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)

How financial products organize spatial networks: Analyzing collateralized debt obligations and collateralized loan obligations as “networked products”

During the 2010s, collateralized loan obligations rapidly became a trillion-dollar industry, mirroring the growth profile and peak value of its cousin—collateralized debt obligations—in the 2000s. Yet, despite similarities in product form and growth trajectory, surprisingly little is known about how these markets evolved spatially and relationally. This paper fills that knowledge gap by asking two questions: how did each network adapt to achieve scale at speed across different jurisdictions; and to what extent does the spatial and relational organization of today's collateralized loan obligation structuration network, mirror that of collateralized debt obligations pre-crisis? To answer those questions, we draw on the global financial networks approach, developing our own concept of the networked product to explore the agentic qualities of collateralized debt obligations and collateralized loan obligations—specifically how their technical and regulatory “needs” shape the roles and jurisdictions enrolled in a global financial network. We use social network analysis to map and analyze the evolving spatial and relational organization that nurtured this growth, drawing on data harvested from offering circulars. We find that collateralized debt obligations spread from the US to Europe through a process of transduplication—that similar role-based network relations were reproduced from one regulatory regime to another. We also find a strong correlation between pre-crisis collateralized debt obligation- and post-crisis collateralized loan obligation-global financial networks in both US$- and €-denominations, with often the same network participants involved in each. We conclude by reflecting on the prosaic way financial markets for ostensibly complex products reproduce and the capacity for network stabilities to produce market instabilities.

Mathematical Estimation Methods and Models for Industrial Companies

The collateralized debt obligations and credit default swaps applications are shown in this paper. The industry obligations secondary market risk estimation methods are considered in this work. The new methods taking into account statistically significant parameters for industrial credit derivatives portfolio are offered for single-name investment risks numerical experiments realization. The mathematical estimation of tranche were shown. The single and multiple name default obligations necessary mathematical modeling methods and formulae for the industrial materials manufacturers derivative credit tools market are shown. It is determined that the portfolio of synthetic debt tools is made of the given parameters. The task of a loss derivative tranches mathematical estimation is solved. Late defaults raise the equity tranches payment required sums with high spreads, early defaults reduce. Also the functional characteristics required for an estimation huge debts problem solving are partly considered in this paper. The problem of the default modeling for market tools and numerical simulation of the obligations influence on conditions of current bistability mode are shown here. Some credit derivatives of industrial manufacturers are demonstrated in the modeling process of default as an example. It is found that the model is an additional factor help us to estimate the default opportunity.

Ethical Challenges of Complex Products: Case of Goldman Sachs and the Synthetic Collateralized Debt Obligations

In analyzing complex products, this study selected the company Goldman Sachs and one of its product offerings, the synthetic collateralized debt obligation (synthetic CDO). The study later analyzed the ethical implications of providing such a complex product to customers. A review of the literature indicates that researchers identified this product and other associated derivatives of the mortgage backed securities as the main causes of the 2008 financial crisis in the United States of America. As such, Goldman Sachs’ offering of the product posed ethical and moral issues. An analysis of the company and its offering was done under the lenses of various ethical theories such as Kohlberg's theory of moral reasoning, the Kantian ethics, the utilitarian perspective, Friedman’s shareholder theory, the stakeholder theory, the market approach to consumer protection, and the contract view of consumer protection. Besides Friedman’s shareholder theory, all other theories judged the product offering morally wrong and unethical. At the end of the study, the author suggested a contribution to knowledge regarding Kohlberg’s theory of moral reasoning in its application to organizations. The author also suggested further research to validate the outcome of Friedman’s shareholder theory regarding this case.

Collateralized Debt Obligations, Collateralized Bond Obligations, and Collateralized Loan Obligations

Collateralized debt obligations (CDOs) are structured products that are issued by a special purpose vehicle with the objective of improving the issuer’s balance sheet, increasing access to illiquid securities, and/or generating a higher yield than would be offered in a traditional fixed income security. This chapter provides an overview of CDOs including a discussion on the history, structure, uses, and impact on investors and the broader financial system. CDOs can be further classified by the type of security held as collateral, such as collateralized bond obligations (CBOs), which typically hold high yield debt, and collateralized loan obligations (CLOs), which hold bank loans. These financial structured products gain notoriety for their role in the financial crisis of 2007–2008 and have since declined in popularity. Despite the negative perception that CDOs carry, securitization continues to play an important function in the financial system and offers benefits to issuers and consumers as long as both parties use the end product responsibly.

Securitized Debt Markets

Securitized debt markets play a vital role in financial markets in risk-sharing and creating alternative financing sources, which provide benefits for both borrower and lenders. This chapter describes the main characteristics of securitized debt and securitized debt instruments. Major securitized debt instruments are mortgage-backed securities (MBSs) including residential mortgage-backed securities (RMBSs) and commercial mortgage-backed securities (CMBSs) as well as asset backed commercial paper (ABCP) and collateralized debt obligations (CDOs). The characteristics of these securities, their associated benefits and uses, and the risk factors that determine the performance of securitized debt instruments are covered. The evolution and size of these securitized markets is also discussed. Overall, the chapter indicates that securitized markets help originators in transferring risks and monetizing illiquid assets and aid investors by providing an efficient mechanism for portfolio diversification and ability to better adjust their investments to their risk preferences.

HEDGING OF SYNTHETIC CDO TRANCHES WITH SPREAD AND DEFAULT RISK BASED ON A COMBINED FORECASTING APPROACH

Hedging of credit derivatives, especially the Collateralized Debt Obligations (CDOs), is the prerequisite of risk management in financial market. Since both spread risk and default risk exist, the models in existing literature resort to the incomplete-market theory to derive the hedging strategies. From another point of view, the construction of hedging strategies of CDO might be regarded as the process of forecasting the changes in value of CDO by the changes in value of hedging instruments. Based on this idea, this paper proposes an alternative hedging approach via the combined forecasting and regression techniques, where the two individual forecasting models are Gaussian copula model and local intensity model, used to hedge against spread risk and default risk, respectively. Finally, the dynamic hedge ratios of CDO tranches with CDS index are derived. A numerical analysis is carried out and the hedge ratios obtained by the new models are compared with those from actual market spreads. It is shown that the model derived in this paper not only provides hedging strategies which agree with the market hedge ratios but that can be effectively implemented as well.

5. Credit risk

Credit risk is the risk that your counterparty might default on future obligations. There are a small number of credit rating agencies operating globally that assign a credit rating to each company under consideration. ‘Credit risk’ explains credit risk modelling and analysis, including credit default swaps, multi-asset credit risk, and collateralized debt obligations. Credit risk models are divided into two main categories: ‘structural form’ and ‘reduced form’. A pervasive problem in credit risk modelling is that while some parameters can be backed out by the calibration process, there are usually others about which the available data is insufficient for us to do anything more than take an educated guess.