Smart Beta Meets China: Building Better Factor Exposure | Jason Hsu, Fujia Liu & Tony Yang

Michael A. Gayed, CFA (The Lead-Lag Report) sits down with Jason Hsu, founder of Rayliant Global Advisors, and China-market specialists Fujia Liu and Tony Yang of China Asset Management (ChinaAMC) to unpack factor investing, thematic tilts, and how global allocators are thinking about dispersion, AI, and energy trends inside Chinese markets.

WHAT YOU'LL LEARN
- The real difference between smart beta, factor investing, and thematic investing
- Why cap-weighted concentration pushes allocators toward smarter weighting schemes
- How core-satellite portfolio construction applies to global and emerging-market allocations
- Why China's AI buildout looks structurally different than the U.S. AI investment stack
- How dispersion across sectors shapes opportunity in Chinese equities
- Where nuclear and energy trends fit into the broader China thematic picture

PANELISTS
Michael A. Gayed, CFA -- Publisher, The Lead-Lag Report; Founder, Lead-Lag Media
Jason Hsu -- Founder, Rayliant Global Advisors
Fujia Liu -- SVP, Global Capital Division, China Asset Management (ChinaAMC)
Tony Yang -- VP, Global Capital Division, China Asset Management (ChinaAMC)

Watch on YouTube: https://www.youtube.com/watch?v=-BF3xlgJTf8

DISCLOSURE
This webinar was sponsored by Rayliant Global Advisors. Michael A. Gayed, CFA and Lead-Lag Media LLC received compensation from Rayliant for coordinating and hosting this program. Commentary from the ChinaAMC (CAMC) participants in this program is limited to broad, thematic market perspective and does not constitute a discussion or recommendation of any specific investment product. Nothing in this program is investment advice or a solicitation to buy or sell any security. All views expressed are those of the participants at the time of recording. Please consult your own financial advisor before making any investment decision.

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Past performance does not guarantee future results. The content in this program is for informational purposes only and should not be considered as investment advice or a recommendation of any particular security, strategy, or investment product. All investments involve risks, including possible loss of principal. Please consult your own investment or financial advisor for advice related to all investment decisions.

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Transcript

Recording Started

SPEAKER_02 0:00

Okay, we'll get started. Uh appreciate those that are here already. I know that's it looks like a small attendance number, but hopefully more people come in. Again, it is early, but appreciate those that have woken up to uh and maybe not woken up. I don't know if you slept late, uh, but you know, if you did wake up recently, try to sleep earlier. Uh appreciate those that are starting to uh come in here. My name is Michael Guyad. I am the publisher of the Lead Lag Report, founder of Lead Lag Media. This webinar is sponsored by Raliant. This is gonna be a good conversation, very different kind of conversation around these uh smart beta factor ways of thinking about investing, how to apply it uh in a portfolio, how to think about it from an international perspective, particularly when it comes to China, with two real experts that are actually in China and from China, uh with uh Fujia and Tony. Uh, if you are here for the CE credits, I will email you after this webinar, get your information, submit that to the CFP board. And if you want to engage or ask questions live during this conversation, feel free to put it in the QA or chat, and we'll try and bring it up here. Uh uh let's get into a quick round of introductions because, like I said, this is a very different kind of webinar than I've done in the past. And start with Mr. Jason's two of Raleigh. Uh Jason's got a storied history in the investment business uh and always wears uh interesting shirts. So uh Jason, feel free to uh introduce yourself to the audience.

SPEAKER_03 1:12

Thanks, Michael. Well, uh, for those of you uh that have connected with me in my prior lives, it would have been uh through Fundamental Index Rafi, uh which recently I think has been sold to uh Vinify TMX for about half a billion dollars. Uh so I'm the one of the few guys who who early on brought to multi-factor investing, uh smart data, I think, was something that uh was coined by me and Rob Arnott. Uh so that's that's that's that bit about me and my connectivity to the ETF and the index world.

SPEAKER_02 1:43

And I mentioned that uh we have a uh unique webinar in that we have uh two people from China to talk about China and investing in China, uh Fujia Lu and Tony Yang. Fujia, introduce yourself to the audience here.

SPEAKER_00 1:55

Hi everyone. Uh my name's Fujia. Um I'm from China Asset Management. Um, so with Tony together, you know, we represent uh the leading China Asset Manager with a total AUM of around 460 billion US dollars. Um glad to be here today with Michael and Jason together.

SPEAKER_02 2:15

And uh Tony, good.

SPEAKER_01 2:17

Hi everyone, I'm Tony. So I've been with the firm um from the industry for about 13 to 14 years. And myself, I've been studying UK and also have broad experience with international investors across the continent. So it's very interesting to see how the perceptions you know of global ass allocation and the way to invest in China today. I'm very glad to be sharing some of our insights we can provide on the local side. So, yeah, back to you.

SPEAKER_02 2:43

All right, so Jason, um, you had coined the term smart beta. I remember using that term quite a bit. I actually um kind of stole off that term when I uh registered on GoDaddy smart leverage. I figured, okay, that might be another sort of thing in the future. I still have those domains, I haven't done anything with them. Um, but um, I want to I want to just set the stage for what uh smart beta is supposed to be. I don't hear the term as much as I used to. I feel like you go through these phases of terminology, smart beta, uh factor, theme. Are these all kind of the same thing?

