An options-based approach to evaluating the risk of Fannie Mae and Freddie Mac

Fannie Mae and Freddie Mac assume a significant amount of interest and prepayment risk and all of the credit risk for about half of the $8 trillion U.S. residential mortgage market. Their hybrid government-private status, and the perception that they are too big to fail, make them a potentially large, but largely unaccounted for, risk to the federal government. Measuring the size and risk of this liability is technically difficult, but important for the debate over the appropriate regulation of these institutions. Here we take an options pricing approach to evaluating these costs and risks. Under the base case assumptions, the estimated value of the guarantees is $7.9 billion over 10 years, with a combined .5 percent value at risk of $122 billion. We evaluate the sensitivity of these estimates to various modeling assumptions, and also to the regulatory regime, including forbearance policies and capital requirements. The analysis highlights the benefits, but also the challenges, of taking an options-based approach to evaluating the value of federal credit guarantees.     

An Empirical Investigation of Alternative Contingent Claims Models for Pricing Residential Mortgages

Researchers have employed option pricing techniques to analyze mortgage financing and valuation. Alternative models (one-, two-, and three-variable models) employing different variables (short- and long-term interest rates and building value) have been designed to price mortgage securities. No prior research has addressed the question of whether the pricing accuracy of these contingent claims models improves as states increase or whether contingent claims models' valuation abilities generate reasonable estimates of primary mortgage market prices. The articles investigates the relative efficiency of each of these alternative mortgage valuation models in predicting primary market mortgage values. Our results show that a two-variable model (short rate and building value) is the most efficient. Valuation results indicate a positive pricing spread between the primary market and the theoretically estimated value.     

The use of credit scoring in the mortgage industry

In times of increased focus on risk management, acquiring or growing comparatively low risk mortgage portfolios has become an attractive value proposition. Banks that pursue an aggressive growth strategy in this sector, do, however, require risk control mechanisms that enable them to make a clear judgment on how great a growth appetite they can afford to have in order to still grow profitably. Moreover, under Basel II, the proper quantification of mortgage portfolio risk tends to help the release of own capital, because the mortgage portfolio is one of those portfolios where the relative benefits of internal ratings-based approaches compared with the standardised approach are greatest. Credit scoring models in general, and credit scorecards in particular, are suitable methods for quantifying the risk of an individual mortgage applicant or mortgage customer. In addition to score card development, this paper reviews alternative scoring model types that could be used for mortgage scoring. It presents reasons why it is beneficial to build such models in-house, before focusing on the steps necessary for building a mortgage scorecard. Finally, it discusses the important topics of creating segments, deploying models and eventually monitoring models.     

Pricing effects in Fannie Mae agency bonds

As a government-sponsored enterprise, Fannie Mae enjoys certain advantages over other firms. The extent of these advantages, while widely discussed, have not yet been fully quantified. This paper empirically examines the returns to Fannie Mae general obligation bonds under the assumptions of the Arbitrage Pricing Theory. The model provides an explicit method for estimating the risk premium on Fannie Mae bonds. The results indicate that liquidity and tax effects are important in explaining the returns to Fannie Mae bonds. The results also indicate that the market does not incorporate changes in the riskiness of the mortgage market into the returns on Fannie Mae bonds. The results provide support for the contention that Fannie Mae, as a government sponsored enterprise, enjoys a significant advantage over other firms in the capital market.     

When it comes to the crunch: What are the drivers of the US banking crisis?

This article considers how permissive regulatory conditions helped change the size and scope of the US mortgage market. Asset backed securitization facilitated an expansion of the US mortgage market and modified the structure of the value chain within which financial assets, risk and liquidity were managed. New sophisticated mortgage products, indulgent lending practices, loose credit assessment and flimsy documentation increased the probability of mortgage default in an economic downturn. US banks were not in a position to absorb mark-to-market losses on mortgage assets and goodwill impairment resulting from a credit crunch because they operate with narrow profit margins and a limited equity cushion in the balance sheet. This article questions the viability and sustainability of this banking business model.     

