The rise of risk-based pricing of mortgage interest rates in Italy

This paper assesses how much mortgage interest rates in Italy are priced on credit risk as proxied by the probability of household mortgage delinquency estimated using the EU-Silc database. Owing to data availability, we restrict the analysis of mortgage pricing to Italian households. Consistent with the more widespread use of credit scoring, estimates indicate that Italian lenders have increasingly priced mortgage interest rates on household credit risk. For mortgages granted between 2000 and 2007, we find that a 1% point increase in the probability of default is associated with a 21 basis point rise in mortgage interest rates, lower than the 38 basis point premium Edelberg (2006) estimated for the US at the end of the 1990s.     

Subprime Mortgage Defaults and Credit Default Swaps

We offer the first empirical evidence on the adverse effect of credit default swap (CDS) coverage on subprime mortgage defaults. Using a large database of privately securitized mortgages, we find that higher defaults concentrate in mortgage pools with concurrent CDS coverage, and within these pools the loans originated after or shortly before the start of CDS coverage have an even higher delinquency rate. The results are robust across zip code and origination quarter cohorts. Overall, we show that CDS coverage helped drive higher mortgage defaults during the financial crisis.     

Putting the squeeze on a market for lemons: Government-sponsored mortgage securitization

Lenders either sell or obtain insurance for many of the mortgages they originate to reduce credit risk and enhance liquidity. An overwhelming majority of the mortgages sold are purchased by government-sponsored enterprises. The prevailing view is that government-sponsorship of mortgage securitization causes mortgage rates to be lower than they would otherwise be. Using a model that incorporates asymmetric information and adverse selection, we provide an example in which government-sponsored mortgage securitization raises the mortgage rate.The analysis and conclusions set forth are our own and do not indicate concurrence by members of the Federal Reserve Research stafls, by the Board of Governors, or by the Federal Reserve Banks. We wish to thank Mark Fisher for his Mathematica expertise. All errors are ours exclusively.     

Foreclosure Delay and Consumer Credit Performance

The deep housing market recession from 2008 through 2010 was characterized by a steep rise in number of foreclosures. The average length of time from onset of delinquency through the end of the foreclosure process also expanded dramatically. Although most individuals undergoing foreclosure were experiencing serious financial stress, the extended foreclosure timelines enabled them to live in their homes without making mortgage payments until the end of the foreclosure process, thus providing temporary income and liquidity benefits from lower housing costs. This paper investigates the impact of extended foreclosure timelines on borrower performance with credit card debt. Our results indicate that a longer period of nonpayment of mortgage expenses results in higher cure rates on delinquent credit cards and reduced credit card balances. Thus, foreclosure process delays may have mitigated the impact of the economic downturn on credit card default—suggesting that improvement in credit card performance during the post-crisis period would likely be slowed by the removal of the temporary liquidity benefits as foreclosures reach completion.     

Loss coverage and stress testing mortgage portfolios: A non-parametric approach

This paper outlines the development of a practical approach to simulating a credit loss distribution function and to implementing a stress test exercise focusing on the entire Spanish mortgage portfolio. Specifically, we determine, via regression model, the main factors that explain why households fail to meet their mortgage payment commitments. This allows us to assign individual borrowers’ PDs and to estimate a rating system for the mortgage portfolio. Then, we simulate the empirical distribution function of mortgage loss rates using a Monte-Carlo resampling method, and compare the loss rates from this function with those provided by the Basel II IRB formulas. Finally, we assess, by running a stress exercise, the ability of banks to withstand certain adverse situations. The main result from this exercise is that, in general terms, Basel II IRB regulatory loss coverage offers fairly adequate protection for banks.     

Pathways After Default: What Happens to Distressed Mortgage Borrowers and Their Homes?

We use a detailed dataset of seriously delinquent mortgages to examine the dynamic process of mortgage default—from initial delinquency and default to final resolution of the loan and disposition of the property. We estimate a two-stage competing risk hazard model to assess the factors associated with post-default outcomes, including whether a borrower receives a legal notice of foreclosure. In particular, we focus on a borrower’s ability to avoid a foreclosure auction by getting a modification, by refinancing the loan, or by selling the property. We find that the outcomes of the foreclosure process are significantly related to: loan characteristics including the borrower’s credit history, current loan-to-value and the presence of a junior lien; the borrower’s post-default payment behavior, including the borrower’s participation in foreclosure counseling; neighborhood characteristics such as foreclosure rates, recent house price depreciation and median income; and the borrower’s race and ethnicity.     

Employment in the Great Recession: How Important Were Household Credit Supply Shocks?

I pool data from all large multimarket lenders in the United States to estimate how many of the over 7 million jobs lost in the Great Recession can be explained by reductions in the supply of mortgage credit. I construct a mortgage credit supply instrument at the county level, the weighted average (by prerecession mortgage market shares) of liquidity-driven lender shocks during the recession. The reduction in mortgage supply explains about 15% of the employment decline. The job losses are concentrated in construction and finance.     

