WEBVTT - Understanding Hyperscalers: Masters in Business with Ankur Crawford 0:00:02.520 --> 0:00:07.040 Bloomberg Audio Studios, Podcasts, Radio News. 0:00:08.119 --> 0:00:11.600 This week on the podcast another extra special guest, Doctor 0:00:11.800 --> 0:00:16.560 Encore Crawford is cohed, a portfolio manager of large cap 0:00:16.640 --> 0:00:20.880 strategies at Alger. She's got a fascinating background. She was 0:00:20.920 --> 0:00:26.040 an engineer at Intel, one a number of patents, and 0:00:26.239 --> 0:00:29.840 was the awardy of the Intel PhD Fellowship. She's been 0:00:29.880 --> 0:00:33.320 recognized as one of the top women in asset management. 0:00:34.040 --> 0:00:38.320 If you're interested all into the details of how artificial intelligence, 0:00:38.680 --> 0:00:43.320 semiconductors and software works, as i am, you're gonna find 0:00:43.320 --> 0:00:47.200 this to be a fascinating conversation with no further ado. 0:00:47.520 --> 0:01:02.880 My conversation with Algers Encore Crawford. I'm Core Crawford. Welcome 0:01:02.960 --> 0:01:03.600 to Bloomberg. 0:01:03.880 --> 0:01:06.640 Thank you for having me. Very so, let's. 0:01:06.400 --> 0:01:09.160 Start with your background, which is really kind of fascinating. 0:01:09.720 --> 0:01:14.760 Bachelor's degree in mechanical engineering and material science and engineering. 0:01:15.160 --> 0:01:19.040 That's a double BS from UC Berkeley, and then a 0:01:19.160 --> 0:01:24.800 master's and a PhD in material science and engineering at Stanford. 0:01:25.000 --> 0:01:26.720 What was the original career plan. 0:01:27.640 --> 0:01:30.200 I didn't have one, to be honest. 0:01:31.240 --> 0:01:33.800 I think when I made the decision to become a 0:01:33.840 --> 0:01:37.280 mechanical engineer, I was kind of following my brother's footsteps, 0:01:37.280 --> 0:01:40.200 who was a mechanical engineer and became an orthopedic surgeon. 0:01:40.800 --> 0:01:43.000 And I realized, if I didn't know what I wanted 0:01:43.000 --> 0:01:45.759 to do, I wanted to keep my options open. 0:01:46.880 --> 0:01:51.920 So he becomes an orthopedic surgeon with a mechanical engineering degree. 0:01:51.960 --> 0:01:55.440 Is he designing replacement joints and things like that. 0:01:55.560 --> 0:01:56.040 He does. 0:01:56.080 --> 0:01:59.680 He does actually bring that aspect of his engineering background 0:01:59.840 --> 0:02:04.320 in to device different device configurations, and he works a 0:02:04.360 --> 0:02:09.400 lot with the device companies as well. But there's also 0:02:09.800 --> 0:02:12.960 you know, as a kid, I loved, you know, figuring 0:02:13.040 --> 0:02:16.160 how figuring out how things work, whether it was like 0:02:16.240 --> 0:02:18.840 a car or a calculator, and I would always be 0:02:19.000 --> 0:02:23.119 kind of fidgeting to understand how things work. I loved building, 0:02:23.760 --> 0:02:28.679 so mechanical engineering kind of felt like, you know, I'm 0:02:28.760 --> 0:02:32.520 just a curious person. So I like to satiate that 0:02:32.639 --> 0:02:34.080 need to know how things work. 0:02:34.440 --> 0:02:37.400 And I read somewhere that you originally wanted to be 0:02:37.440 --> 0:02:38.400 an astronauts. 0:02:38.440 --> 0:02:41.919 This correct did. So I grew up till I was five. 0:02:42.040 --> 0:02:47.320 We lived in Florida close to Cape Canaveral, and we 0:02:47.360 --> 0:02:51.520 would go watch the Space Shuttle take off and I 0:02:51.639 --> 0:02:57.559 was so fascinated by space because it was almost ethereal, 0:02:58.080 --> 0:03:00.640 you know, this thing goes up into the sky. And 0:03:01.880 --> 0:03:06.280 for me, the astronauts were celebrities. So you know, for 0:03:06.320 --> 0:03:08.120 a long time I did want to be an astronaut. 0:03:08.240 --> 0:03:12.399 So I have Florida somewhere in between. You're born in Kansas, 0:03:12.480 --> 0:03:13.160 is this correct? 