Transcript: Ankur Crawford, Portfolio Manager, Alger Capital Appreciation
The transcript from this week’s, MiB: Ankur Crawford, Portfolio Manager, Alger Capital Appreciation, is below.
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MASTERS IN BUSINESS
Bloomberg Radio · Hosted by Barry Ritholtz
Transcript: Dr. Ankur Crawford
Executive Vice President and Portfolio Manager, Alger
00:00:08 BARRY RITHOLTZ: This week on the podcast, another extra special guest: Dr. Ankur Crawford is co-head portfolio manager of large cap strategies at Alger. She’s got a fascinating background. She was an engineer at Intel, won a number of patents, and was the awardee of the Intel PhD Fellowship. She’s been recognized as one of the top women in asset management.
If you’re interested at all in the details of how artificial intelligence, semiconductors and software work, as I am, you’re going to find this to be a fascinating conversation. With no further ado, my conversation with Alger’s Ankur Crawford. Ankur Crawford, welcome to Bloomberg.
00:01:03 ANKUR CRAWFORD: Thank you for having me, Barry.
00:01:05 BARRY RITHOLTZ: So let’s start with your background, which is really kind of fascinating. Bachelor’s degree in mechanical engineering and materials science and engineering — that’s a double BS from UC Berkeley — and then a master’s and a PhD in materials science and engineering at Stanford. What was the original career plan?
00:01:27 ANKUR CRAWFORD: I didn’t have one, to be honest. When I made the decision to become a mechanical engineer, I was kind of following my brother’s footsteps. He was a mechanical engineer and became an orthopedic surgeon. And I realized if I didn’t know what I wanted to do, I wanted to keep my options open.
00:01:46 BARRY RITHOLTZ: So he becomes an orthopedic surgeon with a mechanical engineering degree. Is he designing replacement joints and things like that?
00:01:55 ANKUR CRAWFORD: He does. He does actually bring that aspect of his engineering background into devices, different device configurations. And he works a lot with the device companies as well. But there’s also — as a kid I loved figuring out how things work, whether it was a car or a calculator, and I would always be fidgeting to understand how things work. I loved building, so mechanical engineering kind of felt like — I’m just a curious person. So I like to satiate that need to know how things work.
00:02:34 BARRY RITHOLTZ: And I read somewhere that you originally wanted to be an astronaut. Is this correct?
00:02:39 ANKUR CRAWFORD: I did. I grew up — till I was five, we lived in Florida, close to Cape Canaveral, and we would go watch the space shuttle take off. And I was so fascinated by space because it was almost ethereal — this thing goes up into the sky. And for me, the astronauts were celebrities. So for a long time I did want to be an astronaut.
00:03:08 BARRY RITHOLTZ: So I have Florida somewhere in between. You’re born in Kansas — is this correct?
00:03:08 ANKUR CRAWFORD: Yes, yes. Kansas.
00:03:14 BARRY RITHOLTZ: But you end up in the Middle East.
00:03:16 ANKUR CRAWFORD: Yes.
00:03:17 BARRY RITHOLTZ: And then you’re sent to a convent boarding school in the Himalayas. Is this possibly right?
00:03:17 ANKUR CRAWFORD: Yes.
00:03:17 BARRY RITHOLTZ: That has to be an AI hallucination, right?
00:03:26 ANKUR CRAWFORD: No, that is all correct.
00:03:27 BARRY RITHOLTZ: And then you end up in Buffalo, New York.
00:03:30 ANKUR CRAWFORD: You got it.
00:03:31 BARRY RITHOLTZ: All right, so that’s real human research, not chat. I’m curious — that is a broad global life experience. How does that shape your views on either international investing, or just the concept of risk and reward?
00:03:49 ANKUR CRAWFORD: Yeah, I think it more so shapes the way I think about the cultural differences. When I look at companies, when I look at management teams, I understand very well that there are certain cultural differences that are simply endemic to businesses and to management teams. And just because a management team isn’t necessarily always bullish, or they’re always telling you the negative aspect of their company, doesn’t necessarily mean that there’s something wrong.
An example of this is this company called Nebius, where the CEO is a Russian CEO who is incredibly humble, and he will never tell you what’s right. He will always point out to you all the things that are wrong. And a lot of investors are like, “I don’t — that doesn’t sound good.” And I’m kind of looking at the opportunity, because that’s just his culture, right? It’s his culture not to be boastful.
So just living in all these different countries and having exposure as a kid to many different religions, it gives a really unique perspective on any problem that you look at, because it helps take the blinders off.
00:05:13 BARRY RITHOLTZ: It’s fascinating. I never really thought about how a societal, cultural set of norms makes its way to management. You think about the Japanese culture — the sort of bravado and very aggressive forecasts we tend to see in the United States, you would never see anything like that.
00:05:13 ANKUR CRAWFORD: That’s right.
00:05:35 BARRY RITHOLTZ: In Japan. How do you calibrate what is cultural nuance and what is just, hey, there’s a problem here and they’re telling us this is an issue?
00:05:48 ANKUR CRAWFORD: Yeah, I think you have to know the business, right? The first thing is, know the business, and then you can calibrate the tone of the management. An example is Taiwan Semiconductor. I remember speaking to them over many of these years that we’ve owned the stock.
And I would always say, “You guys are going to become the single supplier of leading edge. Why is it that you can’t take up pricing?” And they would always talk me down and say, “Oh no, we are here to serve our customer, we are here to —” And I was like, “There’s absolutely no reason for you not to be raising pricing.”
And they would just push back, because that wasn’t part of their philosophy. It wasn’t part of the philosophy that Morris Chang had kind of put into place in the early years. However, that is what they ended up doing. And so I had to take that with a grain of salt, understanding that’s their philosophy.
It was a little frustrating at the time, but a business is a business, and at some point the realization of how good that business was came into the numbers.
00:07:01 BARRY RITHOLTZ: So you mentioned the advantage of really understanding the business. You are an Intel doctorate fellow, you worked as an engineer at Intel, you hold multiple patents. How much of an advantage is that when you’re looking at semiconductors or AI or any of the hyperscalers? What advantage does that give you?
00:07:24 ANKUR CRAWFORD: Look, I think understanding the technology is kind of crucial right now, because in this world of AI, there are a lot of people who don’t really understand what is happening under the covers. And that’s dangerous. And that’s why you also see the volatility that you see today — they’re kind of loose holders and not truly understanding the different dynamics of the technology. And it’s just a hard way to invest when you can get shaken out because you don’t have conviction in the technologies.
So I feel like it’s always helped. And in part because — chips. I was a semiconductor analyst when I first started at Alger, and I kind of immediately understood, well, I understand what a deposition tool is. I used one. I understand what etching is. I used this tool. I understand what the issues are in fabricating a chip, and how hard it is to fabricate a chip. So it just gives you a little bit of an edge on the conceptual understanding and where the industry is going.