宏观经济不确定性对中国企业债券信用风险的影响——基于2007-2009年月度面板数据

2007年美国次贷危机引发的金融危机给全球经济造成很大的影响,也为本文提供了很好的研究契机,因此,本文利用2007-2009年89家企业债券的月度面板数据,分析宏观经济不确定性对企业债券信用风险的影响程度。我们发现,金融危机爆发后企业债券的信用风险会显著变大。同时,利用该回归结果对2009年12月的截面数据进行估计,进一步验证了本文的结论。     

Mortgage Contracts,Strategic Options and Stochastic Collateral

This paper offers a game-theoretic model for both the analysis and valuation of mortgage contracts in the context of an economy with complete information and complete contingent claims markets. We analyze the equilibrium strategy of the lender, who holds an option over the magnitude of mortgage credit extended per dollar of collateral offered, and the mortgagor, who holds options to default or prepay, in a class of intertemporal mortgage contracts collateralized by property evolving according to a random process which is common knowledge to both parties to the mortgage contract. Using continuous–time arbitrage valuation principles, we derive the value of the mortgage contract to both parties and show, through both analytical solutions and numerical simulations, that Markov perfect equilibria exist in which, among other properties, a lower flow of housing services accruing to the borrower, per dollar of initial house value, and a correspondingly lower rate of effective depreciation, will elicit a larger volume of funds offered by a lender; the amount of credit offered, the values of the contract to both lender and mortgagor, and the expected losses to both parties from costly bankruptcy are highly sensitive to the perceived volatility of the value of the property collateralizing the mortgage, even in an economy with complete markets or risk neutrality on the parts of lender and borrower; the upper limit on mortgage credit offered by a rational lender may be a small fraction of the current fair market value of the property, regardless of the contractual yield offered by the borrower, and will decrease, at each such yield, as bankruptcy costs or housing service flows increase; and under significant but plausible values for bankruptcy and costs of liquidating property under foreclosure, the flow of mortgage credit can become negatively related to the spread of the mortgage yield over the riskless rate, with the lender preferring a lower contractual yield to a higher one.     

Borrower Risk under Alternative Mortgage Instruments

This paper analyzes differences in borrower risk under alternative mortgage instruments and various borrower characteristics. The traditional approach of measuring borrower risk in terms of actual delinquency and foreclosure data is rejected in favor of a model based on potential delinquency-that is, changes in the mortgage payment to income ratio. The combinations of mortgage terms and borrower characteristics that are most likely to produce a potential delinquency are isolated based on the calculation of hypothetical payment to income ratios over an eight year period.     

The effect of mortgage form on borrower interest rate risk: A portfolio theory approach

The problems faced by U.S. regulatory authorities in controlling residential housing cycles have resulted in a continuing search for methods of reducing the volatility of housing construction. One of the most widely discussed methods of decreasing volatility in mortgage credit is the variable rate mortgage (VRM) whose interest rate is linked to some interest rate index. In this paper we employ a portfolio theory approach to examine the relative riskiness of the VRM and fixed rate mortgage (FRM) for borrower and lender. As expected, we find that relative riskiness depends on the composition of the borrower/lender portfolio of assets and liabilities.     

Differential default risk among traditional and non-traditional mortgage products and capital adequacy standards

We develop a framework to quantify credit risks of non-traditional mortgage products (NMPs). Ex ante probabilities of default are caused by willingness-to-pay and ability-to-pay problems and the high default rates for NMPs confirm that payment shock is a critical default risk indicator. Monte Carlo simulations are conducted using three correlated stochastic variables (mortgage interest rate, home price, and household income) under normal and stressed economies. Results confirm that the default risk of 2/28 and option ARM contracts requiring a minimum monthly interest payment have a greater probability of default than other mortgage products in all economic scenarios. Additionally, the credit risk of NMPs is primarily systematic risk, suggesting that these products should require higher risk-based capital. Due to the non-linear distribution of credit risk, even the advanced internal-based rating approach of the Basle II framework can understate the risk involved in these NMPs.     

The ins and outs of mortgage debt during the housing boom and bust

From 1999 to 2013, U.S. mortgage debt doubled before contracting sharply. I estimate mortgage inflows and outflows that shed light on the sources of volatility. During the boom, inflows from real estate investors tripled, far outpacing other segments such as first-time homebuyers. During the bust, a collapse in inflows keyed the debt decline, while an expansion of outflows due to defaults played a more minor role. Inflow declines partly reflect a dramatic falloff in first-time homebuying, especially for low credit score individuals. Further analysis helps support the notion that the differential decline by credit score reflects markedly tightened credit supply.     

