Residential Mortgage-backed Securities Research Articles

The European Securitization Market: Effects of an Uneven Regulatory Playing Field

ABSTRACT This article critically assesses the European securitization industry’s claim of the existence of an uneven regulatory playing field for securitization structures vis-à-vis financial instruments deemed ‘neighbouring’ to securitization by the industry, like whole loan pools, corporate bonds, and covered bonds. According to market participants, the adverse regulatory treatment of securitization is negatively affecting the European securitization market, by pushing issuers and investors towards other financial instruments that are treated preferentially. Ultimately, this prevents the securitization market from escaping the subdued state in which it has been ever since the global financial crisis. To address this problem, market participants are advocating a fundamental recalibration of the existing regulatory framework. By examining the regulatory framework that applies to securitization structures, against the backdrop of regulation for whole loan pools, corporate bonds, and covered bonds, this article confirms that securitization structures are indeed treated adversely, as claimed by the industry. Nevertheless, a valid comparison can only be drawn between ‘true sale’ residential mortgage-backed securities (RMBS) structures and mortgage covered bonds, given the structural-economic similarities between the two financial instruments. In that regard, the adverse regulatory treatment of RMBS is found to be negatively impacting the European securitization market, by fuelling a ‘crowding out’ of RMBS by covered bonds.

Creditor protection and credit ratings in the US RMBS market

AbstractMore than a dozen years after the Dodd‐Frank Act was introduced, we investigate whether credit ratings for the US residential mortgage‐backed securities (RMBS) market differ given the different levels of creditor protection across the US states. Our paper provides three results. First, for the period 2017–2020, we provide evidence that there is inconsistency between credit rating agencies (CRAs): only for Dominion Bond Rating Service Morningstar (DBRS) and Moody's, we observe that the credit ratings for securitization tranches differ given different creditor protection levels across states. Second, in states with higher creditor protection, the relatively new CRAs, DBRS and Kroll Bond Rating Agency (KBRA), are more likely to provide more optimistic ratings than CRAs historically present in the rating market (Moody's, S&P, and Fitch). Third, issuers appear to issue larger deals in US states that are more creditor friendly.

Hedge funds, systemic risk and the market for mortgage-backed securities

Abstract In the early 2000s, the market for private-label residential mortgage-backed securities was built upon a pyramid of risk, and at the foundation of this pyramid were hedge funds. Few post-mortems recognise the critical role played by these institutional investors. This paper uncovers this essential piece of the puzzle and demonstrates that it is a natural outgrowth of the inherent operational freedom that defines hedge funds. It breaks these foundational risks down into two components—illiquidity risk and tail risk—and proposes solutions to prevent them from spilling over into systemic crises without eliminating the benefits that society reaps from this unique risk-taking. It concludes with important lessons for securitisation markets to consider during and after the COVID-19 recession.

Modeling Financial Products and Their Supply Chains

The objective of this paper is to explore how novel financial datasets and machine learning methods can be applied to model and understand financial products. We focus on residential mortgage backed securities, resMBS, which were at the heart of the 2008 US financial crisis. These securities are contained within a prospectus and have a complex waterfall payoff structure. Multiple financial institutions form a supply chain to create the prospectuses. To model this supply chain, we use unsupervised probabilistic methods, particularly dynamic topics models (DTM), to extract a set of features reflecting community (topic) formation and temporal evolution along the chain. We then provide insight into the performance of the resMBS securities and the impact of the supply chain communities through a series of increasingly comprehensive models. First, models at the security level directly identify salient features of resMBS securities that impact their performance. We then extend the model to include prospectus level features and demonstrate that the composition of the prospectus is significant. Our model also shows that communities along the supply chain that are associated with the generation of the prospectuses and securities have an impact on performance. We are the first to show that toxic communities that are closely linked to financial institutions that played a key role in the subprime crisis can increase the risk of failure of resMBS securities. History: Olivia Sheng served as the senior editor for this article. Funding: This research was partially supported by National Science Foundation [Grant CNS1305368] and National Institute of Standards and Technology [Grant 70NANB15H194]. Data Ethics & Reproducibility Note: No data ethics considerations are foreseen related to this article. The code capsule is available on Code Ocean at https://doi.org/10.24433/CO.8845455.v1 and in the e-Companion to this article (available at https://doi.org/10.1287/ijds.2020.0006 ).

