Stable NIM and Interest Rate Exposure of US Banks with Erik Stafford
This paper shows that the duration risk component of interest rate risk exposure is poorly identified from interest income and interest expense sensitivity measures. Thus, inferences about the net interest rate risk exposures of banks (i.e. net interest margin) are similarly poorly identified from these empirical measures. Empirical interest rate sensitivity measures estimated from time series variation of changes in interest income and interest expenses have little power to measure duration risk, which is caused by discount rate shocks, thereby affecting the time series variation of value or price changes. The “sluggishness” of the deposit rate adjustment to changes in the market rate and the matching of bank interest income and bank interest expense sensitivities to market returns is often viewed as evidence of market power that helps banks to hedge their interest rate risk. We show that much of this empirical relation is actually due to the maturity composition of bank assets and liabilities, where long duration exposure induces rate sluggishness while retaining duration risk exposure. Duration risk is associated with a large risk premium that shows up in the mean return, such that in a cross section of bond portfolios sorted by maturity the mean will be increasing in maturity. We use this prediction to test whether the cross sectional mean of net interest margins can be predicted with maturity composition, finding that nearly 90% of the cross sectional variation is explained, strongly rejecting the notion that stable NIM provides evidence of duration risk being hedged.
How do private equity fees vary across public pensions? (joint with Emil Siriwardane) (Slides)
Internet Appendix An Empirical Guide to Investor-Level Private Equity Data from Preqin
Under Revision for the Journal of Finance
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 available on request)
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.
Overall, no! We show that the level and time series variation in cash flows for most bank activities are well matched by capital market portfolios with similar interest rate and credit risk to what banks report to hold. Ignoring operating expenses, bank loans earn high returns and transaction deposits pay low interest rates, consistent with these activities having a potential edge. The edge among these activities is insufficient to cover the large operating expenses of banks. A large portion of the aggregate US banking sector closely resembles a tax inefficient passive mutual fund. The residual risks of bank activities, presumably generated by the unique components of the bank business model, generate systematic risks that are uncompensated.
A Q-Theory of Banks with Saki Bigio and Jeremy Majerovitz and Matias Vieyra (Slides)
We document five facts about banks: (1) market and book leverage diverged during the 2008 crisis, (2) Tobin's Q predicts future profitability, (3) neither book nor market leverage appears constrained, (4) banks maintain a market leverage target that is reached slowly, (5) pre-crisis, leverage was predominantly adjusted by liquidating assets. After the crisis, the adjustment shifted towards retaining earnings. We present a Q-theory where leverage notions differ because book accounting is slow to acknowledge loan losses. We estimate the model and show that it reproduces the facts. We examine counterfactuals: different accounting rules produce a novel policy tradeoff.
Banks' 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
What explains fee dispersion in private equity? (joint with Claudia Robles-Garcia and Emil Siriwardane)
Financial Regulation in a Quantitative Model of the Modern Banking System with Tim Landvoigt (Slides) (Online Appendix)
WFA Award for the Best Paper on Financial Institutions
Forthcoming at the Review of Economic Studies
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%.
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.
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.
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