The Optimal Mortgage Loan Portfolio in UK Regional Residential Real Estate

In this study, we propose a method based on large deviation theory (LDT), which minimises credit risk (expected loss). We demonstrate how mortgage loan portfolios can be optimised using geographical differences in the risk characteristics of mortgage loans in the UK. Our empirical results show that credit risk can be reduced by a third when the LDT method is used instead of the benchmark portfolios that we calculate with regional-gross-value-added weights and equal weights. More importantly, the difference in the expected loss between these portfolios increases further during bearish housing markets. To see that such numbers matter, in an extreme scenario, the UK mortgage lenders could lose more than 2% a year as the consequence of mortgage defaults, which is equivalent to an annual loss of approximately 20 billion pounds in the UK. Although this extreme state would not continue for a long time, it nevertheless represents a huge potential loss for mortgage lenders and investors.     

Disentangling the Effects of Household Financial Constraints and Risk Profile on Mortgage Rates

In this paper we disentangle the impact of household financial constraints on mortgage rate from a number of dimensions of credit risk. This analysis relies on a dataset that contains information on the economic and financial decisions of Spanish households in four different years: 2002, 2005, 2008, and 2011. Our results suggest that banks’ profitable customers are able to bargain for lower mortgage rates. However, contrary to other studies, the risk profile does not have a significant effect on mortgage rates. Credit institutions tend to charge higher rates during the crisis to all customers, irrespective of their risk profiles.     

Consumer credit-risk models via machine-learning algorithms

We apply machine-learning techniques to construct nonlinear nonparametric forecasting models of consumer credit risk. By combining customer transactions and credit bureau data from January 2005 to April 2009 for a sample of a major commercial bank’s customers, we are able to construct out-of-sample forecasts that significantly improve the classification rates of credit-card-holder delinquencies and defaults, with linear regression R²’s of forecasted/realized delinquencies of 85%. Using conservative assumptions for the costs and benefits of cutting credit lines based on machine-learning forecasts, we estimate the cost savings to range from 6% to 25% of total losses. Moreover, the time-series patterns of estimated delinquency rates from this model over the course of the recent financial crisis suggest that aggregated consumer credit-risk analytics may have important applications in forecasting systemic risk.     

Borrower Self-Selection,Underwriting Costs,and Subprime Mortgage Credit Supply

In the U.S., households participate in two very different types of credit markets. Personal lending is characterized by continuous risk-based pricing in which lenders offer households a continuous distribution of borrowing possibilities based on estimates of their creditworthiness. This contrasts sharply with mortgage markets where lenders specialize in specific risk categories of borrowers and mortgage supply is stepwise linear. The contrast between continuous lending for personal loans and discrete lending by specialized lenders for mortgage credit has led to concerns regarding the efficiency and equity of mortgage lending. This paper sheds both theoretical and empirical light on the differences in the two credit markets. The theory section demonstrates why, in a perfectly competitive credit market where all lenders have the same underwriting technology, mortgage credit supply curves are stepwise linear and lenders specialize in prime or subprime lending. The empirical section then provides evidence that borrowers are being effectively sorted based on risk characteristics by the market.     

Determinants of the ARM share of national and regional lending

We model the ARM share of mortgage lending and provide several unique contributions to the mortgage choice literature. First, we motivate the use of the price spread between fixed- and adjustable-rate credit as a regressor by constraining the effect of FRM and ARM prices to be symmetric and show that the data support this restriction. Second, our data span a far longer time period (six years) than previous research. Third, we estimate separate share equations by region, allowing us to contrast geographic variation in ARM shares. Fourth, we examine the effect of convertible ARMs—which became prevalent in mid-1987—on overall ARM lending.     

A Model of Mortgage Default

In this paper, we solve a dynamic model of households' mortgage decisions incorporating labor income, house price, inflation, and interest rate risk. Using a zero‐profit condition for mortgage lenders, we solve for equilibrium mortgage rates given borrower characteristics and optimal decisions. The model quantifies the effects of adjustable versus fixed mortgage rates, loan‐to‐value ratios, and mortgage affordability measures on mortgage premia and default. Mortgage selection by heterogeneous borrowers helps explain the higher default rates on adjustable‐rate mortgages during the recent U.S. housing downturn, and the variation in mortgage premia with the level of interest rates.     

Subprime Lenders and Mortgage Market Completion

Without a subprime market, some borrowers by virtue of poor credit history, unstable income, and other characteristics are unable to qualify for a mortgage. With a subprime market, there is a more complete credit supply schedule with the market pricing for poorer credit quality in the mortgage rate. By completing the capital market, subprime lenders reduce borrowing constraints. The result is a social welfare gain. Low-credit applicants otherwise denied funding are able to qualify by paying higher interest rates in exchange for offering more equity or lower loan-to-value ratios. This prediction is consistent with the subprime applicants financing or refinancing their mortgages at relatively low loan-to-value ratios.