Investing in emerging markets equity

Core, style, and regional EM access

Traditionally, there have been a number of ways for international investors to access the opportunities offered by the EM equities, such as via a core, style, or regional building block approach. A straightforward way is to invest via EM core managers. In this case, the regional and sector calls are left in the hands of external EM managers.

Another popular approach is to invest in EM equities through a style lens. By tilting between growth and value stocks within the portfolio, investors can seek opportunities to add alpha versus a broad EM equities benchmark. This can be a sound approach for experienced investors with a strong conviction over style factors.

A third common approach is to invest by EM subregions: Asia, Europe, the Middle East and Africa (EMEA), and Latin America (LatAm). Given the different return and risk drivers operating in different regions, tilting the EM portfolio among the regions on a tactical basis may generate excess returns.

The purpose of this study is to examine the empirical evidence regarding the effectiveness of the above three approaches. Our universe consists of all EM equities managers in the eVestment database over an 18‑year period from January 2007 through December 2024.1 The study includes 216 core managers, 70 growth managers, and 58 value managers. When filtered by EM subregion, there are 13 Asia managers, 32 EMEA managers, and 26 LatAm managers.

Historical emerging markets returns dataset

The historical return series of a median EM equity manager was constructed by calculating the median monthly returns of all managers in the relevant eVestment universe, starting from January 2007. For the style portfolio, we constructed a 50/50 portfolio consisting of a median growth manager and a median value manager. In constructing the regional portfolio, we allocated weights to a median EM Asia manager, a median EM EMEA manager, and a median EM LatAm manager based on their respective regional weights in the MSCI EM Index over time. One limitation of this approach is that, in reality, no single manager would be ranked at the median consistently every month. Thus, an investor’s actual return experience would have differed significantly from the median return.

Based on the median EM managers’ track record, compared with the core portfolio, the style and regional portfolios generated higher excess returns at the cost of higher tracking errors (see Figure 1). To reduce the potential impact from the selection of the sample end points, we looked at the rolling three‑year information ratio (IR) of the median portfolios over the same back‑testing period. Figure 2 shows that the EM core strategy had a more stable three‑year rolling IR than either the EM style or EM regional portfolio over the sample period. The style and regional EM equities portfolios had higher information ratios than the core EM portfolio during 55.8% and 71.8% of the time, respectively. Thus, on a risk‑adjusted basis, the style and regional portfolios looked more attractive as measured by the information ratio, with an average rolling three‑year IR of 0.90 and 1.05 compared with 0.81 for the core.

To validate the conclusion above, we analyzed the factor sensitivities of the three median EM equity portfolios over the sample period to see if the differences in performance could be attributed to the three portfolios’ distinct factor profiles (Figure 3). All three median portfolios showed balanced factor profiles. The style portfolio showed a modest bias toward small‑cap stocks, while the regional portfolio was slightly biased toward names with higher valuation and lower beta. None of these biases were regarded as being large enough to have a significant bearing on performance.

EM equity performance with TAA country shifts

In addition to returns generated by underlying EM equity managers, seasoned investors with strong conviction could earn extra alpha by dynamically tilting their allocations between styles, subregions, and single countries. Among the different levers of tactical asset allocation (TAA) calls, historical data point to country rotation within EM as having the highest potential for delivering alpha. To gauge the potential for significant country selection alpha, Figure 4 shows the annual return differences between the best‑ and the worst‑performing EM countries over time. Return divergences between EM regions and styles are also given in Figure 4, and these were much less prominent than the return spreads for countries.

However, tactically adjusting allocations to individual markets within an EM equities portfolio presents a challenging task. The three top‑ and bottom‑performing EM countries from 2007 to 2024 are shown in Figure 5. EM country returns have varied notably from year to year (low autocorrelation), with countries often switching from top three in one year to bottom three in the subsequent year.

As an example, T. Rowe Price’s quantitative EM Country Rotation Model seeks to identify the most and least attractive EM equity markets using four broad categories of metrics: macro, macro financial, fundamental, and sentiment. Each month, the model “longs” the five most attractive EM equity markets and “shorts” the five least attractive markets. An illustrative model ranking for December 31, 2024 is shown in Figure 6. The long and short country positions were scaled to target 15% annualized portfolio volatility. Since the start of the back‑test in February 1999, the model delivered a Sharpe ratio of 1.1 and an attractive annualized return of 20.4% (Figure 7).

Compelling as the back‑test result appears, the actual implementation of dynamic country rotation introduces new challenges:

• Liquid country index exchange‑traded funds (ETFs) are not always available. They are missing in the case of Czech Republic, Egypt, Greece, Hungary, Kuwait, Peru, Qatar, and the United Arab Emirates.
• The expense ratios of EM single‑country ETFs are high: On average, we estimate that EM single‑country ETFs charge an expense ratio of 67 basis points. This is only a touch lower than that of an actively managed EM equity fund.
• Liquid country index futures are not always available, as in the case of Colombia, Czech Republic, Hungary, Egypt, Turkey, Greece, Peru, and the Philippines.
• At times, it could be hard to find reliable broker counterparties for EM country index total return swaps.
• Moreover, TAA investors would often need to allocate to countries with small index weights, increasing the practical implementation difficulties.
• Managing direct security EM country portfolios can also be operationally difficult.
• To illustrate the impact of these constraints, if we were to implement the EM Country Rotation Model by employing liquid country index ETFs only, the Sharpe ratio would have dropped to 0.6 and the annualized return would have fallen to 11.8% (Figure 8).

Conclusion

There are many different approaches to investing in EM equities. As such, it is not possible to say one approach is consistently superior to another. Investors should make informed decisions based upon their alpha generation capabilities, tracking error budget, and implementation constraints. It is also important to understand and leverage a third‑party EM manager’s active management skills as expressed through stock selection, country selection, or style and factor allocation.