Why do private equity fees vary across public pensions? (joint with Emil Siriwardane) (Slides)
We document large variation in net-of-fee performance across public pension funds investing in the same private equity fund. In aggregate, these differences imply that the pensions in our sample would have earned $45 billion more – equivalent to $8.50 more per $100 invested – had they each received the best observed terms in their respective funds. There are also large pension-effects in the sense that some pensions systematically pay more fees than others when investing in the same fund. With better terms, the 95th percentile pension would have $14.91 more per $100 invested whereas the 5th percentile pension would have $1.12. Attributes like size, relationships, and governance account for a modest amount of the pension effects, meaning pensions that should in principle have similar bargaining power, preferences, and information consistently pay different fees.
Investing with style: the effect of managers and consultants on public pension portfolios (joint with Emil Siriwardane) (draft coming soon)
We document a large and heterogenous shift by public pensions into alternative investments (hedge funds, private equity, and real estate) since 2006. Fundamental characteristics like size and funding explain almost none of the cross-sectional heterogeneity in the shift to alternatives. Using a simple variance decomposition, we show that investment consultants account for nearly a 25% of the shift and the rest appears to be idiosyncratic in nature. These results challenge standard models of institutional investors and we suggest alternative approaches to better fit the data.
We decompose bank activities into passive and active components and evaluate the performance of the active components of the bank business model by controlling for passive maturity transformation strategies that can be executed in the capital market. Over the period 1960-2016, we find that (1) unlevered bank assets underperform passive portfolios of maturity-matched US Treasury bonds, (2) the cost of bank deposits exceeds the cost of bank debt, (3) bank equities have CAPM betas near one, while passive maturity transformation strategies have CAPM betas near zero, and (4) portfolios of bank equities consistently underperform portfolios designed to passively mimic their economic exposures. The very strong investment performance of passive maturity transformation strategies over this period may mask the underperformance of the specialized bank activities.
Financial Regulation in a Quantitative Model of the Modern Banking System with Tim Landvoigt (Slides)
WFA Award for the Best Paper on Financial Institutions
Under revision for RESTUD (new draft Aug. 2020)
How does the shadow banking system respond to changes in capital regulation of commercial banks? We propose a quantitative general equilibrium model with regulated and unregulated banks to study the unintended consequences of regulation. Tighter capital requirements for regulated banks cause higher liquidity premia, leading to higher shadow bank leverage and a larger shadow banking sector. At the same time, tighter regulation eliminates implicit subsidies to regulated banks and improves the competitive position of shadow banks, reducing their incentives for risk taking. The net effect is a safer financial system with more shadow banking. Calibrating the model to data on financial institutions in the U.S., the optimal capital requirement is around 16%.
A Q-Theory of Banks with Saki Bigio and Jeremy Majerovitz and Matias Vieyra (Slides)
We investigate the behavior of bank balance sheets in the United States during 2007-2015. The goal is to deepen the understanding of the behavior of banks. During this period, bank aggregate book-equity losses were entirely offset by equity issuances whereas market-value losses were catastrophic and never recovered. We find evidence that supports a theory where banks target market leverage, but where adjustments to a target are very gradual. We also find that, in contrast to the pre-crisis period, during the post-crisis banks relied more on retained earnings rather than on assets sales to adjust to a market leverage target. We present a heterogeneous-bank model that rationalizes these facts and can serve as a building block for future work.
Bank's Risk Exposure with Monika Piazzesi and Martin K. Schneider
Under revision for Econometrica
This paper studies U.S. banks’ exposure to interest rate and credit risk. We exploit the factor structure in interest rates to represent many bank positions in terms of simple factor portfolios. This approach delivers time varying measures of exposure that are comparable across banks as well as across the business segments of an individual bank. We also propose a strategy to estimate exposure due to interest rate derivatives from regulatory data on notional and fair values together with the history of interest rates. We use the approach to document stylized facts about the recent evolution of bank risk taking.
