The Dogs of the Dow is an investment strategy popularized by Michael B. O'Higgins in 1991, which proposes that an investor annually select for investment the ten Dow Jones Industrial Average (DJIA) stocks whose dividend is the highest fraction of their price.
Contents
History
Selecting some components of the DJIA is not a new idea. An article by H. G. Schneider was published in The Journal of Finance in 1951, based on selecting stocks by their price–earnings ratio.
Concept
Proponents of the Dogs of the Dow strategy argue that blue-chip companies do not alter their dividend to reflect trading conditions and, therefore, the dividend is a measure of the average worth of the company; the stock price, in contrast, fluctuates through the business cycle. This should mean that companies with a high yield, with a high dividend relative to stock price, are near the bottom of their business cycle and are likely to see their stock price increase faster than low-yield companies.
Under this model, an investor annually reinvesting in high-yield companies should out-perform the overall market. The logic behind this is that a high-dividend yield suggests both that the stock is oversold and that management believes in its company's prospects and is willing to back that up by paying out a relatively high dividend. Investors are thereby hoping to benefit from both above-average stock-price gains as well as a relatively high quarterly dividend. Of course, several assumptions are made in this argument.
The first assumption is that the dividend price reflects the company size rather than the company business model. The second is that companies have a natural, repeating cycle in which good performances are predicted by bad ones. Due to the nature of the concept, the Dogs may come from a small number of sectors. For example, the ten stocks that belonged to the 2015 Dogs of the Dow list came from only six sectors, including industrials, energy, and healthcare, in contrast to the S&P 500 Index which covers eleven sectors.
Results
O'Higgins and others back-tested the strategy as far back as the 1920s and found that investing in the Dogs consistently outperformed the market as a whole. Since that time, the data shows that the Dogs of the Dow as well as the popular variant, the Small Dogs of the Dow, have performed well.
For example, for the twenty years from 1992 to 2011, the Dogs of the Dow matched the average annual total return of the DJIA (10.8 percent) and outperformed the S&P 500 (9.6 percent), as reported by the Dogs of the Dow website located at dogsofthedow.com.
The Small Dogs of the Dow, which are the five lowest-priced Dogs of the Dow, outperformed both the Dow and S&P 500 with an average annual total return of 12.6 percent.
When each individual year is reviewed, it is clear that both the Dogs of the Dow and Small Dogs of the Dow did not outperform each and every year. In fact, the Dogs of the Dow and Small Dogs of the Dow struggled to keep up with the Dow during latter stages of the dot-com boom (1998 and 1999) as well as during the financial crisis (2007–2009). This suggests that an investor would be best served by viewing this as a longer-term strategy by giving this portfolio of stocks time to recover in case of a rare-but-extreme economic event (e.g., dot-com boom, financial crisis). While most any investor can back test an investment system that performed well over the recent past (data mining), what is unique about the Dogs of the Dow in this regard is that it has been forward tested for over two decades which included multiple booms and busts.
Criticism
On January 8, 2014, John S. Tobey wrote an article in Forbes magazine where he criticized the Dogs. He said that it should use price weighting, instead of equal weighting, because that is what the DJIA uses. He said that, for the year 2013, using the price weighting the Dogs would have returned less, rather than more, than the DJIA. He suggested that it is too simple and it should use more factors such as dividend–payout ratio, growth of cash and earnings, price performance, and many other things. However, he did not say how to combine these into a strategy. He also criticized it for back-testing (although the method was published in 1991). He also said that the strategy would not work well for 2014.