Welcome to Inside Active, a podcast about active managers that goes beyond sound bites and headlines and looks deeper into their processes, challenges and philosophies and security selection. I'm David Cohne, i lead mutual fund and Active Research at Bloomberg Intelligence. For the past few years, markets have been driven by a narrow set of companies benefiting from powerful structural trends,
most notably AI. But as those trends become more widely recognized, the challenge for investors is no longer just identifying them. It's figuring out where the next layer of opportunity lies in what's already priced in. Today, I wanted to explore how an active manager navigates that, how you separate durable growth from how you build conviction and a concentrated portfolio,
and where the market may still be underestimating change. One to me discuss this is doctor Acre Crawford, executive vice president and portfolio manager for Alger, including the Alger focused equity fund ticker alg r X and the Alger Concentrated Equity ETF ticker cn eq Encore. Thank you for joining me today.
Thanks for having me.
David so Alga is known for its positive dynamic change philosophy. How do you define that in practice? And you know, what does it look like in a portfolio today?
Yeah, I think in order to understand what that positive dynamic change means, I you know, it's important to understand the pillars of how we get there. There's two fundamental kind of philosophies that feed into positive dynamic change. The first thing, looking for companies that are simply growing right their market disruptors. Their top line is growing at a at a rate that is impressive and significant. Generally, there's a product that is very compelling and they're market share gainers.
So that's like a typical growth a company that we would we would classify as change because they are changing the market around them and challenging the current state of affairs. On the other side of the ledger, we have what we call life cycle change. And life cycle change is interesting because a lot of growth managers don't think of this as growth. It is companies that may have gone through their their their growth kind of period and have now saturated their markets and they have to decide who
they are. So are they going to continue growth or are they going to you know, just milk what they have and go into kind of a harvesting phase where they have low growth. And what we're looking for is companies that are either going to take advantage of a changing market or they're going to restructure their business such
that they become growth businesses again. And the benefit that you get on this side of the ledger of life cycle change is oftentimes these companies look like they're almost value companies, but we think they're just unrecognized growth and you know, you get the benefit of not only the multiple expanding, but the earnings start starting to surprise to
the upside. So both of these are change factors. Whether that change is coming because the market is changing, the environment is changing, the company is changing, or the CEO is changing, right, And those change factors are often underestimated by the market, and that's that's really where their opportunity for us lies.
So, I mean, when you're evaluating a company, what do you think actually separates you know, durable, compoundent growth from companies that may just be riding a hype cycle.
You know, when we look at businesses, we actually look at them on a three to five year perview, and the reason we do that is because we don't want a company that has a hype cycle behind it that's a one year hype cycle. So by looking at companies over a longer period of time and understanding what they blossom into, it forces you to ask the question, is
this hype or is this durable growth? So I think it's just a natural part of our process, Like we would never pay for a company that has a one year cycle, and we would never pay a high multiple. I remember when I started this business, people would be like, well, what are they growing next year? Let's put you know, whatever that growth rate is, let's put a thirty multiple on that. Like, if it's a thirty percent growth, let's
put a thirty percent thirty multiple on that. It's kind of like a one peg and it would always be funnel me because I was like, well, what if the growth ghost is the next year? You know, at what point do you what point do you make that in? And that's that hype cycle. So if you think in in phrases over a three to five year period, I think it's much more powerful because you kind of separate the winners from from just the hype.
So I guess if we go a little bit deeper, can you kind of walk us through your research process, you know, like from you know the start to you know, actually having high conviction. You know, what are these signals that really kind of move the company from you know, hey, this might be interesting to you, just could really be a high conviction pick for us.
Yeah, I think it. You know that the process, whereas it's hard to say where exactly it starts, sometimes it is a kind of a top down point of view, in which case, like if you think about AI right, that that thinking really came from a more top down point of view. And we then identified the company needs that we're net beneficiaries, and then our team worked on understanding the nuances of each of those companies and identified
where the bottlenecks or where the beneficiaries would lie. On the other hand, we identified who would get impacted negatively
and position portfolios that way. But the but the research process is actually quite deep in that you know, not only do we understand and dig into the quality of the management team, but you know, the durability of the businesses, the competitive dynamic, the you know, the the kind of margin progression and the revenue progression ends up being incredibly important as we think about the durability, you know, the team like we What I would say about Alger is
that we have a team that is probably outsized for the assets that we have, and in part because our research effort is so deep that you know, I think we're we're one of the biggest users of a guidepoint on on the street, and in part because we want to understandstand the fundamental dynamics that is driving the revenue growth, like what are the structural advantages that businesses have to outcompete others? You know, are they becoming a oligopoly? Are
they do they have pricing power? Will the market allow them to have pricing power? Right? So, these are all the questions like what is the technology? You know, what is truly understanding the base level of that technology and what the base level of the product is key. The effort is actually kind of a very holistic effort that that we put forth in order to make decisions as to you know, where to invest.
