Wharton Study Finds Investors Systematically Misjudge Correlated Information, Distorting Asset Prices

Wharton Study Finds Investors Systematically Misjudge Correlated Information, Distorting Asset Prices

A new academic paper from Wharton finance professor Jessica Wachter identifies a behavioral blind spot that may explain persistent anomalies in how markets price risk—and it's a problem that affects sophisticated investors as much as retail traders.

The research, titled "Correlation Neglect in Asset Prices" and co-authored with Hongye Guo, documents what the researchers call a "striking pattern" in U.S. stock market returns: investors consistently treat pieces of information as independent when they're actually correlated, leading to systematic mispricings. For CFOs navigating capital allocation decisions and treasury management, the finding suggests that market signals may be less reliable than traditional finance theory assumes.

The phenomenon, which Wharton has labeled "correlation neglect," represents a departure from the efficient market hypothesis that has dominated finance for decades. That theory assumes investors process information rationally and incorporate it into prices appropriately. But Wachter's research suggests a more fundamental problem: it's not that investors lack information, but that they're processing it incorrectly at a cognitive level.

Here's the practical issue: when multiple data points are actually related—say, rising interest rates and slowing consumer spending—investors often analyze them as separate, unrelated signals rather than recognizing their connection. This creates predictable distortions in how assets get priced, particularly during periods when multiple correlated factors are moving simultaneously.

The research examined patterns in U.S. stock market returns tied to quarterly data, though the paper's authors note the implications extend beyond equities. For finance leaders, the finding raises uncomfortable questions about everything from hedging strategies to valuation models. If the market systematically misreads correlated information, then the "market price" may be less informative than standard corporate finance textbooks suggest.

What makes correlation neglect particularly insidious is its universality. Unlike other behavioral biases that affect primarily retail investors or specific market segments, this one appears to be baked into how humans process information. Wachter's work suggests that even professional investors—the ones CFOs rely on for accurate price discovery—fall prey to the same cognitive pattern.

The timing of the research is notable. As of early 2026, finance teams are grappling with an unusually complex information environment: AI-driven productivity claims, shifting monetary policy, geopolitical instability, and regulatory changes are all moving at once. If investors are indeed treating these correlated factors as independent variables, the resulting price signals may be particularly unreliable right now.

For corporate finance teams, the implications are concrete. When evaluating whether to raise capital, the "market price" of your equity may reflect correlation neglect rather than fundamental value. When stress-testing scenarios, the assumption that markets efficiently incorporate all available information may need revisiting. And when boards ask why the stock price moved, "the market is processing correlated information as if it's independent" is now a legitimate—if unsatisfying—answer.

The research doesn't offer easy solutions. You can't simply "correct" for correlation neglect the way you might adjust for a known accounting distortion. But awareness matters. Finance leaders who understand that markets systematically misread correlated information can at least avoid over-indexing on price signals during periods of high correlation—which is to say, during exactly the moments when you most want reliable market feedback.

The broader question is whether this is a feature or a bug. Traditional finance assumes rational processing leads to efficient prices. Behavioral finance has spent decades documenting the ways humans deviate from that ideal. Wachter's work suggests the deviation may be more fundamental than previously thought—not a failure of discipline or information, but a basic limitation in how we process multiple related inputs.