SPEAKER_03 3:14

Uh I would say um they they are at the end of the day all the same thing. Now people might use them to uh signal that they're looking for something else. But I think for people who use smart beta, it generally is a dissatisfaction with traditional beta, sometimes called bulk beta, right? Like if you say, look, you know, how is the SP 500 today almost just seven companies, right? And there's really no diversification across industry sectors. And then they realize, okay, well, when you do cap weighting, you have this concentration of weights into the the you know, whatever's become the most sort of popular or just you know experience some kind of bubble pricing. And so I think for some people, smart beta is about moving away from cap weighting into sort of more sensible weighting. Now, for the people who want to think about outperformance against the SP 500, rather than what's wrong with SP 500, and just think about look, that's a benchmark. I don't care right or wrong, I want to outperform it. Then they want to talk about factor investing, right? You're adding more factors on top of SP 500, which then gives you sort of an alpha uh systematic uh ability over time. So they are at the end of the day, by construction, by attribution, the same thing, but I think people talk about them differently because of what they want to accomplish in the frame of reference they used to think about investing.

SPEAKER_02 4:33

Yeah, I think it also kind of upheld uh throws off the sort of idea of um you know a beta of one. What does that really mean or matter, right? It's from a statistical perspective. At the end of the day, if things have factor tilts, then it's it's uh it's it's I forget the exact framework. I remember this from the C Fate chapter uh exams, but it's uh it's it's not sort of the traditional alpha uh beta, it's it's multiple types of beta or what drive return. Um on the thematic point, um, Jason, uh let's talk about sort of how that has gone through different cycles. Uh again, I feel like themes have been um in favor, out of favor. I think they're much more in favor now, especially with the AI push in general. But um, how should investors think about what portion of a portfolio should go to thematic types of investments?

SPEAKER_03 5:21

So I I would say I subscribe to a very classic approach, which is coarse outline, right? At the core of your portfolio should be these sort of liquid, large markets that represent global GDP growth. And so within it, clearly, US is large, it's gonna be part of it. I think about emerging markets, and within emerging markets, China is massive, so it should be part of that. And then I would say there are other opportunities that come and go, right? They're not persistently liable, you know, generator of return. So you could think of, you know, like AI is probably a theme today, right? It has extraordinary growth versus everything else. Uh it's probably going to a bit of a bubble, the bubble might crash, and then later on it might then just become a long-term sort of industry driver. But before that, it's probably more thematic, as it's sort of going to its its uh gestation period. Uh so I'd say, you know, there are a lot of themes, and the theme of day could warrant a tactical position within your course ally. Uh so I very much think of themes, they're interesting. If you got timing ability, if you got special, you know, crystal ball that tells you which theme is gonna drive returns for the next year or two, uh, by all means, right? It deserves a a location in your overall portfolio.

SPEAKER_02 6:40

Um, Fuji, I want to go to you. So the um I think when people think about US markets, uh they think about this monolithic co-movement that happens across sectors and industries. Everything tends to correlate somewhat together, school fish moving together. Um and that makes sense because there's so many different investment products, and yeah, once things are put into ETF or different you know, types of vehicles, they tend to move closer together in general. Their beta tend to increase. Like when you put a new stock into an index, the beta increases to the index, despite the stock not having anything fundamentally different. Um, when it comes to China's markets, um, in general, are there is there more dispersion? Is it not the same type of monolithic movements across all of China's markets? Is there more dispersion internally?

SPEAKER_00 7:28

Yeah, that's a great question. I think um, you know, similar to what you have observed uh in US market, the huge dispersion between AI stocks and you know the rest, um, what's happening in China right now is pretty much similar. Um, so really you are seeing this huge outperformance uh driven by the AI sectors. And more specifically, uh, you know, you look at hard tech. Um so you know, similarly, again, I can draw the analogy in the US, you have the debate about hard tech versus software, and in China, it's all of these semiconductor AI infrastructure, you know, really the enablers that are benefiting uh in this round of uh you know market rally. Um but of course, with the recent two weeks, I think the whole world is uh experiencing correction. But I think uh, you know, it's very clear to the global investors that AI trend or AI industry prosperity is going through a few year cycle. So we are uh constructive about the AI themes uh globally, including China.

SPEAKER_02 8:40

What's interesting to me about um the AI movement in China versus the US is it is considerably less expensive to use AI versus in China versus the US. I think Deep Seek is like 10% of the cost of Claude and uh Chat GPT, uh, which I would love to be able to take advantage of because I'm using AI so much in my own business. Um, but um Tony, talk about um from a valuation perspective. You know, Jason kind of alludes to the idea that maybe it's kind of a bubble or entering a bubble. You can argue that's debatable because valuations somebody I saw on CNBC yesterday somebody said it would be the cheapest bubble in history, uh, given just valuations, which I think is a fair point. But uh, as I understand it, valuations when it comes to a lot of these AI companies in China, and by the way, folks, uh connecting that to the smart beta, if we go with smart beta, is is another term for theme or factor, and this is a type of smart beta way of thinking about uh portfolio construction. Uh, how do valuations look, Tony, when it comes to uh AI names in China?

SPEAKER_01 9:38

Okay, so maybe before that I answer your question why the models are cheaper in China. I think you know, China and US they adopt two different methods. So US, they are more about a powerful model for all. So it's very powerful, but you know, applies to everybody's needs. In China, it you know, it's about like 80% of the performance, but it's a much cheaper model in terms of parameters. So you mean like large language model in the US, you probably have one trillion parameters. In China, about 10%. And also when you talk about token, worst token is electricity. So electricity power in China is much 40% cheaper. And per token cost, because of parameter, it consumes less tokens. So combined together, you know, the uh overall cost of using that is cheaper. And another area is for Chinese government, I think they treat AI as an infrastructure. So they want to have this easy accessibility to all populations in all industries, and DeepSeaks is open source, so it's free for everybody for you know retail use. And in terms of the you know, valuation, I was I think it's very different in the sense that you know the uh US uh a lot of AI companies, they are seeing revenues, and some of them are seeing actually you know improving uh trends in terms of profitability. But in China, it's more about the future you know growth story. And if you see before the deep seek moment, I think not many international investors are looking at China at all because of there's nothing you know happened here. But you know, with the deep seek moment, people start to pay attention. But before that, I think a lot of the uh innovation are still going on in multiple industries. So not just the AI, only new energy, on the biotech, a lot of the AI application,