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.     

How Low Can House Prices Go? Estimating a Conservative Lower Bound

In risk management, the credit risk and required capital associated with mortgage assets is often estimated through stress testing where the house price path is an important determinant of the severity of the stress test. Specifically, the extent of credit-related losses is a function of how far house prices are above long-term trend and the extent to which they can fall below trend. Focusing on the latter, we develop a theoretically-based statistical technique to identify a conservative lower bound (CLB) for house prices. Leveraging a model based upon investor incentives, the CLB explains the depth of housing market downturns at both the national and state level over a variety of market environments. This approach performs well in several historical back tests and has strong out-of-sample predictive ability. When back-tested, the estimation approach does not understate house price declines in any state over the 1987 to 2001 housing cycle and only understates declines in three states during the most recent financial crisis. This latter result is particularly noteworthy given that the post-2001 estimates are performed out-of-sample. The CLB is attractive because it (1) provides a leading indicator of the severity of future downturns and (2) allows estimates of trough to recover or decrease in magnitude as markets return to baseline conditions. This estimation technique could prove helpful in measuring the credit risk associated with portfolios of mortgage assets as part of evaluating static or designing dynamic stress tests.     

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.      

Modelo de gestión logística para pequeñas y medianas empresas en México

The market opening and the globalization of supply chains, demand a structural changes in which logistics has a strategic role. Nowadays, clients evaluate product quality, its value added and its availability in time and form, which implies a need to make the process efficient. Several experts have proposed some logistics management models to increase competitiveness in the market, but some of these models are too ambitious for small and medium sized enterprises (SMEs) due to their informal structure and their lack of technical knowledge; other models make indirect reference to the internal information flows, which include whole system disintegration because of the weak interrelation among the different areas. In Mexico, SMEs represent 4.2%, they generate 31.5% of employment and provide 37% of the gross domestic product; that is why it is important to reinforce their competitive position in the market. This research presents the design of a conceptual model of logistic management for SMEs which could provide comprehensive solution through control of the variables involved in the logistics process; to verify that the variables considered in each identified dimension are correct factor analysis was used.     

A Proposal to Improve U.S. Housing Market Incentives: A Response to the Federal Reserve White Paper of January 2012

The U.S. housing finance market has not yet recovered from the housing price bubble that peaked in late 2006. Even though prices have fallen significantly, there are still problems in clearing the market. For the last few years, a group of financial economists and practitioners who are part of the Financial Management Association's Practitioner Demand Driven Academic Research Initiative (PDDARI) have been studying the collapse of the housing market and have concluded that many market participants still have insufficient (and in some cases the wrong) incentives to take actions that would help restore the market's health. In January 2012, Ben Bernanke, Chairman of the Federal Reserve Board, released a white paper that reviewed current housing market conditions and created a framework for policy analysis designed to help reestablish the health of the U.S. housing market as part of the broader effort to foster economic recovery. Using this framework as its starting point, the PDDARI group has come up with a set of proposals whose centerpiece is an “incentive‐compatible” mortgage that encourages homeowners to rebuild their home equity as an essential step to a housing recovery. By incorporating “price appreciation rights” that would provide stronger inducements for lenders or mortgage owners to make loan modifications (particularly, forgiveness of principal), the PDDARI mortgage structure could allow more homeowners to remain in their homes and avoid foreclosures and the large associated deadweight costs (as much as 40% of a home's assessed value). Additionally, the government‐sponsored enterprises, including Fannie Mae and Freddie Mac, are also in need of radical reform, and a transition toward greater private market participation would promote the long‐term health of the mortgage market.     

