Faculty Research: Applying Cutting-edge Asset Pricing Research to Central Banks and Classrooms

When the Bank of England adopted a new tool to monitor financial market risk earlier this year, its foundation came not from a government agency or a think tank, but from the research of Isenberg Finance Professor Fousseni Chabi-Yo, PhD.

A specialist in asset pricing and empirical financial econometrics, Chabi-Yo developed a novel, forward-looking measure of the equity risk premium (ERP) that now plays an active role in how the bank assesses financial stability.

“It was a very welcome surprise,” says Chabi-Yo, who serves as chair of the Finance Department and holds the Berthiaume Endowed Professorship at the Isenberg School of Management. “Translating academic work into something usable by a central bank required clarity, robustness, and real-time applicability features. A key challenge was ensuring the measure remained interpretable and responsive across varying market conditions, especially during high-volatility episodes, which often distort standard models.

“The fact that our approach met these demands speaks to its practical value as well as its theoretical soundness,” added Chabi-Yo, who once worked for the Bank of Canada.

A New Approach to Estimating the Elusive ERP

The equity risk premium—the extra return investors expect for holding stocks over risk-free assets—is “notoriously difficult to estimate,” according to Chabi-Yo, despite its importance to monetary policy, forecasting, and investment decisions. Inspired by earlier work that derived a lower bound on expected returns using option prices, Chabi-Yo and co-author Jonathan Loudis (of the University of Notre Dame) extended that idea to develop a robust framework that doesn’t rely on strict assumptions about investor preferences. Their model offers both upper and lower bounds on expected returns, using only current market data.

“Our measure consistently outperforms existing models in predicting future returns,” Chabi-Yo said. “That’s likely why it gained traction with practitioners and policymakers, like at the Bank of England.”

Building on his ERP work, Chabi-Yo recently published an intertemporal risk factor model in Management Science, expanding the understanding of how equity risk evolves over time. The framework aligns with the Intertemporal Capital Asset Pricing Model (ICAPM) and offers valuable insights into risk pricing and investor behavior.

“Current models often fail to identify the specific risks that investors care about,” he says. “To address this gap, we developed a model that captures both contemporaneous market risk and intertemporal risk, which arises from changes in long-term expected returns and return volatility.”

In an August 2025 study titled “Option-Implied Premia with Intertemporal Hedging,” Chabi-Yo and co-authors Elise Gourier (ESSEC Paris) and Hugues Langlois developed a new way to measure the risk premium investors demand for holding stocks. Their approach improves on existing models by factoring in how investors adjust their strategies over time, and it can be calculated in real time. The research shows that during calm markets, investors tend to plan for the long term—making intertemporal hedging a bigger driver of returns—while in volatile periods, they shorten their horizons. This new measure can serve as an early warning system, helping investors and policymakers prepare for downturns before they happen.

Chabi-Yo points out that his new research extends the Bank of England’s ERP measure.

“Our findings suggest that intertemporal risk is especially relevant during calm market periods, when investors are more sensitive to subtle shifts in long-term economic conditions. This extension enhances the toolkit’s ability to reflect forward-looking risks, thereby offering a more comprehensive understanding of equity risk over time.”

Bridging Finance and AI: Theory Meets Real-World Application

Chabi-Yo sees the future of finance at the intersection of asset pricing, machine learning, and real-time risk monitoring.

“AI-driven models offer new ways to process high-dimensional data, uncover non-linear pricing relationships, and detect early signs of systemic risk,” he says. “While AI holds great promise, however, integrating it meaningfully into asset pricing requires grounding in economic theory and careful attention to interpretability, robustness, and regulatory compliance.”

His research aims to bridge the gap between economic theory and practice by economically motivated models that enhance forecasting and dynamic model updating.

“I plan to engage financial institutions and/or central banks to incorporate some of my measures into real-world applications,” he says.

Chabi-Yo brings this perspective into his Isenberg undergraduate- and graduate-level courses.

“This prepares students to critically assess new methods and become thoughtful practitioners in a rapidly evolving financial landscape,” he said.