0:03:13.280 --> 0:03:13.520 Yes? 0:03:13.720 --> 0:03:17.160 Yeah, canvas, but you end up in the Middle East, yes, 0:03:17.720 --> 0:03:21.720 and then you're sent to a convent boarding school in 0:03:21.760 --> 0:03:27.440 the Himalayas. This is possibly right, right, No, that is 0:03:27.480 --> 0:03:30.160 all correct, and then you end up in Buffalo, New York. 0:03:31.120 --> 0:03:34.760 You got it all right. So so that's real human research, 0:03:34.920 --> 0:03:40.080 not not chat. I'm curious that is a broad global 0:03:41.120 --> 0:03:45.320 life experience. How does that shape your views on either 0:03:46.000 --> 0:03:49.280 international investing or just the concept of risk and reward? 0:03:49.880 --> 0:03:53.280 Yeah, I think it more so shapes the way I 0:03:53.320 --> 0:03:58.320 think about, you know, the cultural differences. When I look 0:03:58.360 --> 0:04:03.360 at companies, when I look at manage teams, I understand 0:04:03.520 --> 0:04:07.560 very well that there are certain cultural differences that are 0:04:07.640 --> 0:04:14.800 simply endemic to businesses and to management teams. And you know, 0:04:14.920 --> 0:04:19.560 just because a management team isn't necessarily always bullish or 0:04:19.600 --> 0:04:23.680 they're always telling you the negative aspect of their company 0:04:24.080 --> 0:04:27.599 doesn't necessarily mean that there's something wrong, and. 0:04:29.480 --> 0:04:32.040 So, you know, I think that that has. 0:04:31.920 --> 0:04:34.960 Been like an example of this is this company called Nebeus, 0:04:35.600 --> 0:04:40.039 where the CEO is a Russian CEO who is incredibly 0:04:40.120 --> 0:04:43.520 humble and he will never tell you what's right. He 0:04:43.600 --> 0:04:45.479 will always point out to you all the things that 0:04:45.520 --> 0:04:47.920 are wrong. And a lot of investors are like, you know, 0:04:48.040 --> 0:04:51.440 I don't that doesn't sound good, And I'm kind of 0:04:51.440 --> 0:04:54.240 looking at the opportunity because that's just his culture, right, 0:04:54.279 --> 0:04:55.320 It's his culture. 0:04:55.040 --> 0:04:55.919 Not to be boastful. 0:04:57.160 --> 0:05:00.360 So just living in all these different countries and having 0:05:00.440 --> 0:05:04.320 exposure as a kid to many different religions, it just 0:05:04.360 --> 0:05:08.920 gives a really unique perspective on any problem that you 0:05:08.960 --> 0:05:12.840 look at because it helps take kind of the blinders off. 0:05:13.720 --> 0:05:18.000 It's fascinating. I never really thought about how does a 0:05:18.040 --> 0:05:21.839 societal cultural set of norms make its way to management. 0:05:22.480 --> 0:05:25.800 You think about the Japanese culture is the sort of 0:05:27.120 --> 0:05:32.080 bravado and very aggressive forecast we tend to see in 0:05:32.120 --> 0:05:34.960 the United States, You would never see anything like that 0:05:35.080 --> 0:05:43.880 in Japan. How do you calibrate what is cultural diffidence 0:05:44.040 --> 0:05:46.839 and what is just hey, there's a problem here and 0:05:46.880 --> 0:05:48.719 they're telling us this is an issue. 0:05:49.000 --> 0:05:51.520 Yeah, you know, I think you have to know the 0:05:51.560 --> 0:05:55.600 business right that the first thing is is know the business, 0:05:55.760 --> 0:05:58.280 and then you can calibrate the tone of the management. 