1 00:00:02,640 --> 00:00:05,320 Speaker 1: Welcome to the Bloomberg Penl podcast. I'm Paul swing you 2 00:00:05,360 --> 00:00:07,760 Speaker 1: along with my co host Lisa Brahmas. Each day we 3 00:00:07,880 --> 00:00:10,440 Speaker 1: bring you the most noteworthy and useful interviews for you 4 00:00:10,520 --> 00:00:12,640 Speaker 1: and your money, whether at the grocery store or the 5 00:00:12,640 --> 00:00:15,960 Speaker 1: trading floor. Find a Bloomberg Penil podcast on Apple podcast 6 00:00:16,120 --> 00:00:18,080 Speaker 1: or wherever you listen to podcasts, as well as at 7 00:00:18,079 --> 00:00:21,280 Speaker 1: Bloomberg dot com. So Shopify, I've got a stock for 8 00:00:21,320 --> 00:00:25,360 Speaker 1: you Shopify, Lisa. The stock is upcent over the last year. 9 00:00:25,400 --> 00:00:28,160 Speaker 1: These are the good folks that help merchants set up 10 00:00:28,160 --> 00:00:31,240 Speaker 1: and manage their online stores. Stock has done phenomenon well, 11 00:00:31,280 --> 00:00:34,120 Speaker 1: just had some great earnings out on the last couple 12 00:00:34,159 --> 00:00:37,680 Speaker 1: of days. Hardly Finkelstein, chief operating Officer Shopify, joins us 13 00:00:37,680 --> 00:00:40,159 Speaker 1: here on our Bloomberg Interactive Broker studio. Hardly, thanks so 14 00:00:40,200 --> 00:00:41,600 Speaker 1: much for being with it. Usually we chat with you 15 00:00:41,600 --> 00:00:42,720 Speaker 1: on the phone, so it's good to have you in 16 00:00:42,800 --> 00:00:46,640 Speaker 1: studio to be here. What is driving the growth of Shopify. 17 00:00:46,760 --> 00:00:49,080 Speaker 1: I mean when people think online, they just they just 18 00:00:49,200 --> 00:00:51,680 Speaker 1: and they think retail. They just think Amazon putting retail 19 00:00:51,720 --> 00:00:53,680 Speaker 1: out of business. But there are a lot of retailers 20 00:00:53,840 --> 00:00:56,319 Speaker 1: using your technology that are kind of getting it done right. Yeah, 21 00:00:56,360 --> 00:00:59,440 Speaker 1: there's a million merchants, a million stores now on Shopify 22 00:00:59,640 --> 00:01:02,280 Speaker 1: and they old sixty one billion dollars in two thousand nineteen. 23 00:01:02,480 --> 00:01:04,760 Speaker 1: That's up about forty nine percent from the previous year. 24 00:01:05,240 --> 00:01:08,120 Speaker 1: Our revenue for two was approximately one point five billion. 25 00:01:08,120 --> 00:01:11,520 Speaker 1: That's up. So certainly I think people are beginning understand 26 00:01:11,520 --> 00:01:13,720 Speaker 1: what Shopify is and what we are is where the 27 00:01:13,720 --> 00:01:16,919 Speaker 1: world's first retail operating system. And uh, we have stores 28 00:01:16,920 --> 00:01:18,720 Speaker 1: that are starting on shop If they getting really big, 29 00:01:18,760 --> 00:01:21,400 Speaker 1: that's the all Birds, that's the bombas Socks of the world, 30 00:01:21,400 --> 00:01:24,080 Speaker 1: that's the gym Sharks of the world. They're becoming category leaders. 31 00:01:24,319 --> 00:01:26,800 Speaker 1: But also we we also big brands I mentioned kitchen 32 00:01:26,840 --> 00:01:29,440 Speaker 1: Aid and PepsiCo and PNG that are also moving over. 33 00:01:29,600 --> 00:01:31,920 Speaker 1: So they use you, your guys platform as opposed to 34 00:01:31,959 --> 00:01:33,880 Speaker 1: building themselves. Is that kind of the way do you 35 00:01:33,880 --> 00:01:35,680 Speaker 1: think about Yes, some of them built these homegrown stores, 36 00:01:36,000 --> 00:01:38,199 Speaker 1: homegrown stores and decided they don't want to run massive 37 00:01:38,200 --> 00:01:40,920 Speaker 1: engineering teams. In other cases, they're migrating over from the 38 00:01:41,000 --> 00:01:44,240 Speaker 1: large enterprise offerings. So if you look at a chart 39 00:01:44,319 --> 00:01:47,280 Speaker 1: of your stock since the end of two thousand and eighteen, 40 00:01:47,520 --> 00:01:51,000 Speaker 1: it's just con stratospheric, right, I mean, it's just absolutely rocketed, 41 00:01:51,080 --> 00:01:54,640 Speaker 1: and I'm trying to understand how you maintain this sort 42 00:01:54,680 --> 00:01:57,280 Speaker 1: of momentum at a time when there is a lot 43 00:01:57,320 --> 00:01:59,480 Speaker 1: of competition and at a time when there still are 44 00:01:59,520 --> 00:02:02,160 Speaker 1: a lot of questions about the economy. Yeah, So a 45 00:02:02,160 --> 00:02:04,040 Speaker 1: couple of things. First of all, I think when we 46 00:02:04,080 --> 00:02:06,800 Speaker 1: first swent public, which is does in fifteen, Shopify was 47 00:02:06,880 --> 00:02:11,040 Speaker 1: really e commerce provider for merchants and entrepreneurs and small 48 00:02:11,040 --> 00:02:14,040 Speaker 1: businesses in English speaking world. Since then, we've expanded well 49 00:02:14,080 --> 00:02:17,440 Speaker 1: beyond e commerce. We now power physical retail across If 50 00:02:17,440 --> 00:02:20,040 Speaker 1: you walk in any Albert store, you'll see Shopify powering 51 00:02:20,040 --> 00:02:22,320 Speaker 1: the physical locations, and we do that across thousands of 52 00:02:22,320 --> 00:02:24,680 Speaker 1: brick and mortar stores. We have a capital business. We've 53 00:02:24,720 --> 00:02:27,360 Speaker 1: given them more than eight hundred million dollars in cash advances. 54 00:02:27,480 --> 00:02:30,480 Speaker 1: We have a payments business. We're launching a fulfillmance business now. 55 00:02:30,760 --> 00:02:33,720 Speaker 1: And we've also expanded beyond just our core geographies um. 56 00:02:33,720 --> 00:02:36,520 Speaker 1: In fact, we've grown our um the amount of merchants 57 00:02:36,560 --> 00:02:39,440 Speaker 1: on our platform outside English speaking countries from twenty four 58 00:02:39,520 --> 00:02:43,120 Speaker 1: percent last year to this past quarter, and so we're 59 00:02:43,120 --> 00:02:45,520 Speaker 1: seeing a larger TAM and we're doing more for our merchants, 60 00:02:45,560 --> 00:02:47,200 Speaker 1: which is why I sort of refer to us as 61 00:02:47,240 --> 00:02:50,440 Speaker 1: this retail operating system, not just an e commerce provider anymore, 62 00:02:50,560 --> 00:02:54,400 Speaker 1: so you know, as an e commerce provider or expanded larger. 