Sharing Started

SPEAKER_01 11:25

I think is the end game, I would not say end game, the ultimate purpose of uh this AI. So the valuation, if you compare it to the you know, 4P level is definitely slightly higher than the the US one because we're smaller, we have much gross potentials. And also because of the trading behaviors, a lot of the onshore retail traders, once they think the stock is a very good model, it's a very good growth story, they're all crowd to that. So we need to be careful on not just you know purchasing the large cap, right? Not the highest cap market gets the largest overweight. So I think back into your smart beta approach, you need to define what's the relevant industry, what's the relevant targets. And valuation is one of considerations, but it should not be the key criteria because there are huge growth stories behind that. The earnings are expected you know in three years, five years' time, you cannot use the current PE to valuate that.

SPEAKER_02 12:25

I just had a bit of an aha moment, um, that point about energy and token costs, uh, just given that uh China is far more uh ahead when it comes to nuclear uh you know uh uh implementation. I'm gonna assume that from a longer term perspective, you can make the argument that AI will almost always be cheaper in China just because nuclear is the cheapest energy source, and presumably a good amount of the electricity is being pulled from that, Tony.

SPEAKER_01 12:51

Yes, I I think in the in the long run this gap will get larger and larger.

SPEAKER_02 12:56

Yeah, that that's uh I hadn't I hadn't thought about it that way, but that's interesting. Um I'm sharing my screen um with a slide that uh you folks at China AMC uh have sent to me to show on this webinar. And I think this is um an interesting thing that I myself have been noticing more and more. Um everyone's talking about robotics. And uh again, it's a theme, but it's probably gonna be more than a theme uh as it as it uh expands more. But uh it seems like China's way, way ahead on the robotic side compared to the US. Uh is that is that a fair statement, uh, Fujia?

SPEAKER_00 14:03

Yeah, absolutely. I think um, you know, we also have a slide showing you that uh, you know, right now, um, if you flip to the third one, um, if you look at some of the uh factories, um, the next one, please. Yeah, so you know, in the past, you probably see, you know, very labor-intensive, for example, in an autofactory, right? So you see a lot of labors and you see some industrial robots, but still with a lot of manual uh processes. However, uh, right now, if you look at the uh chart on the left-hand side, you pretty much see what we call the lighthouse factory. And one of the great examples is Xiaomi, which I'm sure many of the audience are very familiar with. But indeed, I think when we talk about robotics, uh you think of the investment thesis not only because we have obviously the scale advantage, cost advantage, but also think about localization. I think in the past, obviously, you know, there are a lot of components we still need to import. However, right now, if I put I can quote you the statistics, the uh domestic industrial robot installations has increased from 30% in 2020 to 57% in 2024. And also you can imagine the whole localization uh supply chain is very sufficient to really uh embrace the whole ecosystem. So I think uh we have come to the critical point that uh not only is this something, you know, uh we spend a lot of money and then you know, bearing the losses, but right now, you know, these robotics uh not only in factory, but in many of the occasions, such as um, say the retirement house for many consumer type of scenarios, you can imagine in future there are more and more humanoid uh robotics into uh commercialization. And uh if you noticed this year, uh one of the most uh you know in a famous company, Uni Tree, is going to uh is going public uh very soon. And that will again ignite the passion for you know the investment themes around robotics.

SPEAKER_02 16:28

And correct me if I'm if I'm wrong on this, but um is it that a lot of these uh factories, a lot of these companies are are they kind of starting from scratch to you know build from the perspective of making it robotic and autonomous from the start versus an existing factory that's then being retooled? Because I think that's where China might have a big advantage against the US, right? It's like you have factories that might be incumbents and they don't want to change their processes, whereas in China it's fairly easy to do that and just start fresh.

SPEAKER_00 17:00

Absolutely. I think um, you know, um, first of all, you know, there's always a drive to compete and uh drive the cost down and then you know uh compete among the peers. And that's really the uh uh animal spirit uh in China across every sector. So I think in terms of uh changes, there is less resistance if you think about uh in China compared to uh many countries in the world. And uh when one uh when one company proves success in one sector, there will be more and more uh entry uh entries

Sharing Stopped

SPEAKER_00 17:38

entrance to uh you know enter the industry and then start to um really excel uh then the uh incumbent. So I think uh we are very um like open-minded about new changes and new approach of doing things. And that is why, especially in manufacturing uh industry, uh you have seen that China is leading uh in every pretty much subsector uh uh in terms of the whole uh battle chain.

SPEAKER_02 18:08

Um, Jason, I want to go to you. Uh obviously, from a portfolio construction perspective, we're always taught that rebalancing is key because it forces you to buy low, sell high, to go back to target weights. But uh if a theme is going to ultimately be bigger than a theme and become the market, like AI you can argue has become, at least in the US. Uh do we still want to rebalance that or do we want to let it run? I can dump you on that one.