So I do want to get to the you know, pricing power just a second, but I kind of want to just have one more question. You mentioned both you know, top down themes like AI and you know, then you're combining that with bottom up stock picking. Is it one or the other that actually drives decisions or you'd say it's kind of like a combination of both.
It's probably a combination of both. But what I would say is fundamentally we are stock pickers. You know, our philosophy lends us to pick great stocks, and if you look at our alpha, historically it has generally come from that stock picking versus you know, and look AI, I think is a very different theme that is so powerful that you know, it's kind of top down and bottoms up.
But you know, I would say, historically we happen to be very good stock pickers, and I think that our philosophy lends itself to it because we're always looking for what's changing on the margins.
So, you know, as I said, I wanted to talk a little about pricing power because c neck I'm not sure if you call it that or just as an EQ you know focus EQNQ, you know, focuses on companies you know, oligopies or you know, or companies with you know, monopolistic characteristics. If I'm saying that correctly, what are the specific traits it really signaled pricing power to you?
Oh gosh, so you know, it could be it could be many things, right in but in part, when you have markets that have one to three players, that automatically tells you something about the market, right it tells you something about the margin structure. And when that market begins to grow, the net beneficiaries of that are only one to three players, and if the barriers to entry are very high, then they have pricing power. Right. So if I think through, for example, the competitive landscape, and I'll
I'll make this super simple to think through. If you have a company that has an incredibly high margin but the barrier to entry is very low, it will naturally
attract capital. Right. If it's if the technological mode is too low, then it will attract capital into that market and the margins will shrink to a point where it doesn't make more sense for other competitors to come into the market when the barrier to entries are high, whether it's a data mode, a technology in mote and there are only a few players, as what has happened in the semiconductor industry recently, where you know, over the last
two decades, the market is consolidated because it was so difficult to kind of cross the chasm with every next node. So all of a sudden, we have these markets that are effectively duopolies with very high barriers to entry, and therefore they have pricing power. So as you go through looking at pricing power, it's imperative to understand the competitive dynamic, how that competitive dynamic is changing, and how the market
is moving. So I would say, you know, in a nutshell, we're looking for businesses that you know, have high barriers to entry so that they can maintain pricing power.
Yeah, I do want to ask, you know, especially if we're talking about AI tams. You know, there's thought that some of these companies are trading at pretty high premium multiples. How does valuation kind of play in your process?
Yeah, so you know, I'd like to take contention with that that, like what everyone thinks that these these companies are trading at high multiples. And it was just this year that Nvidia was trading at something like a sixteen multiple, which is a sub market multiple, and even today I think it's trading in line with the market and people I think they have it's this misnomer of the stock has gone up a lot, therefore the multiple must be high.
What I think has been largely missed in over the last two and a half years, is that the numbers have also come up significantly such that the multiples have actually contracted in some cases. So we look at you know, Taiwan Semiconductor for example, it trades at a mid teens multiple. You know, to me for one of the most strategic assets on this planet, that does not seem that egracious. You know, it is by far what I would call a one and a half player market with incredible margins.
And you know, something ever happens to SMC we go into a global depression, yet it trades it a fit that a mid teams multiple. So I would take a little bit of issue with this like misnomer that we have these incredibly high multiples in the AI space. Now I think in some of the private markets maybe maybe that's true where the where the multiples are significantly higher and they're like revenue multiples. But that's like a different
ball of wax. So, yes, valuation does play a role in how we think about growth, and you know, you always what we we are cash flow investors. We want to know that that growth will yield cash flow. That is a kind of every single model that we build or every single company that we look at is backed by a DCF or a discounted cash flow model that yields for us a price target. And it is one of the keys to our of how we get to
the valuation. It's not simply PE or PEG or it is based on cash and you know, the terminal growth rates, the terminal values, like all of these things play into our thinking about the valuation. So it is imperative that whatever company we own will they may not be you know, generating a lot of cash today, but as they grow into the business that we expect them to grow into, that they really start to show us the leverage, especially on that free cash flow.
Okay, and you also, you know, your portfolios are fairly ir relatively concentrated. You know, what gives you the conviction to hold say third to fifty names versus a more diversified approach.
