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Do Dividends Really Pay? (Part 2)

May 01, 2018 2:49 AM ET12 Comments
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S&P Dow Jones Indices

By Philip Murphy

Previously, I discussed why a preference for dividend-paying stocks may not have a strong theoretical footing but could be grounded in behavioral and practical reasons. Furthermore, due to possible economic signaling generated by dividends, such strategies may be correlated with widely accepted factors like quality and value. This post demonstrates how specific dividend strategy indices may be related to several major factors. Exhibit 1 lists major characteristics of four popular S&P DJI dividend indices. Dividend strategies can be very different from one another, so it pays to understand individual indices behind various index-tracking products. However, despite their differences, indices are generally much more transparent than actively managed dividend strategies.

The indices in Exhibit 1 highlight four combinations of constituent selection and weighting. For selection, we have either indicated dividend yield ranking or persistent historical dividend growth, while for weighting we have yield weighting or equal weighting. The various combinations of selection and weighting methods contribute to significantly different index performance.

Exhibit 2 shows summary statistics of the four dividend indices regressed on Fama-French factor returns, including market beta (Mkt-rf), small size (SMB), value (HML), and momentum (MOM). AQR's quality factor, Quality Minus Junk (QMJ), is added to form a five-factor regression model.

  • Market Beta (Mkt-rf): All of the indices had statistically significant market betas in a tight range from 0.84 to 0.89, indicating somewhat less equity risk than a broad benchmark.
  • Small Size (SMB): These strategies generally did not present positive SMB loadings and, based on the presence of several negative coefficients, the regressions may indicate a tendency toward larger constituents. However, none of the regression coefficients were statistically significant (at 95% confidence), so the data does not support an inference.
  • Value (HML): With respect to HML loadings, we see differentiation among the indices along the

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