Neglected Risks in the Communication of Residential Mortgage‐Backed Securities Offerings

ABSTRACTExamining the contractual disclosures during the sale of private‐label residential mortgage‐backed securities before the 2008 financial crisis, we find that textual contents in the risk‐factor section predict subsequent losses and yet were not reflected in pricing. Insurance companies, especially life insurers and insurers with low regulatory capital ratios, are more exposed to textual risks. Consistent with issuers hedging litigation risks with disclosure, we find that textual contents are associated with second‐lien underreporting and preissuance written communications. Overall, we find that investors neglected risks in the purportedly safe assets before the crisis.

A Study on Prepayment Risk of Residential Mortgage-backed Securitization in ChinaA Case of "JIAMEI 2018-1 MBS Program"

The Residential Mortgage-Backed Securities market (RMBS) has played a large role in enhancing the liquidity of mortgages, and in relieving the pressure of capital constraints on commercial banks. There are three main risks associated with residential mortgage-backed securitization: prepayment risk, interest rate risk, and default risk. This paper analyzes the prepayment risk in the "JIAMEI 2018-1"RMBS, the largest single RMBS product of the Postal Saving Bank of China (About 14 billion RMB). We introduce the JIAMEI 2 018-1 and study the factors that affect its prepayment risk. Using data, we conclude that the products involved in this case have comparatively low prepayment risk, even under the double influence of the housing finance policy tightening and the impact of the COVID-19 Pandemic.

Navigating the 2023 US Housing Market: Impact on Residential Mortgage-Backed Securities

This article discusses the outlook for the US housing market and its expected impact on the trading dynamics of residential mortgage-backed securities (RMBS) in 2023. Despite the current reduced affordability of housing due to higher mortgage rates and surging home values, single family home prices are unlikely to experience a sharp decline, with growth expected in the second half of the year. The limited housing supply will lead to increased upward pressure on home prices and stronger performance in RMBS. Non-Qualified Mortgage (non-QM) products may face a challenging year in 2023, with delinquencies and losses expected to rise. Credit performance will be critical, and demand for affordability products is likely to increase. Overall, the outlook for the RMBS market remains challenging due to rising interest rates, tightening monetary policy, and the expected increase in the supply of MBS. However, the high level of home equity in the US housing market will create skin in the game for borrowers as well as higher collateral values to protect against credit deterioration.

Intensified Competition and The Impact on Credit Ratings in the RMBS market

AbstractIn this paper, we empirically investigate the impact of intensified competition on rating quality in the credit rating market for residential mortgage‐backed securities (RMBS) in the period 2017–2020. We provide evidence that competition between large credit rating agencies (CRAs) (Moody's and Standard & Poor's) and newer smaller ones (Dominion Bond Rating Service Morningstar and Kroll Bond Rating Agency) creates credit rating inconsistencies in the RMBS market. While a credit rating should solely represent the underlying credit risk of a RMBS, irrespective of the competition in the market, our results show that this is not the case. When competitive pressure is higher, both large and small CRAs tend to adjust their rating standards (smaller CRAs react to large CRAs and vice versa).

The real effects of municipal bond insurance market disruptions

This paper uses a unique data set of local governments' bond issuance, expenditure, and employment to study the impact that the monoline insurance industry's demise has on local governments' operations. To show causality, I use an instrumental variable approach that exploits persistent insurance relationships and the cross-sectional variation in insurers' exposure to high-quality residential mortgage-backed securities. Governments associated with ailing insurers issued less debt, cut expenditures, and hired fewer workers. These effects are concentrated among opaque governments and are persistent. Partial equilibrium calculations show that affected governments' aggregate expenditures and employment levels in 2017 would have been close to 10% higher if bond insurance had remained available.

Ten Years of Evidence: Was Fraud a Force in the Financial Crisis?

