Lead-Lag Live

The Rise of Intangible Value Investing with Kai Wu

• Michael A. Gayed, CFA

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Warren Buffett himself called our economy "asset light" – and for good reason. Today's most valuable companies derive their worth not from factories or equipment, but from intellectual property, brand equity, human capital, and network effects. Yet traditional value investing metrics, developed in the industrial era of railroads and utilities, completely miss these crucial drivers of modern business value.

Kai Wu, founder and CIO of Sparkline Capital, takes us on a fascinating journey through the evolution of value investing and explains why it's due for a radical update. With 50-80% of US company balance sheet value now coming from intangible assets, investors relying solely on price-to-book ratios find themselves increasingly unable to identify true value in today's markets.

The problem extends beyond mere definition. Our accounting standards systematically distort company valuations by expensing rather than capitalizing R&D and other intangible investments. This creates the paradoxical situation where companies investing heavily in their future appear less profitable in the present – a disconnect that creates tremendous opportunity for investors willing to look deeper.

Sparkline's innovative approach leverages artificial intelligence and big data to analyze unstructured information sources, from patent filings to social media, quantifying what traditional financial statements miss. This methodology bridges the growing divide between growth and value investors, applying timeless valuation principles to the digital economy.

Wu shares a compelling case study of NVIDIA, which Sparkline owned when it traded at a seemingly astronomical P/E ratio of 100. After adjusting for NVIDIA's extraordinary intellectual property and innovative culture, their models showed the stock was actually undervalued – a perspective completely missed by traditional metrics.

For investors looking to apply these insights, Sparkline offers two ETFs: ITAN for US markets and DTAN for international developed markets. Both funds seek companies rich in intangible assets but trading at reasonable valuations – essentially value investing adapted for the digital age.

Want to dive deeper into Kai's research? Visit sparklinecapital.com to explore his published papers and learn more about investing in the intangible economy.

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Speaker 1:

Was there some point in history where that definition change, you think, kind of took place that made intangible value more the proper way to think about?

Speaker 2:

value investing. You know, fast forward to today, 100 years later, and it's Google, apple, nvidia, companies for whom intangible assets, or what matter, and physical capital, tangible capital is, you know, not really relevant for generating earnings, really relevant for generating earnings. And even Warren Buffett himself, who, of course you know is a disciple of Ben Graham and a direct student of his, you know, back in the day, has called the economy asset light and pointed out the fact that, you know, companies today are no longer like the exons of the world or GMs, where it's intellectual property, brand, human capital, network effects that drive earnings today.

Speaker 1:

I love this graphic because you really kind of break it down in terms of where the companies fit in. Talk to me about turnover. When it comes to this kind of framework meaning, do a lot of companies tend to go out after some period of time, come in? How does that look?

Speaker 2:

Yeah, I mean there is certainly turnover. It ends up being kind of roughly the same as a more traditional value strategy to think like you know less than you know less than over. The holding period on average is over a year for these names and turnover can be driven by two things just mathematically. So of course there could be changes in the fundamentals. So imagine you own a company and there's these major scandals and the culture starts to decay and employees start to leave. That would be a negative change in fundamentals.

Speaker 1:

So we're going to be talking about a lot of interesting things here, A different spin on investing, focused primarily on the intangible value side of the equation, which I'm personally excited to hear more about. I've gotten to know Kai over the last I don't know six, seven, eight months. Always strikes me as a very thoughtful individual in the field, an entrepreneur which I certainly respect as one myself, and one that I think also a lot of you will enjoy hearing from. And, with all that said, my name is Michael Gaya, publisher of the Lead Lag Report. This is a sponsored conversation by Sparkline Capital, Kai Wu's firm. I got a couple of ETFs I'll touch on. But, Kai, introduce yourself to the audience. Who are you? What's your background? What have you done throughout your career? What are you doing currently?

Speaker 2:

Yeah, Hi, so I'm Kai. I'm the founder and chief investment officer of Sparkline Capital, so my firm is about five or six years old now. We manage two ETFs. One is called ITAN I-T called ITAN, focused on intangible value in the US, and then a second we launched last year called DETAN the same concept, but in developed market international space. My background before that was I co-founded a hedge fund in Boston systematic fund. We did volatility arbitrage and CTA trend following, and before that I got my teeth at GMO, so Jeremy Grantham's firm in Boston. That was just my first job out of college. I studied economics at Harvard and did my thesis in financial crises, so I've been doing a few things up until now. But I think all these kind of arcs converge in what we're doing now and I'm happy to get into it as we go along on this conversation.

Speaker 1:

I didn't know there was a way to study financial crises in a formal setting. I'm curious to hear more about that.

