1 00:00:11,680 --> 00:00:15,000 Speaker 1: Hello, and welcome to another episode of the odd Lot Podcast. 2 00:00:15,000 --> 00:00:19,280 Speaker 1: I'm Joe Watson Ball and I'm Tracy ellowit Tracy. You know, 3 00:00:19,520 --> 00:00:21,760 Speaker 1: we're right in the middle of one of my favorite 4 00:00:21,760 --> 00:00:25,200 Speaker 1: times of the year. Do you know what that is? Uh? 5 00:00:25,960 --> 00:00:29,960 Speaker 1: Super Bowl? I don't know. It's not the super Bowl, 6 00:00:30,000 --> 00:00:32,839 Speaker 1: and it was the super Bowl last night for those listening, 7 00:00:32,880 --> 00:00:34,600 Speaker 1: we're recording this the day after the super Bowl. I 8 00:00:34,600 --> 00:00:36,320 Speaker 1: didn't even watch it, and from what I understand, it 9 00:00:36,400 --> 00:00:38,559 Speaker 1: was really boring, So I guess I didn't miss out 10 00:00:38,560 --> 00:00:41,320 Speaker 1: in anything. I mean, it is February, but February is 11 00:00:41,320 --> 00:00:43,080 Speaker 1: not one of my favorite times of the year because 12 00:00:43,080 --> 00:00:45,560 Speaker 1: the weather is pretty miserable. No, we are in uh, 13 00:00:45,840 --> 00:00:48,440 Speaker 1: the middle or maybe slightly later part of the middle 14 00:00:48,479 --> 00:00:51,880 Speaker 1: of earning season. What makes you like earning season so much? 15 00:00:52,440 --> 00:00:54,880 Speaker 1: Well so, for those who don't know, and probably everyone does, 16 00:00:56,040 --> 00:00:59,600 Speaker 1: most companies report their earnings uh four times a year, 17 00:00:59,640 --> 00:01:01,480 Speaker 1: and they tend to cluster over the span of a 18 00:01:01,520 --> 00:01:05,360 Speaker 1: few weeks. And so much of the time we talk macro, 19 00:01:06,120 --> 00:01:09,280 Speaker 1: we talk about the FED, we'll talk about trade, inflation, 20 00:01:09,440 --> 00:01:12,240 Speaker 1: economic data or whatever. And then every once in a 21 00:01:12,280 --> 00:01:14,640 Speaker 1: while we get to pause and actually hear from the 22 00:01:14,680 --> 00:01:17,920 Speaker 1: companies themselves and really get a sort of a corporate 23 00:01:17,959 --> 00:01:20,920 Speaker 1: perspective on how things are going. And of course, from 24 00:01:20,920 --> 00:01:24,080 Speaker 1: an investor perspective, this is what really matters, because you 25 00:01:24,120 --> 00:01:26,200 Speaker 1: can sort of have these broad movements and other times 26 00:01:26,200 --> 00:01:27,959 Speaker 1: of the year, but if you want to know how 27 00:01:27,959 --> 00:01:31,679 Speaker 1: a sort of specific investment in companies are doing, this 28 00:01:31,760 --> 00:01:35,000 Speaker 1: is when you glean the most as sort of raw information. 29 00:01:35,600 --> 00:01:37,360 Speaker 1: So I'm going to take the other side of this 30 00:01:37,440 --> 00:01:40,919 Speaker 1: and say that I normally don't get that excited about 31 00:01:40,959 --> 00:01:44,800 Speaker 1: earning season. However, I'm willing to admit that this time 32 00:01:44,840 --> 00:01:48,639 Speaker 1: around it is slightly more interesting than usual. But because 33 00:01:48,680 --> 00:01:52,000 Speaker 1: we have a lot of really broad sort of macro 34 00:01:52,400 --> 00:01:56,720 Speaker 1: economic themes that everyone is currently talking about. So a 35 00:01:56,720 --> 00:01:58,440 Speaker 1: couple that spring to mind. You know, we have to 36 00:01:58,480 --> 00:02:01,960 Speaker 1: slow down in China, whether or not that's actually affecting 37 00:02:02,120 --> 00:02:05,520 Speaker 1: US companies earnings, and we've seen some really heavy hitters, 38 00:02:05,560 --> 00:02:09,360 Speaker 1: including Caterpillar and Apple sort of blame things on a 39 00:02:09,400 --> 00:02:13,200 Speaker 1: slowdown in China. We have the retail apocalypse in the 40 00:02:13,320 --> 00:02:16,440 Speaker 1: US as well, this idea that bricks and mortars stores 41 00:02:16,480 --> 00:02:19,880 Speaker 1: are doing worse than other types of stores. So some big, 42 00:02:19,919 --> 00:02:25,400 Speaker 1: big thematic issues and questions currently running through earning season. Yeah, absolutely, 43 00:02:25,440 --> 00:02:28,560 Speaker 1: and especially the violence sell off that we saw at 44 00:02:28,600 --> 00:02:32,639 Speaker 1: the end of a lot of people. You know, people 45 00:02:33,040 --> 00:02:36,040 Speaker 1: adjust their future expectations based on what just happened. We 46 00:02:36,080 --> 00:02:38,800 Speaker 1: saw earnings estimates comes down for a lot of companies, 47 00:02:38,919 --> 00:02:42,600 Speaker 1: and everybody wanted to know because in the end fundamentals 48 00:02:42,720 --> 00:02:45,240 Speaker 1: in theory or with drive markets, was that just a 49 00:02:45,240 --> 00:02:49,720 Speaker 1: blip or companies really seeing a decline in profits? And 50 00:02:49,760 --> 00:02:52,320 Speaker 1: the other thing that I think is interesting from a 51 00:02:52,360 --> 00:02:54,960 Speaker 1: sort of sectoral perspective is that for the last couple 52 00:02:55,000 --> 00:02:59,000 Speaker 1: of years, especially a handful of really red hot tech 53 00:02:59,040 --> 00:03:03,400 Speaker 1: stocks that everyone was about have just dominated markets. If 54 00:03:03,440 --> 00:03:05,400 Speaker 1: you own them, you've done really well. Of course, I'm 55 00:03:05,440 --> 00:03:10,080 Speaker 1: talking about companies like Amazon and Facebook and Netflix and 56 00:03:10,120 --> 00:03:13,160 Speaker 1: so on, Apple of course, and each one of them 57 00:03:13,440 --> 00:03:16,399 Speaker 1: has sort of stumbled a little bit for different reasons, 58 00:03:16,440 --> 00:03:18,760 Speaker 1: and they've come well off their highs from last summer, 59 00:03:19,280 --> 00:03:21,760 Speaker 1: and I think going forward there's still this big question 60 00:03:21,840 --> 00:03:24,920 Speaker 1: like are they just gonna go back to dominating their 61 00:03:24,960 --> 00:03:31,160 Speaker 1: respective industries like they did in or did the sharp 62 00:03:31,240 --> 00:03:35,160 Speaker 1: rewriting of these stocks sort of represent something fundamental where 63 00:03:35,240 --> 00:03:38,160 Speaker 1: they're just not going to be able to put up 64 00:03:38,240 --> 00:03:42,120 Speaker 1: numbers like they did in the past, right, the famous 65 00:03:42,120 --> 00:03:45,560 Speaker 1: fang stocks which led the market higher basically for the 66 00:03:45,600 --> 00:03:49,840 Speaker 1: past few years and then suddenly let it very, very 67 00:03:49,840 --> 00:03:52,680 Speaker 1: sharply lower in the latter half of last year. And 68 00:03:52,680 --> 00:03:55,200 Speaker 1: to your point about a sharp rerating, you kind of 69 00:03:55,240 --> 00:03:59,120 Speaker 1: have to wonder what happened to make everyone sort of 70 00:03:59,160 --> 00:04:02,960 Speaker 1: collectively wake up and realize that their expectations for all 71 00:04:03,000 --> 00:04:06,400 Speaker 1: these companies were sort of out of lack of the fundamentals. Like, 72 00:04:06,480 --> 00:04:08,240 Speaker 1: it's a bit chicken and egg, isn't it. Is it 73 00:04:08,360 --> 00:04:11,320 Speaker 1: the market or is it actually that the fundamental picture 74 00:04:11,560 --> 00:04:15,280 Speaker 1: has changed? Well, Uh, that's very well put. And today's 75 00:04:15,320 --> 00:04:18,119 Speaker 1: guest on the out Lots podcast, I think is someone 76 00:04:18,279 --> 00:04:20,800 Speaker 1: very well positioned to talk about it. We talked to 77 00:04:20,880 --> 00:04:25,040 Speaker 1: him a lot on TV around earnings time, and I thought, Okay, 78 00:04:25,080 --> 00:04:27,800 Speaker 1: I want to have a longer discussion about some of 79 00:04:27,800 --> 00:04:30,120 Speaker 1: these companies. So today we're going to be talking to 80 00:04:30,279 --> 00:04:33,560 Speaker 1: Lead Rogan. He is the founder and CEO of Estimized, 81 00:04:34,000 --> 00:04:39,599 Speaker 1: which is a company that collects by side estimates for earnings. 