63 00:02:54,720 --> 00:02:56,480 Speaker 1: You guys did not come out of Silicon Valley, did 64 00:02:56,520 --> 00:02:59,040 Speaker 1: you. You You guys are in Ottawa. We are absolutely abel 65 00:02:59,160 --> 00:03:03,600 Speaker 1: like the start up community, the startup vibe in Canada. 66 00:03:03,960 --> 00:03:06,040 Speaker 1: It is audaa Audawa the place to do it? Or 67 00:03:06,160 --> 00:03:08,480 Speaker 1: is it just entrepreneurs kind of all over? Yeah? Actually, 68 00:03:08,520 --> 00:03:12,799 Speaker 1: I think startups in entrepreneurship and technology has become geographically agnostic. 69 00:03:13,080 --> 00:03:15,000 Speaker 1: I actually think it's an advantage to be outside of 70 00:03:15,040 --> 00:03:17,160 Speaker 1: Silicon Valley. I have a lot of piers that run 71 00:03:17,200 --> 00:03:19,600 Speaker 1: companies like like Hours in the Valley and they tell 72 00:03:19,600 --> 00:03:22,240 Speaker 1: me that the average tenure of employees they're super short, 73 00:03:22,280 --> 00:03:25,120 Speaker 1: like eighteen months. We see incredible talent coming out of Canada, 74 00:03:25,240 --> 00:03:28,000 Speaker 1: we see incredible loyalty, and I think there's something to 75 00:03:28,040 --> 00:03:30,520 Speaker 1: be said about being the best place to work in 76 00:03:30,560 --> 00:03:32,919 Speaker 1: any single geography. And I think Shoplay is the best 77 00:03:32,919 --> 00:03:34,880 Speaker 1: place to work in Canada and one of them around 78 00:03:34,880 --> 00:03:38,080 Speaker 1: the world. What about competition, I imagine that Amazon would 79 00:03:38,120 --> 00:03:40,360 Speaker 1: love to get a piece of what you're doing. Yeah, 80 00:03:40,400 --> 00:03:42,640 Speaker 1: So we don't get be with Amazon, our million merchants do. 81 00:03:42,760 --> 00:03:44,720 Speaker 1: And I think what Amazon is doing is they're trying 82 00:03:44,720 --> 00:03:46,720 Speaker 1: to build an empire, and what we're doing is we're 83 00:03:46,800 --> 00:03:49,200 Speaker 1: arming the rebels, and the rebels are winning. So you 84 00:03:49,240 --> 00:03:52,200 Speaker 1: see companies like Nike moving off Amazon because they want 85 00:03:52,200 --> 00:03:55,400 Speaker 1: to have a direct relationship with or in consumers. All Birds, 86 00:03:55,440 --> 00:03:57,560 Speaker 1: for example, if you try to buy All Birds and Amazon, 87 00:03:57,600 --> 00:03:59,440 Speaker 1: you can only find fake all Birds and and and 88 00:03:59,640 --> 00:04:02,320 Speaker 1: Albert has been built on Shopify. So basically the idea 89 00:04:02,400 --> 00:04:04,520 Speaker 1: here is rather than go to Amazon, you're trying to 90 00:04:04,560 --> 00:04:06,640 Speaker 1: give them tools to be able to do it themselves 91 00:04:06,920 --> 00:04:09,720 Speaker 1: and create a platform. How do you offer them the 92 00:04:09,760 --> 00:04:13,160 Speaker 1: same kind of visibility that they may get in an Amazon. Yes. 93 00:04:13,240 --> 00:04:15,000 Speaker 1: So certainly if they're gonna put their products on a 94 00:04:15,040 --> 00:04:19,040 Speaker 1: marketplace like Amazon or eBay, they're going to obviously, uh, 95 00:04:19,080 --> 00:04:22,000 Speaker 1: they're gonna rent their customers to those to those brands. 96 00:04:22,279 --> 00:04:25,800 Speaker 1: We actually created a platform where our merchants are brands 97 00:04:25,839 --> 00:04:27,760 Speaker 1: can actually find their own customers and own them, whether 98 00:04:27,839 --> 00:04:30,240 Speaker 1: through social media or you can buy marketing directly from 99 00:04:30,240 --> 00:04:33,839 Speaker 1: Shopify on things like Google or Facebook or Snapchat or Instagram, 100 00:04:33,960 --> 00:04:36,440 Speaker 1: and so rather than simply giving them, customers are renting 101 00:04:36,480 --> 00:04:38,440 Speaker 1: them the way Amazon does, and eventually they can take 102 00:04:38,440 --> 00:04:41,080 Speaker 1: them back. We actually empower these merchants to create their 103 00:04:41,120 --> 00:04:44,120 Speaker 1: own customer basis and then connect directly with them. Where 104 00:04:44,120 --> 00:04:47,920 Speaker 1: are you guys investing in heavily in SFN shop Life 105 00:04:47,880 --> 00:04:50,159 Speaker 1: Fulfilm Network. We think that is if you sort of 106 00:04:50,160 --> 00:04:51,920 Speaker 1: look at what we've been doing the last couple of years, 107 00:04:52,320 --> 00:04:54,600 Speaker 1: we're taking off all the different challenges that a small 108 00:04:54,600 --> 00:04:57,120 Speaker 1: business or a big business may have. We think fulfillment 109 00:04:57,200 --> 00:04:59,240 Speaker 1: is one of those things people don't want to use, 110 00:04:59,480 --> 00:05:02,720 Speaker 1: uh the party logistics companies because either the requirements and 111 00:05:02,800 --> 00:05:04,880 Speaker 1: moms are way too high, or they put everything in 112 00:05:04,920 --> 00:05:07,960 Speaker 1: the same box with their marketplaces logo on it. What 113 00:05:08,000 --> 00:05:10,760 Speaker 1: we're doing is we're creating this network of third party 114 00:05:10,800 --> 00:05:14,320 Speaker 1: warehouses were aggregating them using technology and software. We bought 115 00:05:14,320 --> 00:05:16,760 Speaker 1: a company in Boston called six Rubber Systems last year 116 00:05:16,920 --> 00:05:19,040 Speaker 1: for about four and fifty million dollars. They're going to 117 00:05:19,080 --> 00:05:22,320 Speaker 1: provide incredible robotic technology to make all warehouses a lot 118 00:05:22,320 --> 00:05:25,400 Speaker 1: more effective, and then we're gonna democratize shop of the 119 00:05:25,400 --> 00:05:27,359 Speaker 1: Fulfilming Network. The way we've done with e commerce. Just 120 00:05:27,400 --> 00:05:30,120 Speaker 1: real quick here, I'm wondering what's the most effective platform 121 00:05:30,240 --> 00:05:33,040 Speaker 1: for advertising that you found. It really depends, I think 122 00:05:33,080 --> 00:05:34,800 Speaker 1: for a lot of these DTC brands, the ones that 123 00:05:34,839 --> 00:05:38,560 Speaker 1: are you know, new director consumer mattress companies or companies 124 00:05:38,600 --> 00:05:41,279 Speaker 1: like that. Honestly, social media seems to be the best one. 125 00:05:41,400 --> 00:05:43,280 Speaker 1: Now that being said, others are are in more of 126 00:05:43,360 --> 00:05:46,400 Speaker 1: these traditional industries. Their TV is actually working really well 127 00:05:46,440 --> 00:05:49,680 Speaker 1: for them. Interesting, Probably real quickly, Elon mess Musk is 128 00:05:49,720 --> 00:05:53,520 Speaker 1: taking advantage of this surging share price to sell some stock. 129 00:05:53,560 --> 00:05:56,320 Speaker 1: Are you guys interested in selling stock? Not at this pine? Okay, 130 00:05:56,640 --> 00:05:58,640 Speaker 1: Harlie fickle ste and thank you so much for being here. 131 00:05:58,960 --> 00:06:02,360 Speaker 1: Charlie Finkelstein, two operating officer of Shopify based in Ottawa, 132 00:06:02,520 --> 00:06:14,920 Speaker 1: joining us here in our interactive broker studio. Well, the 133 00:06:14,960 --> 00:06:18,119 Speaker 1: global travel industry is really at the forefront of feeling 134 00:06:18,279 --> 00:06:22,840 Speaker 1: the brunt of the coronavirus. You know, I'm thinking cruise ships, hotels, casinos, 135 00:06:23,560 --> 00:06:27,120 Speaker 1: really seeing business impacted significantly in the shares of those 136 00:06:27,160 --> 00:06:29,640 Speaker 1: companies reflecting it as well. Our next guest has a 137 00:06:30,000 --> 00:06:33,200 Speaker 1: equally cautious view of those sectors. Tuna A Moobi. He's 138 00:06:33,240 --> 00:06:37,360 Speaker 1: a director and industry research analysts at cf R A Research. 139 00:06:37,440 --> 00:06:39,720 Speaker 1: He joins us on the phone, Thanks so much for 140 00:06:39,880 --> 00:06:42,880 Speaker 1: joining us again. I know you've gone become more cautious, 141 00:06:42,920 --> 00:06:45,400 Speaker 1: downgraded a bunch of stocks. Tell us how you see 142 00:06:45,520 --> 00:06:48,599 Speaker 1: kind of some of these uh, casino companies, cruise lines 143 00:06:48,640 --> 00:06:51,920 Speaker 1: and the like. Good morning, uh Paul, my friend, and 144 00:06:52,040 --> 00:06:55,280 Speaker 1: thanks for having me. Um. So over the past um 145 00:06:55,480 --> 00:06:58,159 Speaker 1: two weeks or so, we have actually taken a more 146 00:06:58,680 --> 00:07:03,440 Speaker 1: dare assessment of a potential impact of the coronavirus on UM, 147 00:07:03,560 --> 00:07:06,800 Speaker 1: you know, the overall tourism and UM, you know, the 148 00:07:07,360 --> 00:07:12,000 Speaker 1: cruise ships, UM, the online travel companies, the casinos. The 149 00:07:12,120 --> 00:07:15,960 Speaker 1: one constant theme has emerged is that, UM, you know, 150 00:07:16,120 --> 00:07:19,760 Speaker 1: while it's very difficult to quantify the overall impact, and 151 00:07:19,840 --> 00:07:21,960 Speaker 1: of course no one really knows the duration of how 152 00:07:22,000 --> 00:07:24,520 Speaker 1: long it's gonna last, but we think that it's starting 153 00:07:24,560 --> 00:07:27,440 Speaker 1: to take a toll right now. And you just heard 154 00:07:27,440 --> 00:07:31,160 Speaker 1: about you know, the higher number of death tolls UM, 155 00:07:31,320 --> 00:07:34,480 Speaker 1: as well as more cases being diagnosed. So my sense is, UM, 156 00:07:34,880 --> 00:07:38,640 Speaker 1: you know, the market may still be underestimating the potential 157 00:07:38,680 --> 00:07:40,920 Speaker 1: impact of this, if you remember, UM, I think it 158 00:07:40,960 --> 00:07:43,240 Speaker 1: seems to be some comfort level that if you compared 159 00:07:43,320 --> 00:07:46,080 Speaker 1: to the um the Stars or the Bola, and while 160 00:07:46,160 --> 00:07:50,200 Speaker 1: those cases were ultimately you know, resolved, limiting its impact, 161 00:07:50,680 --> 00:07:53,680 Speaker 1: what warries us here is really the speed and severity 162 00:07:53,880 --> 00:07:56,360 Speaker 1: of of the of the new cases that are being 163 00:07:56,400 --> 00:07:58,360 Speaker 1: diagnosed on the death toll, which kind of leads us 164 00:07:58,400 --> 00:08:00,360 Speaker 1: to believe that this is gonna come. You need to 165 00:08:00,400 --> 00:08:02,960 Speaker 1: be an overhang as as the year goes on for 166 00:08:03,160 --> 00:08:05,240 Speaker 1: for quite some time. You know, it's so interesting to 167 00:08:05,320 --> 00:08:08,920 Speaker 1: hear you speak, because we speak with economists and investors 168 00:08:08,960 --> 00:08:11,720 Speaker 1: who say they're expecting some sort of V shaped recovery 169 00:08:11,880 --> 00:08:15,360 Speaker 1: in the economy of China and beyond. And I'm wondering 170 00:08:15,400 --> 00:08:19,240 Speaker 1: as you look at MGM basically withdrawing their entire outlook 171 00:08:19,320 --> 00:08:22,160 Speaker 1: for the year, citing the disruption from the coronavirus, the 172 00:08:22,240 --> 00:08:24,600 Speaker 1: fact that they get twenty seven percent of their business 173 00:08:24,640 --> 00:08:27,560 Speaker 1: from Macau UH and are losing and estimated more than 174 00:08:27,600 --> 00:08:30,840 Speaker 1: a million dollars a day based on the current shutdown 175 00:08:30,920 --> 00:08:34,040 Speaker 1: that we're seeing, how can we even be so sure 176 00:08:34,400 --> 00:08:38,000 Speaker 1: that a place like MGM could compensate for this later 177 00:08:38,120 --> 00:08:41,720 Speaker 1: on we can be at the short answer, We're actually 178 00:08:41,800 --> 00:08:44,640 Speaker 1: are taking a more negative view of MBM downgrading to 179 00:08:44,720 --> 00:08:48,120 Speaker 1: itsell ahead of their earnings. Um, you know report last night. 