:33,920 --> 00:16:37,480 Speaker 1: was thinking something must change here. So there was some 303 00:16:37,680 --> 00:16:40,760 Speaker 1: different technologies out there, and one of them was image processing. 304 00:16:40,800 --> 00:16:42,640 Speaker 1: So you need to take a picture of yourself and 305 00:16:42,760 --> 00:16:46,280 Speaker 1: then by the image it does the calculation off off 306 00:16:46,480 --> 00:16:48,720 Speaker 1: of the sizing. The thing is that you need to 307 00:16:48,760 --> 00:16:51,000 Speaker 1: take your clothes off. Now I would never get my 308 00:16:51,120 --> 00:16:54,080 Speaker 1: kid taking a picture with naked or half naked and 309 00:16:54,120 --> 00:16:56,960 Speaker 1: send it to doesn't matter how secure the server is, 310 00:16:57,240 --> 00:16:59,920 Speaker 1: it will never happen, especially for women, even even for 311 00:17:00,120 --> 00:17:03,080 Speaker 1: us as men, we will never do that. So I 312 00:17:03,200 --> 00:17:06,400 Speaker 1: was thinking what other possibilities can be to do that. 313 00:17:06,520 --> 00:17:09,240 Speaker 1: So we took the mobile phone sensors, the same sensors 314 00:17:09,240 --> 00:17:12,080 Speaker 1: that are almost every mobile phone for kids when they're 315 00:17:12,080 --> 00:17:14,200 Speaker 1: playing with the phone, they moved from one place to another, 316 00:17:14,359 --> 00:17:17,639 Speaker 1: it's the same sensors. It's accelerometer and the gyro that 317 00:17:17,760 --> 00:17:20,520 Speaker 1: result in the mobile phone and algorithm that we've developed. 318 00:17:20,880 --> 00:17:23,960 Speaker 1: So we know to take the information from the sensors 319 00:17:23,960 --> 00:17:26,280 Speaker 1: when you move the phone over your body from one 320 00:17:26,280 --> 00:17:29,040 Speaker 1: place to another, we know to measure the distance the 321 00:17:29,080 --> 00:17:32,720 Speaker 1: phone is moving between two points. And that's how we 322 00:17:32,800 --> 00:17:36,360 Speaker 1: actually make this technology work for the apparel. So what 323 00:17:36,480 --> 00:17:39,480 Speaker 1: types of companies are you working with to sort of 324 00:17:40,520 --> 00:17:44,000 Speaker 1: get more online traction and and understand how to sort 325 00:17:44,000 --> 00:17:46,960 Speaker 1: of limit some of these returns. So it's amazing that 326 00:17:48,480 --> 00:17:52,440 Speaker 1: we've started actually demonstrating technology back in cs in two 327 00:17:52,440 --> 00:17:55,800 Speaker 1: thousand seventeen, and back then the technology didn't actually work. 328 00:17:55,840 --> 00:17:58,520 Speaker 1: It was more like a proof of concept. Even that 329 00:17:58,640 --> 00:18:02,359 Speaker 1: was not the best scenario. But the CSWO thousand eighteen 330 00:18:02,440 --> 00:18:06,240 Speaker 1: we actually launched the the beta one, and when we 331 00:18:06,320 --> 00:18:09,199 Speaker 1: watched the beta, we understood that so many retailers followed 332 00:18:09,280 --> 00:18:12,320 Speaker 1: us because they have this issue of sizing and faith 333 00:18:12,680 --> 00:18:15,719 Speaker 1: and they need to accommodate the problem. And starting two 334 00:18:15,720 --> 00:18:19,760 Speaker 1: thousand eighteen, when we start demonstrating the actual body measurement 335 00:18:19,760 --> 00:18:23,919 Speaker 1: technology that we're doing today, UM retailers