SPEAKER_03 18:40

We yeah, no, no, because it's it comes down to um you know, over what horizon uh should you pursue a momentum strategy? And that means don't rebalance, let your winner run because people are underestimating just the sheer size of you know, it was the internet revolution before, I think it's the AI revolution now. And what horizon uh would mean reversal kick in because something has sort of gotten ahead of itself, right? It's gone from rational expectation to you know irrational exuberance. And that just kind of rewind the clock back to the year 2000, right? I mean, if you look at what was happening at that time, right? Uh internet was all the rage, right? It was about to change humanity. And of course, if you look over sufficient long horizon, internet in fact did, right? Like the two things that was true circa 2000 was we grossly underestimated just the amazing thing that the internet was going to bring, how it was found foundation gonna change everything. Uh, but we also grossly overestimated in terms of the the player at that time, right? It was the Cisco, so it was the Yahoo, it was WorldCom, uh, who was gonna capture that value. And then so I think it's it's the same here, right? Like, yes, I think AI is going to create value that we can't even begin to fathom, right? So you certainly want to ride that AI revolution. Where there's probably mean reversal to to to for you to take profit on as you kind of go on this exciting journey, is that there are gonna be a lot of companies that create a crazy valuation and taking some profits on those could could be a good idea, right? Like if you had taken profit on Yahoo, on WorldCom on Cisco, and then later on redeploy it to you know the the the the the the you know the Googles and Amazons, you would be a much happier investor.

SPEAKER_02 20:31

US markets are obviously very uh liquid, a lot of depth, you know, a lot of layers to liquidity. Um, Tony, uh when it comes to um investing in China, investing in some of these thematic factor plays, um, talk us through a little bit some of the differences in terms of market structure. Um, what what do you investors need to consider that might be different when it comes to putting money to work in China versus the US from an execution standpoint?

SPEAKER_01 20:58

Okay, so if you think about China's capital control, so most of the money onshore, they cannot invest abroad. So they don't normally can invest in US, you know, emerging markets, unless you are a very specified QD investor. So most of money are within China looking for the onshore products. And because of the competition from SMN perspective, they are forced to provide much more niche market tools in ETFs, smart beta products, providing them more stuff to play with, right? So, in terms of the breadth of the offering in China, Asia alone, China is a huge market with all kinds of offerings in any imaginable subsectors. And the liquidity for the most onshore stocks are actually quite good because people don't cannot trade outside, and there are a lot of ETFs and small beta products there. But the investor crowd who trades this stuff, 90% of the trading volume comes from the retail people. Okay, so only 10% of the trading volume comes from institutional. So the momentum factor in China is even more exaggerated, considering there is only, I mean, there's a 10% price seeding and 10% you know price flow for daily maximum you know volatility for the normal main board and 20% for the starboard and the China X. So when you see um, you know, uh a trend is going on in the AI sector, for example, the memory space, you know, on the memory trips or the AI, there's strong value there, then all the liquidity goes to there. So if you look at the past one year, Half year, especially in the past quarter or so, I think the liquidity has drawn all to the sectors who have the most returns, and all other traditional sectors they you know have not much trading at all. And there are another major player uh in China, the Kwong strategy, uh private funds, a lot of the hedge funds that runs the quantum momentum strategies accelerate that you know trend as well. So if you look at the liquidity side, I think the landscape is very different from the US because people just like to trade and short-term momentum. So selecting the right tools, combine them together, the smart beta, it's my very important.

SPEAKER_02 23:14

Um, Fuji, talk to us about the the sort of tailwinds that come from the government. So in the US, obviously Trump is very pro AI. There was a headline yesterday about Hokal in uh New York, I think, uh putting moratorium on data centers and Trump saying this is a bad move, right? We want to keep on pushing AI, you know, statewide. Um how's the government response to AI uh different from the US?

SPEAKER_00 23:43

I think um obviously the answer is that you have seen um in the last uh even like 10 years ago, you know, the government started to set up the uh you know uh fund, uh like industry fund to subsidize and uh to really support the investment in this uh industry, not only in the primary market, but obviously, as uh Tony pointed out, in the secondary market, you have seen really the prosperity of all the themes around AI, and obviously supported by the capital uh injection from the retail investors as well as the uh institutional investors. So, on the whole, I think the the really the you know um two big players in the world, uh US and China, in the AI uh kind of competition, if you, if you will, um, is really driving the whole um ecosystem development as well as innovation. I think uh, you know, one of the key things that you have observed is that uh people talk about the restrictions on the chips import, especially in the frontier, you know, most advanced chips. But uh on the other hand, in the last five years, that is exactly the reason that China has to accelerate its own development of the uh self-sufficiency in semiconductors, in chips, you know, in equipment, you know, across all the AI industries. So this year, um, although Korean investors, US investors, you know, you all know about SK Heinex, um, you know, MGU, all that. And in China, what's you know, we are embracing and looking forward to is the IPO of uh CXMT, which is the leading uh memory uh company, equivalent of SK Heinex. So I think uh right now in China, you know, we are also in the intense competition uh across the whole value chain. And uh uh you are seeing this reflecting in the capital market as well. And that is exactly the reason that's driving the uh market rally here to date.

SPEAKER_02 26:00

Jason, you've been doing uh emerging market investing for quite a while. Um let's talk about how China differs compared to other emerging markets from an investment perspective, whether it be from a currency conversion side of things or from a you know uh US China trade dynamic. I mean, how does how what are what are the sort of the risks and benefits of doing China in particular? And by the way, this is debatable as far as whether China's an emerging market or not. It's still considered that. I think that's silly, personally.