82 00:04:39,640 --> 00:04:44,000 Speaker 1: But he's also incredibly knowledgeable about the market overall, about 83 00:04:44,000 --> 00:04:47,560 Speaker 1: the business models of these big tech companies, about why 84 00:04:47,720 --> 00:04:51,719 Speaker 1: investors either get excited or lose excitement towards these companies, 85 00:04:51,720 --> 00:04:56,120 Speaker 1: and so just a great perspective hopefully to answer some 86 00:04:56,240 --> 00:04:59,480 Speaker 1: of the questions that we've posed right now. I've been 87 00:05:00,040 --> 00:05:02,799 Speaker 1: you follow him on Twitter. He's been covering the trend 88 00:05:02,920 --> 00:05:06,160 Speaker 1: we're seeing for years and years, and I think we'll 89 00:05:06,200 --> 00:05:08,240 Speaker 1: have a lot to say about this topic. So Lee, 90 00:05:08,360 --> 00:05:10,840 Speaker 1: thank you very much for joining us. That's that's way 91 00:05:10,839 --> 00:05:14,599 Speaker 1: too kind and introduction. No, but I'm serious because often, 92 00:05:14,760 --> 00:05:17,840 Speaker 1: like well, I think we tend to speak about these 93 00:05:17,880 --> 00:05:21,680 Speaker 1: companies and sort of we abstract them. And so Facebook 94 00:05:21,760 --> 00:05:24,839 Speaker 1: is online advertising and social media, or Apple they have 95 00:05:24,920 --> 00:05:26,839 Speaker 1: to sell a lot of iPhones. And one of the 96 00:05:26,880 --> 00:05:29,240 Speaker 1: things that I really enjoy talking to you about is 97 00:05:29,279 --> 00:05:31,279 Speaker 1: you really seem to have a very good understanding of 98 00:05:31,360 --> 00:05:34,720 Speaker 1: sort of where the where the levers are and where 99 00:05:34,720 --> 00:05:38,160 Speaker 1: the hinges are and these companies that make them tick 100 00:05:38,240 --> 00:05:40,640 Speaker 1: and get investors excited, and what is it about one 101 00:05:40,760 --> 00:05:43,240 Speaker 1: that is more exciting and appealing to investors that have 102 00:05:43,320 --> 00:05:47,080 Speaker 1: given time? And uh, I feel like we you can 103 00:05:47,200 --> 00:05:50,360 Speaker 1: drill in to a level on on some of these 104 00:05:50,360 --> 00:05:52,480 Speaker 1: companies in a way that most people I talk to 105 00:05:52,480 --> 00:05:56,880 Speaker 1: you can't. I Admittedly, personally, I think live maybe five 106 00:05:56,960 --> 00:05:59,919 Speaker 1: years in the future with like my interest in technology, 107 00:06:00,640 --> 00:06:04,000 Speaker 1: but my experience as a PM and an analyst on 108 00:06:04,040 --> 00:06:06,200 Speaker 1: the equity hedge fund side kind of draws me back 109 00:06:06,200 --> 00:06:09,200 Speaker 1: into like, what is the rational expectation for the next 110 00:06:09,279 --> 00:06:12,520 Speaker 1: you know, quarter year, two years in these stocks? So 111 00:06:12,560 --> 00:06:16,120 Speaker 1: it kind of converges at some point there. But uh, yeah, 112 00:06:16,360 --> 00:06:18,599 Speaker 1: we live in a time now when there's so much 113 00:06:18,680 --> 00:06:22,880 Speaker 1: creative destruction in tech, and the kind of destruction disruption 114 00:06:23,000 --> 00:06:27,440 Speaker 1: multiple has increased so much for both new technology companies 115 00:06:27,440 --> 00:06:30,120 Speaker 1: that get disrupted by other new technology companies as well 116 00:06:30,120 --> 00:06:33,560 Speaker 1: as old industrial companies and healthcare companies that get disrupted too. 117 00:06:33,640 --> 00:06:37,320 Speaker 1: So yeah, it's it's interesting all around. Okay, So here's 118 00:06:37,360 --> 00:06:41,120 Speaker 1: my first question, based on the interaction that you and 119 00:06:41,240 --> 00:06:44,320 Speaker 1: Joe has had. Joe said, you're very very good at 120 00:06:44,440 --> 00:06:48,719 Speaker 1: pulling out the different parts of different tech companies. Should 121 00:06:48,760 --> 00:06:54,040 Speaker 1: we be lumping all these different companies under the umbrella 122 00:06:54,240 --> 00:06:57,400 Speaker 1: term tech? Like for instance, we talked about the Fang stocks, 123 00:06:57,440 --> 00:07:00,800 Speaker 1: which is a particular subset of tech it do they 124 00:07:00,880 --> 00:07:04,599 Speaker 1: actually share much in common? What do we mean when 125 00:07:04,640 --> 00:07:07,520 Speaker 1: we say tech or thing? So the biggest thing that 126 00:07:07,600 --> 00:07:10,480 Speaker 1: I think is going on in a macro sense. And uh, 127 00:07:10,640 --> 00:07:15,600 Speaker 1: we saw it when Schumer and um Um and Sanders 128 00:07:15,680 --> 00:07:18,840 Speaker 1: came out and said, basically, we don't want you know, 129 00:07:18,920 --> 00:07:21,560 Speaker 1: companies doing buy backs. You need to provide you know 130 00:07:21,640 --> 00:07:26,080 Speaker 1: a certain amount of uh you know, uh upward revision 131 00:07:26,120 --> 00:07:29,080 Speaker 1: to your labor kind of cost. And what's going on 132 00:07:29,240 --> 00:07:33,720 Speaker 1: is that technology throughout the entire ecosystem is driving gross 133 00:07:33,760 --> 00:07:36,880 Speaker 1: margins because you need less people to generate that same 134 00:07:36,920 --> 00:07:40,520 Speaker 1: revenue dollar. So I think that there actually is a 135 00:07:40,880 --> 00:07:44,920 Speaker 1: general thing across the entire spectrum that goes on. Now. 136 00:07:44,960 --> 00:07:48,400 Speaker 1: Of course, you know, the business models are different, but overall, 137 00:07:48,520 --> 00:07:52,160 Speaker 1: the leverage that capital has on labor at this point 138 00:07:52,320 --> 00:07:55,920 Speaker 1: is just it's expanding so quickly. I have a friend 139 00:07:56,040 --> 00:07:59,800 Speaker 1: who used to be a a PM and energy PM 140 00:07:59,800 --> 00:08:02,840 Speaker 1: at a hedge fund here New York moved home to Austin, 141 00:08:02,880 --> 00:08:09,040 Speaker 1: Texas to build a energy services technology company, right because 142 00:08:09,080 --> 00:08:12,200 Speaker 1: he recognized that it's just so inefficient at this point, 143 00:08:12,200 --> 00:08:16,160 Speaker 1: even in that industry. Um and I think that's happening 144 00:08:16,200 --> 00:08:18,880 Speaker 1: across the board with you know, large companies and small companies. 