Speaker 2:

Yeah, so you know, basically I studied economics and Harvard's, obviously a liberal arts school, so it's pretty general. I graduated in 2009, 2010. So right around the aftermath of the globalances whether external credit, asset price or credit imbalances that could potentially proceed and predict, with higher than unconditional probability, a financial crisis. And we did indeed find that to be the case by looking at historical data from Sweden to Japan to the US, and so that was really interesting, kind of as a starting point, trying to get more into the you know, more into the you know asset pricing and evaluation side of things, because of course, my training was more liberal arts. And then, with a natural hopping point, to go to GMO as my first job out of college, where obviously Jeremy Grantham is well known for his work in predicting bubbles. So that was a nice transition just across the river.

Speaker 1:

So you had this really interesting career progression hedge fund, gmo, and then you had your own firm. You got into the entrepreneurship game. Let's talk about Sparkline Capital First of all. Why go that route? I mean, it sounds like you were at several kind of pedigree firms.

Speaker 2:

Yeah, look, I've always been driven in the industry by kind of solving the markets right. The intellectual challenges of trying to figure out how things really work and, on the research side, being in a boutique and being able to kind of drive the research agenda myself has been very rewarding, I think, does free us up at Sparkline toline to conduct research on topics that may at the time not seem obviously relevant or commercial but will over a longer timeframe prove themselves out. And so talk about the research agenda. Basically, gmo, in addition to their work on bubbles, has been really well known and the whole whole firm you know when I was there was over over a hundred billion dollars in assets was built on the back of being pioneers in quantitative investing. So you know, jeremy and his co-founders were really early in the seventies and eighties to be using computers to to find stocks that are undervalued relative to you know their fundamentals like book value, and so they were pioneers of what's now called factor investing or systematic value investing, obviously not specific to GMO, but just in general.

Speaker 2:

The value factor has struggled the past one to two decades as technology stocks. The Magnificent Seven have continued to do really well and your classic value stocks things like banks and energy companies, the kind of low price to book names, have not really done nearly as well. So the question we have tried to answer at Sparkline is why is it that value investing has struggled? Is it the case that value doesn't matter anymore and it's all just memes? Or is the case that it's merely just a question of measurement, that value principles still apply, but we need to be thoughtful about how to adapt the definition of intrinsic value to be more relevant to the modern day.

Speaker 1:

All right. So there's a lot of interesting direction to go with, and I've heard that argument that value is. It's not that value is underperformed, it's just that being defined incorrectly. Was there some point in history where that definition change, you think, kind of took place that made intangible value more the proper way to think about value investing?

Speaker 2:

Yeah, that's a really good question. I don't think it was any kind of discontinuous point in time, but if you do kind of go back a century right. So value investing the father of value investing was Ben Graham, so Graham and Dodd's security analysis investing the father of value investing was Ben Graham, so Graham and Dodd's security analysis, which is the kind of Bible of value, was written in the 1930s when the economy was clearly very industrial. If you've read the book, which is super long and many of the examples may not be that pertinent to today utilities, railroads, those are kind of the hot and big stocks of the day.

Speaker 2:

Fast forward to today, a hundred years later, and it's Google, apple, nvidia, companies for whom intangible assets or what matter, and physical capital, tangible capital is not really relevant for generating earnings.

Speaker 2:

And even Warren Buffett himself, who of course is a disciple of Ben Grimm and a direct student of his back in the day, has called the economy asset light and pointed out the fact that companies today are no longer like the exons of the world or GMs, where it's intellectual property, brand, human capital, network effects that drive earnings today.

Speaker 2:

You can also look at it from a macro standpoint. If you look at the GDP data, intangible investments, from a top-down standpoint, in the national accounts, surpassed tangible investment in the 90s and that gap has only widened ever since. So, whether you look bottoms up at the company level, top-down at the national account level, it's pretty clear that intangible assets are more and more important. My semi-estimate 50 to 80% of the balance sheet of US companies are now intangible, and so, to the extent where more traditional value approaches are focused on book value or tangible equity, they're going to miss out on a lot of these really important drivers of value, which also causes distortions with respect to a bias towards, say, asset-heavy businesses which, as I mentioned earlier, have not performed as well the past couple of decades.

Speaker 1:

When you say intangible, I think digital primarily, but let's talk about the types of intangible assets.

Speaker 2:

Yeah, yeah, so I touched upon them a second ago. So at Sparklin we have a framework with four different categories. So the first one is intellectual property. That's, you know, like patents, obviously would even trade secrets, I would say software, any kind of like know-how, would be in that category. Second, brand equity. That's pretty straightforward, think like Coca-Cola or LVMH. The third category is human capital. You know, this is the having a very talented workforce, but also having the culture be such that these people are all kind of rowing in the same direction. And finally, network effects. Think like Facebook or Google Search. Right, having you know this is the idea of increasing returns to scale. Whereas a network increases in size, it becomes more and more valuable, you know, as a function of the users. So these are the kind of the four main categories of intangible assets that you know, we believe, encompass, you know, most of intangible value today.

