WEBVTT - Adam Parker on Strategies and Valuations 0:00:02.000 --> 0:00:07.160 This is Mesters in Business with Very Results on Bloomberg Radio. 0:00:09.240 --> 0:00:12.400 This week, on the podcast, I have an extra special guest, 0:00:12.640 --> 0:00:18.280 Adam Parker. What a fascinating career UH, top ranked institutional analysts, 0:00:18.280 --> 0:00:23.079 semiconductor analyst, head of research at Sanford Bernstein, head of 0:00:23.200 --> 0:00:27.680 US Equities at Morgan Stanley. Really a master class and 0:00:27.720 --> 0:00:31.800 how to think about creating frameworks for investing, for thinking 0:00:31.800 --> 0:00:37.239 about how to apply quantitative research along with macro and 0:00:37.280 --> 0:00:42.239 fundamental data UH in order to create a differentiated research product. 0:00:42.680 --> 0:00:46.159 Just absolutely a master class in thinking about stocks, and 0:00:46.159 --> 0:00:49.599 thinking about sectors, and thinking about where is the crowd 0:00:50.159 --> 0:00:53.319 wrong and how to come up with a UM very 0:00:53.400 --> 0:00:57.840 outlier perspective, many of which have been giant moneymakers and 0:00:57.920 --> 0:01:02.600 really UH fascinating market calls. I found this conversation to 0:01:02.680 --> 0:01:05.839 be brilliant and insightful, and I think you will also 0:01:06.240 --> 0:01:11.840 with no further ado my conversation with Trivariant Researches Adam Parker. 0:01:14.000 --> 0:01:19.160 This is mesters in Business with Very Results on Bloomberg Radio. 0:01:21.200 --> 0:01:24.480 My special guest this week is Adam Parker. He is 0:01:24.520 --> 0:01:29.319 the founder of Trivariant Research. Previously, he was Global director 0:01:29.360 --> 0:01:33.040 of Research and US equity strategist at Sanford ci Bernstein. 0:01:33.440 --> 0:01:37.280 He was the number one institutional investor ranked analyst in 0:01:37.400 --> 0:01:43.440 semiconductors before he became Morgan Stanley's chief US equity strategist 0:01:43.720 --> 0:01:48.880 and director of Global quant Research. Adam Parker, Welcome to Bloomberg. 0:01:49.160 --> 0:01:51.639 Thanks thanks for having me here. I've been looking forward 0:01:51.680 --> 0:01:54.800 to having this conversation for a while, and I have 0:01:54.960 --> 0:01:59.120 to start with your very interesting academic background. You have 0:01:59.360 --> 0:02:04.000 three agrees and stats, uh not just undergraduate at Michigan, 0:02:04.200 --> 0:02:07.919 but a PhD from Boston University. And in the middle, 0:02:07.960 --> 0:02:13.120 you've got a master's in biostatistics at UNC Chapel Hill. 0:02:13.120 --> 0:02:16.200 Tell us about that. Yeah, well, back then statistics wasn't 0:02:16.200 --> 0:02:18.280 as cool as it is now. Very so I didn't 0:02:18.280 --> 0:02:20.040 know thirty years ago I was going to turn into 0:02:20.080 --> 0:02:22.240 the all the rage and that everyone was kind of 0:02:22.240 --> 0:02:24.800 one a major in you know, data science and analytics. 0:02:24.840 --> 0:02:27.200 It just I was always more of a math guy, 0:02:27.240 --> 0:02:29.600 and I liked having problem sets and then going and 0:02:29.639 --> 0:02:31.239 playing sports, and I didn't want to have to read 0:02:31.360 --> 0:02:34.000 Chaucer or whatever all the other miserable people were doing. 0:02:34.080 --> 0:02:35.720 So kind of motivated me to be a little bit 0:02:35.720 --> 0:02:40.040 more analytical. So so, but the question that raises biostatistics 0:02:40.160 --> 0:02:42.600 is were you always planning on a career in finance 0:02:42.720 --> 0:02:45.000 or was that you know, that was more of UM. 0:02:45.280 --> 0:02:48.280 The biostatistics department was in the School Public Health at UNC, 0:02:48.720 --> 0:02:51.639 and it's really you know, applied statistics applied that at 0:02:51.639 --> 0:02:55.440 that age too, uh, mostly medical data, but it was 0:02:55.480 --> 0:02:59.280 more about learning analytics and you know, programming and UM 0:02:59.560 --> 0:03:01.560 and you can apply it to anything, complied to anything. 