180 00:08:48,200 --> 00:08:51,640 Speaker 1: I think that just confirmed to us, um that you know, 181 00:08:51,840 --> 00:08:53,720 Speaker 1: no one really has a handle of this. So they 182 00:08:53,840 --> 00:08:57,720 Speaker 1: talked about the expanded burn rate about one point five 183 00:08:57,800 --> 00:09:01,160 Speaker 1: million dollars on a daily basis evil, while the casinos 184 00:09:01,320 --> 00:09:04,760 Speaker 1: have been shot down mostly for peril, and that was 185 00:09:04,840 --> 00:09:07,400 Speaker 1: also a thing that we heard from Wind Resources and 186 00:09:07,480 --> 00:09:11,120 Speaker 1: in Las Vegas. So I think you're really starting to see, uh, 187 00:09:11,200 --> 00:09:13,959 Speaker 1: you know, the casinos starting to feel the brunt of this. 188 00:09:14,160 --> 00:09:17,040 Speaker 1: And remember, um, you know, these are you know, in 189 00:09:17,200 --> 00:09:20,720 Speaker 1: an industry that was alreadily already I'm sorry, already massively 190 00:09:20,760 --> 00:09:25,240 Speaker 1: impacted by the Hong Kong protest. So these latest coronavirus 191 00:09:25,320 --> 00:09:27,679 Speaker 1: issue just seems to be adding a saut to to 192 00:09:27,880 --> 00:09:30,679 Speaker 1: injury and really no one how to handle on on 193 00:09:30,800 --> 00:09:33,120 Speaker 1: when this is gonna dissipay. Now, one more thing I'd 194 00:09:33,160 --> 00:09:35,720 Speaker 1: add is that even when the situation is resolved, typically 195 00:09:36,000 --> 00:09:40,000 Speaker 1: from a historical perspective, we usually see several months before 196 00:09:40,080 --> 00:09:43,679 Speaker 1: things can get any semblance of normalization, which is really 197 00:09:43,720 --> 00:09:47,000 Speaker 1: why we think this twenty um at least the first 198 00:09:47,040 --> 00:09:50,120 Speaker 1: half certainly is gonna need much more caution to know 199 00:09:50,520 --> 00:09:55,240 Speaker 1: this is definitely specific to the casino industry the travel industries. 200 00:09:55,920 --> 00:09:58,600 Speaker 1: Is there, though, a broader brush that we could paint 201 00:09:58,800 --> 00:10:02,520 Speaker 1: in terms of the potential longer term impact given your 202 00:10:02,559 --> 00:10:06,760 Speaker 1: experience examining the corporate balance sheets of these companies as 203 00:10:06,800 --> 00:10:10,640 Speaker 1: well as the likes of Amazon and Netflix. Well, you 204 00:10:10,720 --> 00:10:15,160 Speaker 1: know one thing that I'd say that China overall, um, 205 00:10:15,640 --> 00:10:17,600 Speaker 1: you know, most of these companies you talk about, Amazon 206 00:10:17,640 --> 00:10:21,800 Speaker 1: and Netflix have a relatively limited direct exposure in China 207 00:10:21,920 --> 00:10:25,240 Speaker 1: poly due to the regulatory um environment now. But I 208 00:10:25,360 --> 00:10:28,319 Speaker 1: think the UM what I see is some type of 209 00:10:28,600 --> 00:10:33,440 Speaker 1: uh uh you know, um kind of tangential fallout from 210 00:10:33,480 --> 00:10:37,920 Speaker 1: this geopolitical situation. UM. A lot of these companies, even 211 00:10:38,040 --> 00:10:41,160 Speaker 1: when they are not directly operating in China, have some 212 00:10:41,400 --> 00:10:46,160 Speaker 1: type of strategic partnership. That's true certainly for online travel companies, 213 00:10:46,200 --> 00:10:48,480 Speaker 1: and of course casinos have a huge stake in there. 214 00:10:48,960 --> 00:10:53,640 Speaker 1: So every industry is different. China itself has been a major, 215 00:10:54,360 --> 00:10:59,440 Speaker 1: uh you know, kind of driver of global tourism outbound travel, 216 00:11:00,160 --> 00:11:03,360 Speaker 1: and I think what's important to remember is that while um, 217 00:11:03,720 --> 00:11:06,360 Speaker 1: most of the issues right now appeared to be limited 218 00:11:06,400 --> 00:11:10,200 Speaker 1: to China, they could be. In fact, it broader geopolitical 219 00:11:10,520 --> 00:11:14,240 Speaker 1: impact across even the US and other uh you know 220 00:11:14,559 --> 00:11:17,959 Speaker 1: markets like Europe. Of course, that depends on how fast 221 00:11:18,040 --> 00:11:22,240 Speaker 1: those uh cases travel, but overall, while the overall impact 222 00:11:22,360 --> 00:11:25,120 Speaker 1: on GDP growth is the relatively meted at this point, 223 00:11:25,200 --> 00:11:28,439 Speaker 1: I think you could actually uh see that situation get 224 00:11:28,480 --> 00:11:31,240 Speaker 1: out of control pretty fast. So so it's just on 225 00:11:31,360 --> 00:11:33,319 Speaker 1: the cruise lines here. I know, when you talked to 226 00:11:33,360 --> 00:11:35,640 Speaker 1: a lot of people about, you know, why don't you 227 00:11:36,040 --> 00:11:37,760 Speaker 1: go on a cruise, one of the concerns is just 228 00:11:37,920 --> 00:11:39,959 Speaker 1: being you know, stuck with so many people in a 229 00:11:40,040 --> 00:11:42,679 Speaker 1: confined area, and it just seems like, you know, these 230 00:11:42,760 --> 00:11:45,319 Speaker 1: outbreaks of diseases are perhaps more common there. Do you 231 00:11:45,360 --> 00:11:48,679 Speaker 1: think there's longer term risk to kind of just the 232 00:11:48,720 --> 00:11:52,240 Speaker 1: whole market, you know, total market size for the cruising 233 00:11:52,280 --> 00:11:55,400 Speaker 1: industry from this, I think what's interesting that before this 234 00:11:55,520 --> 00:11:59,320 Speaker 1: coronavirus outbreak, um, you know, the cruise industry fundamentals were 235 00:11:59,360 --> 00:12:01,520 Speaker 1: pretty healthy. We're expecting the you know, kind of a 236 00:12:01,600 --> 00:12:05,200 Speaker 1: near record year based on advanced indicators of booking and pricing, 237 00:12:05,280 --> 00:12:08,240 Speaker 1: on board spending. Um, you know, all of those indicators 238 00:12:08,240 --> 00:12:11,000 Speaker 1: seem to be holding up well. Now, Uh it seems 239 00:12:11,000 --> 00:12:13,520 Speaker 1: like all bets are off when you kind of hear 240 00:12:14,080 --> 00:12:17,280 Speaker 1: stories about you know, the diamond prices being quarantined and 241 00:12:17,480 --> 00:12:21,160 Speaker 1: several other ships unable to find landing ports or destinations. 