Lead-Lag Live

Phil Wool on Emerging Market Anomalies, Quantamental Strategies, and Active vs Passive Investment Dynamics

• Michael A. Gayed, CFA

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Uncover the secrets behind the world's most dynamic markets with Phil Wool, the head of portfolio management and chief research officer at Rayliant Global Advisors. Navigate the intriguing differences between developed and emerging markets, and learn how Rayliant Global Advisors leverages behavioral finance and market anomalies to craft innovative strategies. Phil Wool shares his deep expertise, focusing on how these anomalies present unique opportunities, particularly in markets where retail investors have a profound impact, such as China, Korea, and Taiwan.

Gain insights into how emerging markets like Korea's family-owned conglomerates, known as Chaebols, shape the investment landscape with their distinctive governance structures. Explore the debate surrounding active versus passive investment strategies, and understand how systematic approaches can exploit opportunities in both efficient and less mature markets. Phil Wool offers a peek into the strategic decisions behind Rayliant's active ETFs and their potential to capitalize on market inefficiencies often overlooked by traditional indices.

Discover the intricacies of quantamental strategies and the role of strategic partnerships, such as the collaboration with Sumitomo Mitsui DS Asset Management for a Japan fund. Examine the broader implications of geopolitical shifts and economic growth in emerging markets beyond China, particularly in India and Taiwan. This episode promises a comprehensive understanding of emerging markets, offering a unique perspective on how to navigate these complex and vibrant economies for potential alpha.

DISCLAIMER – PLEASE READ: This is a sponsored episode for which Lead-Lag Publishing, LLC has been paid a fee. Lead-Lag Publishing, LLC does not guarantee the accuracy or completeness of the information provided in the episode or make any representation as to its quality. All statements and expressions provided in this episode are the sole opinion of Rayliant and Lead-Lag Publishing, LLC expressly disclaims any responsibility for action taken in connection with the information provided in the discussion. The content in this program is for informational purposes only. You should not construe any information or other material as investment, financial, tax, or other advice. The views expressed by the participants are solely their own. A participant may have taken or recommended any investment position discussed, but may close such position or alter its recommendation at any time without notice. Nothing contained in this program constitutes a solicitation, recommendation, endorsement, or offer to buy or sell any securities or other financial instruments in any jurisdiction. Please consult your own investment or financial advisor for advice related to all investment decisions.

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Speaker 1:

Typically, when people talk about delineating between developed and emerging, they're thinking about the development of the economy but also the development of financial institutions. So across EM you have a really widespread in terms of economic development. You've got economies like South Korea or Taiwan which are extremely well developed. These are some of the biggest exporters of high technology on the planet. They've got really efficient industry and so forth. But in markets like that you'll find the financial institutions are less well developed, so there isn't a huge base of sophisticated institutional investors.

Speaker 2:

I'm excited for this conversation because I only got to hear Phil speak once and I was very impressed when he was talking about Reliant, the funds that Reliant has and the approach that the firm takes. Hopefully, this will be a good conversation. This is a sponsored conversation with one of my clients, Reliant, which has a number of ETFs we're going to get into. I try to bring on clients that are unique in the way they approach markets and I think there's a lot to learn from the way the company Reliant approach markets, and I think there's a lot to learn from the way the company Rayleigh has put things together. So, with all that said, my name is Michael Guyatt, publisher of the Lead Lag Report. Joining me for the rough hour is Mr Phil Wool of Rayleigh, and, Phil, introduce yourself to the audience more formally for those who don't know who you are what's your background?

Speaker 1:

what have you done throughout your career? Where you've grown? Yeah, well, first of all, michael, pleasure to be here. So I'm Phil Wool. I am the head of portfolio management, the chief research officer, at Reliant Global Advisors. We're an asset manager that services primarily institutional clients. We build global equity strategies with a focus on emerging markets, including China, and we've launched in the last couple of years a series of ETFs that give every investor, not just big institutions, access to these markets where we're applying active management. So these are active ETFs that use our proprietary models to do stock picking within EMX China and develop equity markets.

Speaker 1:

My background is actually in the academic world. So before I co-founded Ralliant, I was a professor at the State University of New York. I was teaching investments, but my research was all about behavioral finance and, in particular, I was studying equity market anomalies and how investors could build quantitative strategies to exploit mispricings in markets. A lot of that research was focused on US stocks, because if you're an academic publishing papers, you focus on the US stock market. Those papers are more likely to get published, but it turns out in emerging markets there are many more individual investors. Behavioral bias is more rampant because you don't have as much professional smart money in those markets, and so there's a bigger opportunity to take advantage of those mispricings. And that's one of the reasons that Raeliant started up was really to focus on giving US investors access to that sort of interesting behavioral alpha that we find in emerging markets. So that's me, that's a bit about Raelian, and I'm excited to talk about the strategies and emerging markets generally.