0:03:01.600 --> 0:03:04.160 So like my my PhD thesis was about missing data 0:03:04.440 --> 0:03:06.440 UM in a healthcare setting, but as you know, missing 0:03:06.520 --> 0:03:09.000 data exists everywhere, including a finance so it turned out 0:03:09.000 --> 0:03:12.120 to be pretty applicable. So how frustrating is it to 0:03:12.240 --> 0:03:16.400 you to to see either newspaper headlines or social media 0:03:16.919 --> 0:03:21.519 where people just lack of rudimentary understanding of basic statistics 0:03:21.520 --> 0:03:25.360 and probability, you know. I think the big challenges is, 0:03:25.400 --> 0:03:28.040 as you know, because you're good at this, is taking 0:03:28.040 --> 0:03:30.480 things that are somewhat complicated and then making them sound 0:03:30.520 --> 0:03:33.079 like they're simple and explaining them to everybody. I think 0:03:33.120 --> 0:03:37.600 the average UM intellect of people watching and reading mainstream 0:03:37.600 --> 0:03:40.360 media is still in the junior high or high school level. 0:03:40.440 --> 0:03:42.920 So that's what you've got to resonate with. And I 0:03:43.040 --> 0:03:45.600 romanticize the investment community is slightly above that, but it 0:03:45.600 --> 0:03:47.880 probably is less above that than you think, right, So 0:03:47.920 --> 0:03:51.360 so I love We'll talk about try variate a little later. 0:03:51.800 --> 0:03:55.960 I love the name. I wrote a Bloomber column years ago. Um, 0:03:56.160 --> 0:03:59.320 single variable analysis is for soccers or something like that, 0:03:59.640 --> 0:04:02.080 And so I have to talk to you about But 0:04:02.080 --> 0:04:05.480 but let's with all that stat background, how did you 0:04:05.520 --> 0:04:08.560 get to Sanford CT Bernstein? You know in those days? Um, 0:04:08.680 --> 0:04:11.520 you know, I finished my PhD um in the late nineties. 0:04:11.680 --> 0:04:13.280 I you know, I had some buddies that seemed to 0:04:13.280 --> 0:04:15.640 be getting rich on Wall Street and then I didn't 0:04:15.680 --> 0:04:17.560 really know what they were doing. And one of my 0:04:17.600 --> 0:04:20.520 best friends worked at Sanford Bernstein and and uh, they 0:04:20.520 --> 0:04:23.160 were looking for somebody to write, um, you know, software 0:04:23.279 --> 0:04:26.840 and do analysis called quant research on equities. And I 0:04:26.960 --> 0:04:29.360 interviewed there and I loved it. This bunch of crazy, 0:04:29.360 --> 0:04:32.360 you know, wild people who were brilliant and um, kind 0:04:32.360 --> 0:04:34.120 of a little bit a little bit on the edge 0:04:34.120 --> 0:04:36.320 of being unhinged as human beings. And it was just 0:04:36.400 --> 0:04:39.080 kind of my jam, you know. And so, um, you're 0:04:39.120 --> 0:04:43.080 so buttons up, you don't sound like a crazy but 0:04:43.120 --> 0:04:45.400 it was. It was effort and enthusiasm or just like 0:04:45.400 --> 0:04:48.920 getting the PhD berry, it's basically perseverance one percent intelligence. 0:04:48.960 --> 0:04:50.800 And this was like you get in there and there 0:04:50.880 --> 0:04:54.000 was just no rules, like find something interesting and write 0:04:54.000 --> 0:04:56.359 about it. And so for me, you know, there's this 0:04:56.480 --> 0:04:59.040 database of information on hundreds of stocks and you could 0:04:59.080 --> 0:05:01.240 go in there and analyze as it reached conclusions. Oh way, 0:05:01.240 --> 0:05:03.240 you know along the top market kept name and sure 0:05:03.320 --> 0:05:04.600 these against it or do this or you know, it 0:05:04.680 --> 0:05:06.480 just kind of empirically test everything. And there was a 0:05:06.520 --> 0:05:09.800 bunch of incredibly brilliant people there. So I loved it. Um, 0:05:09.839 --> 0:05:12.320 I loved the environment, and I didn't I didn't even 0:05:12.360 --> 0:05:13.920 know what I was getting into, to be honest with you. 0:05:14.560 --> 0:05:18.440 And then from quant work at Bernstein were you were 0:05:18.440 --> 0:05:20.640 you an analyst and Semmi's there all yeah, so I 0:05:20.640 --> 0:05:22.640 switched to being sem Look at that time, being late 0:05:22.720 --> 0:05:26.440 nineties into the you know TMT bubble, what seemed cool 0:05:26.520 --> 0:05:30.960 to young young Adam Parker was being an analyst. Oh