The MSCI Emerging Market Indices comprise a series of indices designed to track the stock market performance in emerging economies. An emerging market, as defined by MSCI, is a country experiencing rapid economic growth and development, often marked by increasing industrialization, developing infrastructure, expanding capital markets, and rising standards of living. These markets are characterized by their potential for high growth, though they may also present greater volatility and risks compared to developed markets.
Together these indices form the MSCI Emerging Market Index, which is a widely recognized benchmark for emerging market equities.
MSCI country indices are designed to include about 85% of the free float-adjusted market capitalization in each country. This approach ensures that the indices provide a comprehensive representation of the large and mid-cap segments of the respective national equity markets. The country index versions in the charts above are all denominated in USD, capitalization-weighted, and do not include dividends.
The chart above shows a heat map depicting the correlation coefficients among various emerging market indices. Each index is represented on both the x and y axes, with intersections revealing the strength and direction of their correlation. A correlation coefficient of +1 indicates a perfect positive correlation, implying that two indices moved in the same direction during the specified time window. Conversely, a coefficient of -1 signifies that the indices moved in opposite directions. Colors range from deep blue, indicating a negative correlation, to dark red, signifying a strong positive correlation.
The correlation coefficient is important to consider for diversification because it helps investors assess the potential benefits of including different assets in their portfolios. Diversification is the practice of spreading investments across different asset classes to reduce risk. In his book Principles, Ray Dalio called diversification the “Holy Grail of Investing”. He realized that with fifteen to twenty uncorrelated return streams, he could dramatically reduce the risks without reducing the expected returns.
The minimum spanning tree (MST) simplifies the data from the correlation matrix above by retaining only the strongest correlations. If two indices are connected, it means that they are positively correlated and that they tend to move in tandem. By analyzing the structure of the MST, one can identify clusters of indices that move together. This visual tool is especially beneficial when considering international portfolio diversification. In fact, Marti, Gautier, et al. (2017) found that the optimal Markowitz portfolio is found at the outskirts of the tree and that the tree shrinks during a crisis.
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