WEBVTT - Captain America: A Brave New ETF World 0:00:05.640 --> 0:00:06.360 Welcome to Trillions. 0:00:06.360 --> 0:00:08.640 I'm Joel Webber and I'm Eric Belchunis. 0:00:12.240 --> 0:00:13.840 This is going to be a fun episode, Eric. 0:00:13.960 --> 0:00:15.120 Yeah, I've been wanting to do this one for a 0:00:15.160 --> 0:00:15.640 while a. 0:00:15.600 --> 0:00:17.800 While, and we had to jump through them some hoops 0:00:17.840 --> 0:00:21.400 to make it happen. But it seems like a great 0:00:21.440 --> 0:00:24.480 moment to put the spotlight on the United States of America. 0:00:25.120 --> 0:00:28.320 We have President Trump back in the Oval Office. He 0:00:28.400 --> 0:00:32.440 has signed so many executive orders so far, but underlying 0:00:32.479 --> 0:00:34.879 it all is sort of like, you know, this attempt 0:00:34.880 --> 0:00:38.879 to kind of reassert American dominance. When you think about 0:00:39.080 --> 0:00:43.160 the equity market in particular, USA is always number one. 0:00:43.040 --> 0:00:43.280 Right er. 0:00:43.920 --> 0:00:45.800 Yeah, And you know, on our team, we have this 0:00:45.840 --> 0:00:49.720 persistent chat and we've actually it's come down to basically 0:00:49.760 --> 0:00:54.160 like mocking Europe. It's it's like they're the you know, 0:00:54.200 --> 0:00:55.600 we just had a full leaders at the Super Bowl. 0:00:55.960 --> 0:00:57.920 It's like they're the Cleveland Browns or the like, they're 0:00:57.960 --> 0:00:59.840 just a bad team that just can never get going. 0:01:00.520 --> 0:01:04.560 And then the index that we specifically are just marvel 0:01:04.600 --> 0:01:06.679 at is the Nasdaq one hundred. We call it the 0:01:06.680 --> 0:01:10.120 eighth Wonder of the World. It just keeps on freight 0:01:10.120 --> 0:01:13.080 training everything year in, year out. This is the cues, 0:01:13.959 --> 0:01:17.959 and it kind of captures like that American innovation tech 0:01:18.040 --> 0:01:20.319 thing even better than the S and P five hundred 0:01:20.319 --> 0:01:23.480 and so when you compare the cues to like investing 0:01:23.520 --> 0:01:27.119 in Europe, it's just so night and day. But at 0:01:27.160 --> 0:01:31.520 some point it's so much cheaper pete price to earnings 0:01:31.600 --> 0:01:35.200 ratio wise in Europe, everybody's like, oh, it's got to 0:01:35.240 --> 0:01:37.840 go back, but it never goes back. It might go 0:01:37.920 --> 0:01:39.880 back for two months, but then people come right back 0:01:39.920 --> 0:01:42.520 to the queues. And so I just think that the 0:01:42.640 --> 0:01:45.960 US stock market in particular, that the Nasdaq stocks and 0:01:46.000 --> 0:01:53.160 the mag seven are almost like abnormally unusually great where 0:01:53.200 --> 0:01:56.760 they deserve some kind of a scientific breakdown to analyze 0:01:57.360 --> 0:02:00.520 what's really behind all this because it almost breaks your 0:02:00.520 --> 0:02:01.240 brain a little bit. 0:02:01.440 --> 0:02:03.600 Well you know who's not a scientist, me or you, 0:02:04.080 --> 0:02:06.240 But it turns out we work with one. His name 0:02:06.280 --> 0:02:08.679 is Steve how he's a quantitative research at Bloomberg. He 0:02:08.720 --> 0:02:11.760 has a PhD. You started talking to him a while 0:02:11.840 --> 0:02:14.840 ago about America and it's greatness, right, would you learn? 0:02:15.080 --> 0:02:17.280 Yeah, because you know, we were looking at tech and 0:02:17.320 --> 0:02:20.200 innovation in other countries and it's just not. They have 0:02:20.320 --> 0:02:23.799 it there, but no one cares. Why is it rewarded 0:02:23.800 --> 0:02:26.400 in the US and not in other countries? And we 0:02:26.440 --> 0:02:30.600 had an interesting conversation about the culture here, the regulations, 0:02:31.200 --> 0:02:34.240 the mindset, this sort of like you can do it 0:02:34.760 --> 0:02:37.040 and who cares if you fall in your butt? Like 0:02:37.080 --> 0:02:39.919 that doesn't exist everywhere else. Like a lot of people 0:02:39.919 --> 0:02:41.880 are just like get in line and hammer, you know 0:02:41.919 --> 0:02:45.200 what I mean? Like America is a special place, and 0:02:45.520 --> 0:02:47.280 we don't do everything great. We're not number one and 0:02:47.360 --> 0:02:48.880 a lot of things, Joel, but when it comes to 0:02:48.919 --> 0:02:50.680 like the stock market, man. 0:02:50.520 --> 0:02:51.239 We kick ass. 0:02:51.760 --> 0:02:55.520 The US has four percent of the world's population, twenty 0:02:55.560 --> 0:02:58.800 percent of the world's GDP, and our stock market is 0:02:58.919 --> 0:03:02.320 fifty five percent of the whole world. Right, you got 0:03:02.360 --> 0:03:04.760 to go. I think number two is something like Japan, 0:03:05.240 --> 0:03:07.320 where Europe is a continent, is like eight percent or 0:03:07.360 --> 0:03:07.959 something like that. 0:03:08.320 --> 0:03:11.959 So joining us on this episode, Steve, how quantitative researcher 0:03:12.200 --> 0:03:20.840 have Bloomberg in disease? This time on Trillions Captain America. Steve, 0:03:21.000 --> 0:03:21.800 welcome on Trillions. 0:03:22.080 --> 0:03:24.480 Thank you very much for having me finally, and Eric, yeah, 0:03:24.520 --> 0:03:25.120 good to see you. 0:03:25.360 --> 0:03:29.520 So, Steve, Bloomberg is a big place. I work in 0:03:29.560 --> 0:03:32.760 the news group. Eric works in Bloomberg Intelligence. What is 0:03:32.760 --> 0:03:34.600 Bloomberg indsease and what's your day job? 0:03:35.160 --> 0:03:39.440 So Bloomberg Indisses is part of Bloomberg's data team now 0:03:39.680 --> 0:03:42.760 and I am a quant researcher for Bloomberg Indices. And 0:03:42.800 --> 0:03:47.760 we create investible indices or portfolios which can be then 0:03:47.920 --> 0:03:52.120 licensed by as a managers and as owners to track right. 0:03:52.440 --> 0:03:56.720 We create investment products and inducees that we license, and 0:03:56.720 --> 0:03:58.160 then once in a while, if we come up with 0:03:58.160 --> 0:04:00.920 something that we've seen that we think interesting that's worth 0:04:01.160 --> 0:04:04.240 expanding a bit more than we then run long form 0:04:04.240 --> 0:04:04.800 white paper. 0:04:05.080 --> 0:04:08.360 Okay, so he's written some white papers. Did you read them? 0:04:08.640 --> 0:04:10.040 Yeah, I mean I skimmed them. 0:04:10.080 --> 0:04:13.119 Okay, all right, we're gonna we're gonna learn a little 0:04:13.120 --> 0:04:13.280 bit of. 0:04:13.720 --> 0:04:16.640 The pricing power. But you she said, was very good. 0:04:16.920 --> 0:04:20.600 Yeah. And the innovation, I mean, they're they're they're very good. 0:04:20.640 --> 0:04:24.680 And the Index group is obviously mentally in the same 0:04:24.720 --> 0:04:26.560 ballpark as us because we write passive. 0:04:26.839 --> 0:04:27.840 But he sells stuff. 0:04:28.200 --> 0:04:30.480 True. Yeah, you're on the revenue side of the building. 0:04:30.560 --> 0:04:32.840 Yeah, it's important. There's a disclaimer there, which is, you know, 0:04:32.880 --> 0:04:34.520 we're not going to turn on the We're not going 0:04:34.520 --> 0:04:35.880 to talk our own business. 0:04:35.560 --> 0:04:38.599 No, No, I'm part of the terminal value add. 0:04:39.960 --> 0:04:44.320 So Steve, just big picture what makes America fundamentally with 0:04:44.400 --> 0:04:46.480 the research that you do, the data that you see, 0:04:46.800 --> 0:04:51.039 why is American innovation greater than anywhere else in the world? 0:04:51.320 --> 0:04:54.000 So h if you so went real this white pipe 0:04:54.040 --> 0:04:56.720 of because you know, we created a index to try 0:04:56.760 --> 0:04:59.480 to capture innovation as a factor systematically, right, you know 0:04:59.640 --> 0:05:03.239 out there there's new people talk about we try to innovation. 