Three researchers from The College of New Jersey analyze correlation coefficients for a variety of ETFs across asset classes.
One important facet of portfolio construction and portfolio management is diversification. By offsetting the risk associated with individual assets, diversification reduces the variability of portfolio returns.
To achieve diversification, the returns on the various assets in a portfolio should not be highly correlated. Adding securities whose returns are highly correlation does not reduce the variability of the portfolio return and does not contribute to diversification and the reduction of risk. Thus, the investor or portfolio manager needs to identify assets with returns that are low or even negatively correlated.
Exchange-traded funds (ETFs) have become a popular investment vehicle, since the investor acquires a basket of securities without having to select individual stocks or bonds. ETFs may be promoted as a means to achieve diversification and manage risk. Diversification, however, will not be achieved if returns on the various ETFs are highly correlated.
The following tables report the correlation coefficients for a variety of ETFs. Weekly returns are computed from the date of each ETF's inception. The resulting returns are used for the calculation of correlation coefficients. While some ETFs (e.g., the SPDRs based on the S&P 500 stock index) have existed for several years, many are relatively new, having been created only in the last few years. The relative newness of many ETFs limits the number of time periods that may be used to calculate the returns. While the results may be considered preliminary, they do suggest that the returns on many ETFs are highly correlated and hence their ability to contribution to diversification is limited.
Table 1 starts with three aggregate ETFs based on the S&P 500 (the SPDRs, the iShares and the ProShares Ultra S&P500). As would be expected, the returns on SPY, IYY and SSO are highly correlated. The subsequent parts of the table present the correlation coefficients relating SPY, IYY and SSO to ETFs specializing in specific sectors: health stocks, natural resources and real estate investment trusts (REITs), and ETFs based on diversified emerging markets, world stock markets and precious metals. If the investor adds these ETFs to a portfolio holding SPY, IYY or SSO, the expectation would be that risk is reduced through diversification.
With the exception of precious metals, the correlation coefficients in Table 1 are relatively high. The precious metal coefficients are consistently less than 0.3 and in some cases even negative, suggesting that adding precious metals ETFs to an aggregate stock portfolio reduces risk. For the remaining ETFs, the potential for risk reduction is small. With one exception (IGE) the coefficients exceed 0.5 and the majority exceeds 0.8. This may be surprising since even the emerging markets ETFs are highly correlated to the aggregate market ETFs.