Leifu Zhang

PhD Candidate in Finance
Olin Business School
Washington University in St. Louis
leifu.zhang@wustl.edu
Curriculum Vitae

I am a financial economist interested in FinTech and macro-finance (specifically, financial crisis and banking). I am also interested in applying state-of-the-art ML/AI algorithms to economics and finance. Before coming to the US, I studied at the Chinese University of Hong Kong (MPhil) and Peking University (Bachelor's degrees).

References
Brett Green (Principal): b.green@wustl.edu
Jason Roderick Donaldson: j.r.donaldson@wustl.edu
Ohad Kadan: kadan@wustl.edu

Research

Selling Bubbles (Job Market Paper)
A secondary market joint with belief heterogeneity generates overpricing, encouraging entrepreneurs to reveal less information and sell bubbles. The model explains several features of the ICO market.

How does an entrepreneur raise capital from investors with heterogeneous priors? When a secondary market exists, a price bubble arises and provides an incentive for the entrepreneur to manipulate investors’ beliefs through strategic communication. Under mild conditions, the amount of information disclosed decreases in disagreement. Without a secondary market, the price bubble vanishes, and the entrepreneur discloses more information. I discuss applications to emerging capital-raising methods, in particular initial coin offerings, and the regulatory implications for policymakers. [Link to the Paper]

Mutual Fund Portfolio Constraints: Carrying Coals to Newcastle? (with H. Liu)
Investors impose portfolio constraints to curb fund managers' excessive risk-taking. These constraints do not appear binding because they transform local optimums to become constrained global optimums.

Investors often impose short sale and no-leverage constraints on many mutual funds. However, we rarely observe these constraints bind in the portfolios of these funds. Are investors carrying coals to Newcastle? In a principal-agent framework in which the risk-averse agent (manager) is protected by limited liability, we find that such constraints are necessary to curb the manager’s excessive risk-taking due to limited liability. These constraints do not appear binding because there is an interior portfolio weight (between 0 and 1) that is locally optimal, and the constraints transform it to become a constrained global optimum. Moreover, this “non-binding puzzle” is exclusive for the “low-ability” manager, which suggests a new investment skill indicator. [Link to the Paper]

Not Enough or Too Much? On Transparency in the Financial System
A regulator without commitment power leads to excess transparency. The robust transparency policy is “do not play tricks,” and commitment power is not needed.

In general, a regulator’s commitment power is necessary for implementing the optimal transparency policy in the financial system. The literature points out that lack of commitment power leads to excess opacity. Instead, I show an equilibrium featuring excess transparency always exists, and survives standard refinements under mild conditions. Besides, the optimal transparency policy and whether the regulator needs commitment power to achieve it is sensitive to the exogenous information structure, suggesting we should consider ambiguity aversion/robustness. Perhaps surprisingly, under such preference, the optimal transparency policy is “do not play tricks,” and commitment power is not needed. [New Draft Coming Soon][An Old Draft with Fewer Results Available Upon Request]

Robust Stress Test Design with Optimal Information Acquisition (Work in Progress)
I study robust information design with optimal information acquisition in a generic coordination game. One application is that investors’ optimal information acquisition restores the optimality of a “pass/fail” test with one cutoff.

I study the optimal design of stress tests with adversarial coordination and optimal information acquisition. Investors may acquire additional information after observing the test result disclosed by the regulator. Information acquisition is “optimal” in the sense that investors have the “flexibility” to choose what information to acquire optimally. In contrast to the literature without optimal information acquisition, which usually obtains complicated optimal tests, I show a “pass/fail” test with one cutoff is optimal.