The Dogs of the Dow
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Definition of 'The Dogs of the Dow'
The Dogs of the Dow is an investment strategy made popular by Michael O’ Higgins in his book, Beating the Dow, published in 1991.
O’Higgins demonstrated that over a 17-year period from 1973 to 1989, his Dogs strategy averaged a return of 17.9% annually, compared to 11.1% for the Dow.
The strategy proposes that an investor annually select the ten Dow Jones Industrial Average (DJIA/$INDU) stocks whose dividend is the highest fraction of their price. (i.e. Stocks with the highest dividend yield.)
Proponents of the Dogs of the Dow strategy argue that blue chip companies do not alter their dividend to reflect trading conditions and, therefore, the dividend is a measure of the average worth of the company; the stock price, in contrast, fluctuates through the business cycle. This should mean that companies with a high yield, with high dividend relative to price, are near the bottom of their business cycle and are likely to see their stock price increase faster than low yield companies.
With this strategy, an investor will annually reinvesting in high-yield companies and should be able to out-perform the overall market. The logic behind this is that a high dividend yield suggests both that the stock is oversold and that management believes in its companies prospects and is willing to back that up by paying out a relatively high dividend.
Investors are therefor hoping to benefit from both above average stock price gains as well as a relatively high quarterly dividend. Several assumptions are made in this argument:
1. The dividend price reflects the company size rather than the company business model.
2. Companies have a natural, repeating cycle in which good performances are predicted by bad ones.
The Dogs of the Dow were created by data mining. If you look at Dow stocks on January 1 then the high yielding stocks did significantly better than average before 1991 than they did after 1991.
All Dogs of the Dow variations performed randomly after they were created. None of them have performed better after discovery than they did prior to publication.
O’Higgins demonstrated that over a 17-year period from 1973 to 1989, his Dogs strategy averaged a return of 17.9% annually, compared to 11.1% for the Dow.
The strategy proposes that an investor annually select the ten Dow Jones Industrial Average (DJIA/$INDU) stocks whose dividend is the highest fraction of their price. (i.e. Stocks with the highest dividend yield.)
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 high dividend relative to price, are near the bottom of their business cycle and are likely to see their stock price increase faster than low yield companies.
With this strategy, an investor will annually reinvesting in high-yield companies and should be able to 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 companies prospects and is willing to back that up by paying out a relatively high dividend.
Investors are therefor hoping to benefit from both above average stock price gains as well as a relatively high quarterly dividend. Several assumptions are made in this argument:
1. The dividend price reflects the company size rather than the company business model.
2. Companies have a natural, repeating cycle in which good performances are predicted by bad ones.
The Dogs of the Dow were created by data mining. If you look at Dow stocks on January 1 then the high yielding stocks did significantly better than average before 1991 than they did after 1991.
All Dogs of the Dow variations performed randomly after they were created. None of them have performed better after discovery than they did prior to publication.
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