The Effect of Mortgage Price and Default Risk on Mortgage Spreads

Variations over time in mortgage yield spreads should reflect changes in the underlying prepayment option value; moreover, the relationship between mortgage yield spreads and interest rate dynamics should weaken as the value of the borrowers prepayment option declines. We verify this hypothesis through an empirical analysis of residential mortgage yield spread behavior, and we also present evidence that the strength of the relationship between mortgage spreads and interest rate dynamics weakens (strengthens) as the level of default risk increases (decreases). This result is consistent with the competing risks effect between a borrowers option to prepay or default. Our results demonstrate the importance of accounting for mortgage price discount to par as well as default risk when developing time series of mortgage yields.     

Fixed-Rate Endowment Mortgage and Mortgage Indemnity Valuation

We use a contingent claims framework for valuing the the default and prepayment embedded options in certain British fixed-rate endowment mortgages, with a (capped) mortgage indemnity guarantee (MIG). This methodology provides a template for the borrower, lender, and insurer to compare mortgage terms, including the fairness of contract rates, arrangement fees, prepayment penalties, any MIG premiums required, and co-insurance exposure. With empirical inputs, this model may eventually be useful as a mark-to-value proxy for all parties, as expected parameters change (especially interest rate and house price levels, and expected future volatilities), for purposes of determining valued added accounting, appropriate reserves, and indeed for setting premiums and business drivers. Fixed-rate endowment mortgages differ from fixed-rate repayment mortgages primarily because, in the event of early termination, the amount owed by the borrower is a function of the evolution of the term structure of interest rates, whereas for a repayment mortgage it is pre-determined. We compare endownment and repayment mortgages for different levels of loan-to-value ratios, interest rate and house price volatilities.     

GSEs,Mortgage Rates,and Secondary Market Activities

Fannie Mae and Freddie Mac are government-sponsored enterprises (GSEs) that securitize mortgages and issue mortgage-backed securities (MBS). In addition, the GSEs are active participants in the secondary mortgage market on behalf of their own investment portfolios. Because these portfolios have grown quite large, portfolio purchases (in addition to MBS issuance) are often thought to be an important force in the mortgage market. Using monthly data from 1993 to 2005 we estimate a VAR model of the relationship between GSE secondary market activities and mortgage interest rate spreads. We find that GSE portfolio purchases have no significant effects on either primary or secondary mortgage rate spreads. Further, we examine GSE activities and mortgage rate spreads in the wake of the 1998 debt crisis, and find that GSE portfolio purchases did little to affect mortgage rates. This empirical finding is robust to alternative identification assumptions and to alternative model and variable specifications.      

Measuring Potential GSE Funding Advantages

As the size of government sponsored enterprises (GSE) has grown, attention has focused on the relationship between the federal government and the GSEs, with particular attention focused on estimating the impact of this relationship on GSE debt costs. Quantifying the GSEs cost advantage is a controversial exercise with several competing methodologies providing divergent values. Thus, this paper reviews the methods that have been utilized in previous studies and recommends an alternative approach that overcomes many of the criticisms of previous work. By using offering yields on GSE debt, we find that the three housing GSEs enjoyed an average advantage of between 25 and 29 basis points over AA banking sector bonds, between 43 and 47 basis points over A rated bonds, and between 76 and 80 basis points over BBB rated banking issues. We find that our results are robust to both the basic approach taken as well as to model specification.     

Mortgage Default: Classification Trees Analysis

We apply the powerful, flexible, and computationally efficient nonparametric Classification and Regression Trees (CART) algorithm to analyze real estate mortgage data. CART is particularly appropriate for our data set because of its strengths in dealing with large data sets, high dimensionality, mixed data types, missing data, different relationships between variables in different parts of the measurement space, and outliers. Moreover, CART is intuitive and easy to interpret and implement. We discuss the pros and cons of CART in relation to traditional methods such as linear logistic regression, nonparametric additive logistic regression, discriminant analysis, partial least squares classification, and neural networks, with particular emphasis on real estate. We use CART to produce the first academic study of Israeli mortgage default data. We find that borrowers features, rather than mortgage contract features, are the strongest predictors of default if accepting icbadli borrowers is more costly than rejecting good ones. If the costs are equal, mortgage features are used as well. The higher (lower) the ratio of misclassification costs of bad risks versus good ones, the lower (higher) are the resulting misclassification rates of bad risks and the higher (lower) are the misclassification rates of good ones. This is consistent with real-world rejection of good risks in an attempt to avoid bad ones.     

