Invest Like the Best with Patrick O'Shaughnessy
01:00:29 · Alex Sacerdote
[01:00:29] S2: I would like to say that we're so advanced in our AI systems that it's a huge change. But so far, it's helping us get up to speed and we have a handful of great apps. But it's not supplanting the job of the analyst. And so much of what we're doing is we're meeting with as many companies as humanly possible. We're developing relationships with the management teams that we cover. We're talking to the competitors. The system we use is right out of common stocks and uncommon profits, which was written by Philip Fisher in the nineteen fifties. And it's the scuttlebutt approach. It's growth investing. It's get out there and talk to suppliers, customers, competitors, looking for the key characteristics of these leading companies and really developing conviction in them. Now if it's a new complicated area like ABF substrates or PCBs, we're able to get up to speed on those things quickly, but it can't pick stocks for you in any kind of a way. I will say that if you're an analyst who's good at the blocking and tackling, there's a role for that, but you need to have obviously the insight on top. So we're now like using AI to write notes or review the quarter, and those notes are much better, but there better be a really good paragraph on top, which is the wisdom. What does this mean? How does this deal with our thesis? What changed? Don't just be a reporter. So the AI can be a great reporter. It can't pick into the future. The job that the guys did on app eleven two years ago, I think we got two of the best ad tech guys. I knew ad tech. I started actually nearby here in New York at an internet advertising startup. And after I did banking, I knew internet advertising and ad tech, is historically a terrible industry. But Michael and Sam really figured out the AppLovin story before anybody and they followed it when it was private. They know all the competitors. They know all the intricacies of terminology. And Sam went to the Las Vegas App Advertising Conference, and we went to con, and we talked to scores and scores of people. So did the work on the model and developed a great relationship with Adam Feroge, he's one of the best managers out there. I don't see AI doing that.
01:02:54 · Patrick O'Shaughnessy, Alex Sacerdote
[01:02:54] S0: What role does talking to other investors outside of your firm play in your life? [01:02:59] S2: One of the great things is just the friendships I've built with so many smart investors. And frankly, Philip Fisher said, part of his process was get to know a good 10 or 15 like minded people around the country and share ideas. They're great friends to make a lot of them have been on your podcasts. You develop good friendships and then you share ideas, talk ideas. It's important that it's a two way street. I call it the tripod when I like something and then my analyst likes it and then somebody who I really respect also likes it, that's three legs of the stool can really help the conviction. [01:03:40] S0: What have you learned about shaping the products that you offer your investors across the history of the firm? It's not just one monolithic structure anymore. There's several things that if I'm an investor and I wanna give you money, there's a couple ways I can do that. How did you arrive at those things and how can you turn that experience into advice for other investors that are trying to provide their LPs with the right set of options?
01:04:05 · Alex Sacerdote
[01:04:05] S2: So the first fifteen years, it was a long short fund and we wanna be focused. And if you defocus, that can be hard. So we grew that and we got that to the scale that we wanted to. We're 20 years old. Maybe ten years in, people started to ask for a long only product. In 2020, we launched the long only fund. So we're six years on that. That's now larger than the long short. The bulk of the assets are in these two. Sometime in maybe 2015, we formalized that we might be doing privates, and so we gave investors the option to opt in or opt out. And you could do 15% or 25%. So we didn't break the seal on the privates until 2020. In 2021, we offered a hybrid fund that could be 80% into privates, sort of similar approach, but if you wanted more exposure to privates. Very recently, we launched the Whale Rock Mega Cap Tech Fund. We just think there's a huge structural underweight of the largest tech companies in the world. We also realized that a lot of our performance over the years was from some of the largest companies, whether it be Apple or Amazon or Tesla. And so a lot of our largest pools of capital endowments or what have you, they realized they've been massively underweight the largest tech companies in the world because they have a lot of privates, they don't have a ton of public, and then maybe half the public is international. And then of their public bucket, there's a belief that there's no alpha in large caps, so they underweight large cap and they have a lot of small and mid managers that are stock pickers because it's intuitive that large cap can't have alpha. And then in their hedge fund portfolio, even if it's long biased, they're not gonna have 15% in Nvidia and all these other things. We realized that people are worried that there's these big companies. This is just a product of the digital economy and that in tech, the leader usually grows bigger and wins and develops very high market share quickly and there's great competitive advantages. They're also selling around the globe. So this is gonna lead to massive profit pools and massive market caps. And it's just gonna happen in the future. Most endowments are betting against this because they're completely underweight this. Finally, somebody came to us and said, what should we do? I'm on the board of Hamilton college and on their investment committee, were trying to figure out this.
01:06:40 · Alex Sacerdote, Patrick O'Shaughnessy
And so we kept on hearing it. And finally, we said, we'll do this for you because there's a lot of alpha to be had. And the mag or the FANG or whatever, it's gonna be different. In 2022, they all rallied. Last year, they were very divergent. And this year they're down. And so we created the Whale Rock Mega Cap Tech Fund, which is the universe is the top 30 market caps globally. And then we pick the 12 or 13 that are the best. I think there's tremendous alpha in the largest cap because if you think about it, a small cap, it just takes one person to figure out it's good and move it up. But it takes a 100 people, a 100 diversified PMs to realize Google's not a loser, it's a winner. And can we figure that out before 95% of those generalist PMs? And we've been able to do it [01:07:31] S0: You like your odds in that. [01:07:32] S2: Yeah. We like your odds in that. And so there is alpha to be had there. And then as an asset category, it's great because these companies by definition have wonderful motes. And maybe they're not the super s curve, but sometimes they are. I mean, Nvidia sure is. And TSM is really levered to it. And Hynix is extremely levered to it. And ASML is levered to it. We're four months into that one.
01:07:32 · Alex Sacerdote, Patrick O'Shaughnessy
[01:07:32] S2: Yeah. We like your odds in that. And so there is alpha to be had there. And then as an asset category, it's great because these companies by definition have wonderful motes. And maybe they're not the super s curve, but sometimes they are. I mean, Nvidia sure is. And TSM is really levered to it. And Hynix is extremely levered to it. And ASML is levered to it. We're four months into that one. [01:07:59] S0: It sort of sounds like really what you've built is a research machine to understand the world through the lens of companies. The thing you're constantly trying to improve is that research machine and then the way that you would then express that through products is multiplied. But if I was to try to understand Whale Rock, it would be to investigate the research machine first and foremost.
01:07:59 · Patrick O'Shaughnessy, Alex Sacerdote
[01:07:59] S0: It sort of sounds like really what you've built is a research machine to understand the world through the lens of companies. The thing you're constantly trying to improve is that research machine and then the way that you would then express that through products is multiplied. But if I was to try to understand Whale Rock, it would be to investigate the research machine first and foremost. [01:08:17] S2: We call it the Whale Rock Learning Machine and it's a group of 10 highly experienced individuals. Warren Buffett reads books and we read books and we read blogs. In tech, you gotta go out and talk to people. So we do 2,500, 3,000 face to face meetings with management teams. Munger and Buffett talk about compounding knowledge. We've been compounding that knowledge for twenty years. There's changes to the team, but broadly there's a lot of consistency to it. Andrew and Michael have been with me for eighteen years and the average experience level on the team is ten or so years, and that includes some of the newer people. That research engine can support all these products. And it's the same people that do publics and the privates. So we're not gonna scour the world and turn over every a b. But when we see something that fits into our system, we're able to act on it. It's so much fun to [01:09:13] S0: do this with you. When I do this, I ask the same traditional closing question of everybody. What is the kindest thing that anyone's ever done for you?