Speaker 2:

So there's a lot I want to unpack based on this. First of all, I think you're probably familiar with the criticism that the academic world doesn't really match up with the real world when it comes to investing in markets. Talk about the elements of truth to that, the elements of lies to that.

Speaker 1:

Yeah, I mean, I think it's typically people look at finance textbooks and they think to themselves academics in the ivory tower are creating these theories and then, as soon as you deploy those in markets, things start to break down.

Speaker 1:

But my research has always been focused on the shortcomings of theory. What happens in markets? What are the sorts of frictions that you observe when you try to take a strategy and trade it? But, more importantly, where does psychology and where does human behavior actually lead to the sorts of problems that derail finance theory when you try to take that into the real world? And so a lot of what we're doing is looking at departures from theory, where we think certain relationships should hold, where we think fundamentals should dictate prices. But then in markets, especially markets that are really driven a lot more by individual investors, investors doing recreational trading you see anomalies, and that's where the strategies come in. That's what we really built our ETFs to exploit. So I'm very much on board with this idea that the theory doesn't necessarily hold in reality, but I think that's an opportunity for active investors.

Speaker 2:

Let's talk about some of the typical anomalies right that exist in US markets. We know momentum is somewhat of an anomaly and people know it works. You would think if markets are efficient it shouldn't because everyone knows it works. Several other factors anomalies have been noted and a lot of them have been arbitraged away. You can argue works. Several other factors anomalies have been noted and a lot of them have been arbitraged away. You can argue what are some anomalies that you found when it comes to overseas markets that are not in the US, that are really prevalent outside of our borders?

Speaker 1:

Yeah, it's a great point, and referencing anomalies like momentum value is another one that is very well known hasn't worked quite as well as it used to in the US. There are other anomalies related to quality, low volatility. These are the types of factors that investors think about in the US market, for example, and there are a lot of strategies and products that have sprung up to give investors exposure to those factors. Those are typically what we think of as smart beta factors Super simple notions like investing in lower risk stocks is generally more profitable. Investing in cheaper stocks tends to be more profitable. What you find is that over time, as you suggested, those anomalies to the extent that everyone knows about these things they're going to be arbitraged away.

Speaker 1:

One of the nice things about emerging markets, relative to developed markets, particularly the US, is that in emerging markets, it's not as though the individual investors that do most of the trading. So if you look at China, for example, the individual investors that do most of the trading. So if you look at China, for example, up to 80% to 90% of trading is not institutions, it's retail investors. Korea, taiwan 60% of trading is retail investors. They're not reading the academic literature, they're not reading industry reports. They're not watching lead lag interviews. They're really recreational trading. Lead lag interviews. They're really recreational trading, teaching themselves what to do. And so the anomalies that were arbitraged away, where you see all that alpha decay in the US market those anomalies can be resurrected in emerging markets. So things like value, low risk, momentum, quality signals work.

Speaker 1:

Now to your point. There's a lot of interesting stuff in emerging markets that wasn't researched because academics don't have motivation to study anomalies that they can't publish on, and so in emerging markets you see interesting nuances. So in Korea, for example, you have family-owned conglomerates called Chabal and they present interesting characteristics from a governance perspective, and that creates opportunities. If you can pick out well and poorly governed companies, investors even in the local market they tend to undervalue that. We can look at smart money foreign investor flows into emerging markets so we can see what are sophisticated hedge funds and mutual funds and institutions offshore investing in within Taiwan's stock market and you can piggyback on those smart money trades. In some of these markets we can actually see what retail traders are investing in and we can take the other side of their trade. So there are lots of interesting data sets and market-specific anomalies, and that's one of the other things that Raliant really focuses on in the research that goes into our strategies.

Speaker 2:

I feel like we should define emerging markets because, as you know, different indices can have different classifications. Ftse has, I think, as a repulse. Ftse does not include South Korea as an emerging market and MSCI does, or maybe I'm having them flip around. You probably know better than I would. An emerging market and MSCI does, or maybe I'm having them flip around. You probably know better than I would. But how should we think about just the category in general?

