Christian Opp


Christian C. G. Opp

The Wharton School
University of Pennsylvania

oppDescription: Description: Description: Description: Description: Description: Description: Description: Description: Description: Description: Description: at.gifwharton.upenn.edu

Curriculum Vitae (link)

 

Research Interests:

Financial institutions and asset pricing

 


Publications:

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

 

Abstract

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 Cycles," June 2014. Revise & Resubmit Journal of Political Economy.

Abstract

I develop a dynamic general equilibrium asset pricing model that can address a range of empirical regularities related to venture capital intermediation, some of which often have been taken as evidence of investor irrationality. The model characterizes the joint equilibrium dynamics of VC fund flows, alphas, risk premia, failure risk, and IPO volume, as well as their links to the macroeconomy. In the model VC firms' time-varying screening and funding choices feed back into VC fund vintages' alphas and risk exposures. Fragility in VC funding during downturns creates endogenous barriers to entry which benefits those ventures that have obtained funding during previous booms. This effect lowers venture investments' low-frequency risk exposures in booms and can rationalize lenient funding standards, high IPO volume, high idiosyncratic failure risk, and high fund inflows despite low future expected returns.

 

”Adverse Selection and Intermediation Chains," with V. Glode, February 2015. Revise & Resubmit American Economic Review.

Abstract

We propose a parsimonious model of over-the-counter trading with asymmetric information to rationalize the existence of intermediation chains that stand between buyers and sellers of assets. Trading an asset through several heterogeneously informed intermediaries can preserve the efficiency of trade by reallocating an information asymmetry over many sequential transactions. Such an intermediation chain ensures that the adverse selection problems counterparties face in each transaction are small enough to allow for socially efficient trading strategies by all parties involved. Our model makes novel predictions about network formation and rent extraction when adverse selection problems impede the efficiency of trade.

 

“Learning about Distress," April 2015. * Winner of the Marshall Blume Prize in Financial Research [First Prize]

Abstract

I develop an analytically tractable dynamic asset pricing model to study expected returns of financially distressed firms in the presence of learning and investor activism. The model reveals that learning critically affects distressed firms' equity risk exposures and can rationalize low and even negative risk premia close to default. In the face of an aggregate downturn, high downside risk for truly insolvent firms increases the speed of learning, which generates a positive feedback effect on equity holders' default option value. Equity holders' option value is similarly enhanced by the ability to partially free ride on active investors' information acquisition. The model illustrates that the cyclical properties of learning have first-order effects on distress risk premia and can rationalize striking momentum dynamics. premia.

 

Macroprudential Bank Capital Regulation in a Competitive Financial System," with M. Harris and M. Opp, June 2014

Abstract

We propose a tractable general equilibrium framework to analyze the effectiveness of bank capital regulations when banks face competition from other investors, such as institutions in the shadow-banking system. Our analysis shows that increased competition can not only render previously optimal bank capital regulations ineffective but also imply that, over some ranges, increases in capital requirements cause more banks in the economy to engage in value-destroying risk-shifting. To avoid this perverse outcome, the regulator has to set capital requirements high enough, so that risk-shifting activities become less profitable from a bankerÕs private perspective than socially valuable banking activities. Our model generates a set of novel implications that highlight the intricate dependencies between optimal bank capital regulation and the comparative advantages of various institutions in the financial system.

 

Intertemporal Information Acquisition and Investment Dynamics”  , February 2015

 

Abstract

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

Abstract

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.

 

 

ription: Description: Description: Description: Description: Description: Description: Description: Description: Description: Description: Description: U:\Documents\Wharton\Homepage\pixh_grey.gif