You know, I think that a having high conviction as a function of our research process. We have a team of incredible analysts that you know, that are digging up what is a differentiated viewpoint And once you can establish that that differentiated viewpoint, it's actually easy to understand who the winners are and how a stock will progress even if there's a little bit of volatility. And you know, let me give you an example of a stock that
has been recently pretty volatile. It's a company called QXO. And just this morning I was having a discussion with our one of our analysts, and as we're going through the model, I was thinking, Okay, based on these numbers, we believe they'll earn x and twenty thirty and therefore this stock should more than double over the course of the next three years, right, And let's test our conviction level on that statement. And so we went through and
kind of re underwrote the assumptions. And you know, they just did a new acquisition recently yesterday of Top Build, and it took the it took the market a little bit by surprise. But we want to re underwrite our assumptions, you know, stress test them and say what number do we get to. So if I look at this business over a three four year time period, what does it earn and how much do we think the market is willing to pay for that such that we compound the
growth over many years. And let's hypothetically say, for example, QXO is going to earn. You know, I'll just give you kind of the street number, six billion dollars. We can then underwrite that and say, okay, well, if they're going to if there's if there ebit does going to be six billion, how much should we pay for that
in three years? And what's interesting is that if you can underwrite a company that's going to double, if not more than double, then it's a matter of patience and watch execution and understanding your management team because they're at the stewards of your capital. So that's what that's what gives us the conviction to hold through periods of volatility, understanding where a business is going and having conviction in our underlying numbers over not just now, it's over a longer period of times.
So you know, an extension of that, you know, if you have this conviction, how do you determine position sizes? Is there something that helps you determine what would make a smaller position versus the larger in the portfolio.
Yeah, So when you have a twenty to thirty stock portfolio, like the tail end of your portfolio can't be filled with smaller positions. So every position really has to have a meaningful impact and Look, I'm as a you know, as being trained as an engineer. I like to do things like super mathematically. Right, if you have a thirty stock portfolio, you take a undred percent divided by thirty names.
You know, a average position side should be three point three percent, right that that is just like the contribution of each The more conviction you have, the higher it gets above that's three point three percent. The lower conviction you have, the lower it gets on that three point three percent. And you know, there's a little bit of differentiation in the portfolio in part because the benchmark that we compete with, which is the Rustle one thousand growth,
has incredibly weighty positions. So when you have nine to ten percent positions, it becomes more of an exercise on what is the active weight that I want to express in a business that is that we feel bullish about. So that's a little bit on the weighting. But and I would say that that the very top of the portfolio we have to think about the active weight contribution and for the rest of the portfolio you kind of divvy it out like I described.
So, I mean, is there a you know with concentrate? You know, I always bring up you know, risk. How do you think about risk or is there risk management process? Is it kind of volatility, capital loss or something else that you know you're really keeping track of.
Yeah, So it's interesting because as you run more concentrated portfolios, your risk becomes not sector risk, it becomes single name risk. And so the key for understanding the risk in your portfolio is actually understanding where each company sits and you know where, and understanding that the core of these businesses very well. Because again it's all like it's no, it's
not necessarily the sector risk you're taking. It's the execution by the management of the company that you own becomes probably one of your biggest risk factors, and whether or not they can execute that's you know, it is a diversified portfolio. So what we're always trying to do is find the best companies inside of each the best companies on this planet, really a lot of which reside here here in the US. And you know, I think we have to be mindful of the volatility. I e. It
can't be a full on AI type portfolio. It needs to be diversified because that is the mandate that our clients have requested of us. And so there is companies like GFL Waste, which is a waste company, but it has an interesting story behind it that we think that it can drive the position, you know to or drive the stockwatch higher in terms of value. Or Pico, which is a very unique company that has incredible pricing power
that sells airplane parts. So you have to diversify a cross kind of end markets in order to create diversification and capture growth and and mitigate risk.
What would typically cause you to sell stocks fundamental deterioration, valuation, or just better opportunities.
It could be that we're just wrong, right, We could our thesis could be wrong. I would say one thing is, you know we are we are incredibly humble, like we don't stick to a viewpoint and say we cannot be wrong because we had this three five year view. If
if something fundamentally changes, we we do we are. We have the socratic process where we're constantly asking questions and and if all of a sudden there's like thesis creep and we start noticing that there's thesis creep in the way we're viewing the company, I would say that that would be you know, a flag or a yellow flag. As to whether or not the company should be sold.
Other times, it could be that the stock is appreciated much faster than we expected, so it's pulled forward the anticipated return that we expected and the risk reward is simply not the same anymore. You know, where we thought there could be one hundred and fifty percent upside over three years, all of a sudden it appreciates enough such that there's fifty percent upside over three years, which again
is then not really a compelling return from them. So that would you know, that would inspire us to trim, if not sell the stock. Or there could very well be like what you mentioned last, that the opportunity set is changing, and you know, one stock might be up and the other one has gone down, and you just flip flop and to a different into something that has
a better risk reward, you know. And we did this recently, well, not that recently, I guess it was a few months, four or five months ago from you know, we we owned Vertive, which is a cooling company in CNEQ sold Vertive because you know, all of a sudden, we thought the upside was still significant, but the upside in GeV was more immediate, and we we flipped into a different stock.
