An ETF Story: The Ever-Evolving Emerging Market ETF Landscape

Beyond the Monolith: Unpacking the Diverse Universe of Emerging Market ETFs

To many, “Emerging Markets” is a single line item in a portfolio, a monolithic block of high-growth, high-risk potential. This simplification, however, is a dangerous one. Lurking beneath this single label is a universe of immense diversity, where the choice of one ETF over another is not a minor tweak but a profound strategic decision. Two funds, both tracking “Emerging Markets,” can represent vastly different bets on geopolitics, economic sectors, and investment styles. Using comprehensive datasets, this report will peel back the layers of the EM ETF landscape. We will dissect the architectural differences in strategy, geography, and fundamental characteristics to reveal how these choices culminate in a surprisingly wide spectrum of risk and return, empowering investors to move beyond broad assumptions and select the precise tool for their investment thesis.

The EM ETF Landscape: A High-Level Overview

The Emerging Markets ETF space is a multi-hundred-billion-dollar arena where a handful of titans have come to define the asset class for a generation of investors. An initial survey of the landscape reveals a market heavily concentrated in a few dominant products, a clear evolutionary path from expensive first-movers to low-cost core holdings, and a wide chasm in the costs of ownership.

The sheer scale of the market is immediately apparent, with the top two funds alone, the iShares Core MSCI Emerging Markets ETF (IEMG) and the Vanguard FTSE Emerging Markets ETF (VWO), commanding over $211 billion in assets under management (AUM). This concentration underscores a powerful market trend: the gravitation towards passive, low-cost, market-capitalization-weighted solutions as the default entry point for EM exposure. The history of these products tells a story of market evolution. The iShares MSCI Emerging Markets ETF (EEM), launched in 2003, and VWO, launched in 2005, are the category’s elder statesmen. However, the current AUM leader, IEMG, launched in 2012, represents a newer generation of “core” products engineered specifically for cost-efficiency. The more recent success and significant asset gathering of funds like the Avantis Emerging Markets Equity ETF (AVEM) signal a maturing market where investors are increasingly seeking more sophisticated, actively managed, or factor-based strategies.

This evolution is most evident in the cost structure. Expense ratios across the category span a dramatic range, from a rock-bottom 0.07% for behemoths like VWO and the SPDR Portfolio Emerging Markets ETF (SPEM) to a comparatively steep 0.72% for the older, yet still highly liquid, EEM. This tenfold difference in management fees for funds offering superficially similar exposure is a crucial first-level filter for any investor. This “beta-is-a-commodity” environment at the top of the category, a result of fierce fee wars, has created a crowded trade not in a single stock, but in a single strategy. Because so much capital is concentrated in a few market-cap-weighted funds, any ETF that deviates from this norm—whether by excluding a major country, focusing on a specific factor, or employing active management—offers a powerful source of potential diversification.

Data as of 9/24/2025. Source: ETF Action, FactSet

Decoding the Blueprints: From Plain Vanilla to Active and Factor-Tilts

Beyond the headline numbers of size and cost, the true diversity of EM ETFs lies in their construction methodology—their strategic blueprint. This architecture dictates which stocks are included and how they are weighted, leading to fundamentally different portfolios. The approaches range from simple market replication to complex, rules-based factor tilts and fully discretionary active management.

The most common approach is passive beta replication. The largest ETFs, including IEMG, VWO, and SPEM, are prime examples. Their stated strategy is “Factor: Beta” with a “Market Cap” implementation. They do not make active bets; their sole goal is to deliver the return of their underlying benchmark index at the lowest possible cost, reflecting a belief in broad market efficiency.

A growing segment of the market, however, is built on the premise that certain systematic tilts can generate superior risk-adjusted returns over time. These factor-based ETFs are not passive in the traditional sense; they follow a rules-based process to select and weight securities based on specific characteristics. The provided data reveals a rich variety of these strategies:

Dividend: The WisdomTree Emerging Markets High Dividend Fund (DEM) and its small-cap counterpart (DGS) explicitly target companies that pay high dividends.
Low Volatility: The iShares MSCI Emerging Markets Min Vol Factor ETF (EEMV) is designed to provide a less turbulent investment experience by holding a portfolio of stocks that have historically exhibited lower price volatility.
Multi-Factor: A more sophisticated approach combines several factors into a single strategy. Funds like the Schwab Fundamental Emerging Markets Equity ETF (FNDE), the Invesco RAFI Emerging Markets ETF (PXH), and the John Hancock Multifactor Emerging Markets ETF (JHEM) use fundamental measures like sales, cash flow, and dividends to weight stocks, rather than market capitalization. Others, like the Avantis Emerging Markets Equity ETF (AVEM), systematically screen for multiple factors such as value, profitability, and momentum.

