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Jasper Pan, PhD

I am a tenure-track Assistant Professor of Finance at The College of New Jersey. My research asks how financial markets price technological disruption and how firms adapt to it. Current work examines the effects of generative AI on corporate credit spreads and corporate investment, alongside work on measuring diversification and risk in banking. I received my PhD in Finance from Rutgers University, an MA in Economics from Vanderbilt University, and a Bachelor of Arts and Science in Applied Mathematics and Economics from the University of California, Los Angeles.

Research Interests: Corporate Finance, Financial Intermediation and Banking, Artificial Intelligence

Email: panja@tcnj.edu

CV | SSRN | Google Scholar | LinkedIn

WORKING PAPERS

* presented by coauthor. † scheduled.

Equity Prices the Opportunity, Debt Prices the Risk: Generative AI and Corporate Credit Spreads

With P. Gandhi, J. Lu, A. Plazzi, and J. Wei. [SSRN]

Corporate bond spreads widen by roughly eight basis points per standard deviation of workforce exposure to generative AI after the release of ChatGPT, while equity valuations rise. A structural credit model with parameter uncertainty reconciles the opposing responses, which concentrate in credit-fragile firms.

Conference presentations: Wharton-Chicago-Harvard Insolvency and Restructuring Conference (2026)*†, Ohio State Fisher AI in Business Conference (2026)*†, ISB Summer Research Conference (2026)*†, Concordia University AI in Finance Conference (2026)*†, FMA Emerging Scholar Initiative (2026)†, SFA (2026)†, C.r.e.d.i.t. Conference (2026)*†, Eastern Finance Association Early Career Forum (2026), RCF-ECGI Corporate Finance and Governance Conference (2026)†.

Seminars: Rutgers Camden (2026), Drexel (2026)†, Fresno State (2026)†.

Do Measures of Bank Diversification “Measure Up”?

With P. Gandhi and D. Palia. [SSRN]

Standard measures of bank business line diversification do not capture the diversification effect. We propose a correlation-adjusted entropy measure, validate it against the Dodd-Frank and Economic Growth Acts, and find that diversified banks are more profitable and carry lower bankruptcy, tail, and systemic risk.

Conference presentations: FMA (2026)†, FDIC Bank Research Conference (2026)*†, MFA (2026)*, AFA Junior Faculty Mentoring Program (2026), Financial Engineering and Banking Society Conference (2026)*, SFA (2026)†, Eastern Finance Association (2025), Financial Markets and Liquidity Conference (2025)*, RCF-ECGI Corporate Finance and Governance Conference (2025), International Moscow Finance Conference (2025), Contemporary Issues in Financial Markets and Banking Conference (2025), Friends of Women in Finance Symposium (2025), Sydney Banking and Financial Stability Conference (2024)*, PBFEAM Conference (2024), AFA Committee on Racial Diversity Mentoring Program (2023).

Seminars: UNSW, Melbourne, Sydney, Monash, Rutgers, CEU, Victoria, AUT (all 2025, presented by coauthor).

Awaiting the Prompt? Generative AI Uncertainty and Firm-Level Investment

With P. Gandhi, S. Kedia, J. Lu, and J. Wei. [SSRN]

Firms with greater workforce exposure to generative AI cut investment after the release of ChatGPT, by 0.57 percentage points of lagged assets per standard deviation of exposure. The decline concentrates in physical capital and is smaller where assets are redeployable, consistent with a real-options mechanism: uncertainty raises the value of waiting under irreversibility.

Conference presentations: FMA (2026)*†, SFA (2026)†.

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