Photo by my wife Yang Yi in 2025
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Xuyuanda Qi
Xuyuanda Qi
Email: xq622@nyu.edu
Cells: +86-157 2138 3500 (China)
I am an Assistant Professor of Finance at NYU Shanghai. My research interests lie primarily in theoretical corporate finance, venture capital contracts, financial innovation and mechanism design.
Working Papers
with Kostas Koufopoulos and Giulio Trigilia
Presented at FTG 2025, WFA 2025, SAET 2025
Abstract: In this paper, we demonstrate that demandable debt provides an effective solution to the leverage ratchet effect without requiring any additional information beyond that assumed in the existing literature. Demandable debt-holders have an option to request full repayment of debt at any time. If the firm's leverage exceeds its target debt ratio, debt-holders will exercise their option and sell this excess debt back to the firm. This mechanism efficiently disciplines the firm to maintain the target debt ratio, except under extreme negative shocks leading to inevitable bankruptcy. Furthermore, we show that as the model's time intervals shorten, the firm can asymptotically achieve the full tax shield benefits without incurring any bankruptcy risk.
with Kostas Koufopoulos and Giulio Trigilia
Abstract: In a classical durable-good monopoly environment, we construct mechanisms that implement static monopoly profits while being renegotiation proof. We derive two main results. First, if collective bargaining can be ruled out, then a long-term contract can generate a coordination failure which prevents renegotiation and fully restores monopoly power. Second, with arbitrary renegotiation, a long-term (smart) contract can introduce an asymmetry of information between sellers and potential buyers, which prevents the monopolist from reselling at lower prices. The smart contract approximately achieves static monopoly profits. When the low-valuation customer values the good close to its marginal cost and the discount rate is close to one, the static monopoly allocation can be uniquely implemented, closing the discontinuity between the 'gap' and the 'no-gap' cases.
Cursed with Knowledge? Strategic Risks of AI-Powered Monitoring
with Yang Yi
Major Revision at Management Science
This paper was previously circulated under the title "Optimal AI Adoption in Investment Monitoring."
Abstract: Why are some financial institutions slow to adopt artificial intelligence (AI) despite its decreasing costs, while others are quick to embrace it? This paper develops a theoretical framework to understand the tradeoff between using AI for better borrower evaluation and maintaining strict financial discipline. Although AI improves the ability to assess borrower quality during refinancing, it can also encourage financiers to refinance initially speculative borrowers, thus exacerbating adverse selection in initial lending. To avoid these risks, some institutions may optimally choose not to adopt AI. Our model predicts that lower AI costs drive adoption only when this adverse selection is not severe. Moreover, AI adoption is most beneficial for institutions with a moderate-quality lending pool. These results help explain the strategic dynamics of AI adoption in lending and investment monitoring.
with Chen Chen
Major Revision at Operations Research
Abstract: We study an information design problem in which a school advisor strategically discloses information to promote her student in a job market with n potential employers. The advisor can send different signals to different employers (i.e., private persuasion) or broadcast the same signal to all employers (i.e., public persuasion). After receiving the signals, the employers can communicate with each other to reduce uncertainty about the candidate in their self-interest. We demonstrate that as long as the candidate can accept at most one offer and has a known preference among the employers, public persuasion is optimal, regardless of how employers communicate. The optimal public persuasion can be derived from a first-best relaxation problem that only imposes the employers' participation constraints. We then focus on a specific case in which the candidate's characteristics can be summarized as a one-dimensional variable, and all of the receivers' utility functions are linear in this variable. We derive the optimal mechanism in a closed form for the two-receiver case. In the general case, a convex optimization problem with n decision variables and constraints can be efficiently solved to obtain an optimal mechanism. We provide structural properties and a better understanding of the optimal mechanism from a dual viewpoint.
