Jared Tanimoto | 0:00

Welcome back everybody to the For the Wealth of It podcast. I'm here with my co-hosts Jay Boekeloo and Brett Maikowski. Today we have Kai Wu on. He's a good friend of mine. I'm excited to have Kai on. He has quite the impressive resume. So he's a Harvard graduate, studied economics there, and then went over to GMO where he worked under Jeremy Grantham. And most recently he started his own both ETF Lineup of ETFs as well as runs his own hedge fund. So I won't get into too much detail there. I'll pass it over to Kai and maybe you could walk us through kind of your journey from college to where you are now.

Kai Wu | 0:38

Yeah, thanks, Jared. It's great to be here. So look, I kind of entered college actually as a government major. I really had very little exposure to business or Wall Street. My mother's an artist and my father's a doctor. So kind of coming into college, it was like, all right, well, like, I'm interested in politics. I'm interested in the way the world works. Pretty quickly found economics as, you know, perhaps a more quantitative way of viewing social systems. Studied econ for a few years and, you know, ultimately did my senior thesis on the topic of financial crises. So I actually ended up doing an internship my sophomore year on Wall Street. You know, obviously, you'd be going to Harvard, there are a lot of recruiters on campus trying to kind of get you in that pipeline to come become an investment banker. And that was '07. Right. So I remember actually, you know, Chuck Prince, you know, if the music keeps playing, you got to keep dancing. He actually gave a talk to us as the interns. So that was kind of the world that I found myself in my sophomore summer. Obviously things went south from there. And, you know, I ultimately left with no interest in going directly to Wall Street, but did end up with an interest in financial systems and, you know, what would ultimately lead to crises such as what was unfolding before our very eyes. So I wrote my thesis with a professor named Ken Rogoff, who's pretty well known for— I guess he was the head of the World Bank, but also because he wrote a bunch of papers and ultimately a book on the history of financial crises going back hundreds of years, studying what events and macro imbalances ultimately led to these crises that led to stock price collapses and asset price collapses and so on and so forth. So I actually worked with him on gathering kind of a different set of data with the idea of trying to figure out, can we predict crises ex ante? So in other words, is it the case that when there's an imbalance in the trade surplus, or in the currency, or in asset prices and leverage ratios, that that leads to a conditionally higher chance of a crisis? And the answer we found was yes. So that was a really interesting introduction into the more macro aspects of bubbles and And credit. And that's what led me to my first job out of college, which was at GMO, as you mentioned, working for Jeremy Grantham, who's of course very well known as a bubble prognosticator, having predicted the Japan bubble in the '90s and then the dot-com and then the financial crisis in '08. So it was a really cool time to be at GMO. As I was a 21-year-old kid, I walk in the door and the firm was just doing so well, right? We had correctly called the financial crisis, and as a result, the assets were just kind of coming flying into the door, and there was just too much to be done. And there was one project that they wanted specifically to be worked on, which was they wanted someone to kind of help them expand some of their forecasting capabilities to other asset classes outside of equities. And the firm at that point had divisions in different countries, in Australia, London, San Francisco, that focused on these different niches. And what was really cool was they said, hey, we need somebody to to go travel around the world for a year and go work with all these different portfolio managers. But this person needs to be not that important because otherwise, you know, nothing gets done. So I was like, all right, well, like, how about me? Because, you know, I just walked in the door. So it was like the best thing in the world. I, you know, got a chance to work with, you know, all these really smart people, ton of, you know, breadth of experience traveling, you know, Australia, London, San Fran, as I mentioned, then back to Boston. Spent, you know, 4 or 5 years more working with, you know, Jeremy and the team as part of the asset allocation division. And then, you know, left in 2014. And then, you know, got joined up with a guy from my group who was spinning out a hedge fund firm and kind of was the co-founder on that fund. You know, I was like 25 at the time, and it was called Kaleidoscope Capital. We, you know, we grew the firm up to a few hundred million dollars in assets, kind of same sort of asset base, endowments, foundations, which was really cool. And then ultimately in 2018, decided to leave and kind of start my own solo operation here, Sparkline Capital, which is what I do now. And kind of along the way, I mean, there was, you know, a lot of different pivots. Like, you know, the most important one was I now focus on ETFs. I mean, we can get into why that is, but, you know, obviously the client base for ETFs are very different than institutional funds. So endowments and foundations are a little bit less, you know, at least historically, the target audience for ETFs, although that is sort of starting to change a little bit. You know, the other important aspect is the incorporation of new investment techniques. So, you know, one of the big, you know, kind of the overall, there's kind of these 2 through lines, I guess. So the first one is, you know, so go back to GMO. Obviously Jeremy's well known for his skills in identifying bubbles. What he's also well known for is you being one of the original investors using computers to pick stocks. So starting in the late '70s, early '80s, he kind of recognized along with his co-founders that a lot of the traditional stock picking techniques they were using could be automated using computers. And, you know, he would go to the Harvard library and kind of dust off those physical papers and hand-enter them into computers and, you know, was one of the early quants. You know, one of the things that has happened obviously through time is that the kind of bread and butter of most quant strategies is this idea called value investing, right? The idea of buying cheap price-to-book stocks. That strategy has not done as well the past decade due to a variety of factors. And so one of the kind of throughlines, as I mentioned, was, you know, my desire to figure out why that could be the case and what could be done to potentially improve some of the returns and kind of get it back to its former glory. The second piece is this idea of, you know, so yeah, there's traditional quant techniques, regressions, structured data from the '70s and '80s. But over time, obviously, we've seen kind of progress on machine learning and now AI. The question became, to what extent can we use many of these new tools in order to answer questions that were previously unable to be explored? And that's kind of where these ideas converged in what I'm doing now, which is this idea of trying to Quantify intangible assets. So the basic thesis here is that, you know, the reason why I believe that, you know, a lot of traditional value strategies have underperformed is their omission of intangible value. That's human capital, brand equity, intellectual property, network effects. These are the assets that for the largest companies today, you know, Nvidia, Google, are kind of the drivers of corporate value, yet they remain kind of unquantified in most traditional accounting data. And so where you have to go to find the information is unstructured data. That's patents, trademarks, go to LinkedIn bios of the employees at companies. But this data is now unstructured. And so what you need is a specialized toolkit to be able to quantify these things. And that's where the AI comes into play. So we were creating large language models around 2019, 2020, and now obviously leverage the kind of more cutting-edge tools that have been built subsequently. But so the idea is, you know, can we identify intangible value using unstructured data that we quantify via sort of large language models and other natural language processing techniques? And that was kind of where That was kind of the thesis that, you know, led me to launch my own firm where, you know, I would have the kind of sandbox to be able to do all these kind of fun, interesting activities.