0:05:03.560 --> 0:05:05.480 How do you actually do it? Right? There's the r ETF, 0:05:05.520 --> 0:05:09.400 which is an activetf F you know would selects them 0:05:09.480 --> 0:05:11.720 and you know it does what it does right. And 0:05:11.760 --> 0:05:14.120 then there's accuse, which is actually, when you think about it, 0:05:14.320 --> 0:05:17.640 not intentionally innovation index, just as all the companies that 0:05:17.680 --> 0:05:20.359 happens to be listed on the NAS Exchange, which of 0:05:20.400 --> 0:05:23.520 course has agglomeration effect, right, everybody sort of congregates that. 0:05:24.000 --> 0:05:25.839 But so it's not intentional. So how do you actually 0:05:25.920 --> 0:05:28.560 do it? So we start to actually look into some 0:05:28.800 --> 0:05:31.679 systematic accounting attributes. So R and D is a natural 0:05:31.680 --> 0:05:34.360 place to look, right, Companies spend and report R and 0:05:34.400 --> 0:05:36.680 D not or always consistently, and they may sort of 0:05:36.680 --> 0:05:39.320 attribute things a little bit differently, but generally the direction 0:05:39.440 --> 0:05:42.599 is correct. And people previously have looked at R and 0:05:42.640 --> 0:05:45.400 D intensity, you know, so normalized by sales so they 0:05:45.400 --> 0:05:48.360 can compare companies in the cross section. That's one way 0:05:48.360 --> 0:05:50.239 to do it, but we found actually was even better. 0:05:50.720 --> 0:05:53.760 It's actually to look at persistence of R and D spending, right, 0:05:53.839 --> 0:05:56.880 companies that grow their R and D spending three consecutive 0:05:56.960 --> 0:06:00.440 years year and year right, so, and by screening for 0:06:00.480 --> 0:06:04.039 these such as gets expensive. Yes, that gets expensive, but 0:06:04.040 --> 0:06:05.880 but more than that, it also means that there's a 0:06:05.960 --> 0:06:08.080 highly grow of persistence that needs to be funded by 0:06:08.080 --> 0:06:12.000 internally generated cash flow. On top of it, you probably 0:06:12.240 --> 0:06:15.600 soft indicative of the skills that you have the confidence 0:06:15.600 --> 0:06:18.840 in your own ability to convert right R and D activities, 0:06:18.880 --> 0:06:23.839 which is inherently very expensive and on certain into valuable 0:06:23.960 --> 0:06:24.880 intentionibal capital. 0:06:25.360 --> 0:06:28.359 I want to go even deeper and just okay, you 0:06:28.400 --> 0:06:31.880 grew up in I grew up in America. I basically 0:06:32.000 --> 0:06:35.080 was raised outside. I went down played with people like 0:06:35.160 --> 0:06:37.760 droll down the street. We got into football games in 0:06:37.760 --> 0:06:41.080 the backyard. Then I entered little league games, had to 0:06:41.120 --> 0:06:44.440 get along with teammates from all over the place. There 0:06:44.520 --> 0:06:49.480 was also a feeling of optimism in the in my 0:06:49.600 --> 0:06:53.000 upbringing at all times pretty much it was like anything's possible. 0:06:53.720 --> 0:06:56.279 And then you go to high school and college and 0:06:56.320 --> 0:07:00.200 you're frequently grouped with people to work on tasks and 0:07:00.720 --> 0:07:03.840 as a team try new things, and. 0:07:04.440 --> 0:07:06.880 I break breakdown problems. 0:07:06.560 --> 0:07:11.240 Breakdown problems, and there's also credit from being the one 0:07:11.240 --> 0:07:13.840 that does the good thing, like there's a number one 0:07:13.880 --> 0:07:17.760 winner kind of celebrated here. Not to mention the bankruptcy 0:07:18.280 --> 0:07:23.240 laws and the regulatory environment, it just seems like, I'm 0:07:23.280 --> 0:07:24.520 not sure how you replicate that. 0:07:24.800 --> 0:07:28.080 I think recently there was a very good interview that 0:07:28.400 --> 0:07:31.400 Jeff Bezos gave at the Old Book. You know, he 0:07:31.520 --> 0:07:34.520 mentioned that one of the biggest, you know, I think 0:07:34.680 --> 0:07:37.640 reasons why America manages to have such a vibrant tach 0:07:37.680 --> 0:07:41.240 sector innovative industry is because of the presence of a 0:07:41.360 --> 0:07:43.640 risk capital market, which is different from a banking market, 0:07:43.680 --> 0:07:45.840 right financial