man, 0:05:31.000 --> 0:05:33.960 these tech analysts, they seem that seems like a great job. 0:05:34.000 --> 0:05:36.040 And Bernstein in those days, you know, you were really 0:05:36.040 --> 0:05:37.880 an expert you wrote, you know, a hundred hundred un 0:05:38.040 --> 0:05:40.240 page black book. It was called on an Industry, and 0:05:40.279 --> 0:05:42.080 you you could tear apart the p and ls of 0:05:42.120 --> 0:05:44.600 the companies and you really understood, Um, you know, we 0:05:44.720 --> 0:05:47.520 spend all our time on six to ten stocks, so 0:05:47.600 --> 0:05:50.600 you really knew those companies, that management teams, the things 0:05:50.640 --> 0:05:52.800 that impacted the volatility of the pan l you you 0:05:52.920 --> 0:05:54.640 kind of became an expert. And so I really want 0:05:54.720 --> 0:05:56.440 to do that. And I just got lucky that it 0:05:56.480 --> 0:05:59.320 was semiconductors. Um. I basically just kept going in saying 0:05:59.440 --> 0:06:00.640 I want to do this, I want to do this. 0:06:00.760 --> 0:06:03.520 And the first sector they offered me very was European 0:06:03.600 --> 0:06:07.960 electric utilities. So much fun. Yeah, and I I really 0:06:07.960 --> 0:06:10.240 struggled with how I'm going to communicate to them. I'm 0:06:10.240 --> 0:06:11.960 really on board with the fact that you you you're 0:06:11.960 --> 0:06:14.640 allowing me to be an analyst, but I can't move 0:06:14.720 --> 0:06:16.440 to London. Yeah, that's it. I can't move to London. 0:06:16.480 --> 0:06:18.400 I just I just got engaged or whatever. So I 0:06:18.400 --> 0:06:20.920 I enabled to sort of convince them, yes, thank you, 0:06:20.920 --> 0:06:22.760 I'm an analysts, but no, I'll wait for the first 0:06:22.839 --> 0:06:24.320 US one. And it could have been anything. It could 0:06:24.320 --> 0:06:26.200 have been food it could have been I didn't really care. 0:06:26.240 --> 0:06:28.159 And when Semi get you have you didn't have a 0:06:28.200 --> 0:06:30.480 tech background. I have been engineering because a lot of 0:06:30.520 --> 0:06:36.120 the analysts covering Semi's they're they're electric consigners, executor software design. 0:06:36.320 --> 0:06:39.239 I used to, you know, and and Burnstein's hiring model 0:06:39.279 --> 0:06:41.400 back then was basically get a mckensey guy who was 0:06:41.440 --> 0:06:43.120 an expert on an industry or somebody who worked at 0:06:43.120 --> 0:06:44.840 one of those companies. I was one of the rare 0:06:44.960 --> 0:06:48.440 counter examples of you know, um from within. Yeah, I 0:06:48.520 --> 0:06:50.480 think the PhD and statistics probably helped me. I used 0:06:50.480 --> 0:06:52.440 to just say, look, I'm probably better accounting the chips 0:06:52.520 --> 0:06:54.640 and knowing what they are, you know. And and it 0:06:54.720 --> 0:06:56.520 turned out that in those days would really matter to 0:06:56.520 --> 0:06:59.280 getting the stocks right was sort of a non consensus 0:06:59.360 --> 0:07:01.760 in correct view of the gross margins six months forward, 0:07:01.960 --> 0:07:04.599 and so that didn't really require the expertise on circuit 0:07:04.640 --> 0:07:06.760 design and the like. In fact, you know this, but 0:07:06.880 --> 0:07:09.840 sometimes those the people who work at the companies turned 0:07:09.880 --> 0:07:11.480 out to be not very good at calling the stock 0:07:11.520 --> 0:07:13.160 price of the owned company they worked at, because you 0:07:13.200 --> 0:07:15.200 have all kinds of biases from the people you like, 0:07:15.440 --> 0:07:17.680 and you don't like and that kind of stuff. So, um, 0:07:17.840 --> 0:07:19.800 it worked to my advantage, but I think probably wouldn't 0:07:19.800 --> 0:07:22.200 have happened if I didn't labor through that PhD. So 0:07:22.320 --> 0:07:25.880 how do you get from Bernstein to Morgan Stanley? Yeah? 0:07:25.920 --> 0:07:27.960 So after I did SEMIS for a few years, and 0:07:28.040 --> 0:07:30.440 you know, that's a very competitive, you know business. You 0:07:30.480 --> 0:07:32.400 get up every day and there's a there's a there's 0:07:32.400 --> 0:07:35.120 a person at admiral