This article synthesizes the large literature regarding the role of various players in residential mortgage-backed securities (RMBS) securitization at the center of the 2008–09 US housing and financial crisis. Underwriting banks facilitated wide-scale mortgage fraud by knowingly misreporting key loan characteristics underlying mortgage-backed securities (MBS). Under the cover of complexity, credit rating agencies catered to investment banks by issuing increasingly inflated ratings on both RMBS and collateralized debt obligations (CDOs). Originators who engaged in mortgage fraud gained market share, as did CDO managers who catered to underwriters by accepting the lowest-quality MBS collateral. Appraisal targeting and inflated appraisals were the norm. RMBS and CDO prices indicate that the marginal AAA investor was unaware of pervasive mortgage fraud and ratings inflation, but these factors were strongly related to future deal performance. The supply of fraudulent credit was not uniform, but clustered in certain geographic regions and zip codes. As these dubious originators extended credit to those who could not afford the loans, the credit expansion led to house price booms and subsequent crashes in these zip codes. Overall, a consistent narrative based on substantial research indicates that conflicts of interest, misreporting, and fraud were focal features of the financial crisis. (JEL G01, G21, G28, K42, R30)

Rise of the Machines: Application of Machine Learning to Mortgage Prepayment Modeling

Key to the valuation of agency residential mortgage-backed securities (MBSs) is the modeling of voluntary prepayment and default behaviors of the underlying borrowers in the mortgage pool. The proliferation of pool- and loan-level data coupled with access to advanced machine learning algorithms has opened the door to the application of machine learning to mortgage prepayment modeling. The modular prepayment model, one that relies on defined functions to predict mortgage prepayment, has dominated the MBS market nearly since its inception. However, machine learning models are beginning to make inroads and, in some cases, are replacing traditional modular prepayment models. The modular and machine learning model differ in the following ways: In the case of modular prepayment models, either added or multiplicative, the modeler defines the functional form of each feature as well as the “tuning” of the parameters passed to each. Machine learning or “second generation” mortgage prepayment models differ in the sense that the modeler “tunes” the hyperparameters that determine the bias variance tradeoff while the machine determines the functional form of each feature of the model. In this article, the authors propose a machine learning mortgage prepayment model using a boosted gradient classifier, trained at the loan level and generalized to the pool level. A gradient boosted classifier is a tree-based model using an ensemble of weak learners to create a strong committee for prediction.

Commentary: Credit Rating Failures in the Aftermath of the Mortgage Meltdown

Credit ratings from the major rating agencies failed to signal the true risk content of residential mortgage-backed securities (RMBS), collateralized debt obligations (CDOs), and commercial mortgage-backed securities (CMBS) issued from 2005 through 2007. This article compares the failures across rating agencies and asset classes, using data filed by the rating agencies with the Securities and Exchange Commission (SEC). The data confirm the terrible performance of RMBS ratings. The likely causes include a combination of the breakdown of mortgage industry lending practices and the concurrent deterioration of rating agency practices. The data show that CDO ratings perform somewhat better than RMBS ratings. That result is perhaps surprising and likely reflects the confounding effects of the SEC’s definitions of its reporting categories. The data also show bad performance for CMBS ratings although the underlying causes differ from those driving the results for RMBS and CDOs. Moreover, the data show high levels of rating withdrawals across all asset classes, raising the question of possible underreporting of defaults. <b>Key Findings</b> ▪ Rating agency data reported to the SEC confirm the terrible performance of RMBS ratings, with triple-A-rated RMBS displaying 10-year default rates of 30% to 35% as of year-end 2017. The likely causes include a combination of the breakdown of mortgage industry lending and securitization practices and the concurrent deterioration of rating agency practices. ▪ The data show that CDO ratings performed better than RMBS ratings, likely because the data include ratings for many synthetic corporate CDOs. Other studies indicate that performance is significantly worse for CDOs backed by structured finance assets. ▪ CMBS ratings also performed poorly. Although CMBS rated triple-A displayed 10-year default rates of only 2% to 3%, those rated double-A had default rates of 12% to 19% while single-A-rated CMBS default rates were 23% to 32%. ▪ The data document high levels of unexplained rating withdrawals on structured finance securities. The effect of such withdrawals may be to artificially depress the reported default rates.

