Until 2004, the Washington Redskins appeared to have a tremendous ability to predict the future. Prior to that year's election, since 1936, the Redskins' performance in their last home game before the election accurately predicted the party that would gain control of the White House. That's a pretty interesting piece of data mining, but as the 2004 election showed, it had no real influence on the outcome.

In truth, that connection between the Redskins' performance and the election results was due to pure random chance. Oh sure, you can concoct all sorts of stories about how teams feed off their fans, and that the feelings of the particularly partisan D.C. population could have influenced the outcome. When you pull back the covers, though, even explanations like that are little more than an attempt to force-fit a theory to a peculiar string of data points.

People who believed that the game could predict the outcome of the election were committing a common logical error. They believed that correlation was causation. But in reality, those are two very different things.  

Unnecessarily rough calculation -- 15-yard penalty -- repeat second down
Investors, too, are guilty of confusing correlation and causation. For example, investors often diversify their portfolios using correlation statistics or judge the riskiness of their holdings using beta -- a measure of the relative volatility of a stock compared to the rest of the market. But here's the rub: Past stock price movements have absolutely no long-term effect on future stock price movements. That's true of individual stocks and the market as a whole.

Nevertheless, many academic studies tend to focus on metrics such as beta because they are easily measurable. Yet what looks good in the textbook can fail miserably in the real world.

Take, for instance, this collection of seven leading companies that I originally pulled together in 2004 (and reported on about a year later):


Beta on

Total return

Fannie Mae (NYSE:FNM)



Johnson & Johnson (NYSE:JNJ)



Bank of America (NYSE:BAC)



Allstate (NYSE:ALL)



Ball Corporation (NYSE:BLL)



Praxair (NYSE:PX)



General Growth Properites (NYSE:GGP)



Whole account



S&P depository receipts (benchmark, SPY)



All data split-adjusted

By the correlation metric known as beta, all seven of these companies should have trailed the market. Yet four of the seven outperformed, and the collection as a whole easily outshined its benchmark index. If beta and correlation statistics had anywhere near a complete ability to predict the future movements of stocks, there is no way this group would have wound up on top. That's especially true now, since two years have passed since my last review of this portfolio, and any short-term "noise" should have worked its way out of the system by this point.

Profit from what really matters
In investing, over time, all that really counts is the quality of a business, the strength of its moat against competition, and the value you get for your investing dollar. All the historical price correlations in the world won't get you one step closer to true investing success.

Our market-beating performance at Motley Fool Inside Value showcases just how well you can do by paying attention to the business behind the stocks rather than merely their price movements. Want to check out our history and our current stock recommendations? Click here for a 30-day free trial. And don't let any more misconceptions hold you back from achieving your true investing potential.

Fool contributor and Inside Value team member Chuck Saletta is married to a wonderful woman who has a master's degree in applied statistics and who has taught him much about statistical fallacies. At the time of publication, Chuck owned shares of Bank of America and Johnson & Johnson, and his wife owned shares of General Growth Properties. Fannie Mae is an Inside Value recommendation. Johnson & Johnson and Bank of America are Income Investor picks. The Fool has a disclosure policy.