WEBVTT - ARK's Head of Research on How They Find the Next Huge Winner 0:00:10.920 --> 0:00:14.760 Hello, and welcome to another episode of the Odd Lots Podcast. 0:00:14.800 --> 0:00:18.760 I'm Joe, Wasn'tal, and I'm Tracy all Away. So, Tracy, 0:00:19.600 --> 0:00:22.720 here's something that I never thought I would see again. 0:00:22.840 --> 0:00:27.360 So I first started following markets in the late nineties, um, 0:00:27.440 --> 0:00:30.560 you know, dot Com era, and something that I never 0:00:30.640 --> 0:00:33.200 thought I would see again in my career after that 0:00:33.479 --> 0:00:39.279 ended was the superstar fund manager. Okay, why is that? Well, 0:00:39.360 --> 0:00:41.760 actually that's a totally true. What I mean is more 0:00:41.880 --> 0:00:46.879 the superstar stock picker. Because of course, back in the 0:00:46.920 --> 0:00:49.640 old days there were a lot of like star stock 0:00:50.040 --> 0:00:53.920 stock pickers, fund managers, you know, Peter Lynch comes to mind, 0:00:54.320 --> 0:00:58.480 some of the other tech investors back then. But these days, 0:00:59.040 --> 0:01:03.200 with e t s, with online brokerages that make it 0:01:03.240 --> 0:01:06.199 really easy for individuals to buy stocks on their own, 0:01:06.800 --> 0:01:09.559 it really sort of seemed to me like that era 0:01:09.840 --> 0:01:13.959 was just gone. Right, So I suppose there was this 0:01:14.080 --> 0:01:18.280 idea that the time of stock picking has come and gone, 0:01:18.400 --> 0:01:20.480 and that if you want to make good returns in 0:01:20.520 --> 0:01:23.119 the market, you should just pour all your money into 0:01:23.160 --> 0:01:26.280 something like an smp F t F like a these 0:01:26.319 --> 0:01:29.000 sacks or something like that, and just stick with it 0:01:29.240 --> 0:01:32.240 and don't bother trying to outperform the market, because over 0:01:32.400 --> 0:01:35.640 a longer period of time, even the best stock pickers 0:01:36.160 --> 0:01:40.880 UH had eventually underperformed. Right. I think this mantra of 0:01:41.080 --> 0:01:44.120 don't try to pick stocks a if you try to 0:01:44.160 --> 0:01:47.520 pick stocks, you're probably gonna underperform the index, and be 0:01:48.360 --> 0:01:50.800 if you come across a mutual fund or a fund 0:01:50.800 --> 0:01:54.320 manager who's good at picking stocks, oh it's probably just luck. 0:01:54.680 --> 0:01:57.160 It's not gonna last to you know. Even if even 0:01:57.160 --> 0:01:59.240 if there is someone who can beat the market, how 0:01:59.280 --> 0:02:01.320 are you going to know whether it's actually worth putting 0:02:01.320 --> 0:02:03.360 her money with them? And so like this idea that 0:02:03.440 --> 0:02:06.400 everyone should just index, um they're trying to beat the 0:02:06.440 --> 0:02:09.680 market is kind of a loser's proposition. It's really been 0:02:10.120 --> 0:02:12.480 drilled into people's heads, and I think, like, you know, 0:02:12.600 --> 0:02:16.240 for years, they're really we just haven't had a sort 0:02:16.240 --> 0:02:19.919 of another a new Peter Lynch or Buffet. You know, 0:02:19.960 --> 0:02:23.120 there's like Stark Quantz, maybe some bond fund managers who 0:02:23.160 --> 0:02:25.880 are known, but the idea of like someone who's just 0:02:25.960 --> 0:02:30.280 really associated with a great track record of picking individual 0:02:30.360 --> 0:02:34.079 stocks hasn't been a thing for a while. And yet 0:02:34.639 --> 0:02:39.400 and yet a star stockpicker emerges over the horizon. Yeah, 0:02:39.440 --> 0:02:44.040 exactly right, So obviously that really Uh, that's for the 0:02:44.120 --> 0:02:47.560 first time in a long time, there is currently a 0:02:48.160 --> 0:02:51.280 fund manager, a stock picker who is a mass an 0:02:51.320 --> 0:02:55.079 incredible track record, an incredible following, And of course we're 0:02:55.120 --> 0:02:58.840 talking about Cathy Wood. She is the CEO and chief 0:02:58.840 --> 0:03:02.880 investment officer of ARC invest and there is this a 0:03:02.880 --> 0:03:07.480 total fascination with ARC and this family of actively traded 0:03:07.520 --> 0:03:09.880 E t f s that have just done a phenomenally 0:03:09.880 --> 