This strategic divergence is mirrored in the management discipline, which exists on a spectrum from purely passive to fully active. While most of the largest funds are designated as “Passive,” a significant and growing cohort occupies a middle ground. “Systematic active” funds, such as the Avantis Emerging Markets Equity ETF (AVEM) and the Dimensional Emerging Core Equity Market ETF (DFAE), combine a rules-based, factor-driven approach with the flexibility of active management, allowing managers discretion to deviate from a benchmark. Further along the spectrum are “traditional active” funds, such as the Capital Group New Geography Equity ETF (CGNG), which rely more heavily on the fundamental, bottom-up security selection of their portfolio managers to navigate opportunities.

The choice between these strategies is an implicit statement on market efficiency. The clear hierarchy in expense ratios—with passive beta funds being the cheapest, followed by factor funds, and then the various forms of active funds—reflects this philosophical divide. An investor selecting VWO is voting for market efficiency and cost minimization. An investor choosing FNDE is betting that fundamental factors can outperform market-cap weighting. And an investor selecting AVEM or CGNG is expressing confidence that active management, whether systematic or traditional, can exploit the well-documented inefficiencies within emerging markets to generate alpha, justifying a higher fee.

Data as of 9/24/2025. Source: ETF Action, FactSet

Where in the World? The Critical Impact of Geography

Perhaps the most significant, and often least appreciated, driver of divergence in EM ETFs is their geographic composition. An investor’s choice of fund can result in wildly different exposures to key countries like China, India, Taiwan, and South Korea. These differences are not random; they are the direct result of two major fault lines in the world of index construction: the strategic “China question” and the methodological split between index providers MSCI and FTSE regarding the classification of South Korea.

The “China conundrum” is a defining feature of modern EM investing. Due to the immense size of its equity market, standard market-cap-weighted funds have a heavy allocation to Chinese companies. IEMG, for instance, allocates approximately 24.9% of its portfolio to China, while VWO’s allocation is even higher at 30.8%. In response to rising geopolitical risks, regulatory uncertainty, and periods of economic underperformance, a distinct category of “ex-China” ETFs has gained prominence. Funds like the iShares MSCI Emerging Markets ex China ETF (EMXC) and the Columbia EM Core ex-China ETF (XCEM) explicitly exclude China, resulting in a 0% allocation. This single decision fundamentally reshapes the portfolio, dramatically increasing the weight of other key markets. In EMXC, for example, the weights of India (22.3%), Taiwan (28.6%), and Brazil (5.3%) are significantly elevated compared to their weights in IEMG.

A second, more technical distinction with massive real-world consequences is the “MSCI vs. FTSE divide,” which centers on the classification of South Korea. MSCI, the index provider for funds like IEMG and EEM, classifies South Korea as an emerging market. Consequently, IEMG has a substantial 11.4% allocation to the country. Conversely, FTSE, the provider for VWO and SCHE, classifies South Korea as a developed market. As a result, VWO has a 0% allocation to South Korea. This seemingly arcane methodological difference means that an investor choosing between the two largest ETFs in the category is making a major, implicit strategic bet on the role of South Korea. A holder of IEMG has significant exposure to global technology giants like Samsung and SK Hynix, giving the portfolio a more developed, tech-heavy flavor. A holder of VWO explicitly avoids this, resulting in a portfolio more concentrated in what might be considered more traditional emerging economies.

Data as of 9/24/2025. Source: ETF Action, FactSet

Beneath the Surface: A Fundamental Dissection of Style and Size

Having established the strategic and geographic differences, the analysis now turns to the financial DNA of the companies within these ETFs. An examination of aggregate fundamental metrics reveals the distinct investment styles—Value versus Growth—that these portfolios represent. The choice of ETF is not just about which countries to own, but what kind of companies.

Valuation metrics, such as the Price-to-Earnings (P/E) and Price-to-Sales (P/S) ratios for the next twelve months (NTM), provide a clear picture of an ETF’s style tilt. Value-oriented funds, which screen for metrics like dividends or fundamental strength, exhibit predictably lower valuation multiples. The WisdomTree Emerging Markets High Dividend Fund (DEM) trades at a P/E NTM of just 8.66, while the Schwab Fundamental Emerging Markets Equity ETF (FNDE) has a P/E NTM of 9.91. In stark contrast, broad market funds like IEMG sit in the middle with a P/E NTM of 14.27. Funds with a growth tilt, such as the WisdomTree Emerging Markets ex-State-Owned Enterprises Fund (XSOE), which often has a higher concentration in consumer and technology sectors, trade at a premium valuation with a P/E NTM of 17.01.