242 00:12:21,280 --> 00:12:23,679 Speaker 1: My sense is that there is a certain amount of 243 00:12:23,720 --> 00:12:28,480 Speaker 1: weariness out there, um among potential cruise passengers in terms 244 00:12:28,520 --> 00:12:32,360 Speaker 1: of booking pending the resolution of this issue. So, um, 245 00:12:32,480 --> 00:12:35,880 Speaker 1: I think you're starting to see the guidance from cruise companies. Uh. 246 00:12:36,000 --> 00:12:38,199 Speaker 1: You know, at risk is actually why we took a 247 00:12:38,280 --> 00:12:41,600 Speaker 1: more negative stance on Royal Caribbean as well as um 248 00:12:41,800 --> 00:12:45,240 Speaker 1: A Norwegian Cruise, both of which we downgraded well obviously 249 00:12:45,280 --> 00:12:48,440 Speaker 1: along on carnivals. So uh, this is something that's gonna 250 00:12:48,559 --> 00:12:53,400 Speaker 1: over over the industry until any more visibility in terms 251 00:12:53,480 --> 00:12:56,640 Speaker 1: of the potential resolution to not just real quick here 252 00:12:56,720 --> 00:12:59,439 Speaker 1: thirty seconds. Do you buy this argument that Netflix is 253 00:12:59,440 --> 00:13:01,839 Speaker 1: getting a whach boost from this because people are sitting 254 00:13:01,920 --> 00:13:04,559 Speaker 1: home and doing Netflix and chill rather than going out 255 00:13:04,600 --> 00:13:09,360 Speaker 1: potentially getting coronavirus a leita. That's something we've heard before, 256 00:13:09,480 --> 00:13:12,679 Speaker 1: but I'd say a little bit far fetched at this point. 257 00:13:13,240 --> 00:13:15,920 Speaker 1: It's really hard to kind of connect those dots. That 258 00:13:16,040 --> 00:13:18,880 Speaker 1: being said. I mean, I can understand why, you know, 259 00:13:19,040 --> 00:13:22,520 Speaker 1: maybe isolated cases that could be true, but hard to 260 00:13:22,600 --> 00:13:25,120 Speaker 1: generalize here do you know, Moby, thank you so much 261 00:13:25,160 --> 00:13:27,839 Speaker 1: to know MOBI director and industry analysts. It's c f 262 00:13:27,960 --> 00:13:29,840 Speaker 1: R A Research and joining us on the phone from 263 00:13:29,880 --> 00:13:31,679 Speaker 1: New Jersey, I love that I write a bunch of 264 00:13:31,720 --> 00:13:34,599 Speaker 1: stories about how Netflix. You know, we talk about the 265 00:13:34,720 --> 00:13:37,760 Speaker 1: negative impact of the coronavirus, but there are companies benefiting 266 00:13:37,800 --> 00:13:39,560 Speaker 1: because people are staying home and they've got to do something, 267 00:13:39,640 --> 00:13:54,880 Speaker 1: so they might as well watch movies. On Monday, the 268 00:13:54,920 --> 00:13:57,959 Speaker 1: Department of Justice and anced charges against four members of 269 00:13:58,040 --> 00:14:03,160 Speaker 1: China's People's Liberation Army hack of Equifax, and this was 270 00:14:03,280 --> 00:14:06,000 Speaker 1: something that exposed millions of Americans and their private data. 271 00:14:06,520 --> 00:14:11,040 Speaker 1: It raises questions. Putting aside this particular case, it raises 272 00:14:11,120 --> 00:14:14,120 Speaker 1: questions about just how well we are able to detect 273 00:14:14,720 --> 00:14:19,040 Speaker 1: the attacks that our data is exposed to every single day. 274 00:14:19,120 --> 00:14:22,080 Speaker 1: Joining us here in studio, Steve Wagner, Global Managing Director 275 00:14:22,080 --> 00:14:25,440 Speaker 1: of Decision Analytics four experience. Uh, Steve, so glad to 276 00:14:25,520 --> 00:14:27,720 Speaker 1: have you. I want to start with that, where are 277 00:14:27,840 --> 00:14:31,080 Speaker 1: we when it comes to detection when it comes to 278 00:14:31,120 --> 00:14:35,400 Speaker 1: these attacks? Sure? Well, the particular angle that we tend 279 00:14:35,440 --> 00:14:38,480 Speaker 1: to come at this from in my business is is 280 00:14:38,800 --> 00:14:43,840 Speaker 1: really fraud and identity um within commercial transactions? So a 281 00:14:43,920 --> 00:14:46,400 Speaker 1: lot of ways you can answer your question. We're focused 282 00:14:46,440 --> 00:14:50,840 Speaker 1: on that particular angle UM I think when we think 283 00:14:50,880 --> 00:14:53,840 Speaker 1: about it, and we just released a study that we've 284 00:14:53,880 --> 00:14:58,360 Speaker 1: done a six hundred six thousand, five hundred consumers and 285 00:14:58,920 --> 00:15:01,440 Speaker 1: six fifty bi no. This is in thirteen countries around 286 00:15:01,440 --> 00:15:04,160 Speaker 1: the world, and we've been looking at this question of 287 00:15:04,680 --> 00:15:08,080 Speaker 1: how businesses should sort of say, shape their understanding, how 288 00:15:08,120 --> 00:15:10,560 Speaker 1: do they react, what do they do? So the big 289 00:15:10,960 --> 00:15:15,120 Speaker 1: issue is businesses faced with those kind of security threats 290 00:15:15,640 --> 00:15:19,480 Speaker 1: instinctively sometimes will just clamp down, right, I you know, 291 00:15:19,560 --> 00:15:21,000 Speaker 1: the best thing for me to do is to not 292 00:15:21,440 --> 00:15:24,520 Speaker 1: be involved digitally with anybody. Of course, that doesn't really 293 00:15:24,560 --> 00:15:28,400 Speaker 1: allow you to do business very much. So the business persons, Yeah, 294 00:15:28,440 --> 00:15:30,320 Speaker 1: the business person really has to think through what's the 295 00:15:30,440 --> 00:15:31,800 Speaker 1: right way to do that, what's the right way to 296 00:15:31,880 --> 00:15:35,080 Speaker 1: make commerce work? So what our business people are generally 297 00:15:35,200 --> 00:15:38,800 Speaker 1: thinking about is how do I create an extraordinary digital 298 00:15:38,880 --> 00:15:42,040 Speaker 1: experience for my consumers? That's what they want to do, right. 