0:05:58.800 --> 0:06:03.200 And you know, example, as Taiwan Semiconductor, I remember speaking 0:06:03.200 --> 0:06:05.719 to them over many of these years that we've owned 0:06:05.720 --> 0:06:08.480 the stock, and I would always say, you guys are 0:06:08.520 --> 0:06:12.520 going to become the single supplier of leading edge. Why 0:06:12.640 --> 0:06:15.080 is it that you can't take up pricing? And you 0:06:15.120 --> 0:06:18.080 would always talk me down and like, oh, no, you know, 0:06:18.320 --> 0:06:21.640 we are here to serve our customer. We are here 0:06:21.680 --> 0:06:24.919 to and I was like, there's absolutely no reason for 0:06:24.960 --> 0:06:28.039 you not to be raising pricing, and they would just 0:06:28.160 --> 0:06:32.359 push back and not really because that wasn't part of 0:06:32.360 --> 0:06:35.320 their philosophy, and it wasn't part of their philosophy that 0:06:35.400 --> 0:06:38.159 Morris had Morris Chang had kind of put into place 0:06:38.200 --> 0:06:43.680 in the early years. However, that is what they ended 0:06:43.760 --> 0:06:45.960 up doing, and so I had to take that with 0:06:46.040 --> 0:06:48.680 a grain of salt, understanding that's their philosophy. It was 0:06:48.720 --> 0:06:52.760 a little frustrating at the time, but you know that 0:06:52.960 --> 0:06:57.080 a business is a business, and at some point the 0:06:57.160 --> 0:07:01.159 realization of how good that business was came into the numbers. 0:07:01.720 --> 0:07:05.360 So you mentioned the advantage of really understanding the business. 0:07:06.000 --> 0:07:08.920 You're in an Intel doctorate fellow, you worked as an 0:07:08.920 --> 0:07:13.920 engineer at Intel, you hold multiple patents. How much of 0:07:13.920 --> 0:07:18.200 an advantage is that when you're looking at semiconductors or 0:07:18.280 --> 0:07:22.720 AI or any of the hyperscalers. What advantage does that 0:07:22.800 --> 0:07:23.120 give you? 0:07:24.960 --> 0:07:29.400 Look, I think understanding the technology is it's kind of 0:07:29.440 --> 0:07:34.160 crucial right now because in this world of AI, I 0:07:34.200 --> 0:07:37.080 think there's a lot of people who don't really understand 0:07:37.120 --> 0:07:42.200 what is happening under the covers, and that's dangerous. And 0:07:42.240 --> 0:07:45.280 that's why you also see the volatility that you see today, 0:07:46.200 --> 0:07:50.520 because you know they're kind of loose holders and not 0:07:50.560 --> 0:07:54.560 truly understanding the different dynamics of the technology. 0:07:55.240 --> 0:07:58.280 And it's just a hard it's a hard. 0:07:58.040 --> 0:08:00.560 Way to invest when you can get shaken out because 0:08:00.560 --> 0:08:04.720 you don't have conviction in the technologies. So it's I 0:08:04.720 --> 0:08:08.440 feel like it's always helped, and in part because you 0:08:08.480 --> 0:08:11.040 know chips. I was a semiconductor analyst when I first 0:08:11.040 --> 0:08:16.120 started at alger and I kind of immediately understood, well, 0:08:16.520 --> 0:08:18.440 I understand what a deposition tool is. 0:08:18.840 --> 0:08:19.680 You know, I used one. 0:08:19.760 --> 0:08:22.400 I understand what etching is I used this tool, I 0:08:22.480 --> 0:08:27.560 understand what the issues are in fabricating a chip, and 0:08:27.760 --> 0:08:31.040 you know how hard it is to fabricate a chip, 0:08:31.560 --> 0:08:34.520 so you know, it just gives you a little bit 0:08:34.600 --> 0:08:39.600 of a edge on the conceptual understanding and where the 0:08:39.679 --> 0:08:42.800 industry is going, so you know early I remember in 0:08:42.800 --> 0:08:45.840 twenty thirty, eleven, twelve or thirteen, one of those years, 0:08:46.160 --> 0:08:49.120 I put together a presentation about how we're at the 0:08:49.240 --> 0:08:52.960 end of Moore's Law and what will happen if we're 0:08:53.000 --> 0:08:54.400 at the end of Moore's law. And I sent the 0:08:54.400 --> 0:08:57.320 presentation out to all of the companies that I covered, 0:08:57.360 --> 0:09:00.480 and I said, I would like your feedback and tell 0:09:00.520 --> 0:09:01.440 me why I'm wrong. 0:09:02.240 --> 0:09:04.920 But that was thinking kind of eight nine. 0:09:04.800 --> 0:09:08.960 Years ahead because it had implications for the entire sector. 0:09:09.600 --> 0:09:12.760 And so those kinds of insights I think are easier, 0:09:13.080 --> 0:09:16.040 not that any everyone can have them, they just come 0:09:16.120 --> 0:09:18.800 probably a little easier because I understand the technology. 