145 00:08:19,400 --> 00:08:23,520 Speaker 1: So then when we talk about the facebooks and the 146 00:08:23,560 --> 00:08:26,760 Speaker 1: Amazons and the Netflix of the world. Where do they 147 00:08:26,800 --> 00:08:30,840 Speaker 1: fit into this trend? Is it that they are essentially 148 00:08:31,480 --> 00:08:35,760 Speaker 1: the most leveraged in terms of capital to labor or 149 00:08:35,800 --> 00:08:40,920 Speaker 1: are they facilitating other entities in their drive to be 150 00:08:41,480 --> 00:08:46,240 Speaker 1: uh more efficient? Honestly, I think it's the former. UM. 151 00:08:46,760 --> 00:08:48,520 Speaker 1: I believe I could be wrong with this, but I 152 00:08:48,559 --> 00:08:53,439 Speaker 1: believe Facebook is the company that has the highest revenue 153 00:08:53,520 --> 00:08:58,120 Speaker 1: dollars per employee in history. Now they've increased headcount over 154 00:08:58,120 --> 00:09:00,640 Speaker 1: the last year pretty substantially. I don't know if that's 155 00:09:00,640 --> 00:09:04,200 Speaker 1: true anymore, but it definitely used to be uh. And 156 00:09:04,640 --> 00:09:08,600 Speaker 1: you see that across the board. UM, it's pretty amazing 157 00:09:08,679 --> 00:09:12,160 Speaker 1: what's going on, honestly, UH. And then you get things 158 00:09:12,240 --> 00:09:16,600 Speaker 1: like Tinder, right which have just exploded in an entire 159 00:09:16,760 --> 00:09:20,040 Speaker 1: industry of what people care about, right, Like, what is 160 00:09:20,160 --> 00:09:22,240 Speaker 1: one of the most fundamental things that you have to 161 00:09:22,240 --> 00:09:24,280 Speaker 1: do is you find somebody to fall in love with 162 00:09:24,320 --> 00:09:27,160 Speaker 1: and marry and and be with. And these platforms have 163 00:09:27,240 --> 00:09:30,240 Speaker 1: just made life so much more efficient for people. And 164 00:09:30,280 --> 00:09:32,960 Speaker 1: the leverage that they have on people's dollars and time. 165 00:09:33,320 --> 00:09:36,600 Speaker 1: I think the other thing that people haven't quite graphed yet, 166 00:09:36,840 --> 00:09:39,520 Speaker 1: and it started with kind of the online games and 167 00:09:39,679 --> 00:09:41,560 Speaker 1: remember it from like Zinga and stuff, but it was 168 00:09:41,600 --> 00:09:45,280 Speaker 1: just such the like the front end of this massive 169 00:09:45,320 --> 00:09:49,120 Speaker 1: trend is people are generally bored. People need to find 170 00:09:49,160 --> 00:09:54,000 Speaker 1: things to do with their time. And the algorithms that 171 00:09:54,040 --> 00:09:56,920 Speaker 1: we've developed that started as linear models and now our 172 00:09:57,000 --> 00:09:59,960 Speaker 1: machine learning models, and the massive amounts of data that 173 00:10:00,040 --> 00:10:02,920 Speaker 1: we collect on people and their behavior inside of these platforms, 174 00:10:02,920 --> 00:10:05,959 Speaker 1: whether it's Amazon with their shopping habits, or Facebook with 175 00:10:06,000 --> 00:10:09,280 Speaker 1: their reading habits, or or Tinder with their you know, 176 00:10:09,360 --> 00:10:14,080 Speaker 1: swiping habits. It's it's on one hand, amazing and the 177 00:10:14,080 --> 00:10:18,800 Speaker 1: other hand, I find incredibly dangerous that these models are 178 00:10:19,480 --> 00:10:23,400 Speaker 1: managing people's behavior so well at this point that I'm 179 00:10:23,440 --> 00:10:27,160 Speaker 1: not quite sure people really understand are they getting something 180 00:10:27,160 --> 00:10:28,800 Speaker 1: good out of these platforms? Are they getting something but 181 00:10:28,840 --> 00:10:31,920 Speaker 1: out of these platforms with the platforms are are are 182 00:10:31,960 --> 00:10:36,000 Speaker 1: massaging their behavior so much And that's obviously flowing through 183 00:10:36,040 --> 00:10:38,680 Speaker 1: to their you know, are poo their average revenue per user, 184 00:10:38,679 --> 00:10:42,720 Speaker 1: which Facebook was up another like sevent this quarter. Um, 185 00:10:42,840 --> 00:10:45,520 Speaker 1: So they have so much leverage with the technology and 186 00:10:45,559 --> 00:10:49,160 Speaker 1: the data on our behavior now that that's only going 187 00:10:49,200 --> 00:10:52,560 Speaker 1: to increase that these models get better. So aside from 188 00:10:52,679 --> 00:10:56,040 Speaker 1: the potential societal damage. I mean, I think you just 189 00:10:56,200 --> 00:11:00,560 Speaker 1: enunciated the goal case. Sorry, yeah, it is of bol case. 190 00:11:00,559 --> 00:11:04,120 Speaker 1: It's also the like, yeah, it's fearful societally, but it 191 00:11:04,200 --> 00:11:07,040 Speaker 1: is the bool case, right. So the bool case is 192 00:11:07,120 --> 00:11:10,480 Speaker 1: sort of this, um, you know, technology and the capital 193 00:11:10,600 --> 00:11:13,720 Speaker 1: that tech has basically has this huge amount of leverage 194 00:11:13,760 --> 00:11:17,680 Speaker 1: on labor costs and that's a big advantage in today's market, 195 00:11:17,840 --> 00:11:21,280 Speaker 1: and so they're sort of accruing all these various benefits 196 00:11:21,320 --> 00:11:26,720 Speaker 1: through that. I'm curious what you think happened in the 197 00:11:26,840 --> 00:11:30,440 Speaker 1: fourth quarter and sort of late third quarter of last 198 00:11:30,520 --> 00:11:34,600 Speaker 1: year when we did have that big sort of sudden 199 00:11:34,720 --> 00:11:39,680 Speaker 1: disappointment or disbelief in the tech companies that had previously 200 00:11:39,840 --> 00:11:43,520 Speaker 1: been leaders of the market. I honestly think, you know, 201 00:11:43,559 --> 00:11:48,160 Speaker 1: looking at our entire data set UM, we collect estimates 202 00:11:48,400 --> 00:11:51,240 Speaker 1: on on everything in the US public markets as well 203 00:11:51,240 --> 00:11:55,560 Speaker 1: as the economic estimate data, and I think the number 204 00:11:55,600 --> 00:11:58,240 Speaker 1: one thing that we saw was that financial has actually 205 00:11:58,280 --> 00:12:02,000 Speaker 1: led to the downside, not technology. And what that said 206 00:12:02,040 --> 00:12:04,080 Speaker 1: to me, along with the fact that the credit markets 207 00:12:04,120 --> 00:12:08,480 Speaker 1: were literally frozen, the corporate credit markets stopped everything for 208 00:12:08,559 --> 00:12:11,160 Speaker 1: like a month and a half, that it was actually 209 00:12:11,160 --> 00:12:14,040 Speaker 1: more of a macro thing than it was a technology thing. 