with Bowen Lou, Jiding Zhang, Chen Jin and Liangfei Qiu
(Full paper available upon request)
Abstract: This study examines the market forces driving Bitcoin’s interconnected exchange and mining markets, developing a systematic framework that captures the interplay between exchange rate, liquidity, and mining activities. We model how fluctuations in the Bitcoin exchange market affect the entry and exit dynamics of the mining market, characterized by the supply and demand of mining rigs. Empirically, leveraging a unique dataset of the purchase and listing of mining rigs from a leading e-commerce platform, we find that the effects of the exchange market conditions are pronounced for investors, as potential entrants to the Bitcoin mining market. They have a significant impact on the demand for mining rigs. Bitcoin investors tend to associate a higher valuation of Bitcoin with a higher Bitcoin exchange rate and consider the liquidity of the market when making mining decisions. In addition, our empirical results indicate that the electricity consumption of mining Bitcoin moderates the effects, shaping the responsiveness of mining rig demand to the exchange market conditions. To further contextualize these findings, we develop a game-theoretic model that uncovers the micro-foundations of investor decision-making and the role of certain types of miners in market stabilization. Overall, this study elucidates the economic implications of Bitcoin exchanges on Bitcoin mining activities, which contribute to the operational performance of the Bitcoin system. It enriches our understanding of how investor activities are affected and coordinated within IT-enabled markets, while illuminating the information transmission and underlying connection among them.
Optimal Staging of Early Startups
Abstract: When early startups stage the financing of their capital investments, they are at risk of being severely diluted by venture capitalists later on. It is puzzling that early startups do so in a competitive financial market. This paper shows that staging is beneficial to an early startup with a small upside return and a high capital intensity of early development. In this case, absent staging, the entrepreneur gets a small number of shares, which provides him with weak incentives to increase the startup's value. If the financing is staged, reevaluation of the startup during the follow-on round incorporates all the nonverifiable information about interim performance. Staging provides additional incentives since the entrepreneur gets more shares when interim performance is better. Between round financing and tranched financing, the two most prevalent forms of staging, round financing generates stronger incentives for the entrepreneur, but a lower payoff to the venture capitalist, than tranched financing. As a result, with a smaller upside return and a higher capital intensity of early development, the venture capitalist is less likely to participate in round financing, and tranched financing is more likely to be used to ensure his participation. All the above results are robust in a mechanism design framework.
This figure shows how the choice of financing form depends on two empirically important parameters. The X-axis is the capital intensity of early development, and the Y-axis is the upside return of the startup. Staging is not beneficial in two cases. 1. When the upside return is huge, staging is generally detrimental, and no staging is chosen. 2. When the upside return is minimal and the capital intensity of early development is high, the startup cannot attract any financing, and staging is trivially not helpful. Otherwise, staging is feasible and beneficial. Between two prevalent forms of staging, tranched financing is more likely to be chosen with small upside return and high capital intensity of early development; round financing is more likely to be chosen otherwise.
When do incomplete contracts matter?
with Aristotelis Boukouras, Kostas Koufopoulos and Giulio Trigilia
Abstract: This paper derives conditions under which the introduction of a third-party agent solves the renegotiation-proofness problem of Moore and Repullo (1988)-type mechanisms, without introducing the potential for other agents to collude with the third-party. The key novelties of our mechanism are: (i) the introduction of a third-party agent only off-equilibrium and with some probability; (ii) the fact that both its existence and its identity are unknown to the other agents. We show that under these conditions, which are satisfied in many empirical applications, a hidden third-party agent can restore the implementation of the efficient allocation. If this agent does not observe the state of the world, we provide a sufficient condition for implementation to succeed.
Leverage Dynamics with Reputation
Presented in the FTG 2019 Summer Program
This work analyzes the classic trade-off theory of capital structure in a dynamic model where the firm does not have any commitment power. The equilibrium analyzed in this paper depends on the firm's whole history (reputation) instead of the firm's current income and debt level. This paper proves that under this non-Markov structure, the firm may repurchase its outstanding debt, which breaks the Leverage Ratchet effect discussed in Admati, DeMarzo, Hellwig, and Pfleiderer (2018). This paper also proves that under mild conditions, the equity value in a non-Markov equilibrium can be higher than the equity value in the Markov equilibrium, the one depicted in DeMarzo and He (2021). Interestingly, with some conditions, the firm can achieve the first best equity value as if the firm has commitment power. In this case, reputation is a perfect substitute for commitment power.
This figure plots the revised Leverage Target policy that maximizes the equity holders' value as if the firm has commitment power. When the firm's income is not too low, the firm maintains its leverage target. In other words, the firm issues more debt when its income rises and repurchases the outstanding debt when its income drops. This breaks the Leverage Ratchet Effect discussed in Admati, DeMarzo, Hellwig and Pfleiderer (2018). When the firm's income is too low, the firm does not issue or repurchase any debt. In this case, if the firm's income goes up later, the firm starts to maintain the leverage target again; and if the firm's income drops further, the firm defaults as predicted in Leland (1998).
Pre-Ph.D. Publication
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