Passive allocations, through index funds or ETFs, can provide breadth and affordability, but they may also bring baggage: often concentrated exposures to state-owned enterprises, governance risks, and companies with questionable balance sheets. On the other end of the spectrum, discretionary active managers may offer selectivity but sometimes at the cost of higher fees.

For allocators seeking to capture EM opportunity with efficiency and control, a third path is possible: quant strategies focusing on larger and more liquid EM names.

When Robeco first applied quantitative models to emerging markets in the late 1990s, the consensus view was that systematic investing could not succeed in such an environment. Data quality was patchy, corporate disclosures were inconsistent, and markets were prone to political shocks. Moreover, many believed that only boots-on-the-ground discretionary analysis could cope with these uncertainties.

But inefficiency has always been fertile ground for systematic investors. Our conviction was that, if anything, EM complexity made a disciplined, rules-based approach more instead of less valuable. By focusing on observable, repeatable drivers of returns and managing risk systematically, quant investing could provide a consistent approach to targeting alpha.

In 2000, we launched our proprietary stock selection model, which became an integral part of our Fundamental EM team’s investment process. Over time, our research¹ confirming that factors such as value and momentum were just as effective in EM as in DM was validated by academic recognition in journal publications between 2003 and 2005. These developments collectively led to the launch of our first pure EM quant portfolios in 2007, leveraging insights from our extensive experience in DM.

Built on five complementary factors (value, quality, momentum, analyst revisions, and short-term signals), the EM quant model was designed to be robust, aiming to deliver long-term alpha. Factor definitions have been refined and enhanced over time, with the growth of alternative data and AI techniques. Innovations such as China-specific data signals to capture local nuances have been adopted, making the model more adaptable in the short-term. Additionally, advances in portfolio optimization that reduce trading frictions while maintaining diversification have been implemented.

Two decades later, EM quant is no longer an experiment but an established discipline at Robeco. Our experience across multiple EM quant strategies has shown us that systematic factor investing can succeed in markets once considered too opaque. This evolution has been accompanied by growing recognition from institutions worldwide: quant is no longer seen as a ‘black box’, but as an explainable, evidence-based framework for navigating EM complexity.

Over time, our factor definitions have been enhanced to make them more robust, risk-aware, and adaptive to changing markets. Each factor — from value and quality to momentum and analyst revisions — is refined using advanced techniques that help avoid unrewarded risks and reduce bias. For example, our momentum signal corrects for exposure to broader market movements, focusing instead on genuine stock-specific trends. Similarly, other elements such as alternative data have been selectively incorporated where they strengthen predictive power, ensuring the model remains both economically grounded and forward-looking.

The debate over where factor premiums are strongest in EM is well rehearsed. Smaller-cap stocks may show higher theoretical premiums, but those advantages may not survive the realities of implementation. For institutional allocators deploying billions, the question is not just where premiums look largest in theory, but where they can be harvested most effectively after costs and with meaningful scale.

The more liquid EM stocks – which we define as approximately 700 large- and mid-cap stocks representing 95% of the market cap of the MSCI Emerging Markets Index – present a pragmatic solution. Their greater liquidity profile means that their factor premiums are far more ‘harvestable’. Higher daily turnover, tighter spreads, and more efficient execution all contribute to translating signals into real-world results.

Nor does a focus on larger and more liquid stocks imply compromised diversification. Sectoral and geographic profiles remain broad, ensuring that allocators are not trading off efficiency for concentration. Instead, they are accessing EM exposure and targeting alpha in a way that aims to be efficient, scalable and repeatable, aligning with the needs of long-horizon institutional investors.

Robeco’s EM ‘Plus’ range complements our EM Enhanced Indexing and Active Equities strategies, applying the same stock selection model, managed by the same team, benchmarked against the same MSCI EM Index – however, with a focus on the larger and more liquid portion of the EM universe.

This focus has several powerful effects. First, it reduces transaction costs, which in EM can meaningfully erode returns if left unmanaged. Second, it supports fee structures that are highly competitive, making the strategies attractive alternatives to passive allocations. And third, it increases scalability and liquidity.

The ‘Enhanced Indexing’ variant of the EM Plus strategy offers factor tilts at index-like costs. The ‘Active Equities’ variant targets additional alpha while maintaining robust risk management. Together, they offer institutions a choice: efficient EM exposure that improves on passive approaches, or a more active approach with greater tracking error flexibility.

Because the same research engine powers each strategy, they can be customized to client-specific objectives for risk, return, and sustainability — making our Plus range a versatile building block for many different mandates.

Moreover, quant strategies are particularly attractive for clients seeking consistency. Because the investment process is systematic, it avoids style drift or emotional decision-making. This makes quant a strong fit for mandates where transparency, replicability, and cost-efficiency are priorities.

For allocators, EM exposure has often been framed as a binary choice: passive for efficiency, active for potential alpha. The Plus range demonstrates that this need not be the case. It offers a middle ground –systematic, transparent, and cost-efficient, yet still designed to add value beyond the benchmark.

Today’s environment sharpens the need for such solutions. The dominance of a few mega-cap US names has left portfolios more concentrated than many realize. Adding EM exposure can be an effective way to increase diversification. Yet, with fee pressure intensifying and scrutiny on manager value-add increasing, the form of that exposure can matter as much as the allocation itself.

Robeco’s EM Plus quant strategies are tailored for this moment. They reflect nearly two decades of systematic investing in emerging markets, a willingness to innovate within a disciplined framework, and an understanding of institutional imperatives for cost, scale, and risk management.

In many ways, this is the natural evolution of EM allocation. Where once institutions had to choose between efficiency and alpha, they now have access to strategies that combine both. That synthesis, grounded in research and refined through experience, is what Robeco’s EM Plus range brings to the table.

Footnotes

¹Van der Hart, J., Slagter, E., and Van Dijk, D., 2003, “Stock selection strategies in emerging markets”, Journal of Empirical Finance; Van der Hart, J., De Zwart, G., and Van Dijk, D., 2005, “The success of stock selection strategies in emerging markets: is it risk or behavioral bias?”, Emerging Markets Review.