Jared Tanimoto | 7:42

Really cool. To kind of break that last part down before we move on. You were talking about the intangible value there. I know in one of your reports, I think you use an example with like Taylor Swift. I'm just trying to pull what that was. That was like a really good connection kind of to explain what intangible value is, but can you kind of break that down in simpler terms, what that actually means for how that helps you invest?

Kai Wu | 8:12

Yeah. So as I mentioned, there's kind of these 4 pillars of intangibles, and one of those is brand equity, right? So what is it that allows a firm like Coca-Cola to be able to charge what it charges and get distribution the way it does? Why would we pay more money to buy a Hermès bag than something we can buy, you know, at, you know, at Costco or something, right? And the reason why is brand equity, that these companies have invested heavily in advertising, marketing, and kind of creating this association that, you know, we as customers have that then, you know, translate into, you know, better distribution and better, you know, higher prices. And so the question is, how do you quantify that? And there are many ways of going about it. I have a separate paper that focuses on using social media data. To look at the personality of different brands. But in this case, the Taylor Swift paper, the idea was to look at trademarks. And so the reason why it's a Taylor Swift paper was this was, it was published around the time of the Eras Tour when, you know, that it was like kind of the summer of Taylor Swift and then also Barbie, the Mattel movie that, you know, was obviously a number one kind of blockbuster. And, you know, actually what I did was I said, let's use Mattel as an example, right? Where what we can do is we can look at the historical evolution of their trademark portfolio, Mattel's. Through time. And what you can see is just look at the Barbie IP itself, how originally it was a single trademark around the doll, and then they added additional things for doll accessories, and then furniture and children's lunchboxes. And then they even got ahead of themselves in the late '90s where they started getting trademarks on credit cards and internet things that never ended up becoming products. Then they retrenched, and then obviously there's been a resurgence under the current CEO. The brand's kind of taken off again. And so you can see that both through time, but also cross-sectionally. You can look at their entire portfolio, the Hot Wheels, all the things that they've been kind of building through time, and using that as a way of quantifying, hey, it is the case, it happens to be the case that this company is very focused on building on its brands, and we can measure that through all the different trademarks that they own. And so that's just one way of quantifying this overall concept, which we try to apply broadly to all the stocks, saying, hey, which companies here have really strong brands that aren't currently being reflected in the stock price? That's the value component, Because obviously if you just pick the companies with the most brands or the most patents, you're ending up with like the IBMs of the world. We care very much for, in terms of yield, looking for guys who have brands, but their stock prices aren't yet reflecting these things.

Jay Boekeloo | 10:33

I'm curious, like, did you have some of this discovery while you were working with GMO and go, hey, I want to break out on my own and apply some of these theories that I have? Or was it something that you were like, I'm going to just go try this, and then started learning kind of by natural attrition?

Kai Wu | 10:51

Yeah, I think the idea of trying to think about what additional factors would be relevant to quantify intangibles was kind of always bubbling up behind my mind. I had a sense that what was happening in the machine learning world would be relevant. But if you rewind the clock to 2014, that was before large language models were even invented. I think we had Word2Vec, which was a very simple embeddings-based model. But, you know, back then, I mean, you know, quants were starting to explore using kind of deep neural networks for various things, but it wasn't really clear that natural language, so the application of these models towards the written word and looking to try to predict the next token, was the path forward, right? A lot of people at the time were still trying to kind of directly predict stock prices using this. And I actually wrote a piece, and this wasn't until 2019. I think, where I explicitly spelled out this thesis that I think that latter path of trying to predict stock prices using these fancy models was a dead end because of the complexity around the noisiness of data and the fact that markets are reflexive and change through time. But that the application of these tools towards trying to better comprehend natural language was kind of the killer app. And that would ultimately be what You know, I view and still continue to believe will be the most transformative in our industry.

Jay Boekeloo | 12:10

I'm curious. I mean, so a lot of times, like when you think of quantitative analysis, a lot of people point to the historical perspective of, hey, it hasn't been as accurate. Now we're going into this world of AI and things. Do you think that it's the reason... One, is that just a misunderstanding that it actually has historically been accurate that you find in quantitative analysis, or Do you think, no, the reason it's missed the boat is because of human error and now it's getting better because we have AI?

