Working Papers
Intervention with Screening in Panic-Based Runs (with Lin Shen) Conditionally Accepted at Journal of Finance
Presentations: WFA 2017, FIRS 2017, FTG Summer School 2017, Lisbon Meetings in Game Theory and Applications, Tsinghua Theory and Finance Workshop, Penn, INSEAD
Presentations: WFA 2017, FIRS 2017, FTG Summer School 2017, Lisbon Meetings in Game Theory and Applications, Tsinghua Theory and Finance Workshop, Penn, INSEAD
Abstract: Policymakers frequently use guarantees to reduce panic-based runs in the financial system. We analyze a binary-action coordination game under the global games framework and propose a novel intervention program that screens investors based on their heterogeneous beliefs about the system's stability. This program attracts only investors who are at the margin of running, and their participation boosts all investors' confidence in the financial system. Compared with government guarantee programs, our proposed program is as effective at reducing panic runs yet features two advantages: it costs less to implement and is robust to moral hazard.
Information Traps in Over-the-Counter Markets
Presentations: WFA 2019, SFS Cavalcade 2019, EFA 2020, FTG European Summer Meeting 2019, FTG Summer School 2019, Wharton, Penn (econ), INSEAD, Penn State (econ), Federal Reserve Bank of Philadelphia, McGill, Tsinghua University (PBCSF), Peking University (HSBC), SJTU (Antai).
Presentations: WFA 2019, SFS Cavalcade 2019, EFA 2020, FTG European Summer Meeting 2019, FTG Summer School 2019, Wharton, Penn (econ), INSEAD, Penn State (econ), Federal Reserve Bank of Philadelphia, McGill, Tsinghua University (PBCSF), Peking University (HSBC), SJTU (Antai).
Abstract: I analyze the interaction between information acquisition and market liquidity in over-the-counter markets with adverse selection. Buyers acquire information to avoid buying lemons when they expect low liquidity in the future. However, information acquisition generates a cream-skimming effect on the pool of assets and harms future liquidity. A liquid market can go through a self-fulfilling market freeze when buyers start to acquire information. More importantly, if information acquisition continues for an extended period, the market gets stuck in an information trap with low liquidity. This prediction helps explain the dynamics of liquidity in the US non-agency residential mortgage-backed security market.
Size Discount and Size Penalty: Trading Costs in Bond Markets (with Gabor Pinter and Chaojun Wang) R&R at Review of Financial Studies
Presentations: Stern Microstructure Conference 2021, INSEAD, EFA 2021, AFA 2022, Wharton
Presentations: Stern Microstructure Conference 2021, INSEAD, EFA 2021, AFA 2022, Wharton
Abstract: We show that larger trades incur lower trading costs in government bond markets (“size discount”), but costs increase in trade size after controlling for clients’ identities (“size penalty”). The size discount is driven by the cross-client variation of larger traders obtaining better prices, consistent with theories of trading with imperfect competition. The size penalty, driven by the within-client variation, is larger for corporate bonds, during major macroeconomic surprises and during COVID-19. These differences are larger among more sophisticated clients, consistent with information-based theories. The size penalty in US Treasuries is about three times as small as in UK gilts.
Information Chasing versus Adverse Selection (with Gabor Pinter and Chaojun Wang)
Presentations: Market Microstructure Exchange, University of Washington, Toulouse School of Economics, Wharton, INSEAD, Asia-Pacific Market Structure Webinar, Australasian Finance & Banking Conference, Finance Theory Webinar, World Symposium on Investment Research
Presentations: Market Microstructure Exchange, University of Washington, Toulouse School of Economics, Wharton, INSEAD, Asia-Pacific Market Structure Webinar, Australasian Finance & Banking Conference, Finance Theory Webinar, World Symposium on Investment Research
Abstract: Contrary to the prediction of the classic adverse selection theory, a more informed trader receives better pricing relative to a less informed trader in over-the-counter financial markets. Dealers aggressively chase informed orders to better position their future quotes and avoid winner's curse in subsequent trades. On a multi-dealer platform, dealers' incentive of information chasing exactly offsets their fear of adverse selection. In a more general setting of OTC trading, information chasing can dominate adverse selection when dealers face differentially informed speculators, while adverse selection always dominates when dealers face differentially informed trades from a given speculator. These two predictions---which contrast sharply with each other---both find strong empirical support in the UK government bond market.