start to sign 336 00:18:24,000 --> 00:18:27,520 Speaker 1: up for air lies and pilots and try it out. 337 00:18:28,040 --> 00:18:32,520 Speaker 1: And today we have to to one customers that sign 338 00:18:32,600 --> 00:18:35,919 Speaker 1: up with our solution. It stakes it takes time for 339 00:18:35,960 --> 00:18:38,800 Speaker 1: the till one customers to start the integration. It takes 340 00:18:38,840 --> 00:18:42,760 Speaker 1: it takes longer than we actually anticipated because what we 341 00:18:42,880 --> 00:18:46,720 Speaker 1: see is that the retailer is not that much of 342 00:18:46,800 --> 00:18:50,120 Speaker 1: a computer oriented of an I T company that can 343 00:18:50,160 --> 00:18:53,320 Speaker 1: have a technology like that and start working with it 344 00:18:53,480 --> 00:18:55,720 Speaker 1: as like as as we can see for the small 345 00:18:55,720 --> 00:18:58,960 Speaker 1: and medium size retailer that's doing it in in a 346 00:18:59,000 --> 00:19:02,520 Speaker 1: couple of days or we they actually integrated. So it's 347 00:19:02,560 --> 00:19:05,800 Speaker 1: it's takes it takes the time to integrate it, but 348 00:19:06,200 --> 00:19:09,920 Speaker 1: we as well done the integration on Shopify platforms platform 349 00:19:09,960 --> 00:19:12,800 Speaker 1: and light Speed platform. It's the same like Shopify, but Europe, 350 00:19:12,880 --> 00:19:16,480 Speaker 1: on Europe, Netherlands, and we can see these these small 351 00:19:16,560 --> 00:19:19,840 Speaker 1: ones are taking this technology and integrated within a couple 352 00:19:19,840 --> 00:19:23,320 Speaker 1: of hours and they stopped working with it, and it's amazing. 353 00:19:23,600 --> 00:19:26,640 Speaker 1: It's amazing product. You see how they can save returns, 354 00:19:26,680 --> 00:19:29,600 Speaker 1: which kills their business if they don't. Right, absolutely running, 355 00:19:29,680 --> 00:19:31,800 Speaker 1: Thanks so much for coming on and measuring my co 356 00:19:31,960 --> 00:19:34,760 Speaker 1: host here. Thank you for not measuring. As I said, 357 00:19:34,760 --> 00:19:36,359 Speaker 1: I'm a forty two regular right off the rack down. 358 00:19:36,560 --> 00:19:38,760 Speaker 1: Don't have to worry about me running. Lucan founder and 359 00:19:38,800 --> 00:19:42,120 Speaker 1: CEO of my size. Just a really cool technology. Keep 360 00:19:42,200 --> 00:19:44,520 Speaker 1: us in the loop as this thing continues to develop. 361 00:19:44,560 --> 00:19:46,399 Speaker 1: It really like to kind of see how this places 362 00:19:46,400 --> 00:20:02,240 Speaker 1: are very interesting technology as more and more clothing goes online. 363 00:20:04,960 --> 00:20:08,879 Speaker 1: We've talked a lot about Libra, which is the cryptocurrency, 364 00:20:09,160 --> 00:20:12,159 Speaker 1: or at least it's been called a cryptocurrency. It's an 365 00:20:12,200 --> 00:20:15,680 Speaker 1: idea that Facebook is putting out there, and I really 366 00:20:15,720 --> 00:20:18,159 Speaker 1: am excited to bring in Aaron Brown. I always love 367 00:20:18,200 --> 00:20:20,400 Speaker 1: speaking with him. He's the former managing director and head 368 00:20:20,400 --> 00:20:23,200 Speaker 1: of financial market research at a q R Capital Management. 