Kai Wu | 12:39

Yeah. So I think, you know, historically what I would've said was there's kind of a spectrum. There's strengths and weaknesses to different approaches. So kind of to take things to kind of a caricatured level, quants are really good at like scale. They can like look at thousands of stocks, ingest information very quickly in a completely disciplined, emotionless way, which is an advantage in markets, obviously. Whereas humans, they don't have the same breadth, or processing power. Like, I can't sit here and read a million 10-Ks in 10 minutes. But what I can do, you know, as a human is get really deep into the weeds and churn up additional data that wouldn't be available in a digitized format. Like, I can go and export calls and, like, listen, you know, even just reading the urgent call transcripts at one point was an edge that machines couldn't do. Now, what's happened, you know, as you can kind of see where I'm going with this, is that a lot of those things, those datasets are now becoming publicly available and now digitized and accessible to machines. And we now have the tools that we use as quants to ingest the information are getting better. So maybe before we couldn't actually understand, we couldn't even access the earnings call transcript, let alone ingest the information in a meaningful way. Well, now the LLMs exist to both access the data and also structure it in a meaningful way. So we've kind of solved, we're on the way to solving that problem. So I think there will be a convergence between these things where a lot of the strengths And weaknesses of the 2 different schools are starting to get more in this common area. So it's definitely an interesting time and exciting time for somebody who both views himself as being a fundamental investor who tries to understand what's going on and what drives stock markets, but also is interested in and likes working with the tools that are allowing more and more of this to be automated in a more efficient way.

Jay Boekeloo | 14:24

No, I absolutely love that convergence. And it seems like that seems to be Like, I don't know if it's a human condition or if it's systematic or what, because, you know, you think of like Mac versus PC, they started to converge. They're doing a lot of the same things. You think of the market in general, it's now a world market as opposed to these very delineated, you know, national markets. So really interesting that it's now, you're like you said, fundamental and quantitative is kind of going towards the same arena, if you will. That's neat.

Kai Wu | 14:56

Yeah, I mean, I guess the only thing I would add is I actually wrote a piece on this and Jared's read this on AI financial analysts. And one of the common tropes these days is, oh, AI is going to take all our jobs, right? We're going to be as humans unemployed. But what I actually did in this paper was I broke down the actual tasks that investors do on a day-to-day basis. And if you unbundle an analyst's job, there's a bunch of different things they're doing. Everything from making investment decisions all the way down to scrubbing data. It turns out that AI is really good at the scrubbing data component and less good at applying judgment, at least current AI, as of today, August 19th, 2025. As of today, you can actually think about the job of an investor just evolving. It's like, all right, well, I'm going to spend more of my time now on the reasoning component because that's what the O3 or O5 models are less good at. But I'm going to spend less time now on mapping tickers to databases because that's what they're really good at and what's really annoying for me. And that might evolve through time. But if you look at the history of any job, like in that paper, I look at the ATMs that actually led to an increase in bank tellers, kind of paradoxically, that the nature of work just is always constantly evolving. And so we as humans just need to think a little bit more about what on our day-to-day basis are we doing that can be better done by a computer and be okay giving that up. And meanwhile, kind of upskill in the areas where say the AIs are currently less good.

Jay Boekeloo | 16:21

Yeah, I seem to identify a, like a, there's a pattern that people who are in that world where you are more in the computer world and AI world that understand it, they seem to have less fear about the loss of jobs, right? So you, what you're saying is parroting a very close friend of mine, shout out to Derek Webb. And he's like, no, this frees us up to do the things that human capacity Or what we can do that a computer can't, right? You're saying that same thing. And it's actually refreshing as a person who isn't a technology guy to be like, okay, yeah, you're right. There are still things computers can't do, right? So like you said, don't fall for the trope of we're doomed.

Kai Wu | 17:00

Yeah, I think as someone who works with large language models on a daily basis, like you kind of know what the pitfalls are. Once you can see how the sausage is made, you're like, yeah, you know, like these things are fallible. Whereas obviously, like if you're kind of on the outside, like, you know, it's The same way as when I go to my doctor, like I don't know anything about medicine really. So like, I'm always, you know, kind of thinking what are the worst case scenarios? And you don't really have that when, if you're actually in the profession, you're like, well, I know what the risks are. I've seen all the studies. I look at it, I have the data. And so you're a little bit more like inured to a lot of the kind of sensationalism surrounding the AI wave.

Jay Boekeloo | 17:33

Yeah, no, that's a great analogy. Thank you for that.

Jared Tanimoto | 17:35

I wanted to shift gears just a little bit and talk about maybe your transition from GMO and Kaleidoscope to starting your own business and how that's I've been both on your career side as well as personal side. I know you're a recent dad and I know when, at least when you come out and visit, it seems like you have a decent amount of flexibility, a good team helping you run your funds. And then maybe to continue that path, like how has AI helped you run the business that you are today? I know last time we had a conversation, we were talking about AI, but you were kind of joking that like a lot of quants had been using it for years. It's just now that they introduced the language component to it. But I guess with the more recent models, has that helped your day-to-day?