0:09:19.160 --> 0:09:24.520 So I see the advantage of having the technical background 0:09:24.720 --> 0:09:29.320 as an analyst. I'm curious what made you leave the 0:09:29.400 --> 0:09:34.760 technical field being an engineer and working with Semis to 0:09:34.800 --> 0:09:37.560 becoming an analyst in the space and working on the 0:09:37.600 --> 0:09:39.000 financing of semis. 0:09:39.480 --> 0:09:46.280 Yeah, you know, I had gone through my graduate career 0:09:46.559 --> 0:09:49.200 and really I had set some goals for myself. I 0:09:49.200 --> 0:09:52.920 want to write this many papers, I want to you know, present, 0:09:53.120 --> 0:09:54.360 I want you know, I want. 0:09:54.200 --> 0:09:55.520 To be useful to society. 0:09:56.400 --> 0:09:58.480 And at the end of it, I felt like I 0:09:58.480 --> 0:10:03.160 had kind of achieved all those but I wasn't happy. 0:10:04.360 --> 0:10:07.880 I just wasn't content and happy. And I thought to myself, 0:10:07.960 --> 0:10:10.160 my gosh, if I have achieved everything that I set 0:10:10.160 --> 0:10:13.320 out to do and yet I'm still not happy. What 0:10:13.480 --> 0:10:17.440 happens if I become a professor and i'm you know, 0:10:17.640 --> 0:10:20.520 and we just go through a tough spot on you know, 0:10:21.000 --> 0:10:24.560 raising money or whatever it might be like in the research, 0:10:27.320 --> 0:10:30.720 Will I be able to Will I be even unhappier? 0:10:31.400 --> 0:10:34.040 And I think that self awareness made me realize I 0:10:34.120 --> 0:10:36.640 needed to go look somewhere else. And when I came 0:10:36.679 --> 0:10:39.520 to alger it was really like I was thinking I'd 0:10:39.559 --> 0:10:41.880 be here for two years and then go back and 0:10:41.920 --> 0:10:45.880 do a postdoc somewhere and be a professor, and I 0:10:45.920 --> 0:10:46.440 never left. 0:10:46.679 --> 0:10:49.960 Huh, really really interesting. One of the complaints I've heard 0:10:50.000 --> 0:10:54.080 from people who are technologists or engineers or what have you, 0:10:54.240 --> 0:10:59.319 is everything has become so increasingly specialized and narrow that 0:10:59.400 --> 0:11:01.840 you get put in to a silo, you have no 0:11:01.960 --> 0:11:06.160 idea what's going on in any of the adjacent science 0:11:06.280 --> 0:11:09.280 is more or less even within your field, everybody gets 0:11:09.320 --> 0:11:10.080 too specific. 0:11:10.600 --> 0:11:13.040 Was that a concern, Oh, for sure, And that's a 0:11:13.040 --> 0:11:15.960 great insight it is. Actually, you know, I was in 0:11:16.000 --> 0:11:18.319 a room this is probably at you know, fifteen by 0:11:18.320 --> 0:11:21.560 fifteen room. I spent you know, three and a half 0:11:21.640 --> 0:11:25.480 years in the basement of a building at Stanford taking care. 0:11:25.320 --> 0:11:27.120 Of a tool that was about this big. 0:11:27.640 --> 0:11:31.559 I was the plumber and the electrician and carrying out 0:11:31.600 --> 0:11:33.040 cryopumps and fixing them. 0:11:33.520 --> 0:11:37.280 And it was a very narrow, lonely. 0:11:37.040 --> 0:11:40.000 Experience I can imagine. 0:11:39.880 --> 0:11:43.640 And my advisor was fantastic, but you know, just that 0:11:43.800 --> 0:11:48.200 process required. It was very narrow and I'm very proud 0:11:48.240 --> 0:11:51.920 of the work that we did, but it was very, 0:11:52.040 --> 0:11:53.480 very niche. 0:11:53.720 --> 0:11:57.079 So you moved from a field governed by the laws 0:11:57.120 --> 0:12:02.000 of physics and nature to another field kind of governed 0:12:02.040 --> 0:12:06.640 by the eccentricities of human behavior. What are the challenges 0:12:06.640 --> 0:12:07.719 in that transition? 