Now both have done well, but you're counting on GeV to have just more immediate upside and and longer three or three year long upside, which which is which has happened?
So then how do you handle being early versus being wrong, especially in you know, fast moving themes.
Ah, that's a great question, you know. I think really understanding a business allows you to have the conviction to hold if you're early. And I'll give you an example. You know, we wrote this paper in three years ago. It's called AI and the Declining Cost to Create and it basically went through how artificial intelligence is going to
recavioc in software. This was probably an effort that was a two to three month effort in researching and talking to experts in the industry, and a lot of the experts actually disagreed with this viewpoint, but it was very clear that one of the modes for software was starting
to come unraveled. And once we saw it, it was all almost like you couldn't unsee it right, And that conviction allowed us to hold that thought over the last three years kind of get us out of long held beloved software positions that we had held in the portfolio. For many, many years, and it allowed us to hold our ground because we were early. The market didn't believe it, you know, a lot. We got a lot of pushback from like if we would ever just float this to
to kind of industry insiders. There was a lot of a lot of pushback, but we ended up being right and you're seeing it today in the market. So we were early now, you know, to some extent, it didn't hurt us because you know, software didn't perform the way you know, semiconductors or the rest of the AI food
chains performed, and where we put the capital. But really the crux of it is is truly understanding and having a well researched thesis so that you're not wrong and you know, but I will say, but also having a humility to accept that you could be wrong. You know, so I've given you obviously like one of our big successes. I'm sure I could pull out one that we've been wrong on, but but yeah, or I'll give you another example like TSMC. I would say that we were early.
We started buying this when you know, when it was eighty and I remember we started buying it, and we bought it because it was trading at twelve times cash flow, right, and I mean we were sitting here thinking, my gosh, you know, how is it that the most strategic asset in the world, that is going from a three player
market to a one and a half player market. And at the time, it wasn't that clearer that Intel and Samsung were going to struggle as much as they did, But that was one aspect of our bullishness because we felt that they were going to struggle. You know, there was this overhang that China was going to invade Taiwan, so you know, there was a lot of kind of like dark clouds over this company, but it fundamentally is
one of the most strategic businesses. So you know, we held that point of view that even if it is a three player market, it shouldn't trade at twelve times. We held the point of view that China wouldn't be invading Taiwan, at least not at that moment in time. We watched the Taiwanese elections, we saw that it was likely not going to happen like that they were not going to be replaced with a new party, and it all gave us conviction to buy more of the stock.
But that was very counter to you know, what the rest of the market was thinking.
So you've been, you know, pretty vocal about AI being a generational opportunity. Where do you think we are today in that cycle? And you know, where do you think the market's still underestimating its impact?
Oh gosh, David, look, I think I don't I don't know about the market. I would say that people are still very confused. You know, people are pretty still very confused about you know, what AI can do. Are we in a bubble? I just feel like we are in like such the early early innings of artificial intelligence and its capability, and as it becomes more democratized, the real power of this technological it's not even an evolution, it's
a revolution, will become evident to everybody. I think that there's a lot of like concern for the market or from the from the people that you know, AI will I don't want this data center in my backyard or and in part I think it's because they don't truly understand how capable this technology can be. And if we don't build it here, someone also build it somewhere else. I think that there's just a lot of misunderstanding about artificial intelligence on a kind of human level as well
as in the markets. I mean, I've heard so many people I get asked this all the time, like are we in a bubble? And I'm just like, I like sometimes look at people who ask me that, I'm like, gosh, like, go try and use these tools before before you ask that question. Because once you start to use the tools for more than an alternative to search on, you truly
ask it to do things for you. I think you'll be mind blown and you'll understand how much compute we're going to use and why people are spending this kind of capital in order to support this industry. And look, I've held the belief that I think in twenty four I was pretty public about my viewpoint that capex is going to go up in twenty four, in twenty five,
twenty six, twenty seven, and twenty eight. And that framing comes from the viewpoint that the amount of computational need that we will have is going to grow logarithmically like it's going to be an exponential growth, right, it is not linear. And you know, if you build a supply demand model for tokens, it's quite clear to see how
this is quite feasible. And look, the only fly in that ointment is if we get algorithmic changes that allow us to do more compute or more intelligence with less compute on a large scale basis, like two three orders of magnitude, right and then, but that's a technological shift that if that's going to happen, we hopefully catch.
Well, it's definitely going to be exciting to watch. Unfortunately we need to end here, but core, this is a fun discussion. Thank you so much for joining me.
Oh thanks thanks for having me David.
I also want to thank our listeners. If you liked the episode, please share it, subscribe, and leave a review. If you'd like to see more of our research on the terminal, go to bi fund, go for fund and Active Research until on next episode. This is David Cone with the inside Active
St