and a person that you know, uh, 0:07:35.880 --> 0:07:39.680 every there your competitors you want to like just you 0:07:39.760 --> 0:07:41.680 want to make them look stupid on the conference calls, 0:07:41.680 --> 0:07:43.080 and you want to ask the smartest question and you 0:07:43.120 --> 0:07:44.720 want to be number one ranked, right, So you do that, 0:07:44.880 --> 0:07:47.040 and you know very you know, once you get number 0:07:47.040 --> 0:07:48.840 one a few times, all you think about is like, 0:07:48.960 --> 0:07:51.040 am I gonna lose it? There's no joy in repeating 0:07:51.080 --> 0:07:53.120 as number one, There's only the fear of losing it, right, 0:07:53.120 --> 0:07:55.400 because then you're like, wait a minute, Like investors don't 0:07:55.400 --> 0:07:57.120 like me as much as I used to. So you know, 0:07:57.400 --> 0:08:00.960 I felt like I wasn't really incrementally you know, doing 0:08:01.000 --> 0:08:03.560 that again wasn't going to drive me anymore. And um, 0:08:03.800 --> 0:08:06.520 you know I was offered, um, you know, this position 0:08:06.560 --> 0:08:08.440 to run research at Burnstein, and so I transitioned to 0:08:08.480 --> 0:08:09.800 be the director of research for a while, which was 0:08:10.000 --> 0:08:13.560 attracting and retaining, hiring, firing, that kind of stuff. Management position, 0:08:13.680 --> 0:08:15.880 not research got me away from that. But the beautiful 0:08:15.960 --> 0:08:17.520 for a year. But the beautiful part was I then 0:08:17.800 --> 0:08:20.840 was helping other analysts RAMP and so I got to learn, Okay, 0:08:20.840 --> 0:08:23.040 I'm gonna lauch the household products guy, I'm gonna launch 0:08:23.720 --> 0:08:27.440 the capital equipment guy industrial and so in that year 0:08:27.600 --> 0:08:29.440 I was helping kind of four or five analysts RAMP. 0:08:29.480 --> 0:08:31.360 I started realizing like this kind of interesting, I'm kind 0:08:31.360 --> 0:08:32.719 of I can apply what I know with Sammy's and 0:08:32.760 --> 0:08:35.400 helped them. And so early in oh eight, at the 0:08:35.440 --> 0:08:37.800 very beginning of a wait, the strategy and quant research 0:08:37.920 --> 0:08:39.880 job opened up at Burnstein and that's how I transitioned 0:08:39.880 --> 0:08:42.520 to being a little bit more quote unquote macro. So 0:08:42.960 --> 0:08:44.160 I did that for a couple of years, and then 0:08:44.160 --> 0:08:46.079 I transitioned to Morgan Stanley to be the strategist there. 0:08:46.160 --> 0:08:49.280 And for people who may not remember this, in the nineties, 0:08:49.400 --> 0:08:53.959 Bernstein's uh bevy of analysts were top top. So in 0:08:54.000 --> 0:08:56.040 oh seven, when I was a director of research at Burnstein. 0:08:56.200 --> 0:08:59.880 These the data UM Burnstein at twenty three u s 0:09:00.000 --> 0:09:01.920 and also that were publishing eighteen were ranked in the 0:09:02.000 --> 0:09:04.640 top three and eleven were number one. That's unbelievable. So 0:09:04.760 --> 0:09:07.720 it was really a number one machine UM in terms 0:09:07.760 --> 0:09:10.839 of the analysts UM that worked there. And you know, 0:09:10.920 --> 0:09:12.520 I I, you know, was my job was get the 0:09:12.559 --> 0:09:14.600 five that weren't in the top three in the top 0:09:14.679 --> 0:09:16.199 three and hire a few more that will eventually be 0:09:16.720 --> 0:09:18.439 you know, number one in the future, you know. And 0:09:18.640 --> 0:09:19.800 and then that was in the US, and we also 0:09:19.840 --> 0:09:23.199 were building a European business too, So so obvious obvious 0:09:23.360 --> 0:09:28.880 after the fact question. Bernstein was substantial in size, But 0:09:29.040 --> 0:09:32.640 they weren't you know, Gulman, Saxmom Stanley, Merrill, Lynch. What 0:09:32.880 --> 0:09:35.760 was the secret of success? Why were they punching so 0:09:35.960 --> 0:09:38.640 far outside of that weight class? I think they're you know, um, 0:09:38.880 --> 0:09:42.280 it was the it was multiple things. But I'd say, 0:09:42.360 --> 0:09:43.920 you know, you don't have a prime brokerage business, you 0:09:43.960 --> 0:09:46.240 don't have a banking