Speaker 1:

Yeah, so you had it right. We generally follow MSCI, so we would include South Korea among the emerging markets. Typically, when people talk about delineating between developed and emerging, they're thinking about the development of the economy but also the development of financial institutions. So across EM you have a really widespread in terms of economic development. You've got economies like South Korea or Taiwan which are extremely well developed. These are some of the biggest exporters of high technology on the planet. They've got really efficient industry and so forth.

Speaker 1:

But in markets like that you'll find the financial institutions are less well-developed, so there isn't a huge base of institutional investors. Some of the market regulations are lagging behind. There are capital controls and FX restrictions that make those markets challenging from a global allocator's perspective. So it can be economic development, it can be the speed of GDP growth in these economies. It can be just that the financial institutions are lagging behind Generally, the types of frictions that lead a market to land in the emerging category these are exactly the types of things that create alpha opportunities. So for us, when I'm thinking about where I can find the biggest mispricings, I'm going to go to markets where there's a less developed financial institutional infrastructure. I can go in the market and trade, but I'm not trading against lots of other sophisticated institutions.

Speaker 2:

Generally, I think, isn't that sort of key to the whole idea of identifying anomalies. You need to have large money also at some point. Try to arbitrage in a way, and you hope you're among the first to do that to really benefit from and generate that alpha. To the extent that, as we know, the last several years of emerging markets have broadly been a very hard category to the MESA, a lot of institutions have just, I think, avoided. So you mentioned the infrastructure has really not been there. There's been. Even if the infrastructure were there, it doesn't seem like there's that much interest because US markets keep doing what they're doing and it's been a very passive environment anyway in terms of fund flows. So if you identify an anomaly when it comes to overseas markets, I mean, how long can it take for it to close?

Speaker 1:

That's another great point. Ultimately, we need other smart investors to recognize that there's a mispricing. We need prices at some point to converge to fundamentals In emerging markets. That can happen in two ways. One, we're not the only professional money manager operating in these markets. It's just that there's an imbalance. There are more retail investors and the retail investors are doing more trading and they're having a bigger influence on the prices than institutions.

Speaker 1:

But ultimately to the extent that whatever the retail dumb money has missed eventually shows up in companies' financials. Eventually, companies that have lots of opportunity and potential for growth they realize that growth and it starts to show up in their cash flows and their net income. Eventually even individual investors in those countries. They're going to wake up to the mistakes that they've made and they'll sell the stock that's overvalued if the earnings growth never materialized. They'll buy a stock if suddenly they see that earnings have jumped.

Speaker 1:

So that's one way it happens and the other way is other institutions eventually get wise to the mispricings and in the long run, even though those institutions make up a smaller part of the capital, their trades can have influence and gradually push prices back up to where they should be Now. The speed of convergence in emerging markets means that generally high conviction strategies that run really concentrated portfolios in these markets. It can take a long time for some of those mispricings to converge, and so one of the reasons that we like a more systematic, higher breadth strategy in these markets is that we can trade many different opportunities and, even though some of them might be slower to converge than others, we wouldn't go through periods where everything in the portfolio is underperforming relative to the benchmark. So different ways of getting active in EM.

Speaker 2:

All right. So I'm going to bring in a question and I'm going to broaden out a little bit. For somebody watching on X from Gustavo what's the difference between trusting the numbers, slash earnings, differentiating that from gambling? Now, the criticism around anything emerging market related is you don't know if the numbers are real. Standards are not like they are in the US. How do you think through that? Because maybe the anomalies are structural, just because there is this trust element around what it is that people are actually trading off.

Speaker 1:

Yeah, this is critical in emerging markets and I think one of the reasons that we tend to see discounts in emerging markets, one of the reasons that mispricings can persist, is that investors who don't have a specialization in EM, they look at the financials and they understand Accounting standards in EM. There are so many different types of emerging markets. Accounting standards are all over the board. Enforcement, auditing generally lag behind developed markets, and so there is validity to this concern that accounting integrity, the enforcement of financial reporting rules in EM it's not up to par, and so investors who can't get into the nitty gritty and differentiate between good and bad actors, ultimately they decide they're either going to stay away completely or they're going to apply a huge discount to emerging markets. So our job as an active investor that specializes in EM, we go in and we're trying to make those really fine differentiations between companies that, even within an accounting system that's not as well developed, that they have strong financial reporting integrity. We can look for red flags, so inconsistencies, where you expect that if one quantity, like accounts receivable, is moving in one direction, sales should have a corresponding move, and if you don't see that, that can be a red flag.