markets. You know, if you think about landing 0:07:45.920 --> 0:07:49.280 right banks land Europe has a very good banking industry, 0:07:49.720 --> 0:07:53.040 but the ability to have risk capital venture right to 0:07:53.200 --> 0:07:56.600 invest in things that has one hundred chunds or even 0:07:56.680 --> 0:07:58.880 less to work out. That's gonna when it pays off, 0:07:59.000 --> 0:08:00.920 pays out one to to one hundred and one to 0:08:00.960 --> 0:08:03.880 one thousand. That is the type of risk taking that 0:08:04.000 --> 0:08:09.000 comes with I think both culturally and also past dependence. Right, 0:08:09.080 --> 0:08:11.520 some of it has to do with cultural this idea 0:08:11.600 --> 0:08:14.760 of being encouraged as a child to try things and 0:08:14.800 --> 0:08:16.920 not be told that you likely will not succeed, but 0:08:16.920 --> 0:08:19.240 to be told just try it. Right. Then, there was 0:08:19.320 --> 0:08:22.040 also the fact that Americas happened to have succeeded in 0:08:22.080 --> 0:08:25.560 the tech industry, a bunch of people succeeded by concentrated 0:08:26.080 --> 0:08:31.840 entrepreneurship and equity appreciating, giving them the confidence of saying, yeah, 0:08:32.240 --> 0:08:35.480 I can take a risk investing in in venture. 0:08:36.040 --> 0:08:38.760 But if you take venture capitalists could invest in the 0:08:38.840 --> 0:08:43.040 European I mean they're not like just legally allowed to 0:08:43.080 --> 0:08:45.440 invest in the US like they they if they thought 0:08:45.480 --> 0:08:47.840 Europe was the better odds to get that like Unicorn, 0:08:47.920 --> 0:08:48.880 they would go there, right. 0:08:48.840 --> 0:08:51.120 So, like, well, part of it I think to be 0:08:51.160 --> 0:08:53.920 fair to Europe is that Europe. When I recently, I've 0:08:54.000 --> 0:08:55.959 taken a few trips business trips to Europe to try 0:08:55.960 --> 0:08:59.400 to understand how to actually get European clients to buy stocks, 0:08:59.440 --> 0:09:02.040 and one we've noticed that there's just such a huge 0:09:02.040 --> 0:09:04.800 amount of fragmentation of markets. It's impossible to get a 0:09:04.840 --> 0:09:07.840 huge market right because everyone little country still has its 0:09:07.840 --> 0:09:11.719 own language, you know, own regulation and just customs, and 0:09:12.000 --> 0:09:16.120 it's impossible to scale what product. So if you're an airbnb, right, 0:09:16.280 --> 0:09:18.960 you can have the entire US market. If you succeed here, 0:09:19.120 --> 0:09:22.600 you become this behemoth and then go overseas. Everybody is lightweight, 0:09:22.720 --> 0:09:25.800 you know. So I think it's a combination of issues. 0:09:25.840 --> 0:09:30.040 I think cultural, you know, sort of is certainly at 0:09:30.080 --> 0:09:31.920 the core of it, but you know, there are other 0:09:32.320 --> 0:09:35.720 sort of institutional factors. 0:09:40.800 --> 0:09:44.240 This idea of international also is something Bogel I wrote 0:09:44.240 --> 0:09:46.520 a piece about a month ago, and I was like, 0:09:46.600 --> 0:09:49.600 Bogel was kind of right about international. In ninety three 0:09:49.800 --> 0:09:52.360 is the first time he had written, you don't really 0:09:52.400 --> 0:09:56.439 need international. The US has all the capitalism you need. 0:09:56.559 --> 0:09:59.439 If you had followed his advice, man you would have 0:09:59.600 --> 0:10:02.440 really benefitted by not going international. So a lot of 0:10:02.440 --> 0:10:07.559 people that I know, advisors and portfolio managers, they're always 0:10:07.600 --> 0:10:10.880 in this dilemma of whether to rotate internationally, but it 0:10:11.040 --> 0:10:14.280 just doesn't ever pan out. And I think that's part 0:10:14.320 --> 0:10:16.840 of why this matters now is that we got big 0:10:16.960 --> 0:10:21.600 valuations here, low valuations in Europe. But does Europe have 0:10:21.679 --> 0:10:23.120 to go up just because it's due? 0:10:23.400 --> 0:10:25.920 Well, so, the one thing is that if you recall 0:10:26.160 --> 0:10:28.920 a post dot com bubble in the early few thousands, 0:10:28.920 --> 0:10:31.360 you know that was a period when a bunch of 0:10:31.559 --> 0:10:33.679 sort of things that we are not used to. How 0:10:33.679 --> 0:10:34.160 did it happen? 