0:12:10.880 --> 0:12:16.600 You know, I don't really I didn't know anything when 0:12:16.600 --> 0:12:18.959 I started in this business. I knew a lot about 0:12:18.960 --> 0:12:23.560 atoms and materials and magnets and how to how to 0:12:23.640 --> 0:12:27.920 make a chip. But I really didn't know very much 0:12:27.960 --> 0:12:35.400 about investing, so honestly it was all new to me. 0:12:36.280 --> 0:12:40.320 So the challenge was really understanding like it. I was 0:12:40.360 --> 0:12:44.080 always asking why, well, why does this happen? Or why 0:12:44.120 --> 0:12:45.720 does the stock go up on this? Or why does 0:12:45.760 --> 0:12:50.240 stock not go up on this? And understanding that human 0:12:50.320 --> 0:12:56.839 behavior aspect was more a fascination versus a challenge because 0:12:57.120 --> 0:13:02.240 this idea of expectations versus the truth. You know, I 0:13:02.520 --> 0:13:04.600 grew up in a world where there is a single 0:13:04.679 --> 0:13:09.440 answer right where you write an equation and there is 0:13:09.480 --> 0:13:14.559 a way to do it, versus you know, people can 0:13:14.640 --> 0:13:17.440 skin the cat in so many different ways. In what 0:13:17.480 --> 0:13:20.320 we do, you can get to the same result in 0:13:21.000 --> 0:13:26.360 you know, an infinite number of ways. But so that 0:13:26.520 --> 0:13:30.080 was I suppose that was the challenge of understanding that 0:13:30.120 --> 0:13:34.440 there isn't just one way of doing it, but perhaps 0:13:34.480 --> 0:13:38.040 you have to understand the different ways than adopt your 0:13:38.040 --> 0:13:40.959 own way of approaching the problem. 0:13:41.559 --> 0:13:44.480 I love the Richard Feynman quote, imagine how much harder 0:13:44.520 --> 0:13:49.680 physics would be if electrons had feelings. It always always 0:13:49.720 --> 0:13:54.960 cracks me up at the intersection of science and investing. 0:13:56.800 --> 0:14:04.000 So you answer a recruiting ad from Alger despite knowing 0:14:04.120 --> 0:14:09.440 nothing about investing. What made you think your skills might 0:14:09.480 --> 0:14:12.840 get you through the door at a shop like Alger. 0:14:13.000 --> 0:14:16.920 I didn't, really, I really didn't. I was reading a book. 0:14:17.000 --> 0:14:19.640 It was written by a bunch of Mackenzie consultants at 0:14:19.640 --> 0:14:22.560 the time, and I forgot the name of the book, 0:14:22.600 --> 0:14:26.000 but it was all about you know, profit and loss 0:14:26.040 --> 0:14:32.840 and just businesses, how businesses are run. And I really 0:14:32.920 --> 0:14:36.440 didn't know, honestly, Berry, what I was applying for. I 0:14:36.520 --> 0:14:40.840 knew that I needed to do something else. I had 0:14:40.880 --> 0:14:43.400 worked at Merrill Lynch for a summer before I had 0:14:43.400 --> 0:14:46.480 started graduate school, and I loved it. It was on 0:14:46.880 --> 0:14:50.800 like kind of the emerging markets debt desk, and. 0:14:52.080 --> 0:14:53.680 I was like, let me give this a go again. 0:14:54.600 --> 0:14:57.360 And when I applied to Alger, I knew that I 0:14:57.440 --> 0:15:01.920 was curious enough that I would be able to cross 0:15:01.960 --> 0:15:05.280 the chasm and I would be able to you know, 0:15:05.400 --> 0:15:07.080 learn and give back to our company. 0:15:07.920 --> 0:15:08.200 Huh. 0:15:08.200 --> 0:15:09.720 Really, really, I really did know. 0:15:10.920 --> 0:15:14.280 Well, that's really fascinating. We'll explore that more coming up. 0:15:14.320 --> 0:15:19.320 We continue our conversation with Encore Crawford CopM of the 0:15:19.440 --> 0:15:24.280 Large Cap Strategy at Alger and PM of the Concentrated 0:15:24.320 --> 0:15:30.840 Portfolio ETF. Talking about her career at Alger. I'm Barry Results. 0:15:30.880 --> 0:15:35.480 You're listening to Masters in Business on Bloomberg Radio. I'm 0:15:35.520 --> 0:15:39.520 Barry Ridults. You're listening to Masters in Business on Bloomberg Radio. 0:15:39.960 --> 0:15:43.240 My extra special guest this week is doctor OnCore Crawford. 