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Want Higher Investment Returns? Root for the Steelers
It's that time of year again, when analysts and data crunchers pore over National Football League statistics to try and glean who will have the best performance Super Bowl Sunday -- stock-market performance, that is.
It’s that time of year again, when analysts and data crunchers pore over National Football League statistics to try and glean who will have the best performance come Super Bowl Sunday -- stock-market performance, that is.
The "Super Bowl Indicator" is a fund statistic that looks at the past performance of teams to glean the future performance of the stock market. According to Investopedia, the indicator is based on the belief that a win for a team from the old AFL, or the current AFC division, means the stock market will fall in the coming year, while a win for a team from the old NFL, or the NFC division, bodes well for an up year on the stock market.
But if the indicator is to be believed, no matter which team wins this year -- Pittsburgh Steelers or Green Bay Packers -- the stock market will stage a powerful rally this year. Both teams hail from the old NFL.
If you want to see real double-digit returns on your investments, though, root for the Steelers. A report from analytics firm Capital IQ found that the average annual return for the Standard & Poor’s 500-stock index after a Steelers win is 26%.
And while a Packers win would signal an upside stock market, the average return after a Packers victory is 23%, according to Capital IQ. Even with that kind of record, you might want to root for a Packers loss — the average return, including the two years the Packers played in the Super Bowl and lost, was 29%.
But before you start betting heavily -- on the Steelers or the stock market — Marketwatch columnist Mark Hulbert cautions that while the Super Bowl Indicator has had its successes, it’s not infallible.
“The real Achilles' heel of the Super Bowl Indicator, at least from a statistical point of view, is that all it has going for it is a 79% success rate,” he writes. “And while you might think that this is good enough to bet on it, you're wrong: Many phenomena that have absolutely nothing to do with each other are nevertheless highly correlated statistically.”
