Forecasting | Peer-Reviewed Research

Why Managers Keep Misreading the Future

New research reveals how overreliance on past earnings skews corporate forecasts — and what can be done about it.

Based on research from Yuhang Xing, Dayong Huang (North Carolina – Greensboro), Lijun Lei (North Carolina – Greensboro) and Mengmeng Wang (North Carolina – Greensboro)

Key findings:

Managers often overestimate the relevance of past earnings when making future forecasts, especially after strong or volatile financial quarters.
This bias persists even among highly competent executives and can negatively affect investment, hiring and valuation decisions.
Management teams with diverse job experiences and values are significantly better at avoiding these forecasting errors.

“Past performance is not a guarantee of future results.”

It’s a familiar disclaimer in the world of finance — but one that corporate managers often fail to follow themselves.

When issuing earnings guidance, executives frequently assume that recent trends will continue, even when there’s little reason to believe they will. This tendency to overemphasize past earnings can lead to misguided forecasts, misaligned investment decisions and market volatility.

The problem of “managerial overextrapolation” is well known in behavioral finance scholarship, but it’s a difficult one to study. Unlike analysts or investors, corporate managers have both strong incentives to be accurate and access to superior internal data — yet their beliefs and biases are harder to isolate due to strategic forecasting and other confounding factors.

To tackle this problem, a recent study co-authored by Yuhang Xing, associate professor of finance at Rice Business, analyzes more than 21,000 earnings per share (EPS) forecasts from 2001 to 2018. The results show a clear pattern: when companies post strong or volatile earnings, management is more likely to assume that performance will continue in the same direction — even when the data doesn’t support that assumption.

“Managers want to be accurate, but they’re still human,” says Xing. “They often treat recent earnings as a roadmap to the future, even when that’s a shaky assumption.”

The Problem of “Overextrapolation”

The tendency to overextrapolate future earnings based on past performance is rooted in a cognitive bias known as the representativeness heuristic. The concept explains how people judge probability based on how much a new situation resembles a known one — often at the expense of more objective analysis.

In the context of earnings forecasting, this means managers might see a few strong quarters and conclude the company is on a sustained growth trajectory, even if market or operational fundamentals suggest otherwise.

Xing’s study, forthcoming in Management Science, shows that overextrapolation intensifies when recent earnings are especially attention-grabbing. For example, if a company posts several consecutive gains or suffers a sharp loss, managers interpret these data points as meaningful signals rather than what they often are: statistical noise.

To confirm causality, the research team examined the 2017 Tax Cuts and Jobs Act, which imposed a one-time tax hit on some firms. Despite the temporary nature of the event, affected companies issued pessimistic forecasts afterward — evidence that even when earnings distortions are clearly one-off events, they still influence managerial expectations.

“Managers want to be accurate, but they’re still human,” says Xing. “They often treat recent earnings as a roadmap to the future, even when that’s a shaky assumption.”

What Makes a Team More Accurate?

If even a known, one-time shock like the tax reform can distort forecasts, what can help managers avoid this bias? Xing and her coauthors explored whether certain individual traits or team dynamics might make a difference.

For example, they tested whether executive ability might protect against the representativeness bias. Using proxies like outside board appointments and professional certifications, they found no meaningful difference. Even highly competent leaders overextrapolated.

Likewise, demographic diversity (e.g., gender or nationality) showed no consistent change.

But what did make a difference was diversity in management experience and values. Having a variety of relevant perspectives appeared to challenge groupthink and strengthen information processing — leading to more accurate guidance. Management teams with a broader mix of job experience, industry backgrounds and political viewpoints were less likely to overextrapolate.

“Teams with a range of experiences and viewpoints made better predictions,” says Xing. “It’s not just who’s on the team — it’s how differently they think.”

Why Overextrapolation Matters for Investors

Forecasts don’t just affect internal planning. Investors rely on earnings guidance to shape expectations, and in turn, those expectations help determine stock prices. When managers oversell future earnings based on past performance, the company may face a steeper price drop when reality doesn’t match the hype.

On the flip side, an overly conservative forecast might cause a firm to miss out on timely investments or lose ground to competitors. “Companies make decisions based on their assumptions about the future,” Xing notes. “If those assumptions are wrong, the consequences can be significant.”

In fact, the study found that stocks of firms with high expected earnings underperformed those with low expectations by 0.5% per month. That gap suggests that inflated expectations — even when based on a plausible narrative — can set companies up for a fall.

Ultimately, the findings challenge the notion that managers always behave rationally. Even with access to superior internal data, executives often misread what those numbers mean for the future. For board members, institutional investors and regulators, the research offers a subtle but critical insight: Better forecasts may depend less on individual brilliance and more on the structure of the team doing the forecasting.