210 00:12:14,480 --> 00:12:17,120 Speaker 1: And the second those credit markets on froze, we got 211 00:12:17,120 --> 00:12:22,360 Speaker 1: this huge rebound in everything. So as things freeze up, 212 00:12:23,120 --> 00:12:27,080 Speaker 1: the higher beta names obviously get hit harder, and those were, 213 00:12:27,200 --> 00:12:30,160 Speaker 1: you know, the tech names, and portfolio managers that you 214 00:12:30,200 --> 00:12:32,600 Speaker 1: know have to liquidate things tend to liquidate the things 215 00:12:32,640 --> 00:12:34,640 Speaker 1: that have been performing best, which is not a good 216 00:12:34,640 --> 00:12:37,120 Speaker 1: strategy because you're supposed to hold your winners and sell 217 00:12:37,120 --> 00:12:40,440 Speaker 1: your losers. But that's just what happens in hedge fund 218 00:12:40,440 --> 00:12:44,080 Speaker 1: and asset management world. Um So the rerating of the 219 00:12:44,160 --> 00:12:47,120 Speaker 1: multiple for these names, I don't think it was a 220 00:12:47,120 --> 00:12:51,720 Speaker 1: fundamental thing. Yes, growth is slowing, obviously we are probably 221 00:12:51,720 --> 00:12:54,600 Speaker 1: going to have an earnings recession in f y nineteen, 222 00:12:55,200 --> 00:12:58,120 Speaker 1: But I don't think this was a technology specific thing. 223 00:12:58,200 --> 00:12:59,599 Speaker 1: I think it was just when you look at the 224 00:12:59,640 --> 00:13:02,720 Speaker 1: beta of some of these names, when people sold everything 225 00:13:02,760 --> 00:13:05,000 Speaker 1: across the board and what was kind of a slow 226 00:13:05,000 --> 00:13:08,120 Speaker 1: motion panic because of the credit markets. Yeah, these things 227 00:13:08,160 --> 00:13:11,880 Speaker 1: got hit the hardest. Nonetheless, we have seen some of 228 00:13:11,920 --> 00:13:17,200 Speaker 1: these big companies clearly run into some idiosyncratic stumbles and 229 00:13:17,320 --> 00:13:20,120 Speaker 1: it started actually not at the end of last year, 230 00:13:20,160 --> 00:13:21,960 Speaker 1: but in the middle of last year. The first bomb 231 00:13:22,160 --> 00:13:25,160 Speaker 1: was Facebook. I think it was one of the biggest 232 00:13:25,400 --> 00:13:28,440 Speaker 1: single day market cap losses any day, and they're like, yes, 233 00:13:28,480 --> 00:13:30,640 Speaker 1: we're going to have to spend a lot more money 234 00:13:30,679 --> 00:13:33,439 Speaker 1: than we thought. What is going on, Let's start with them. 235 00:13:33,480 --> 00:13:36,040 Speaker 1: So what is going on with Facebook right now? Because obviously, 236 00:13:36,040 --> 00:13:39,440 Speaker 1: as you said, if not currently at some point, the 237 00:13:39,520 --> 00:13:44,080 Speaker 1: greatest revenue in history per employee. But we also know 238 00:13:44,160 --> 00:13:47,840 Speaker 1: that there's numerous scandals. It's unclear the degree to which 239 00:13:47,840 --> 00:13:49,760 Speaker 1: they're really hitting the business model or if it's just 240 00:13:49,800 --> 00:13:52,960 Speaker 1: a thing that media people like to talk about. But 241 00:13:53,280 --> 00:13:55,600 Speaker 1: what is going on with Facebook's business model right now? 242 00:13:56,320 --> 00:13:59,640 Speaker 1: So as it is with the other kind of social 243 00:13:59,679 --> 00:14:04,040 Speaker 1: media companies, I think the market still has some PTSD 244 00:14:04,280 --> 00:14:07,760 Speaker 1: from the tech boom or the tech bubble, because in 245 00:14:07,800 --> 00:14:11,400 Speaker 1: the tech bubble you're talking about the one. Yeah, I don't, 246 00:14:11,400 --> 00:14:16,600 Speaker 1: I don't consider this last round. Um. I think people 247 00:14:16,640 --> 00:14:20,120 Speaker 1: are worried that as the user growth trails off, that 248 00:14:20,280 --> 00:14:23,680 Speaker 1: as it was in the tech bubble, that the business 249 00:14:23,720 --> 00:14:26,200 Speaker 1: will trail off as well, and the growth will trail off. 250 00:14:27,040 --> 00:14:30,760 Speaker 1: I think that is PTSD because it doesn't seem like 251 00:14:30,840 --> 00:14:34,480 Speaker 1: that's actually going to happen this time. Largely because we've 252 00:14:34,560 --> 00:14:37,720 Speaker 1: learned a lot, or they've learned a lot that by 253 00:14:37,720 --> 00:14:42,040 Speaker 1: buying and bundling these other platforms like WhatsApp and and 254 00:14:42,080 --> 00:14:45,920 Speaker 1: the rest, that they've kind of locked people into this ecosystem, 255 00:14:46,200 --> 00:14:49,520 Speaker 1: especially on the social side, brilliant model using oh off 256 00:14:49,680 --> 00:14:52,680 Speaker 1: to have people log into all their other stuff for 257 00:14:52,680 --> 00:14:55,680 Speaker 1: for almost forever, you couldn't do Tinder without logging in 258 00:14:55,800 --> 00:14:58,440 Speaker 1: via Facebook, right, they became the social graph instead of 259 00:14:58,480 --> 00:15:02,920 Speaker 1: just another social platform. So I think people were and 260 00:15:03,000 --> 00:15:05,880 Speaker 1: still are, in a sense worried that as the growth 261 00:15:05,880 --> 00:15:08,560 Speaker 1: trails off to sub ten percent, you over your kind 262 00:15:08,600 --> 00:15:13,040 Speaker 1: of user growth rates, um that they're kind of leverage 263 00:15:13,080 --> 00:15:15,360 Speaker 1: on that revenue stream kind of goes away. But the 264 00:15:15,440 --> 00:15:18,400 Speaker 1: r POO numbers keep growing so quickly that they keep 265 00:15:18,440 --> 00:15:21,120 Speaker 1: showing that they can just turn the dial on you 266 00:15:21,120 --> 00:15:23,680 Speaker 1: know what, people, what they get out of people. The 267 00:15:23,800 --> 00:15:27,600 Speaker 1: regulatory side, I think is serious and that's probably what 268 00:15:27,720 --> 00:15:31,040 Speaker 1: re rated the multiple because the growth hasn't slowed too much, 269 00:15:31,960 --> 00:15:34,840 Speaker 1: and I think that that's, uh, it's fair. Do I 270 00:15:34,960 --> 00:15:37,280 Speaker 1: really think that the government is going to clamp down 271 00:15:37,280 --> 00:15:40,600 Speaker 1: too much on this, No, probably not. We probably don't 272 00:15:40,640 --> 00:15:44,400 Speaker 1: have the you know, the gumption to do that politically 273 00:15:45,200 --> 00:15:48,560 Speaker 1: we should, but we don't. There's too many other you know, 274 00:15:48,600 --> 00:15:52,720 Speaker 1: cross currents going on there um. But I do think 275 00:15:52,800 --> 00:15:58,040 Speaker 1: that people on the BYE side assume that there is 276 00:15:58,200 --> 00:16:01,600 Speaker 1: more risk than upside at this point given the growth rate, 277 00:16:02,280 --> 00:16:05,040 Speaker 1: because there are so many other companies that are growing 278 00:16:05,120 --> 00:16:07,760 Speaker 1: so quickly, especially in the enterprise tech space, that they 279 00:16:07,800 --> 00:16:10,840 Speaker 1: could just rotate into. If we were in a situation 280 00:16:10,920 --> 00:16:14,600 Speaker 1: where we weren't in this big kind of enterprise technology 281 00:16:14,640 --> 00:16:19,080 Speaker 1: CAPEC supercycle, maybe Facebook would have held its multiple a 282 00:16:19,080 --> 00:16:22,080 Speaker 1: little bit better. But at this point, uh, you know, 283 00:16:22,360 --> 00:16:41,400 Speaker 1: you can rotate into a lot of other things. So 284 00:16:41,600 --> 00:16:45,880 Speaker 1: before we get into specific companies, um too much for 285 00:16:45,880 --> 00:16:49,160 Speaker 1: for Facebook or for any other tech stock, or I 286 00:16:49,160 --> 00:16:51,200 Speaker 1: should say, for any of the big tech stalks like 287 00:16:51,600 --> 