Research

Publications

1. Are There Too Few Publicly Listed Firms in the US?

   with Craig Doidge, George Andrew Karolyi, and René M. Stulz, Financial Review, 2025, 60, 317–329.

   Abstract:

   Doidge, Karolyi, and Stulz (2017) show that from 1999 to 2012, the US develops a listing gap relative to other countries, meaning that it has abnormally few publicly listed firms. In this paper, we update their evidence to 2023 and find that the listing gap increases, but at a low rate. By 2023, the US has about half as many listed firms per capita as other developed countries. We discuss some of the important questions raised by the existence and increase of the listing gap to which we hope researchers will find answers.

   
   
   Coverage: Harvard Law School Forum on Corporate Governance; Forbes; Congressional Research Service (CRS) Report, Library of Congress

Work in Progress

1. Artificial Intelligence, Opportunity, and Regulatory Uncertainty: Implications for Asset Pricing

   
   Presentations: 2026 AFA PhD Poster Session (scheduled); 2025 OSU Fisher AI in Business Conference; 2025 SFA (scheduled); 2025 Hetergeneous Agents in Asset Pricing; 2025 Finance Theory Group
   
   Abstract:

   This paper studies two channels—opportunity and regulatory uncertainty—through which Artificial Intelligence (AI) affects the stock prices and risk premia. On the one hand, advances in AI present firms with opportunities, leading them to exhibit characteristics of growth firms and earn lower expected returns. On the other hand, firms face increased regulatory uncertainty in AI development, increasing their political risk exposure and resulting in higher expected returns. Using conference call transcripts, I construct a firm-level measure of AI Exposure that captures the level of attention analysts and managers devote to AI-related topics at specific points in time. Empirically and theoretically, I show that these two channels exert opposing effects: firms focused on opportunity earn a negative AI risk premium, while those more affected by regulatory uncertainty earn a positive AI risk premium.

   
   

2. Physical Climate Risk, Asset Prices, and Labor Productivity

   
   Abstract:

   This paper introduces a Composite Exposure Index that quantifies firms’ physical climate risk exposure by drawing on a novel plant-level dataset and aggregating it to the firm level. With this index, I first show that physical climate risk is systematically priced in the cross-section of stock returns, evidencing a significant “Composite Premium” associated with physical climate risk in asset valuation. Second, I find that, for firms with high ex-ante exposure to physical climate risk, ex-post natural disasters negatively affect labor productivity and tangible assets, while positively affect intangible assets.

Book Chapters

1. Liquidity Management with Index Futures Contracts for Active Managers

   with Shaojun Zhang, in Derivatives Applications in Asset Management: From Theory to Practice. Springer Nature, 2025.