Publications

Extrapolation Bias and Robust Dynamic Liquidity Management with Alejandro Rivera  (Management Science 2021)

Working Papers

Knightian Uncertainty and Capital Structure: Theory and Evidence (R&R, the Review of Corporate Finance Studies)

Constrained Mutual Funds, Flow of Funds, and Asset Pricing Anomalies with Matthew Linn [updated draft coming soon]
Presented:  Maryland (BB)

Abstract: We explain the low-risk and momentum anomalies in stock returns, attributing them to the demand pressure from constrained mutual funds. Building on Black (1972), our model shows that leverage-constrained mutual funds optimally tilt their portfolios toward high-beta assets. When investors chase returns, market fluctuations result in large flows to mutual funds with high betas. The flows "passed through" by the fund exert significant demand pressure on high-beta stocks, reducing equilibrium expected returns. We empirically verify that this mechanism explains a substantial fraction of the betting-against-beta alpha. As high beta stocks are past winners (losers) in good (bad) times, our mechanism explains almost all the alpha associated with the momentum strategy.

Robust Security Design  with Uday Rajan  [under review]

Abstract:   We consider the optimal contract between an entrepreneur and investors in a moral hazard model when both parties have limited liability, are risk-neutral toward cash flow risk, and are ambiguity-averse. In the static setting, the first-best security is either convertible debt or levered equity. The optimal second-best security has an equity-like component in high cash flow states. Finally, if the two parties can renegotiate the contract after acquiring more information, the initial contract is risky debt. It is later renegotiated to a security with an equity component, and the conversion factor depends on the information acquired in the interim.

Competition and Lending standards with Multidimensional Private Information with William Mann 

Abstract We investigate how loan terms respond to competition between lenders when borrowers have multidimensional private information. In our model, competitive lenders screen borrowers using contracts with an interest rate and a collateral requirement. Compared to a monopolistic lender, a competitive market offers uniformly lower collateral requirements, and a larger share of funded projects is negative NPV. The competitive market may be more or less efficient than the monopolist, depending on the deadweight cost of collateral and the degree of selection externalities. In principle, efficiency could be greatly improved by an uninformed regulator who completely controls the interest rate schedule. However, simpler policies such as minimum collateral or higher interest rates do little to improve efficiency.

How Secure is Blockchain? with Ing-Haw Cheng
Presented:   Michigan  

Abstract:   I show that users' coordination can make the Blockchain insecure in equilibrium. Through the distributed trust property, the Blockchain system becomes more secure as more users participate in the system. However, it is costly but not impossible for an atomic attacker to sabotage the system (e.g., a “51%” attack). In the model, the rational users optimally transfer their wealth to the Blockchain to maximize expected gains but fail to internalize the likelihood of inviting the attacker even if they know the attacker’s strategy. The inefficiency increases with the presence of fanatics who underestimate the possibility of such attacks. I use global game techniques with users’ multidimensional private information to solve equilibrium strategies, a critical departure from standard global games.

Robust Dynamic Capital Structure 

Abstract:   I incorporate ambiguity-averse equity holders uncertain about the distribution of a firm’s assets into Leland's dynamic capital structure model (1994). My model shows the optimal default threshold increases with Knightian uncertainty, whereas it decreases with risk. When the effect of uncertainty dominates that of risk, a firm optimally defaults earlier than predicted by a traditional dynamic model with risk alone. My ambiguity-augmented model predicts substantially lower leverage ratios in comparison to the benchmark model of Leland (1994).

Work in Progress

Re-Imaging the Structure of Token Markets (with Andy Wu and Robert Dittmar at the University of Michigan)  (sponsored by Ripple) 

Abstract  Blockchain-based platforms and ecosystems are increasingly important in entrepreneurial finance, particularly in the form of initial coin offerings (ICO) and initial exchange offerings (IEO). However, technical limitations of public blockchains such as Ethereum have prevented these platforms from expanding beyond financing blockchain-centric startups. In three related projects, we theoretically and empirically examine the returns to these funding mechanisms and the incentives of speculators, token users, and exchanges in financing on and off the blockchain. We first document that the market-adjusted long-term returns to ICOs are predominantly negative and find higher returns in comparable IEO deals intermediated by crypto exchanges. We then develop a two-sided matching market model to capture the different roles of ICO and IEO speculators and predictive analytics that relate entrepreneurs’ financing decisions (traditional venture capital vs. blockchain-based financing; ICO vs. IEO) and funding returns to (1) project characteristics such as duration and activity intensity and (2) ratio between token users and token speculators. 

Robust Renegotiation Contract

Abstract  I characterize the optimal renegotiation contracts in which contracting parties mind model uncertainty. I extend Lee and Rajan's (2020) model to incorporate the case where the parties cannot observe the entrepreneur’s action in the interim stage. When the informed entrepreneur offers a renegotiation, the parties play a signaling game. On the other hand, when the uninformed investors move first, they offer a menu of contracts at the renegotiation.