The Panic of 2007-2008 was a run on the sale and repurchase market (the “repo” market), which is a very large, short-term market that provides financing for a wide range of securitization activities and financial institutions. Repo transactions are collateralized, frequently with securitized bonds. We refer to the combination of securitization plus repo finance as “securitized banking”, and argue that these activities were at the nexus of the crisis. We use a novel data set that includes credit spreads for hundreds of securitized bonds to trace the path of crisis from subprime-housing related assets into markets that had no connection to housing. We find that changes in the “LIB-OIS” spread, a proxy for counterparty risk, was strongly correlated with changes in credit spreads and repo rates for securitized bonds. These changes implied higher uncertainty about bank solvency and lower values for repo collateral. Concerns about the liquidity of markets for the bonds used as collateral led to increases in repo “haircuts”: the amount of collateral required for any given transaction. With declining asset values and increasing haircuts, the U.S. banking system was effectively insolvent for the first time since the Great Depression.

We investigate a structural model of market and firm-level dynamics in order to jointly price long-dated S&P 500 options and tranche spreads on the five-year CDX index. We demonstrate the importance of calibrating the model to match the entire term structure of CDX index spreads because it contains pertinent information regarding the timing of expected defaults and the specification of idiosyncratic dynamics. Our model matches the time series of tranche spreads well, both before and during the financial crisis, thus offering a resolution to the puzzle reported by Coval, Jurek and Stafford (2009).

Using a novel measure of contract strictness based on the ex-ante probability of a covenant violation, I investigate how lender-specific shocks impact the strictness of the loan contract that a borrower receives. Exploiting between-bank variation in recent portfolio performance, I find evidence that banks write tighter contracts than their peers after suffering defaults to their own loan portfolios, even when defaulting borrowers are in different industries and geographic regions than the current borrower. The effects of recent defaults persist after controlling for bank capitalization, although negative bank equity shocks are also strongly associated with tighter contracts. The evidence is consistent with lenders learning about their own screening technology via defaults and adjusting contracts accordingly. Finally, contract tightening is most pronounced for borrowers who are dependent on a relatively small circle of lenders, with each incremental default implying covenant tightening equivalent to that of a ratings downgrade.

This paper documents that new loans to large borrowers fell by 47% during the peak period of the financial crisis (fourth quarter of 2008) relative to the prior quarter and by 79% relative to the peak of the credit boom (second quarter of 2007). New lending for real investment (such as working capital and capital expenditures) fell by only 14% in the last quarter of 2008, but contracted nearly as much as new lending for restructuring (LBOs, M&A, share repurchases) relative to the peak of the credit boom. After the failure of Lehman Brothers in September 2008 there was a run by short-term bank creditors, making it difficult for banks to roll over their short-term debt. We document that there was a simultaneous run by borrowers who drew down their credit lines, leading to a spike in commercial and industrial loans reported on bank balance sheets. We examine whether these two stresses on bank liquidity led them to cut lending. In particular, we show that banks cut their lending less if they had better access to deposit financing and thus they were not as reliant on short-term debt. We also show that banks that were more vulnerable to credit line drawdowns because they co-syndicated more of their credit lines with Lehman Brothers reduced their lending to a greater extent. 

We argue that a firm’s aggregate risk is a key determinant of whether it manages its future liquidity needs through cash reserves or bank lines of credit. Banks create liquidity for firms by pooling their idiosyncratic risks. As a result, firms with high aggregate risk find it costly to get credit lines from banks and opt for cash reserves in spite of higher opportunity costs and liquidity premium. We verify our model’s hypothesis empirically by showing that firms with high asset beta have a higher ratio of cash reserves to lines of credit, controlling for other determinants of liquidity policy. This effect of asset beta on liquidity management is economically significant, especially for financially constrained firms; is robust to variation in the proxies for firms’ exposure to aggregate risk and availability of credit lines; works at the firm level as well as the industry level; and is significantly stronger in times when aggregate risk is high.

Key words: Bank lines of credit, cash holdings, liquidity premium, lending channel, asset beta.
JEL classification: G21, G31, G32, E22, E5.

This paper presents a comprehensive analysis of mortgage delinquency using a unique loan-level dataset from a major national mortgage bank from 2004 to 2008. Our analysis highlights two major agency problems underlying the mortgage crisis: one between the bank and mortgage brokers that results in lower quality broker-originated loans, and the other between banks and borrowers that results in information falsification by borrowers of low-documentation loans--known in the industry as “liars’ loans”--especially when originated through a broker. While nearly all the difference in delinquency rates between bank and broker channels can be attributed to observable loan and borrower characteristics, most of the difference between full- and low-documentation types is due to unobservable heterogeneity. Both differences are not fully compensated by the loan pricing.

A popular explanation for the recent rise in mortgage default is that securitization led to lender moral hazard. According to the story, lending banks that could easily resell loans to (possibly naive) securitizers had little incentive to carefully screen potential borrowers. Some research has supported this view by exploiting what appear to be credit score cutoff rules used by securitizers. In this paper we argue that the cutoff rule evidence has been misinterpreted and is in fact consistent with an equilibrium model where all actors are rational and lender moral hazard is avoided. Even without securitization, cutoff rules emerge endogenously as a rational response of lenders to per-applicant fixed costs in screening. Securitizers’ response to lender cutoff rules is determined by the degree of information asymmetry between lender and securitizer. Both institutional evidence and findings from a loan-level dataset containing nearly 60% of active residential mortgages in the United States appear consistent with our model. Discontinuous jumps in mortgage volume and default rate at the FICO credit score of 620 are apparent, implying a change in lender screening behavior at the threshold, but in our main sample of conforming loans there is no corresponding jump in the securitization rate at this score.