So early on, I remember in 2011, ’12 or ’13 — one of those years — I put together a presentation about how we’re at the end of Moore’s Law and what will happen if we’re at the end of Moore’s Law. And I sent the presentation out to all of the companies that I covered and I said, “I would like your feedback, and tell me why I’m wrong.” But that was thinking kind of eight, nine years ahead, because it had implications for the entire sector. And so those kinds of insights, I think, are easier. Not that everyone can’t have them — they just come probably a little easier because I understand the technology.
00:09:19 BARRY RITHOLTZ: So I see the advantage of having the technical background as an analyst. I’m curious what made you leave the technical field — being an engineer and working with semis — to becoming an analyst in the space and working on the financing of semis?
00:09:39 ANKUR CRAWFORD: Yeah, I had gone through my graduate career, and really I had set some goals for myself. I want to write this many papers. I want to present. I want to be useful to society. And at the end of it, I felt like I had kind of achieved all those goals, but I wasn’t happy.
I just wasn’t content and happy. And I thought to myself, my gosh, if I have achieved everything that I set out to do and yet I’m still not happy, what happens if I become a professor and we just go through a tough spot on raising money, or whatever it might be like in the research? Will I be even happier? And I think that self-awareness made me realize I needed to go look somewhere else.
And when I came to Alger, it was really like — I was thinking I’d be here for two years and then go back and do a postdoc somewhere and be a professor. And I never left.
00:10:46 BARRY RITHOLTZ: Really, really interesting. One of the complaints I’ve heard from people who are technologists or engineers or what have you is that everything has become so increasingly specialized and narrow that you get put into a silo. You have no idea what’s going on in any of the adjacent sciences, more or less even within your field. Everybody gets too specific. Was that a concern?
00:11:11 ANKUR CRAWFORD: Oh, for sure. And that’s a great insight. I was in a room — this is probably a 15-by-15 room. I spent three and a half years in the basement of a building at Stanford taking care of a tool that was about this big.
00:11:11 BARRY RITHOLTZ: Wow.
00:11:27 ANKUR CRAWFORD: I was the plumber and the electrician, carrying out cryopumps and fixing them. And it was a very narrow, lonely experience.
00:11:38 BARRY RITHOLTZ: I can imagine.
00:11:39 ANKUR CRAWFORD: And my advisor was fantastic, but just that process required — it was very narrow. And I’m very proud of the work that we did, but it was very, very niche.
00:11:53 BARRY RITHOLTZ: So you move from a field governed by the laws of physics and nature to another field kind of governed by the eccentricities of human behavior. What are the challenges in that transition?
00:12:10 ANKUR CRAWFORD: I didn’t know anything when I started in this business. I knew a lot about atoms and materials and magnets, and how to make a chip. But I really didn’t know very much about investing. So honestly, it was all new to me.
So the challenge was really understanding — I was always asking why. Well, why does this happen? Or why does the stock go up on this? Or why does the stock not go up on this? And understanding that human behavior aspect was more a fascination versus a challenge, because this idea of expectations versus the truth — I grew up in a world where there is a single answer, right?
Where you write an equation and there is a way to do it, versus people can skin the cat in so many different ways in what we do. You can get to the same result in an infinite number of ways. So I suppose that was the challenge, of understanding that there isn’t just one way of doing it, but perhaps you have to understand the different ways, then adopt your own way of approaching the problem.
00:13:41 BARRY RITHOLTZ: I love the Richard Feynman quote: imagine how much harder physics would be if electrons had feelings. Right? Always cracks me up, at the intersection of science and investing. So you answer a recruiting ad from Alger despite knowing nothing about investing. What made you think your skills might get you through the door at a shop like Alger?
00:14:13 ANKUR CRAWFORD: I didn’t really. I really didn’t. I was reading a book — it was written by a bunch of McKinsey consultants at the time, and I forgot the name of the book, but it was all about profit and loss and just businesses, how businesses are run. And I really didn’t know, honestly, Barry, what I was applying for.
I knew that I needed to do something else. I had worked at Merrill Lynch for a summer before I had started graduate school and I loved it. It was kind of the emerging markets debt desk. And I was like, let me give this a go again.
And when I applied to Alger, I knew that I was curious enough that I would be able to cross the chasm, and I would be able to learn and give back to our company.
00:15:07 BARRY RITHOLTZ: Huh. Really, really —
00:15:08 ANKUR CRAWFORD: But I really didn’t know.
00:15:10 BARRY RITHOLTZ: Well, that’s really fascinating. We’ll explore that more coming up.
We continue our conversation with Ankur Crawford, co-PM of the large cap strategy at Alger and PM of the concentrated portfolio ETF, talking about her career at Alger. I’m Barry Ritholtz, you’re listening to Masters in Business on Bloomberg Radio.
00:15:35 BARRY RITHOLTZ: I’m Barry Ritholtz, you’re listening to Masters in Business on Bloomberg Radio. My extra special guest this week is Dr. Ankur Crawford. She is portfolio manager at Alger, where she co-PMs the large capital appreciation strategy as well as running the concentrated ETF.
So we were talking earlier about — you answered an ad that Alger had put up to hire people. I read a story that Alger’s CEO Dan Chung hired you right on the spot. That’s kind of unusual in this space. Tell us about what happened there.
00:16:17 ANKUR CRAWFORD: It was funny. I actually walked into this meeting — I had just come back from Tahoe, I’m a big skier — and I was really frustrated because it was pouring outside, and I walked in like drenched and really upset. And I was like, the only good thing about this is that it’s snowing in Tahoe. And Dan happens to be a skier.
I didn’t know that. And so we started this conversation talking about our mutual love of skiing. After that, I think he realized I didn’t know very much at all about investing, and he asked me my opinion of Intel versus AMD. And this was 2003, 2004, and peak —
00:17:01 BARRY RITHOLTZ: Intel.
00:17:02 ANKUR CRAWFORD: It was peak Intel. And I remember saying, “You know, I worked at Intel, and I think I prefer AMD versus Intel, because this is kind of what I’m seeing inside of Intel.” Not inside information, but more the culture that had developed. And we had this long discussion about it.
That evening they hosted a kind of get-together for all of the applicants. And Dan and I got into an argument about NAND versus hard disk drives.
00:17:38 BARRY RITHOLTZ: And you were on the NAND side, right?
00:17:39 ANKUR CRAWFORD: Well, he was telling me that all hard drives were going to go to zero.
00:17:44 BARRY RITHOLTZ: And he was eventually right?