Kai Wu | 18:16

Yeah, so just, I'll answer that question in a second. Just to kind of step back, why transition and how has that changed? So GMO, when I was there, was a 500-person firm. We had about $160 billion in assets. My team, I think was, I want to say around 10 people on the investment side. And then obviously there were plenty of people working in IT and in operations and sales, marketing, and So yeah, being part of an organization, a large organization is really cool. Like, I think it was a great place to begin my career. Like, I came from a liberal arts background studying econ. And so like, didn't have any of the kind of like the trade exposure to like, how do you actually go about like, you know, doing this quant investing stuff? And, you know, found great mentors at GMO, including Jeremy himself. But, but, but, you know, just a lot of people there and the culture, I like what I liked about it was very, it was very academic. Yeah. Right. So a lot of people that had PhDs and therefore approach things in kind of a rigorous, you know, research way. You know, I think ultimately though, like what I'm doing now is very fulfilling and it's not so much a lifestyle thing. It's more just like the ability to kind of have complete freedom on the research side has been instrumental to me. Right. Like I, at one point considered doing a PhD in economics instead of doing, and I ended up going into industry instead, going into investing, which I think, you know, That was the right decision for me. But, you know, I still always have that kind of itch that needs to be scratched, which is like, the goal is to kind of understand markets because if I understand markets, then I can deliver alpha for my clients, right? So it all kind of translates in a good way, right? Being in the for-profit sector is nice because like there's that constant feedback loop, which is like, I only succeed if my clients do well and they only do well if I, you know, come up with novel investment ideas. So how do you go about doing that? And not specifically about GMO, but just in general, being in a larger organization can be constraining. It's very difficult to go out there and say, hey, look, I think that this kind of crazy idea of these large language models are really interesting. Why don't we buy a bunch of GPUs and start exploring?

Kai Wu | 20:13

Maybe it would have flied, but probably not in most places. And so the nice thing about being independent is you have that flexibility to be able to kind of explore ideas that may not at least without kind of looking backwards, seemed like an obvious place to go. And I think that's what's led me to, without tooting my own horn, being kind of definitely in the right places, right? Like, kind of correctly calling a few of these big trends just because I was willing to take an early risk and try things out. So I do think that there's a lot of value there. Of course, there's a trade-off, which is a lot less infrastructure, less support, less resources being a small company. But to your second point, Jared, I think that's where a lot of what's happened on the tech front has been actually very enabling. I think it was like, I don't know if it's Sam Altman, one of these guys talks about the idea of the first billion-dollar one-person company, like the billion-dollar unicorns or whatever, which is like, maybe that's like, I'm not quite there, obviously. But I do think that the sentiment makes sense, right? Back in the day, if you wanted to set up a quant firm, you had to build your own servers. You don't have to do that anymore because now we have AWS and Amazon Web Services. You can outsource all that stuff. A lot of the operations infrastructure can be outsourced as well. Really what you're left with is what your core strength is and what your core mission is. For me, that's the research and alpha generation and even the operations and trading around the ETFs we run. You know, there's a firm called Alpha Architect who manages a lot of those things and they manage, you know, $15 billion. So, you know, they're probably better equipped to do it than, you know, me as a small firm in the same way as Amazon Web Services is better equipped to, you know, manage my cloud than I am individually. If I was setting up my own servers, which I did, by the way, in my, in the middle firm Kaleidoscope, I did build my own server room and that was kind of fine, but obviously the outcome wasn't the best. So I think that like, yeah, technology is very enabling. And I think AI is only going to be a continuation of that with regards to a lot of the things which you would normally have hired an analyst or outsourced to the Philippines to do, like data scrubbing or web scraping. Those sorts of activities could now be done way more efficiently by AIs. So I think going back to this theme we discussed earlier of the AI financial analyst, to the extent the junior analyst role can largely, not fully, but largely be accomplished by you know, AIs, you know, that kind of allows someone, you know, kind of in more, more in my position who knows how to work with these, these tools to, to kind of have a bit more leverage. So I, so I definitely think that the world is evolving in that direction where, you know, the, the kind of like, you know, not just in finance, but also in technology, the kind of the lone entrepreneurs with a good idea and, you know, questions they want to explore can get a lot further than without kind of requiring this kind of big build-out of, you know, middle management and other functions, which, you know, quite frankly, can kind of hamper progress in that dimension.

Brett Maikowski | 23:07

Yeah, Kai, I want to talk about how you talked about the difference between a large company and doing things on your own, and how you just have so much more freedom, and, you know, the ability to go try new things. And can you talk about just like maybe the belief you have to have in yourself? Because there is no, like, no one there to maybe like rein you back in and say, that's a crazy idea, or that'll never work or whatever. And you just have to like really have confidence that your, your new ideas or whatever it is that you're trying to do is going to work, or you have a strong belief that it will.

Kai Wu | 23:39

Yeah, I think you have to be a little bit like disagreeable or a little bit like, you know, delusional, I guess, um, to, to be an entrepreneur. And that certainly, you know, is somewhat the case, you know, in my situation and, you know, in most entrepreneurs' situation, they have to truly believe in what they're doing. Sometimes you see people break off and they start their own firm because they, oh, I can get a higher payout ratio, or I can get more equity. It's like, all right, cool. But that's doing it for the wrong reason. I think that could be one factor, but I think the main factor for people I would consider investing with or backing, whatever, would be that they truly believe in themselves and the ideas of what they want to create.

Jay Boekeloo | 24:18

I am curious. I want to touch back on the family side and things, the personal side as well. But before, it's really rare that we get a fund manager in front of us that we can actually ask something. And so kind of piggybacking off what Brett was saying, I've always wondered, so you hear a lot of these managers that have, they have these, their own theses, right? Like they're like their belief. So it could be that small value is the best, or some people are going to think that growth companies are the better way to go. And I always wonder, like, what is it that you are willing to do to avoid confirmation bias? Like, at what point, if something shows, because you're an analytical guy, would you say, all right, the data seems to say this? Because I just, I'm, every time I've asked anybody that, they're like, it just won't happen. I don't believe. I'm like, okay, but what, you have to be open to changing and pivoting, right? So how do you avoid that confirmation bias?