0:15:43.720 --> 0:15:48.720 She is portfolio manager at Alger, where she copms the 0:15:48.840 --> 0:15:55.400 large Capital Appreciation strategy as well as running the Concentrated ETF. 0:15:56.200 --> 0:16:00.160 So we were talking earlier about you answered an and 0:16:01.840 --> 0:16:06.000 that Alger had had put up to hire people. I 0:16:06.080 --> 0:16:10.840 read a story that Alger's CEO, Dan Chung hired you 0:16:11.000 --> 0:16:13.880 right on the spot. That's kind of unusual in this space. 0:16:14.280 --> 0:16:16.080 Tell us about what happened there. 0:16:17.360 --> 0:16:20.680 It was funny. I actually walked into this meeting. I 0:16:20.720 --> 0:16:23.280 had just come back from Tahoe. I'm a big skier, 0:16:23.720 --> 0:16:26.720 and I was really frustrated because it was pouring outside 0:16:27.280 --> 0:16:32.440 and I walked in like drenched and really like upset, 0:16:32.480 --> 0:16:34.160 and I was like, the only good thing about this 0:16:34.320 --> 0:16:36.760 is that it's snowing in Tahoe. 0:16:37.480 --> 0:16:39.040 And Dan happens to be a skier. 0:16:39.240 --> 0:16:42.600 I didn't know that, and so we started this conversation 0:16:42.760 --> 0:16:47.880 talking about, you know, our mutual love of skiing. After that, 0:16:48.040 --> 0:16:50.200 I think he realized I didn't know very much at 0:16:50.240 --> 0:16:54.800 all about investing, and he asked me my opinion of 0:16:54.840 --> 0:16:55.800 Intel versus AMD. 0:16:57.280 --> 0:16:59.880 And this was two thousand and three, two thousand. 0:16:59.600 --> 0:17:02.040 And four and peak Intel. 0:17:02.360 --> 0:17:03.320 It was peak Intel. 0:17:03.520 --> 0:17:06.160 And I remember saying, you know, I worked at Intel, 0:17:07.000 --> 0:17:10.639 and you know, I think I prefer AMD versus Intel 0:17:10.720 --> 0:17:13.040 because this is you know, kind of what I'm seeing 0:17:13.040 --> 0:17:16.720 inside of Intel, not inside information, but more the culture 0:17:17.240 --> 0:17:22.240 that had developed. And we had this long discussion about it. 0:17:22.680 --> 0:17:26.680 That evening, they hosted a a kind of a get 0:17:26.720 --> 0:17:31.359 together for all of the applicants, and Dan and I 0:17:31.400 --> 0:17:38.000 got into an argument about nanded versus hard dist drives and. 0:17:37.800 --> 0:17:39.360 You were on the nan side, right. 0:17:39.920 --> 0:17:42.080 Well, he was telling me that all hard to strives 0:17:42.160 --> 0:17:44.119 were going to go to zero. 0:17:44.600 --> 0:17:45.960 And he was eventually right. 0:17:45.880 --> 0:17:47.880 And he will be eventually right. And you know what's 0:17:47.920 --> 0:17:50.760 so funny. I just had this discussion with him yesterday. 0:17:52.000 --> 0:17:54.520 I was like, Dan, we had this discussion twenty two 0:17:54.560 --> 0:17:55.000 years ago. 0:17:55.480 --> 0:17:57.840 It only took you two decades to be right. You know, 0:17:58.040 --> 0:18:01.000 in trading is the same as wrong. 0:18:01.560 --> 0:18:04.479 Well, it was great because we had this Really it 0:18:04.520 --> 0:18:08.200 wasn't it wasn't a heated conversation, but it was definitely 0:18:08.640 --> 0:18:12.040 kind of looking at this problem in two different ways. 0:18:13.080 --> 0:18:16.080 And as we were walking out, he was like, you're hired. 0:18:16.160 --> 0:18:18.520 Just like that, Just like that. I need someone who's 0:18:18.720 --> 0:18:20.639 not afraid of me, will stand up and make me 0:18:20.760 --> 0:18:23.920 think of this problem from multiple angles. 0:18:24.119 --> 0:18:27.640 Well, I think it's a little bit of the culture 0:18:27.680 --> 0:18:31.159 that we have at ALGA of it's always better to 0:18:31.240 --> 0:18:35.600 have different perspectives versus go along with the norm and 0:18:35.680 --> 0:18:42.159 be consensus, and to always encourage that debate. So, you know, 0:18:42.440 --> 0:18:46.240 and one thing I am for sure is especially because 0:18:46.440 --> 0:18:49.360 again I come from a place of we're always trying 0:18:49.400 --> 0:18:50.080 to find the truth. 