Speaker 1:

So I think the challenge you could put me wrong on this is how do you ascribe a valuation around each of those categories, right? It's like how do you consider if the market has priced in a network effect as being overvalued or undervalued? So let's talk about that. And then maybe also of the four categories. Do we tend to see cycles meeting there sometimes when the market favors brand equity over human capital? You know, let's go through that.

Speaker 2:

Yeah, no, that's a. Those are both very good questions, so let's do the second one first, because I think that is, you know, more easily answered. The answer is yes, absolutely Right, like one of the interesting story I could tell is that of Warren Buffett. Going back to you know what I said earlier. You know, when he first founded Berkshire Hathaway, his investments were primarily traditional value stocks, berkshire itself being in that category, and over time he kind of expanded what I call the investment moats to be more intangible. He met Charlie Munger. He invested in Coca-Cola, where brand was very important and human capital, the culture and the management he would always applaud. And then, over time, obviously the biggest investment over the past two decades has been Apple, which he valued for not just its brand and management but also the intellectual property and the network effects.

Speaker 2:

So my thought would be network effects is kind of the most recent one where, as the world became more and more connected by the internet and other telecommunications technologies, it's become more important because of course the value of network is a function of the number of people connected and the world become bigger and more and more connected over time.

Speaker 2:

You know, obviously, intellectual property and technology that the capital stock of the world has increased in that aspect only more recently, right Even going back 50 years. Obviously technology was an important element of what we do, but less so and same with brands. So I'd say that there's that time series element. There's also a cross-sectional element. One of the things that we did, as I mentioned, we launched an international fund and we did a lot of research to do that to extend the intangible value concept from the US to non-US countries, and one thing we found was that in the US, the intangible value concept from the US to non-US countries, and one thing we found was that in the US, the kind of primary driver of value was intellectual property, which makes sense since we had the best tech companies. But if you go to say Europe, it tends to be more brand equity that drives the value of these companies, which again makes sense if you think of LVMH and many of these kind of.

Speaker 1:

And I thought the next thing is you were talking about yeah, that makes total sense. Now, the moment you were saying that it's like, my mind immediately went to brand as far as luxury right On Europe, whereas in the US it is the IP.

Speaker 2:

Yeah, exactly, and so yeah, and to answer your second question, which is how do we measure it. I think that's like you know, and I can go on for the next hour about this if you want, but that's where it's easier said than done. Nobody, from an intuitive standpoint, would argue against the idea that we should be, to the extent we can, incorporating intangible assets into our measure of intrinsic value. Of course that's the case. Otherwise you're always going to be underweight or short. Nvidia and Google, apple, all these great companies but how do you actually do that? It's easier said than done.

Speaker 2:

So the first thing we did to try to attempt to measure this so this is kind of sequential is we tried to basically correct for accounting distortions that penalized intangible intensive companies. So not to get too technical, but basically when you do physical capital expenditures, so physical CapEx, that CapEx is capitalized, it becomes an asset on your balance sheet. You build a factory with $100 million. It's a $100 million asset on your balance sheet. You depreciate that over time. Now the inconsistency is that an intangible company that was trying to do the same thing, but doing it on the intangible side say doing research and development into a new drug or engaging in a marketing and branding campaign or investing in training employees, that this investment is not capitalized. Instead, it's expensed, meaning that these companies get a hit to their bottom line in that year and they don't get to grow an asset on their balance sheet, which is why I say Coca-Cola has no book value. And there is one more thing I should mention, which is that acquired intangibles do show up, because if I acquire another company, there's an item called goodwill that gets put on. But this is a further distortion in as much as it penalizes companies that do homegrown innovation, which is many companies and arguably a better way of building out a company's IP.

Speaker 2:

So the first thing we did was say what if we just treated intangible investment like R&D the same way as we do physical CapEx? And you can do that. And what you find is that it helps a little bit and, in other words, your portfolio as a value investor is a little bit less biased against technology stocks and healthcare and pharma, life sciences and consumer brands, but only a little bit less. And if you look at the performance of the value factor say Fama French, which is in a deep drawdown today relative to its peak in, say, 2007, it's a little bit less bad, but you're still deep in the hole.