299 00:15:42,240 --> 00:15:46,600 Speaker 1: What we found in this particular study was that of 300 00:15:46,680 --> 00:15:49,960 Speaker 1: businesses believe that they're actually doing a good job of 301 00:15:50,000 --> 00:15:54,960 Speaker 1: identifying who's coming to them, um Electronically, fifty of consumers 302 00:15:55,400 --> 00:15:58,360 Speaker 1: believe that the business is actually understand who they are, 303 00:15:59,440 --> 00:16:03,040 Speaker 1: which is obviously a significant mismatch. So do you think 304 00:16:03,080 --> 00:16:06,200 Speaker 1: the businesses that think the businesses think they're doing a 305 00:16:06,280 --> 00:16:09,320 Speaker 1: good good job identifying who their customers are? Is that 306 00:16:10,560 --> 00:16:12,840 Speaker 1: is that kind of false sense of security there? Do 307 00:16:12,920 --> 00:16:16,400 Speaker 1: you think that that is a really valid number? Well? What, well, 308 00:16:16,400 --> 00:16:18,200 Speaker 1: I think the numbers valid in the study, but what 309 00:16:18,360 --> 00:16:20,240 Speaker 1: they're what you have to get to in order to 310 00:16:20,360 --> 00:16:23,840 Speaker 1: understand that mismatch is the way businesses are looking at 311 00:16:23,880 --> 00:16:26,600 Speaker 1: it today versus the way consumers are looking at it. 312 00:16:26,920 --> 00:16:29,040 Speaker 1: So the way when you when you talk to a consumer, 313 00:16:29,080 --> 00:16:31,240 Speaker 1: what do they care about first and foremost in the 314 00:16:31,360 --> 00:16:35,120 Speaker 1: digital interactions, they care about security. So actually, when you 315 00:16:35,200 --> 00:16:38,560 Speaker 1: talk to a consumer your business, you're dealing with them 316 00:16:38,640 --> 00:16:42,840 Speaker 1: online in disha of security. Make them feel better, make 317 00:16:42,880 --> 00:16:45,520 Speaker 1: them happier to interact with you. A business. On the 318 00:16:45,600 --> 00:16:48,400 Speaker 1: other hand, when you rank their priorities, number one in 319 00:16:48,480 --> 00:16:53,040 Speaker 1: their priority list is uh creating an experience that is 320 00:16:53,320 --> 00:16:56,120 Speaker 1: targeted to that individual, right, So in other words, they'll 321 00:16:56,120 --> 00:16:58,280 Speaker 1: look at it, they'll say, yeah, I understand. I know 322 00:16:58,360 --> 00:17:00,840 Speaker 1: who Paul is. I've seen them before. Um, that's all 323 00:17:00,880 --> 00:17:02,480 Speaker 1: I need to know. Now. The real question is whether 324 00:17:02,560 --> 00:17:04,480 Speaker 1: or not the things I say to Paul and what 325 00:17:04,600 --> 00:17:07,080 Speaker 1: I do with Paul is really on target or not. 326 00:17:07,880 --> 00:17:10,200 Speaker 1: And the consumers just saying, hey, look, actually, when you 327 00:17:10,280 --> 00:17:12,879 Speaker 1: asked me for passwords and you asked me, you know, 328 00:17:12,960 --> 00:17:15,960 Speaker 1: put me into a credential environment. That's what I'm willing 329 00:17:16,040 --> 00:17:18,680 Speaker 1: to share. So, you know, but this goes really to 330 00:17:18,760 --> 00:17:21,159 Speaker 1: the heart of do you know who you're dealing with? 331 00:17:21,640 --> 00:17:27,080 Speaker 1: Do you know what the incoming attention you're getting really 332 00:17:27,320 --> 00:17:30,080 Speaker 1: is about. According to the same study you you talked about, 333 00:17:30,080 --> 00:17:33,320 Speaker 1: how fraud continues to increase, with fifty seven percent of 334 00:17:33,359 --> 00:17:35,960 Speaker 1: businesses citing an increase in the past twelve months. And 335 00:17:36,040 --> 00:17:38,200 Speaker 1: I just wonder how much this is an increase in 336 00:17:38,280 --> 00:17:41,080 Speaker 1: the ability to detect some of these and how much 337 00:17:41,160 --> 00:17:44,560 Speaker 1: is an increase in attacks or is it both? Yeah, 338 00:17:44,640 --> 00:17:46,800 Speaker 1: So I think there's an opportunity in the market right 339 00:17:46,840 --> 00:17:50,359 Speaker 1: now because I think what we've identified this mismatch between 340 00:17:50,400 --> 00:17:54,040 Speaker 1: how consumers feel and where businesses are. Businesses also believe 341 00:17:54,600 --> 00:17:57,240 Speaker 1: that if they really understand who the consumer is, fraud 342 00:17:57,280 --> 00:18:00,200 Speaker 1: will go down so sort of it's clear in the 343 00:18:00,280 --> 00:18:03,760 Speaker 1: study that businesses aren't quite getting it right yet. So 344 00:18:04,040 --> 00:18:08,200 Speaker 1: what businesses need to do is UM is take more 345 00:18:08,240 --> 00:18:11,639 Speaker 1: advantage of the data and the analytics that are available 346 00:18:11,760 --> 00:18:14,680 Speaker 1: within these online digital environments. So right now, I don't 347 00:18:14,680 --> 00:18:16,959 Speaker 1: think they do that enough. They tend to say, all right, 348 00:18:17,000 --> 00:18:19,720 Speaker 1: I've gotten passwords for this individual, I know their name, 349 00:18:19,760 --> 00:18:22,280 Speaker 1: I know if you I know them. But actually there's 350 00:18:22,359 --> 00:18:26,760 Speaker 1: a quite a bit more UM available, and in particular, 351 00:18:27,119 --> 00:18:31,919 Speaker 1: there's there are quite a few individual threat modality fraud 352 00:18:32,040 --> 00:18:35,000 Speaker 1: tools that you can use. And the question is are 353 00:18:35,080 --> 00:18:38,960 Speaker 1: these being knitted together into a comprehensive way or our 354 00:18:39,000 --> 00:18:41,679 Speaker 1: business is just employing Oh, I use I use device, 355 00:18:41,800 --> 00:18:46,200 Speaker 1: I d oh, I use biometric behavioral biometrics, I use this, 356 00:18:46,880 --> 00:18:49,560 Speaker 1: when in fact, what you really need to win today 357 00:18:50,000 --> 00:18:53,639 Speaker 1: is you need a comprehensive capability that incorporates sort of 358 00:18:53,800 --> 00:18:56,879 Speaker 1: all of the different tools that are available, layers that 359 00:18:57,160 --> 00:19:01,360 Speaker 1: with UM analytics so that you can really instruct strong defenses. 