0:03:14.400 well in terms of returns, but also attracted an extraordinary 0:03:14.520 --> 0:03:18.639 amount of investor cash in the last couple of years. Right, 0:03:18.960 --> 0:03:21.760 So the ARK E t f s, I mean, I'm 0:03:21.760 --> 0:03:26.040 looking at their performance. They have, you know, five different 0:03:26.200 --> 0:03:30.440 thematic portfolios alone that have basically doubled over the past year, 0:03:30.520 --> 0:03:33.760 which is pretty amazing if you think about it. Uh, 0:03:33.840 --> 0:03:36.560 it's amazing enough for just one stock to double in 0:03:36.640 --> 0:03:39.240 price like that and in just the space of twelve months, 0:03:39.240 --> 0:03:43.360 but to do it across multiple ETFs is really remarkable. 0:03:43.560 --> 0:03:47.920 And I think within their actual portfolio there's a tiny, 0:03:48.120 --> 0:03:52.839 tiny number of stocks that haven't risen recently, and I'm 0:03:52.880 --> 0:03:56.360 not even sure there are any actually, Um, it's a 0:03:56.440 --> 0:04:00.360 really amazing performance. It's really true to Actually I'm looking 0:04:00.400 --> 0:04:04.760 at at the end of their performance of a r 0:04:04.880 --> 0:04:08.360 k K, which is the sort of flagship innovation E 0:04:08.520 --> 0:04:10.760 t F that ARC has was up a hundred and 0:04:10.840 --> 0:04:15.160 fifty two for the year. Extraordinary returns. And if you 0:04:15.200 --> 0:04:18.240 look at the holdings, they're just all of the companies 0:04:18.320 --> 0:04:20.880 that have absolutely killed it in the recent environment. Tesla 0:04:21.200 --> 0:04:26.880 is the biggest one, but other names Square the Payments Company, Phenomenal, Roku, 0:04:27.320 --> 0:04:32.360 huge winner, Zillo, Spotify, tell Doc, which of course had 0:04:32.360 --> 0:04:36.200 an incredible year thanks to the rise of remote medicine 0:04:36.200 --> 0:04:41.800 and so forth. So it is a just extraordinary number 0:04:41.839 --> 0:04:44.520 of winners that this uh, this is a fund and 0:04:44.600 --> 0:04:48.160 the related funds, there's a related fund for finance and 0:04:48.680 --> 0:04:51.880 medicine that have that they've brought it just the track 0:04:51.920 --> 0:04:55.039 records incredible. If if anyone follows Eric Bolkunis, who's sort 0:04:55.040 --> 0:04:58.960 of Bloomberg intelligence is E t F analysts, I feel 0:04:58.960 --> 0:05:01.960 like three quarters of his tweets these days are just 0:05:02.080 --> 0:05:06.200 about how extraordinary this family of funds and the performance 0:05:06.240 --> 0:05:10.840 of ARC invest has been lately. Yeah. Absolutely, and uh, 0:05:11.400 --> 0:05:15.400 you mentioned Kathy would already, but it's sort of it's 0:05:15.440 --> 0:05:19.800 given rise to occults around her. I guess I don't 0:05:19.839 --> 0:05:22.200 want to say cult because that has negative connotations, but 0:05:22.320 --> 0:05:25.560 certainly there's been a lot of admiration and fascination with 0:05:25.760 --> 0:05:28.760 what she's been doing over at ARC. Yeah, and uh, 0:05:29.520 --> 0:05:32.919 we're recording this January twenty. I saw Erica bell Kuna's 0:05:32.920 --> 0:05:37.360 tweet just today that ARC has taken in is the 0:05:37.480 --> 0:05:40.480 third most popular fun family right now in terms of 0:05:40.560 --> 0:05:42.960 new money coming in so far, you're to date that 0:05:43.520 --> 0:05:46.960 that exceeds the money coming into Black Rocks. I share 0:05:47.000 --> 0:05:49.640 his family, which is much bigger. I mean that's like, 0:05:50.240 --> 0:05:52.280 that's like the name brand. That's like basically the Coca 0:05:52.360 --> 0:05:56.640 Cola of e t F So to have a sort 0:05:56.680 --> 0:06:00.599 of small boutique fund firm with a few deply traded 0:06:00.640 --> 0:06:03.760 fund pulling in more than I shares, it's just it's 0:06:03.800 --> 0:06:07.800 staggering stuff. Yeah. Absolutely, So we are going to be 0:06:08.040 --> 0:06:11.240 talking to someone from Ark today, right we are. So 0:06:11.360 --> 0:06:13.800 the question is how do they do it? How do 0:06:13.920 --> 0:06:17.000 they find how do they pick stocks? I mean, Tesla 0:06:17.160 --> 0:06:19.080 is obviously this huge winner, but it wouldn't