Business marketing: understand what customers value

How do you define the value of your market offering? Can you measure it? Few suppliers in business markets are able to answer those questions, and yet the ability to pinpoint the value of a product or service for one's customers has never been more important. By creating and using what the authors call customer value models, suppliers are able to figure out exactly what their offerings are worth to customers. Field value assessments--the most commonly used method for building customer value models--call for suppliers to gather data about their customers firsthand whenever possible. Through these assessments, a supplier can build a value model for an individual customer or for a market segment, drawing on data gathered form several customers in that segment. Suppliers can use customer value models to create competitive advantage in several ways. First, they can capitalize on the inevitable variation in customers' requirements by providing flexible market offerings. Second, they can use value models to demonstrate how a new product or service they are offering will provide greater value. Third, they can use their knowledge of how their market offerings specifically deliver value to craft persuasive value propositions. And fourth, they can use value models to provide evidence to customers of their accomplishments. Doing business based on value delivered gives companies the means to get an equitable return for their efforts. Once suppliers truly understand value, they will be able to realize the benefits of measuring and monitoring it for their customers.     

Pricing fixed rate mortgages: Some empirical evidence

We develop a simple model based on the hypothesis that yields in the secondary mortgage market provide a basis for pricing new loans in the primary mortgage market. The model is then expanded to include potential interest rate variations due to lender characteristics and whether the loans meet securitization requirements. The empirical results, using a two-year sample of single-family mortgage rates, conform to the predictions of the model. In particular, we find that the interest rates on FRMs in the primary market move in a one-to-one relationship with secondary market yields. We also find significantly lower interest rates on these mortgages that can be sold in the secondary market versus those that cannot, thus indicating the value of the ability to securitize mortgages.     

Mortgage Default with Asymmetric Information

This article analyzes mortgage-market equilibrium when borrower default costs are private information. By applying the approach of Rothschild and Stiglitz (1976), it is shown that asymmetric information regarding default costs distorts the contract choices available in the mortgage market, preventing safe borrowers (those with high default costs) from fully satisfying their demand for mortgage debt. Large loans are available for a substantial interest-rate premium, but only risky borrowers find this premium worth paying. The article builds on an empirical literature designed to test the ruthless-default principle from option-based models of mortgage pricing. That literature provides evidence against ruthless behavior, suggesting that default costs play an important role in borrower decisions. The article takes a further step by arguing that such costs are private information, which has important implications for market equilibrium.     

Mortgage Fund Flows, Capital Appreciation, and Real Estate Cycles

This paper provides strong evidence for a positive feedback loop between property prices and mortgage supply, using data from the U.S. commercial property and mortgage markets over the 1991 to 2011 period. The empirical analyses control for the endogeneity of property prices, mortgage flows, mortgage interest rates, and loan to value ratios, and provide two main findings. First, exogenous increases in mortgage supply, measured with the growth of the CMBS market, significantly reduce property cap rates. Second, volatility of past price changes and the “biggest loss” in property values in the past significantly affect mortgage supply. This positive feedback loop may be an important driving force for real estate cycles.     

Asymmetric Information in the Subprime Mortgage Market

Because of impersonal securitization in the secondary market, the ultimate investors in a mortgage have only a limited amount of information about the borrower??s characteristics. This creates an asymmetric information problem because of hidden knowledge on the part of the primary lenders, who naturally have much better access to this information. This is aggravated by the free rider problem when there are multiple investors. We discuss to what extent the secondary market then seeks to sort the loans to ameliorate this problem and what role reputations play. More importantly, however, the actions of the primary lender in terms of which kinds of loans they choose to approve are partly hidden, and this typical principal-agent situation importantly aggravates the incentive problem. To judge the nature and magnitude of this moral hazard dilemma, we use data to compare how well investors in the secondary mortgage market can predict default given the information they typically have access to as compared to the ability of primary lenders to similarly predict default given the larger set of information they typically will have access to. Finally, the implications of these results are indicated, particularly in light of the recent mortgage crisis.     

Anforderungen an die Abbildung von Versicherungsunternehmen im Rahmen mathematisch-ökonomischer Modelle in der Unternehmenspraxis

The article analyses the requirements which are to be fulfilled when modelling the insurance business from an economic perspective by means of mathematical models. The goal of the discussion is to define what the management needs to draw meaningful conclusions for steering of an insurance company. The authors emphasise the importance of the objective of the analysis, the different views which are important when analysing an insurer (book value versus market value perspective) as well as the importance of the timeline in models. The inclusion of time and the resulting options serve as a reference for the classification of models as being dynamic or static. A discussion of the validity of the model results, in the context of the basic assumptions of the model used, is given at the end of the article.     

