Publications

Strategic Fragmented Markets with Ana Babus, Journal of Financial Economics (forthcoming)                                                                                                         
We study the determinants of asset market fragmentation in a model with strategic investors that disagree about the value of an asset. Investors choices determine the market structure. Fragmented markets are supported in equilibrium when disagreement between investors is low. In this case, investors take the same side of the market and are willing to trade in smaller markets with a higher price impact to face less competition when trading against a dealer. The maximum degree of market fragmentation increases as investors' priors are more correlated. Dealers can benefit from fragmentation, but investors are always better off in centralized markets.
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Trading Costs and Informational Efficiency with Eduardo Dávila, Journal of Finance, 76 (3), 2021, pp. 1471-1539
We study the effect of trading costs on information aggregation and acquisition in financial markets. For a given precision of investors' private information, an irrelevance result emerges when investors are ex-ante identical: price informativeness is independent of the level of trading costs. When investors are ex-ante heterogeneous, a change in trading costs can increase or decrease price informativeness, depending on the source of heterogeneity. Our results are valid under quadratic, linear, and fixed costs. Through a reduction in information acquisition, trading costs reduce price informativeness. We discuss how our results inform the policy debate on financial transaction taxes/Tobin taxes.                                                                           
                                                                                                                                                                                                                                                              [bibtex]
Collateralizing Liquidity**,  Journal of Financial Economics 131 (2019), pp. 299-322
I develop a dynamic model of optimal funding to understand why financial assets are used as collateral instead of being sold to raise funds. Firms need funds to invest in risky projects with non-observable returns. Since holding these assets allows firms to raise these funds, investing firms value the asset more than non-investing ones. When assets are less than perfectly liquid and investment opportunities are persistent, collateralized debt minimizes asset transfers from investing to non-investing firms and, thus, is optimal. Frictions in asset markets lead to an illiquidity discount and a collateral premium, which increase with the asset's illiquidity.​
                                                                                                                                                                                                                                                              [bibtex]
**Previously titled " Equilibrium Collateral Constraints".
Fragility in Money Market Funds: Sponsor Support and Regulation*,  Journal of Financial Economics 121 (2016​), pp. 595-623
Money Market Funds (MMFs), which are crucial to short-term funding markets, rely on voluntary support of fund sponsors to maintain stable share values. I develop a general equilibrium model of MMFs to study how sponsor support affects the industry’s fragility and regulation. Adverse asset-quality shocks lead MMFs to liquidate assets. When liquidity in asset markets is limited, asset prices are lower if more funds liquidate. Lower asset prices, in turn, make sponsor support costlier and even more liquidations occur. This feedback leads to complementarities in sponsors’ support decisions. Based on the model’s insights, I derive implications for the regulation of MMFs.                                                                                                                                                               
                                                                                                                                                                                                                    [bibtex]   [Presentation UWFC]
* Previously titled "The Regulation of Money Market Funds: Adding Discipline to the Policy Debate".  
Modernization of Tax Administrations and Optimal Fiscal Policies ​with Martin Besfamille, Journal of Public Economic Theory 11 (6), 2009, 897 - 926, December 
Since Sandmo (1981), many articles have analyzed optimal fiscal policies in economies with tax evasion. All share a feature: they assume that the cost of enforcing the tax law is exogenous. However, governments often invest resources to reduce these enforcement costs. In a very simple model, we incorporate such investments in the analysis of an optimal fiscal policy. We characterize their optimal level and we show numerically how they interact with the other dimensions of the optimal fiscal policy. Finally, we highlight the differences between our results and those obtained in a model without investment in the tax administration.
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Working papers

 The Value of Arbitrage with Eduardo Dávila and Daniel Graves                                                                                                                                        April 2022 
This paper studies the social value of closing price differentials in financial markets. We show that arbitrage gaps exactly correspond to the marginal social value of executing an arbitrage trade. Moreover, arbitrage gaps and price impact measures are sufficient to compute the total social value from closing an arbitrage gap. Theoretically, we show that, for a given arbitrage gap, the total social value of arbitrage is higher in more liquid markets. We compute the welfare gains from closing arbitrage gaps for covered interest parity violations and several dual-listed companies. The estimated social value of arbitrage varies substantially across applications.