Speaker 2:

So, the point being that this was okay, but it was no panacea, and if you think about why that might be the case, it just comes down to the fact that just think of this even more. Basically, if you fact that, you know, just think of this even more. Basically, if you have two companies that are engaging in R&D and one invents, you know, amazing, you know blockbuster drug and the other one, you know, can't pass trials, well, obviously, even if these two companies put the same amount of value in, the output is very different, and this is a feature of intangible assets, that there's kind of this non-linearity between input and output costs. And so we decided a better way. You know that the accounting methodology was kind of a non-starter that we can't look at historical cost-based analysis and we still have to look at the output of this investment, and that was kind of the next step that we went forward to.

Speaker 1:

How much does the importance of these different intangible assets change, Meaning, is there a volatility to brand equity? Is there a volatility to IP? I mean, I assume not, but I mean presumably there's an aspect there.

Speaker 2:

Yeah, I mean, it depends if you're asking at the company level or, like at the, you know, at the sector level. At the company level, definitely, you know, you have examples of. You know one thing I looked at was like Amazon right, when they first got set up in the late 90s, they were just an online bookstore, right, so they had you know good brand and you know some IP, but you didn't really have network effects. But over time, as they expanded into like the third-party marketplace, into AWS and other aspects like that, they their kind of network effects grew and grew and grew. They obviously became huge and they have this massive moat now with their logistics and distribution, and so that changed through time. Their brand arguably improved and obviously they've had some negative components as well. So, again, these things are dynamic. They do evolve through time, both at the overall level, as we discussed, but also at the company level.

Speaker 1:

We're going to get into the individual funds themselves. But OK, so you've got the framework. Us international side of things. Talk to me about people's understanding of the concept. All this makes a lot of sense, right, but I think people tend to be talking their old ways of analyzing markets. You find that it's hard to get people around the idea that value is just not defined properly, that this is a better framework.

Speaker 2:

Yeah. So you know, maybe before I yeah, so I think let's talk about two things. So first let me just go back to what I was saying. I want to kind of just finish that thread there on how we measure intangible value. And so if accounting is not the way forward, like, what is the path?

Speaker 2:

And you know, the insight we had was look, we actually live in like the 21st century where we now have access to what's called big data, right, just massive. Everyone. You know there's huge exponential growth in information available to companies that may exist outside of the 10K and 10Q. This could range from anything from trademarks to user-generated data, social media, right. All this information now exists about with potentially relevant information on companies. And so why aren't we using that? Because that would seem like a natural place to look for insights into companies and tangibles, and so we said that that's an interesting place, let's start with that.

Speaker 2:

But then the barrier we ran into was that this data is large and unstructured. So think about like an example of a patent. Intuitively, if you wanted to measure, say, google's IP, you would say, all right, let's read all the patents. There's thousands, hundreds of thousands of patents here, which is obviously time consuming but in theory, doable. The problem is you can't do it systematically. You can't just take a bunch of patent abstracts and throw them through a linear regression. Instead, you need better tools to process the text. So the first thing we did was we said let's just use a simple natural language processing tool, like just dictionary-based approach. So let's look for keywords, Because what we're trying to do here is to distinguish from lagging edge versus leading edge patents. So we can say let's just look for all patents that mention AI. Right, that would be one simple hack and you can do. You know more sophisticated versions of that and that's, you know, directionally helpful because it'll help you distinguish which. You know which companies don't just have a lot of patents but have really innovative ones.

Speaker 2:

But then over time, you know, we started doing more sophisticated techniques. So around 2019, 2020, you know, I wrote a paper where I kind of highlighted the potential large language models which underpin today's chat GPT as a way of taking this unstructured data and processing it into a you know, a factor or to a single score, and over time we used to train our own models, you know, from scratch, in-house and over time. Obviously, the providers, such as the open AIs and anthropics of the world have become so much better and have invested so much more resources into these foundational models. Now we utilize those, which has been a huge boon to what we do right, because now a greater and greater share of the insight in these unstructured data sets can now be measured.

Speaker 2:

I think the final piece I should mention is when we convert this into actual scores for companies. We are value investors, so we're not going to say, hey, which company has the most innovative patents? Because then you're just going to get Google we care about. You know which company has the most innovative patents relative to market cap? So it's more of a dividend yield or a earnings yield or, in this case, a patent yield. And we blend together all these different measures of intangible assets from IP side to brand, to human capital which companies have the most talent relative to the market cap, which have the most brand metrics and you come up with a single composite score for valuation. So that's kind of our overall process, where we are using large language models and AI merely as a tool not necessarily predict the stock price directly, but instead as a tool to take the unstructured information about companies that are kind of hidden in all these unstructured data sources and to create factors around the four pillars which we can then bring into the creation of a value factor.

Speaker 1:

I love that. The website sparklinecapitalcom for ITAN factor. I love that. The website sparklinecapitalcom for ITAN. I love this graphic because you really kind of break it down in terms of where the companies fit in. Talk to me about turnover when it comes to this kind of framework meaning do a lot of companies tend to go out after some period of time, come in? How does that look?