Speaker 1:

There are much more sophisticated measures of earnings quality that you can apply. Some of those are market specific and that's one of those signals that stopped working in the US. So it used to be. Prior to the mid-1990s there were earnings quality signals measuring. To the mid-1990s there were earnings quality signals measuring, for example, accruals versus cash flows. That worked really well in the US market. Once that anomaly was published, once institutional investors started really paying attention to earnings quality, that was arbitraged away In EM. Earnings quality is a perfect example of a signal that works really well, in part because accounting integrity is such a problem in EM. So I would argue it is an issue, but this is one of those things that creates opportunity for smart investors who can be active and make those differentiations.

Speaker 2:

How do you think, through analyzing international markets from the standpoint of how strong their legal structure, is potential for corruption at the government level interacting with the private sector? I mean, I've got to assume that's not that easy to necessarily quantify.

Speaker 1:

Yeah, it's not easy to quantify in some cases. In some cases it's very clear cut. So when you look at Korea, for example, which MSCI includes among emerging markets, the Korean discount is something that people talk about. This is a market where half of the index market capitalization is tech stocks and yet it trades at a forward PE of 10. Compare that to a market like Taiwan. A market like Taiwan which is relatively cheap. It's trading at a forward P of like 20 times, but the institutions in Taiwan are a bit stronger than in South Korea, so sometimes you can see this showing up in terms of a discount Again in Korea.

Speaker 1:

When you think about what gives rise to that discount, in large part it's corporate governance concerns. I mentioned Shable. This is a corporate structure in Korea big family-owned conglomerates where minority shareholders are often at a huge disadvantage, recognizing that that's an issue in Korea. This is a market where you want to develop methods of detecting strong versus weak corporate governance. That can be a huge differentiating factor when you're looking for bargains in those markets. So, again, I tend to look at any kind of deficiencies in a particular emerging market in terms of accounting transparency, in terms of corporate governance, in terms of legal institutions. It creates opportunities to pick winners and losers in those markets from an active standpoint.

Speaker 2:

Let's get into some of the specifics around the funds so we can kind of go through the process. So I think the approach obviously is interesting, makes a lot of sense. So I'm showing here the sheet on how RAYC works. First of all, quantamental is quite the term to explain. Let's let's explain what a quantum mental approach means.

Speaker 1:

Yeah, you know this is a term that when we started using it it wasn't very common. A lot of people have adopted, uh, this terminology, and it can mean so many different things. You know, for some, uh, it is a fundamental researcher and they've just got some quantitative screening tools that they're using to help aid in the research. For us, we're much closer to the quant end of the spectrum, so we think about quantamental ultimately as systematic strategies that stem from fundamental insights as to what are the important factors that an investor should be looking at in these markets, and we develop trading signals and we apply those and we can talk a little bit more about how that happens. But ultimately, every trading signal that we use it's got some intuitive foundation in companies' fundamentals or some obvious behavioral bias that we think we can exploit if we just measure it in the right way.

Speaker 1:

So this is not a black box. It's a set of systematic signals and for us, the goal is we just want to try to synthesize in a really rigorous, automated way the types of things that a good local fundamental analyst would be doing, and if we can accomplish that, then we can apply that frame of analysis to not just a handful of stocks, or maybe a dozen stocks that one analyst could cover. We can apply that methodology to thousands of stocks that make up EM. So if you look at our portfolios, what you'll find is we'll have some familiar names You'll see a Samsung or a Taiwan semiconductor manufacturing, but you'll also see lots of smaller stocks that it would be hard for an EM fundamental deep dive researcher to cover, and for us that's part of the approach to unlocking the opportunity. So, to your point, having somebody do a deep dive is hard to cover and for us, that's part of the approach to unlocking the opportunity.

Speaker 2:

I see it to your point having somebody do a deep dive is hard to do, so let's talk about how you filter that universe. On the sheet here it says you're looking at the mainland listed China, asia and then you've got basically kind of a big data aspect to this. What are some of these inputs? I mean, you mentioned different signals here, but let's talk about some of the more important ones that have sort of the higher weightings as far as how much they impact the decision.

Speaker 1:

Yeah. So we start with the universe so say it's China, We've got ETFs that address different markets, so we've got a China ETF, we've got EMX China and we've got a developed ETF which includes US stocks, but say we're looking at the China universe First. We've made a decision with China that we only want to invest in onshore China A shares. So that's the first decision we make. Is there's sort of a strategic determination that A shares those mainland listed stocks? That that's really where you want to go for growth in China, for diversification, for alpha.

Speaker 2:

And sorry, just to be clear, so a lot of the China-based ETFs. Are they also A shares? Is this sort of like uniform across?