These valuation differences are directly linked to underlying growth expectations. Using NTM earnings and sales growth estimates, the same pattern emerges. The value- and dividend-focused funds show muted growth prospects; DEM has a forecasted NTM earnings growth of a mere 0.36%. The broad market, represented by IEMG, has a much healthier estimated earnings growth of 14.05%. Confirming its growth orientation, XSOE boasts a robust estimated NTM earnings growth of 15.61%.

This shows that an ETF’s stated strategy is a powerful filter that creates a quantifiable fundamental profile. An investor buying DEM is not just buying “dividend stocks”; they are acquiring a portfolio with a deep value bias, low growth expectations, and heavy exposure to cyclical sectors. This portfolio will behave very differently from a broad market fund. This allows investors to use factor ETFs as precise tools to express a macroeconomic view. For instance, a belief that EM valuations are overly compressed and poised for a rebound might lead to selecting a deep value fund, whereas a belief in the continued dominance of the EM consumer and technology sectors would favor a growth-oriented fund.

Data as of 9/24/2025. Source: ETF Action, FactSet

The Final Verdict: How Strategy Dictates Risk and Return

The architectural differences in strategy, geography, and fundamentals are not merely academic; they have a direct and profound impact on the metrics that matter most to investors: performance and risk. The data clearly demonstrates that the wide dispersion in how these ETFs are built leads to an equally wide dispersion in their outcomes. This proves that the choice of an EM ETF is a truly active decision, even when selecting a so-called passive fund.

An analysis of total returns over the past year highlights this divergence vividly. The Freedom 100 Emerging Markets ETF (FRDM), which excludes countries with low “freedom scores” like China, delivered a stellar 1-year total return of 25.62%. This significantly outpaced the broad-market IEMG, which returned 19.00%. At the other end of the spectrum, the dividend-focused DEM returned just 8.53% over the same period. This 17-percentage-point performance gap in a single year within the same asset class is not random; it is the direct result of FRDM’s exclusion of an underperforming China and DEM’s value tilt being out of favor relative to the growth and technology themes that have driven the broader benchmarks.

Risk profiles also vary dramatically. The standard deviation of returns, a key measure of volatility, shows that strategies designed to mitigate risk are working as intended. The iShares MSCI Emerging Markets Min Vol Factor ETF (EEMV) has a 3-year annualized standard deviation of 11.43%, substantially lower than the 16.91% for the broad-market IEMG and the 17.32% for the active AVEM. Investors in EEMV have indeed experienced a much smoother ride, though this has come with a trade-off in absolute returns.

Ultimately, risk-adjusted returns, as measured by Sharpe Ratio in the below table, provide a more holistic view of performance. Here, the data suggests that more sophisticated strategies have been rewarded. The active, multi-factor AVEM has a 3-year Sharpe Ratio of 0.79, superior to IEMG’s 0.66. Meanwhile, the original, high-cost EEM has a Sharpe Ratio of just 0.59, lagging its cheaper and more comprehensive passive competitors. This indicates that simply buying the oldest or most liquid product is not a guarantee of superior risk-adjusted performance. The evidence is clear: the seemingly passive choice of an EM index or factor tilt can be a more significant driver of returns than the overall performance of the asset class itself.

Data as of 9/24/2025. Source: ETF Action, FactSet

Conclusion: From Broad Assumptions to Precise Solutions

The journey through the emerging markets ETF landscape reveals a clear truth: “emerging markets” is not a destination, but a vast and varied territory with many paths an investor can take. The idea of a single, monolithic EM exposure is a relic. As demonstrated, the choice of ETF—driven by index methodology, strategic tilts, and geographic focus—is a powerful decision that profoundly shapes portfolio outcomes. A simple market-cap weighted fund makes an implicit bet on Chinese technology, while a dividend-focused fund bets on mature, value-oriented industries, and an ex-China fund takes a deliberate stance on geopolitical risk.

Navigating this complex terrain requires more than just a ticker and an expense ratio. It demands a granular understanding of what lies beneath the surface. This is where the power of comprehensive, institutional-grade data becomes indispensable. With a user-friendly platform like ETF Action, advisors and investors can move beyond the monolith, dissecting funds by their true exposures, comparing their fundamental DNA, and stress-testing their performance profiles. The ability to screen, analyze, and compare across hundreds of data points transforms the challenge of ETF selection into an opportunity—the opportunity to find the exact product that aligns perfectly with a specific market view, risk tolerance, and investment thesis.