00:17:45 ANKUR CRAWFORD: And he will be eventually right. And you know what’s so funny? I just had this discussion with him yesterday, and I was like, “Dan, we had this discussion 22 years ago.”
00:17:55 BARRY RITHOLTZ: It only took you two decades to be right. In trading, early is the same as wrong.
00:18:01 ANKUR CRAWFORD: Yeah. Well, it was great, because we had this really — it wasn’t a heated conversation, but it was definitely kind of looking at this problem in two different ways. And as we were walking out, he was like, “You’re hired.”
00:18:15 BARRY RITHOLTZ: Just like that.
00:18:15 ANKUR CRAWFORD: Just like that.
00:18:15 BARRY RITHOLTZ: I need someone who’s not afraid of me, who will stand up and make me think of this problem from multiple angles.
00:18:23 ANKUR CRAWFORD: Well, I think it’s a little bit of the culture that we have at Alger, of it’s always better to have different perspectives versus go along with the norm and be consensus, and to always encourage that debate. And one thing I am for sure — especially because, again, I come from a place of, we’re always trying to find the truth. There is an answer. I do bring that to the table here too, in that there is an answer, right?
Whether or not you look at it from one angle versus the other, there is an answer. The earnings are the answer. The trajectory of earnings are the answer. And getting that right can be a topic of debate, and how you get there — we can debate it to make sure that we’re getting to the truth.
00:19:15 BARRY RITHOLTZ: So you start in the analyst training program at Alger, you advance to a research associate, then an analyst, then a tech sector head, and ultimately a portfolio manager. What transition was the most challenging? What changed the way you thought about the job?
00:19:36 ANKUR CRAWFORD: I would say that the transition from being an analyst to a portfolio manager. And even as a tech sector head, I kind of had my fingers in everything, and my little OCD tendencies were still able to play out a little bit. That transition to portfolio manager, however, required a different skill set, which was allowing for other people to do the thinking and the detailed work, which I loved to do. And kind of taking a much more macro perspective and a bigger picture perspective, where it was a much more Socratic methodology of questioning and asking the right questions to guide the analysts in the right direction. And that was like — I used to do that with the companies, right?
I would ask all these questions of the companies, but doing it with your peer set and people that work with you is a little bit different. And so that was kind of a tough transition for me.
00:20:52 BARRY RITHOLTZ: So you have a PhD but not an MBA. I’m curious, the apprenticeship you went through, going through all those steps at Alger — what do you think you learned through that process that, hey, a green MBA right out of school is going to take them a couple of years to figure out?
00:21:12 ANKUR CRAWFORD: When you are on the hook for real performance for real clients, and you make a wrong decision, it isn’t like doing poorly on a test, right? It’s simply not equivalent, because you actually feel the pain of having made that decision that impacted someone else. So I think learned abilities that are experiential just have a different impact than when you’re sitting in a classroom. Because I think in a classroom, the consequences are just lower than they are when you’re really investing other people’s money.
00:22:02 BARRY RITHOLTZ: That is the classic academia versus real life. All right, I didn’t get a hundred, I got a 96, isn’t the same as this one position is ruining all of my performance for the quarter.
00:22:15 ANKUR CRAWFORD: That’s right.
00:22:16 BARRY RITHOLTZ: It’s very different.
00:22:17 ANKUR CRAWFORD: And I think what you learn from it is — I have this book where I used to write down, and not so much anymore, but I have all my learnings from when I was a kid in the business, to remind myself not to make those same mistakes again. And I haven’t looked at it in a while. I probably should go back and see how I developed, because there were so many learnings that I would carry with me and have shaped who I am today.
00:22:49 BARRY RITHOLTZ: I think that’s how Ray Dalio wrote Principles — just writing all his mistakes and what he learned from them.
00:22:54 ANKUR CRAWFORD: Oh, really?
00:22:54 BARRY RITHOLTZ: Yeah.
00:22:54 ANKUR CRAWFORD: I love Principles. I actually have his book for kids.
00:22:58 BARRY RITHOLTZ: Oh, really?
00:22:59 ANKUR CRAWFORD: Yes. I thought it was so good.
00:22:59 BARRY RITHOLTZ: That one I haven’t read. But he’s described Principles as just every mistake he’s made, every adjustment he’s made, and ultimately how to turn errors into better performance. It’s really very insightful, especially from a time when Wall Street didn’t love to admit they ever got anything wrong.
It’s kind of fascinating. So you ran Alger’s tech sector and then took over, with your colleague, the capital appreciation strategies. Being hyper-focused in one sector versus broad capital appreciation — what’s that transition like? That sounds like a really big leap, from something you’re very comfortable with to, gee, there’s a lot of risk and a lot of uncertainty around that sort of new job description.
00:23:50 ANKUR CRAWFORD: Yeah, absolutely. But look, there’s things that rhyme. And I think the sector I struggled with most was healthcare, because it is so incredibly esoteric.
00:24:02 BARRY RITHOLTZ: Why is healthcare so esoteric? You come out with a drug, you sell a few billion dollars worth, everybody’s happy.
00:24:08 ANKUR CRAWFORD: Yeah, but it doesn’t quite work that way all the time.
00:24:08 BARRY RITHOLTZ: No, does it?
00:24:08 ANKUR CRAWFORD: So there’s all this legislative overhang, there’s regulatory stuff that’s happening. There’s subsidies that come and go. There’s a political backdrop that you have to always be aware of for healthcare. So healthcare actually was a part of the market where it didn’t really rhyme with anything that I had done before. But if you think about industrials and financials, those were cyclicals — cyclicals of a different nature.
Some were long-time cyclicals versus semis. Financials were also cyclicals tied to the economy. The emphasis more on the macro was something I started to incorporate more in my thinking. But for someone who is very curious — I’m always curious and I’m always asking questions — to me it was kind of a breath of fresh air to expand my purview, to understand and synthesize how the world works. I quite enjoy having that broader perspective.
And what else is super interesting — and I’ve only had this appreciation probably in the last decade — is how history rhymes. So I have become a bit of a history fan. And in part because I started when I was working with my now 18-year-old and doing history homework with her. And all of a sudden I started to realize there is so much that is similar that is going on today, as has happened before.
So I think that is also really fascinating as you start to pull the big picture together, because it just gives you a different perspective on sectors and how to invest.
00:26:18 BARRY RITHOLTZ: Huh. Really, really interesting. So you also are the sole manager of the Alger Concentrated Equity strategy, which is now in ETF form. When I think of concentrated portfolios, we’re talking 15, 20, 25 names. How many names are in it, and then how do you size them? Are they all equal weight, or how — what does that look like?