business. So there was this perception 0:09:46.280 --> 0:09:49.400 of independence. You hire people who were you know, generally 0:09:49.480 --> 0:09:51.640 were you know, experts in the industry. I was an exception, 0:09:52.040 --> 0:09:54.480 but there were generally people who were running the Mackenzie 0:09:54.520 --> 0:09:57.120 practice consulting the aerospace companies, and they would be hired 0:09:57.160 --> 0:09:59.120 to cover Boeing or those kind of things. So kind 0:09:59.160 --> 0:10:01.840 of the industry now, and I think the Bye side, 0:10:02.040 --> 0:10:04.319 you know, relied on that is sort of a you know, 0:10:04.440 --> 0:10:07.400 an external voice. When you interview the Bye side, they 0:10:07.480 --> 0:10:09.080 tend to not care if the Cell side are good 0:10:09.080 --> 0:10:11.040 stock pickers or not. They might blame them if they're bad, 0:10:11.360 --> 0:10:13.160 but they're never gonna say I rely on the Cell 0:10:13.240 --> 0:10:15.360 side for their stock selection skills. That's what they're supposed 0:10:15.360 --> 0:10:17.240 to be doing. So I think what helped Bernstein gain 0:10:17.679 --> 0:10:19.800 prominence was the fact that all right, we don't even 0:10:19.920 --> 0:10:21.600 try to do that at an expert level, just try 0:10:21.640 --> 0:10:23.800 to help people be smarter about the investment countries and 0:10:24.120 --> 0:10:28.640 controversies and write detailed, um, you know, sensible issues on 0:10:28.679 --> 0:10:30.480 those investment convers So that that was that was a 0:10:30.480 --> 0:10:33.360 business model, and it really worked back through and at least, 0:10:33.400 --> 0:10:35.640 you know, until maybe ten years ago. So so let 0:10:35.760 --> 0:10:38.000 you raise such a fascinating question I want to ask 0:10:38.040 --> 0:10:43.839 you about. And we're recording this UM late April, after Netflix, 0:10:44.320 --> 0:10:49.480 which had fallen fifty from its October peak UM at 0:10:49.559 --> 0:10:53.880 their earnings call, they announced a decrease in subscribers. The 0:10:53.960 --> 0:10:59.360 stock falls another overnight the next day. There are all 0:10:59.440 --> 0:11:03.640 these down grades from the major cell side shops, cut 0:11:03.760 --> 0:11:06.599 cut to neutral, cut to hold, cut to and it 0:11:06.760 --> 0:11:10.319 raises the question, and I'm sure lay people asked this 0:11:10.480 --> 0:11:12.920 question to themselves all the time. Hey, the stock is 0:11:12.960 --> 0:11:15.480 now down from where you told me to buy it. 0:11:16.320 --> 0:11:20.400 What's the point of this down grade? Thanks for nothing? Yeah, 0:11:20.440 --> 0:11:23.720 I mean the south side um defend the entire analysts 0:11:24.400 --> 0:11:29.000 go okay, yeah, you know. I when I got to 0:11:29.080 --> 0:11:32.199 Morgan Stanley in I'll answer this one. I got in 0:11:32.400 --> 0:11:36.000 the late fall of I wondered if the research department 0:11:36.040 --> 0:11:39.439 there generated any alpha with the recommendations, and so I 0:11:39.559 --> 0:11:42.600 analyzed they had stored data from three to ten. There's 0:11:42.600 --> 0:11:46.040 about thirty five stock recommendations that were kind of stored, 0:11:46.160 --> 0:11:50.280 so you let the statistician loose on the data. And 0:11:50.920 --> 0:11:53.319 about half were overweight rated half were equal underweight. So 0:11:53.360 --> 0:11:55.560 I thought, all right, did the overweights beat the equal underweights? 0:11:56.160 --> 0:11:58.880 Your exact question, I considered, So I didn't stock down 0:11:59.640 --> 0:12:01.240 after mark it, and then they downgradeed. You do not 0:12:01.320 --> 0:12:03.520 give them credit for that being a credit You lack 0:12:03.559 --> 0:12:06.320 it by twenty four hours. You bade an adjusted meaning 0:12:06.400 --> 0:12:08.800 you know, adjustable how much thing to be moved. And 0:12:09.080 --> 0:12:12.320 it turned out, at least for the observations over seven years, 0:12:12.400 --> 0:12:16.400 that they had about four percent average um alpha between 0:12:16.400 --> 0:12:18.839 the overweights and equal underweights. So I published that as 0:12:18.880 --> 0:12:21.320 a