The Emerging Markets Revival and the Case for Systematic, Diversified Exposure

Key Takeaways

• EM equities outperformed developed markets by >10% in 2025
• RAM AI’s systematic strategy manages €1bn, 500‑600 stocks
• Strategy blends quality, value, low‑risk factors via deep‑learning
• Index concentration rose to 25% in top five EM stocks
• Systematic approach reduces drawdowns, lowers volatility versus benchmark

Summary

Emerging‑market equities delivered more than a 10% outperformance versus developed markets in 2025, sparking renewed investor interest. Swiss‑based RAM Active Investments has built a €1 billion systematic strategy that targets broad factor exposure while managing liquidity, governance and concentration risks. The fund, launched in 2009, now holds 500‑600 stocks across Asia, Latin America, Eastern Europe and the Middle East, delivering an 8% yield—roughly three times the U.S. level. Its deep‑learning infrastructure processes 500 alpha inputs per stock, integrating fundamentals, sentiment and ESG data to generate diversified, convex returns.

Pulse Analysis

The 2025 outperformance of emerging‑market equities marks a turning point for a region long hampered by valuation gaps and currency volatility. Lower inflation, earlier rate‑cut cycles, and a weakening U.S. dollar have created a macro environment conducive to capital inflows. At the same time, AI‑related capital expenditure is spilling over into semiconductor hubs like Taiwan and South Korea, offering growth catalysts that complement traditional value drivers. Investors are therefore re‑evaluating EM exposure not just for price appreciation but for its emerging role in the global AI supply chain.

Systematic investing is uniquely suited to the fragmented, data‑rich landscape of emerging markets. RAM Active Investments leverages a proprietary deep‑learning platform that ingests daily news, fundamentals, ESG metrics and market micro‑structure signals for over 4,000 securities. By applying strict liquidity and sustainability screens, the model filters out opaque firms, while 500 alpha inputs per stock generate nuanced factor tilts across quality, value, momentum and low‑risk dimensions. This disciplined, quantitative workflow eliminates behavioral bias and enables consistent, transparent portfolio construction that would be infeasible through discretionary analysis alone.

Since its 2009 inception, RAM AI’s EM equity strategy has demonstrated a convex return profile, with beta near 1 in rising markets and around 0.7 during downturns, resulting in lower volatility and a stable 5% tracking error versus the MSCI EM benchmark. The diversified 500‑600‑stock portfolio reduces idiosyncratic risk, while embedded ESG considerations align with Article 8 regulatory standards. For institutional investors seeking exposure to the region’s demographic tailwinds and AI growth without the concentration risk of passive indices, the systematic approach offers a compelling blend of performance, risk management and sustainability.