00:26:43 ANKUR CRAWFORD: Yeah, so this portfolio is 20 to 30 stocks. It is an actively managed, fully transparent ETF. And when we think about sizing for the portfolio — look, the concept of this portfolio is to just invest in the best businesses that are going to have the greatest change and have the best risk-reward at any given point in time.
00:27:10 BARRY RITHOLTZ: So tell us the full name of the ETF and the —
00:27:14 ANKUR CRAWFORD: It’s the Concentrated Equity portfolio, and the ticker CNEQ. So the idea here is we want to invest in the best companies that are going to be benefited by the best growing trends in the market, and the compounding nature of earnings should drive the portfolio and drive the companies that are within that portfolio. So position sizing is just like any other portfolio: the risk-reward dictates how big the companies are in the portfolio. And there are some that — Nvidia’s currently at a 13.5% position in the portfolio, whereas there’s other companies that we’re weighting at the bottom of the portfolio, kind of like Figure Technologies, that is smaller and waiting to see when the true traction in their markets starts and the overhang of some of the selling — and to take it up.
But each of the businesses that are owned in this portfolio have large opportunity and big TAM.
00:28:27 BARRY RITHOLTZ: Total addressable market. Yes. CNEQ. All right, I’m going to make a note of that.
So I know Alger, back when it was Alger Capital Growth or Alger Capital Management, launched in 1964. What does growth investing mean at Alger? Because there are definitions that seem to be different from place to place. What are you looking for that perhaps the market hasn’t priced correctly?
00:28:54 ANKUR CRAWFORD: So I think what makes us interesting as growth investors is that the fundamental thing we look for is not necessarily growth — it is change. And the change begets the growth, right? So the growth is an output of the change. And I think that’s an important differentiator, because it’s not just expressed as, let’s do a screen and find the companies that are growing the fastest.
It is, let us look for the change. Because where there is change, there is often unidentified opportunity, and because of that, we will get the growth. So we have a significant research team that is always looking for change. Now, the way that Fred had initially incepted this concept of change was to look at two different pillars.
The first is what we call high unit volume growth. And that is a typical kind of company that is growing their top line. They become market dominant, or have a positioning where they’re taking a lot of share, very forward thinking, and it expresses itself as high top line and growing bottom line. It could be small and mid-cap companies, it could be larger companies.
Really, it spans the gamut of change and growth. So that would be more of a typical growth company. Traditional growth.
00:30:21 BARRY RITHOLTZ: A kind of a traditional growth company.
00:30:21 ANKUR CRAWFORD: Yeah. The other side, which I think makes us really unique, is what we call lifecycle change.
And oftentimes we like to show this — it’s almost like an S-curve. We like to invest in the companies that are early on in the S-curve, and companies that have already gone through the S-curve, they’re kind of saturated out of their markets and they’re starting to question who they are.
00:31:05 BARRY RITHOLTZ: Saturated as in fully priced, or saturated as in, hey, that’s as big as their market share is going to get?
00:31:11 ANKUR CRAWFORD: Yeah, that’s as big as their market is going to get. So what you see is oftentimes companies where they were great growth companies, and all of a sudden their growth has stabilized, or growth is starting to approach GDP.
00:31:25 BARRY RITHOLTZ: Mature.
00:31:25 ANKUR CRAWFORD: Kind of more mature, right? So kind of a more mature company. And then the management has a decision to make: am I still a growth company, or am I going to just milk what we have? And oftentimes that begets change.
So a new management comes in and decides we’re going to jettison all our low-growth businesses and start buying higher-growth businesses, and it changes the profile of the business. It could be a regulatory change that makes the company a little bit more growthy than it was historically. It could be M&A that again re-accelerates top line growth. It could be a technological change that they really embrace.
And this was Microsoft in its early days, when Satya Nadella first came to the helm. So it’s almost as if the company had a decision to make, and we’re looking for changes where the decision from here is to get onto a growth trajectory — and then study how they execute, such that it drives both top line and bottom line growth. So oftentimes when we buy companies that are on that side of the ledger, people will think they’re value names, and they’re not really value names. They’re actually unidentified and misunderstood growth. And that’s how we think of them.
And a great example of this is what’s happening to the hard disk drive companies right now, where they were trading at single digit multiples, but in an era of AI, all of a sudden you need a lot more data and you need to store all that data. So hard disk drives all of a sudden became in shortage, and now they’re taking pricing, and their earnings power has gone up three, four, fivefold over the last few years.
00:33:24 BARRY RITHOLTZ: Even though people thought it was at the tail end of their useful —
00:33:24 ANKUR CRAWFORD: That’s right.
00:33:24 BARRY RITHOLTZ: — life cycle, they found a second life.
00:33:32 ANKUR CRAWFORD: That’s right. And so that is also a change, and it happens to be a change in the market broadly, right?
00:33:41 BARRY RITHOLTZ: So that raises a really fascinating question I have to ask you. There are companies that appear to be on the back end of their lifecycle, their growth has plateaued. Maybe they’re not gaining market share, maybe the market itself isn’t growing. How can you identify when something is legitimately fading, or potentially at the start — like, I know IBM just had a rough quarter, but how many times has that company reinvented itself and been left for dead only to surprise everybody?
And there’s a bunch of others. Microsoft, you brought up, is another example. What were they, 30, 40 years old when Nadella came in? That’s a huge turnaround story. So how do you identify when, hey, these guys are never going to be what they once were, versus, no, there’s something real happening?
00:34:42 ANKUR CRAWFORD: Okay, so there was this publicly traded fintech company that was just struggling, in part because they had saturated their markets and there was nowhere for them to grow. And it was becoming a lot more competitive. CEO and CFO leave, new management comes in, put together a brand new strategy that is fantastic. Our team looks at it, it’s like, promising.
However, the core issues of their business have not been resolved, right? Do you go from a four and 5% grower to a 10, 12, 15% grower with the strategy? We couldn’t really resolve that they would be able to get there, because the pressures in their markets were so significant.
00:35:33 BARRY RITHOLTZ: Competitive, mature, et —
00:35:35 ANKUR CRAWFORD: — cetera. Competitive maturity. They were just fighting to kind of stay alive, or stay at that like three, four, 5% type growth. So that was one that we looked at. The catalyst was a new CEO, a new management team.
Like, the entire management team was different, but to us it wasn’t really logical that they could change the trajectory of the business. Microsoft, a completely different story, because Satya comes in, he says, we’re going to turn the ship, we’re going to develop cloud. And then we started to understand what it meant to go to a SaaS-based business. Gosh, in the near term it would be depressing their earnings, but longer term it’s really interesting, right?
And they can get to a mid-teens type growth again, which they did get to. I mean, Microsoft, if you remember, everyone thought Google was going to take over. Google Sheets was going to take over Excel. And like, why do we all need Microsoft?