00:16:55,760 Speaker 1: the Fang stocks. Do you think the share prices that 288 00:16:55,800 --> 00:16:59,720 Speaker 1: we saw before, say the middle of last year were 289 00:17:00,400 --> 00:17:05,920 Speaker 1: justified by the earnings outlook or were they overly optimistic? Yeah? 290 00:17:05,960 --> 00:17:08,399 Speaker 1: I mean, I think given the growth rates in the 291 00:17:08,920 --> 00:17:11,920 Speaker 1: you know, thirties, forties fift for some of these big 292 00:17:11,920 --> 00:17:16,680 Speaker 1: companies on the revenue side, the multiples are certainly not outlandish, 293 00:17:16,880 --> 00:17:20,159 Speaker 1: and given their ability to use their balance sheets and 294 00:17:20,280 --> 00:17:24,040 Speaker 1: stock to buy other high growth names. I don't see 295 00:17:24,040 --> 00:17:28,080 Speaker 1: why those multiples are not sustainable. UM Now when you 296 00:17:28,200 --> 00:17:30,959 Speaker 1: take a look at something like Apple, which relies on 297 00:17:31,000 --> 00:17:33,439 Speaker 1: a whole different kind of set of things that is 298 00:17:33,480 --> 00:17:38,800 Speaker 1: more um you know, sale of iPhones based the you 299 00:17:38,840 --> 00:17:42,640 Speaker 1: know when they got over a trillion dollars in market cap. Yeah, 300 00:17:42,640 --> 00:17:44,560 Speaker 1: there's some law of large numbers coming in there with 301 00:17:44,720 --> 00:17:47,480 Speaker 1: just literally how many of these widgets can you sell 302 00:17:47,680 --> 00:17:50,320 Speaker 1: every quarter every year? And what is the growth rate 303 00:17:50,359 --> 00:17:53,520 Speaker 1: for them? And where are you in terms of UH 304 00:17:53,680 --> 00:17:57,560 Speaker 1: saturation of the market. But Facebook isn't Facebook is not 305 00:17:57,600 --> 00:18:00,600 Speaker 1: really growing their user base anymore. It's us How good 306 00:18:00,640 --> 00:18:02,679 Speaker 1: can the platform get? How much leverage they have on 307 00:18:02,720 --> 00:18:05,800 Speaker 1: the people there already? And I don't see that going 308 00:18:05,840 --> 00:18:09,399 Speaker 1: away if and he's done an incredible job of just 309 00:18:09,560 --> 00:18:13,840 Speaker 1: creating this universe of things that you're locked into. I 310 00:18:13,880 --> 00:18:16,120 Speaker 1: want to get to Apple in a second, but before 311 00:18:16,160 --> 00:18:17,560 Speaker 1: I want to go back to what you said about 312 00:18:17,560 --> 00:18:22,160 Speaker 1: the sort of enterprise software upgrade supercycle in these UH 313 00:18:22,440 --> 00:18:27,200 Speaker 1: enterprise software cloud names, because actually in Q four, while 314 00:18:27,240 --> 00:18:29,160 Speaker 1: we saw this big sell off, there were a handful 315 00:18:29,160 --> 00:18:32,719 Speaker 1: of tech companies that almost seemed completely unaffected by it. 316 00:18:33,400 --> 00:18:36,480 Speaker 1: UM you know companies like work Day, which probably not 317 00:18:36,560 --> 00:18:38,199 Speaker 1: a lot I think not a lot of people are 318 00:18:38,200 --> 00:18:39,720 Speaker 1: probably that familiar with. But I think they're kind of 319 00:18:39,760 --> 00:18:43,439 Speaker 1: like a salesforce type company. What is this class of 320 00:18:43,520 --> 00:18:46,639 Speaker 1: companies that people got really excited about and why didn't 321 00:18:46,680 --> 00:18:48,520 Speaker 1: they get caught up in the down draft to the 322 00:18:48,560 --> 00:18:53,400 Speaker 1: same degree they did? Uh, they weren't down, they were 323 00:18:53,440 --> 00:18:59,000 Speaker 1: down again high beata names. If you listen to Mark 324 00:18:59,040 --> 00:19:02,240 Speaker 1: being off sale for CEO on his earnings calls the 325 00:19:02,320 --> 00:19:05,920 Speaker 1: last two years, basically he has been dead on right 326 00:19:06,560 --> 00:19:09,200 Speaker 1: about the fact that he believes there is a supercycle 327 00:19:09,240 --> 00:19:13,920 Speaker 1: going on in capex for enterprise technology. Basically, we got 328 00:19:14,040 --> 00:19:17,720 Speaker 1: the tax legislation and that freed up a lot of 329 00:19:17,920 --> 00:19:21,760 Speaker 1: money for investment, supposedly right now for really large companies. 330 00:19:21,840 --> 00:19:24,080 Speaker 1: We kind of saw them do share buy backs. But 331 00:19:24,440 --> 00:19:27,439 Speaker 1: also when you look at the financial sector, they hadn't 332 00:19:27,480 --> 00:19:30,000 Speaker 1: gone through a huge CAPEX cycle in a long time, 333 00:19:30,240 --> 00:19:33,120 Speaker 1: a lot of legacy technology sitting around there. They did 334 00:19:33,240 --> 00:19:36,720 Speaker 1: take the money and invest a lot in software. I 335 00:19:36,720 --> 00:19:39,479 Speaker 1: think one of the reasons why people may not see 336 00:19:39,640 --> 00:19:44,040 Speaker 1: as much CAPEX that they thought they would or should 337 00:19:44,080 --> 00:19:47,600 Speaker 1: have happened because of those tax cuts. UM is because 338 00:19:47,640 --> 00:19:49,840 Speaker 1: it doesn't cost as much money anymore to do the 339 00:19:50,359 --> 00:19:52,440 Speaker 1: cap expending because a lot of it's not it's it's 340 00:19:52,440 --> 00:19:56,200 Speaker 1: not physical things, right, it's it's software driving your business. Um, 341 00:19:56,240 --> 00:19:59,359 Speaker 1: it's not hiring a hundred thousand people, right, it's hiring 342 00:19:59,359 --> 00:20:01,920 Speaker 1: a couple of people to manage the software. And so 343 00:20:02,000 --> 00:20:05,440 Speaker 1: we are seeing this massive investment in new software products 344 00:20:05,440 --> 00:20:09,119 Speaker 1: sas products right that you don't have to software software 345 00:20:09,119 --> 00:20:10,639 Speaker 1: is a service that you don't have to spend a 346 00:20:10,680 --> 00:20:14,879 Speaker 1: ton of money to simply buy and install your you know, 347 00:20:14,920 --> 00:20:18,120 Speaker 1: you're spending money every every month, every every year, right, 348 00:20:18,320 --> 00:20:21,520 Speaker 1: it's not this massive investment up front and being off 349 00:20:21,520 --> 00:20:25,640 Speaker 1: has been right, and it is driving everything from uh, 350 00:20:25,760 --> 00:20:27,960 Speaker 1: you know HR which is kind of the workday thing, 351 00:20:28,040 --> 00:20:31,159 Speaker 1: and updating how you manage your people to how you 352 00:20:31,200 --> 00:20:34,920 Speaker 1: manage your you know, internal systems, how you manage your logistics, 353 00:20:35,480 --> 00:20:38,600 Speaker 1: how you manage your payment network. Square is on fire 354 00:20:38,720 --> 00:20:42,040 Speaker 1: right now because every you know, every store that you 355 00:20:42,080 --> 00:20:45,280 Speaker 1: go to, every juice bar is now running a Square machine. Right. 