Work in Progress
How large are bank equity frictions? (joint with Jonathan Wallen and Wenhao Li)
Are banks exposed to interest rate risk? (joint with Emily Williams)
What explains fee dispersion in private equity? (joint with Claudia Robles-Garcia and Emil Siriwardane)
The Cross-Section of Banks' Leverage Choice with Erik Stafford
Firm Selection and Corporate Cash Holdings with Berardino Palazzo
Forthcoming Journal of Financial Economics
Among stock market entrants, more firms over time are R&D–intensive with initially lower profitability but higher growth potential. This sample-selection effect determines the secular trend in U.S. public firms’ cash holdings. A stylized firm industry model allows us to analyze two competing changes to the selection mechanism: a change in industry composition and a shift toward less profitable R&D–firms. The latter is key to generating higher cash ratios at IPO, necessary for the secular increase, whereas the former mechanism amplifies this effect. The data confirm the prominent role played by selection, and corroborate the model’s predictions.
Capital Requirements, Risk Choice, and Liquidity Provision in a Business Cycle Model
Journal of Financial Economics, Volume 136, Issue 32, May 2020 pages 355-378
This paper develops a quantitative dynamic general equilibrium model in which households’ preferences for safe and liquid assets constitute a violation of Modigliani and Miller. I show that the scarcity of these coveted assets created by increased bank capital requirements can reduce overall bank funding costs and increase bank lending. I quantify this mechanism in a two-sector business cycle model featuring a banking sector that provides liquidity and has excessive risk-taking incentives. Under reasonable parametrizations, the marginal benefit of higher capital requirements related to this channel significantly exceeds the marginal cost, indicating that US capital requirements have been sub-optimally low.
Firm Financing Over the Business Cycle with Juliana Salomao
The Review of Financial Studies, Volume 32, Issue 4, 1 April 2019, Pages 1235–1274
We study the investment and financing policies of public U.S. firms. Large firms substitute between debt- and equity financing over the business cycle whereas small firms' financing policy for debt and equity is pro-cyclical. This paper proposes a novel mechanism that explains these cyclical patterns in a quantitative heterogeneous firm industry model with endogenous firm dynamics. We find that cross-sectional differences in investment policies and therefore funding needs as well as exposure to financial frictions are key to understand how firms' financing policies respond to macroeconomic shocks. Financial frictions cause firms to be larger with lower valuations and less investments.
Big Data in Finance and the Growth of Large Firms with Maryam Farboodi and Laura Veldkamp
Journal of Monetary Economics. Volume 97, 2018, pp. 71-87
Two modern economic trends are the increase in firm size and advances in information technology. We explore the hypothesis that big data disproportionately benefits big firms. Because they have more economic activity and a longer firm history, large firms have produced more data. As processor speed rises, abundant data attracts more financial analysis. Data analysis improves investors' forecasts and reduces equity uncertainty, reducing the firm's cost of capital. When investors can process more data, large firm investment costs fall by more, enabling large firms to grow larger.
Remapping the Flow of Funds, with Monika Piazzesi and Martin K. Schneider
Chapter in NBER book Risk Topography: Systemic Risk and Macro Modeling (2014), Markus Brunnermeier and Arvind Krishnamurthy, editors (p. 57-64)
The Flow of Funds Accounts are a crucial data source on credit market positions in the U.S. economy. In particular, they combine regulatory data from various sources to produce a consistent set of flow and stock tables in major credit market instruments by sector. The events of the last five years have underscored the importance of positions data to guide economic analysis. Viewing positions as payment streams typically requires more information than book value or fair value. However, much of this information is already contained in the data sets from which the Flow of Funds accounts are constructed. This chapter first argues that quantitative analysis of credit market positions would benefit tremendously if the additional information about the structure of payment streams were more readily available, and derives some concrete alternatives for data collection.
Comment: Government Guarantees and the Valuation of American Banks by Andrew G. Atkeson, Adrien d'Avernas, Andrea Eisfeldt, Pierre-Olivier Weill. Prepared for the NBER Macroeconomics Annual 2018, volume 33, Martin Eichenbaum and Jonathan A. Parker, editors