EDUCATION         

• Ph.D. in economics, Princeton University, 2014

RESEARCH AREAS

• Financial intermediation (banking, mutual funds)

• Fixed-income markets

• Monetary policy transmission

WORKING PAPERS

1. [New] Investor Fragility, Bargaining Power, and Pricing Implications for Short-Term Funding Markets (with Sean Tibay and Ashley Wang), updated in October 2025

• Summary: Flow-induced funding shocks from open-end funds affect pricing in the highly frictional short-term funding markets, and relative bargaining power plays a critical role in shaping such pricing dynamics. 

• Conferences: 2025 WFA, 2025 FIRS, 2025 CICF

2. Investor Flows, Monetary Policy, and Portfolio Management of Money Market Funds (with Jay Im and Ashley Wang), updated in March 2025

• Summary: How do money market funds (MMFs) manage their portfolios in response to monetary policy changes? We find that anticipation of rate cuts and lower policy uncertainty prompt more risk-taking and liquidity-reduction behaviors among MMFs.

• Conferences: 2024 China International Conference in Finance (CICF), 2024 EFA in Bratislava

3. Payment Risk and Bank Lending (with Ye Li), updated in November 2025

• Summary: Using confidential Fedwire data, we measure banks’ exposure to liquidity risk from depositor-initiated payment transfers and show that banks facing greater payment risk extend fewer loans. After the GFC, despite high reserve balances, this negative effect intensified and became increasingly sensitive to aggregate liquidity conditions and regulatory constraints.   

• Conferences: 2022 Adam Smith Workshop, 2022 OCC Research Symposium on Systemic Risk and Stress Testing in Banking, 2022 Northeastern University Finance Conference, 2022 SFS Cavalcade, 2022 Barcelona School of Economics Summer Forum, 2026 AEA

4. The Network Structure of Money Multiplier (with Ye Li and Huijun Sun), updated in April 2024

• Summary: We develop a model of bank lending and payment system where the “money multiplier”—the ratio of loans financed by deposits to banks’ liquid assets that buffer potential deposit outflows—depends on the network topology of interbank payment flows. We estimate the model using Fedwire payment data and identify banks that have a large impact on the equilibrium multiplier due to their systemic importance in the payment network.

• Conferences: 2022 Advances in Macro-Finance Tepper-LAEF Conference, 2022 European Banking Center Network Conference at Tilburg, 2022 EFA in Barcelona, 2022 CESifo Conference on Money, Macro, and International Finance, 2022 European Banking Center Network Conference, 2023 Bank of Canada Conference on Networks in Modern Financial & Payments Systems, 2023 Financial Intermediation Research Society (FIRS) Conference, 2024 AFA

PUBLICATION

1.  Carbon Emissions, Mutual Fund Trading, and the Liquidity of Corporate Bonds (with Jie Cao, Xintong Zhan, Weiming Zhang, and Linyu Zhou), Management Science, forthcoming

• Summary: Investor flows of bond mutual funds negatively respond to funds’ carbon exposure. Such carbon-induced redemption (rather than a fundamental shift in funds’ investment preferences) prompts funds to sell bonds issued by high-carbon companies. Consistently, high-carbon bonds experience deteriorated liquidity, particularly those heavily owned by mutual funds.

2. Mutual Fund Fragility, Dealer Liquidity Provisions, and the Pricing of Municipal Bonds  (with Maureen O’Hara and Xing (Alex) Zhou), Management Science 70-7 (2024): 4802-4823.

• Summary: Could mutual fund fire sales during a major crisis reshape market perceptions and generate lasting effects on asset pricing and dealers' liquidity provision? In the aftermath of the COVID-19 crisis, the pricing of mutual-fund-held municipal bonds reflects a post-crisis "fire sale premium."

• 2021 WFA Best Paper Award on Investment Management

3. Does Mutual Fund Illiquidity Introduce Fragility into Asset Prices? Evidence from the Corporate Bond Market  (with Hao Jiang, Zheng Sun, and Ashley Wang), Journal of Financial Economics, 143.1 (2022): 277-302.

• Summary: Does liquidity transformation by mutual funds introduce fragility to the underlying market? We create novel bond-level latent fragility measures based on asset illiquidity levels of the bond's mutual funds holders. Bonds with higher such fragility measures experience more volatile returns and outflow-induced selling.

• Download our bond-level fragility measures: SAS format, STATA format. Click here for data description. 

4. Liquidity Restrictions, Runs, and Central Bank Interventions: Evidence from Money Market Funds  (with Lei Li, Marco Macchiavelli, and Xing (Alex) Zhou), Review of Financial Studies, 34.11 (2021): 5402-5437. 

• • Summary: Redemption restrictions on investors, like gates and fees introduced in the 2016 money market fund (MMF) reform, are meant to improve financial stability. However, we find that when such restrictions are contingent on MMF's liquidity level (WLA), it exacerbates the run on MMFs during the COVID-19 crisis.

  • Media: VoxEU, Crane Data, Financial Times [1], Financial Times [2], Money and Banking Blog

  • This paper is cited by the SEC in their Proposed Amendments on Money Market Fund Rules (Dec 2021) to support the proposal of decoupling gates/fees from WLA.

5. Reciprocal Lending Relationships in Shadow Banking, Journal of Financial Economics, 141.2 (2021): 600-619.

• Summary: Post-crisis regulations apply stricter liquidity rules to both money market funds (MMFs) and banks, requiring MMFs to do more overnight lending and banks to borrow longer-term. MMFs and banks resolve this liquidity dilemma by developing a reciprocal “bundling” strategy across various markets. 

6. Institutional Herding and Its Price Impact: Evidence from the Corporate Bond Market  (with Fang Cai, Song Han and Dan Li), Journal of Financial Economics, 131.1 (2019): 139-167.

• • Summary: The level of institutional herding (by insurers, mutual funds, and pension funds) in corporate bonds is substantially higher than what is documented for equities, and sell herding is much stronger than buy herding. In addition, sell herding leads to large price distortions: a return reversal of about 4% in the subsequent 1.5 years. [Additional Appendix]

  • Media: ETF.com