SPEAKER_03 26:30

A lot of times you you simply can't argue with the uh index provider, right? They have uh they almost have uh you know a dick dictatorial control over uh what they put in an index, what they exclude. Uh, you know, and and and so yes. You know, China is uh in the EM index, it is the largest single country in there. Uh and you know, from that perspective, uh when you kind of think about uh EM, you really want to put it uh next to the DM. And DM, of course, in this case is dominated by the US, right? So in a way, when you think about EM, EM, you just think about G2, right? It's really just US and then China for all intents and purposes. Uh and so let's just talk about when did EM uh last outperform the US, right? It's been a while. Uh I think for those who stayed away from you know international diversification into EM, you would have been a very happy person during the last 20 plus years. But in the 10 years prior to that, uh you had a relentless EM outperformance over uh the US, and it really was uh relentless, relentless Chinese uh technology uh companies outperforming the US for about 10 years straight running. Uh and I think this stuff tailed back to what Fu Fuja and Tony was talking about, which is uh you know China uh hardware, you know, uh uh was actually the biggest benefactor, uh beneficiary from the internet revolution. I you know, the internet before it became this ubiquitous uh thing everywhere, we have to rewire the world. And I think we're in the process of rewire rewiring the entire world for AI, uh redoing all the data center, redoing all the cloud servers. Uh so I think you know, if you think about EEM versus DM, in this case, maybe you in China versus the US, uh it's not just you have lower valuation in China, and then any kind of profit taking in the US makes sense to go to China or go to EM. Uh, but it is that the front end of any revolution tends to be hardware, right? That's why the microns, uh, HK Heinek have done so well, the Samsung and the TSMC have done so well, because while the software companies are trying to figure out a business model, they're burning cash like there's no tomorrow. Uh the hardware companies, they only take cash. They have uh unbelievable margin, and the margin is doubling and tripling if you've been following the uh earnings report from uh Samsung and TSMC. Uh and so they're the biggest winner for at least the the first you know five-year cycle, and that might actually continue and be 10 years, like what we saw at the start of the internet.

SPEAKER_02 29:02

I feel the pain of the burning cash because I'm doing a lot of that stuff on my end. It is brutal, the the amount of cash I'm burning.

SPEAKER_03 29:09

Hardware providers, thank you for it though.

SPEAKER_02 29:11

Yeah, yeah, exactly right. Um talk Tony, talk talk to us a little bit about um how the demographic aspect of China uh provides either headwind or tailwind to the robotics side. Um I say that purposely. I mean I I think I'm right on this that the uh population growth is obviously I think slowed or turned negative, right? Because of the the one-child policy. Um and the US is different from that perspective, but every country is dealing with you know aging demographics. But how's the aging demographic aspect of China factor into the robotics push?

SPEAKER_01 29:50

Well, I think if you look at demographic change, I think a lot of the population aging issue was of one of the concerns, and you know, they have less working labors in future. Uh, but if you look at the you know, the graduation university students, them university uh degrees, you have like six million you know in the science technology every year for another about 12 years. So after only after 12 years, we start to see the labor force start to really impact the actual labor workers. But the need for the robotics does not really, you know, it's not really dry driven by the you know the population, not enough people to work. It's about the breadth of opportunity to incorporate into existing manufacturing industries. A lot of applications uh you know doing the new innovation, driving the old factory, transforming to robotics to increase efficiency, because now they are going global. A lot of local firms, they are building global supply chain and they're selling to global, right? So this kind of demand is driving the efficiency needs. And when you have the robotics, when you have the AI enhancement in productivity, I think the things you can do are much larger because now we're competing at a global level. And obviously, I think one of the uh factors if you think 20 years down the road, when the population really do shrink, then the robotics you know can play a vital role in 10 years or 20 years' time. But in the current stage, the population for the graduation people for the talents are still very, you know, very enough. I would say that. Yeah.

SPEAKER_02 31:28

Uh use the word uh larger. So I want to get into this conversation around uh cap size for a bit, Fuji. Um size is a factor, right? Smart beta is a factor, feeding factor, small versus large a factor way of looking at things. Um how do you differentiate our small caps versus large caps when it comes to China's markets, uh, and in particular when it comes to anything that's robotics or AI driven? I know a lot of small will go large because everyone's investing in these companies, right? But uh there's obviously an aspect of sort of differentiation in terms of government support for larger companies versus smaller companies.

SPEAKER_00 32:04

Yes, uh, I think if you look at the uh investment from the traditional multi-factor perspective, as you say, uh, you know, speaking of small versus large, in the last, I would say, three to four years, um, you know, especially China's economy is going through this transition from you know old to new economy driver, hence the uh headline growth rate is moderating. You are seeing the small cap outperforming uh large cap indeed. And one of the reasons is actually their premium liquidity, and that is exactly resonating with the outperformance of quant strategies mentioned by Tony earlier. However, I would say this year, you know, when something, especially the industrial trend or industrial prosperity, is very clear, for instance, AI themes, um, this year you are seeing the crowding effect around the large cap companies, which are the really the market leaders of every subsector of the AI industry. Hence, you know, the really the uh market performance is driven by the in in in institutional investors, because you know, they have really the bargaining power and the capital advantage, if you will. Um, and then you you see the uh you know uh like optical communication, for instance, in China, the leaders uh in no light, uh, etc. are really uh making new highs. So in this particular period, you will see the extreme uh power of large cap versus a small cap. So this year, actually, uh the loan-only fund outperformed the uh so-called market neutral or you know, quantum fund by a lot, by a wide gap. Um, but this is again, you know, especially because you are seeing great visibility of the industrial trend, and also you are seeing the profitability, you are seeing capital chasing this market. Um, but again, when something, for instance, right now, there's no themes very clear what is driving the market, you are you are again looking at small-to-me caps starting to have a better performance.

SPEAKER_02 34:28

Uh Tony, a lot of people that are on this will recognize some of the names mentioned, like SKINX and others, but there's a lot of companies in China's markets in the US that people have never heard of, no idea how to even find them. Um, you're on the ground there with CAMC. Talk to us about how you go about sourcing you know investment opportunities, how do you look at new opportunities, how do you even research new opportunities?