have been 0:06:19.120 --> 0:06:21.360 a huge winner for them unless they had been in 0:06:21.440 --> 0:06:24.040 it for a lot longer than most people. So the 0:06:24.160 --> 0:06:27.520 question is how do they how do they find and 0:06:27.640 --> 0:06:31.440 pick great stocks that trouts the market? Everyone would like 0:06:31.520 --> 0:06:34.560 to know. Well, I'm also I'm also interested in how 0:06:34.640 --> 0:06:37.479 they deal with inflows as they get bigger, and whether 0:06:37.600 --> 0:06:39.479 or not that makes it harder to have a sort 0:06:39.520 --> 0:06:42.559 of active E t F that is focused on stock picking. 0:06:42.960 --> 0:06:45.560 So this is going to be a really interesting conversation 0:06:45.640 --> 0:06:48.480 I can tell. Yeah, I'm super excited about this one. 0:06:48.600 --> 0:06:50.880 So we're going to be speaking with Brett Winton. He 0:06:51.000 --> 0:06:55.320 is the director of research at arc Um. He's been 0:06:55.400 --> 0:06:59.520 with the company since its founding in Previously to that, 0:06:59.839 --> 0:07:03.800 he worked with Kathy Wood at Alliance Bernstein. They've worked 0:07:03.839 --> 0:07:07.760 together since two thousand seven. So with any luck, we're 0:07:07.800 --> 0:07:10.240 going to learn at least some of the secrets of 0:07:10.520 --> 0:07:13.679 um arc from Brett and how they do it. Although 0:07:13.680 --> 0:07:15.920 I should say, you know, to some extent, maybe it's 0:07:15.920 --> 0:07:18.960 not a secret because part of what they do is 0:07:19.000 --> 0:07:22.400 their research is very open, it's very transparent. They post models. 0:07:22.440 --> 0:07:25.320 So we're gonna we're gonna really learn, hopefully how it 0:07:25.400 --> 0:07:27.600 all works up. Brett, thank you very much for joining us, 0:07:28.040 --> 0:07:30.600 Thank you for having me. Happy to be here. So 0:07:31.560 --> 0:07:37.240 you've worked with Kathy previously at Alliance Bernstein since two 0:07:37.280 --> 0:07:41.360 thousand seven with ar Sin. Why do you sort of 0:07:41.520 --> 0:07:44.920 compare and contrast big picture, and then we'll get into 0:07:45.000 --> 0:07:48.920 details what the research process looks like at a sort 0:07:48.960 --> 0:07:53.920 of traditional asset management firm versus the sort of open, 0:07:54.040 --> 0:07:57.560 transparent research approach you take it our. I think it's 0:07:57.600 --> 0:08:00.160 interesting and that I was over hearing your intro and 0:08:00.440 --> 0:08:02.720 you were talking about stock picking, and I was hearing that, 0:08:02.840 --> 0:08:05.480 and and I don't think of what we do as 0:08:06.120 --> 0:08:10.400 stock picking at least at its inception level. So we 0:08:10.520 --> 0:08:14.160 really look at the technology level first. And so we 0:08:14.520 --> 0:08:20.680 specifically seek to identify disruptive technologies that basically technology platforms 0:08:20.760 --> 0:08:23.760 that future historians will look back upon and say, oh 0:08:23.840 --> 0:08:26.800 my gosh, that was a signpost technology that was as 0:08:26.840 --> 0:08:30.720 big as the computer, that was as big as electrification. Uh. 0:08:30.840 --> 0:08:35.000 And and there's an established criteria for identifying these technologies 0:08:35.040 --> 0:08:38.199 for it's called general purpose technology theory. But they all 0:08:38.559 --> 0:08:41.800 follow steep cost of clients, they all cut across sectors, 0:08:42.120 --> 0:08:45.199 and they all themselves or platforms of innovation. And so 0:08:45.559 --> 0:08:48.120 that actually matches that we're investing in those kinds of 0:08:48.200 --> 0:08:52.040 technologies matches with three critical weaknesses that I see in 0:08:52.120 --> 0:08:56.880 traditional fund management that create inefficiencies pricing inefficiencies that we 0:08:57.000 --> 0:09:01.520 seek to exploit. So the technology fall follow steep cost 0:09:01.600 --> 0:09:04.640 of clients, that the drama of those cost of declines 0:09:04.679 --> 0:09:07.959 don't manifest over the next three or six months, So 0:09:08.080 --> 0:09:10.600 it's it actually can look very linear over a short 0:09:10.640 --> 0:09:13.720 time horizon, and so it