Historical Echoes: When Pigskins Fly – the Super Bowl and Other “Predictors”
More than three decades ago, Robert Stovall, a money manager, championed a theory put forth by a sports columnist. Stovall studied the performance of stock indexes after each Super Bowl and concluded that the winner could predict stock market trends. For fifteen consecutive years, between 1967 and 1983, the New York Stock Exchange showed annual gains when a team from the old National Football League won the Super Bowl and fell when a team from the old American Football League emerged as the victor.
Two academic researchers put Stovall’s conclusions to the test; their findings, published in a 1990 Journal of Finance paper, showed that the predictions were accurate twenty out of twenty-two times between 1967 and 1988 for each of the following stock indexes: New York Stock Exchange, S&P 500, Dow Jones Industrial Average, and American Stock Exchange. (Note that the researchers used the pre-merger placement of the Pittsburgh and Baltimore teams. So the victories by the Steelers [1975-76, 1979-80] and Colts  counted as NFL wins.)
In more recent times, the accuracy rate drops significantly, or perhaps not, depending on one’s perspective. Among various debunkings of the theory, this humorous one comes with a great line: “Statistically significant success in prediction does not automatically lead to economically profitable strategies.”
New York Giants fans who also subscribe to this Super Bowl theory: You have one more reason to root for your team. Should the Giants prevail this year, however, let’s hope it doesn’t cause a repeat of the 2008 experience, when stock markets diverged from the theory and experienced a downward spiral.
Super Bowl victories aside, sales of these items have also been cited for their ability to gauge the state of economic activity: lipstick, Spam, and cardboard boxes.
Because official statistics are subject to publication lags, some researchers have begun to examine Internet search terms and word frequency for more timely insight into economic conditions. Searches for “jobs” and “unemployment benefits” were compared with unemployment data over the same period, while “estate agents” was correlated with house price inflation as a likely predictor of changes in employment rates and housing prices, respectively. A more recent New York Fed finding declared that “Internet search counts possess useful information, not available in other variables, to now-cast or forecast the trajectory of some financial market data.”
The Economist evaluated the number of newspaper articles using the term “recession,” thus creating the R-word index. Researchers at the San Francisco Fed expanded on the index by examining more search terms in thirty newspapers to gauge consumer sentiment. And an analysis of social-media posts led to the announcement in 2011 of the high-heel index.
The views expressed in this post are those of the author and do not necessarily reflect the position of the Federal Reserve Bank of New York or the Federal Reserve System. Any errors or omissions are the responsibility of the author.