Benefits to Homeowners from Mortgage Portfolios Retained by Fannie Mae and Freddie Mac

Mortgage investing is the domain of financial intermediaries, such as Fannie Mae and Freddie Mac, who possess specialized knowledge and experienced analytic teams. Capital is channeled to homeowner/borrowers at lower cost through such entities. As the demand for mortgage borrowing outstrips aggregate domestic saving (which is currently negative) foreign sources of capital should become even more significant. Foreign capital can be channeled efficiently into the U.S. mortgage market by Fannie and Freddie. Their debt has the highest credit standing and their risk management ability has been demonstrated by their enormous retained portfolios of mortgages.     

The Effects of Purchases of Mortgages and Securitization by Government Sponsored Enterprises on Mortgage Yield Spreads and Volatility

In this paper, we investigate the effects of GSE (government sponsored enterprise) activities on mortgage yield spreads and volatility. Using various regression procedures (i.e., vector error correction (VEC) and GARCH models) and controlling for default and prepayment risk, we find that securitizations and purchases of mortgages by GSEs reduce mortgage yield spreads and volatility. In particular, we find that the yield spread between conforming and 10-year constant maturity treasury (CMT) rates decreases by 8.0 bp per $1billion increase in the level of GSE securitizations. Similarly, if GSEs increase mortgage purchases, the yield spread decreases 10.5 bp per $1billion increase of purchases. In addition, we hypothesize and find that GSE activities have a spillover effect to the non-conforming mortgage market; via investor substitutions, GSE purchases and securitizations of conforming loans reduce non-conforming loan rates. Thus, the measured influence of GSE activities is biased downward when measured using the spread of non-conforming loans over conforming loan rates. We also find that purchases of mortgages by GSEs significantly reduce mortgage yield volatility. In sum, our findings show that GSE activities reduce and stabilize mortgage market rates.     

The pricing of FIREARMs (“Falling Interest Rate Adjustable-Rate Mortgages”)

The purpose of this article is to propose and price a new type of adjustable-rate mortgage: the FIREARM (Falling Interest Rate Adjustable-Rate Mortgage). The interest payments on this mortgage adjust downward whenever interest rates decline, while remaining stable when interest rates increase. The FIREARM is alternatively priced as a prepayable and non-prepayable mortgage with a spread over the short-term interest rate. We price these two instruments and contrast their prices with those of fixed-rate mortgages using the parsimonious assumptions of a non-stationary arbitrage-free binomial term structure model.     

Commercial Mortgage Default: A Comparison of Logit with Radial Basis Function Networks

This article explores the use of artificial neural networks in the modeling of foreclosure of commercial mortgages. The study employs a large set of individual loan histories previously used in the literature of proportional hazard models on loan default. Radial basis function networks are trained (estimated) using the same input variables as those used in the logistic. The objective is to demonstrate the use of networks in forecasting mortgage default and to compare their performance with that of the logistic benchmark in terms of prediction accuracy. Neural networks are shown to be superior to the logistic in terms of discriminating between good and bad loans. The study performs sensitivity analysis on the average loan and offers suggestions on further improving prediction of defaulting loans.     

Nonparametric prediction for the time-dependent volatility of the security price

In this paper we consider a continuous time model for the security price with the time-dependent volatility. It is shown that the non-normality and non-linear dependency of the short-term return, the major characteristics observed on many financial assets, can be incorporated into our model. In order to evaluate the option price formula on the model we propose a nonparametric predictor for the volatility function without reference to a specific functional form. We examine the so-called continuous record asymptotics and show that the proposed predictor is asymptotically minimax for a wide class of the volatility functions. One of the most important results is that the application of the Black-Scholes method can be justified by plugging the proposed predictor in the standard Black-Scholes formula even if the volatility changes over time.     