0:18:50.119 --> 0:18:51.120 There is an answer. 0:18:51.920 --> 0:18:54.080 I do bring that to the table here too, and 0:18:54.160 --> 0:18:57.439 that there is an answer, right whether or not you 0:18:57.480 --> 0:19:00.880 look at it from one angle versus the other. There 0:19:01.040 --> 0:19:03.840 is an answer, like the earnings are the answer, the 0:19:03.880 --> 0:19:07.960 trajectory of earnings are the answer, and getting that right 0:19:08.800 --> 0:19:10.760 is you know, it can be a topic of debate 0:19:10.760 --> 0:19:13.240 and how you get there. We can debate it to 0:19:13.359 --> 0:19:14.840 make sure that we're getting to the truth. 0:19:15.480 --> 0:19:19.800 So you start in the analyst training program at alger 0:19:20.400 --> 0:19:24.960 you advance to a research associate, then an analyst, and 0:19:25.080 --> 0:19:29.720 a tech sector head and ultimately a portfolio manager. What 0:19:29.960 --> 0:19:32.840 transition was the most challenging? What changed the way you 0:19:33.000 --> 0:19:34.520 thought about the job. 0:19:37.000 --> 0:19:41.359 I would say that the transition from kind of being 0:19:41.400 --> 0:19:45.359 an analyst to a portfolio manager, and even as a 0:19:45.720 --> 0:19:48.879 tech sector head, it was I kind of had my 0:19:49.040 --> 0:19:56.560 fingers in everything, and I was my little OCD tendencies 0:19:56.960 --> 0:20:02.680 were still able to play out a little bit. That 0:20:02.720 --> 0:20:07.080 transition to portfolio manager, however, required a different skill set, 0:20:07.760 --> 0:20:12.480 which was allowing for other people to do the thinking 0:20:12.800 --> 0:20:16.880 and or the detailed work which I loved to do, 0:20:18.000 --> 0:20:21.640 and kind of taking a much more macro perspective and 0:20:21.760 --> 0:20:25.199 a bigger picture perspective, where you know, it was a 0:20:25.240 --> 0:20:31.280 much more socratic methodology of questioning and asking the right 0:20:31.359 --> 0:20:36.400 questions to guide the analysts in the right direction, so. 0:20:38.000 --> 0:20:39.119 You know, and that was like I. 0:20:39.160 --> 0:20:41.280 Used to do that with the companies, right, I would 0:20:41.320 --> 0:20:44.000 ask all these questions of the companies, But doing it 0:20:44.040 --> 0:20:46.919 with your peer set and people that work with you 0:20:47.080 --> 0:20:50.280 is a little bit different, and so that was a 0:20:50.440 --> 0:20:51.840 kind of a tough transition for me. 0:20:52.400 --> 0:20:57.600 So you have a PhD, but not an MBA. I'm 0:20:57.680 --> 0:21:01.080 curious the apprenticeship you went through going through all those 0:21:02.040 --> 0:21:05.320 steps at alger What do you think you learned through 0:21:05.359 --> 0:21:09.119 that process that, hey, a green NBA right at a 0:21:09.160 --> 0:21:11.240 school is going to take them a couple of years 0:21:11.240 --> 0:21:11.960 to figure out. 0:21:12.640 --> 0:21:16.520 You know, when you are on the hook for real 0:21:16.560 --> 0:21:22.240 performance for real clients and you make a wrong decision, 0:21:22.920 --> 0:21:27.080 it isn't like doing poorly on a test, right, It's 0:21:27.080 --> 0:21:34.920 simply not equivalent because you actually feel the pain of 0:21:35.000 --> 0:21:41.199 having made that decision that impacted someone else. So, you know, 0:21:41.800 --> 0:21:49.800 I think learned abilities that are experiential just have a 0:21:49.840 --> 0:21:54.200 different impact than when you're sitting in a classroom because 0:21:54.200 --> 0:21:56.480 I think in a classroom that the consequences are just 0:21:56.600 --> 0:22:01.760 lower than they are when it's when you're really investing 0:22:01.800 --> 0:22:02.560 other people's money. 