Poring over stale financial information might not seem like a particularly useful investment strategy, but new research suggests that yesterday’s news can help drive tomorrow’s profit: Investors can generate an impressive average annual return of close to 8 percent using a simple strategy that relies on the stock market’s reaction to releases of previously announced economic data.
This finding comes from a group of researchers including McCombs Assistant Professor Shimon Kogan, who looked at how U.S. stock and Treasury futures prices respond to the information contained in the monthly U.S. Leading Economic Index (LEI). They found the prices moved strongly, even though much of the information in that report had already been released elsewhere.
The study, “Investor Inattention and the Market Impact of Summary Statistics,” was published in the February 2012 issue of Management Science. Findings suggested that investors could look at previously published components of the LEI, such as unemployment figures and housing starts, to figure out in advance what the index will show. Based on that prediction, they were able to trade S&P 500 futures in the direction of the announcement a day before the LEI’s release, and then trade in the opposite direction of the announcement afterward.
The researchers chose the LEI because it is a widely followed release of previously released statistics that are readily available. They examined LEI announcements from 1997 to 2009, and compared those to data on S&P 500 futures returns. They found that a positive LEI announcement was accompanied by positive returns the day before and the day of the release. Negative announcements were similarly associated with negative returns. The impact was short-term, however, lasting only a day for before returns were reversed.
Risks to Investors
Kogan cautions that the findings, while revealing significant implications for how markets employ information in pricing, don’t describe a strategy that would be practical for typical investors trying to profit from changes in the monthly index.
“We don’t have that many trading opportunities a year,” Kogan explains. “There are 12 releases a year, but half of them are going to be close to zero, so you may have a few trading opportunities a year. That’s not worth setting up the infrastructure you need to really make money off this.”
Also, while the study shows solid average returns over time, an investor would run the risk of losing money trading on any individual release.
“You could run this strategy and in a month you could lose a lot of money,” Kogan says. “It’s not the type of profit opportunity where you’re guaranteed to make money each time you trade. None of the findings in the literature of finance are of that sort, where we can say, ‘Here’s the recipe. Go ahead and print money.’”
While Kogan and his colleagues — including researchers from the University of Washington, Columbia University and the Conference Board (the organization that publishes the LEI) — didn’t find a risk-free route to riches, they did contribute significantly to the literature on how markets process information, as revealed in prices.
One important finding is that aggregate stock and bond markets, rather than merely individual stocks, can respond significantly to the release of stale information. Previous investigators have documented similar individual stock price movements. But this is the first to find that stale macroeconomic data can move something as broad as the S&P 500 Index. The research also pushed into new terrain by finding these effects with recurring information released on a regular basis.
Kogan says the overall finding didn’t especially surprise him, but the size of the response was greater than expected.
“I would have been surprised to find, given what I know, that markets were fully efficient,” he says. “But the magnitude that we’re finding is actually quite substantial, given that we’re looking at an aggregate market index and not individual stocks.”
Information's Influence on Prices
Kogan’s next research project focuses on using computers to analyze text in articles about companies and economics in general to uncover and quantify their effect on prices.
“It fits into that general area of trying to understand how information feeds into prices and whether the price movements that we see are fully reflective of information,” he says.
The new project also fits into a wider stream of research in behavioral finance that elaborates on efficient-market theories, identifying variations and exceptions to the idea that prices always perfectly reflect information available to investors.
While the latest findings don’t necessarily suggest a specific trading strategy, Kogan says there is a takeaway for individual investors. Namely, before an investor trades based on data from earlier reports, he or she should consider whether prices already reflect that information.
“It’s very unlikely that you’re the only person who’s privy to that information and came to that conclusion,” he says.