Speaker 1:

the board. So initially access to A shares was difficult. So some of the oldest mutual funds ETFs that you find that trade China they mostly trade Hong Kong stocks or US ADRs, chinese companies that listed, you know, on the NYSE or the NASDAQ. That is, in our view you end up with kind of a selection bias going to be invested in tech stocks that when they started up couldn't list in China because they weren't profitable and they're really strict listing standards in China. So the 10 cents, the Alibabas, the you know net ease type companies, those are more prominent offshore.

Speaker 1:

Onshore what you get is maybe 15% of the index or so in that kind of internet technology, explicit tech allocation, but a lot of the market cap is actually material stocks. It's industrials, it's companies that are really more closely tied to China's real economy, and that's what we want to target. The other benefit onshore is that if I trade Alibaba I'm trading against really smart investors, because that's a stock that is mostly traded by offshore institutional investors. Onshore, like I said, 80% of trading volume is retail. So onshore your counterparty is probably a retail investor. That is, you know, either just having fun with it or doing sort of amateur analysis. So we think we have a bigger edge there.

Speaker 2:

So I mean stuff real quick about that, that move that China had, you know, when they announced stimulus and it went bonkers for a day or two. I mean, was that smart versus dumb flows? Was that sort of the dumb flows the automatic reaction? From what you could tell?

Speaker 1:

Yeah. So when I talk with clients and colleagues, other investors, offshore sentiment toward China has been bad. That's not a surprise to anyone. Onshore, if you can believe it, sentiment is even worse. So the typical mainland retail investor had just given up on the stock market.

Speaker 1:

When you think about the timing of China's stimulus announcements, part of it was the People's Bank of China was waiting for the Fed to move and then, as soon as the Fed cuts, they're going to go in with lots of monetary stimulus. They had been doing that kind of monetary stimulus before and it's not really helpful if consumers aren't spending money, businesses aren't investing. It's a liquidity trap. The timing of fiscal stimulus announcements that's what everyone was waiting for. The fact that they did that at the end of September, right before a seven-day holiday, china's golden week holiday, when the markets are closed.

Speaker 1:

The object there was get retail investors excited. This is playing on FOMO and trying to make retail investors plunge back into the market, boost the index and that reflects well on China sentiment and the goal is to try to get it into some kind of sustaining virtuous cycle. So I think what you saw there was retail investors suddenly getting excited again about the stock market. We've seen it cool off since the holiday ended because there hasn't been any specific announcement forthcoming as to the size of that fiscal stimulus or what it's going, seen it kind of cool off since the holiday ended because there hasn't been any kind of specific announcement forthcoming as to the size of that fiscal stimulus or what it's going to, what it would entail in terms of allocation of the stimulus. But that's the situation we're in now. I think it's still much better than it was a couple of months ago.

Speaker 2:

Let's talk about cycles and anomalies. I think when we talk about anomalies, some people seem to think that anomalies are exactly where you want to invest in. The bigger they are, the better the alpha, the better the risk gesture returns. But, as you and I both know, anomalies can take time to close. It's going to get charged away. So do you find that, when you look at the data around anomalies where you can generate some outperformance, that there are these rolling extended periods where, even though it looks like the anomaly is an opportunity, it's actually an issue?

Speaker 1:

Yeah. So you definitely see cycles in anomalies. We see it in developed markets, we see it in the US stock market, you see it in emerging markets as well. One of the things that we've noted is that the cycles in emerging markets might have different frequencies. So value in China, for example, it doesn't have these decade-long cycles of underperformance and outperformance that we've seen in the US. It tends to be much shorter, value is going to work most of the time and it might underperform for a few months or a few quarters, but it generally comes back.

Speaker 1:

Now in emerging markets because of the cycles and factors, because of the time it can take for an anomaly to close in an individual stock. Generally, the approach that we favor is multi-factor. So we would suggest, regardless of which product you choose to buy, to get into these markets, that a single-factor strategy is going to be exposed to those cycles and that kind of delay in convergence. Multi-factor is nice because where value might not be working, maybe measures of earnings quality are doing a better job, maybe it's sentiment that's driving the market, and so looking at signals of momentum or signals that retail investors have overbought a particular stock might be more effective. And getting back to the construction of the strategies and thinking about how we go from this universe and filter it down to the portfolio. We're applying signals across a number of different categories. So within the strategy we've got 150 plus trading signals, but ultimately they're trying to capture things like companies' fundamentals. They're trying to capture the behavior of companies' managers and signals that companies' managers are sending about whether they think their own stock is overvalued or undervalued.