Kai Wu | 25:13

Yeah. You're pointing out a really important phenomenon here, which is, you know, this kind of survivorship bias issue where it's like markets go through cycles, right? We're currently the past 10, 15 years been through a growth cycle or a tech cycle, right? A US large cap cycle, whatever, right? And before that, we were in a small cap cycle. Like if you were starting your fund in 2001, and you were small cap value emerging, whatever, like you're crushing it. And so like, I think people oftentimes attribute their skill to what is really just luck. That they just happen to be operating using a certain investment style in a good time for that thing. The problem becoming, of course, that retrospectively we look back at the performance of different managers and the ones who took the most risk, who just levered long tech, did the best, or levered long small-cap value, did the best, which is obviously learning the wrong lesson because there's no risk management inherent in that. Then there's that survivorship bias issue. The same thing is with CEOs. People study CEOs and, well, CEOs who are really outgoing and take a lot of risk are the best ones, but you're obviously ignoring the ones that failed because they took too much risk. So I think you end up with that problem. I do agree with you, Jay, that trying to mitigate that sort of confirmation bias and just this dogmatic clinging to one philosophy versus another is critical because at the end of the day, We need a philosophy that is, I think, data-driven and empirical, where you're willing to challenge your assumptions. And when the facts change, you change your mind. And that's, to a large extent, been a component of my evolution personally, right? Because remember, I was trained by Grantham and that lineage of the Warren Buffetts, Ben Grahams of the world, of the traditional value applied quantitatively. And, you know, over time, you know, have continued to believe that, you know, you want to buy cheap assets. Like, of course, that's by definition true, but just that the definition of what is intrinsic value needs to evolve, right? So I've made tweaks to, you know, ideally change the framework in a way that's more adapted to the modern economy while still ideally, you know, leveraging kind of the timeless principles of the Ben Graham's, you know, and value investing school. So that's kind of been the way I've chosen to navigate that. But you know, you know, I think that there are many investors, of course, like who you know just have a playbook and they just want to keep running it off the cliff. And then others make the opposite mistake. They say, "You know what? Like I'm done with this. Let's throw security analysis out, right?" And like we're just going to go, you know, ape into growth, which doesn't work either, right? So I think you need to be like thoughtful about it. And you know, and my my my like journey was you know quite frankly like pretty iterative, where it you know was was a lot of different research studies on specific intangibles and like. accounting frameworks that over time collectively led me to this new paradigm for how I want to approach markets. But it wasn't like, oh yeah, I just decided one day to do it. It was very much driven by research.

Jay Boekeloo | 28:08

Yeah. And I really appreciate the research because we utilize that as advisors all the time, right? These things that academics are studying and trying to take out any sort of bias from it. But it is such a an interesting phenomenon to your point where I feel like as soon as humans enter it, we have inherent biases. We have the human brain. So the biology of wanting to identify patterns because of survival, even when they are not there. And so it's just a fascinating topic. So I really appreciate you sharing kind of your process and being willing to say that. So

Kai Wu | 28:42

yeah, I think you're touching on a good point as well, like just the publication. Component, right? And this goes back to the question that, you know, Jared, you were asking me around, like, you know, why go independent? And, you know, and I think part of that also is the ability to kind of share my ideas, right? Like, you know, at most quant firms, many quant firms, they're very secretive, right? Because they want to kind of protect their alpha, which makes sense, of course. But like, you know, the good thing is that the markets I traffic in are, you know, large-cap, you know, liquid stock markets. I'm not doing some kind of niche thing. And so like the capacity is very large. It's not like I'm so worried about that. And by the time people catch up, like we're onto the next thing anyways. And so I'm, you know, pretty comfortable with publishing. And I think that has been very rewarding. Like, you know, I have people reach out to me, like, you know, a lot of students, like younger people as well being like, hey, this actually like transformed how I was thinking about things. I changed my PhD thesis, for example, to be this topic because of like some podcasts I saw you on. Right. Which is really cool. Like, you know, not that I have like an ego where I want to like be some kind of like Nobel laureate, because I'm definitely I don't even have a PhD. I can't be. But like, I do think that to the extent like education is very important, like being able to put out like rigorous studies on like certain— on why intangible value matters or, you know, how AI can be used, you know, I hope around the edges can, you know, guide the industry in a way that is, you know, less kind of influenced by kind of commercial interests or, you know, hype than, you know, and more so by what is the data actually showing us.

Jared Tanimoto | 30:09

Yeah.

Jay Boekeloo | 30:09

Yeah. That's brilliant.

Jared Tanimoto | 30:10

We usually do this at the very end. I just wanted to throw out real quick, Kai puts out a really good— puts out really good research papers. So if you go to his website, you could subscribe. Jared, I think you'd find it really interesting. Where can people subscribe or find that information?

Kai Wu | 30:26

Yeah, just go to sparklinecapital.com. That's sparklinecapital.com. And all my papers are posted there and you have like the little box you can put into to kind of get them directly into your inbox.

Jay Boekeloo | 30:38

That's great. One of the things you touched on was you said, you know, we have to identify the risk is that we don't identify the risk if we let our bias take over. You took a big risk. You said, I'm going to leave this comfortable job and I'm going to go start my own thing. Tell us, were you married at the time? Did you like, was there a conversation around that? How did you Assess your risk and then take that leap.