Speaker 2:

Yeah, I mean there is certainly turnover. It ends up being kind of roughly the same as a more traditional value strategy. So think, like you know less than you know less than over. The holding period on average is over a year for these names and turnover can be driven by two things just mathematically. So of course there could be changes in the fundamentals. So imagine you own a company and there's these major scandals and the culture starts to decay and employees are to leave Right, that would be a negative change in fundamentals. Or on the other side, you could have a company that you know they start investing in, I don't know, ai, some kind of emerging technology, early on and as we, as that trend starts to take off, they really benefit on the IP side from that. So fundamentals do change and they do evolve through time, but pretty slowly on average. For example, company cultures generally are pretty sticky through time. The founders set the tone and hopefully the managers can carry that torch moving forward when you see a lot more.

Speaker 2:

I think a lot more of the turnover actually gets driven by the price side. And this is the same, by the way, for like traditional value price to book type strategies where you know prices are just a lot more volatile than fundamentals, and so what ends up happening is you own a stock that you like and then you know prices, you know they run up and you, you know, at some point you say this stock is now overvalued, we'll take our profits and rotate and move on. Or you find stocks that you think are kind of interesting but not quite at your threshold Precious fall, holding constant fundamentals, and that's when you buy. So a lot of turnover is driven by precious, but even then, that being said, going back to my initial answer, the overall turnover is pretty slow, a little bit over a year on average, but obviously that changes based on market conditions.

Speaker 1:

So I often use this line that what you own often matters a lot less than how much you own of it. All right, talk to me about how you go about weighting with this type of approach. We know that very well-known market gap weighting, weighting some factor tilt, right. But given that some of this stuff you can argue is a little bit squishy, right, how do you think about weighting on this?

Speaker 2:

Yeah, no, we've actually thought a lot about this question when we designed these funds. So, as you point out, there's kind of two extremes you can use. On one end you can use full market cap waiting. On the other end you can use equal waiting. So full market cap waiting has the advantage of tons of liquidity, kinds of liquidity and, um, you know, in theory, to the extent where clients, whether you like it or not, measure you against the s&p, that will, you know, reduce the amount of tracking error to that um. The downsides, of course, are that now you're kind of constrained with respect to your breadth, like you can't really tilt that much on the, you know, on the smaller cap names, um and um, and you also face concentration risk in as much as if you, like some of the top companies, like you can only hold so much, I mean, you're going to be massively overweight, say the Mag7. Equal weight has the opposite problem. So equal weight you have the most breadth and you know is kind of the most unique portfolio, the most active share, but the downside, of course, being that a lot of that active share is just driven by this single factor the size tilt against S&P, and you know, and if it goes in your favor, you look at the hero, and if it goes against you, you look at an idiot. And so that's not really that fair. And plus, it has lower liquidity. And so we tried to throw the needle here, and what we ended up doing was devising a kind of halfway between solution to throw this needle, which is basically the square root of market cap. So you can think of like a chart where, like, you have the market cap on the X axis and then the Y axis is your position. It's a square root function, so it's like a concave function, and the advantage of that is that if a stock is, say, nine times bigger than another stock, it only gets three times as much weight. So it does get more weight and that helps increase the liquidity and reduce the dependence over-dependence on the size tilt, but it also still leaves enough room to be making pretty active decisions. So we kind of settled on that as a middle ground and, by the way, this was something that I didn't invent. We did this at GMO and I'm sure many other coin shops also use such a technique.

Speaker 2:

But going back to this overall question, so the portfolio is built like this we effectively have an investment universe, going back to this overall question. So the portfolio is built like this we effectively have an investment universe In the case of the US fund, it's like the top 1,000 US stocks and then in the international universe it's a universe of non-US stocks. What we do is we have scores for each company, we line all the stocks up for each company, we line all the stocks up, we then, within our universe, take the top 10% to 15%, depending on the fund, and then that's your portfolio. We don't equal weight. We then apply two tilts. One is by the factor. So obviously more intangible value means more weight, and then also more market cap means more weight, but only proportionally to the square root, not the full market cap to weight, but only proportionally the square root, not the full market cap to help create more diversification.

Speaker 1:

All right, so a lot of interesting points here. We talk about weighting from that perspective, which is easier when it's a US-only fund. Let's talk about DTAN, because when you're dealing with international investing, you now have to think about country weightings as part of that. Walk me through how that looks. Is that just a function of sort of the output on the individual names? In terms of the intangible assets? How does the country allocation look right now for DTM?

