Emerging markets (EM) are an intriguing segment of the global equity markets. While access to EM has improved, market inefficiencies persist, and the availability of reliable company information and data still trails that of the developed world. For information that is accessible, liquidity and trading limitations can introduce challenges for its exploitation, offering ongoing investment opportunities for skilled active investors. Emerging markets also provide opportunities across different countries and industries, which can vary significantly.

But the capture of this alpha isn't guaranteed; multiple sources of risk exist which can degrade return potential. For individual companies, bankruptcy, fraud, and significant financial loss come with higher likelihoods in emerging markets, while trading halts and bad data also prove headaches for quantitative-oriented investors. Compounding these stock-level risks are various macro-level issues — currency crises, geopolitics, trade disputes, elections, oil shocks — all of which can yield dramatic market outcomes.

For these reasons we've designed a framework that allows us to capitalize on alpha opportunities across securities, industries, and countries while balancing against adverse risk outcomes.
 

The lead role: Company fundamentals

The starting point for our framework is to recognize that fundamentals matter. Prices don't always reflect those fundamentals throughout time, however, which is where the investment opportunities arise. As markets move, different fundamentals become more significant measures for different types of companies. Consequently, we have found that different types of signals will be more effective at detecting those mispricings. The challenge is to determine which fundamentals are the most important for which types of companies.

The value of a company is made up of two parts: the value of its existing operations and expectations about its future growth prospects. To demonstrate how this helps us select the most important information for specific company types, consider two companies: one slow growth and one fast growth.

For a slow-growth company, expectations about future growth prospects play a minor role in valuing the firm, as slower-growth companies have limited growth prospects. The value of the firm is driven by earnings generated from existing operations. Investors are sensitive to the price they pay for an earnings stream. Consequently, valuation-oriented signals are more effective at evaluating the future performance prospects of slower-growth companies.

For a faster-growth company, expectations about future growth prospects are the main driver of valuation, so we focus on information that gives us insights into those prospects. As a result, we find that growth signals are more effective at evaluating the future performance prospects of fast-growth companies. This framework allows for a more refined evaluation of each stock. It also helps increase the likelihood that we are evaluating a stock's performance potential through the correct lens. It allows us to unify both value and growth stock selection approaches within a single stock selection model, which produces a balanced core portfolio.

Adaptive stock selection models are especially important for investing in EM, where growth rates by country, sector, and security have changed dramatically over the last decade. Our research and investment experience have shown that this adaptive bottom-up stock selection framework is essential in capturing inefficiencies within equities, and to driving consistent performance over the long term.

Top-down dynamics

Within emerging markets, a top-down investment approach can complement bottom-up stock selection. In fact, a major allure of EM has long been the return opportunities arising between countries and industries. The opportunities created by this dispersion can be significant. In recent years, top-down effects have had more pronounced influences on market behavior. Recent examples are being seen in the impact of the 2019 China/US trade war and the COVID-19 crisis, which brought about cascading consequences on countries and industries.

To reflect this changing dynamic, we recently introduced a top-down element to our investing framework. Advances in modeling techniques have also increased our confidence that top-down opportunities can be a source of added return rather than risk. In the past, we have been skeptical about the effectiveness of top-down investment approaches, but to counter these challenges, we leveraged a more refined, direct approach.

We model top-down insights at the combined country-industry group level. By taking this approach, we generate a much broader set of top-down insights, affording us diversification across our investment bets. This approach further allows us to more efficiently target attractive opportunities.

Modeling at the country-industry group level also helps us avoid having to combine separate country and industry group models. Our approach unifies country and industry top-down approaches, while increasing the viability of exploiting return dispersion between countries and industries. We then evaluate the attractiveness of each country-industry group, staying true to our philosophy and focusing on fundamentals, utilizing valuation and growth-related insights.

Through the introduction of explicit top-down factors, our unified framework provides consistent insights across all country-industry dimensions. This adds to our confidence that top-down insights will translate into viable sources of return.