bar four So in other words, the stocks they 0:12:21.400 --> 0:12:24.200 liked did four percent they didn't like, And then how 0:12:24.280 --> 0:12:27.480 did it do versus so that basic indexing, Yeah, well 0:12:27.520 --> 0:12:29.160 that was kind of a new market neutral, right, So 0:12:29.280 --> 0:12:31.200 like you overweight longs and your short equal on the weights, 0:12:31.240 --> 0:12:33.319 and then and then I had a quant model that 0:12:33.520 --> 0:12:35.360 you know, the long top pointel beat the bottom by 0:12:35.600 --> 0:12:38.400 nine percent, so I sort of said, look, I think 0:12:38.480 --> 0:12:41.079 quantitative stuff probably you know, is a little bit better 0:12:41.080 --> 0:12:42.959 than fundamental stock. But then the when the last bar 0:12:43.240 --> 0:12:45.719 was thirteen percent, which was if you only bought the 0:12:45.760 --> 0:12:47.880 overweight rated stocks at the model light and you only 0:12:47.960 --> 0:12:50.480 sort of shorted the equal underweights and the model didn't like, 0:12:50.520 --> 0:12:52.599 you get thirteens. The whole point of this was a 0:12:52.720 --> 0:12:57.079 combination of something quantitative and maybe unemotional, combined with the 0:12:57.080 --> 0:12:59.960 fundamentals would be superior to either discipline alone. And actually 0:13:00.000 --> 0:13:02.599 i've spent most of my life since then, you know, 0:13:02.600 --> 0:13:05.640 the last twelve years in that sort of combination sphere. 0:13:06.080 --> 0:13:08.040 So I think I'm trying to defend it by saying, look, 0:13:08.040 --> 0:13:11.160 I think there's some value in it, for sure, but 0:13:11.600 --> 0:13:13.920 there's not value in changing the recommendation after it's happened. 0:13:14.080 --> 0:13:15.640 My own personal opinion on Netflix, And I'm not a 0:13:15.679 --> 0:13:17.960 fundamental analyst there, but I did write about it bury 0:13:18.040 --> 0:13:21.360 it's interesting. Um, I've had two learning lessons of that. 0:13:21.440 --> 0:13:23.880 This one applied to one. When things change, you have 0:13:23.960 --> 0:13:26.040 to admit it, and this one I think has both 0:13:26.080 --> 0:13:28.040 macro and micro changes. I think the macro would be, 0:13:28.480 --> 0:13:30.600 you know, everyone bought too many streaming services during COVID, 0:13:30.640 --> 0:13:32.800 and maybe it doesn't need they're out of their house again, right, 0:13:32.920 --> 0:13:35.000 and so it's reopening and and And the micro is 0:13:35.200 --> 0:13:38.520 they've got to think about pricing and maybe charging people 0:13:38.600 --> 0:13:41.800 to or not charging the inverse for advertisements. So that's 0:13:41.880 --> 0:13:44.480 kind of a business model change. And the other thing 0:13:44.800 --> 0:13:46.280 so maybe you have to say to yourself, well, it's 0:13:46.320 --> 0:13:48.719 not exactly the same fundamentally. Maybe you know, sometimes I 0:13:48.760 --> 0:13:50.960 guess i'd answer your question by saying, sometimes the stocks 0:13:51.000 --> 0:13:54.200 down twenty five but the fundamentals are worse than right 0:13:54.280 --> 0:13:55.920 that maybe not in this case, but I'm saying in aggregate. 0:13:55.960 --> 0:13:58.280 And the second learning lesson I've had from analyzing a 0:13:58.360 --> 0:14:00.600 lot of behavior on the short selling it and running 0:14:00.640 --> 0:14:03.960 my own fund is you make more money shorting stocks 0:14:04.040 --> 0:14:06.920 down from highs than you do add highs. So it's 0:14:07.040 --> 0:14:08.959 very tough to short stock add a high because you're 0:14:09.000 --> 0:14:12.880 fighting positive price momentum. Right, So when the stocks down 0:14:14.040 --> 0:14:15.920 and then you short it, I guarantee you make more 0:14:16.000 --> 0:14:18.439 money shorting stocks down twenty from highs than you do 0:14:18.520 --> 0:14:21.200 at high So it's not necessarily true that Netflix isn't 0:14:21.200 --> 0:14:23.480 a short here um, But I'm not a fundamental an else, 0:14:23.560 --> 0:14:26.200 and in that in that case, I'm not convinced that 0:14:26.800 --> 0:14:28.720 it isn't worse. It's still trades in a hundred times 0:14:28.760 --> 0:14:31.120 forward free cash flow. It's got a high correlation to 0:14:31.600 --> 0:14:33.760 low quality and work from home. It's got a high 0:14:33.800 --> 0:14:37.080 correlation to negative correlation to inflation. So I don't have growth. 