ABOUT
Finance PhD candidate
Schulich School of Business, York University
Email: aliahmdi@yorku.ca
RESEARCH INTERESTS
Corporate Finance, Corporate Governance and Law, Sustainable Finance, Labor and Finance, Artificial Intelligence
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REFERENCES
Ambrus Kecskés (supervisor), Full Professor, Schulich School of Business, York University, Canada
Roni Michaely (coauthor), Full Professor and Chair, University of Hong Kong Business School
Kee-Hong Bae (committee member), Full Professor and Chair, Schulich School of Business, York University, Canada
Phuong-Anh Nguyen (committee member), Associate Professor, School of Administrative Studies, York University, Canada
JOB MARKET PAPER
The Double-Edged Sword of Executive Personal Liability: Firm Value vs. Social Responsibility
Business for a Better World Dissertation Award, Colorado State University and RRBM (2025)
Best Paper Award Semifinalist, Financial Management Association Conference, 2025
Best Paper Award, Canadian Sustainable Finance Network Conference (2025)
Canadian Securities Institute Research Foundation (CSI-RF) PhD Scholarship (2024, two-time recipient)
Abstract: Executive personal liability for corporate social misconduct increases compliance but also reduces shareholder value. To causally demonstrate this tradeoff, I exploit a landmark court ruling that strengthened executives’ criminal liability for water and air pollution in the Ninth Circuit. I study U.S. public firms matched to their polluting plants nationwide in a difference-in-difference framework. After the ruling, firms with one standard deviation higher water and air pollution exposure to Ninth Circuit experienced an immediate 0.5% decline in equity value relative to control firms, while firms with higher ground pollution exposure did not. Toxic emissions released into water and air decreased by 8% in plants located in Ninth Circuit. Lack of any impact on ground emissions as well as a spatial regression discontinuity analysis support causality. The pollution reduction was achieved by reducing production volume, increasing abatement, and reallocating pollution to unaffected plants. These costly compliance responses reduced firm-level pollution but also reduced cash flows and increased their volatility. At the executive level, CEO compensation increased in affected firms.
Selected presentations: EFA Doctoral Tutorial (2025), NFA (2025), FMA (2025), SGF Conference (2026), RCF-ECGI Corporate Finance and Governance Conference (2025), CSFN Conference (2025), B4BW Symposium at Colorado State University (2025), CAFM (2025; schedule conflict)
WORKING PAPER
Does Corporate Production of AI Innovation Create Value?
With: Ambrus Kecskés, Roni Michaely, and Phuong-Anh Nguyen
Best Paper Award, Academy of Finance Conference (2025)
Best Paper Award, Eurasia Business and Economics Society Conference (2025)
Best Paper Award, Vietnam International Conference in Finance (2025)
Best Paper Award, Vietnam Symposium in Climate Transition (2025)
Best Paper Award, Finance Symposium (2024)
Abstract: Yes, by decreasing firm risk, not by increasing profitability, and with investors taking years to recognize the value created. We start, using novel AI patent data, by documenting significant corporate production of AI innovation as early as 1990. Then, we show that a signification motivation for a firm's AI production is the mutually reinforcing effects of the firm's innovation capacity (exogenous R&D stock) and its labor inputs' AI exposure (both the firm's own and its customers'). We use the interaction of these two effects to instrument for AI production. We find that producing AI creates firm value through a large, permanent decrease in risk (cash flow and stock return, systematic and idiosyncratic). Further evidence suggests that AI lowers physical capital intensity and increases bargaining power for producing firms. The initial market reaction to AI patent announcements is economically small, but abnormal stock returns thereafter are significantly positive (about 5% per year) for (only) roughly three years, suggesting initial undervaluation followed by gradual correction. We find no evidence of investor learning, except during the past five years. We empirically distinguish producing AI innovation versus AI adoption, automation, general technology, and other potential confounds.
Selected presentations: EFA (2024), CREDIT International Conference - GRETA (2024), CCA-ESCP Workshop on Financial Institutions and Corporate Finance (2025), FINEST Autumn Workshop (2025), FMA Consortium on Asset Management (2025), RBFC (2024)
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