Speaker 2:

Yeah, that's another good question. So, as I mentioned before, like before I started Sparkline, you know I was doing kind of more hedge fund style investing and you know, when you go long short and you're, you know, highly levered on both sides, on both sides risk management at the factor level is very important. So this is your bar, or actually only models, where you can strain not just by country but you also can strain by sectors or industries and you want to be very, very tight there to kind of remove any unwanted exposures to various risk factors that could create volatility and hence create problems, to the extent that you're highly levered In long-only funds. I've actually found that that is kind of trying to be QQ'd. You're kind of over-concentrating the models by attempting to do all the kind of sector neutralization and style neutralization in countries, and so instead what we've decided to do is to let the weights go bottoms up.

Speaker 2:

It might be the case that at any point in time, the best companies say all the human capital and all the talent is going into the tech sector. Well, that's great, we should allow the fund to overweight tech. Or if all the talent happens to be in, say, germany, that's great, we should let the fund overweight Germany. So I think to a large extent you don't want to mess with it too much. Obviously, if things are going really crazy, that's when you might need some constraints. But at least in our research, when we design the fund and also positions, today that hasn't really been the case, and so, to answer your question, we let the weights the country weights and sector weights go bottoms up, just depending on what stocks on an individual basis appear attractive on intangible value.

Speaker 1:

I feel like we need to hit on currency to some level here, because obviously currency returns are a part of total returns when you're investing overseas. But maybe a little bit more nuanced how does currency volatility play into intangible asset value?

Speaker 2:

Honestly, we don't really include that as a specific component of intangible value. We view stocks as real businesses and their fundamentals are what they are. And in the DTN fund we actually do not currency hedge, so we're not hedging, we're not paying to hedge out the FX exposure. So the stock prices will kind of move up and down also with the dollar as it turns out. You know, we do think the dollar remains expensive. You know, whether I'm purchasing per parity or any other metric, you know, and when we launched the fund in September we thought that could be a nice tailwind to have for investors.

Speaker 1:

you know, in the fund yeah, and obviously there's been a lot of demand on the international side because international has done a lot better than the US and that's more of a traditional valuation call right, I mean, as opposed to intangible value. But make the case for I think it's compelling when it comes to the US, but make the case for intangible value as being a big driver of that value discussion when it comes to international too. I think also part of this is also around the idea that style classifications in the US growth versus value, I'd argue, is more driven because of tech. In people's minds that's the quintessential growth sector characteristic. You don't have that in anything international, which means I think typically most would view international markets anyway in passive form as value.

Speaker 2:

Yes, I want to answer that question in two parts. So I wanted to pull on that thread a little bit about the value versus growth style thing. And is it just tech? So I actually wrote a separate paper on this in 2019 where I created I basically argue that tech is not a is a first approximation of innovation, but obviously it's not sufficient, right, because there's innovative tech companies and non-innovative tech companies. There are companies in industrials that are very innovative and others that are not, right? Amazon's a retailer, google's a communications company, and so I devised a factor called I called it disruption factor, so innovation and then was able to use that as a way of kind of saying you know what is the exposure of, say, a traditional value portfolio or growth portfolio to that factor? And indeed it is the case that traditional value portfolios tend to load on a short innovation factor, whereas growth tends to load on a long, but it's not always 100% correlated. So I just wanted to make that distinction and I think that actually flows nicely into what is the point of these funds, right?

Speaker 2:

So, whether in US or not in US, kind of the point of this fund is to try to deal with this situation we find ourselves in now, where the investment community has become like super bifurcated, where you have value investors kind of your old school guys who are kind of holding onto these principles but finding themselves increasingly, first of all, with poor performance on a relative basis, but also in stocks that are kind of your old economy names financials, energy materials, industrials, companies with much less dynamic businesses and then you find, on the opposite side, your growth investors who have done pretty well on the back of the tech or innovation tailwind we've seen in the past two decades, but are increasingly exposed to overvalued names, because the world's kind of caught up to this idea that tech's done better, right, people are pretty performance chasing in general, and also there are these big swings right, 2022 is not a good year for investors in technology stocks. Interest rates were raised, there are other things that happened, and a lot of these companies that had pretty high multiples to begin with ended up getting smoked. Because that's a big, the valuation compression can be pretty painful, and so what we're trying to do with these products here is trying to bridge the gap between value and growth, to create a strategy that say applies value, investing these timeless principles, but also in a more modern way with an acceptor exposure that includes technology companies and can operate successfully in sectors other than the most traditional ones. We find that price to book ratio still works if you apply it in certain old economy sectors. It just doesn't work for technology companies. You can't pick between Google and Microsoft by using price to book. But intangible value does work, or we found it does work, at least in the more modern sector. So this is a way of taking value, investing and modernizing it.