doesn't really impact UH. An 0:09:13.800 --> 0:09:16.160 understanding of that cost de client doesn't impact the way 0:09:16.200 --> 0:09:19.280 analysts model the company on the cell side over the 0:09:19.400 --> 0:09:21.680 next quarter or two. But if you take a step 0:09:21.720 --> 0:09:24.360 back and you have an intentionally longer term point of view, 0:09:25.120 --> 0:09:29.760 you can actually UH come to radically different conclusions about 0:09:29.880 --> 0:09:32.120 what the future state of the world is likely to 0:09:32.240 --> 0:09:35.360 look like relative to others, just by having an understanding 0:09:35.440 --> 0:09:38.040 of of the mechanics of how a cost decline occurs 0:09:38.360 --> 0:09:41.000 and then what the demand elasticity of that price difference 0:09:41.280 --> 0:09:44.800 is going to be. So that's like from the beginning, 0:09:44.840 --> 0:09:46.960 we set ourselves up to say, hey, we're not gonna 0:09:47.160 --> 0:09:50.400 we're not gonna try to trade stocks or identify securities 0:09:50.440 --> 0:09:53.439 that are mispriced on the basis of priced earnings or 0:09:53.559 --> 0:09:56.600 price to sales or any kind of shorthand for valuation, 0:09:57.080 --> 0:09:58.800 and we're not Also, we're also not going to try 0:09:58.840 --> 0:10:03.360 to do a full um DCF because a full discounted 0:10:03.400 --> 0:10:05.319 cash flow model, because then you get to cheat with 0:10:05.360 --> 0:10:07.400 how you use the discount rate in your terminal rate 0:10:07.440 --> 0:10:09.800 of growth. Instead, we're gonna say, if we own one 0:10:09.840 --> 0:10:13.120 of these companies, uh five years from now, if we're 0:10:13.120 --> 0:10:17.800 then forced to sell it to a technological pessimist, what 0:10:18.200 --> 0:10:20.560 will that person be forced to pay given the cash 0:10:20.600 --> 0:10:23.760 flow generation of the business at that time. And so, 0:10:24.000 --> 0:10:27.680 just by underwriting the positions over a five year perspective, 0:10:28.240 --> 0:10:30.880 we've been able to and still are able to identify 0:10:31.280 --> 0:10:35.079 really radically under priced securities. Uh So, I think of 0:10:35.160 --> 0:10:39.079 it as where value investors and intangible assets. Intangible assets 0:10:39.120 --> 0:10:42.720 are very difficult to understand how much cash flow they 0:10:42.760 --> 0:10:45.920 can can generate, but we really do the work of 0:10:46.000 --> 0:10:48.559 trying to figure that out over the time horizon. That 0:10:48.720 --> 0:10:52.800 matters in uh in the part of the capital structure 0:10:52.960 --> 0:10:56.120 that we're in equities or infinite and duration, it's really 0:10:56.280 --> 0:10:58.280 kind of dumb to underwrite them over a year or 0:10:58.320 --> 0:11:02.560 two because the market volatility is you know, really high, 0:11:02.760 --> 0:11:05.280 Like I can't tell you what the next twelve months 0:11:05.320 --> 0:11:07.520 of equities is going to look like I can actually say, 0:11:07.600 --> 0:11:11.400 with reasonable assurance over five years, this position is under priced. Uh. 0:11:11.480 --> 0:11:14.800 And so that's like the first major inefficiency we exploit. 0:11:15.320 --> 0:11:18.160 And at the technology level, what that means is, so 0:11:18.320 --> 0:11:20.920 take Tesla, which is a position that everybody is well 0:11:20.920 --> 0:11:23.959 aware of because we have a perspective on what the 0:11:24.040 --> 0:11:27.360 cost declines of batteries is going to do. It allows 0:11:27.480 --> 0:11:30.400 us to demonstrate to our satisfaction that we think by 0:11:31.480 --> 0:11:34.400 there will be electric vehicles that are sticker priced comparable 0:11:34.480 --> 0:11:38.319 to internal combustion engine vehicles and the average internal combustion 0:11:38.360 --> 0:11:40.959 engine vehicle. So you'll walk into a dealership and say, 0:11:41.080 --> 0:11:43.319 do I want a Toyota camera that you know it 0:11:43.400 --> 0:11:46.240 costs me more over time it I have to take 0:11:46.280 --> 0:11:48.400 it to the dealership more often because it breaks down 0:11:48.440 --> 0:11:51.520 more often, and it costs me basically the same amount 0:11:51.520 --> 0:11:53.559 of money out of pocket. Or do I want the 0:11:53.800 --> 0:11:56.760 down market equivalent of a Model three, which is faster 0:11:56.880 --> 0:11:59.280 off the line, cost me less money over time, and 0:11:59.360 --> 0:12:01.439 it costs me less money today. It would be a 0:12:01.559 --> 0:12:05.440 real surprise if people didn't shift over to buying electric vehicles. 