00:36:38 BARRY RITHOLTZ: I asked myself that question every time I launch and look at the annoying new ribbon that they changed a decade ago. But I use both.
00:36:47 ANKUR CRAWFORD: But you use both. Yeah. And after all these years — and I assume in 10 years we’ll still be using Microsoft. So Satya then pivoted the ship and got into the cloud business with Azure.
And so we watched the actions as well. So we can dream the dream and then test the hypothesis and see whether or not they’re executing against it.
00:37:13 BARRY RITHOLTZ: Hmm. Really, really interesting. Let me reverse the question to you and say, what leads you, when you’re running a concentrated portfolio, to say, I’m going to sell this? Is it the fundamentals deteriorating, the thesis not working out? Sometimes is it based on valuation? Or is it simply, we only have room for X number of companies, and this opportunity is here and that opportunity is all the way up here?
00:37:40 ANKUR CRAWFORD: It’s all of the above, right? There are examples of selling a company because there’s a better opportunity and you don’t want to take double the risk to the same end market, yet the upside of one is greater than the upside in the other. There are examples of you sell, or at least trim, because the price target has been achieved — and maybe beyond, the price target has been achieved. So the risk-reward is simply different.
There are examples of disappointments — companies that disappoint relative to our expectations, and they didn’t deliver on what we expected them to do, and the hypothesis didn’t play out. So I think there’s all of the above, and every sale has a different reason.
00:38:30 BARRY RITHOLTZ: Really, really interesting. Coming up, we continue our conversation with Dr. Ankur Crawford, executive vice president and portfolio manager at Alger, diving into her AI thesis. I’m Barry Ritholtz, you’re listening to Masters in Business on Bloomberg Radio.
00:38:58 BARRY RITHOLTZ: I’m Barry Ritholtz, you’re listening to Masters in Business on Bloomberg Radio. My extra special guest today is Dr. Ankur Crawford. She’s portfolio manager at Alger, where she co-PMs the large capital appreciation strategy and runs the concentrated ETF for the firm.
So we are legally obligated to discuss artificial intelligence, but you are the perfect person to have this conversation with. There’s a quote of yours that I found fascinating. You said, when software begins to write software, innovation becomes exponential — that’s already happening. Walk us through what this means for earning power for the semiconductors, for the hyperscalers, and then for the rest of the S&P 500.
00:39:42 ANKUR CRAWFORD: Okay, so that is a very big question. Look, I think we are at this — I mean, Elon would call it a singularity — we’re at this point in time where we have never seen this kind of innovation. And imagine everything that — let’s take what’s easiest to describe. Software. We used to sit and code software, right? And we had to understand the coding, we had to debug it.
It would take a long time. Well, when software begins to write software, that whole process is truncated. And imagine what can be done in our largely digital world when software begins to code, decode and create.
00:40:36 BARRY RITHOLTZ: So let me push you a little bit there. The large language models that are out there give AI the ability to effectively cut and paste everything that’s been done before. How good is AI at creatively innovating code that’s never been written before?
00:40:59 ANKUR CRAWFORD: So look, I am not a coder, so I can’t tell you whether the code is elegant, or can be taken to production. I will tell you that I was able to build a pretty interesting app inside of a few months. And this is just doing it on the weekends — occasionally on the weekends, not even every weekend. And that was all vibe coded.
So it is adding this technology that is highly viable. You talk to coders, they are using it 90% of the time and are now just instructing, and have to have the logical framework of how to use the code. And I think the big picture here is that once the code begins to write the code, then it’s not going to necessarily be creative. The creation still has to come from you.
The insight still has to come from you, but it can actually innovate, right? The innovation curve for you is significantly higher. So that’s what we’re seeing today, where these digital assets are becoming more innovative, or they’re allowing us to be more innovative. And we’ve hit that point in time where we’re getting exponential innovation, and we’ve never really seen anything like this before.
Humanity hasn’t seen this before, in such a short period of time. If you look at previous industrial revolutions, they would be over generations. It wouldn’t be coming in the span of five years. And so this is what makes it really interesting. Because you asked, how good is it for semiconductors, and how good is it for the rest of the S&P and the hyperscalers — the impact on all of these differs. So, software: we wrote a paper three years ago called “AI and the Declining Cost to Create.”
And it was all about how, when software begins to write software, the cost to create software goes to zero. And what happens to the incumbents when the cost to create software is zero, right? One of the moats goes away. And that necessarily means that the operating profit of businesses must change.
Not that software is dead. It’s just that the operating profile of all of the companies must change, because it becomes more competitive, right? And where does that value go? We had five and a half trillion dollars of spending, now $6 trillion of IT spending. Fifty percent of that was IT services and software. And our contention was that the value would go from IT services and software into hardware and networking, because that is really what is driving this innovation curve.
So there’s entire sectors that have grown a lot and others that are facing their own pressures. I would say the same thing for any sector in the market. We spoke about healthcare earlier — how can a UnitedHealthcare actually use AI to bend the cost of care? And can there be incumbents that cross the chasm, or there might be some that can’t cross the chasm, and there are new companies that begin to use AI to bend the cost of care?
00:44:43 BARRY RITHOLTZ: So I’m glad you brought up healthcare. I’ve been fascinated not so much by bending the curve of cost from somebody like United, but all of the small biotechs and new molecules, and the huge wealth of existing chemistry and pharmaceuticals and studies we’ve done that nobody’s really had the ability to go back to and say, hey, maybe something’s in here that we’ve missed. The most clichéd example is — I never pronounce it right — sildenafil, Viagra, was supposed to be a heart treatment and had this unusual side effect, and now it’s a multibillion-dollar med. Same thing with GLP-1s, originally for diabetes, but hey, everyone’s losing a lot of weight on these.
I’m curious, not so much on the cost side, but there’s this giant body of unexcavated research that just seems like it’s waiting for AI to attack it.
00:45:50 ANKUR CRAWFORD: Yeah. And so recently I was actually on a panel where I was the moderator for a company — and I’ve forgotten the name of the CEO and the company — but they’re basically a new AI company that is taking this compendium of knowledge and taking it to companies and saying, marry it with the data that you have. And can we start finding not only the solutions for your targets, but use this history to get there faster? So there’s lots of efforts being made on this right now.
I do think that we will accelerate drug discovery and the impact it will have to healthcare. I mean, look, the holy grail is personalized healthcare at some point.
00:46:41 BARRY RITHOLTZ: Wasn’t DNA testing supposed to give us that a couple of years ago?
00:46:45 ANKUR CRAWFORD: Well, DNA, yes, but DNA testing used to cost a million dollars per sample, right? And today it’s a hundred. So we’re getting to the point where we can actually look at our individual DNA, and it just takes time. And at some point, can we marry it with some AI insights?