Mortgage Lending, Race, and Model Specification

This study examines the role of race in home mortgage lending by investigating the sensitivity of race estimates to variations in model specification. I compare parameter estimates based on a statistical model utilized by the Federal Reserve Bank of Boston, using a subset of the data that corresponds to FDIC-supervised institutions, with estimates obtained from several alternative variations specified to reflect information obtained from reviews of the mortgage loan application files. Estimates of the race effect are shown to be highly sensitive to the assumptions that underlie the model; minor modifications in model specification are sufficient to eliminate the race effect. The empirical results suggest that the statistical models used to evaluate the impact of race in mortgage lending may not provide reliable information about lending bias.     

The Gap between the Theory and Practice of Corporate Valuation: Survey of European Experts

The valuation of companies or their assets is at the heart of most financing and investment decisions. Over the last five decades, academics have developed several simple and sophisticated models for corporate valuation. Yet valuation estimates of a firm or its assets appear to vary widely among practitioners. It is unclear whether these differences arise from practitioners' use of different valuation models or from differences in their assumptions about the inputs used in those models. To provide some insights into this issue, the authors recently surveyed 365 European finance practitioners with CFAs or equivalent professional degrees. They find that almost all survey respondents use the Discounted Cash Flow (DCF) model (along with some version of Relative Valuation that relies on the use of “comparables”). But the estimation methods of such practitioners for almost all inputs in the DCF model, including beta, the equity market risk premium, leverage, cost of debt, and terminal value, vary widely. This can be a serious problem because even small differences in inputs can cause huge variations in valuations. Such differences arise primarily because theory provides little guidance on how to estimate parameters, leaving practitioners to make their own assumptions and judgments. In sum, the authors' findings suggest that the process of estimating valuation parameters can be as important as the choice of the valuation model itself, and requires the serious attention of academics and practitioners. The authors recommend that key valuation parameter estimates be disclosed in financial and valuation reports. Their findings are also relevant to policy makers because the concept of “fair value” plays such a central role in post‐crisis regulation.     

Appraisal Quality and Residential Mortgage Default: Evidence from Alaska

We empirically examine the effect of appraisal quality on subsequent mortgage loan performance using data from the high volatility housing market of Alaska in the 1980s. We develop measures of appraisal quality by computing the residual between a hedonic estimate of house value using available information from other appraisals compared to actual ex ante appraised value. We then estimate proportional hazard models of mortgage default and find that several measures of appraisal quality, particularly appraised value in excess of hedonic estimates, are significantly related to default risk. Using valuations subsequent to loan default, we are also able to evaluate how well house price indices perform in terms of estimating current loan-to-value and offer some additional evidence on the controversy over the role of net equity versus trigger events as determinants of mortgage default. We also show that defaults are related to ex ante measures of housing market conditions, with additional implications for underwriting policies and the current industry trend away from traditional appraisal and toward automated valuation.     

Government intervention in the mortgage market: A study of anti-redlining regulations

This paper addresses the question of whether economic incentives exist for mortgage lenders to avoid or to minimize mortgage originations in neighborhoods inhabited primarily by low-income racial minorities. The Option Pricing Model is utilized to determine what mortgage borrower characteristics affect the market value of the mortgage contracts. It is found that existing laws do not enable mortgage lenders to vary either origination prices or mortgage terms so as to adjust for differences in the market values of mortgages. As a result, incentives are created for both the mortgage lender and the mortgage insurer to avoid originations and underwritings in areas with relatively high default probabilities. Various changes in mortgage lending regulations are suggested to eliminate these incentives, and the effects of alternative programs to subsidize mortgage borrowers with relatively high default probabilities are considered.