0:10:34.280 --> 0:10:34.400 Right? 0:10:34.440 --> 0:10:37.760 International, I'll perform the US right, Europe, I'll perform the 0:10:37.880 --> 0:10:41.640 US EM I'll perform the US value, I'll perform growth right, 0:10:42.520 --> 0:10:45.959 and bones actually outperform stocks, you know, for many years 0:10:46.440 --> 0:10:50.280 until things sort of then resumed. It's long run trajectory 0:10:50.320 --> 0:10:53.320 and you have to triumph of the optimists. But you 0:10:53.360 --> 0:10:55.320 know there are conditions in which you know. 0:10:55.640 --> 0:10:57.760 I think the point you're making, though, which is is 0:10:57.760 --> 0:11:02.440 a good control. Bogo really had very deep wisdom, and 0:11:02.480 --> 0:11:05.200 he knew US would have bad years. He was going 0:11:05.240 --> 0:11:07.840 to stay invested. I think if you add international and 0:11:07.920 --> 0:11:10.439 bonds and this other stuff, when they go up and 0:11:10.480 --> 0:11:12.679 the US goes down, it gives you comfort and like 0:11:12.720 --> 0:11:15.000 it helps you hang in there. So if you have 0:11:15.080 --> 0:11:18.560 a behave, if you're somebody who can't have the intestinal 0:11:18.600 --> 0:11:21.080 fortitude to just stick to the US. But the returns 0:11:21.080 --> 0:11:24.439 I'm talking about are actually inclusive of those bubbles bursting 0:11:24.640 --> 0:11:28.360 two thousand and eight, two thousand and one, International way lags. 0:11:28.400 --> 0:11:30.959 But you're right, there's these sections of time that could 0:11:31.000 --> 0:11:34.679 be years where you're going to underperform. But I think 0:11:34.720 --> 0:11:37.240 in Bogel's case, he was like, I'm committed to the 0:11:37.280 --> 0:11:41.040 S and P five hundred. I don't need the feeling 0:11:41.080 --> 0:11:43.320 that something else in my portfolio is up, which is 0:11:43.360 --> 0:11:45.160 a level of wisdom that's hard to get to. 0:11:45.840 --> 0:11:47.800 Yeah, I mean, part of it is exactly because the 0:11:47.920 --> 0:11:49.920 US is such a huge economy with such a tremendous 0:11:49.920 --> 0:11:53.080 complexity that there is everything that's happening right inside of 0:11:53.080 --> 0:11:56.079 individual countries that's only exposed to oil or banking on 0:11:56.200 --> 0:11:58.520 and so on and stuff forth. So this national boundary 0:11:58.520 --> 0:12:01.079 division was always obitring the US place. I never really 0:12:01.120 --> 0:12:03.559 like the comparison or two lines of a Europe US 0:12:03.640 --> 0:12:06.679 up performing Europe because it's not the Apple Store comparison. 0:12:06.679 --> 0:12:10.200 If you actually compared sort of sector weights adjusted or 0:12:10.240 --> 0:12:13.719 equity duration adjusted, you will find that the difference, what 0:12:13.800 --> 0:12:16.000 there is, a premium difference, is not as big as 0:12:16.280 --> 0:12:17.280 one might have thought. 0:12:17.280 --> 0:12:18.400 Or see if I want to bring it back to 0:12:18.440 --> 0:12:22.719 your your paper and how you think about building in 0:12:22.880 --> 0:12:28.040 disease that can help capture investment. Right, So you brought 0:12:28.080 --> 0:12:31.960 up persistent R and D being the data point that 0:12:32.160 --> 0:12:34.240 is like kind of the north start for the style investing. 0:12:35.240 --> 0:12:37.200 How do you go about getting that data? By the way, 0:12:37.480 --> 0:12:39.920 it's all you know, the companies are doing this, but 0:12:40.000 --> 0:12:42.800 like what do you see when you look at those numbers? 