SPEAKER_01 34:50

Yeah, I mean, now given the AI tools, a lot of desktop research works uh dedicated to the AI support. So much more time can be spent on the ground doing the actual research, visiting companies, talking to the management. I think that's very, very key going forward from investment, identifying new companies. You know, this is something you need a large local research team. You know, as a China MC, one of the largest local house, we have about 300 research people, you know, traveling every day, visiting for like 4,000 companies a year, just to get an idea of what's going on in the latest, especially in the technology sector, it just keeps updating every single week, right? So that's one of the key differences in the traditional industries, the consumption names, the old industry name, they don't really change that much. So being on a quarterly visit would do the work. Now I think with this um, you know, the new AI tools, they help you to do the ground data cleaning work and you can filter out. So, what's the you know, some of the fundamental data to support uh you know, starting point for us to research? Then we narrow down to the on-ground, you know, visit to the management company, and you will see a lot of interesting names that even didn't even pop up to the investment team locally one year ago, now become the very popular names uh in the AI space. I think that goes to the most of the mutual fundhouses who are on the ground providing the insights. And these insights we incorporate into our smart beta or the indexed design technology uh methodology to understand what reflects their latest investment, you know, uh the latest RD directions. So I think given these insights, that's where the alpha is coming from. And we think that's very important for the international master to distinguish the Chinese names and no longer the Internet 2.0 era where the Alibaba tension, that's all you know, put people people know, like the Jongji Inno Lite, the communication for optical modules. Now it's like the largest supplier of the AI optical modules worldwide. I think the top seven of the top 10 suppliers worldwide are from China. So that's changed a lot from one year ago. So these kind of names they have 10 times followed their prices in the last 10 months. So this is something you need to have the on-ground research team to really cover the updates, give you the latest conviction to invest.

SPEAKER_02 37:18

Jason it really, and you've got um a number of investment strategies and vehicles. Um, because obviously the question for a lot of people is how do you actually actually execute on some of these themes, some of these smart beta plays, you know, tons of ETFs in the US. Um talk to us a little bit about how people uh access these types of videos.

SPEAKER_03 37:39

So uh you know, like all EK providers, we have a suite of the core allocation, and so those are the boring stuff, right? Like US large, international large, like I m more broadly. Uh, and then uh we bring to markets uh regularly things that we think are you know probably theme of the decade, right? Something that is big enough, persistent enough, that really warrants a meaningful allocation within your satellite. So uh, you know, we we certainly brought forth uh in in partnership, that's why we're all on this webinar together with you, uh, in partnership with uh China Asset Management, like essentially the Black Rock of China, uh a China uh transformative technology ETF. Uh so it's a thing we believe in. You know, I talked about, you know, you turn the clock back to the start of the internet, right? It was Asia hardware led by a lot of China hardware that outperformed you know NASDAQ for about 10 years running. Uh, we expect that to probably repeat. It's starting at a much lower valuation, which makes that that you know, return advantage uh significantly more likely to be realized. Uh so you know, we we brought to market kind of a smart beta construction uh of uh Chinese technologies that are listed at Hong Kong, that are listed in China, and like Fu Jia and Tony have mentioned, these are a lot of names that you've not heard of, right? Because Ayuaba and TenSense are no longer the front runner in terms of uh AI tech. And certainly they're not hardware tech. It's really the hardware tech that is going to dominate, that is going to basically lay the groundwork, you know, till the soil that that will then become nutrient for all software tech, software AI technology company to thrive. But in the beginning, it's really the the hardware guys, and a lot of these hardware guys are the niche component makers that you've never heard of, but they are dominant and they have enormous margin, and they're in many ways the only game in town. Uh, so that's you know, thematically we we we believe in uh the AI theme, but within that theme, what we really, really believe in is the the the you know hardware leadership that is probably gonna be the the outperforming uh thematic sector for the next 10 years.

SPEAKER_02 39:51

And and Fuji, how how diverse is that uh hardware opportunity set when it comes to China's markets? Meaning, are we talking about three companies, 10, 20? I mean, what what does the what does the sort of opportunity set look like?

SPEAKER_00 40:03

Actually, there's um a huge basket of uh stocks. Um, because uh, you know, as Jason pointed out, when we think about this collaboration and this uh particular thematic product, we think of what is really outperforming across the entire industry that are innovative, that are driving China to future. So we are not only defining the uh transformative tech just in AI, but also in advanced manufacturing, also in biotech, uh, you know, also in new energy. So again, you know, when you think about the 15th five-year plan, uh, you know, what is really the uh top-down guidance, you are looking at a basket of industries that is driving China to transform. And then within each industry, because many of them are just emerging, so you are seeing new entries, you are seeing competition, you are seeing little giants growing to be large companies, and then you know, great examples are you know, say, optical communications, as we kept mentioning. So I think you are looking at a long way, uh, you know, really a pathway to the new future leaders. And that is why, you know, when you think about investment in China, innovative sectors, of course, you know, you look at the financials right now, but bear in mind many of the sectors will change uh together with the technology innovation. So I think for us to create this index, we look at really RD to be the most primary sector, uh primary uh metric to drive the uh innovation because we are we don't want to look at things static. We think everything is changing dynamically, um, and that is why our uh you know basket of stocks will keep evolving together with the industry change.

SPEAKER_02 42:09

Survivorship bias is a real thing. Uh, Tony, this idea that yeah, companies boom and bust, they exist and they don't exist, and the NSEs are showing you just what's existed, and yeah, a lot of companies have obviously gone by the wayside. Um, you mentioned from a research perspective, there's a lot of on-the-ground work that's done. But presumably there's gonna be some companies that are not gonna make it. I mean, just competition is gonna cause that and mismanagement. Um, talk us through some of the some of the risks when it comes to uh investing in this type of a part of the marketplace and how you try to avoid that that risk of ruin, in quotes, from an individual individual company just not not making it.