369 00:20:23,359 --> 00:20:26,000 Speaker 1: But I'm especially excited today because he wrote a column 370 00:20:26,480 --> 00:20:30,359 Speaker 1: as a Bloomberg opinion columnist that I found incredibly compelling. Aaron, 371 00:20:30,400 --> 00:20:33,000 Speaker 1: thank you so much for being with us. Uh. It 372 00:20:33,119 --> 00:20:37,120 Speaker 1: was talking about how, in general, the bitcoin and cryptocurrency 373 00:20:37,200 --> 00:20:41,320 Speaker 1: community is moving outside of the financial system that is 374 00:20:41,359 --> 00:20:44,360 Speaker 1: sort of entrenched, and that Facebook was doing the exact 375 00:20:44,440 --> 00:20:47,160 Speaker 1: opposite and from the top down trying to come up 376 00:20:47,359 --> 00:20:51,600 Speaker 1: with some kind of monetary unit that could rival the dollar, 377 00:20:51,960 --> 00:20:56,000 Speaker 1: the euro, the yend. Can you explain how that's the case. Yeah, 378 00:20:56,080 --> 00:20:59,480 Speaker 1: thanks for having me. The best term for what libra 379 00:20:59,720 --> 00:21:03,959 Speaker 1: is something called digital cash. Now cash is something that 380 00:21:03,960 --> 00:21:05,320 Speaker 1: it can be a dollar bill, it could be a 381 00:21:05,320 --> 00:21:08,639 Speaker 1: gold coin. It can be anything that you can pass 382 00:21:08,680 --> 00:21:11,600 Speaker 1: from one person to another without leaving a transaction record, 383 00:21:12,080 --> 00:21:15,960 Speaker 1: and that the individual can identify, I can can validate. 384 00:21:16,000 --> 00:21:20,480 Speaker 1: It's hard to counterfeit um. Bitcoin and other cryptocurrencies are 385 00:21:20,560 --> 00:21:24,600 Speaker 1: much broader ideas, you know, trying to re engineer both 386 00:21:24,920 --> 00:21:28,919 Speaker 1: technology of exchange and financial system or whatever. Uh. Libre 387 00:21:29,040 --> 00:21:30,760 Speaker 1: is an old idea. It's a you know, it's it's 388 00:21:30,760 --> 00:21:33,359 Speaker 1: a gold coin, it's a dollar bill. It just happens 389 00:21:33,359 --> 00:21:36,000 Speaker 1: to be digital, meaning that it's a number. It's not 390 00:21:36,080 --> 00:21:40,320 Speaker 1: a physical piece of paper. It's not a piece of metal. Um. 391 00:21:40,320 --> 00:21:43,160 Speaker 1: So in one sense, it's very conservative idea. It's just saying, Okay, 392 00:21:43,240 --> 00:21:46,080 Speaker 1: let's take cash and let's let's make it digital, something 393 00:21:46,119 --> 00:21:49,520 Speaker 1: that bitcoin does. But bitcoin does tons of other stuff too. 394 00:21:50,000 --> 00:21:53,240 Speaker 1: I think Libra is a competitor to other forms of cash. 395 00:21:53,280 --> 00:21:55,280 Speaker 1: When I say it's a competitor to the US dollar, 396 00:21:55,640 --> 00:21:58,480 Speaker 1: I don't mean the US dollar financial system, you know, 397 00:21:58,520 --> 00:22:01,160 Speaker 1: with a central bank and the fat banking. I mean 398 00:22:01,560 --> 00:22:04,760 Speaker 1: those physical pieces of paper that people use, whether you know, 399 00:22:04,880 --> 00:22:07,680 Speaker 1: buying a cup of coffee or putting a whole bunch 400 00:22:07,680 --> 00:22:10,959 Speaker 1: in a suitcase to buy a boatload of drugs. Whatever. Uh, 401 00:22:11,359 --> 00:22:14,240 Speaker 1: that's what Libra is going to That's the market Libra 402 00:22:14,320 --> 00:22:17,800 Speaker 1: is going to attack. So it's interesting erin we've had, 403 00:22:18,000 --> 00:22:20,640 Speaker 1: you