0:12:43.240 --> 0:12:46.520 So companies, first of all, that they increase, they are 0:12:46.559 --> 0:12:49.439 required to you know, sort of disclose their R and 0:12:49.520 --> 0:12:52.800 D and you know spending expenditures and you know for 0:12:52.800 --> 0:12:55.640 a long time depending on or coman treatment. If R 0:12:55.679 --> 0:12:58.240 and D spending is immediately allowed to be expensed, they 0:12:58.280 --> 0:13:00.800 are actually incentivized, you know, to expand and so they 0:13:00.800 --> 0:13:04.960 can reduce their textbook you know income. But more broadly, 0:13:05.040 --> 0:13:08.000 we're just looking for, you know, in a systematic fashion, 0:13:08.160 --> 0:13:11.200 metrics that can most succinctly, sort of in the sufficient 0:13:11.200 --> 0:13:15.720 sufficient statistic way identify companies accurately that fit the profile 0:13:15.720 --> 0:13:17.360 we're looking for. So in this case, we're looking for 0:13:17.400 --> 0:13:20.360 innovative companies. You know, what is one metric that really 0:13:20.360 --> 0:13:23.800 captures companies? You know ability to innovate, and we zoomed 0:13:23.800 --> 0:13:27.680 in on the R and D spending metric in particular. 0:13:27.800 --> 0:13:32.440 We found that more than the intensity is the persistence 0:13:32.760 --> 0:13:35.320 of R and D spending that really allows you to 0:13:35.640 --> 0:13:39.160 sort of screen down to the companies that are genuinely innovative. 0:13:39.280 --> 0:13:41.440 Well, it's an example of the company that goes that 0:13:41.600 --> 0:13:44.240 big on R and D but maybe isn't as persistent, 0:13:44.280 --> 0:13:46.000 and what's that? What's that when that's more persistent? 0:13:46.280 --> 0:13:49.640 So like, I don't want to go into an individual company, 0:13:49.640 --> 0:13:51.440 but more more more likely I think it's one thing 0:13:51.559 --> 0:13:53.160 is like if you look at, for example, the art 0:13:53.240 --> 0:13:56.120 portfolio versus the you know, sort of the queues or 0:13:56.360 --> 0:13:59.880 or in this case, the Bloomberg be invent Index, which 0:14:00.080 --> 0:14:03.960 which is which we created and it's comfortable to the cues. 0:14:04.000 --> 0:14:05.520 And here I do want you I want to give 0:14:05.559 --> 0:14:09.400 credit to my colleague Garl Panzea who who you know, 0:14:09.440 --> 0:14:13.240 helped create this this metric. Uh, is that if you 0:14:13.320 --> 0:14:16.359 go back to compare the rc ETF you know membership, 0:14:16.440 --> 0:14:18.679 the companies in there spend a tremendous amount of money 0:14:18.679 --> 0:14:20.680 on R and D. Right, and if you normalize by 0:14:20.760 --> 0:14:23.600 net sales, the average ratio is perhaps higher in fact 0:14:23.600 --> 0:14:26.600 than the companies that are contained in this portfolio. But 0:14:26.600 --> 0:14:29.760 if you compare the performance over time sort of you know, 0:14:30.320 --> 0:14:33.920 this index is tremendously outperformed the art portfolio over time. 0:14:34.240 --> 0:14:36.760 Now why is that. It's because the companies that held 0:14:36.760 --> 0:14:40.080 in her profile in the portfolio tend not to be 0:14:40.400 --> 0:14:43.640 consistently profitable. As a result, they don't consistently spend the 0:14:43.720 --> 0:14:44.920 R and D. They sort of one of those things. 0:14:45.080 --> 0:14:47.200 They spent one year when they have profits, the next 0:14:47.240 --> 0:14:49.160 year they spend less, and so on and so forth. 0:14:49.280 --> 0:14:51.640 So the average is high, but the persistence is not 0:14:51.760 --> 0:14:54.720 very high. And as we all know, so those of 0:14:54.800 --> 0:14:56.560 us who are trying to innovate, it's one of those 0:14:56.600 --> 0:14:59.040 things where you can't really just you have to get it, sticks, 0:14:59.240 --> 0:15:01.840 stick to it. You have really you know, persevere through, 0:15:02.120 --> 0:15:05.280 you know, uh, and that's how you menually make the discovery. 