So look, I think healthcare is going to be greatly impacted. I think that I’m most excited actually to see how we can democratize healthcare, because really our healthcare system here is kind of broken.
00:47:19 BARRY RITHOLTZ: Not kind of.
00:47:21 ANKUR CRAWFORD: To be polite. And how can we take down that cost of care? I would love to have universal healthcare. It just can’t be done in the construct of healthcare as it is today. So can we use AI to provide universal healthcare? I think we can. It will take a few years, maybe a decade, but I think we can. And this is a global statement.
It’s not necessarily just the US. It’s bringing the cost of care down enough such that anyone on this planet will have access to healthcare.
00:48:01 BARRY RITHOLTZ: So I’m going to assume that you think all the AI bubble talk is wildly overblown?
00:48:09 ANKUR CRAWFORD: Yes, I do think it’s wildly overblown. Look, I think the trade has gotten a bit harder, in part because the first two to three years of the trade was, oh, you just have to buy the GPUs. And anything that the GPU touched was gold.
And then it became more nuanced. Well, agents use CPUs, and we have a memory shortage, and memory has now gone up four times in price. So capex budgets are going up. So that question of ROI is coming to the fore.
And how much does capex have to go up to accommodate the supply chains being as tight as they are? And there’s technological differences between a CPU versus a GPU and how they’re used, and the Chinese might be coming, and right? So there’s a lot of different aspects that have made it a little bit harder. The open versus closed source debate — the open model versus a closed model, that’s another debate. The debt and the CDS spreads widening, that’s another.
So all of a sudden we’ve gone from a relatively simple “we’re going to need AI, we are going to need compute” to there’s a slew of different narratives that one can press on for the bear case. Now, I structurally believe — we just talked about healthcare and the innovation curve in healthcare and what that can give back to society. That is true value, right? If we can bend the cost of care from X to X minus, that is value that’s created for humanity, and we will pay for that value.
The other day, there’s been this big debate about token maxing, and there was —
00:50:03 BARRY RITHOLTZ: Define that for the lay listener.
00:50:06 ANKUR CRAWFORD: Yeah. Token maxing was this behavior that companies were encouraging their engineers to basically have leaderboards of who can use the most tokens. Which sounds insane, right? It would almost be like telling your employees to see how much they can spend on lunch, and whoever spends the most on lunch gets an award, right?
00:50:31 BARRY RITHOLTZ: Well, I imagine if you’re a FedEx driver and the company holds a competition for who’s going to go through the most amount of gas and tires, meaning making the most deliveries — not a bad thing for the company.
00:50:44 ANKUR CRAWFORD: Not necessarily a bad thing. But in this case, what was being used is actually not necessarily tied to deliveries. It was just, use the most tokens as you can. It didn’t kind of matter what you built with it, right?
So there wasn’t as much scrutiny as to how many quote-unquote deliveries you made. You just burned through your tires. So it was kind of inefficient. But they came out and they said, we blew through our entire budget in a quarter —
00:51:27 BARRY RITHOLTZ: For the year. The whole —
00:51:28 ANKUR CRAWFORD: — budget for the year. Yeah, the entire budget for the year in a quarter. And we haven’t gotten an ROI. Well, no kidding.
Well, they turned around last week and they laid off 10% of the people that worked for the company because of AI. Well, somewhere along the way the use of artificial intelligence allowed them to kind of refine their workforce.
00:51:52 BARRY RITHOLTZ: That sounds like they didn’t lay off people because of AI. It sounds like they laid off people because management was kind of mis-incentivizing the employees.
00:52:03 ANKUR CRAWFORD: Well, I mean, they said that they laid off people because of AI. There’s been many companies — like Jack Dorsey at XYZ also, he cut 40% of the staff blaming AI. Who knows really what the real reason is? It could be AI, or it could be they just overhired.
00:52:23 BARRY RITHOLTZ: Which he has a history of.
00:52:24 ANKUR CRAWFORD: Which he has a history of.
00:52:25 BARRY RITHOLTZ: If you track him over his various companies.
00:52:27 ANKUR CRAWFORD: Right. And many of these companies did, right? So I can’t absolve that.
However, Uber in particular said it was because of AI. They have been very front-foot-forward on the use of AI, and now they’re able to increase productivity enough that they can titrate down their workforce. So I do think that there is value that is being created because of AI. I think that it is not necessarily a technology that’s plug and play into an enterprise, and there has to be some learnings before you can get to that ROI.
00:53:09 BARRY RITHOLTZ: And we’re seeing those stumbles in that learning curve.
00:53:12 ANKUR CRAWFORD: That’s right. And all these examples — it doesn’t mean that it’s never going to work. And my viewpoint is that where there is value, we work in a system of rewarding value. So if you can create value, I believe that whoever uses that system that creates the value, they will pay for it.
00:53:35 BARRY RITHOLTZ: So you’ve described the demand for compute as insatiable. What would have to happen for you to say, all right, we’re getting to saturation, or satiation? What does the top of the cycle look like? Or is it so far off in the future that we can’t even think about it?
00:53:54 ANKUR CRAWFORD: What I would say is that this is not a question where I can say, oh, in 2030 we won’t need compute. I think it’s a function of how much we put into the ground, right? It’s a delicate balance of, if we put X into the ground today — the hyperscalers are spending $650 billion, or whatever that number is —
00:54:18 BARRY RITHOLTZ: It’s circular, it’s this, it’s that. We’ve heard these complaints now for two years.
00:54:20 ANKUR CRAWFORD: Right. But $650 billion seemed like a really big number, yet we are still short compute, right? You’re hearing from the hyperscalers, we do not have enough. The neoclouds are telling you that there are four times as many asks for compute as they have capacity.
00:54:38 BARRY RITHOLTZ: Wow.
00:54:38 ANKUR CRAWFORD: So if one says that we are short compute today, I don’t really understand the logic. Now let’s fast forward two and three years. If we put $3 trillion into the ground next year or the year after — which we cannot do today, because we are short power, we are short people, we are short capacity, we can’t make those chips.
But let’s hypothetically say we put in $3 trillion of compute into the ground in 2028. I would say that that is overcapacity. But we can’t do it, because there is almost a natural limiter to the growth of this market in that we don’t have the chips, we don’t have the people, we don’t have the power, right? And so the market is being capped.
If all normal forces — and if we had an infinite supply of everything — I think we would be in overcapacity today, because it’s such a big market. Everyone would be building at a pace that they want it to be, that they would want to be first. But the fact is, it’s actually a blessing that the market is being capped by all of these supply chain shortages. The fact that we don’t have plumbers and electricians to actually work in the data centers is capping the growth of data centers.