Identifying Price Informativeness with Eduardo Dávila                                                                                                                                                     April 2022
This paper shows how to identify and estimate price informativeness. Starting from i) an asset pricing equation and ii) a stochastic process for asset payoffs, we show how to exactly recover relative price informativeness from regressions of changes in asset prices on changes in asset payoffs. Applying our identification results, we estimate a panel of stock-specific measures of informativeness for U.S. stocks. In the cross-section, large, high turnover, and high institutional ownership stocks have higher informativeness. In the time series, the median, mean, and standard deviation of the distribution of informativeness have steadily increased since the mid-1980s.
​                                                                                                                                                                                         Replication code and informativeness data  
Designing Stress Scenarios with Thomas Philippon                                                                                                                                                          March 2022
We develop a tractable framework to study the optimal design of stress scenarios. A principal wants to manage the unknown risk exposures of a set of agents. She asks the agents to report their losses under hypothetical scenarios before mandating actions to mitigate the exposures. We show how to apply a Kalman filter to solve the learning problem and we characterize the scenario design as a function of the risk environment, the principal's preferences, and the available remedial actions. We apply our results to banking stress tests. We show how the principal learns from estimated losses under different scenarios and across different banks. Optimal capital requirements are set to cover losses under an adverse scenario while targeted interventions depend on the covariance between residual exposure uncertainty and physical risks.
Specialization in Banking with Kristian Blickle and Anthony Saunders                                                                                                                          May 2021
Using highly detailed data on the loan portfolios of large US banks, we document that these banks "specialize" by concentrating their lending disproportionately into one industry. This specialization improves a bank’s industry-specific knowledge and allows it to offer generous loan terms to borrowers, especially to firms with access to alternate sources of funding and during periods of greater non-bank lending. Superior industry-specific knowledge is further reflected in better loan and, ultimately, bank performance. Banks concentrate more on their primary industry in times of instability and relatively lower tier-1 capital. Finally, specialization counteracts a well documented trend in reduced lending by large banks to opaque SMEs.
​Volatility and Informativeness with Eduardo Dávila                                                                                                                                                    October 2020
We explore the relation between price volatility and price informativeness in financial markets. We identify two channels (noise reduction and equilibrium learning) through which changes in informativeness are associated with changes in volatility. When informativeness is sufficiently high (low), volatility and informativeness positively (negatively) comove in equilibrium for any change in primitives. We provide conditions on primitives that guarantee that volatility and informativeness comove positively or negatively for any change in parameters. We recover stock-specific primitives for US stocks, and find that most stocks lie in the region of the parameter space in which informativeness and volatility comove negatively.
A Model of Infrastructure Financing with Viral Acharya and Suresh Sundaresan                                                                                           September 2020
Infrastructure projects involve multiple parties: government, private sector firms that build and manage, and outside investors who supply financing. Private sector firms need incentives to implement and maintain the projects well; governments may lack commitment not to extort cash flows (for instance, by limiting user fees) from projects once implemented. This double moral hazard problem limits the willingness of outside investors to fund infrastructure projects. To ameliorate these two moral hazards, we show that the optimal design of infrastructure financing features (I) government guarantees to investors against project failure; (II) bundling of development rights for the private sector and investors; (III) tax subsidies to the private parties out of infrastructure externalities; and, (IV) “general obligation” financing in the form of cross-guarantees between high-quality projects and “revenue only” financing without cross-guarantees for low-quality projects. These features are found to be relevant in the practice of infrastructure financing.
​Transparency and Bank Runs                                                                                                                                                                                                   April 2015
In a banking model with imperfect information, I find that more precise information increases the economy's vulnerability to bank runs. For low transparency levels, depositors cannot distinguish bad from good states based on their private signals and, absent liquidity shocks, have no incentives to withdraw early. As transparency increases, and private signals become more informative, depositors' incentives to withdraw strengthen and run-proof contracts become costlier in risk-sharing terms: the bank must offer less to early withdrawers to prevent runs. When transparency is high enough, the bank would rather forgo return and hold excess liquidity than choose a run-proof deposit contract.