0:12:05.760 --> 0:12:08.680 So with that as your initial perspective, you can say, hey, 0:12:08.920 --> 0:12:10.920 so if we are at we think they're going to 0:12:10.960 --> 0:12:15.040 be forty million electric vehicles sold by If if we're 0:12:15.080 --> 0:12:18.400 at forty million and the rest of the market, consultants, etcetera, 0:12:18.559 --> 0:12:22.280 or something like seven million, well there's probably some inefficiently 0:12:22.360 --> 0:12:27.400 priced assets exposed to that technology. So by identifying by 0:12:27.559 --> 0:12:31.600 underwriting over a time horizon, that's that's reasonable, we believe. 0:12:32.280 --> 0:12:36.680 And by identifying basically fertile terrain where technologies are misunderstood, 0:12:37.280 --> 0:12:41.760 then we can basically concentrate our exposure into equities that 0:12:41.840 --> 0:12:44.800 are more likely to be mispriced. So that's the I 0:12:44.960 --> 0:12:47.360 just talked a lot, But that's the first of three 0:12:47.440 --> 0:12:51.280 inefficiencies that we exploit. So I wanted to back up 0:12:51.280 --> 0:12:54.480 for a second because one thing, one thing I wonder 0:12:54.520 --> 0:12:58.200 a lot about in tech investing is what's the firm's 0:12:59.000 --> 0:13:03.800 collective ground here? Does it come primarily from finance or 0:13:04.040 --> 0:13:07.480 is there a lot of technological expertise? And what I 0:13:07.559 --> 0:13:10.679 mean by that is you mentioned that you're looking at 0:13:10.880 --> 0:13:15.400 technologies across a long term time horizon. Some of your 0:13:15.440 --> 0:13:18.640 E t F s are very very technical. I know 0:13:18.800 --> 0:13:21.880 you have a genomic revolution E t F for instance, 0:13:21.920 --> 0:13:24.600 and I think you're looking at space exploration as well. 0:13:25.000 --> 0:13:28.400 So how do you build up the tech expertise in 0:13:28.559 --> 0:13:31.439 order to be confident in your calls on what's going 0:13:31.520 --> 0:13:35.520 to work out in the long term. Well, that actually 0:13:35.720 --> 0:13:39.360 leads right into the second inefficiency that I see us exploiting. 0:13:39.600 --> 0:13:43.319 Because all of these technologies are a cross sector technologies, 0:13:43.720 --> 0:13:47.679 they actually kind of cut across the skis of traditional 0:13:47.880 --> 0:13:52.760 sector based analysts. Uh. You know, the auto analyst um 0:13:53.120 --> 0:13:56.080 had been told for years and years and years by 0:13:56.120 --> 0:13:59.120 the Tier one suppliers and by the automotive companies that 0:13:59.280 --> 0:14:03.480 electrically goals were actually not a meaningful technology. Not only 0:14:03.559 --> 0:14:06.120 that they're a niche technology, not only that the people 0:14:06.200 --> 0:14:07.840 trying to do it, we're crazy and we're probably going 0:14:07.880 --> 0:14:09.800 to bankrupt, and we'll be able to get the assets 0:14:09.840 --> 0:14:11.880 when we need them and we can invest in it 0:14:12.040 --> 0:14:15.480 later on if required. Uh and so and and that 0:14:15.640 --> 0:14:18.880 auto analysts who's sitting and basically that echo chamber of 0:14:18.920 --> 0:14:22.440 information with the quarterly calls with the CFO, the annual 0:14:22.560 --> 0:14:25.680 calls with the CEO, who has spent his and in 0:14:25.760 --> 0:14:28.520 this case it's always a heat in autos his entire 0:14:28.640 --> 0:14:31.760 career basically being like, well, now Ford's better than Nissan, 0:14:31.960 --> 0:14:36.520 and now GM is better than Ford. UH has has 0:14:36.600 --> 0:14:40.800 developed a pattern of thinking that basically doesn't allow him 0:14:40.880 --> 0:14:44.920 to UH really understand whether or not an electric vehicle 0:14:45.360 --> 0:14:50.000 will be competitive with these technology with the existing legacy technology, 0:14:50.560 --> 0:14:53.480 or or given him a good tool set by which 0:14:53.560 --> 0:14:55.960 to assess whether or not it will UH. And and 0:14:56.080 --> 0:15:00.080 so when I was at Alliance Bernstein Alumina, which as 0:15:00.080 --> 0:15:03.720 a genomics company is UH, you know, nineties plus percent 0:15:03.800 --> 0:15:06.240 of genome sequence in the world go through illumino boxes. 