Christian Opp

Christian C. G. Opp

The Wharton School
University of Pennsylvania

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Curriculum Vitae [link]


Research Interests:

Financial institutions and asset pricing



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

“Venture Capital and the Macroeconomy," October 2016.
Revise & Resubmit Journal of Political Economy.


I develop a model of venture capital (VC) intermediation that can explain central empirical facts about the magnitude and cyclicality of VC activity, and allows evaluating its impact on the macroeconomy. The framework reveals how pro-cyclical VC investment dynamics are self-reinforcing through a risk premium channel that rationalizes strongly declining funding standards in booms. VC investments' growth contributions generate significant societal value added, despite their strong cyclicality, even after accounting for large uninsurable idiosyncratic risks associated with VC contracts. The proposed general equilibrium model yields exact solutions despite the presence of informational frictions, imperfect risk sharing, and endogenous growth.


Real Anomalies,”  with J. van Binsbergen, March 2017



We examine the importance of asset pricing anomalies (alphas) for the real economy. We develop a novel quantitative model with lumpy investment that features such informational inefficiencies and yields closed-form solutions for cross-sectional distributions of firm dynamics. Our findings indicate that anomalies can cause material real inefficiencies, raising the possibility that agents that help eliminate them can provide significant value added to the economy. The framework reveals that alphas alone are poor indicators of real distortions, and that efficiency losses depend on the persistence of alphas, the amount of mispriced capital, and the Tobin's q of firms affected.


Voluntary Disclosure in Bilateral Transactions,”  with V. Glode and X. Zhang, January 2017



We analyze optimal voluntary disclosure by a privately informed agent who faces a counterparty endowed with market power in a bilateral transaction. While disclosures reduce the agent's informational advantage, 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 privately informed agent always finds it optimal to design a partial disclosure plan that implements socially efficient trade in equilibrium. Our results have important implications for understanding the conditions under which asymmetric information impedes trade and for regulating information disclosure.


“Learning, Optimal Default, and the Pricing of Distress Risk," March 2017.
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.


“Over-the-Counter vs. Limit Order Markets: The Role of Expertise Acquisition and Market Power," with V. Glode, January 2017



Over-the-counter (OTC) markets have large trading volume, even though they exhibit frictions absent in centralized limit order markets. We analyze the relative merits of these two market structures when some traders use price quotes to screen privately informed counterparties and expertise is endogenous. Surprisingly, frictions present in OTC markets, such as time-consuming search, can promote higher efficiency. First, screening may be less aggressive and inefficient when traders can reach fewer counterparties promptly. Second, OTC markets with predictable and exclusive trading encounters encourage expertise acquisition, which is beneficial when expertise improves allocative efficiency, but harmful when it causes adverse selection.


Bank Capital, Risk-taking and the Composition of Credit," with M. Harris and M. Opp, January 2017


We propose a general equilibrium framework to analyze the cross-sectional distribution of credit and its exposure to shocks to the financial system, such as changes to bank capital, capital requirements, and interest rates. We characterize how over- and underinvestment in different parts of the borrower distribution are linked to the capitalization of the banking sector and the distribution of borrowers' risk characteristics and bank dependence. Our model yields a parsimonious asset pricing condition for firms' cost of capital that sheds light on heterogeneity in interest rate pass-through across borrower types, as well as its dependence on the health of the banking sector.


On the Efficiency of Long Intermediation Chains,”  with V. Glode and X. Zhang, October 2016



We study a classic problem in economics where an agent uses his market power to inefficiently screen his privately informed counterparty. We show that, generically, if efficient trade is implementable, either by adding competition or more broadly by allowing for incentive-compatible mechanisms that eliminate market power, it is also implementable via a trading network that takes the form of a long intermediation chain in which each trader's information set is similar to those of his direct counterparties.


Intertemporal Information Acquisition and Investment Dynamics”  , February 2015



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


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.



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