Stock prices get corrected for good or bad news over much longer periods than is commonly expected, which explains both short-term returns and the level of firm valuation, according to a recent paper.
Investors are often surprised when stock prices respond too slowly to good news or bad news in earnings announcements by firms. Those prices may take a few months or a few quarters to adjust to the news. In investor parlance, that stretch is known as the “post-earnings announcement drift,” or PEAD.
In a recent paper, Wharton finance professor Sean Myers and his co-authors tracked PEAD between 1999 and 2020 for all companies listed on the New York Stock Exchange, the American Stock Exchange, and Nasdaq. They found PEAD is a much bigger phenomenon than previously imagined, in two ways. One, it lasts for multiple years. Two, it matters for determining the level of stock prices, and not just short-term returns.
The paper, titled “The Cross-Section of Subjective Expectations: Understanding Prices and Anomalies,” was co-authored by Ricardo Delao, a professor of finance and business economics at the University of Southern California’s Marshall School of Business, and Xiao Han, a finance professor at the Bayes Business School in City, University London. The paper will be presented at the Frontiers in Quantitative Finance Conference on September 26.
Explaining Short-Term Price Fluctuations and Long-Term Levels
A key focus of the paper is to explore not just fluctuations in stock prices that affect returns over one or two quarters, but also to try to explain the long-term level of stock prices of individual firms, and consequently their market capitalization or valuation.
For instance, General Motors trades at about 9 times earnings, while Tesla commands a price-earnings ratio of 200. Despite the two companies having similar earnings, that factor of 20 difference in price-earnings ratios gives GM a market capitalization of $55 billion, while Tesla commands a valuation of more than $1 trillion. (All such observations have a caveat: They are “averages across many firms and averages across many earnings surprises,” Myers clarified.)
“That is a massive level difference,” Myers said. “Surprisingly, we find that this gradual adjustment to earnings surprises actually appears to explain a very large amount of this level difference in firm value.”
A Puzzling Disconnect in Valuation Levels
Myers described that “level difference” as a “puzzling disconnect,” where firms with very high valuations don’t seem to earn enough to justify those valuations. The paper’s authors offered two explanations for that disconnect.
One is that investors consciously price in their compensation for risk. That would explain the differences in discount rates and consequently the valuation levels for stocks that seem disconnected from their earnings. Investors perhaps perceive some stocks as safer than others, similar to bonds, and are therefore content with relatively lower returns, Myers said.
The other possibility is that investors do not apply a similar rigor in their price discovery or realize the disconnect it has from earnings. “That would mean the difference in valuation is driven by overly optimistic earnings forecasts for the expensive firms, and overly pessimistic forecasts for the undervalued firms,” Myers said. “If that’s the case, there’s a big price inefficiency occurring in the stock market.”
According to Myers, their findings are especially relevant now, with the enthusiasm over AI and its potential. “We’ve seen great enthusiasm outside of Nvidia. But most firms have not delivered high earnings based on AI,” he said. “People still have this idea that other companies like Microsoft or Apple will benefit substantially from AI down the road,” he said. “That may be true, but our results would say that on average, those beliefs are too optimistic and are likely to be disappointed. They’re probably in the right direction with AI as good news for these firms, but our results would show they likely have the wrong magnitude. They’re overstating how beneficial this would be for those firms.”
Modeling Subjective Expectations
A model used in the study found that price inefficiency was the strongest explanation for the earnings-firm valuation disconnect. But that explanation did not fully satisfy the paper’s authors.
The model solved that problem by noticing a strange “stubbornness” over time in investors’ beliefs about cash flows at firms. “So, if a stock is overpriced and investors expect very high cash flows for that firm, that bet will pay off on average, even if you disagree and want to bet against that firm,” Myers said. “But it will be fairly risky because investors are stubborn in their beliefs, and they won’t correct their beliefs over just the next one quarter or one year. You’ll likely need to wait five years or more before they really adjust their beliefs about these firms.”
But investing in that type of setting can be risky, according to Myers. “The puzzling thing about the stock market seems to be that when people are wrong, they don’t realize it,” he said. “There are firms that people think will take off and grow substantially. But after three, four, or five years of disappointment, people still hold on to those very optimistic beliefs and the stock price stays relatively high. It takes quite some time for the price to decline.” That stubbornness plays out the same way for firms that are underpriced, too, where pessimistic beliefs persist for long periods.
