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Pavel Zryumov

  • Assistant Professor of Finance
  • Simon Business School
  • University of Rochester

Research Interests

Corporate Finance, Asymmetric Information in Financial Markets, Contract Theory


Working Papers

Design of Macro-prudential Stress Tests


(Reject and Resubmit, Review of Financial Studies)

  • with Dmitry Orlov and Andy Skrzypacz, May 2018.
  • Rome Junior Finance (2017), Fed Stress Testing Research Conference (2017), Wharton Liquidity (2017), FTG (2018), FIRS (2018), WFA (2018), SED (2018)

We study the design of stress tests that provide information about systemic risk in banks’ portfolios and impose contingent capital requirements to prevent bankruptcies. The optimal stress test discloses information partially: when risk is low, capital requirements reflect full information and set mild restrictions on dividend issuance; when risk is high, the test is not fully transparent and requires banks to hold precautionary liquidity. With heterogeneous banks, optimal stress tests reveal information gradually and require weak banks raise capital first. The results are robust to allowing bailouts and equity issuance. We discuss how stress tests interact with ex-ante portfolio choice.

Dynamic Adverse Selection: Time Varying Market Conditions and Endogenous Entry

  • May 2015.
  • SFS Cavalcade (2015), MIT Junior Finance (2015), WFA (2016)
  • FTG Best Finance Theory Job Market Paper (2015)

In this paper I analyze the effect of time-varying market conditions and endogenous entry on equilibrium dynamics of markets plagued by adverse selection. I show that variation in gains from trade, stemming from market conditions, creates an option value and distorts liquidity when current gains from trade are low. An improvement in market conditions triggers a wave of high quality deals due to the preceding illiquidity and lack of incentives to signal quality. When gains from trade are high, the market is fully liquid; high prices and no delay in trade attract low-grade assets, and the average quality deteriorates. My analysis also reveals that illiquidity can act as a remedy as well as a cause of inefficiency: partial illiquidity allows for screening of assets and restores efficient entry incentives. I demonstrate model implications using several applications: early stage financing, initial public offerings, and private equity buyouts.

Optimal Issuance under Information Asymmetry and Accumulation of Cash Flows


We reexamine the classic yet static information asymmetry model of Myers and Majluf (1984) in a fully dynamic market. A firm has access to an investment project and can finance it by debt or equity. The market learns the quality of the firm over time by observing cash flows generated by the firm's assets in place. In the dynamic equilibrium, the firm optimally delays investment, but investment eventually takes place. In a "two-threshold" equilibrium, a high-quality firm invests only if the market's belief goes above an optimal upper threshold, while a low-quality firm invests if the market's belief goes above the upper threshold or below a lower threshold. However, a different "four-threshold" equilibrium can emerge if cash flows are sufficiently volatile. Relatively risky growth options are optimally financed with equity, whereas relatively safe projects are financed with debt, in line with stylized facts.

Working In Progress

Debt and Human Capital

with Dmitry Orlov and Felipe Varas.


Persuading the Principal To Wait


with Dmitry Orlov and Andy Skrzypacz, August 2018.

Journal of Political Economy, forthcoming.

A principal decides when to exercise a real option. A biased agent influences this decision by strategically disclosing relevant information. To persuade the principal to wait it is optimal to commit to delayed disclosure of all information. Without long-term commitment, this promise is credible only if the agent’s bias towards delayed exercise is small; otherwise, the agent pipets information, probabilistically delaying the principal’s action. When the agent is biased towards early exercise, his lack of commitment to remain quiet leads to immediate disclosure, hurting the agent. Our model applies to pharmaceutical companies conducting post-market clinical trials to influence the FDA or equipment manufacturers testing their products to attract customers.

On the linear and nonlinear generalized Bayesian disorder problem (discrete time case)


with Albert Shiryaev

Optimality and Risk-Modern Trends in Mathematical Finance, pp. 227-236. Springer Berlin Heidelberg, 2010.

This paper considers a generalized Bayesian disorder (quickest detection) problem in discrete time with two types of penalty function — linear and non-linear ones. An explicit solution is given for the linear penalty function. Disorder problem is reduced to optimal stopping of multidimensional Markov process in case of non-linear penalty.


  • FIN 511 - Continuous Time Methods in Finance (2018, Simon)
  • This is an advanced course in the theory of capital markets. The first part of the course covers classical continuous time models of no-arbitrage pricing, portfolio choice, and equilibrium pricing. The second part of the class presents recent developments in consumption- and production-based equilibrium models, intermediary asset pricing, credit risk and other topics.
  • FIN 448 - Fixed Income Securities (2017-present, Simon)
  • This course offers an introduction to debt markets. It provides institutional background and introduces concepts and models used for pricing of various fixed income instruments such as fixed-coupon bonds, floating-rate notes, forwards and swaps, mortgage backed securities, and corporate debt, among others.
  • FNCE250 - Venture Capital and the Finance of Innovation (2015-2017, Wharton)
  • This course covers the finance of technological innovation, with a focus on the valuation tools useful in the venture capital industry. These tools include the "venture capital method," comparables analysis, discounted cash flow analysis, contingent-claims analysis. The primary audience for this course is finance majors interested in careers in venture capital or in R&D-intensive companies in health care or information technology.

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