360 00:19:01,440 --> 00:19:03,640 Speaker 1: Steve Wagner, thanks so much for joining us. Really fascinating 361 00:19:03,720 --> 00:19:05,639 Speaker 1: that discussion is more and more of our time is 362 00:19:05,680 --> 00:19:08,920 Speaker 1: spent online. Uh, you have to balance the does the 363 00:19:09,440 --> 00:19:11,680 Speaker 1: business know me and are they protecting my data? And 364 00:19:11,720 --> 00:19:14,080 Speaker 1: all those times. Such an interesting concept that, you know, 365 00:19:14,240 --> 00:19:17,560 Speaker 1: there's one thing about having artificial intelligence detecting all of 366 00:19:17,640 --> 00:19:20,160 Speaker 1: the incoming threats. It's another thing just know who you're 367 00:19:20,200 --> 00:19:22,320 Speaker 1: dealing with at any given time and how do you 368 00:19:22,400 --> 00:19:25,040 Speaker 1: do that well, and that sort of dual approach to 369 00:19:25,200 --> 00:19:27,520 Speaker 1: trying to stave off some of the attacks that are 370 00:19:27,560 --> 00:19:29,800 Speaker 1: seeming that seemed to be increasing for every business that 371 00:19:29,880 --> 00:19:33,120 Speaker 1: does that does that operates in the online world, which 372 00:19:33,160 --> 00:19:36,879 Speaker 1: is everyone everyone. Steve Wagener, Global Managing Director, Experience Digions 373 00:19:37,080 --> 00:19:41,199 Speaker 1: Decision Analytics, based in Orange County, California, but joining us 374 00:19:41,200 --> 00:19:56,760 Speaker 1: here in our Bloomberg Interactor broker Studio Tesla really in 375 00:19:56,800 --> 00:20:00,360 Speaker 1: the front and focus today which shares up one point 376 00:20:00,440 --> 00:20:03,200 Speaker 1: six percent. This is amazing because ahead of the open 377 00:20:03,320 --> 00:20:06,000 Speaker 1: we saw shares down as much as seven point two 378 00:20:06,080 --> 00:20:08,680 Speaker 1: per cent. And this comes after a filing showing that 379 00:20:08,760 --> 00:20:12,119 Speaker 1: they planned a two billion dollar offering of common stock 380 00:20:12,200 --> 00:20:14,200 Speaker 1: taking advantage of the rally and the share price that 381 00:20:14,280 --> 00:20:19,639 Speaker 1: we've seen that's been absolutely astronomical. I'm trying to understand 382 00:20:20,080 --> 00:20:22,480 Speaker 1: a why people don't seem to care that they're going 383 00:20:22,520 --> 00:20:26,280 Speaker 1: to be diluted, very very marginally. But typically this is 384 00:20:26,359 --> 00:20:30,760 Speaker 1: something that that matters, uh, and be why then Tesla 385 00:20:30,840 --> 00:20:33,320 Speaker 1: didn't raise more? Kevin Tynan joining us here in our 386 00:20:33,320 --> 00:20:36,920 Speaker 1: interactive broker studios Kevin Tyne and Senior Auto's analyst for 387 00:20:37,040 --> 00:20:40,760 Speaker 1: Bloomberg Intelligence. Kevin, let's just first talk about the response. 388 00:20:40,880 --> 00:20:44,280 Speaker 1: Why are shares up today? Um? Well, because I think 389 00:20:44,359 --> 00:20:48,720 Speaker 1: the idea of adding uh capital of the balance she 390 00:20:49,119 --> 00:20:53,600 Speaker 1: wasn't an overhang, right. I think that the investors believe 391 00:20:53,760 --> 00:20:56,840 Speaker 1: that they are. He said this in the middle of 392 00:20:57,600 --> 00:20:59,840 Speaker 1: they're going to be profitable from here forward. They're going 393 00:20:59,880 --> 00:21:03,159 Speaker 1: to fund themselves from here forward. So I think that 394 00:21:03,480 --> 00:21:06,639 Speaker 1: that removed the bear case or that bear argument at 395 00:21:06,720 --> 00:21:10,240 Speaker 1: that time. Uh So, needing a little bit of capital here, 396 00:21:10,320 --> 00:21:12,600 Speaker 1: it's it's it's not that big a deal to sort 397 00:21:12,600 --> 00:21:15,800 Speaker 1: of reverse, especially when you think of the circumstances, right, 398 00:21:15,840 --> 00:21:18,680 Speaker 1: it was it's a no brainer considering the way the 399 00:21:18,760 --> 00:21:21,160 Speaker 1: stock is run and and the amount of it's it's 400 00:21:21,280 --> 00:21:23,200 Speaker 1: absolutely the right thing to do. And to your point, 401 00:21:23,240 --> 00:21:26,560 Speaker 1: I would say, why not do even more than that? Um? 402 00:21:27,119 --> 00:21:29,520 Speaker 1: But but a lot of the way this has managed, 403 00:21:29,600 --> 00:21:33,040 Speaker 1: this company has manages about that perception, right, Just the 404 00:21:33,160 --> 00:21:36,159 Speaker 1: idea of burning short sellers, right, is just something you 405 00:21:36,200 --> 00:21:38,920 Speaker 1: don't really see from most ceo s. Right, you run 406 00:21:39,000 --> 00:21:44,600 Speaker 1: the business the right way, uh profitably growth and that 407 00:21:44,800 --> 00:21:48,080 Speaker 1: takes care of itself. To actively sort of target that 408 00:21:48,200 --> 00:21:50,800 Speaker 1: group is just it's just unorthodox. And I think that's 409 00:21:50,920 --> 00:21:53,160 Speaker 1: a big part of it, is that perception that raising 410 00:21:53,200 --> 00:21:56,760 Speaker 1: capital shows a sign of weakness, that we can't fund ourselves, 411 00:21:56,840 --> 00:21:59,560 Speaker 1: when in fact it's just part of the process and 412 00:21:59,640 --> 00:22:01,200 Speaker 1: when it make sense to do so, you do it. 413 00:22:01,600 --> 00:22:04,160 Speaker 1: So the company also announced that they're going to spend 414 00:22:04,200 --> 00:22:06,840 Speaker 1: about three and a half billion