0:15:05.600 --> 0:15:10.440 And in fact, if you compare the US you know 0:15:10.720 --> 0:15:13.800 index and why he has performed Europe. You know, going 0:15:13.800 --> 0:15:17.920 back to our discussion earlier, the biggest difference between US 0:15:17.960 --> 0:15:20.560 and Europe is not even the level, right, is actually 0:15:20.560 --> 0:15:24.400 the percentage of companies that have persistence a high degree 0:15:24.400 --> 0:15:28.240 of persistence. And we started the millennium actually with the 0:15:28.320 --> 0:15:31.920 US and Europe being at similar levels of intensity and 0:15:32.320 --> 0:15:35.520 percent of companies that have uh, sort of three consecutive 0:15:35.600 --> 0:15:37.320 years R and the growth. And it was over the 0:15:37.400 --> 0:15:40.920 last twenty years that difference really diverged, right Uh. And 0:15:41.000 --> 0:15:42.920 you can so in the in the paper, you have 0:15:42.960 --> 0:15:44.880 these sort of tables. You can check out these numbers. 0:15:45.240 --> 0:15:47.720 That's why, in my opinion, it's not just R and 0:15:47.800 --> 0:15:53.720 D spending. It's a U S thing. And and I 0:15:54.360 --> 0:15:56.000 talk to people on Twitter life and they say, well, 0:15:56.040 --> 0:15:58.480 you can get growth here. You just it's hard to 0:15:58.520 --> 0:16:01.240 get growth other places. Sometimes there's these speculative bubbles like 0:16:01.240 --> 0:16:04.240 in China, but pound for pound, you're just you're just 0:16:04.240 --> 0:16:06.000 going to get more growth here in some of these 0:16:06.040 --> 0:16:08.800 big companies that are in the US, they're just growing. 0:16:08.840 --> 0:16:11.000 But Steve's going to bring it back to persistent R 0:16:11.040 --> 0:16:11.880 and D being that thing. 0:16:11.920 --> 0:16:14.280 And if you go, yeah, but that that that exists 0:16:14.280 --> 0:16:16.160 in Europe too, but nobody cares. 0:16:16.240 --> 0:16:19.240 Like that, not to nearly the same extent right over. 0:16:19.080 --> 0:16:21.840 The last time in percent increase, that's right. 0:16:22.120 --> 0:16:25.800 The share of companies that sort of really remained persistent 0:16:25.880 --> 0:16:28.800 in R and D spending just dropped, right, and bisector 0:16:28.800 --> 0:16:31.000 of the sector, you can compare them, Whereas in the 0:16:31.120 --> 0:16:33.720 US tech sector is you know, sort of over fifty percent. 0:16:34.280 --> 0:16:36.400 You know, in Europe you're talking about half that and 0:16:36.520 --> 0:16:40.240 actually peaked in twenty thirteen, and actually it is even 0:16:40.280 --> 0:16:43.760 smaller today. In other words, I think it's a kind 0:16:43.800 --> 0:16:45.520 of a in the American the case is kind of 0:16:45.520 --> 0:16:48.480 a virtual cycle, right when you have these innovative companies, 0:16:48.720 --> 0:16:50.880 and I show in the paper that when they invest 0:16:50.920 --> 0:16:54.360 persistently R and D, it produces intensible capital which then 0:16:54.400 --> 0:16:56.960 becomes truly valuable, right, and it spins out cash flow. 0:16:57.000 --> 0:16:59.960 Right if Apple invents the iPhone, invents the AirPods, if 0:17:00.000 --> 0:17:02.680 becomes a six of a product, and that cash flow 0:17:02.960 --> 0:17:05.399 funds R and D. Because R and D is inherently 0:17:05.520 --> 0:17:08.600 a very opaque, asymmetric information activity, right, you don't really 0:17:08.640 --> 0:17:12.200 want to erase external financing to fund it because nobody's 0:17:12.240 --> 0:17:14.240 going to know how you're spending it. So you want 0:17:14.240 --> 0:17:17.160 to use internally generated cash flow, which is why what's 0:17:17.359 --> 0:17:20.000 nice about this metrip we created is that we don't 0:17:20.000 --> 0:17:23.400 need explicitly even screen for cash flow because these companies 0:17:23.480 --> 0:17:27.760 that persistently invest in R and D automatically are profitable 0:17:27.880 --> 0:17:30.919 and general cash flow and they invest in themselves. So 0:17:30.960 --> 0:17:33.119 which is why today you're seeing the AI race is 0:17:33.160 --> 0:17:36.119 all the hyperscalers that are investing capacs by the hundreds 0:17:36.160 --> 0:17:40.240 of billions themselves. They're not boring, right, So what. 0:17:40.200 --> 0:17:42.920 You're describing is effectively a flywheel, right, this is the 0:17:43.480 --> 0:17:45.639 R and D flywheel that that's what makes me. 0:17:46.320 --> 0:17:48.639 Let's say we decided to go into Europe. Europe had 0:17:48.680 --> 0:17:50.440 an ice run for six months like two years ago. 0:17:51.359 --> 0:17:54.359 Is that flywheel going to start there and keep getting rewarded? 