know, thinking about the bitcoin, the volatility has really 404 00:22:20,680 --> 00:22:23,240 Speaker 1: come back into that security. I sit down about eight 405 00:22:23,240 --> 00:22:26,520 Speaker 1: point seven percent today. It just had this incredible run 406 00:22:27,119 --> 00:22:29,359 Speaker 1: over the last couple of weeks, a couple of days, 407 00:22:29,440 --> 00:22:33,919 Speaker 1: crazy trading who was actually trading this thing. Well, you know, 408 00:22:33,920 --> 00:22:36,280 Speaker 1: I wrote a call about ten days ago saying the 409 00:22:36,359 --> 00:22:40,320 Speaker 1: two thousand nineteen rally and bitcoin was completely different from 410 00:22:40,359 --> 00:22:43,399 Speaker 1: the earlier one. It was not marked by access of volatility. 411 00:22:43,440 --> 00:22:45,879 Speaker 1: It was real money. It was based on fundamentals, and 412 00:22:45,920 --> 00:22:48,600 Speaker 1: you could really you know, trace it. Uh for the 413 00:22:48,640 --> 00:22:51,119 Speaker 1: last ten days made me a liar, And we're seeing 414 00:22:51,240 --> 00:22:54,200 Speaker 1: not a liar just you were postulating. It turns out 415 00:22:54,200 --> 00:22:57,000 Speaker 1: perhaps it's a little more volatile than that. Yeah, well 416 00:22:57,000 --> 00:22:59,520 Speaker 1: we'll change. I mean, we're now seeing the last well, 417 00:22:59,640 --> 00:23:02,960 Speaker 1: certainly last week, we were just seeing a lot of 418 00:23:03,119 --> 00:23:05,440 Speaker 1: kinds of stuff we saw on you know, late two 419 00:23:05,440 --> 00:23:09,119 Speaker 1: thousand seventeen and in previous crypto rallies. Are seeing a 420 00:23:09,119 --> 00:23:12,520 Speaker 1: lot of retail investors. We're seeing real money selling, we're 421 00:23:12,520 --> 00:23:15,800 Speaker 1: seeing high volatility. We're seeing how you know, once it 422 00:23:15,840 --> 00:23:18,760 Speaker 1: starts going up, there's you know, just massive people piling in, 423 00:23:18,800 --> 00:23:20,199 Speaker 1: and if it starts to go down a little bit, 424 00:23:20,240 --> 00:23:23,080 Speaker 1: that people pile out. Um. I hope this isn't just 425 00:23:23,160 --> 00:23:24,720 Speaker 1: like a flash in the pan. I mean, I hope 426 00:23:24,720 --> 00:23:27,200 Speaker 1: this is just like a minor thing. It does seem 427 00:23:27,240 --> 00:23:30,360 Speaker 1: to be connected around the libre announcement, which has no 428 00:23:30,920 --> 00:23:34,000 Speaker 1: you know, I mean, it's not that tig an announcement period, 429 00:23:34,040 --> 00:23:35,920 Speaker 1: and it certainly doesn't have a huge effect on the 430 00:23:35,960 --> 00:23:38,160 Speaker 1: long term value of crypto, but it got a lot 431 00:23:38,160 --> 00:23:40,120 Speaker 1: of people excited, and I think it got a lot 432 00:23:40,119 --> 00:23:43,960 Speaker 1: of uh people piling in. So I think what we're 433 00:23:43,960 --> 00:23:47,199 Speaker 1: seeing uh in late June is you know, kind of 434 00:23:47,200 --> 00:23:50,840 Speaker 1: a mini boom and bust uh. And I hope that 435 00:23:50,880 --> 00:23:52,919 Speaker 1: the rest of two thousand nineteen is going to go 436 00:23:52,960 --> 00:23:56,879 Speaker 1: along on a nice, steady fundamental move up or down, 437 00:23:57,000 --> 00:24:00,680 Speaker 1: but not you know, based on real investors, real money 438 00:24:00,680 --> 00:24:03,520 Speaker 