356 00:20:45,359 --> 00:20:47,520 Speaker 1: And and then on top of that, it's amazing that 357 00:20:47,640 --> 00:20:49,919 Speaker 1: companies like this now they have all the data and 358 00:20:49,960 --> 00:20:53,560 Speaker 1: they can offer that juice bar owner debt right and 359 00:20:53,600 --> 00:20:56,199 Speaker 1: to you know, invest in their company and you know, 360 00:20:56,280 --> 00:21:00,800 Speaker 1: kind of sidestep the whole regular financial system. So it's 361 00:21:00,800 --> 00:21:03,360 Speaker 1: all adding up to a lot of leverage for these 362 00:21:03,400 --> 00:21:06,720 Speaker 1: companies that are small and makecap companies mostly, but their 363 00:21:06,760 --> 00:21:10,520 Speaker 1: growth rates are incredible and there's really no reason those 364 00:21:10,520 --> 00:21:14,000 Speaker 1: growth rates should slow significantly unless we get a real 365 00:21:14,080 --> 00:21:18,760 Speaker 1: economic downturn. Okay, I'm gonna jump in and steal Joe's 366 00:21:18,800 --> 00:21:24,479 Speaker 1: idea for the next question. Uh, much like any tech entrepreneur, really, um, Apple, 367 00:21:24,600 --> 00:21:29,160 Speaker 1: We're going to talk about Apple. Lots of concerns around 368 00:21:29,200 --> 00:21:32,080 Speaker 1: Apple at the moment. Is it going to be able 369 00:21:32,119 --> 00:21:35,120 Speaker 1: to sell as many phones in the future. Are its 370 00:21:35,119 --> 00:21:38,520 Speaker 1: current phones too expensive or not innovative enough to make 371 00:21:38,560 --> 00:21:41,359 Speaker 1: people buy new models? Plus you have the sort of 372 00:21:41,400 --> 00:21:46,520 Speaker 1: glaring um issues around China and this notion that maybe 373 00:21:46,640 --> 00:21:50,639 Speaker 1: Chinese nationals just aren't buying as many phones as they 374 00:21:50,720 --> 00:21:54,760 Speaker 1: used to. Maybe they're buying from um, non Apple competitors, 375 00:21:54,800 --> 00:21:58,359 Speaker 1: like you know, domestic manufacturers. Where do you stand on 376 00:21:58,400 --> 00:22:01,199 Speaker 1: Apple and which concerns do you think are sort of 377 00:22:01,240 --> 00:22:03,880 Speaker 1: justified at the moment. I think there's some near term 378 00:22:03,920 --> 00:22:07,840 Speaker 1: concerns and some long term concerns that are much bigger. Um. 379 00:22:07,880 --> 00:22:11,679 Speaker 1: I think near term the risks aren't that high. The 380 00:22:11,720 --> 00:22:16,280 Speaker 1: Apple multiple is already pretty low. The installed user base, 381 00:22:16,560 --> 00:22:19,199 Speaker 1: you know, for the phones isn't going away tomorrow. It's 382 00:22:19,240 --> 00:22:22,560 Speaker 1: gonna take at least at least two to three years 383 00:22:22,920 --> 00:22:26,480 Speaker 1: to really turn over that installed base if something else 384 00:22:26,520 --> 00:22:30,440 Speaker 1: were to come out to kind of subsume the market. Um. 385 00:22:30,720 --> 00:22:33,719 Speaker 1: Near term though, the risk is China really, which has 386 00:22:33,760 --> 00:22:35,320 Speaker 1: been driving a lot of the growth. They were down 387 00:22:35,359 --> 00:22:38,960 Speaker 1: twenty year over year and revenue this quarter this past quarter, 388 00:22:39,640 --> 00:22:41,680 Speaker 1: and I think Tim Cook has a little bit less 389 00:22:41,760 --> 00:22:44,639 Speaker 1: visibility than he used to on his revenue because of 390 00:22:44,680 --> 00:22:47,720 Speaker 1: the fact that China is is such a question mark. UM. 391 00:22:47,840 --> 00:22:49,639 Speaker 1: So I think investors have to look at that. But 392 00:22:49,680 --> 00:22:52,960 Speaker 1: it's very hard to believe that they're going to be 393 00:22:52,960 --> 00:22:55,520 Speaker 1: able to push the multiple for Apple down too much further. 394 00:22:55,520 --> 00:22:58,720 Speaker 1: It's already a pretty cheap stock as it goes. I think, 395 00:22:59,080 --> 00:23:01,760 Speaker 1: you know, people look at the services side of the company, 396 00:23:01,760 --> 00:23:04,479 Speaker 1: which is growing very quickly, which has a higher margin, 397 00:23:04,640 --> 00:23:07,080 Speaker 1: and say, hey, you know, this company should have a 398 00:23:07,119 --> 00:23:09,919 Speaker 1: higher multiple. I don't necessarily believe that's the case, and 399 00:23:09,960 --> 00:23:12,119 Speaker 1: I think the market agrees as it hasn't given the 400 00:23:12,160 --> 00:23:15,760 Speaker 1: company that higher multiple. I think that that services revenue 401 00:23:15,760 --> 00:23:18,919 Speaker 1: is also more at risk than people think if the 402 00:23:18,960 --> 00:23:24,480 Speaker 1: installed base of hardware kind of disappears long term. The 403 00:23:24,600 --> 00:23:27,800 Speaker 1: risk is basically this, The AI is coming, and it's 404 00:23:27,840 --> 00:23:31,920 Speaker 1: coming to consumers. You know, Alexa is great for Amazon 405 00:23:32,040 --> 00:23:34,239 Speaker 1: in terms of their ability to collect data on what 406 00:23:34,320 --> 00:23:36,560 Speaker 1: you want. It's God knows, it's listening to me in 407 00:23:36,600 --> 00:23:39,480 Speaker 1: my living room because I get ads like five minutes 408 00:23:39,560 --> 00:23:41,400 Speaker 1: later for things my wife and I are talking about 409 00:23:41,400 --> 00:23:45,320 Speaker 1: that we have never searched for at all. They're definitely listening. 410 00:23:45,800 --> 00:23:49,280 Speaker 1: But that that AI is not the A I'm talking about. 411 00:23:49,359 --> 00:23:51,760 Speaker 1: I'm talking about something that probably comes out of Google 412 00:23:51,880 --> 00:23:56,320 Speaker 1: or some left field place the Google buys. That completely 413 00:23:57,040 --> 00:24:02,920 Speaker 1: changes the paradigm for your interaction. Is the operating system. 414 00:24:03,000 --> 00:24:05,920 Speaker 1: And if somebody gets there before Apple, when a lot 415 00:24:05,920 --> 00:24:08,240 Speaker 1: of a lot of companies are investing in this stuff, 416 00:24:08,400 --> 00:24:12,840 Speaker 1: specifically Google, the Chinese companies are obviously investing heavily, and 417 00:24:12,920 --> 00:24:15,960 Speaker 1: they have tremendous amounts of data that drives all of this. 418 00:24:16,520 --> 00:24:19,640 Speaker 1: If they get there before Apple, which has notoriously been 419 00:24:19,840 --> 00:24:24,120 Speaker 1: bad in this specific space and has not had success 420 00:24:24,119 --> 00:24:27,440 Speaker 1: as Syria as a disaster if they get there before 421 00:24:27,600 --> 00:24:32,000 Speaker 1: Apple risks the hardware not becoming important anymore if it's 422 00:24:32,040 --> 00:24:34,320 Speaker 1: just the software. I want to talk about this a 423 00:24:34,320 --> 00:24:37,800 Speaker 1: little bit further, this idea of the hardware becoming less 424 00:24:37,800 --> 00:24:40,280 Speaker 1: important to software, because something I think you pointed out 425 00:24:40,720 --> 00:24:44,800 Speaker 1: during a TV appearance recently is how in China, whereas 426 00:24:44,800 --> 00:24:47,199 Speaker 1: in the US we think of iOS as being the 427 00:24:47,200 --> 00:24:51,239 Speaker 1: main platform for that we use, we download ad from 428 00:24:51,240 --> 00:24:53,119 Speaker 1: the app store and so forth, that it's really we 429 00:24:53,440 --> 00:24:55,800 Speaker 1: chat and the software that is the main thing that 430 00:24:55,840 --> 00:24:57,840 