0:14:37.320 --> 0:14:39.520 You know stocks like that are gonna work, so you 0:14:39.560 --> 0:14:41.680 know I don't. I don't know the fundamentals. And one 0:14:41.760 --> 0:14:44.280 of one of my favorite things about having you who 0:14:44.400 --> 0:14:48.160 is an independent research shop instead of a cell side analyst. 0:14:48.520 --> 0:14:50.640 I'm not getting a phone call tomorrow from the PR 0:14:50.720 --> 0:14:54.520 person begging me to take everything Adam said out about Netflix. 0:14:54.720 --> 0:14:57.960 Can't he can't talk about you can talk. You'd go anywhere. 0:14:58.000 --> 0:15:00.760 You could talk about anything that's right without friction. So 0:15:01.160 --> 0:15:05.120 that leads to another question. How freeing is that that 0:15:05.280 --> 0:15:08.360 you can actually say what's on your mind and you're 0:15:08.400 --> 0:15:13.040 not thinking about what Obviously legal is important, but sometimes 0:15:13.120 --> 0:15:17.200 compliance gets a little over enthusiastic, and PR even more stuff. 0:15:17.200 --> 0:15:19.560 I would say, you know, I should look this up. 0:15:19.640 --> 0:15:23.280 So this this is an exaggeration, but I would say 0:15:24.000 --> 0:15:27.240 I would say maybe ten years ago when I worked 0:15:27.280 --> 0:15:30.040 at Morgan Stanley, Um, I think there was fifty thousand 0:15:30.040 --> 0:15:32.720 employees and ten thousand legal and compliance in ten thousand 0:15:32.760 --> 0:15:37.520 and I t so that those are some but that's 0:15:37.560 --> 0:15:40.200 something like that. So look, these are amazing firms, and 0:15:40.200 --> 0:15:42.120 morganize an incredible firm with great people and a lot 0:15:42.160 --> 0:15:43.720 of whom are closest. But what I'd say is that 0:15:43.840 --> 0:15:46.200 there's positive and negative. The big firms have bigness disease, 0:15:46.280 --> 0:15:49.160 and the taxes on your time become substantial. Right, you know, 0:15:49.240 --> 0:15:52.480 you need a bunch of videos to money laundering and 0:15:52.520 --> 0:15:53.800 a bunch of you know, every firm has this, you 0:15:53.840 --> 0:15:56.040 know that you know, compliance stuff. You've got a bunch 0:15:56.120 --> 0:15:58.960 of three sixty feedback M D and E D promotion, 0:15:59.080 --> 0:16:01.600 the E S G diversity and include the number of 0:16:01.680 --> 0:16:04.400 things you have to do just time taxes, time taxes. 0:16:04.560 --> 0:16:06.440 It's a huge tax. And so for me, you know, 0:16:06.520 --> 0:16:08.240 it's very freeing. We're not a broken deal or our 0:16:08.280 --> 0:16:10.560 whole job is to write you know, interesting research that 0:16:10.600 --> 0:16:13.320 makes people think. We sell data. We you know, create baskets. 0:16:13.360 --> 0:16:15.200 We do a lot of outsource sort of chief chief 0:16:15.320 --> 0:16:18.200 risk officer or work where people we signed onto sculture agreements. 0:16:18.240 --> 0:16:20.400 People send us their portfolios and we we kind of 0:16:20.440 --> 0:16:22.240 analyze them and try to give them some interesting thoughts 0:16:22.240 --> 0:16:24.920 about it that aren't in you know, axioma or you know, 0:16:25.040 --> 0:16:27.480 things they can get from other other vendors. So, um, 0:16:27.840 --> 0:16:30.120 it's really freeing. It's it's really freeing. But you know, 0:16:30.240 --> 0:16:32.560 you know you don't have the resources. Um, you don't 0:16:32.600 --> 0:16:34.480 get the first class to uh, you know, you know 0:16:34.600 --> 0:16:38.320 Beijing either, So there's some positive negatives. Wit you're flying commercial, 0:16:39.560 --> 0:16:43.760 Come on, I always always fly commercial, man, So let's 0:16:43.800 --> 0:16:46.720 talk semis they've been driving everything from the shortage of 0:16:46.760 --> 0:16:51.640 automobiles to inflation. Give us the broad overview from your perspective. Yeah, well, 0:16:51.960 --> 0:16:53.760 you know, one of the things that is tricky when 0:16:53.760 --> 0:16:57.080 your investor barri is you know what what a cyclical 0:16:57.200 --> 0:16:59.880 and what's structural, and you know you can confuse yourself 0:17:00.000 --> 0:17:01.720 when something sicklal when you think it isn't, and when 0:17:01.760 --> 0:17:05.160 the periodicity changes, and those kind of things. So uh love, 0:17:05.240 --> 0:17:09.720 I love all this math talking amplitude. Pity, I'm so excited. 