Dividends can pay–without paying!

///Dividends can pay–without paying!

Dividends can pay–without paying!

By | 2017-01-13T12:55:55+00:00 October 3rd, 2011|Research Insights|0 Comments
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(Last Updated On: January 13, 2017)

The Dividend Month Premium

  • Sam Hartzmark and David Solomon
  • A recent version of the paper can be found here.

Abstract:

We document that companies have positive abnormal returns in months when they are expected to pay dividends. Abnormal returns in predicted dividend months are high both relative to all other companies (by 53 basis points per month), and relative to dividend-paying companies in months without a predicted dividend (by 37 basis points per month). These results are consistent with time-series effects of dividend clienteles – investors who desire dividends bid up the price before the ex-dividend day. Consistent with this, daily returns increase as the ex-dividend day approaches, and are negative afterwards. Returns are also larger in periods of economic uncertainty, when demand for dividends may be higher.

Data Sources:

The authors use CRSP for returns and dividend data. The sample period is 1927 through 2009.

Discussion:

Investors are often obsessed with dividend-paying stocks, and for good reason–historically, buying high div-yield stocks has been a good bet.

The figure below shows the performance of high-dividend stocks (labeled “DIV”) vs low-dividend stocks from 1971-2010 within the SP500 universe. Who wouldn’t want a few extra % per year tacked on to their equity portfolio?

The results are hypothetical results and are NOT an indicator of future results and do NOT represent returns that any investor actually attained. Indexes are unmanaged, do not reflect management or trading fees, and one cannot invest directly in an index. Additional information regarding the construction of these results is available upon request. (Source: Turnkey Research)

Interestingly, the ‘outperformance’ of high-dividend stocks was very high from 1971-1990: ~15% vs 7%!

The results are hypothetical results and are NOT an indicator of future results and do NOT represent returns that any investor actually attained. Indexes are unmanaged, do not reflect management or trading fees, and one cannot invest directly in an index. Additional information regarding the construction of these results is available upon request. (Source: Turnkey Research)

Nonetheless, the ‘outperformance’ of high-dividend stocks was non-existent from 1990-2010!!!

The results are hypothetical results and are NOT an indicator of future results and do NOT represent returns that any investor actually attained. Indexes are unmanaged, do not reflect management or trading fees, and one cannot invest directly in an index. Additional information regarding the construction of these results is available upon request. (Source: Turnkey Research)

Despite the empirical evidence that dividend-paying stocks have not really helped investors in recent memory (past 20 years), the reverence for dividends and high-yield stocks does not appear to have vanished. However, this paper highlights a way in which dividends may still find a way to generate alpha–something we all love!

All the strategies analyzed in this paper are very similar:

  1. Sort stocks into those who are predicted to pay a dividend and those who will not pay a predicted dividend. Dividends are considered “predictive” if the firm paid a past dividend on a regular schedule (for example, a company would have a predicted dividend in month t if they paid a dividend in month t-3, t-6, t-9, or t-12.).
  2. Long the predicted dividend payers, short the alternatives

Table III below highlights a very basic strategy of going long all ‘predicted dividend’ firms at the beginning of the month and shorting a basket of non-dividend payers. This rough-cut strategy generates around 53bp a month in alpha, or around 6%/year. Also, 41bp are attributed to the long-only leg of the strategy: in other words, if you simply purchased all predicted dividend payers at the beginning of month t, you’d earn around 5%/year in returns that are unexplained by “risk.”

The results are hypothetical results and are NOT an indicator of future results and do NOT represent returns that any investor actually attained. Indexes are unmanaged, do not reflect management or trading fees, and one cannot invest directly in an index. Additional information regarding the construction of these results is available upon request.

Table IX takes the analysis in Table III a bit further and segments predicted dividends based on the recent history of dividends paid by the firm. The most exciting results are attached to the long book which goes long all predicted dividend payers who also had a dividend increase in the last year (86bp/month) and the short book which goes short all predicted dividend-paying companies who missed a dividend payment in the last year (73bp/month). The L/S combo could theoretically generate over 1.5%/month in alpha! Of course, I’d imagine the negative short book returns are driven by a handful of companies with predicted dividends that end up not paying out a dividend–so the ride along this L/S rollercoaster might be too intense for most investors.

The results are hypothetical results and are NOT an indicator of future results and do NOT represent returns that any investor actually attained. Indexes are unmanaged, do not reflect management or trading fees, and one cannot invest directly in an index. Additional information regarding the construction of these results is available upon request.

Table VII explores some additional angles on the monthly dividend strategy–looks like the lowest hanging fruit is to trade semi-annual dividend paying firms who are predicted to pay a dividend (115bp/month).

Figure 1 is 100% finance porn–warning, for alpha-seekers only-the portfolio that is a long-short portfolio, using the within-companies definition (long in months 3, 6, 9 and 12, short in months 1, 2, 4, 5, 7, 8, 10 and 11), earns around the same return as the HML factor, but with a heck of a lot less risk–oh yeah!

The results are hypothetical results and are NOT an indicator of future results and do NOT represent returns that any investor actually attained. Indexes are unmanaged, do not reflect management or trading fees, and one cannot invest directly in an index. Additional information regarding the construction of these results is available upon request.

Investment Strategy:

  1. Each month identify all the predicted dividend companies; go long these companies
  2. Each month identify all firms that are not predicted to pay a dividend; go short these companies to hedge your long book
  3. Make money

Commentary:

To keep this write up simple and to the point I’ve highlighted all the results based on monthly rebalance of a portfolio that invests in stocks expected to pay a dividend. There is some additional analysis embedded in the paper that looks at the daily returns to strategies that actually trade before the ex-date on a dividend. There are some very interesting avenues to explore within this category of trading, but the complications are 10x when one moves from monthly rebalanced strategies to daily rebalanced strategies.

Another aspect of this paper that is mentioned, but not really understood, is the accounting and tax implications of running a ‘buy all the predicted dividend paying companies.” All else equal, owning a stock that pays a dividend vs owning a stock that doesn’t pay a dividend is tax inefficient (you are forced to realize tax on dividends paid). Plus, trading in and out of dividend paying stocks every 30 days won’t trigger the favorable “qualified-dividend” 15% tax rate, but will instead stick you with a nice 30-40% income tax bill at year end–ugg, I hate taxes. Of course, you could plug this strategy in your tax-deferred retirement accounts, but that could be a serious pain in the rear.

Finally, figure 1 just blows my mind. I’d like to re-backtest the results and put the monthly returns on this strategy through our ringer of quantitative analysis–things that look to good to be true, often are.

Overall, this is a thought provoking paper on an ‘ancient’ finance topic–the new insight is refreshing and welcome–hope you enjoy the read.


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About the Author:

After serving as a Captain in the United States Marine Corps, Dr. Gray earned a PhD, and worked as a finance professor at Drexel University. Dr. Gray’s interest in bridging the research gap between academia and industry led him to found Alpha Architect, an asset management that delivers affordable active exposures for tax-sensitive investors. Dr. Gray has published four books and a number of academic articles. Wes is a regular contributor to multiple industry outlets, to include the following: Wall Street Journal, Forbes, ETF.com, and the CFA Institute. Dr. Gray earned an MBA and a PhD in finance from the University of Chicago and graduated magna cum laude with a BS from The Wharton School of the University of Pennsylvania.
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