0:15:06.480 --> 0:15:09.479 At Aligned Ferns Seins, it was covered by our industrials analysts, 0:15:09.600 --> 0:15:12.280 and you know, he didn't know what to do with it. 0:15:12.400 --> 0:15:14.000 He almost would have had to take on a whole 0:15:14.080 --> 0:15:18.480 new like set of learnings in order to successfully cover 0:15:18.640 --> 0:15:21.840 this company that to him looked extremely high priced. It 0:15:22.040 --> 0:15:25.280 was not like Dana Her or Honeywell to him. And 0:15:25.440 --> 0:15:28.440 so he was perpetually a neutral. So the way that 0:15:28.600 --> 0:15:32.520 we approach kind of technology and markets is our analysts 0:15:32.520 --> 0:15:36.040 are assigned by technology rather than by sector. UH. And 0:15:36.160 --> 0:15:39.640 so it helps that our batteries analyst is able to Sam, 0:15:39.720 --> 0:15:42.400 who's great. He does the cost decline work on batteries. 0:15:42.440 --> 0:15:44.840 He understands how it's going to feed into certainly the 0:15:45.280 --> 0:15:48.880 electric vehicle industry, but he also can look at kind 0:15:48.920 --> 0:15:51.880 of the energy storage within the utility space think about 0:15:51.960 --> 0:15:55.400 how that impacts kind of the propensity for utility spend. 0:15:55.680 --> 0:15:58.960 He can understand how it's gonna impact aerial drones and 0:15:59.040 --> 0:16:02.400 their ability to both delivered parcels from place to place 0:16:02.520 --> 0:16:06.640 or or deliver people from place to place. By selecting 0:16:06.720 --> 0:16:11.280 for people that are expert in the technology, we believe 0:16:11.360 --> 0:16:14.800 we get an edge against basically sector experts who who 0:16:14.880 --> 0:16:18.000 are used to a kind of competitive landscape that that 0:16:18.280 --> 0:16:22.480 doesn't get dramatically upturned. Another example is in in banks, 0:16:22.560 --> 0:16:26.080 like I'm sure many bank analysts kind of poo pooed 0:16:26.160 --> 0:16:29.360 and overlooked Square. Well, our view is that you know 0:16:29.480 --> 0:16:32.520 you you have a digital bank branch in your pocket, 0:16:32.680 --> 0:16:35.720 and most of certainly the US is going to begin 0:16:35.840 --> 0:16:38.800 banking in that way over the next five years. And 0:16:39.320 --> 0:16:41.680 uh Square is a choir and customers through its peer 0:16:41.760 --> 0:16:44.400 to peer transfer app, the cash app at something like 0:16:44.480 --> 0:16:47.600 twenty dollars per customer. Traditional banks pay upwards of a 0:16:47.720 --> 0:16:51.720 thousand dollars per customer account. The products that that Square 0:16:51.800 --> 0:16:54.960 is gonna offer is going to expand, and that retail 0:16:55.040 --> 0:16:58.760 bank branch infrastructure is going to depreciate much more rapidly 0:16:58.880 --> 0:17:01.920 than any of the executive are willing to acknowledge or 0:17:02.320 --> 0:17:06.400 or maybe even understand. Uh and so a traditional banks 0:17:06.440 --> 0:17:09.639 analyst is not necessarily even empowered to turn around and 0:17:09.760 --> 0:17:12.760 suggest Square to his portfolio managers. It might be off 0:17:12.880 --> 0:17:15.560 limits to him. Uh and and and so kind of 0:17:15.680 --> 0:17:19.040 by focusing on the technologies that matter, with the analysts 0:17:19.040 --> 0:17:22.920 focused directly on those technologies, actually unlocks a lot of 0:17:23.000 --> 0:17:27.040 other sort of like misunderstood opportunities. Companies that fall through 0:17:27.080 --> 0:17:30.600 the cracks and UM and sectors that are really right 0:17:30.880 --> 0:17:35.440 for getting disrupted U that have people who have built 0:17:35.480 --> 0:17:39.159 their whole careers on understanding that the structure of the 0:17:39.280 --> 0:17:42.879 sector as it currently exists rather than as it likely 0:17:43.200 --> 0:18:02.479 is to exist. So this is this is really interesting, 0:18:02.520 --> 0:18:05.439 this sort of this sort of structural problem in stock 0:18:05.520 --> 0:18:11.800 identification as a result of people being bucketed into traditional 0:18:12.080 --> 0:18:16.160 UM sectors rather than starting at the technology technology level. 