Speaker 1:

We're looking at signals that are capturing information that other market participants have. If it's smart money type trading signals, we're looking for an indication that other intelligent, sophisticated investors like a particular stock, and then we might want to copy what they're doing. On the flip side, we might see evidence that individual investors are bidding a stock too high, that they're irrationally exuberant, and then we want to fade that type of trading. So those are the sorts of signals that we're looking at, and when you have dozens, hundreds of trading signals, that's where the data science comes in. That's where, when I'm putting it all together, ultimately I want to have a smart way of combining signals that might be correlated, that they interact in interesting ways. There might be nonlinearities, and so that's where we use the more hardcore quant methodology just to put all that information together and score stocks in the universe, and that's what leads to a final portfolio that we trade.

Speaker 2:

And I assume it's sort of a weight of the evidence type approach. So you've got all these signals. They don't all have to line up.

Speaker 1:

Exactly. Yeah, I mean ultimately the way that we use machine learning. We're not using it to discover new trading signals, all the trading signals. They're based on some kind of fundamental insider intuition. The way that we use machine learning, it's really just trying to automate the process of building confidence in a particular signal. Has it worked historically? Has it worked through different market environments? How does it work relative to other signals that we're using? Is it giving us truly unique information or is it just maybe a less effective duplicate of something that we've already discovered? And so, for us, that's what machine learning AI amounts to within the process just a smarter way of making those empirical judgments as to how to weight signals and how to put it all together.

Speaker 2:

How often is there turnover? I mean, if this is sort of actively looking at all these different signals, presumably the data can change fairly regularly, right? So how does this turnover look?

Speaker 1:

Yeah, so we rebalance the portfolios roughly on a monthly basis, which kind of makes sense when you think about how frequently you want to trade a portfolio. In large part, that's going to have to do with the type of information that underlies the trades. What would lead us to trade a stock? For us, typically it's those medium-term, longer-term movements in price, but it's also lots of fundamental information. Fundamental information tends to be released on a weekly or a monthly or quarterly basis, and so we trade the portfolio roughly monthly.

Speaker 1:

Now in emerging markets retail investors they tend to trade really quickly. So that's one of the biggest behavioral biases that's observed with individuals is that when we're trading our own portfolio for fun, we tend to overtrade, and so the anomalies that we see in emerging markets they tend to play out over shorter periods in terms of the frequency of trading, and so the turnover is going to be higher because you're really responding to what retail investors are doing. So the strategies typically generate turnover of 150% 200% one way per annum. But, importantly, the turnover is actually judged against the alpha opportunity. So we're not going to trade and incur turnover and incur trading costs unless we think the opportunity is big enough to justify it.

Speaker 2:

Let's talk about the developed market fund that you have RAYD for a bit here. I find this to be an interesting portfolio when I look at it in the sense that you do not have the same degree of concentration risk as the S&P 500 does, at least from a US specific perspective. Talk to me about how this is constructed, the anomalies that are trying to be captured here, and then, importantly, how are you managing that top 10 risk?

Speaker 1:

So when we think about developed markets, it probably makes sense to just take a step back and explain how we came as an emerging market specialist to run a developed markets portfolio. Within emerging markets, the biggest distinction is just that a broader class of anomalies still works really well within EM. Of course, to learn what you're going to exploit within emerging markets, it helps to study markets that have a much longer history. In China, I have maybe a decade of really good data. I can go back 30 years in terms of the data in the database, but not all of that's representative because these emerging markets are changing so fast. But the US has been in more of a steady state for a longer period of time, and so I can look at the US and I can learn a lot about quality signals, value, about risk and all of these things that I'm going to want to apply in emerging markets, and so, as a byproduct of doing good emerging markets research, we've studied developed markets over much longer history, and so, whereas I don't think there's as much alpha opportunity in developed markets, I think smart investors make these markets more efficient. It's not that the signals don't work, and I think if you put things together in a smart way and this is where machine learning comes into play you can amplify the alpha that you would get if you were just investing in value or low risk within these markets. Get if you were just investing in value or low risk within these markets.

Speaker 1:

Now, in terms of thinking about concentration risk, I think that this is really one of the key distinctions between active and passive.

Speaker 1:

Passive strategies you are at the mercy of the market in terms of how have they valued these really big tech companies like NVIDIA, alphabet, amazon and so forth.