Speaker 1: people interact with, and then people can add all kinds 431 00:24:57,880 --> 00:24:59,840 Speaker 1: of services onto that. So I want you to explain that. 432 00:24:59,880 --> 00:25:04,520 Speaker 1: But also a story that's emerged recently in the US, 433 00:25:05,080 --> 00:25:08,080 Speaker 1: or just immerged recently period is some of these fights 434 00:25:08,119 --> 00:25:11,679 Speaker 1: between Apple and Facebook and Apple and Google referring to 435 00:25:11,840 --> 00:25:15,800 Speaker 1: developer access, and I'm wondering if there's a connection there 436 00:25:15,840 --> 00:25:19,399 Speaker 1: where Apple is starting to worry that even in the US, 437 00:25:20,080 --> 00:25:23,159 Speaker 1: that these services from the likes of Facebook and Google 438 00:25:23,680 --> 00:25:27,840 Speaker 1: could essentially become the user's main home rather than iOS. 439 00:25:27,920 --> 00:25:30,879 Speaker 1: So explain this issue, because I don't think maybe people 440 00:25:30,960 --> 00:25:34,199 Speaker 1: totally understand it and and say, is this kind of 441 00:25:34,200 --> 00:25:36,880 Speaker 1: what we're seeing the battle now playing in the US. Yeah, 442 00:25:36,880 --> 00:25:40,200 Speaker 1: so I'll explain it from my own personal perspective. Frankly, um, 443 00:25:40,320 --> 00:25:45,760 Speaker 1: I switched over to Apple from BlackBerry in two thousand 444 00:25:46,520 --> 00:25:50,160 Speaker 1: five something like that, right to get an iPhone, and 445 00:25:51,000 --> 00:25:53,639 Speaker 1: I've refused to switch over to Google, which all of 446 00:25:53,680 --> 00:25:57,040 Speaker 1: my other productivity apps are on Gmail Calendar, just like 447 00:25:57,359 --> 00:26:01,520 Speaker 1: every Google docs everything, because they don't the Android operating system. 448 00:26:01,560 --> 00:26:04,600 Speaker 1: Apple just simply, I think, has a better operating system, 449 00:26:04,640 --> 00:26:07,200 Speaker 1: the apps work better, it's more seamless, all of these things. 450 00:26:08,040 --> 00:26:10,320 Speaker 1: So I am stuck in that operating system. But in 451 00:26:10,440 --> 00:26:12,959 Speaker 1: China and I don't care about the hardware anymore. The 452 00:26:13,000 --> 00:26:15,480 Speaker 1: Google's hardware just as good as Apple's hardware. At this point. 453 00:26:15,960 --> 00:26:19,280 Speaker 1: In China, they've now gone to the next step above 454 00:26:19,320 --> 00:26:23,680 Speaker 1: that where we chat and we pay are an ecosystem 455 00:26:23,720 --> 00:26:25,680 Speaker 1: in and of themselves. So people just go into these 456 00:26:25,680 --> 00:26:29,720 Speaker 1: apps and they have all sorts of amazing utilities inside 457 00:26:29,720 --> 00:26:32,320 Speaker 1: of it. It's they're literally paying for everything. It's stores 458 00:26:32,400 --> 00:26:35,280 Speaker 1: inside of these apps. They've got their email that it's everything, 459 00:26:35,720 --> 00:26:39,120 Speaker 1: and so the the operatings doesn't even matter anymore because 460 00:26:39,160 --> 00:26:42,640 Speaker 1: it's subsumed inside of the app. You have to know 461 00:26:42,800 --> 00:26:45,800 Speaker 1: that Google is thinking about this with kind of the 462 00:26:45,800 --> 00:26:49,480 Speaker 1: ecosystem that they've built. Uh. And and there are others 463 00:26:49,880 --> 00:26:53,160 Speaker 1: an Apple, which is not good at building software outside 464 00:26:53,200 --> 00:26:55,520 Speaker 1: of the os Like what's the last piece of software 465 00:26:55,520 --> 00:26:58,440 Speaker 1: that you love from Apple? Right, Maps was a disaster, 466 00:26:58,680 --> 00:27:03,360 Speaker 1: and so Apple risks seriously falling way behind and having 467 00:27:03,359 --> 00:27:05,919 Speaker 1: the Harvard is not matter at all. It could be 468 00:27:06,440 --> 00:27:08,520 Speaker 1: that we get to a payments place in the U 469 00:27:08,640 --> 00:27:11,000 Speaker 1: S which we're way behind on, where one of these 470 00:27:11,040 --> 00:27:13,920 Speaker 1: apps subsumes it. It could be it could be it 471 00:27:13,920 --> 00:27:15,720 Speaker 1: could be something else, could be a social thing. It 472 00:27:15,760 --> 00:27:17,920 Speaker 1: could be whether Facebook has tried to bundle all these 473 00:27:17,920 --> 00:27:20,680 Speaker 1: things together but like you know, I don't think it's 474 00:27:20,680 --> 00:27:23,280 Speaker 1: worked that well instead of one app, or it could 475 00:27:23,280 --> 00:27:24,920 Speaker 1: be an AI. So it could be any of these 476 00:27:24,920 --> 00:27:29,560 Speaker 1: things that just rips Apple's revenue flow away from it 477 00:27:29,640 --> 00:27:32,440 Speaker 1: from selling you know, this hardware which a thousand dollars 478 00:27:32,440 --> 00:27:34,240 Speaker 1: for a phone right where you can get a good 479 00:27:34,240 --> 00:27:38,359 Speaker 1: one for like two d h um. So, you mentioned 480 00:27:38,359 --> 00:27:41,720 Speaker 1: the possibility of an earnings recession. I think you said 481 00:27:41,760 --> 00:27:46,760 Speaker 1: this year in nineteen So is there a risk that 482 00:27:46,920 --> 00:27:51,080 Speaker 1: part of that earnings recession comes from tech companies as 483 00:27:51,119 --> 00:27:54,480 Speaker 1: a whole, or are we going to see weakness in 484 00:27:54,560 --> 00:27:59,080 Speaker 1: one firm, say an Apple, offset by strength in another 485 00:27:59,119 --> 00:28:00,880 Speaker 1: firm like a Google Goal to the point you were 486 00:28:00,880 --> 00:28:05,080 Speaker 1: just making about a sort of closed software ecosystem. And secondly, 487 00:28:05,200 --> 00:28:09,520 Speaker 1: if we get an earnings recession, how disastrous is that 488 00:28:09,720 --> 00:28:12,960 Speaker 1: for the market's given that earnings have been pretty strong 489 00:28:13,080 --> 00:28:16,160 Speaker 1: for a few years now. Yeah, So on the first question, 490 00:28:16,280 --> 00:28:18,159 Speaker 1: I think it's the latter. I think it's gonna be 491 00:28:18,200 --> 00:28:23,000 Speaker 1: a bit more idiosyncratic. The the enterprise market is going 492 00:28:23,000 --> 00:28:25,680 Speaker 1: to continue to be really strong unless the general economy 493 00:28:25,760 --> 00:28:28,320 Speaker 1: falls off a cliff, which I think is you know, 494 00:28:28,359 --> 00:28:30,560 Speaker 1: on like maybe we get a recession in you know, 495 00:28:30,720 --> 00:28:33,280 Speaker 1: late nineteen twenty something like that. But I just don't 496 00:28:33,280 --> 00:28:35,640 Speaker 1: think it will matter too much for that cycle. At 497 00:28:35,680 --> 00:28:37,399 Speaker 1: some point, that cycle will come to an end, but 498 00:28:37,680 --> 00:28:40,640 Speaker 1: it doesn't seem to be ending anytime soon right now. Yeah, 499 00:28:41,040 --> 00:28:43,480 Speaker 1: certain companies will have their own issues, but I don't 500 00:28:43,480 --> 00:28:46,720 Speaker 1: think a broader earnings recession will come about because of tech. 501 00:28:47,280 --> 00:28:49,959 Speaker 1: The way that we're seeing the numbers, it looks like 502 00:28:50,040 --> 00:28:53,320 Speaker 1: if it happens, it's going to happen because of two things. 