0:18:16.520 --> 0:18:19.320 You know, you, I think that's two inefficiencies. What is 0:18:19.440 --> 0:18:24.520 the third inefficiency that you seek to exploit? Uh, that 0:18:24.640 --> 0:18:28.800 you see within the sort of traditional investment selection approach, Well, 0:18:29.080 --> 0:18:31.920 you alluded to it, Joe, but we, Uh. All of 0:18:31.960 --> 0:18:36.480 these technologies are themselves platforms a top which other innovations 0:18:36.600 --> 0:18:39.200 are going to be built, and so it's really easy 0:18:39.320 --> 0:18:42.760 to suffer from a failure of the imagination. You really 0:18:42.840 --> 0:18:45.800 can't like. So some people try to model these technologies. 0:18:45.840 --> 0:18:49.040 They say, these are the three areas where it's selling today, 0:18:49.200 --> 0:18:50.959 and we're just going to drag out the growth rate, 0:18:51.040 --> 0:18:52.600 and that's going to be the size of the market. 0:18:53.560 --> 0:18:56.520 You can't pre imagine all the things that are going 0:18:56.560 --> 0:18:58.800 to happen on top of it. And so the only 0:18:58.920 --> 0:19:03.040 hope to begin to understand the potential scope and breadth, 0:19:03.400 --> 0:19:05.560 the areas where it will apply apply and where it 0:19:05.600 --> 0:19:09.840 won't is to um expand your information footprint, to be 0:19:09.960 --> 0:19:13.159 totally transparent about what you believe is going to happen. 0:19:13.560 --> 0:19:16.320 And so we publish blogs, we publish white papers, we 0:19:16.480 --> 0:19:19.840 talk on podcasts. We have our own podcast, it's f 0:19:20.080 --> 0:19:22.600 y I for your innovation. You should listen to it, uh, 0:19:22.680 --> 0:19:25.160 And we do that because when we produce this information, 0:19:25.280 --> 0:19:30.200 when we're transparent with our forecasts, that information attracts other information. 0:19:30.320 --> 0:19:33.040 People come back at us and say, I don't understand 0:19:33.080 --> 0:19:35.960 how you got to that conclusion you're wrong about solid 0:19:36.040 --> 0:19:39.680 state batteries. They really seek to combat us to to 0:19:40.119 --> 0:19:43.280 argue from first principles whether or not we're right and 0:19:43.560 --> 0:19:47.200 why and and so this helps us to understand both 0:19:47.280 --> 0:19:51.320 the limitations are of our ability to tell what's going 0:19:51.359 --> 0:19:54.359 to happen in the future and to get a sense 0:19:54.560 --> 0:19:57.200 for some things that we may not have imagined that 0:19:57.280 --> 0:20:00.719 we should be underwriting in to our fund mental models. 0:20:01.320 --> 0:20:03.960 Uh and so and that's very different. You know, just 0:20:04.160 --> 0:20:07.280 being able to access Twitter uh is not something that 0:20:07.840 --> 0:20:10.439 was is allowed in a lot of fun management shops. 0:20:10.680 --> 0:20:13.640 That seems crazy to me. Our analysts are on Twitter, 0:20:13.680 --> 0:20:15.920 they're interacting with the community. You know, this is the 0:20:15.960 --> 0:20:17.880 way you understand how the world is going to work. 0:20:18.280 --> 0:20:20.359 We believe that it gives us a competitive edge that 0:20:20.680 --> 0:20:23.440 from the beginning we've designed ourselves to be able to 0:20:23.560 --> 0:20:27.440 compliantly do that. Uh and and to kind of operate 0:20:27.560 --> 0:20:31.400 in the technology circles where these technologies are actually being 0:20:31.440 --> 0:20:35.160 grappled with and built and um and deployed into the market. 