dollars in capex this year. 415 00:22:07,400 --> 00:22:09,399 Speaker 1: Give us us Is that enough for some of the 416 00:22:09,520 --> 00:22:16,680 Speaker 1: plans they've announced. It is because of UM he loves leverage, 417 00:22:16,760 --> 00:22:20,960 Speaker 1: and really in this environment, who doesn't UM. So a 418 00:22:21,040 --> 00:22:24,200 Speaker 1: lot of that fixed investment will come from from borroing, 419 00:22:24,320 --> 00:22:27,960 Speaker 1: like so, even the Shanghai factory was money taken down 420 00:22:28,040 --> 00:22:30,679 Speaker 1: from the from the Chinese government, and same thing probably 421 00:22:30,760 --> 00:22:34,400 Speaker 1: with Berlin. So so that capex number that they put 422 00:22:34,440 --> 00:22:37,119 Speaker 1: out there probably does not include anything they would borrow 423 00:22:37,280 --> 00:22:41,080 Speaker 1: to UM to build those factories or to expand out 424 00:22:41,160 --> 00:22:44,040 Speaker 1: and get to some level of scale in China. Whether 425 00:22:44,200 --> 00:22:48,240 Speaker 1: that's distribution infrastructure or sales infrastructure. All that stuff will 426 00:22:48,280 --> 00:22:50,520 Speaker 1: come out of that cap X number, but the buildings 427 00:22:50,600 --> 00:22:53,200 Speaker 1: themselves will come from the borrowing. Ela Musk has said 428 00:22:53,240 --> 00:22:55,479 Speaker 1: that they were not going to be raising more capital 429 00:22:55,600 --> 00:22:58,480 Speaker 1: this year, so this isn't about face for him. Also, 430 00:22:58,640 --> 00:23:01,840 Speaker 1: Tesla has been cutting pockets expenditures over the past few 431 00:23:01,960 --> 00:23:05,399 Speaker 1: years in response to criticism about burning through cash, and 432 00:23:05,480 --> 00:23:08,399 Speaker 1: they reported an actually that profit, which is one of 433 00:23:08,440 --> 00:23:12,080 Speaker 1: the reasons why shares rallied so much. Given that, and 434 00:23:12,200 --> 00:23:14,639 Speaker 1: given that they seem to be doubling down on the 435 00:23:14,720 --> 00:23:18,640 Speaker 1: spending and not necessarily the cash generation, why are investors 436 00:23:18,920 --> 00:23:22,040 Speaker 1: so sanguine about this move? Well? I think also to 437 00:23:22,600 --> 00:23:28,080 Speaker 1: keep in mind the projects that he's that he's teased, right, 438 00:23:28,200 --> 00:23:32,719 Speaker 1: so there's roadster two point oh, there's semi truck, There's 439 00:23:33,240 --> 00:23:37,439 Speaker 1: there's cybertruck, there's Model why coming, There's all these grand plans. 440 00:23:37,480 --> 00:23:43,560 Speaker 1: There's Robotaxi fleet a million units in so so investors 441 00:23:43,640 --> 00:23:46,959 Speaker 1: the reaction will be like, he's funding the growth, right, 442 00:23:47,040 --> 00:23:49,720 Speaker 1: There's enough things to do, there's factories to build, there's 443 00:23:49,960 --> 00:23:52,320 Speaker 1: products to put out there that this is what you 444 00:23:52,440 --> 00:23:54,240 Speaker 1: have to do. You need capital do it and that's 445 00:23:54,280 --> 00:23:57,159 Speaker 1: what he's doing real quick. What's the demand for electric 446 00:23:57,200 --> 00:24:00,200 Speaker 1: vehicles to have a boy, you know, it was is 447 00:24:00,240 --> 00:24:05,240 Speaker 1: in the one percent range in nineteen, So one of 448 00:24:05,280 --> 00:24:08,560 Speaker 1: the bulls think it will be well if if you 449 00:24:08,680 --> 00:24:12,000 Speaker 1: ask the Uber bowls, it's gonna be that everybody who 450 00:24:12,040 --> 00:24:14,280 Speaker 1: owns a car will have to have an electric vehicle. 451 00:24:14,320 --> 00:24:17,520 Speaker 1: Plus it's not only a vehicle, right, it's your smartphone, 452 00:24:17,600 --> 00:24:22,159 Speaker 1: It's it's everything. So Tesla as a technology company can 453 00:24:22,240 --> 00:24:24,000 Speaker 1: be all things. Everybody who needs a car and a 454 00:24:24,080 --> 00:24:28,960 Speaker 1: phone is their addressable market. Kevin Tyne and Senior Auto's 455 00:24:28,960 --> 00:24:31,880 Speaker 1: analyst Bloomberg Intelligence joining us here on our Bloomberg Interactive 456 00:24:31,880 --> 00:24:34,280 Speaker 1: Broker Studio. Tesla stock up just you know, about one 457 00:24:34,320 --> 00:24:36,480 Speaker 1: and one and a half percent here, But that back 458 00:24:36,560 --> 00:24:38,919 Speaker 1: on the news of a two maybe two point three 459 00:24:39,000 --> 00:24:42,480 Speaker 1: billion dollar stock offering, UH and the associated the dilution 460 00:24:42,520 --> 00:24:45,000 Speaker 1: and supply into the marketplace. Just extraordinary that the stocks 461 00:24:45,000 --> 00:24:47,880 Speaker 1: trading up. But Kevin was mentioning there is a lot 462 00:24:47,920 --> 00:24:50,600 Speaker 1: of capital demand for this company and there's a cull 463 00:24:50,680 --> 00:24:53,720 Speaker 1: to of belief behind Elon Musk, and I think there 464 00:24:53,760 --> 00:24:56,440 Speaker 1: are other company companies that if they suddenly decided to 465 00:24:56,520 --> 00:25:00,880 Speaker 1: invest money in some questionable project, people wouldn't rally behind them. 466 00:25:01,160 --> 00:25:03,320 Speaker 1: Elon Musk is a different case. It's a different case. 467 00:25:03,440 --> 00:25:06,880 Speaker 1: It is a cold stock for many. Thanks for listening 468 00:25:06,920 --> 00:25:09,320 Speaker 1: to the Bloomberg P and L podcast. You can subscribe 469 00:25:09,359 --> 00:25:12,119 Speaker 1: and listen to interviews at Apple Podcasts or whatever podcast 470 00:25:12,200 --> 00:25:15,679 Speaker 1: platform you prefer. Paul Sweeney, I'm on Twitter at pt Sweeney. 471 00:25:15,800 --> 00:25:17,960 Speaker 1: I'm Lisa abram Woy. It's I'm on Twitter at Lisa 472 00:25:18,000 --> 00:25:20,640 Speaker 1: abram wits one before the podcast, you can always catch 473 00:25:20,760 --> 00:25:22,520 Speaker 1: us worldwide. I'm Bloomberg Radio.