Research

My research asks how financial contracts and market mechanisms shape information production, risk-taking, and real corporate decisions, and how capital structure and financial distress affect firms' operations, employment, and aggregate welfare. My recent work extends this agenda to automated market making, prediction markets, decentralized finance, and AI-driven financial markets.

Research statement (PDF)

Working papers

1. Prediction Markets as Data Marketplaces: The Price of Information under Automated Market Making

   With Zhan Pang

   We study prediction markets as data marketplaces in which trading produces valuable forecast data. An informed trader or a noise trader submits an order to an automated market maker using the logarithmic market scoring rule. A Bayesian arbitrageur observes the order but not trader type and corrects the price. Liquidity equals the informed trader's expected trading profit per unit of acquired information and the market maker's expected net payout per unit of information reflected in the final price. Because informed orders scale with liquidity while noise orders do not, liquidity affects how well the arbitrageur can distinguish the two types. Greater liquidity therefore need not deliver more information. We endogenize information acquisition and characterize optimal liquidity and market entry.

2. Rational Expectations Equilibrium with an Automated Market Maker

   With Zhan Pang

   We characterize the Grossman–Stiglitz rational expectations equilibrium with costly information acquisition in a prediction market operated by an automated market maker. The market maker executes all orders in a single batch under the logarithmic market scoring rule, and uninformed traders condition their beliefs on the execution price. In a sufficiently liquid market, greater liquidity makes the price more informative only by inducing more traders to acquire the signal: it damps price movements toward zero or one and thereby raises the signal's value. Noise trading shelters informed traders only up to a point: at any finite liquidity, the signal's value vanishes at both extremes of noise-trading volatility. The market maker's expected cash flow is positive in a shallow market and negative in a deep one.

3. Automated Market Making and Liquidity Provision in Prediction Markets (draft available upon request)

   With Zhan Pang

   2026 Wabash River Finance Conference

   We model an automated market maker's liquidity as the price of information. Under the logarithmic market scoring rule the market maker pays that liquidity, in expectation, for each unit of entropy a trader resolves. Bearing that subsidy and valuing the accuracy the trade delivers, the market maker prices as a monopsonist: a deeper liquidity buys more information but raises the bill on every unit, so it marks the liquidity down below the marginal value it places on accuracy. Under sequential arrival, free entry decides how much the market learns, and need not reward early arrival when the market opens where the information acquisition barely covers its cost through trading.

4. Put Credit Rating Agency's Money Where Its Mouth Is

   With Zhan Pang and Alexei Tchistyi

   Revise and Resubmit, Management Science

   2022 Finance Theory Group Spring Meeting; 2023 American Finance Association Annual Meeting; 2023 American Real Estate and Urban Economics Association International Conference, Cambridge

5. Rare Disaster Information Paradox

   With Peter DeMarzo and Alexei Tchistyi

   2022 American Finance Association Annual Meeting; 2022 SFS Cavalcade North America

6. A Model of Capital Structure Under Labor Market Search

   2018 SFS Cavalcade North America; 2018 Wabash River Finance Conference; 2019 Finance Theory Group Summer School; 2020 Midwest Finance Association Annual Meeting

7. Credit Risk in General Equilibrium: The Case of Equity-Maximizing Capital Structure

   With Tim Johnson and Chelsea Yu

   Previously titled: The Private and Social Value of Capital Structure Commitment

   2018 UBC Winter Finance Conference; 2018 SFS Cavalcade North America; 2018 Western Finance Association Annual Meeting; 2018 Northern Finance Association Annual Meeting

8. Executive Pay-for-Performance Sensitivity and Stochastic Volatility

   With Shuaiyu Chen and Yan Liu

   2022 SFS Cavalcade Asia

9. The Contract Year Phenomenon in the Corner Office: An Analysis of Firm Behavior During CEO Contract Renewals

   With Yuhai Xuan

   Minnesota Corporate Finance Conference; Drexel 8th Annual Academic Conference on Corporate Governance; 2015 Brigham Young University Red Rock Finance Conference; 2016 American Finance Association Annual Meeting

Publications, forthcoming and accepted papers

1. Corporate Resiliency and the Choice between Financial and Operational Hedging

   With Viral V. Acharya, Heitor Almeida, and Yakov Amihud

   Previously titled: Efficiency or Resiliency? Corporate Choice between Operational and Financial Hedging

   Forthcoming, Journal of Financial and Quantitative Analysis

2. How Does Health Insurance Affect Firm Employment and Performance? Evidence from Obamacare

   With Heitor Almeida, Yuhai Xuan, and Ruidi Huang

   Previously titled: The Impact of Obamacare on Firm Employment and Performance: Theory and Evidence

   Management Science 72, 6003–6024

3. The Client Is King: Do Mutual Fund Relationships Bias Analyst Recommendations?

   With Michael Firth, Chen Lin, and Yuhai Xuan

   Journal of Accounting Research 51, 165–200

4. Inside the Black Box: Bank Credit Allocation in China's Private Sector

   With Michael Firth, Chen Lin, and Sonia Wong

   Journal of Banking and Finance 33, 1144–1155