JEL Classifications: D82, G01, G18, G21, G24, G28, N22.
Keywords: Financial Crisis, Moral Hazard, Mortgages, Securitization

We present a model in which issuers of asset backed securities choose to release coarse information to enhance the liquidity of their primary market, at the cost of reducing secondary market liquidity or even causing it to freeze. The degree of transparency is inefficiently low if the social value of secondary market liquidity exceeds its private value. We analyze various types of public intervention — mandatory transparency standards, provision of liquidity to distressed banks or secondary market price support — and find that they have quite different welfare implications. Finally, transparency is greater if issuers restrain the issue size, or tranche it so as to sell the more information-sensitive tranche to sophisticated investors only

This paper develops a structural credit risk model of a bank that issues deposits, share-holders’ equity, and fixed or floating coupon bonds in the form of contingent capital or subordinated debt. The return on the bank’s assets follows a jump-diffusion process, and default-free interest rates are stochastic. The equilibrium pricing of the bank’s deposits, contingent capital, and shareholders’ equity is studied for various parameter values characterizing the bank’s risk and the contractual terms of its contingent capital. Allowing for the possibility of jumps in the bank’s asset value, as might occur during a financial crisis, has distinctive implications for valuing contingent capital. Credit spreads on contingent capital are higher the lower is the value of shareholders’ equity at which conversion occurs and the larger is the conversion discount from the bond’s par value. The effect of requiring a decline in a financial stock price index for conversion (dual price trigger) is to make contingent capital more similar to non-convertible subordinated debt. The paper also examines the bank’s incentive to increase risk when it issues different forms of contingent capital as well as subordinated debt. In general, a bank that issues contingent capital has a moral hazard incentive to raise its assets’ risk of jumps, particularly when the value of equity at the conversion threshold is low. However, moral hazard when issuing contingent capital tends to be less than when issuing subordinated debt. Because it reduces effective leverage and the pressure for government bailouts, contingent capital deserves serious consideration as part of a package of reforms that stabilize the financial system and eliminate “Too-Big-to-Fail."

In a model with multiple agents with different risk aversions facing margin constraints, we show how securities’ required returns are characterized both by their beta and their margins. Negative shocks to fundamentals make margin constraints bind, lowering risk free rates and raising Sharpe ratios of risky securities, especially for high-margin securities. Such a funding liquidity crisis gives rise to a “basis,” that is, a price gap between securities with identical cash-flows but different margins. In the time series, the basis depends on the shadow cost of capital which can be captured through the interest-rate spread between collateralized and uncollateralized loans, and, in the cross section, it depends on relative margins. We apply the model empirically to the CDS-bond basis and other deviations from the Law of One Price, and to evaluate the effects of unconventional monetary policy and lending facilities.

The 2007-2009 financial crisis has led legislators on both sides of the Atlantic to propose laws that would require most “standardized” over-the-counter (OTC) derivatives to be cleared centrally. This paper examines these proposals. Although OTC derivatives did not cause the crisis, they do facilitate large speculative transactions and have the potential to create systemic risk. The main attraction of the central clearing proposals is that they will make positions in standardized derivatives more transparent. However, our experience from the 2007-2009 crisis suggests that large losses by financial institutions often arise from their positions in non-standard OTC derivatives. The paper argues that one way forward is for regulators is to require all OTC derivatives (standard and non-standard) to be cleared centrally within three years. This would maximize the benefits of netting and reduce systemic risk while making it easier for regulators to carry out stress tests. The paper divides OTC derivatives into four categories and suggests how each category could be handled for clearing purposes. 

Counterparty credit risk has become one of the highest-profile risks facing participants in the financial markets. Despite this, relatively little is known about how counterparty credit risk is actually priced. We examine this issue using an extensive proprietary data set of contemporaneous CDS transaction prices and quotes by 14 different CDS dealers selling credit protection on the same underlying firm. This unique cross-sectional data set allows us to identify directly how dealers’ credit risk affects the prices of these controversial credit derivatives. We find that counterparty credit risk is significantly priced in the CDS market. The magnitude of the effect, however, is relatively modest and is consistent with a market structure in which participants require collateralization of swap liabilities by counterparties. The pricing of counterparty credit risk became much more significant after the Lehman default at both the market level and at the level of individual CDS dealers. Furthermore, there is some evidence of strategic behavior by CDS dealers with the best credit. Surprisingly, we find that counterparty credit risk is not priced in the CDS spreads for financial firms in the sample, but is priced for the nonfinancial firms. This may suggest that the market expects large CDS dealers to be treated as too large to fail when other major financial firms begin to default

We address the problem of allocating the counterparty-level credit valuation adjustment (CVA) to the individual trades composing the portfolio. We show that this problem can be reduced to calculating contributions of the trades to the counterparty-level expected exposure (EE) conditional on the counterparty’s default. We propose a methodology for calculating conditional EE contributions for both collateralized and non-collateralized counterparties. Calculation of EE contributions can be easily incorporated into exposure simulation processes that already exist in a financial institution. We also derive closed-form expressions for EE contributions under the assumption that trade values are normally distributed. Analytical results are obtained for the case when the trade values and the counterparty’s credit quality are independent as well as when there is a dependence between them (wrong-way risk).