0:17:54.359 --> 0:17:57.280 In other words, are the European companies going to spend 0:17:57.280 --> 0:18:01.240 it as well, our work as hard as in the US, 0:18:01.320 --> 0:18:04.080 where that R and D is rewarded with these intangible 0:18:04.320 --> 0:18:06.840 brands and you know, huge, great products that we have. 0:18:07.240 --> 0:18:09.200 Yeah, I think that's probably a challenge. I mean, France, 0:18:09.200 --> 0:18:12.200 I think just announced one hundred billion euro projects try 0:18:12.280 --> 0:18:16.440 to replicate or to to emulate America Stargate AI project. 0:18:16.720 --> 0:18:19.560 I think their challenge there is I think again, all 0:18:19.600 --> 0:18:21.879 these factors that are not pointing in the right direction, right, 0:18:21.960 --> 0:18:24.200 so they don't have a you know, sort of unified 0:18:24.240 --> 0:18:27.199 single market. The language is not English. It's hard for 0:18:27.240 --> 0:18:29.520 them to draw talent. They have a lot of you know, 0:18:29.600 --> 0:18:33.480 so well trained French engineers from their cause, but you know, 0:18:33.560 --> 0:18:35.400 sort of it's hard for them to I think, get 0:18:35.440 --> 0:18:37.640 your scale. You talk about the work culture, they don't 0:18:37.680 --> 0:18:40.520 have as much. I think the text code probably makes it, 0:18:40.920 --> 0:18:43.080 you know, such the people are not as incentivized to 0:18:43.480 --> 0:18:45.680 work those long hours, sleep on the factory floors and 0:18:45.720 --> 0:18:47.480 so on. I mean I'm generalizing here. I mean they 0:18:47.480 --> 0:18:52.280 are really genuinely creative, ingenious, hardworking people in Europe. Like 0:18:52.280 --> 0:18:55.000 there's the Mistraw model, AI model that's really I think 0:18:55.800 --> 0:18:57.679 the state of the art. But I think, what if 0:18:57.680 --> 0:19:00.320 you're sort of, so to speak, generalizing there is think 0:19:00.400 --> 0:19:02.120 those factors that work against them? 0:19:02.200 --> 0:19:06.040 Okay, So I used to take meetings a number of 0:19:06.080 --> 0:19:09.600 years ago with Huawei. Do you know what Huawei? The 0:19:09.640 --> 0:19:12.400 stat that they would point to persist in R and D. Yeah, 0:19:12.680 --> 0:19:15.199 and it was a big number, and they would like 0:19:15.440 --> 0:19:17.959 show it how much bigger they spent, how much more 0:19:18.000 --> 0:19:20.680 money they spent on R and D than American companies. 0:19:21.359 --> 0:19:24.560 So let's bring China into this. China spins a ton 0:19:24.640 --> 0:19:27.239 on R and D. What is that? How does that 0:19:27.800 --> 0:19:29.200 challenge your assumptions. 0:19:28.720 --> 0:19:31.240 In so so you got cleary. You know, so this 0:19:31.320 --> 0:19:33.520 episode is a cuptain in America, right, and the last 0:19:33.560 --> 0:19:37.160 time years, America is far and away the biggest, most 0:19:37.200 --> 0:19:41.000 successful you know, spender and creative innovation. 0:19:41.119 --> 0:19:44.000 By the way, see you're Captain America. That's that was 0:19:44.000 --> 0:19:44.880 That was the joke. 0:19:45.080 --> 0:19:47.760 Yeah, that was the nickname you got. 0:19:48.680 --> 0:19:51.000 That's funny, even though I'm not. 0:19:52.000 --> 0:19:54.560 I know it adds to the humans run with it. 0:19:54.680 --> 0:19:56.800 So so so if you look in the paper and 0:19:56.840 --> 0:19:58.800 Fogus figure travel, like I was sort of doing a 0:19:58.840 --> 0:20:02.520 tabulation of like what percentage of the companies you know, 0:20:02.640 --> 0:20:06.320