Speaker 1:

We don't have to follow market cap weights. We're active investors. We can look at a company like NVIDIA and we can make a determination that it's expensive 50 times next year's earnings is not cheap, but they have a lot of fundamental strength going for them that might justify that price tag, whereas I can look at Tesla it's also a big weight in the S&P 500. And I might decide that there's growth opportunity there, but maybe it's not as compelling, and so that helps with the concentration risk. And then the second piece is when you look at a broader set of companies, because as a systematic investor, I can apply my methodology to every stock traded on the US exchanges. It means that I'm going to find opportunities in names that are smaller, and, generally, if I'm looking for inefficiency in developed markets, you're more likely to find it in undercover stocks, stocks that a lot of hedge funds and big institutional traders are going to overlook, and so that's another way of controlling concentration risk.

Speaker 2:

What's been some of the pushback that you've heard from allocators, financial advisors, around the methodology, the approach. I mean, let's face it, it's been a remarkable cycle in the sense that it's been very hard to just beat in quotes, passive market cap weighing S&P. I see that as somebody who is a big fan of taxable and active right, knows what other issues are doing, know what I myself have observed. What do you say to those people that say you know, why should I consider something like what you're doing when the S&P is working?

Speaker 1:

Yeah, well, it's a smart question for investors to ask. Investors should always be asking if I'm going to invest in something active and I'm going to pay more for access to those active methodologies, is it really doing anything for me? In developed markets, I think the bar is higher because we know these markets are more efficient, so there's just that much greater argument to go passive in these markets. I think it comes down to, like I said, looking at passive and the type of portfolio that you get when you invest in the S&P 500, what's driving your portfolio's performance? It's really, these days, a small subset of companies, and some investors are taking a look at that and thinking to themselves well, that's great, and maybe I should have some allocation to that passive core, but at the same time, there are probably lots of opportunities that you're missing when the index gets that top heavy, and so the biggest pushback, honestly, is just that emerging markets. So, when we think about where we started, emerging markets can be a scary place, and so investors have to develop comfort with that.

Speaker 1:

I think an active approach naturally helps to manage the risk and it turns some of those risks that we see in emerging markets accounting risk, geopolitical risk, political instability. It can turn those into opportunities, because whenever there's that kind of disruptive change, they're going to be winners and losers Within developed markets. I think a systematic methodology it's really a rigorous way of doing active investing. So I think more and more investors are going to start to trust that quantitative, systematic strategies. It can just be a really disciplined way of getting active exposure within markets, even efficient markets like the US the Japan fund as well earlier this year.

Speaker 2:

Interesting on that. First of all, I guess what was the impetus to launch the Japan fund and how does Japan, from an anomaly perspective, look? I mean, it's one of the more interesting markets. A lot of big structural changes in terms of corporate governance we can get into. But let's talk about RAYJ.

Speaker 1:

Yeah. So the Japan fund I wish we'd launched it a year earlier. We've been talking about it for a really long time With the Japan strategy. This gets back to something I mentioned earlier on about looking at local nuance in emerging markets. Now, japan is not an emerging market, it's a developed market. But in many ways it resembles some of those highly developed East Asian emerging markets. So when you look at Japan, you find that retail trading, while it's not 60% of volume, it's still significant. It's 20, 30% of trading volume. So there are a lot of retail investors. It's a market that is really broad, thousands of stocks. But when you go outside the Nikkei, when you start looking at the broader topics market, what you find is that there's not much analyst coverage and so for foreign investors. Looking at Japan, it's a market that has a lot of idiosyncrasy and it can be confusing.

Speaker 1:

We wanted a partner in Japan. So, in the same way that we think we're really good at East Asian merchant markets, we recognize we really want someone local to help us build a good strategy for Japan. We found that in Sumitomo Mitsui DS Asset Management. So this is one of the biggest banks in Japan. It is the biggest active, the biggest banks in Japan. It is the biggest active fund management company in Japan and so when they wanted to launch a US-Japan ETF, they found us and we started working together and developed a strategy that uses our systematic quantum mental methodology as an input to the process of a local fundamental research team.

Speaker 1:

So it's a bit different than the other three railing DTFs in the sense that I said Ray C, ray E, ray D are much further on the quant end of the spectrum. Ray J is on the fundamental end of the spectrum where quant is kind of an input to the process and we just think there's a lot of opportunity there. You mentioned structural change. There's corporate reform, we're seeing Japanese consumers start to throw off the sentiment of deflation and stagnation and, as I said, at those inflection points there's really big opportunity.

Speaker 2:

I mean I like that. It looks fairly concentrated right. You got 32 holdings as opposed to 2,127. So it's very filtered from that standpoint.

