Path Dependence in Finance Education: Why Curriculum Change Lags Behind Market Innovation

One of the first lessons taught in university economics and business programs is path dependence—the idea that previous decisions can limit current choices, even when superior alternatives become available. While this principle is commonly explained with other phenomena—e.g., the QWERTY keyboard persistence and fossil fuel dominance— it is equally valid in finance education and academic research contexts.

At business schools around the world, especially ones that train students for careers in investment banking, asset management, or corporate finance, both coursework and faculty research are still dominated by historical precedent. The design of finance programs, the finance research topics prioritized in academic journals, and even the kind of writing assignments students receive are influenced by what already came before—not necessarily what the finance industry is in the process of becoming.

Historical Anchors: What Business Schools Are Built On

Core models such as the Capital Asset Pricing Model (CAPM), Modern Portfolio Theory, and Efficient Market Hypothesis (EMH) have taught finance for decades. They are elegant, powerful, mathematical, and foundational frameworks—and most finance faculty built careers around them. As a consequence, undergraduate and MBA programs continue to be grounded in these theories, despite ample evidence that real markets don’t act as efficiently or rationally as previously thought.

A 2023 analysis conducted by the Financial Times of 50 highly ranked MBA programs found that while more than 70% still require courses focused on traditional portfolio theory, fewer than 25% require any exposure to behavioral finance, fintech or crypto markets—all of which represent fast-growing parts of the financial services industry.

This gap between what academics pay attention to and the trajectory of industry development serves as an illustration of how path dependence limits curricular reform. The direction in which your organization should go is costly to change due to faculty expertise, existing course materials, and institutional identity, even when beckons.

The Cost of Change in Business Education

Why are business schools not pivoting faster?

The answer is institutional constraints. Tenured professors might be specialists in interest rate modelling or capital budgeting, yet find themselves out of their depth trying to teach decentralized finance or algorithmic trading. Updating textbooks, redesigning syllabi, and re-aligning entire programs takes time and money. They also have to deal with potential internal resistance from faculty who may see no added value in newer topics—or who fear that short-term trends will pass.

Path dependence tells us that schools won’t move away from the infrastructure they’ve built: databases, case studies, alumni networks and employer relationships all point to a specific version of finance that’s embedded in history.

But markets don’t just sit still. Blockchain, machine learning in trading, ESG investing, and behavioral finance: all of these innovations are now integral to many financial firms. However, they’re still considered electives, not essentials, at many leading business schools.

A Real-World Example: Behavioral Finance vs. Classical Models

Think about behavioral finance—a discipline that introduces a factor of psychology to investment decision-making. Although its importance has been validated by Nobel Prizes (e.g., Richard Thaler in 2017), the topic continues to be an optional seminar in many business programs rather than a must-have requirement.

Yet, according to a 2022 report from JPMorgan, more than 60% of institutional asset managers currently use behavioral insights in their decision-making processes. The industry has certainly moved on—but business education has yet to catch up.

Implications for Students and Institutions

A background in only the classics is just not going to cut it if students want to excel in modern finance. They must be conversant in a range of subjects, including digital assets, financial data science, and behavioral bias. But because of path dependence, many of them are still graduating without this essential toolkit.

Even research done by faculty is biased. A quick perusal of the Journal of Finance or the Review of Financial Studies suggests that traditional asset pricing frameworks still dominate, even as the likes of BlackRock and Fidelity have made ESG and AI-driven strategies their top research priorities.

Conclusion

Path dependence helps explain why finance education often trails financial innovation. Faculty, curricula and institutions are bound by yesterday’s decisions and investments. For students, this means that looking for progressive electives or independent projects is key. For schools, it means realizing that yesterday’s models, while good, shouldn’t hinder tomorrow’s learning.

And for those of you drafting finance research topics, or planning future syllabi, the lesson is clear: do not let the past be the reason for what you teach.