Subprime Borrowers: Mortgage Transitions and Outcomes

Public policy concerns increasingly have focused on subprime lending. Our research uses a survey of prime and subprime borrowers to address whether borrowers inappropriately are channeled to the subprime segment, if once having taken out a subprime mortgage borrowers are stuck in this market segment, and whether borrowers face higher costs by taking out subprime mortgages. We find that subprime borrowers are less knowledgeable about the mortgage process, are less likely to search for the best mortgage rates, and are less likely to be offered a choice among alternative mortgage terms and instruments—possibly making them more vulnerable to unfavorable mortgage outcomes. Our analysis of market segmentation confirms that typical mortgage underwriting criteria are most important in explaining whether borrowers obtain prime or subprime mortgages—higher credit risk borrowers are more likely to get a subprime loan. Our results further show that search behavior and other demographic factors including adverse life events, age, and Hispanic ethnicity contribute to explaining market segment, suggesting that borrowers may inappropriately receive subprime mortgages. While we find some persistence to market segment—borrowers are more likely to take out a subprime mortgage if their previous mortgage came from the subprime segment—we also find that market segment is not immutable. Analysis of the survey responses indicates that borrowers with subprime mortgages significantly are more dissatisfied with their mortgage outcomes. This is not surprising because subprime borrowers look worse across typical mortgage underwriting criteria. Consistent with policy concerns, however, despite holding constant these and other factors, taking out a mortgage in the subprime segment, by itself, appears to increase dissatisfaction with mortgage outcomes. We do not provide a definitive answer to the question of whether subprime lending, on balance, serves homebuyers well by providing access to mortgage credit to those otherwise constrained, or rather serves homebuyers poorly by inappropriately assigning them to a market where costs are high and the ability to transition to more attractive prime mortgages remains low. Our analysis, however, does provide some empirical support for concerns raised by critics of subprime lending, and for this reason justifies continued public policy debate and analysis.     

Environmental Taxes, International Capital Mobility and Inefficient Tax Systems: Tax Burden vs. Tax Shifting

This paper deals with the so-called double dividend of an environmental tax reform. In a model with only labor and a polluting input as factors of production, we find that society faces a trade-off between internalizing environmental externalities and raising revenues in the least distortionary way. However, if capital enters the production structure, an ecological tax reform may render the tax structure more efficient from a non-environmental point of view, thereby raising not only environmental quality but also private incomes.     

Loan Portfolio Swaps and Optimal Lending

Theories on loan portfolio swap hedging are based on a portfolio-choice approach. This paper presents an alternative: a firm-theoretic model for bank behavior with loan portfolio swaps. Our paper derives the optimal loan rate and rate-taking loan amount of the banks portfolio, and relates them to the market loan rate, counterparty loan rate, swap default risk, capital-to-deposits ratio, and deposit insurance. We find that in the bilateral default risk approach, the comparative static results are generated by four factors: the banks risk magnitude about the equity market value, loan composition in the swap contract, the substitution effect in the loan portfolio, and the income effect from the swap transaction. The results imply that changes in the payoff asymmetry in the event of swap default and the banks regulatory parameters have a direct effect on the banks loan portfolio for lending and swap transactions.We would like to thank two anonymous referees for helpful comments and advice.     

Determinants of stock market volatility and risk premia

Summary. We show the dynamics of diverse beliefs is the primary propagation mechanism of volatility in asset markets. Hence, we treat the characteristics of the market beliefs as a primary, primitive, explanation of market volatility. We study an economy with stock and riskless bond markets and formulate a financial equilibrium model with diverse and time varying beliefs. Agents states of belief play a key role in the market, requiring an endogenous expansion of the state space. To forecast prices agents must forecast market states of belief which are beliefs of others hence our equilibrium embodies the Keynes Beauty Contest. A market state of belief is a vector which uniquely identifies the distribution of conditional probabilities of agents. Restricting beliefs to satisfy the rationality principle of Rational Belief (see Kurz, 1994, 1997) our economy replicates well the empirical record of the (i) moments of the price/dividend ratio, risky stock return, riskless interest rate and the equity premium; (ii) Sharpe ratio and the correlation between risky returns and consumption growth; (iii) predictability of stock returns and price/dividend ratio as expressed by: (I) Variance Ratio statistic for long lags, (II) autocorrelation of these variables, and (III) mean reversion of the risky returns and the predictive power of the price/dividend ratio. Also, our model explains the presence of stochastic volatility in asset prices and returns. Two properties of beliefs drive market volatility: (i) rationalizable over confidence implying belief densities with fat tails, and (ii) rationalizable asymmetry in frequencies of bull or bear states.This research was supported by a grant of the Smith Richardson Foundation to the Stanford Institute for Economic Policy Research (SIEPR). We thank Kenneth Judd for constant advice which was crucial at several points in the development of this work. We also thank Kenneth Arrow, Min Fan, Michael Magill, Carsten Nielsen, Manuel Santos, Nicholas Yannelis, Ho-Mou Wu and Woody Brock for comments on earlier drafts. The RBE model developed in this paper and the associated programs used to compute it are available to the public on Mordecai Kurzs web page at http://www.stanford.edu/ mordecai.This revised version was published online in January 2005 with corrections to the Cover date.     