Punishment or Forgiveness? Loan Modifications in Private Label Residential Mortgage-Backed Securities from 2008 to 2014

ABSTRACT I estimate the extent to which modifications of privately securitized mortgages increased or forgave debt during the Great Recession and aftermath, from 2008 to 2014. I find that loan modifications weakened household balance sheets by adding $20 billion to household debt, with the net amount of debt added per modification doubling from 2010 to 2014. I also find that the increase in debt is consistent with capitalization of fees, but not missed interest payments. Capitalization of fees is significant because it has been associated with a principal-agent problem between investors and mortgage servicers preventing efficient loss mitigation, as well as consumer financial protection abuses.

Financiarización y crisis del mercado hipotecario de viviendas nuevas para los trabajadores en México

Este trabajo tiene por objetivo analizar la organización y transformación institucional del sector financiero hipotecario en México. Para ello se realiza un análisis sobre el número y montos de inversión y circulación, tanto de créditos hipotecarios como de Bonos Respaldados por Hipotecas (BORHs). A partir de la crisis financiera global originada en el mercado hipotecario estadounidense, paradójicamente, se ha venido fomentado el crecimiento de la propiedad hipotecaria en México a través de su financiarización. Este proceso se ha llevado a cabo mediante el incremento acelerado de la participación en el mercado de BORHs por parte de instituciones públicas de financiamiento de vivienda; en contraste con el repliegue de entidades financieras privadas e instituciones bancarias. Al incremento en la emisión de bonos y el otorgamiento de créditos hipotecarios, corresponde también un incremento en la cantidad de viviendas deshabitadas; indicio de una crisis provocada por la sobreproducción de viviendas.

COVID-19 and Structured Finance Litigation: CMBS and CLO Disputes on the Horizon

This article describes the structure of the trillion-dollar CMBS and CLO markets and their current distressed states, given the ongoing economic effects of the COVID-19 pandemic. It then outlines various disputes that may arise from this distress. For CMBS, these include control and valuation disputes; waterfall disputes; “busted deal” disputes; REIT, “repo,” and margin call disputes; fraudulent selling and misrepresentation disputes; and repurchase claims. For CLOs, the potential disputes involve CLO managers, CLO arrangers, CLO investors and trustees, and CLO valuation issues. In each instance, the article describes the parties involved, the legal issues that are likely to arise, and—where possible—the applicable law from prior litigation in respect to the same or similar issues. The article concludes that many of these disputes are likely to result in litigation again soon, given the ongoing effects of the COVID-19 pandemic and current economic forecasts within the CMBS and CLO markets. <b>TOPICS:</b>CMBS and commercial mortgage loans, CLOs, CDOs, and other structured credit <b>Key Findings</b> • The world is facing a COVID-driven economic slowdown that many believe will expose flaws in the market for commercial mortgage-backed securities (CMBS) comparable to those seen in the residential mortgage-backed securities (RMBS) market in 2007–2008. • This broad, multisector, economic downturn is also likely to severely impact the hundreds of billions of dollars of collateralized loan obligations (CLOs) that have been issued in recent years. Wide-ranging, cross-sector defaults are expected for the loans that collateralize CLOs, and extreme loss severity is expected when those defaults occur. • Both CMBS and CLO industry participants and legal counsel involved, or looking to become involved in the industries, should scrutinize potential disputes closely and prepare for potential litigation in the near future.

Contagion versus Interdependence Across Regional U.S. Housing Markets and Implications for RMBS Geographic Diversification Strategy

Executive Summary Home prices in the United States often exhibit little (and sometimes even negative) correlation across different regions. This reflects segmentation in the national housing market and also provides an apparent opportunity for investors to diversify their exposure to regional downturns by creating residential mortgage-backed securities (RMBSs) out of geographically dispersed home loans. Unfortunately, in a crisis, correlations may rise, and the benefits from geographical diversification may disappear just when investors most desire them. Using a flexible generalized autoregressive conditional heteroscedasticity (GARCH) technique, I find that regional correlations indeed rose dramatically during the latest downturn, in some cases to unprecedented levels. Moreover, this increase in co-movement was clearly financial contagion, and not merely interdependence. Investors in mortgage-backed and other housing securities should thus not rely on house price correlations calculated during “normal” t...