Kai Wu | 31:05

Yeah. So I, my wife and I have been married since 2018. We actually started dating right after I quit my job at GMO to do Kaleidoscope. And I remember like, you know, when we first started dating, like at one point, like my business partner came over to our apartment and I was like, hey, Kristen, can you just like go somewhere? Just like, can you just like leave? And so she never actually met him for a while. And so she was like, is he a real person? Are you actually employed or is this whole GMO thing made up? And like, you didn't actually like, Right. But, you know, obviously it was real and we built a pretty successful company. And, you know, and then when I left, I sold my equity back, right? So I was left with enough savings that I felt comfortable taking another risk and doing Sparkline. And this was around the time we got married. So I just sold my business and we were engaged, but not yet married. Then I got married maybe 6, 12 months afterwards, I think. And yeah. And so That was kind of the evolution. And yeah, you know, I mean, being married is great, actually. I feel like, you know, having a supportive partner is huge. You know, being an entrepreneur, like, it's very lonely sometimes. And like having a partner who, you know, is super supportive and kind of like has seen you at your best and your worst and has kind of like, you know, it's funny, like she talks to people and people assume because of, you know, how she looks, oh yeah, you know, like I'm a big quant. So like, you know, I can talk to you condescendingly, but she understands more about quant investing than I'd say 95% of people I know. Just because she's had to deal with me so much. So yeah, I mean, I think it's really cool and really good to have partners kind of in this journey.

Jay Boekeloo | 32:39

So is that something, is she a part of any decision processes that you make? Like obviously not as far as investments, but on the business side of where to locate or something like that, do you bounce ideas off her or are you one that go, hey, we keep that separate. We've got our personal life and then we've got our professional life.

Kai Wu | 32:55

Yeah, I mean, I try to involve her to the extent possible, you know, try not to be too annoying, but, and generally on more of the human side of things, right? Like, hey, so like, you know, I have this client and like, he's having this issue, like, how should I think about this? Because she's very empathetic and, you know, understands people very well. She's a physician, she's a doctor. And so she deals with patients all the time. Obviously, I'm not really asking her like, you know, about like equations or quant stuff. But yeah, you know, I think that like having that having that counterbalance. Like we have very different personality types. If you ever met us, you know, she's kind of the, you know, she's like grew up in Texas from the South, like very like kind of bubbly and warm. I'm more kind of analytical. And so, you know, we approach things in different ways and sometimes having like a different viewpoint when it comes to dealing with a challenging, you know, interpersonal or strategic question can be very helpful.

Jared Tanimoto | 33:44

One last question for me. So one thing I admire you other than probably being like one of the smartest people I've met is your ability to kind of see trends. And I guess the way you analyze and understand things allows, at least talking with you, to be able to really understand, you know, what's going around in the world and to be able to point out things that are kind of unique. I enjoy just talking, having conversations, because every time we talk, it's like, have you heard about this? And I'm like, no. It's always something new to my radar. What things right now have kind of been new on your radar that you've been interested in or been noticing within, I guess, even just the world or even investments?

Kai Wu | 34:26

Yeah. I mean, there's, there's like so much going on right now. I feel like it's, we're like very lucky, right? Like to be living in kind of this exciting time. Right. Like, I feel like there is like, you know, huge changes afoot that, you know, in 50 to 100 years, like the world will be unrecognizable and we're lucky enough that we can kind of be alive to witness and perhaps participate in some of these I mean, I do think AI is like a really big, big thing. You know, from an investment standpoint, I think there are like areas of the market that are pretty frothy. And, you know, we can get into that if you want to separately. But, but I do think that the technology itself is game-changing in the same way the internet, right? There was a dot-com bubble and, you know, the telecoms were, you know, went down 95% and went bankrupt. But like ultimately the internet was kind of completely transformative in how we do things. I think the same thing is true here with AI and all the derivative components, right? Like self-driving cars and, you know, robotics and all the other things that are kind of drinking from that well will change the structure of society, right? Like, self-driving cars alone will change the way that cities are structured and suburbs and how people live and commute will be quite different. Maybe not in 10, 20 years, but by the time our kids are grown and their grandkids or our grandkids' kids are grown, I mean, they're going to be living in totally different lives. So I think that Like, you know, projecting that forward a little bit and thinking a little bit more about like, hey, so as somebody who's just like, you know, a kind of observer of the human experience and kind of around here, you know, are there things I can be doing to kind of participate and get some exposure to those things? Even if not, even just as a hobby, not maybe not just financial exposure. I mean, like, yeah, like this is kind of an interesting thing. I, you know, can I somehow be involved? I'd love to be involved. If for no other reason, then you can then, you know, tell your grandkids that, that, you know, you were involved back in, back in the day and have some kind of cool war stories. to go along with it. But yeah, I mean, there's just so many cool, so many exciting things happening right now. And I think that like, again, we're just very, very lucky to be able to be a part of it.

Jay Boekeloo | 36:21

I think that's something that I hear a lot out of— I mean, by any traditional metric, it sounds like, Kai, you've been successful, right? And I find that that is a common quality in successful entrepreneurs, is that positive kind of opportuni— not opportunistic, I'm sorry, but optimistic And I love how you're framing this, right? Because it's true. Even anthropologically, we look at these periods of time. If you look at the macro level, it's a lot longer than our little lives. And we are in the middle of this chaotic tech boom. And, you know, what used to be, you have to live for 100 years to see the differences, is happening now in 10 years. And I love that you're like, this is cool. This is, we're going to get to see these transitions. Yeah, I don't know. I don't, there's no question there. I just thought that was a really cool perspective. I do. But going from that, one of the things, since you are an entrepreneur, one of the things that I hear a lot of people talk about is they want to own their own business. They want to go into this because they want more freedom. They want more time. They want to do what they want to do. Have you found that to be the case or are you like, hey, entrepreneurs, or, you know, people who want to do this, heads up. It's not as much time as you think that you'll have for free time.