0:17:09.800 --> 0:17:12.879 I'm back back in college. You know. I think what 0:17:13.000 --> 0:17:14.600 you said is right though, that there are kind of 0:17:14.640 --> 0:17:18.040 an important barometer um for a lot of broader issues. 0:17:18.119 --> 0:17:20.080 The two things that I'm tracking right now really carefully 0:17:20.119 --> 0:17:23.360 are a concept called book to bill, which is sort 0:17:23.359 --> 0:17:25.399 of how much revenue did you ship out versus what 0:17:25.520 --> 0:17:28.280 is your order flow look like? And is the order 0:17:28.400 --> 0:17:30.760 high order flow higher than you shipped out? Book to 0:17:30.800 --> 0:17:33.640 bill ratio generally that's still above one for most semi 0:17:33.680 --> 0:17:36.200 conductor companies, meaning future demand looks a little bit better 0:17:36.240 --> 0:17:38.760 than trailing demand. But that book to bill ratio has 0:17:38.800 --> 0:17:41.480 come down from maybe one point one five to one 0:17:41.520 --> 0:17:43.679 point eight to one point oh six so down due 0:17:43.720 --> 0:17:46.240 to the supply as we finally get you know, supply 0:17:46.480 --> 0:17:49.879 catching up, you know, post covid um. So you I 0:17:49.960 --> 0:17:51.720 think when that if you think about it, it's a 0:17:51.760 --> 0:17:53.320 weird way to think about it, but there's probably one 0:17:53.359 --> 0:17:56.359 second where production equals consumption and then you're either about 0:17:56.400 --> 0:17:58.600 to start overproducing consumption or you know you're about to 0:17:58.600 --> 0:18:01.000 start underproducing. So I think will get to equilibrium in 0:18:01.000 --> 0:18:02.880 the second half of this year in really most parts 0:18:02.920 --> 0:18:05.159 of the semi conductors. Wow, that's that would be a 0:18:05.320 --> 0:18:11.080 huge huge windfall fort by cars. Yeah, I think that's right. 0:18:11.119 --> 0:18:13.440 And I think the second thing that's important related to 0:18:13.520 --> 0:18:15.880 this is backlog. So you know, one of the things 0:18:15.920 --> 0:18:18.840 that I think Bernstein was good about and is making 0:18:18.880 --> 0:18:20.760 you think like you're the CEO as an analyst, so 0:18:20.880 --> 0:18:23.760 think like your CEO, you know, stepping you know, kind 0:18:23.760 --> 0:18:26.320 of stepping to the thought process that you're running the company. 0:18:26.440 --> 0:18:29.280 So if you're the CEO of any industrial company, auto 0:18:30.800 --> 0:18:34.200 home appliance, any real business, you've had trouble selling product 0:18:34.400 --> 0:18:36.080 in the last eighteen months because you couldn't get the 0:18:36.080 --> 0:18:38.359 supplies you need. So you go to your procurement officer 0:18:38.440 --> 0:18:42.400 and you say, yo, how about stop bottlenecking my final revenue. 0:18:42.680 --> 0:18:44.080 So what does that person do. It calls a semi 0:18:44.080 --> 0:18:46.480 conductor supply chain. It says, I want two million eighteen 0:18:46.520 --> 0:18:48.320 months from now, I want two million twelve months from now, 0:18:48.400 --> 0:18:49.800 and by the way, I want to hundred million twenty 0:18:49.840 --> 0:18:51.680 four months from now. And you start piling on the 0:18:51.760 --> 0:18:54.560 backlog so that they know, hey, I'm gonna be there, 0:18:54.600 --> 0:18:56.359 gonna be there for a while, ramp it up, right, 0:18:56.400 --> 0:18:59.160 And so that has some interesting contagion in the economy, 0:18:59.280 --> 0:19:02.600 right because these guys start planning their back law back um, 0:19:02.680 --> 0:19:04.879 you know, their capacity as if that backlog is going 0:19:04.920 --> 0:19:06.880 to be there. One of the very weird parts about 0:19:06.880 --> 0:19:09.120