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Dogs Of The Dow Vs. Laggards: Which Is A Better Play?

Dogs Of The Dow Vs. Laggards: Which Is A Better Play?

The Bernstein quantitative research team recently took a look at some popular contrarian trading strategies to see how they stack up. Analyst Ann Larson looked at how the “Dogs of the Dow” strategy has historically performed compared to buying the leaders and laggards of the S&P 500.

The Dogs of the Dow strategy involves buying the 10 highest-yielding Dow Jones stocks at the end of each year and re-adjusting annually. Bernstein looked back at how the Dogs strategy performed over the past 20 years. In addition, the firm tested two other strategies: annually buying the worst third of performers in the S&P 500 (laggards) and the best third of performers in the S&P 500 (leaders).

The Results

Larson found that the Dogs of the Dow strategy has produced a 390 percent return in the past 20 years compared to a 349 percent gain by the S&P 500. The S&P 500 laggards strategy, however, generated an even better gain of 459 percent. The S&P 500 leaders strategy fell short of the S&P 500’s gains.

Larson also found that by weeding out value traps from the laggards group by using the Bernstein Alpha Model, a simple modification of the laggard strategy would have produced on overall 20-year gain of 853 percent.

Larson also discussed the negative impact that crowding has on stock performance.

The most crowded stocks tend to underperform during periods of market volatility.

“In addition, crowded stocks have a negative return skew; they react more negatively to bad news and less positively to good news as measured by earnings revisions or earnings surprise,” Larson explained.

According to Bernstein, the technology sector is currently the most crowded sector, while the energy sector is the least crowded.

Larson noted that Apple Inc. (NASDAQ: AAPL), Microsoft Corporation (NASDAQ: MSFT) and, Inc. (NASDAQ: AMZN) are the three most crowded stocks in the market today.

Latest Ratings for AAPL

Jun 2019Initiates Coverage OnOutperform
Jun 2019MaintainsBuy
May 2019MaintainsOverweight

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