0:20:36.000 --> 0:20:38.720 So I wonder if you could bring a lot of 0:20:38.880 --> 0:20:42.359 the discussion that we've been having and sort of try 0:20:42.520 --> 0:20:46.680 to solidify it with a single stock example. I wanted 0:20:46.720 --> 0:20:49.920 to talk about Tesla because, of course, Kathy made a 0:20:50.000 --> 0:20:52.719 pretty famous call a couple of years ago. I think 0:20:52.800 --> 0:20:56.240 it was for Tesla's stock to go to four thousand dollars, 0:20:56.920 --> 0:21:00.480 and it has since hit that on a split adjusted basis, 0:21:00.680 --> 0:21:03.280 and you have a new price target on it. What 0:21:03.960 --> 0:21:09.159 is it that your methodology and your organizational structure was 0:21:09.280 --> 0:21:13.879 seeing about Tesla in particular that others aren't seeing. There 0:21:14.000 --> 0:21:17.080 was a lot of criticism and incredulity about that call 0:21:17.160 --> 0:21:19.000 when you made it a couple of years ago. So 0:21:19.520 --> 0:21:22.159 what was it that you saw? For one thing? So 0:21:22.280 --> 0:21:25.399 we have a cost A client on lithium I AM batteries. 0:21:25.440 --> 0:21:27.400 We think we have a better understanding of what goes 0:21:27.440 --> 0:21:31.200 into an electric vehicle than probably probably any other shop 0:21:31.280 --> 0:21:34.000 on the street. I don't know, certainly anybody than anybody 0:21:34.040 --> 0:21:37.480 publishing that informs both our top line forecasts I alluded 0:21:37.520 --> 0:21:40.720 to it. We we believe forty million units will be 0:21:41.119 --> 0:21:46.680 sold by of electric vehicles uh and and because they'll 0:21:46.960 --> 0:21:50.600 be cheaper than traditional cars. When we first began that 0:21:50.720 --> 0:21:53.440 top line forecasting, the EI A and and you know 0:21:53.560 --> 0:21:57.520 the OPEC, these policy agencies thought that electric vehicles were 0:21:57.520 --> 0:22:00.280 gonna sell in the two hundred three hundred thousand unit 0:22:00.840 --> 0:22:04.400 annually through the end of their forecast through. So first 0:22:04.400 --> 0:22:06.280 of all, you do that and you say, well, we 0:22:06.440 --> 0:22:10.479 must be doing something wrong, like what are we misunderstanding here? Uh, 0:22:10.640 --> 0:22:14.160 And it turns out I don't think we were misunderstanding anything. 0:22:14.240 --> 0:22:17.200 It's just that there's not actually a great set of 0:22:17.280 --> 0:22:21.640 incentive structures for people to make reasonable, first principles long 0:22:21.760 --> 0:22:25.400 term forecasts. I've been surprised. I thought that we would 0:22:25.400 --> 0:22:27.879 basically from inception, I thought we would be kind of 0:22:28.000 --> 0:22:32.000 duplicating the work of consultants like Mackenzie Global Institute, but 0:22:32.080 --> 0:22:34.800 we would understand the mechanics of how those forecasts were built, 0:22:35.040 --> 0:22:36.920 and so that would give us an edge. But we 0:22:37.280 --> 0:22:40.600 got totally different results. Sometimes sometimes we got similar results, 0:22:40.640 --> 0:22:42.560 in which case it's very easy to say, wow, this 0:22:42.720 --> 0:22:44.760 is kind of priced in. You know, there's probably not 0:22:45.200 --> 0:22:48.199 much that's of interest to us here. Um. But sometimes 0:22:48.240 --> 0:22:50.639 we got very different results. And I think it's for 0:22:50.800 --> 0:22:54.800 consultants because they actually are paid to to cater to 0:22:54.880 --> 0:22:58.200 the biases of the executives that hire them. But that aside. So, 0:22:58.800 --> 0:23:01.080 first of all, we think Tesla is you know, right 0:23:01.119 --> 0:23:05.520 now share of the electric vehicle industry forty million units. 0:23:07.160 --> 0:23:09.639 If they maintain their share, which we think they can 0:23:09.760 --> 0:23:11.800 scale production at that rate, then that would put them 0:23:11.840 --> 0:23:15.200 at ten million units in um we think that the 0:23:15.680 --> 0:23:20.160 electric vehicle industry is gonna consolidate. It's actually the products 0:23:20.200 --> 0:23:22.879 are differentiated on a software basis, much more so than 0:23:22.920 --> 0:23:25.879 internal combustion, So you could get to a naturally higher 0:23:26.000 --> 0:23:31.119 margin in that industry relative to traditional automotive And so 0:23:31.240 --> 0:23:33.680 you can do pretty simple math to to actually say 0:23:33.960 --> 0:23:38.720 Tesla as an electric vehicle manufacturer, just leaving aside robotaxi 0:23:38.880 --> 0:23:42.199