Kai Wu | 37:34

Yeah, I think it goes back to my earlier answer that there's like always going to be trade-offs in making that decision. So you think about like being an entrepreneur as opposed to working for a medium-sized firm, as opposed to working for a large firm, right? You have the most autonomy as a small firm, but the least resources, right? So like, you know, I'm not exactly staying in the Four Seasons when I go, you know, travel to meet a client. And I can't necessarily, you know, call up, you know, one of my analysts to go Do something I don't want to do myself, right? So you kind of lose the resources component when you go independent, but in exchange, you get to structure your world and your day how you want. And that can be both good and bad. Like if you're not the kind of self-starter type, that could actually be bad because maybe what you'd be doing all day is just sitting around like you know playing video games or something, right? But if you're like very motivated and you know kind of believe in the mission of the organization, then in fact, like that kind of your drive will actually lead you to work. You know, perhaps definitely more effectively and perhaps even more hours, right? Like, 'cause you're just truly like, you know, you believe and you're just like completely convicted behind the idea and it's your baby, it's your idea. It's not just, oh, I'm an employee somewhere and like I get paid my W-2, right? So I do think that like there is, it depends on the type of person, but at least for myself, I can say like, I'm significantly more motivated on being able to kind of like have this be, you know, an organization that will like be shaped by my efforts, either good or bad, depending on, you know, how well I do. So I think like that's, That's definitely an important thing and is very nice. But again, it doesn't come without its drawbacks. You know, having a, you know, nice fat paycheck and having, you know, an expense account is of course a great thing to have. But, you know, would I choose freedom, you know, importantly intellectual freedom, which I mentioned, or would I choose, you know, the golden handcuffs? I think like the answer is pretty clear, at least in my case.

Jay Boekeloo | 39:20

Yeah. It seems like the theme of this is convergence because even what you're saying now goes back to all A lot of the themes that you were pointing out earlier. So what I hear in this is the upside is kind of more exciting for you, right? Is like, that's, you're willing to give up the trade-offs for this upside potential. And then that ties into, well, if I'm optimistic, of course that upside potential is much more exhilarating because you see that I'm going to reach it. But then at the same time, you're also saying, I just lost my train of thought because it As you were saying it, I was like, oh my gosh, this goes right back to what you were saying before. It'll come back to me. But it's funny how everything you've said is kind of coming together here at the end.

Kai Wu | 40:02

Yeah, no, I think that's important. Most people I know have kind of consistency in their life, whatever it is that gives their life meaning. You oftentimes see that where they're in all the different dimensions, whether it's work, I don't know, religion, hobbies, all the different things that give people's lives meaning. You know, seeing a consistent through line across those different dimensions is something that like I often find like is present in the people I know who are the happiest and who are kind of the most centered and balanced in the way that they choose to kind of build their lives. I think oftentimes when you see people be unhappy, it's because there's inconsistencies in some of their values. And maybe they have one part that's going really well, but, you know, let's say their marriage is falling apart because they're working too much or whatever, right? Like, I think there's— those imbalances oftentimes happen and it can be very like, you know, tragic for people. So, Jay, I think what you're saying is actually correct, that to the extent one can live life in a way that they kind of create balance and consistency in all different aspects, that I think does contribute to true happiness.

Jay Boekeloo | 41:05

Yeah, no, I think that's exactly right. And that's exactly where this podcast sits, right? Is like we're trying to help people find that balance. And so we want to bring on people that give an example of that. Or if somebody isn't, maybe they even have their epiphany and go, oh man, yeah, I am feeling imbalanced. But you're right. I think the happiness comes from a balanced life. And we've said this before on the show, is like, that doesn't mean equal parts. It means that you just feel like all parts are satisfied in your life. And then as you were saying that, it came back to me, survivor bias. So you talked about that earlier. So this optimism, this upside, and all these entrepreneurs, But then you also do have survivor bias because a lot of the people who make it are the ones who we hear messaging from. And we have to be careful because there are other people who take the risk, they do everything right, and they don't make it. But we don't think that means they're any less happy. That's where that optimism comes in, right? The entrepreneurial spirit. But

Kai Wu | 42:00

well, I think it, this is like that classic, like Jeff Bezos, like regret minimization idea, right? Like when he started Amazon, left, I think it was like D.E. Shaw. Right? A quant fund. You know, his idea was, look, if I don't do this, I'll be really unhappy. I'll always, you know, be like, man, what if I just started Amazon? Right? Like, and obviously it did work out for him. But even if it hadn't, you know, he'd always be left kind of wondering, you know, what did I give up by staying at this job? And so, you know, there's, there's definitely some kind of psychic value in that, that, you know, again, it's, it's a little bit abstract, but, you know, should, should go into the equation, you know, when, when, when you're weighing this. And again, not, not to say that like entrepreneurship is like the best thing in the world and everyone should be doing it. I think I'm actually saying the opposite of that for the select group of people who are crazy enough to want to take the risk. But yeah, I mean, I think like trying to kind of think holistically about the different aspects aside, it's not just a financial decision, right? It's like, do I have the research freedom? Do I have the support network of, you know, my wife, whatever, like around me to kind of be there with me on the journey? Am I sitting at the right kind of technological inflection point where, you know, the tech trends are going to be a a tailwind, not a headwind for what I want to do. I mean, these are all these different factors that require some sort of projection, but are obviously crucial in determining whether or not that's something that you should be doing.