1: and looking at the fundamentals as opposed to people afraid 439 00:24:03,560 --> 00:24:05,600 Speaker 1: of missing out. Well, Aaron, I want to pick up 440 00:24:05,600 --> 00:24:08,040 Speaker 1: on the idea that some people connected this to Libra 441 00:24:08,320 --> 00:24:11,480 Speaker 1: and some people who were just speculating. But Danny Masters 442 00:24:11,560 --> 00:24:14,399 Speaker 1: was on our show earlier this week of coin shares, 443 00:24:14,840 --> 00:24:18,040 Speaker 1: and he was saying that there is direct connection in 444 00:24:18,200 --> 00:24:23,120 Speaker 1: terms of this creates a platform for people to potentially 445 00:24:23,320 --> 00:24:28,920 Speaker 1: use bitcoin right right next to dollars as transfer cash, 446 00:24:28,960 --> 00:24:32,400 Speaker 1: So it creates the piping for bitcoin to enter more 447 00:24:32,440 --> 00:24:36,080 Speaker 1: commonplace methods of payment. Do you ascribe to that kind 448 00:24:36,119 --> 00:24:39,960 Speaker 1: of idea, Yeah, that's absolutely true. Among other things, libra 449 00:24:40,040 --> 00:24:43,200 Speaker 1: is a very crypto friendly form of cash, and all 450 00:24:43,240 --> 00:24:45,760 Speaker 1: the problems we've had with you know, bitcoin and financial 451 00:24:45,760 --> 00:24:48,640 Speaker 1: mark and and cryptocurrencies and so on has been when 452 00:24:48,640 --> 00:24:51,480 Speaker 1: people try to connect them to dollars. That's where you 453 00:24:51,480 --> 00:24:53,560 Speaker 1: get the fraud. That's where you get the volatility, that's 454 00:24:53,560 --> 00:24:56,360 Speaker 1: where you get the regulators upset. You know, as long 455 00:24:56,400 --> 00:24:59,439 Speaker 1: as people are just using cryptocurrency in itself, it's a 456 00:24:59,520 --> 00:25:02,679 Speaker 1: very uh to day calm. You know. It's a rapidly 457 00:25:02,760 --> 00:25:06,960 Speaker 1: changing technology, but it's one that has been clearly beneficial 458 00:25:07,040 --> 00:25:10,639 Speaker 1: and useful. So if Libra is successful, now that's a 459 00:25:10,720 --> 00:25:12,720 Speaker 1: huge if. I mean, all we really have is twenty 460 00:25:12,720 --> 00:25:15,159 Speaker 1: eight logos of companies and Facebook saying they want to 461 00:25:15,160 --> 00:25:18,159 Speaker 1: do it. We don't really have the kind of you know, 462 00:25:18,240 --> 00:25:20,760 Speaker 1: infrastructure and commitment. I'm sorry. The other thing we do 463 00:25:20,800 --> 00:25:22,920 Speaker 1: have is Facebook has invested a ton of money in 464 00:25:23,200 --> 00:25:27,240 Speaker 1: writing code and developing this. But if it is successful, 465 00:25:27,480 --> 00:25:30,800 Speaker 1: it will make it much easier to use cryptocurrencies, and 466 00:25:30,840 --> 00:25:33,440 Speaker 1: I think it would tame the volatility and cryptocurrency quite 467 00:25:33,480 --> 00:25:36,960 Speaker 1: a bit. Aaron, how do you think the regulatory environment 468 00:25:37,040 --> 00:25:40,400 Speaker 1: around crypto broadly defined, is going to evolve. I think 469 00:25:40,440 --> 00:25:44,120 Speaker 1: when the Facebook made its announcement about libra that kind 470 00:25:44,119 --> 00:25:46,440 Speaker 1: of perked up the ears of a lot of regulators 471 00:25:46,440 --> 00:25:48,320 Speaker 1: and politicians in Washington. How do you think this is 472 00:25:48,320 --> 