Speaker 2:

The other way we think about this is on the growth side, which is here's a way of owning innovative companies, but with a valuation discipline such that if a stock goes up too much, we'll sell it. A great example that I talked about in my last investor letter is NVIDIA. So in ITN, our original fund, which is about four years old, we actually owned NVIDIA at inception. So this is 2021. The P ratio of NVIDIA was around 100.

Speaker 2:

So a traditional value investor would say this thing's super expensive, there's no way I'm not even touching it. But then, once our models adjusted for intangibles, their IP, their innovative culture, etc. We actually found that the stock was not only cheap but very cheap, went up a ton, at which point the model said, all right, well, this is still a good stock, but it's just not cheap anymore and so let's rotate out. And we ended up going into some other more under the radar AI plays. But I think that illustrates pretty nicely that this strategy, while being kind of focused on innovation and modern and tangible intent of the businesses, is still a value strategy and still cares a lot about the price you're paying for a lot of these assets.

Speaker 1:

All that makes a kind of sense to me. Those that are listening to this you know that are intrigued by the idea. They're looking at the funds and you know they might be used to seeing some ETFs that trade. You know hundreds of thousands of volume shares traded daily and they see the volume on ITAN and DTAN. Maybe they get a little bit concerned about liquidity. I want you to do some myth busting around volume, liquidity and how people should think about smaller funds.

Speaker 2:

Yeah, and look, what I'm going to say here is not specific to what I'm doing. It applies to any ETF, just based on the way these things are built. So ETFs are just baskets. They're baskets of stocks and, due to the arbitrage allowed by CreateRedeem, they generally trade very close to NAV. And the way that works is, if it trades at a premium, the market makers will arbitrage that one way, or at a discount the other way.

Speaker 2:

The capacity or liquidity of an ETF is a function primarily of the liquidity of the underlying stocks. So, for example, if I had a single stock ETF where the only holding was Apple, which is super liquid, the ETF would basically have the liquidity of Apple, more or less. And so what you evaluate and this is again not just specific to me when you evaluate ETFs that are, say, thinly traded or kind of new or smaller ETFs, what you want to look at is what are the actual underlying holdings? If you're holding micro-cap emerging market stocks, then it may actually not be that liquid and the spread, the bid-ask spread, if you go on your screen should be pretty wide to reflect that. If it's just trading mega-cap US stocks, it should be pretty narrow.

Speaker 2:

In our case, itan, I think it's trading around 5 cents wide. So currently I mean, and it holds Russell 1000, so top 1000 US stocks, so it's large and mid cap names, so that's pretty liquid. Dtn is a bit wider. It's a bit it holds non-US names, which is a little bit less good, but in both cases these are kind of your large cap stocks, like Amazon and Google are kind of the top two current holdings of ITAN. So I think that liquidity generally has not been a concern. We've had investors put in amounts of money that are significant percentages of the fund in a single day and have had no issues with trading. But of course, if that's something you, if you're interested in this concept, feel free to reach out to me. Or you know the trading team, you know Alpha Architect, who does the operations for the fund, as you know, will obviously be able to kind of help, you know, with any kind of specific questions.

Speaker 1:

So about how to think about this in terms of a diversified portfolio, obviously still equities, obviously still in a correlate to equities, maybe slightly less so, you know, at least in kind of higher volatility junctures. But how do you want to think about pairing this against more traditional passive investments? Can this be a core?

Speaker 2:

allocation. So one of the things that we were pretty deliberate to do is to ensure that these stocks, that the ETFs, had sufficient diversification. So both ETFs have over 100 names, right? So it's not like you're. Hey, you're buying a fund with three stocks and therefore you would, by definition, need to have a handful of managers to kind of diversify around that. In our case, we hold enough stocks that you know, even though the active share can be, you know, pretty high relative to, say, the S&P 500, you're pretty diversified across a lot of names. So you know that would help with the question around core holdings.

Speaker 2:

I mean, there's look, there's three different ways I've found that our clients use our funds. So first is, you know, as you mentioned, as the first is, as you mentioned, as a kind of way of getting tracking error against a passive index that loads up on these intangible value factors which we believe should lead to outperformance. A second way is as a value substitute that will tend to give you a bias towards your old economy stocks, which you may want to offset. But you can offset it by just buying, say, the QQQ, but then you're just going growth. So another way of doing that would be to instead add, say, one of our funds which allows you to still be kind of value-focused but just apply it on the intangible as opposed to tangible side of the balance sheet. And because our funds tend to be more intangible, intensive, tend to be more tech and grand focused, you kind of balance out some of the old versus new economy exposures and the final way I've seen this be used is on the growth side, where you have folks who want to be exposed to technology and growth and innovation but also want a fund that will be aware of the valuation so that as things run up they'll kind of take profits and prudently rotate into other less overvalued assets.

