Investors use estimates of a stock’s future price, set by finance industry analysts, as one tool to assess the asset’s value in coming months and decide whether to buy or sell. At first blush, very high “consensus” analyst target prices—that is, the average of financial analysts’ individual target prices—may look appealing to investors and tempt them to buy.
But hidden in the widely available numbers is a cautionary tale, according to Yale SOM’s Thomas Steffen and Frank Zhang. When the researchers looked at dispersion, or the degree to which analysts’ individual stock price predictions varied—a figure that’s not readily available to the general public—they found a critical link between the degree of dispersion and how well consensus target prices ultimately predicted actual future stock returns.
In a new paper, Steffen and Zhang say that when dispersion is low—meaning analysts’ stock price predictions are more closely aligned—the consensus price does a decent job at forecasting actual returns. But high-dispersion predictions tend to result in very poor stock returns. In fact, in cases of high dispersion, investors are more likely than not to see negative market-adjusted returns. That’s especially true for stocks that have high retail interest, which suggests that individual investors are being misled by the inflated target prices that are readily accessible online.
To calculate dispersion, Steffen and Zhang used analysts’ individual target prices from 1999 to 2020, which they pulled from the Institutional Brokers’ Estimate System (IBES) platform. The researchers then compared consensus target prices and dispersion from IBES to actual stock return data from the Center for Research in Security Prices.
The researchers also looked at analysts’ earnings forecasts and firms’ actual earnings data. As they dug deeper into the numbers, they arrived at a possible explanation for cases of high dispersion: some analysts appear to delay or only partially adjust their stock price predictions after bad news about a company breaks. Indeed, the researchers found that high-dispersion stocks tend to be covered by analysts who delay and incorporate less bad news when they’re updating their target prices.
Analysts’ failure to act in these cases widens the gap between current and predicted stock prices, leaving the consensus figure too high even as the actual stock price may have dropped because of the negative news. “The consensus figure doesn’t end up reflecting the deteriorating fundamentals,” Zhang says.
One reason why analysts may choose not to revise down their stock price prediction after negative news, leaving their prediction stale, is to curry favor with the companies they’re covering. “If analysts are pessimistic about a company, then their brokerage firm may be less likely to be awarded investment banking business from that company, like issuing stocks or bonds for them,” Zhang says. “So when bad news hits, they don’t update.”
Analysts also need to preserve the contacts they have within a company who share the financial information they need to shape their views. “Analysts want access to managers, and they’re hesitant to go public with any really negative views,” Steffen adds.
The findings suggest not only that retail investors shouldn’t rely too heavily on consensus target prices, Steffen and Zhang say, but that—theoretically, at least—they could use a hedging strategy to actually benefit from the different dispersion outcomes.
Steffen and Zhang looked at what would happen if investors were to take a long position with stocks characterized by low dispersion and high predicted returns—buying them as they expected their price to rise—and take a short position with stocks that were marked by high dispersion and high predicted returns—selling these stocks as they anticipated poorer returns—and found they could have earned more than 11% annually on average.
“Investors could benefit from this strategy,” says Steffen, “but it’s hard to do because the dispersion information is not readily available to your average Joe investor.”
For example, sites like Yahoo Finance and MarketWatch don’t display information on dispersion for consensus analyst target stock prices. And tracking down individual analysts’ target prices to calculate dispersion oneself would require pricey subscriptions to multiple banks’ analyst reports.
Ideally, investors would have easy access to dispersion figures so they could apply the hedging strategy—or at least better assess how well consensus target prices predict a specific stock’s returns. “One potential remedy is for policymakers to encourage sites like Yahoo and MarketWatch to display additional information,” Steffen says, including the makeup of target prices, how stale they are, and when they were last updated.
Barring that, there are clues that investors can look for to attempt to figure out whether a consensus price is marked by low or high dispersion. For example, some sites provide the highest and lowest target prices, and when the range between them for a particular stock is large, dispersion is also typically high, they say. An especially big difference between a current stock price and the analysts’ consensus target price might also be a sign of high dispersion, according to the researchers.
Dispersion, the researchers suggest, could well be one of several overlooked factors that are influencing stock target prices. It’s a dynamic that investors should keep their eye on, they say. “This paper helps to shine a light on what we can learn by focusing on these less apparent parts of analyst outlooks,” says Steffen.
“The Yale School of Management is the graduate business school of Yale University, a private research university in New Haven, Connecticut.”
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