503 00:28:53,480 --> 00:28:57,719 Speaker 1: One industrials because of China and to the consumer in 504 00:28:57,760 --> 00:29:01,640 Speaker 1: the US. We think consumer estimates are still too high 505 00:29:01,680 --> 00:29:06,000 Speaker 1: for nineteen UM. You have a great UH analyst over here, 506 00:29:06,000 --> 00:29:09,760 Speaker 1: Seema Shah. I think we're in agreement there that we're 507 00:29:09,840 --> 00:29:13,080 Speaker 1: probably on the back part of the you know, top 508 00:29:13,120 --> 00:29:17,320 Speaker 1: of the hill for consumer growth, and the risk there 509 00:29:17,440 --> 00:29:21,800 Speaker 1: is that those estimates and actuals continue to come down. Further. 510 00:29:22,200 --> 00:29:25,000 Speaker 1: We're seeing in our data set, which tends to lead 511 00:29:25,080 --> 00:29:27,760 Speaker 1: the cell side data set in either direction up and down, 512 00:29:28,440 --> 00:29:31,800 Speaker 1: that estimates have come down quite a bit. And and 513 00:29:31,840 --> 00:29:35,240 Speaker 1: we're right now we would be projecting an earnings recession 514 00:29:35,440 --> 00:29:39,440 Speaker 1: for UM, which would mix between Q one and Q 515 00:29:39,600 --> 00:29:44,040 Speaker 1: two um fy nineteen. Well, on that cheery note of 516 00:29:44,320 --> 00:29:47,600 Speaker 1: expecting an earning it won't matter. It's not to the 517 00:29:47,640 --> 00:29:50,120 Speaker 1: second question. Sorry, I don't think it's gonna matter that 518 00:29:50,200 --> 00:29:53,360 Speaker 1: much unless you get another credit market issue or or 519 00:29:53,400 --> 00:29:57,120 Speaker 1: some other macro issue. Just because you're negative on you know, 520 00:29:57,160 --> 00:30:00,680 Speaker 1: the earnings numbers. Again, market's gonna look forward a year, 521 00:30:00,960 --> 00:30:03,160 Speaker 1: right and the numbers right now, you know people are 522 00:30:03,160 --> 00:30:07,400 Speaker 1: taking that into considerations. All right. Well, on that positive note, Lee, 523 00:30:07,480 --> 00:30:10,440 Speaker 1: Drogen really appreciate you on I was very excited to 524 00:30:10,480 --> 00:30:11,920 Speaker 1: have a chance to talk to you for a longer 525 00:30:11,960 --> 00:30:14,760 Speaker 1: time than we get on TV, and I really just, uh, 526 00:30:14,880 --> 00:30:16,720 Speaker 1: I learned a lot, So thank you very much. Yeah, 527 00:30:16,720 --> 00:30:18,880 Speaker 1: thanks for having I love the odd Lots name for 528 00:30:18,920 --> 00:30:37,640 Speaker 1: the five it's thanks, I think than thanks. Thank Tracy. 529 00:30:38,200 --> 00:30:40,400 Speaker 1: I always learn a lot talking from Lee, and I 530 00:30:40,440 --> 00:30:44,120 Speaker 1: feel like even in that short conversation, some of these ideas, 531 00:30:44,200 --> 00:30:48,120 Speaker 1: like about the platform wars, how I could really up 532 00:30:48,280 --> 00:30:51,880 Speaker 1: end how we interact with the Internet and our computers. 533 00:30:52,520 --> 00:30:55,760 Speaker 1: Um why people are so excited about some of these 534 00:30:55,880 --> 00:30:59,040 Speaker 1: enterprise cloud companies. I feel like I just learned a 535 00:30:59,040 --> 00:31:03,560 Speaker 1: ton about the current landscape of tech and tech investing. Yeah, 536 00:31:03,640 --> 00:31:05,480 Speaker 1: it was a great conversation. But you know what I 537 00:31:05,560 --> 00:31:08,320 Speaker 1: always wonder when we're whenever we're talking about tech, I 538 00:31:08,360 --> 00:31:13,360 Speaker 1: always wonder if tech, more than other industries, is something 539 00:31:13,440 --> 00:31:16,600 Speaker 1: of a wild card when it comes to making earnings 540 00:31:16,720 --> 00:31:20,240 Speaker 1: estimates or forecasts for the future, just because I mean, 541 00:31:20,240 --> 00:31:24,840 Speaker 1: technology is basically all about searching for the next paradigm 542 00:31:24,960 --> 00:31:29,320 Speaker 1: or the next breakthrough in business, and it seems so 543 00:31:29,400 --> 00:31:32,680 Speaker 1: hard to figure out what that might be, and so 544 00:31:33,320 --> 00:31:35,520 Speaker 1: I don't know, I just find it more difficult than 545 00:31:35,600 --> 00:31:37,600 Speaker 1: than a lot of other things. I also think It's 546 00:31:37,600 --> 00:31:40,680 Speaker 1: interesting too that I think a lot of the people 547 00:31:40,720 --> 00:31:43,920 Speaker 1: who are running these companies come from sort of non 548 00:31:43,920 --> 00:31:47,200 Speaker 1: traditional backgrounds where maybe they don't feel beholding to this 549 00:31:47,280 --> 00:31:49,560 Speaker 1: idea of like, oh, we gotta like hit this estimate. 550 00:31:49,720 --> 00:31:52,360 Speaker 1: And Jeff Bezos is probably the most famous in this 551 00:31:52,560 --> 00:31:57,480 Speaker 1: respect of not thinking about the court, thinking about each 552 00:31:57,560 --> 00:32:02,000 Speaker 1: quarter's numbers as being important to hit. So there are 553 00:32:02,080 --> 00:32:05,480 Speaker 1: just a lot of wild cards in the industry, both 554 00:32:05,600 --> 00:32:07,800 Speaker 1: short term and long term. And yeah, as you said, 555 00:32:07,880 --> 00:32:10,360 Speaker 1: like whatever is that. You know, there was one day 556 00:32:10,360 --> 00:32:12,959 Speaker 1: when it looked like IBM head ultimate lock in and 557 00:32:13,000 --> 00:32:15,480 Speaker 1: then no one even like talks about them anymore. So 558 00:32:15,880 --> 00:32:18,880 Speaker 1: absolutely there's short term and long term volatility in terms 559 00:32:18,880 --> 00:32:21,160 Speaker 1: of where all this is going. Yeah, and for every 560 00:32:21,240 --> 00:32:24,520 Speaker 1: Jeff Bezos, I guess there's a sort of Elizabeth Holmes right, 561 00:32:24,600 --> 00:32:29,560 Speaker 1: who made far too outlandish promises and basically, um, well 562 00:32:29,920 --> 00:32:32,520 Speaker 1: uh didn't make it. Let's put it that way. Um, 563 00:32:32,560 --> 00:32:36,360 Speaker 1: But anyway, earnings recession in ten, that'll be something interesting 564 00:32:36,480 --> 00:32:40,560 Speaker 1: and that'll be a story we're watching on that happy note. Yes, 565 00:32:40,720 --> 00:32:43,720 Speaker 1: um okay, So this has been another edition of the 566 00:32:43,760 --> 00:32:46,600 Speaker 1: All Thoughts podcast. I'm Tracy Alloway. You can follow me 567 00:32:46,640 --> 00:32:49,920 Speaker 1: on Twitter at Tracy Alloway and I'm Joe Wisn't thal 568 00:32:50,000 --> 00:32:52,360 Speaker 1: You could have follow me on Twitter at the Stalwart 569 00:32:52,680 --> 00:32:55,280 Speaker 1: and you should definitely follow Lee on Twitter He's at 570 00:32:55,480 --> 00:32:59,080 Speaker 1: l Droken. Also be sure to follow our producer topor 571 00:32:59,160 --> 00:33:02,280 Speaker 1: Brehead he's at or His Tea, as well as the 572 00:33:02,280 --> 00:33:07,040 Speaker 1: Bloomberg head of podcast Francesca leaving at Francesca Today. Thanks 573 00:33:07,040 --> 00:33:07,520 Speaker 1: for listening.