0:22:02.960 --> 0:22:07.320 That is the classic academia versus real life. All Right, 0:22:07.359 --> 0:22:09.280 I didn't get one hundred, I got a ninety six. 0:22:09.480 --> 0:22:13.240 Isn't the same as this one position is ruining all 0:22:13.320 --> 0:22:15.600 of my performance for the quarter. 0:22:15.560 --> 0:22:16.040 That's right. 0:22:16.760 --> 0:22:19.280 It's very different, and I think what you learn from 0:22:19.359 --> 0:22:22.080 it is I mean, there are certain I have this 0:22:22.119 --> 0:22:25.080 book where I used to write down and not so 0:22:25.200 --> 0:22:28.040 much anymore. But I have all my learnings from when 0:22:28.080 --> 0:22:32.080 I was a kid in the business where to remind 0:22:32.160 --> 0:22:34.160 myself not to make those same mistakes again. 0:22:35.280 --> 0:22:37.960 And I haven't looked at it in a while. 0:22:38.040 --> 0:22:41.840 I probably should go back and see how I developed, 0:22:41.920 --> 0:22:46.560 because there were so many learnings that I would carry 0:22:46.600 --> 0:22:48.760 with me and have shaped who I am today. 0:22:49.320 --> 0:22:52.320 I think that's how Ray Dalio wrote Principles, just get 0:22:52.359 --> 0:22:54.440 writing all his mistakes and what he learned from them. 0:22:54.520 --> 0:22:57.680 Oh really, I love Principles. I actually have his book 0:22:57.760 --> 0:22:58.320 for kids. 0:22:58.600 --> 0:23:04.400 Oh really, I don't real but he's described Principles as 0:23:05.080 --> 0:23:08.800 just every mistake he's made, every adjustment he's made, and 0:23:08.880 --> 0:23:13.879 ultimately how to turn errors into better performance. It's really 0:23:14.880 --> 0:23:18.639 very insightful, especially from a time when Wall Street didn't 0:23:18.720 --> 0:23:21.480 love to admit they ever got anything wrong. It's kind 0:23:21.480 --> 0:23:25.120 of fascinating. So you ran Alger's tech sector and then 0:23:25.760 --> 0:23:32.280 took over with your colleague the capital appreciation strategies, being 0:23:32.400 --> 0:23:37.240 hyper focused in one sector versus broad capital appreciation. What's 0:23:37.280 --> 0:23:40.639 that transition like? That sounds like a really big leap 0:23:41.119 --> 0:23:44.639 from something you're very comfortable with to gee, there's a 0:23:44.640 --> 0:23:47.919 lot of risk and a lot of uncertainty around that 0:23:48.080 --> 0:23:50.080 sort of new job description. 0:23:50.320 --> 0:23:50.520 Yeah. 0:23:50.560 --> 0:23:53.840 Absolutely, But look, there's things that rhyme. And I think 0:23:53.880 --> 0:23:58.399 that the sector I struggled with most was healthcare because 0:23:58.400 --> 0:23:59.960 it is so incredibly esotary. 0:24:01.000 --> 0:24:05.440 And why why is healthcare so esoteric? You come out 0:24:05.440 --> 0:24:07.480 with a drug, you sell a few billion dollars worth, 0:24:07.520 --> 0:24:08.359 everybody's happy. 0:24:08.760 --> 0:24:10.760 Yeah, but it doesn't quite work that way all the 0:24:10.800 --> 0:24:11.560 time now it does it. 0:24:12.640 --> 0:24:16.639 So and there's all this like legislative you know, overhang, 0:24:16.880 --> 0:24:21.440 there's regulatory stuff that's happening, there's subsidies that come and go, 0:24:21.520 --> 0:24:26.119 There's there's a political backdrop that you have to always 0:24:26.119 --> 0:24:27.320 be aware of for healthcare. 0:24:28.040 --> 0:24:30.720 So, you know, healthcare. 0:24:30.320 --> 0:24:34.840 Actually was a part of the market where it didn't 0:24:34.920 --> 0:24:38.840 really rhyme with anything that I had done before. But 0:24:38.880 --> 0:24:42.000 if you think about industrials and financials, those were cyclicals, 0:24:42.520 --> 0:24:45.280 cyclicals of a different nature. You know, some were long 0:24:45.680 --> 0:24:51.040 kind of longtime cyclicals versus semis. You know, financials were 0:24:51.040 --> 0:24:54.840