00:25:52,280 Speaker 1: going to evolve? You know, I think my I usually 473 00:25:52,320 --> 00:25:53,720 Speaker 1: feel this. You know, we're we're going to work out 474 00:25:53,720 --> 00:25:57,560 Speaker 1: to a sensible consensus. There are some real advantages. They're 475 00:25:57,960 --> 00:26:01,720 Speaker 1: tremendous economic advantages to going to crypto, and libra is 476 00:26:01,720 --> 00:26:04,159 Speaker 1: a much better form of cash than dollars or gold 477 00:26:04,480 --> 00:26:07,280 Speaker 1: or or anything else people have used, you know, seashells 478 00:26:07,359 --> 00:26:10,960 Speaker 1: or salt or big rocks. But so so it's going 479 00:26:11,000 --> 00:26:15,400 Speaker 1: to happen. I think some form of global digital currency, 480 00:26:15,680 --> 00:26:19,320 Speaker 1: digital cash will be around, and I think regulators will 481 00:26:19,359 --> 00:26:23,080 Speaker 1: allow the innovations and useful parts of crypto. But it 482 00:26:23,160 --> 00:26:26,400 Speaker 1: also raises you know, it kind of undermines a regulatory regime. 483 00:26:26,400 --> 00:26:30,280 Speaker 1: An awful lot of law, especially taxes, but also other 484 00:26:30,400 --> 00:26:35,800 Speaker 1: laws are enforced through currency regulations. Uh, if everybody is 485 00:26:35,880 --> 00:26:38,840 Speaker 1: using cash, you know, if there's no paper record, or 486 00:26:38,880 --> 00:26:43,000 Speaker 1: at least no traceable, searchable law enforcement record of transactions, 487 00:26:43,080 --> 00:26:46,159 Speaker 1: an awful lot of crimes become a lot easier. We 488 00:26:46,240 --> 00:26:48,200 Speaker 1: used to have one of those common crimes we used 489 00:26:48,200 --> 00:26:50,920 Speaker 1: to have was mugging. Now people just don't carry enough 490 00:26:50,920 --> 00:26:54,879 Speaker 1: cash to make mugging worthwhile. Right now, the credit cards 491 00:26:55,680 --> 00:26:59,360 Speaker 1: is a huge issues switch to hacking, right so criminals 492 00:26:59,400 --> 00:27:03,200 Speaker 1: are going to switch to whatever, uh whatever works for them. 493 00:27:03,240 --> 00:27:05,840 Speaker 1: But so there's a tremendous amount of regulatory work that 494 00:27:05,880 --> 00:27:08,040 Speaker 1: has to be done. You know, people have to agree 495 00:27:08,119 --> 00:27:11,440 Speaker 1: on regulations. There are, of course many people in crypto 496 00:27:11,520 --> 00:27:14,639 Speaker 1: who feel that they can do without governments and go 497 00:27:14,760 --> 00:27:17,040 Speaker 1: through it, but that's just not realistic. Very good. Thank 498 00:27:17,080 --> 00:27:19,160 Speaker 1: Aaron Brown, Thank you so much. A calmness for Bloomberg 499 00:27:19,240 --> 00:27:22,320 Speaker 1: Opinion talking all things trip though. Thanks for listening to 500 00:27:22,320 --> 00:27:25,119 Speaker 1: the Bloomberg Penl podcast. You can subscribe and listen to 501 00:27:25,160 --> 00:27:28,359 Speaker 1: interviews at Apple Podcasts or whatever podcast platform you prefer. 502 00:27:28,600 --> 00:27:31,239 Speaker 1: I'm Paul Sweeney, I'm on Twitter at pt Sweeney. I'm 503 00:27:31,280 --> 00:27:33,959 Speaker 1: Lisa bram Woods. I'm on Twitter at Lisa bram Woods. 504 00:27:34,040 --> 00:27:36,920 Speaker 1: One before the podcast, you can always catch us worldwide 505 00:27:36,920 --> 00:27:37,879 Speaker 1: on Bloomberg Radio.