Christian Opp

Christian C. G. Opp

The Wharton School
University of Pennsylvania

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Curriculum Vitae [Link]


Research Interests:

My work analyzes institutions and informational frictions in financial markets, with a special focus on their impact on allocative efficiency.


Published and conditionally accepted articles:

“Venture Capital and the Macroeconomy," August 2018 [BibTeX]
Review of Financial Studies (Conditionally accepted)


I develop a model of venture capital (VC) intermediation that quantitatively explains central empirical facts about VC activity and can evaluate its macroeconomic relevance. I find that VC-backed innovations' impact is significantly larger than suggested by observed aggregate venture exit valuations, even after accounting for large exposures to systematic and uninsurable idiosyncratic risks. The risk properties of venture capital play a quantitatively important role in both explaining empirical regularities and shaping the value of ventures' contributions to economic growth. The model is analytically tractable and yields exact solutions, despite the presence of matching frictions, imperfect risk sharing, and endogenous growth.

“Over-the-Counter vs. Limit-Order Markets: The Role of Traders’ Expertise," with V. Glode, July 2018 [BibTeX]
Review of Financial Studies (Conditionally accepted)


Over-the-counter (OTC) markets attract substantial trading volume despite exhibiting frictions absent in centralized limit-order markets. We compare the efficiency of OTC and limit-order markets when traders' expertise is endogenous. We show that asymmetric access to counterparties in OTC markets yields increased rents to expertise acquisition for a few well-connected core traders. When the existence of gains to trade is uncertain, traders' higher expertise in OTC markets can improve allocative efficiency. In contrast, when expertise primarily causes adverse selection, competitive limit-order markets tend to dominate. Our model provides guidance for policymakers and empiricists evaluating the efficiency of market structures.

”Voluntary Disclosure in Bilateral Transactions,”  with V. Glode and X. Zhang
Journal of Economic Theory, 2018, 175: 652–688 [BibTeX]


We characterize optimal voluntary disclosures by a privately informed agent facing a counterparty endowed with market power in a bilateral transaction. Although disclosures reveal some of the agent's private information, they may increase his information rents by mitigating the counterparty's incentives to resort to inefficient screening. We show that when disclosures are restricted to be ex post verifiable, the informed agent optimally designs a disclosure plan that is partial and that implements socially efficient trade in equilibrium. Our results shed light on the conditions necessary for asymmetric information to impede trade and the determinants of disclosures' coarseness.

”Real Anomalies,”  with J. van Binsbergen
Journal of Finance (Forthcoming) [BibTeX]


We examine the importance of cross-sectional asset pricing anomalies (alphas) for the real economy. We develop a novel quantitative model of the cross-section of firms that features lumpy investment and informational inefficiencies, while yielding distributions in closed form. Our findings indicate that anomalies can cause material real inefficiencies, raising the possibility that agents that help to eliminate them add significant value to the economy. The framework reveals that the magnitude of alphas alone is a poor indicator of real implications, and highlights the importance of alpha persistence, the amount of mispriced capital, and the Tobin's q of firms affected.

”On the Efficiency of Long Intermediation Chains,”  with V. Glode and X. Zhang Journal of Financial Intermediation (Forthcoming) [Link] [BibTeX]


Intermediation chains represent a common pattern of trade in over-the-counter markets. We study a classic problem impeding trade in these markets: an agent uses his market power to inefficiently screen a privately informed counterparty. We show that, generically, if efficient trade is implementable via any incentive-compatible mechanism, it is also implementable via a trading network that takes the form of a sufficiently long intermediation chain. We characterize information sets of intermediaries that ensure this striking result. Sparse trading networks featuring long intermediation chains might thus constitute an efficient market response to frictions, in which case no regulatory action is warranted.


”Asymmetric Information and Intermediation Chains,”  with V. Glode.
American Economic Review, 2016, 106(9): 2699-2721 [BibTeX] [Link] [Appendix]

Best Paper Award --- 12th Annual Conference in Financial Economics at IDC-Herzliya


We propose a parsimonious model of bilateral trade under asymmetric information to shed light on the prevalence of intermediation chains that stand between buyers and sellers in many decentralized markets. Our model features a classic problem in economics where an agent uses his market power to inefficiently screen a privately informed counterparty. Paradoxically, involving moderately informed intermediaries also endowed with market power can improve trade efficiency. Long intermediation chains in which each trader's information set is similar to those of his direct counterparties limit traders' incentives to post prices that reduce trade volume and jeopardize gains to trade.


