Given the known flaws in EM benchmarks (duration, currency, instrument type), it's possible to construct a passive, rules-based strategy to correct them. This 'smart beta' approach can systematically deliver a better Sharpe ratio than the underlying index, even if absolute returns are lower before leverage.
Active management is more viable in emerging markets than in the US. The largest EM ETF (EEM) has a high 0.72% expense ratio, the universe of stocks is twice as large as the US, and analyst coverage is sparse. This creates significant opportunities for skilled stock pickers to outperform passive strategies.
Contrary to the growth narrative, the MSCI China index returned just 3.4% over the last decade with over 24% volatility. During the same period, the emerging market ex-China index delivered a higher return of 4.8% with significantly lower volatility (17.5%), highlighting structural headwinds in China for investors.
A powerful EM strategy involves identifying businesses with proven, powerful models from developed markets, like American Tower. Local EM investor bases may not be familiar with the model's potential, creating an opportunity to buy these companies at a displaced valuation before their predictable results drive multiple expansion.
Over the past two decades, equity analysis has evolved beyond simply valuing a company's physical or financial assets. The modern approach focuses on identifying "alpha" factors—trading baskets of stocks grouped by shared characteristics like strong balance sheets or non-US revenue exposure.
Simple replication of managed futures indices is slow and has high tracking error. A superior “informed replication” approach combines backward-looking index data with forward-looking trend system priors and active risk management, resulting in a more robust beta-like exposure.
While broad emerging market currency indices appear to have stalled, this view is misleading. A deeper look reveals that the "carry theme"—investing in high-yielding currencies funded by low-yielding ones—has fully recovered and continues to perform very strongly, highlighting significant underlying dispersion and opportunity.
The extra return investors receive for taking on risk has compressed globally. For emerging markets, this premium is now negative at -1%, meaning investors are not being paid for the additional risk they're assuming compared to safer assets like government bonds.
Within any emerging market country, the annual return dispersion between equities, local debt, and hard currency debt is enormous. An investor who can consistently pick the winning asset class, even just over 50% of the time, will generate superior long-term returns due to this massive performance gap.
Standard emerging market benchmarks are misleading. Equity indices are heavily concentrated in a few countries, while bond indices suffer from inconsistent duration, ignore the vast derivatives market, and create unintended G10 currency bets due to their dollar-basing.
In emerging markets, where 'six sigma' events happen frequently, statistical risk models like Value at Risk are ineffective. A more robust approach is scenario analysis, stress-testing portfolios against specific historical crises like 1998 or 2008 to understand true vulnerabilities.