And so it is allowing for duration versus kind of having a one-time growth pop, which you were not going to pay a high multiple for. So I think that oversupply is a function of how much we put into the ground and how we use it.
00:56:20 BARRY RITHOLTZ: So let’s unpack some of that. In the beginning of ’25, when DeepSeek first was released and everyone was startled, the initial reaction was, oh, we’ve overbuilt, we don’t need this many GPUs, we don’t need all these giant data centers, we just need slightly clever software that can do more with less. Didn’t take long before that just was overrun with, no, we need horsepower. We really need the ability for big problems to not come up with clever little workarounds, but we need the firepower.
And then again, more recently, we’ve seen a number of open source models out of China that seem to be doing a whole lot more with less. At what point does it begin to become, hey, do we really need $3 trillion worth of capacity? Don’t we just need to take a little bit of that, working out of the constraints we have, the way the Chinese models have?
00:57:23 ANKUR CRAWFORD: Yeah. So one of the things that I think is well understood is that the Chinese models didn’t do this on their own. So the way I like to think of it is, you have like an animal world, right? I just went on safari to Kenya, and giraffes almost always have birds sitting on their necks, and those birds are — it’s a mutually symbiotic relationship.
I suppose it’s not that symbiotic to the giraffe, but the bird gets to rest on the giraffe’s neck and benefits from the fact that the giraffe is walking around. So similarly, I think —
00:58:06 BARRY RITHOLTZ: What does a giraffe get out of that?
00:58:07 ANKUR CRAWFORD: I suppose the bird might keep the —
00:58:10 BARRY RITHOLTZ: Bugs away.
00:58:11 ANKUR CRAWFORD: — keep the bugs away, or eat the ticks on the giraffe.
00:58:11 BARRY RITHOLTZ: Gotcha.
00:58:11 ANKUR CRAWFORD: I don’t know. But similarly, the Kimi model is a little bit like the bird on the giraffe. Whereas I look and I think that the Chinese are very innovative in their own right.
I think they’re very good fast followers. However, they need the giraffe, which is our LLMs, in order to survive. And so I think there are many different ways to address what is happening. The scenario that I think is actually most logical — which I’m not quite sure that the large language models will do — is basically to hold the n and n-minus-one model internal, and allow for certain businesses, certain companies, the US government, other governments who are not going to distill this model and kind of feed a Kimi-type model, allow for them use of that model, and only make public the n-minus-two model. And that way it keeps any of the distillation at bay.
Now, in order for that to happen, all of the frontier models will have to agree to do this, because if there’s any frontier model that is equivalently as good, then it kind of breaks the ecosystem that I’m describing. But so I think the point is that you need to spend the capex for the training in order to get that output, so that Kimi can train on that output.
01:00:05 BARRY RITHOLTZ: So these open — training on the output, not creating their own LLM.
01:00:09 ANKUR CRAWFORD: Well, Kimi has created their own LLM by feeding off the — it’s called distilling — feeding off the output from the large language models. So a lot of the spending that is happening is actually coming from the use of the compute, from the inference aspect. So you train, and then you have to infer.
So then the inference is what we experience as consumers. And so that inference is driving a majority of the spend. And you look at the revenues of OpenAI, Anthropic — I’ve never seen growth like this. I don’t think we ever have seen growth that is as significant as what we’re seeing today.
01:00:55 BARRY RITHOLTZ: You know, people frequently make a comparison to the dot-coms, and I always feel like that’s a terrible comparison, because these are real companies with real revenue, real potential profits — not clicks and eyeballs. But the one thing some of the skeptics have pointed out that almost resonates is, during the internet era we had this huge boom where most of that value ended up landing in the consumer’s lap, not the investors’ laps, because so many of those companies crashed and burned. How similar or different is this environment to that?
01:01:39 ANKUR CRAWFORD: So I think it’s quite different. Look, there may be parallels at some point — i.e., do we overbuild, and how long does it take to actually eat through that overbuild? So you think about the 2000s.
One of the reasons we overbuilt is because we had dreamed the dream of what the internet would be. And pets.com was actually a brilliant idea.
01:02:05 BARRY RITHOLTZ: Just a little early.
01:02:06 ANKUR CRAWFORD: Just early. Now it’s Chewy. But Chewy became a significant business. Amazon has built a multi-trillion-dollar business off the back of consumers buying on the internet. But we didn’t have the internet, right?
We had dial-up, right? Dial-up is not good enough to increase productivity back then. What I would argue today is that we actually have the tools. All we needed — we had the internet, we had the productivity, we had the infrastructure that was needed for ubiquitous intelligence. All we needed was the chips, right?
We need the data centers and the chips, and that’s what is happening today. And so if we actually need ubiquitous intelligence and infinite intelligence to some extent — if we overbuild, we will eat through that overbuild as well.
01:03:14 BARRY RITHOLTZ: So what do you think the skeptics misunderstand about AI? Is it the scale, the economics, how durable the investment cycle is? What are the bears getting wrong here?
01:03:27 ANKUR CRAWFORD: I think it’s the duration. I definitively think — I think maybe it’s all of the above, really. But it’s duration, it’s the scale, it’s the economics. All three of those is where I think they’re pushing on the wrong thread.
01:03:45 BARRY RITHOLTZ: So last question before I get to all of my favorite questions I ask all my guests: what do you think investors aren’t talking about or thinking about that perhaps they should be? What is getting overlooked here? And it could be any asset, geography, policy, whatever — but what aren’t people talking about but should?
01:04:08 ANKUR CRAWFORD: Yeah. I think that people aren’t really talking about the net positive benefits to humanity from AI. We talked about healthcare, and how we can make healthcare available to any human on this planet. The same goes for education. There’s no reason why any child should be quote-unquote left behind. I mean, I’ve been shocked at what I’ve been reading recently — kids going to college and they can’t read.
Right? That is a failure of our education system that can be solved using artificial intelligence. And this is again a global issue. It is not a local issue.
This is something that we can — there’s no one that should not be educated. And the anti-AI, or climate change, right? I mean, I do think that using AI, will we be able to solve the problems that we have with climate change? Will we be able to engineer things that will help with the rapid rate of climate change? And a lot of the AI doomers or AI naysayers, who don’t want the data center built in their backyard or a data center built anywhere, are ignoring the fact that there are many different aspects of AI that will be good for humanity.
And does it require great change? And is change scary? It is, and it will require change. It will require change from all of us. But the end point is actually quite beautiful.
01:05:58 BARRY RITHOLTZ: I like that. You’re such a techno-optimist. All right, let’s jump to our favorite questions, starting with who your mentors were who helped shape your career.
01:06:09 ANKUR CRAWFORD: Oh gosh. I think that’s a pretty easy one. Our CEO Dan Chung has been pivotal in my career growth. And I told you, he hired me from Stanford without my knowing anything — I really knew nothing about this business.
