The US stock market had a marvelous year in 2017. The major benchmark S&P 500 returned 21.60%[1] including dividends. But savvy investors probably noticed that there were some significant discrepancies among the major indexes: If you chose the tech-heavy NASDAQ composite, you would have made 29.58%[2] last year, while if you invested in the small-cap Russell 2000, you would have profited only 14.52%[3].
It appears that volatility wasn’t the only number that was suppressed in the stock market last year: Stock correlations also remained low. So what does it mean to investors when stock correlations are low?
Simply put, stock correlations measure the contemporaneous movement among stocks and explain why stocks move in different directions. Stock correlations are particularly important statistics for portfolio weighting, while weighting is important for portfolio returns. For example, the large-cap S&P 500 is value-weighted, meaning that each stock makes up a portion of the index according to its market cap. Therefore, the mega-caps in the S&P 500 are capable of single-handedly driving up the index. However, if the S&P 500 were equal-weighted, then all the stocks would contribute in the same way to move the overall market.
How much does the weighting scheme matter to a portfolio? Let’s compare the value-weighted and equal-weighted S&P 500 performance history, as shown in Figure 1 below. Starting from the bottom of the financial crisis in March 2009, the equal-weighted ETF RSP outperformed the value-weighted ETF SPY by 30%, simply due to the weighting difference.
Figure 1. SPY vs. RSP since March 2009
Source: Yahoo! Finance
Figure 2. Value vs. Equal Since 1986
Source: Center for Research in Security Prices
Is there anything else that explains the equal weighting outperformance besides stock correlations? Yes. The answer is January. We notice that the equal-weighted portfolio averages a 3.98% return in January across the 30 years, 3.11% above the value-weighted portfolio, while there is no dramatic difference for the rest of the year. This pattern suggests that the difference between the value-weighted and equal-weighted portfolios comes mainly from just one month. In fact, this “January effect” has long been documented by academic research. Scholars find that while stocks generally rise in January, small-caps tend to be more affected than large-caps are. Generally, low stock correlation dictates the divergence between value and equal investing. Beyond that, low stock correlation signals a stock picker’s market – more specifically, one needs to choose the right sector to generate alpha.
Leo Chen, Ph.D.
Portfolio Manager & Quantitative Strategist
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