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I previously wrote about the challenges of passive investing, with the view that increasing globalization has resulted in increasing correlations among the world's major stock indices. I also recently looked at changes in Betas of various equities in the article The Challenges of Using Beta to Measure Risk. These same concepts can be applied to looking at country performance. From a U.S. perspective, one can calculate a beta for these different indices to assess the overall level of risk, and also see how that risk has changed over time.

For this article I'll look at the following indices using a 48 month beta:

  1. S&P 500 - One of the two leading indices in the United States, the S&P 500, tracks the largest 500 stocks. The S&P 500 is a market capitalization weighted index. It was switched to float adjusted, meaning that only shares available would be considered as part of the market capitalization. Many foreign indices use this method since several companies have large stakes owned by the government. The S&P 500 does not capture the impact of dividends. For the casual investor, the best way to gain exposure is through either SPDR S&P 500 Trust ETF (NYSEARCA:SPY) or Vanguard's S&P 500 ETF (NYSEARCA:VOO).
  2. FTSE 100 - The FTSE 100 represents the 100 largest market capitalization stocks on the London Stock Exchange. It is also a float adjusted market capitalization weighted index. General exposure to stocks in the United Kingdom can be obtained through the iShares MSCI United Kingdom ETF (NYSEARCA:EWU).
  3. iBOVESPA - iBOVESPA is an index of about 50 stocks that are traded on the Sao Paulo Stock, Mercantile & Futures Exchange. It is a theoretical index based on the stocks that represent about 80% of trading volume of the previous 12 months. iBOVESPA also accounts for dividend reinvestment. iShares MSCI Brazil Index Fund (NYSEARCA:EWZ) provides the easiest way to gain exposure to iBOVESPA, but does not exactly track it.
  4. DJIA - The Dow Jones is one of the most recognized stock indices. It is a combination of 30 leading U.S. companies. It is a price-weighted average, unlike the S&P 500, which is weighted by equity market capitalizations. The DJIA was formed on May 26, 1896 by Charles Dow. For the casual investor, the easiest way to obtain exposure to the DJIA is through the SPDR Dow Jones Industrial Average ETF (DIA).

FTSE 100 Beta Decomposition

Source: Created from data from Yahoo!Finance.

The first observation is that the correlation coefficient seems to shift between 50% and 90% in periodic cycles. The volatility ratio also appears to have an overall downward trend in the available data. Prior to the Great Recession, the correlation was trending downward, by then becoming much more correlated to the U.S. stocks.

iBOVESPA Beta Decomposition

Source: Created from data from Yahoo!Finance.

This chart of the iBOVESPA from Brazil shows a somewhat expected pattern for a rapidly growing emerging market country. The volatility ratio has shown a significant downward decline, having started at around 3x the S&P 500 volatility and now being around just 1.2x. However, at the same time, the correlation coefficient has drifted up from just above 50% to around 75%. This has resulted in a slight downward trend in beta. The large spike in volatility during the middle of the 2000s was possibly due to excitement for emerging markets, but also the commodity boom. I would hypothesize that the significant influx of capital created the additional volatility.

DJIA Beta Decomposition

Source: Created from data from Yahoo!Finance.

I also wanted to include a comparison of the DJIA against the S&P 500. As expected, it shows a pretty tight correlation over the past 55 years ranging from lows of 90% to 98-99%. As perhaps expected, the correlations weakened periodically in the 90s, possibly due to the increasing influence of technology companies in the S&P 500. The volatility has also fluctuated. It appears that the DJIA is actually more volatile than the S&P 500. It is quite possibly related to the nature of the companies in the index, since it is over-weighted in Industrials (27% to 13%) and slightly under-weighted across most other sectors. Perhaps more likely is that 30 companies, while providing good diversification, are still measurably less diversified than 500.

Comparing betas of global indices is a little different from comparing betas of U.S. equities since (at least for the U.S. equities) they exist more closely within the U.S. macroeconomic environment. However, the foreign companies in the FTSE 100 and iBOVESPA exist essentially outside the U.S. macroeconomic environment. Hence, one would naturally expect lower correlations. However, it also means there are other risks to the representative ETFs for these countries. Clearly, one should also place some value in Modern Portfolio Theory. It should be noted that the capital asset pricing model is a single factor model, and there are other possible multi-factor models that could explain more of the variation in returns.

Conclusion
This analysis clearly shows the increasing correlation of Brazil-- and I would suspect, most emerging markets. It shows a leading developed market that has a fluctuating, but still increasing correlation. However, it also shows the reduction in volatility in Brazil, suggesting the expected returns should also be lower. While I am positive about emerging markets, I would also expect lower returns over time. This pushes U.S. based investors seeking better diversification further afield. Market Vectors Africa Index ETF (NYSEARCA:AFK) might be one possibility. However, it has limited assets and a low trading volume.

Disclosure: I am long EWZ, SPY.

Disclaimer: This article is for informational and educational purposes only and shall not be construed to constitute investment advice. Nothing contained herein shall constitute a solicitation, recommendation or endorsement to buy or sell any security.

Source: Changing Risk and Correlation Among Global Indices