SPEAKER_01 42:49

Yeah, I think that that has been a lot of the concern in the past when the information disclosure was not so transparent. So I think that's one of the key aspects that exchange regulators are trying to improve. First, you know, regardless of the company is good or not, you need to disclose the right information for people to judge and review, right? So that's step one. So that's a lot of you know regulation have been going on to um you know enforce people to post on the latest transparent and also authentic data on the financial, but also on the ESG aspect, on governments, on internal controls. So that's step one. Step two, I think a lot of the uh risk comes from the uh you know the competition, as you mentioned. There's a huge competition in onshore in terms of price wall. So if you don't have a lot of capital, uh strong parent company, or a lot of the you know, previous economy profits in terms of the huge price war competition, that's what we see in the internet you know, name giants on the delivery side, on the you know e-commerce side, they just draw down the margin crazy. So that's why you see a lot of Hong Kong stocks in the old industry internet names are you know plumbing. Uh, that's why I think for the onshore research team, one of the key issues for them to ask definitely is the risk first, and whether this company will give you a fundamental risk by holding them. Then the next question is how much they can grow, because you know the perpetual, the permanent loss of capital is the number one risk for us. And we do a lot of the screenings, not just on the upside, but on the downside protection and to have your longer play. So we have both the sector analyst and also the ESG analyst. And together with fundamental research people offshore and onshore combining to give composite ratings and also provide the latest views. And we encourage internal debates. So we do not run a consensus-based or the top-down CIO approach where just no decision has been made, but we encourage different perspectives, different debate within the team. And you see when we formulate a lot of the technology names, especially in the early stage, there are definitely a lot of risk. So we want to try to minimize that by having the on-the-ground latest and cross-check on the suppliers, on the end customers. So we also go to expert calls. We also go to the non-traditional routes of information data gathering sources. That's how we minimize the risk.

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SPEAKER_00 45:38

Yeah, sure. I think this is one of our favorite slides as well. However, when you think about what US and China play different roles in the whole AI ecosystem, you are looking at different edge provided by the two countries. So, you know, to elaborate on that, obviously US has been leading in the frontier model, large language model, and also leading in the hyperscale. Obviously, they account for 75% of the world compute. So everything about cutting edge technology or leading edge chip design, I think that really is what US leading the whole world of. However, as we have already mentioned briefly earlier, China really has the scale advantage. And DeepSeek is a great example that offered to the whole world in open source, but only at uh one-tenth of the cost of the US model. On the other hand, you know, mentioned earlier that we have the sufficiency in energy, uh, in the uh electricity costs. Um again, you know, in terms of AI infrastructure and uh uh supply chain, we are very proud to be leading uh due to our scale advantage and cost advantage in the whole manufacturing capability. So I think again, US and China play the complementary role as well as being competitors of each other in every aspect of this whole AI ecosystem. But in the world, uh in the end, I think the whole world really benefits on one hand the cutting-edge technology, but on the other hand, the cost cut uh in terms of the large language model as well as the uh AI infrastructure built out. So uh when you look at investments, uh investment opportunities, you really want to find the winners in different countries, in different capital markets. And that is why in China right now, you have seen the rotation uh in the, especially in the ETF or smart beta play to be around upstream materials, midstream uh equipment, as well as the uh semi uh semiconductor chips. And then I think in future, as also will be playing out in the US, at one point you will see the uh uh unit economics work out so that you will see the commercialization and application to uh outperform. So I think uh there's still a long way to go to expect the uh investment opportunities to be playing out.

SPEAKER_02 48:43

A couple of questions here. Uh this will go to you, Jason, on uh somebody saying I'm investing in mid-cap tech in Asia that underweights

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SPEAKER_02 48:50

China. Uh are your offerings likely to be included in a regional smart ETF? So this is an interesting point about vehicles. It's like uh a lot of uh ETFs have a name that sounds like it plays a part of the world or a theme, but it's not really pure play. Um so, Jason, how would you address that for somebody that's looking at this part of the marketplace?

SPEAKER_03 49:13

So, first and foremost, you know, whenever you buy an ETF, uh you must realize that you know people have gotten really, really good at giving a compelling name, right? And it may not match, like you know, Mike was saying, uh, what you will actually get within the ETF. So the most important thing is look at the ETF, look at the index of tracks, and then go look at you know at least the top 10 names and say, hey, you know, do those names map into the opportunities you're trying to access? And and and what you'll often see is uh, you know, uh if it's a a let's say an EM product, right? You know, when you look through it, uh, you know, some people exile China in their EM offering. Uh and so you may not be getting some of the most interesting uh kind of hardware plays uh that are dominant uh in kind of the AI world as sort of you know the only game in town when it comes to components. So I think it's just useful to look through, and especially when you look at something that's more Asia theme, uh, you know, it could be it could mean anything, right? So someone could be making a big bet on India, who unfortunately thus far seems to be kind of left out, and maybe is the one one of the few kind of Asian economies that is perhaps suffering from AI because they're probably seeing a lot more of their kind of software outsourcing, you know, their their SaaS play, their cost and outsourcing being taken away, whereas a lot of you know hardware like you know, Korea, mainland China, Taiwan uh are are like the biggest uh beneficiaries. So you really want to look through when it's such a broad theme like Asia, exactly what are you getting uh in that Asia product? What calls are they making? Uh and I would say if they're not making calls on AI hardware, uh you likely won't get as pure of a play uh for at least the front end of the uh AI revolution.

SPEAKER_02 50:59

So uh another good question here. Uh I'll go to you, Tony, on this. Uh, how does China get European, Asian, Latamp countries to purchase their hardware and software when most of these countries are risk-averse due to China's privacy policies? Now, so there's there's there's a narrative around that, and then there's the the reality of that. And uh the truth is probably somewhere in between. But uh I think it's an interesting question, sort of how do you how do you convince other countries to uh be more comfortable?