“This stubborn clinging-on to that optimism keeps the price elevated for quite some time,” Myers continued. “It gradually declines as this optimism lessens, but that is a much slower process than what an efficient market or a statistician would argue. On the flip side, we see the same thing for undervalued firms, where we have many instances where people expect some firms to go bankrupt in the next year, and then some certainly do. But a surprising number survives more than what people were forecasting.” Such optimism and pessimism were fairly symmetric across the study sample.
The study’s findings emphasize that “the mistakes in investors’ expectations are about magnitudes, not directions.” Here, magnitude refers to the difference in cash flow or earnings between firms. For instance, companies like Tesla grow their earnings more than those like GM do, Myers noted. He again clarified that those references are to averages across firms in the study sample, and not observations on specific companies.
“So, when people have high earnings expectations for Tesla and lower expectations for GM, that’s the correct direction,” Myers explained. “But quantitatively, people go too far. They are just way too optimistic about Tesla’s earnings and way too pessimistic about GM’s earnings. They have the right direction, but the magnitudes are off.”
Takeaways for Investors and Companies
There is no arbitrage opportunity in either of those two scenarios of overoptimism or excessive pessimism, Myers noted. “You are going to have to take a risky bet, and you will need to wait quite a long time for these beliefs to adjust.”
The study also revealed that the overoptimism for firms with high price-earnings ratios and consistent pessimism for firms with low price-earnings ratios is predictable multiple years out into the future.
Investors could spot opportunities in those scenarios. “If you have the patience, you can bet on firms that are substantially undervalued or substantially overvalued,” he said. “You just have to wait until this optimism or pessimism gradually fades.”
Institutional investors could have it even better than retail investors. “Our study highlights a massive opportunity for institutional investors that have a long investment horizon and the risk tolerance, because any bet can move against you when you hold for such long horizons.”
For companies, a big takeaway from the study is that they should not treat their stock prices as the be-all and end-all measure of their underlying fundamental value, Myers said. “If a firm is struggling to generate the earnings necessary to justify its price, it shouldn’t just assume that there’s a wisdom of the crowds, and that investors know the firm will do well in the future. They should seriously assess what they’re investing in and how they can increase their earnings to meet that valuation.”
That logic holds for the opposite side, too, where investors may overstate the risks a firm faces and predict that it will go bankrupt in the foreseeable future. “If you’re running a firm, you should feel confident that the market seems to be overly pessimistic about some firms and that you are likely to survive and persist longer than the market is forecasting,” Myers advised.
Why a Correction Doesn’t Occur Quickly
When a low-performing company has a good quarter or a high performer has a poor quarter, investors may dismiss it as a flash in the pan, or be in denial. They sometimes also make excuses to stick to their beliefs even in the face of evidence to the contrary.
For instance, if a company like Tesla has a dip in earnings, investors may blame an economic slowdown and argue that its car sales will increase when the economy improves, Myers said. “Or, they will say that the company will pivot to become an AI company or into robotics or self-driving cars, or there will be something about Grok (an AI chatbot from Elon Musk’s company xAI). People seem to hold on strongly to those beliefs, and that keeps the stock price from quickly correcting.”
“High price-earnings ratios are accounted for by both low expected returns and overly high expected earnings growth,” the paper noted. When some firms post earnings that do not justify high valuations, investors may be unfazed and stay loyal. They would perceive those stocks as safe and discount them at a lower interest rate, which will translate into a high price, Myers said.
“It’s all about the perceived risk,” Myers continued. “People will pay top dollar for some firms, because they find those firms to be safe — almost like Treasury bonds — or they’re just very optimistic about the future cash flows, or some mix of the two.”
One might expect better-informed investors, such as institutions, to have an advantage in a market where others are overoptimistic or overly pessimistic. But the stubbornness of expectations is a bigger force on stock price discovery since those are the beliefs held by most investors, Myers said. He recalled the adage that is often attributed to John Maynard Keynes: “The market can remain irrational longer than you can remain solvent.”
Sean Myers
Assistant Professor of Finance