And he recognized that. Why not take a shot on someone who’s non-traditional? And he himself is a non-traditional thinker. He was a lawyer, and he thinks very much outside of the box. So over the years he’s challenged me in ways that have been sometimes frustrating.
But I learn from it. He pushes me in ways that sometimes I don’t understand, but again, I learn from and grow from. So yeah, I think Dan’s like my number one mentor.
01:07:11 BARRY RITHOLTZ: Let’s talk about books. What are some of your favorites? What are you reading currently?
01:07:15 ANKUR CRAWFORD: So my favorite book is a book called Think Again. It’s by Adam Grant.
01:07:15 BARRY RITHOLTZ: Oh, of course.
01:07:15 ANKUR CRAWFORD: Who’s an organizational psychologist. And I know it’s an odd — was he at Harvard? Wharton?
01:07:24 BARRY RITHOLTZ: Wharton, I think.
01:07:24 ANKUR CRAWFORD: Yeah. And I know it’s an odd book to be a favorite book of mine. But in the context of business, it definitively is. And in part it’s because it talks about how you can have a hypothesis, but you have to be humble enough to understand that you can also change your hypothesis — but you have to have the confidence enough to hold a hypothesis.
And really, intelligence is about the ability to morph and be nimble. And it’s not about arrogance. Our business requires a constant questioning of what you think, right?
And those that become very tied to a thesis end up, I think, on the wrong side of a lot of trades. And so I just loved the book because of the way he writes about intelligence and the humility of questioning, and of holding conversations with people. And I think this is true for society in general right now — of having conversations where you may not agree, but to hear other people out, even if they don’t agree with you.
01:08:53 BARRY RITHOLTZ: Anything you’re reading currently?
01:08:55 ANKUR CRAWFORD: The last book I read was the recent one by Brad Jacobs, which was How to Make a Few More Billion Dollars. Brad Jacobs is the CEO of QXO. And he wrote his first book, How to Make a Few Billion Dollars.
And then he wrote How to Make a Few More Billion Dollars. And what I thought was so interesting about the book is the first two chapters are about how he centers himself. And he’s an incredibly successful entrepreneur, has built many businesses really from scratch — he’s a self-made billionaire — and he starts every morning meditating, right? And how he finds that center.
And to me it’s — we often don’t talk about that aspect of investing and business. It feels sometimes really transactional. But hearing that aspect of Brad, it only puts him in even higher regard for me.
01:09:58 BARRY RITHOLTZ: Hmm. Really interesting. What are you streaming these days? What are you either listening to or watching?
01:10:04 ANKUR CRAWFORD: Oh gosh, I don’t watch much. I don’t have that much time. And usually when I do watch something with my kids, I fall asleep. But I am a runner, and so I have a lot of time that I spend running, and I’m constantly listening to podcasts.
My favorite ones happen to be MacroVoices. I love The Knowledge Project.
01:10:26 BARRY RITHOLTZ: Oh, Shane Parrish. Yeah, he’s a regular on Sunday mornings for me.
01:10:31 ANKUR CRAWFORD: Yeah. And so, I mean, the variety of conversations that he has with different people, from wellness and wellbeing — I was listening to one about the Alpha School and how education should be reshaped. There’s just an awesome amount of diversity of thought.
The Circuit, which is all about semiconductors and chips. I’m trying to think of other ones that I listen to regularly. That’s all that comes to mind.
01:11:04 BARRY RITHOLTZ: That’s a nice list. To start with our final two questions: what sort of advice would you give to a recent college grad interested in a career in either engineering, materials science, or investing?
01:11:18 ANKUR CRAWFORD: Oh wow. Well look, I think for any college grad, make sure that you do something that you love, right? And it doesn’t have to be that you love it every day, but you spend a lot of your time at work. A third — more than a third — of your life is going to be spent from here on out at work.
Make sure that you do something that you believe in, that gives you great gratification, that you feel like you’re contributing to society. Don’t just do it because you’re on a treadmill of, I’m going to go do this because I set out to do this path and I just have to go trotting along. Allow yourself the grace to change and to change your mind. I did, and it was probably the best risk that I ever took.
The best gamble that I ever took on was completely pivoting in my career. So allow yourself to explore, because you change over time as well. What you want today may be different from what you want in five, in 10 years. But definitively, make sure that you love what you do, because once you know that you love what you do, you will be the best at it.
01:12:40 BARRY RITHOLTZ: Huh. And our final question: what do you know about the world of investing today that might have been useful 20 or so years ago, when you were first starting out?
01:12:53 ANKUR CRAWFORD: So you told me this question would stump me, and it is stumping me.
01:12:58 BARRY RITHOLTZ: Well, the answers that I’m not looking for are, you know, buy Amazon in ’02 when it was $7. It’s what insight might have been useful way back when. What have you learned? What expensive lessons came along that, you know, I could have saved myself a lot of headache had I figured this out sooner?
01:13:23 ANKUR CRAWFORD: You know what, Barry? I don’t think I would — in my way-back machine, I wouldn’t go tell myself anything.
01:13:30 BARRY RITHOLTZ: So it’s the path, and not necessarily —
01:13:32 ANKUR CRAWFORD: Yeah, it’s the journey. My most painful moments as an investor have been the biggest learning moments for me. They’ve branded me in some way with that experience. And so I wouldn’t want to shortcut that, because it has shaped me. And every single time I’ve fallen on my face, it has shaped me and it has reminded me of the perils of not paying attention to X, Y or Z. Or, I won’t make that same mistake again. Because again, it goes back to that first question you asked me about academic versus learning on the job.
01:14:20 BARRY RITHOLTZ: You need the real experience. You need the scars. You need the —
01:14:22 ANKUR CRAWFORD: You need the experience, you need the scars. And it’s a little bit like your kids, right? You can tell your kids, don’t do that, you’re going to get hurt. Don’t do that, you’re going to get hurt. Well, sometimes they just have to fall down and get hurt to realize they’re going to get hurt.
01:14:34 BARRY RITHOLTZ: Makes a ton of sense. Ankur, thank you so much for being so generous with your time.
We have been speaking with Ankur Crawford, portfolio manager at Alger. If you enjoy this conversation, well, be sure and check out any of the 653 we’ve done over the past 12 years. We launched July 2014. You can find those at iTunes, Spotify, YouTube, Bloomberg, wherever you find your favorite podcasts.
I would be remiss if I didn’t thank the crack team that helps put these conversations together each week. Alexis Noriega is my video producer. Sean Russo is my researcher. Anna Luke is my producer. I’m Barry Ritholtz. You’ve been listening to Masters in Business on Bloomberg Radio.
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