Price Discovery in the Residential Mortgage-backed Security, Credit Default Swap, and ABX Markets

This paper analyzes price discovery among residential mortgage-backed securities (MBS), their credit default swaps (ABCDS), and the associated ABX contracts. VECM regressions show that the MBS and ABX markets lead price discovery over the ABCDS market. Neither the MBS nor the ABX market consistently dominate one another so that MBS and ABX markets respond to information simultaneously. Thus, while there is evidence that ABCDS were mispriced, there is no evidence for ABX market “overshooting” that was previously thought to have helped cause the recent mortgage market bubble and bust.

Liar’s Loans, Mortgage Fraud, and the Great Recession

ABSTRACT This paper contributes to research on misrepresentation in private residential mortgage-backed securities by using new data on losses from foreclosure to estimate higher than expected losses associated with income overstatement and adverse selection in no/low documentation loans, using full documentation loans as a counterfactual. Overall, no/low documentation loans account for $350 billion of the $500 billion lost from 2007 to 2012. No/low documentation loans lost an additional $5200 per loan, implying $97 billion of total no/low documentation losses were higher than expected. I also find underwriting exceptions differentially predict loss by documentation type, which provides evidence consistent with originator-led adverse selection.

Fair Value versus Amortized Cost Measurement and the Timeliness of Other-Than-Temporary Impairments: Evidence from the Insurance Industry

ABSTRACTWe investigate the impact of recurring fair value versus amortized cost measurement for accounting recognition purposes on the timeliness of insurers' other-than-temporary (OTT) impairments of non-agency residential mortgage-backed securities (NAMBS) around the 2007–2009 financial crisis. Unlike largely predetermined amortized cost measurement, recurring fair value measurement requires firms to invest in information and control systems to assess relevant economic conditions and estimate fair values quarterly. We expect these systems discipline insurers' OTT impairments. Exploiting statutory requirements that PC (life) insurers measure securities with NAIC designations from 3 to 5 at fair value (amortized cost) and disclose security-level accounting information, we predict and find that PC insurers record timelier OTT impairments of the same NAMBS with NAIC designations of 3 to 5 than life insurers. We predict and find weaker evidence of spillover effects to the timeliness of OTT impairments of the same NAMBS with NAIC designations of 1 or 2.JEL Classifications: G22; M41.Data Availability: Data are available from public sources cited in the text.

Risk Allocation Through Securitization – Evidence From Non-Performing Loans

Employing a unique and hand-collected sample of 648 true sale loan securitization transactions issued by 57 stock-listed banks across the EU-12 plus Switzerland over the period from 1997 to 2010, this paper empirically analyzes the relationship between true sale loan securitization and the issuing banks’ non-performing loans to total assets ratios (NPLRs). We provide evidence for an NPLR-reducing effect during the boom phase of securitizations in Europe suggesting that banks in our sample (partly) securitized NPLs as the most risky junior tranche and did not (fully) retain NPLs as a reputation and quality signal towards less informed investors in imperfect capital markets. In contrast, we find the reverse effect during the crises period in Europe indicating that issuing banks provided credit enhancement and demonstrated `skin in the game'. Our baseline result remains robust when controlling for endogeneity concerns and a potential persistence in the time series of the NPL data. Moreover, results from a variety of sensitivity analysis reveal that the NPLR-reducing effect is stronger for opaque securitization transactions, for issuing banks exhibiting higher average levels of NPLRs and for banks operating from non-PIIGS countries. In addition, a reduction of NPLRs through securitization is observed for issued collateralized debt obligations, residential mortgage-backed securities, consumer and other unspecified loans as well as for non-frequently issuing, systemically less important and worse-rated banks. Our analysis offers essential insights into the loan risk allocation process through securitization and provides important implications for the vital debate on reducing NPL exposures and the process of revitalizing and regulating the European securitization market.