”Rating Agencies in the Face of Regulation,”  with M. Opp and M. Harris.
Journal of Financial Economics, 108 (2013), pp. 46-61 [BibTeX] [Link]


This paper develops a theoretical framework to shed light on variation in credit rating standards over time and across asset classes. Ratings issued by credit rating agencies serve a dual role: they provide information to investors and are used to regulate institutional investors. We show that introducing rating-contingent regulation that favors highly rated securities may increase or decrease rating informativeness, but unambiguously increases the volume of highly rated securities. If the regulatory advantage of highly rated securities is sufficiently large, delegated information acquisition is unsustainable, since the rating agency prefers to facilitate regulatory arbitrage by inflating ratings. Our model relates rating informativeness to the quality distribution of issuers, the complexity of assets, and issuers' outside options. We reconcile our results with the existing empirical literature and highlight new, testable implications, such as repercussions of the Dodd-Frank Act.


Working Papers:

Bank Capital and the Composition of Credit," with M. Harris and M. Opp, August 2017 [BibTeX]


A growing empirical literature highlights the importance of compositional changes in credit for economic activity, including the buildup of leverage and risk. We develop a model of the composition of credit that transparently identifies features of an economy determining which types of borrowers are primarily affected by changes to bank capital and regulations governing it. Our theory echoes the complexity of compositional changes, revealing that even increases in capital ratio requirements can locally increase banks' riskiness. We derive new testable predictions, e.g., on the relations between prices and regulatory risk weights, and between interest rate pass-through and bank capital scarcity.


“Learning, Optimal Default, and the Pricing of Distress Risk," March 2017 [BibTeX]
Winner of the Marshall Blume Prize in Financial Research [First Prize]


I propose a tractable asset pricing model to study distressed firms' returns when agents dynamically learn about firm solvency and make optimal default decisions. As distressed firms' access to finance depends on investors' information quality, the future speed of learning critically affects prices and risk premia. Through this feedback channel, the cost of equity can decrease with leverage and become negative, contrary to typical interpretations of Modigliani and Miller (1958). The model yields closed-form solutions and sheds light on key asset pricing puzzles related to financial distress, including the momentum anomaly and abnormal returns following private placements of public equity.


“To Pool or Not to Pool? Security Design in OTC Markets," with V. Glode and R. Sverchkov, May 2018 [BibTeX]


This paper studies the optimality of pooling and tranching for a privately informed security originator facing buyers endowed with market power (perhaps due to liquidity shortages). Contrary to the standard result that pooling and tranching are optimal practices, we find that selling assets separately may be preferred by originators as it weakens buyers' incentives to inefficiently screen them. Our results can shed light on observed time-variation in the practice of pooling and tranching in financial markets, in particular, the dramatic decline in the size of the ABS market following the most recent financial crisis.


Intertemporal Information Acquisition and Investment Dynamics”  , February 2015 [BibTeX]



This paper studies intertemporal information acquisition by agents that are rational Bayesian learners and that dynamically optimize over consumption, investment in capital, and investment in information. The model predicts that investors acquire more information in times when future capital productivity is expected to be high, the cost of capital is low, new technologies are expected to have a persistent impact on productivity, and the scalability of investments is expected to be high. My results shed light on the economic mechanisms behind various dynamic aspects of information production by the financial sector, such as the sources of variation in returns on information acquisition for investment banks or private equity funds.


“Cycles of Innovation and Financial Propagation,” January 2010 [BibTeX]


Episodes of boom-bust cycles tend to occur in sectors with recent arrivals of new technologies and are often related to excessive funding by the financial sector. In this paper, I develop a dynamic general equilibrium model consistent with a role for the financial sector in propagation during such episodes. I extend a standard Schumpeterian growth model by incorporating (a) a monopolistically competitive financial sector and (b) time-varying technological conditions in real sectors. I identify two propagation channels. The first operates through financial firms' acquisition of sector-specific knowledge (skill channel); financial firms chase "hot sectors" and thereby amplify fluctuations. The second channel originates in an interaction between competition in the financial sector and patent races in product markets (competition channel). Financial firms' temporary competitive advantages in access to new ventures imply market segmentation: financial firms maximize the surplus generated by the client firms they can currently attract, anticipating competing financial firms' future screening and funding decisions. Relative to the Pareto optimum, the competition channel generates overinvestment in sectors with temporarily improved technological conditions; excessively high growth in these sectors comes at the cost of lower growth in the economy as a whole. The model links financial propagation to time variation in the cross section of asset prices. Exposures to aggregate risk dampen amplification effects.