Speaker 2:

Like we did a paper called Investing in AI Investing in AI Navigating the Hype, and we did a study of the dot-com boom and bust and one thing we found was that if you just buy the internet stocks, you do really well and then you do really poorly. But if you're instead dynamic and you're kind of rotating through based on valuations, kind of always rotating into the cheapest internet stocks, you do okay. And that's kind of the idea here, which is I find that you know you don't need to kind of worry about should I trade in and out of this, based on, like you know, the valuations of, say, the tech ETF or whatever, but it could just be something that will smoothly, hopefully, navigate you through the various valuation cycles.

Speaker 1:

Any thought on how policy initiatives from the Trump administration could maybe impact the way intangible value is valued? I mean, I think about deregulation that may be impacting the IP side. I think about tariffs may be impacting even the brand equity side. I mean, does that factor into anything as you think about the portfolio?

Speaker 2:

Yeah, actually, the last paper I wrote, which came out, I think, about a few weeks ago in April, was called Investing Amid Trade Wars, and it talked about the impact of tariffs on global trade and on stocks more specifically. One of the nice things about intangible assets is they can't be tariffed. So if you have a physical good and it goes over on a ship to customs, it's going to get inspected and potentially tariffed, whereas an intangible asset think like streaming music or video, any kind of software, even services type thing cannot be tariffed, right. So that's actually makes intangible assets, I think at least, a lot more robust when it comes to the impact of this tariff driven volatility, right Like tariffs are on, tariffs are off. Tariffs are on, tariffs are off. We don't know how things will play out. It's possible that we end up with nothing, that that sticks, but I think, regardless, we're going to end up. I think, regardless, this has been a shot across the bow. Um, you know, companies and countries are now, you know, standing kind of more, more, uh, sanitized to the kind of, um, geopolitical risks of supply chains going through various countries and, as such, like this is a factor that will affect all companies, but I think those businesses that are more intangible, intensive, have a bit of advantage just because of the nature of intangible assets.

Speaker 2:

And I think the second thing that's really happened is and this is partially unintentionally and partially intentional on the part of the administration is this kind of like sell America theme right? So we've seen over the past year past year to date, I guess you know international stocks have rallied 15%, while US stocks are basically flat. So this huge gap has opened up in US versus non-US. We've seen US bonds sell off, we've seen the US dollar sell off, as capital is apparently fleeing the US into, you know, other geographies. And so I think what's happened is a lot of US investors have found themselves offsides to overweight US stocks. And that's a function of you let your winners run. So when US stocks do really well and they end up being 70%, 80%, maybe 100% of your portfolio, you just kind of say that's working. But what's happened is, you know, now it's the opposite case, where the idiosyncratic political risk is now in the US, not as much abroad. And so if you're an investor who has, you know, 90 to 100% in US stocks, right, maybe I should think about diversifying internationally, maybe this I can't tell you whether or not this theme will continue moving forward, but it might.

Speaker 2:

And the problem here, the challenge, is that the international stock index is not that good, right? So I think about IFA or Acquiax US. It's about 25% financials and then 20% industrials, right, it is very. The kind of general stereotype of non-US stocks as being less dynamic, less innovative is actually true, at least at the index level. And so the key with DTAN which is the you know find, where we took the concept and put it into non-US markets is that it only invests in a subset of names and invests in a subset that are the most intangible, intensive, so they're kind of levered to this growing intangible economy, this trend of growth. It owns, as we discussed, more healthcare, more brand-intensive companies, even within industrials, the more innovative technology names. So it's a way, I think, of diversifying outside of the US while still maintaining exposure to this intangible theme which I think you know over the next, you know, 10, 20 years will only become more and more pronounced and important to the economy.

Speaker 1:

And personally I think it makes the entire concept makes a lot of sense and I've seen other papers outside of viewers that have similar arguments. Speaking of those papers, where can people get access to those?

Speaker 2:

Yeah, so just go to my website sparklinecapitalcom. I publish all my research there.

Speaker 1:

Perfect, and I obviously did learn more about the funds sparklinecapitalcom. Any final?

Speaker 2:

thoughts here before we wrap up. No, this has been a fun discussion and I look forward to answering any other questions that come up. You can feel free to reach out to me directly online or just send me an email. I think my email's posted on my website somewhere.

Speaker 1:

I appreciate those that watched this live. Again, this will be a podcast under Lead Lag Live. We're going to be doing these monthly, so you'll be hearing more from Kai and we'll get into some more nuances, especially as it relates to the environment, and maybe some analysis on individual positions across the two ETFs. Hopefully, I'll see you all in the next episode. Thank you, kai, I appreciate it.

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Michael A. Gayed, CFA

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