The Disciplining Role of Accounting in the Long-Run

One role of accounting is to discipline softer (more manipulable) sources of information. We use a principal-agent model of hidden actions and hidden information to study this role. In our model, there is both a verifiable signal (a publicly observed output) and an unverifiable signal (a productivity parameter privately observed by the agent). In a one-period setting, the optimal contract does not make use of the agents report on the private signal. However, when the output is tracked over two periods, the agents communication can be valuable. This reversal of results suggests uncovering the disciplining role of accounting may require a long-term perspective.JEL Classification: D82, M41     

Pension Plan Investment Management Mandates: An Empirical Analysis of Manager Selection

We examine the impact of several factors on the selection of portfolio managers for Australian pension plan mandates. Performance measures do not affect the probability of a mandate allocation. Pension sponsors tend to choose managers with top-quartile five-year performance who have recently beaten a market benchmark. Management expenses have a negative impact on a managers chances. A surprising result is sponsors tolerance for high portfolio trading costs. Mandates are spread across manager investment styles. The style and institutional attributes of preferred managers suggest trustees reputation and prudential concerns matter, particularly for the aggregate annual mandate allocations.     

Credit Scoring and Mortgage Securitization: Implications for Mortgage Rates and Credit Availability

This article develops a model of the interactions between borrowers, originators, and a securitizer in primary and secondary mortgage markets. In the secondary market, the securitizer adds liquidity and plays a strategic game with mortgage originators. The securitizer sets the price at which it will purchase mortgages and the credit-score standard that qualifies a mortgage for purchase. We investigate two potential links between securitization and mortgage rates. First, we analyze whether a portion of the liquidity premium gets passed on to borrowers in the form of a lower mortgage rate. Somewhat surprisingly, we find very plausible conditions under which securitization fails to lower the mortgage rate. Second, and consistent with recent empirical results, we derive an inverse correlation between the volume of securitization and mortgage rates. However, the causation is reversed from the standard rendering. In our model, a decline in the mortgage rate causes increased securitization rather than the other way around.     

From new deal institutions to capital markets: Commercial consumer risk scores and the making of subprime mortgage finance

The investment fueled US mortgage market has traditionally been sustained by New Deal institutions called government sponsored enterprises (GSEs). Known as Freddie Mac and Fannie Mae, the GSEs once dominated mortgage backed securities underwriting. The recent subprime mortgage crisis has drawn attention to the fact that during the real estate boom, these agencies were temporarily overtaken by risk tolerant channels of lending, securitization, and investment, driven by investment banks and private capital players. This research traces the movement of a specific brand of commercial consumer credit analytics into mortgage underwriting. It demonstrates that what might look like the spontaneous rise (and fall) of a ‘free’ market divested of direct government intervention has been thoroughly embedded in the concerted movement of calculative risk management technologies. The transformations began with a sequence of GSE decisions taken in the mid-1990’s to implement a consumer risk score called a FICO^® into automated underwriting systems. Having been endorsed by the GSEs, this scoring tool was gradually hardwired throughout the industry to become a distributed and collective ‘market device’. As the paper will show, once modified by specific GSE interpretations the calculative properties generated by these credit bureau scores reconfigured mortgage finance into two parts: the conventional, risk-adverse, GSE conforming ‘prime’ and an infrastructurally distinct, risk-avaricious, investment grade ‘subprime’.     

What's in a Name? An Experimental Examination of Investment Behavior

A fundamental unresolved issue is whether information asymmetries underlie investors predisposition to invest close to home (i.e., domestically or locally). We conduct experiments in the United States and Canada to investigate agents portfolio allocation decisions, controlling for the availability of information. Providing participants with information about a firms home base, without disclosing its specific identity, is not sufficient to change investment behavior. Rather, participants need to know a firms name and home base. Additional evidence indicates that participants have a greater perceived familiarity with local and domestic securities and, in turn, invest more in such securities.The authors thank Ann Gillette, Josef Zechner (the editor), and two anonymous referees for helpful comments and acknowledge the financial support of the Federal Reserve Bank of Atlanta, Georgia Tech, and Social Sciences and Humanities Research Council of Canada. The views expressed here are those of the authors and not necessarily those of the Federal Reserve Bank of Atlanta or the Federal Reserve System.     

Interest-only and principal-only mortgage strips as interest-rate contingent claims

Interest-only (IO) and principal-only (PO) mortgage strips are valued in a stochastic interest-rate environment. The prepayment rate of the underlying mortgages is affected by two considerations not present in the pure financially rational model: (1) The property owner's holding period is assumed to follow a Gamma distribution, resulting in the possibility of prepayment due to the sale of the property (i.e., prepayment that is too early based on market interest rates); and (2) borrowers are assumed to face heterogeneous transaction costs related to refinancing the existing mortgage, and delay refinancing when market conditions make it optimal to do so (refinancing too late). Properties of IO/PO strips are identified by the finite difference method.