Jay Boekeloo | 43:18

Yeah, no, and that's, I think you're exactly right. To anybody out there as well, we're not saying, obviously we're advocates for owning your own business or being an entrepreneur. And really what Kai, I think what you just said is even more accurate. We are bigger advocates for doing something that you later won't regret if you hadn't done it, right? And we can get more concise than that, but that's really what the point of this is. And so to be on the flip side, if you are happy going 9 to 5 and coming home and you have nothing to worry about with your work, you're like, I am 100% focused on my family and myself and working out. That sounds awesome. You don't need to go and try to start a business and be stressed out because you will work into those hours that you right now are enjoying. So yeah, thank you for—

Kai Wu | 44:04

Yeah, no, I completely agree with that. I know a lot of people for whom that is like, you know, you have to be honest with yourself. What is your utility function? Like, what brings you happiness and joy? And how do you want to construct your life? And for those people, like, that job is like the ideal situation. You know, but if you're the type of person who's like, man, like, I want to be like, you know, staying up all night thinking about the next day's work, that's not the ideal, right? So like, it goes back to the point, you know, which I think is a common theme here in this discussion, Just around this idea of like balance, right? You want like the flywheel to be spinning such that all things are kind of contributing towards the end goal. And so you want a job that contributes to your happiness as opposed to detracts from it. And if that's the type of thing that makes you happy, then that 9 to 5 that's stable and secure is kind of the perfect role for you. If you're the type of person who wants to like be like, you know, trying to change the industry, like whatever, like then, you know, probably not the ideal situation. And, but just knowing that you have to kind of build your life, you know, your marriage, your friendships, you know, whatever around that common goal such that they kind of all reinforce each other as opposed to being in conflict, which I think again is what leads to unhappiness.

Jared Tanimoto | 45:08

So we kind of, as we wrap up, based on kind of just the name of our podcast, For the Wealth of It, what would you say true wealth means or how would you define true wealth?

Kai Wu | 45:20

You saying how would I define it for myself or how should I as a philosopher define it as, you know, for the kind of humanity as a whole?

Jared Tanimoto | 45:30

That's good. No one has ever posed that second one. Let's go with the second one for right now.

Kai Wu | 45:34

Yeah, I think the second one, I mean, my response would be it's individualized, right? Like what drives happiness for, you know, you and me and, you know, so-and-so is going to be different. Everyone has their own objective function, as I mentioned, right? And I think if your goal was to kind of provide happiness for every human in the world, you couldn't, there's no one-size-fits-all answer. It's not like, oh yeah, we should all be entrepreneurs or we should all be employees. Right. To take your example, it's, hey, you know, we want— you should be able to build your life in the way that is kind of the most, you know, reinforcing of those things that make you happy. Whether it's like, you know, some people really care about family, other people don't care about that. And that's fine. Like, if you don't care about family, that's totally fine. But like, you know, then structure your life in a way that like you can then, you know, prioritize the things that you do care about, whatever that might be. And, you know, obviously this is like very, very trite to say, but like, You know, financial wealth is, is one aspect and is often a tool to achieve freedom and achieve goals in life, but is obviously like, I think too many people use it as a scorecard solely because it's the most easy to quantify, right? This goes back to my intangible value framework, right? Like people tend to, you know, manage what they can measure. They like the tangible assets, but the intangibles are oftentimes what matter more.

Jared Tanimoto | 46:44

And I feel like you've hit pretty well on the individual answer over the past 20 minutes here. So

Kai Wu | 46:49

yeah, I'll let you guess what my answer would be.

Jared Tanimoto | 46:53

But to wrap up, how can people find you? I know you put out a lot of your reports online. How can they get in contact? Are you on social media, website? What's the best way?

Kai Wu | 47:02

Yeah, so my website, which I mentioned before, sparklinecapital.com, is where I have all my research papers published, and you can sign up for my email list. If you want to contact me directly, you can, I guess, email me. My email is somewhere on my website, or you can reach out there. There's a form submission. Also, I'm on social media, so LinkedIn and Twitter. My handle is CKaiwu, C-K-A-I-W-U, for both platforms. And, you know, I'll try my best to engage.

Jared Tanimoto | 47:27

Awesome. Well, really appreciate you being here. Thanks for jumping on and we will see you at Future Proof.

Kai Wu | 47:33

Awesome. Good seeing you guys.

Jared Tanimoto | 47:34

Thanks, guys. Thank you.

Speaker 1 | 47:37

Thank you. The views depicted in this material are for information purposes only and are not necessarily those of Cetera Advisor Networks, High Note Financial, or Savvy Advisors. They should not be considered specific advice or recommendations for any individual. Neither Seder Advisor Networks, High Note Financial, or Savvy Advisors, nor any of its representatives may give legal or tax advice. Jay Boekeloo is an investment advisor representative offering advisory services through High Note Financial LLC. Jared Tanimoto is an investment advisor representative offering advisory services through Savvy Advisors. Brett Maikowski is an investment advisor representative and registered representative offering advisory services and securities through Through Cetera Advisor Networks LLC, member FINRA, SIPC, a broker-dealer and registered investment advisor. Cetera is under separate ownership from any other named entity. THM Wealth Management is located at 102S Goliath Saint, Suite 103, Rockwall, TX 75083.