SPEAKER_01 51:23

Well, I think that's a common question across the world. Uh there's definitely the national security issue, there's the company privacy issues, but after all, you need to know what why are you purchasing them? I mean, so what kind of functions, what does these products actually fulfill your needs? If the Chinese products are so good, right? So at the really low cost and performs well, is it at the company's interest to explore whether this is going to be uh you know valuable addition to your firm's infrastructure? And privacy issue is even highly sensitive in China now because all of SOEs they care about these privacy uh policies. So there are being new forces uh in the regulations, in the laws to prevent manipulating of the data on the software side, on the AI side. But from an investment perspective, if you look at the supply chain and also the importance of China supply chain, you cannot go around China. It's impossible. So, regardless, I mean, whether there is a still panic issue to be solved, I think the China is playing a vital role in the supply chain supply side. Well, the you know US play on the demand side. There's a big competition, but there's an ecosystem that white need each other. So I would say it's it's an issue we're improving and it's an issue that is uh applied to all. But we are we're seeing the new trend as demand and the product side will have the competitiveness.

SPEAKER_02 52:54

Again, folks, if you're for the CE credit, I will email you afterwards to get your information, submit it to the CFP board. Uh, I'm gonna try to make this an edited uh webinar recording that'll go out on the YouTube channel shortly after this uh after this uh recording. Um as we wrap up here, maybe just some final thoughts um from each of the panelists here, and I appreciate everybody that's here, especially given that as the earliest webinar I've ever done. So if you're on the West Coast, kudos to you for waking up and watching this in bed. Uh Fujia, um what should what shouldn't people here really take away the most from everything we talked about when it comes to uh China, AI, smart beta factor, all the things we kind of touched on?

SPEAKER_00 53:32

Yeah, I think um, you know, when you think about um the whole world, what is really driving the change right now, and that is actually one of the most simple questions, because it cannot just happen in one part of the world, it's happening everywhere. So I think thinking of China is actually easy from that perspective. You look at what is innovative, what is growing, and what is changing. And China is indeed going through this transformation. So thinking of China in the old model of real estate, internet, education is in the past. I think you should look at what is happening right now and pursuing opportunities to drive the future.

SPEAKER_02 54:18

Uh Tony, Les and you and I got together, we were talking about uh EVs. So I don't know if you want to leave uh anything to the audience as far as a cool new EV that you were gonna buy yourself. Uh, but any sort of majors or takeaways from you?

SPEAKER_01 54:29

Yeah, actually, I changed my traditional cars, both of the cars to EVs in the past year. And you know, I'm really excited, even on the ground, seeing every new model coming out every every month, just huge competition, and that reflects the innovation is going on on the ground. And I would say investing to China uh now requires a lot of knowledge, and also accessibility is very different now. There are A shares, there are Hong Kong shares, there are ADRs, and most of international investors probably do not have too much um you know idea on what's going on in the starboard, in the innovation board on China. So we want to build something that you know incorporates the accessibility, also the investment research insights, and also the holistic picture of all innovation-related industry into one product and dedicated to China investment. And that's why we partnered with Jason on Reliance product on the Q to give you the access and also to provide you the local insights within the smart beta world. Yeah.

SPEAKER_02 55:29

Uh by the way, folks, it's the first time that the the ticker was actually mentioned, CNQQ. If anybody's curious, uh to Jason. But Jason, any kind of thoughts on that? Maybe just hit on a little bit uh to the extent you're comfortable. Um, that that collaboration with CMC.

SPEAKER_03 55:46

Oh, yeah, yeah. So uh, you know, I it it's always good to repeat you know the ticker, right? Because ultimately, you know, if you like what we're saying, if you like the methodology behind it, if you like the theme behind it, uh C and QQ, you know, China's QQ, right? It's China's NASDAQ, China's transformative tech, uh is something you want to look into. All right, so I mean just to conclude, right? Uh I don't think of US and China as competing in the AI space, right? That's the absolutely wrong way to think about it. Just imagine, right? Like there for Amazon and Google, uh, and every major you know tech success in the US, there is a counterpart in China, right? They don't compete because uh they they they have protected home turf, right? Like, you know, the Chinese tech companies don't come to the US, US tech companies don't go to China as a result. Both make billions upon billions in profits every year from a massive captive market, right? So they compete in name, but not in reality. So if you want to harvest the value that AI is gonna create for China, um you you you've gotta make sure you're you're playing some of these AIA names. Uh so that's the first thing I want people to remember is if you want to harvest the value that AI can create for the Chinese market, you're not gonna get that from the Anthropics, the Open AI, the Microsoft, the Amazons, right? Like it's the the the their corresponding counterparts in China, and then you'll find them in the CNQQ. And the other part is there's also a time element to it, right? As I mentioned so many times on this call, right? The first 10 years of the internet revolution was all the hardware players. I think the first 10 years of the AI revolution is gonna be hardware players as well. And in that sequencing, if you're looking to rebalance and tactfully select your theme, I would say, you know, Asian hardware, so a lot of that's gonna be these leaders in in China, and that uh makes the rebalancing from whatever you've already made a lot of money on in some US AI names, right? You might want to do some rebalancing into some of these hardware names in China just so that you're appropriately capturing that that theme for the next decade.

SPEAKER_02 57:54

I think it's a uh a good place to wrap up this uh conversation. Appreciate those that attend to this. Again, folks, I will email you afterwards uh and learn more about uh what Jason's doing with Raliant and what Tony and Fuji are doing with CMC. Uh, I encourage you to uh consider these types of uh ways of think about putting money to work because it's different. And I think if you want to have differentiate returns, you have to have different types of holdings uh from different parts of the world. So thank you very much for joining, and we'll see you all in the next webinar. Thank you, Jason. Thank you, Tony. Thank you, Michael.

SPEAKER_00 58:22

Thank you. Bye-bye.