Speaker 1:

Very different With the other ETFs. The goal is to give clients broad exposure to EM, or to China. In this case, it's much more like a best ideas portfolio and in fact it is really targeted at growth within Japan's market and identifying, you know, 30 or so companies that our team thinks are best poised to exploit that growth.

Speaker 2:

It's an interesting sector mix to see discretionary be the largest. I know that's more on the automobile side. Is that typical when you look at Japan market averages? I mean, how does this sector mix if we're compared to just look at the Nikkei itself.

Speaker 1:

No, it's not, and I think that really reflects that sort of high conviction. Go anywhere. Nature of the portfolio the portfolio is driven by themes, so top down there's sort of an identification of growth themes. So you know, japanese consumption resurgence, looking at AI and how Japan fits into that supply chain, those would be sort of themes that you might imagine the team, using input from Reliance Quantum Mental Models, is going to go in and pick individual stocks within each of those themes and so you can end up with a fairly skewed sector exposure, but again just looking for undervalued growth at a reasonable price within Japan.

Speaker 2:

I know it's hard to choose among four children, obviously, but of the four different funds, we'll talk about the Ex-China one shortly. I mean, which one do you think is the most intriguing, the most sort of undervalued or under the radar, that really you think it's going to be the next big winner.

Speaker 1:

Yeah. So what I can tell you is where we're seeing a lot of interest right now, and I think that is clearly emerging markets, ex-china, china. We may see things shift a bit if stimulus comes through and sentiment toward China improves, but I think a lot of investors recognize that there are big changes happening now that there is geopolitical tension between the US and China. Countries are reorganizing supply chains. There's tons of growth happening within each of these markets, so people in India, taiwan, getting wealthier over time and that's driving a transformation of these economies and there's a lot of interest in trying to find the winners and losers as those changes happen.

Speaker 1:

I think the other thing with EMX China, we're seeing the Fed's pivot and we could have another hour-long conversation about what's going to happen with the US dollar, but I think most would agree that in the long run we're going to see a cycle of dollar weakening, which tends to be good for emerging markets, and I think there are just a lot of tailwinds. And then, when you look at valuation, as I said, you've got markets like Korea trading at 10 times forward earnings. India, which is one of the most richly valued economies within EM, trades at 25 times earnings, which is like the S&P 500. You know it's just growing a lot faster. So I think that's, for my money, probably the most interesting of the four.

Speaker 2:

Yeah, it's interesting. It's like there's a steepened risk aspect to China china in some, you know, uh, some advisors minds, right. It's like if they have a mom and pop investor and they're looking, their statement and the statement has the fund names and it has china in the name. There's an immediate allergy to that right. So it makes sense to have a product that explicitly removes china at the same time. That makes me think that china is probably one of those underinvested parts of the public marketplace and whenever China does move, it's going to move very hard because there aren't that many big players that are in there Right Lots of money on the sidelines.

Speaker 1:

I mean, when you hear a market being referred to as uninvestable, that's a pretty good.

Speaker 2:

A totally momentum, and then it's investable right. That's always how it works Exactly.

Speaker 1:

Yeah, and having a China fund and an ex-China fund. Ultimately it's giving investors building blocks so that they can create whatever exposure they'd like. Maybe you don't want that headline risk in China, so you'd go 100% EMX China. I've talked with plenty of investors who wanted to be early on China and they're tactically overweight. So that's the cool thing about ETFs you can mix and match and kind of create what suits you.

Speaker 2:

For those who want to learn more about Rayleigh and the funds and just in general engage more with you. How would you recommend they do so? Engage more with you. How would you?

Speaker 1:

recommend they do so. Yeah, I mean definitely look at our funds website and you've already shared some of the resources that you can get on the fund site. On the fund site there's contact information you can reach out if you're looking for more information, if you've got other questions. Our team is really research focused and we love to talk about EM and equity markets in general, so definitely take a look and reach out if you've got questions or interest.

Speaker 2:

Again. Folks, this is a sponsored conversation by Aurelien. It's a lot of interesting things we talk about here. I do have to agree that I think yes, when it comes to emerging markets, you need to have that more fundamental quantitative overlay. For a lot of reasons it's a tough place to invest in until it's not, and when it's not a tough place to invest in, I think products like these have a real shot at standing out in a big way. I appreciate those that watch. Please share, like, repost all that good stuff. This video it will be edited soon enough and special thanks to Phil Wool of Reelings for the conversation. Thank you, phil, appreciate it. Thanks, michael.

Speaker 1:

Thanks everybody Take care Cheers everybody.

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Michael A. Gayed, CFA

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