Collateralized Debt Obligations Research Articles

Collateralized Commodity Obligations: Modeling and Risk Assessment

In this article the authors address the risk characteristics and rating of Collateralized Commodity Obligations (CCO), which are recently devised structured products similar to the Collateralized Debt Obligation (CDO). Commodities as an asset class have been in the spotlight of investors’ attention for the past decade. CCOs, which are fixed income instruments, provide fixed income investors an exposure to commodity markets. The underlying assets of a CCO are Commodity Trigger Swaps (CTS); these are similar to Credit Default Swaps, but instead of a default, a “trigger” occurs when a commodity price reaches a certain pre-set level. Rating agencies have used their CDO evaluators to rate CCOs, however particular characteristics of commodity prices and an abundance of historical price data for commodities render such an approach questionable. Recently, S&amp;P has withdrawn its ratings for CCOs, which may be linked to some concerns regarding their rating approach. The authors examine the historical performance of CCOs and propose two novel approaches to their rating. The first is a flexible multivariate parametric model for commodity prices: a mean-reversion model with correlated trends. The second approach is close in spirit to the historical simulation method for risk management and is based on the block bootstrap technique. The authors apply both approaches to an example of a CCO and compare the results to the ratings provided by the rating agencies. They find that simulated ratings are sensitive to the model assumptions; the default probabilities resulting from the agencies’ ratings underestimate both historically observed and bootstrap-simulated default probabilitie; and the non-parametric approach most closely matches the historically observed probabilities of default. The results demonstrate the benefit of a data-driven, non-parametric modeling approach to rating CCOs. <b>TOPICS:</b>Commodities, CLOs, CDOs, and other structured credit, information providers/credit ratings, statistical methods

The impact of collateralized debt obligation arbitrage on tranching and financial leverage of structured finance securities

For several years leading up to the outbreak of the financial crisis, growth in the use of arbitrage collateralized debt obligations (CDOs) was explosive. In this paper, we discuss potential sources of such arbitrage opportunities, in particular, potential gains due to "bond-like pricing". For this purpose, we examine the risk profiles of CDOs in some detail, which reveals significant differences between CDO tranches and corporate bonds, in particular concerning a considerably increased sensitivity to systematic risks. Treating the structured products as singlename instruments allows us to quantify these differences. We then price CDO tranches approximately with the Merton model, similar to corporate bonds. Using a sample CDO portfolio, we describe some opportunities for "CDO arbitrage" when investors consider corporate and CDO bonds as substitute investments and use bond-like pricing. We then discuss how tranches with high systematic risk can be generated and how CDO arrangers can exploit this to their advantage. It comes as no surprise that precisely these types of structures featured in many of the CDOs issued prior to the outbreak of the financial crisis.

Toward model value-at-risk: bespoke CDO tranches, a case study

In the aftermath of the subprime crisis the importance of model risk has come to be understood, leading regulators to ask for model risk measurement and management in financial institutions. On the other hand, in spite of recent advances, the subject still lacks a clear and widely accepted methodology as is the case for market or credit risk: although the methods in these fields are questioned and can be improved, there is, as far as practical issues are concerned, a wide acceptance of some guiding principles. This is not the case for model risk. We argue that the mainstream research has to be supplemented by new insights and methods when it comes, for example, to over-the-counter credit products. We propose, in particular, a new method, called model value-at-risk, that aims to answer such questions as, what is the model-dependent value-at-risk of an investment at one year at a confidence level of 95%? We have chosen the case study of bespoke collateralized debt obligation tranches, but most of our reasoning could be adapted to other complex contracts where market prices are not available and the choice of benchmark pricing method is subject to uncertainty: for example, mortgage-backed and residential mortgage-backed securities, collateralized loan obligations, leveraged buyouts and real options. These topics will be the subject of further research.

Analysis of Systematic Risks in Multi-Name Credit and Equity Markets

In this paper, we present an intensity-based common factor model that is used to analyze the valuation of common systematic risks in multi-name credit and equity markets. In particular, we use a hybrid intensity model to price single-name credit instruments such as credit default swaps (CDSs), multi-name credit derivatives such as collateralized debt obligations (CDOs), and equity index options such as calls and puts on the S&P 500. Once we have the expressions for the model prices of these instruments, we then calibrate the model parameters to fit the market data. We study two problems, the “forward” and “backward” problems: in the former, we start from equity index options and then compute the CDO tranche spreads, while in the latter, we fit the parameters to the CDO tranche spreads and then compute the equity index option prices and implied volatilities. We find that, based on our hybrid model, the systematic risks in the two markets were similar from 2004 to 2007, while the credit market incorporated far greater systematic risk than the equity market during the financial crisis from 2008 to 2010.

Valuation of collateralized debt obligations with hierarchical Archimedean copulae

Abstract Modelling portfolio credit risk is one of the crucial challenges faced by financial services industry in the last few years. We propose the valuation model of collateralized debt obligations (CDO) based on hierarchical Archimedean copulae (HAC) with up to three parameters, with default intensities calibrated to market data and with random loss given defaults that are correlated with default times. The methods presented are used to reproduce the spreads of the iTraxx Europe tranches. Our approach describes the market prices better than the standard pricing procedure based on the Gaussian distribution. We also obtain a flat correlation smile across tranches thereby solving the implied correlation puzzle.

Regulating Performance-Enhancing Technologies

This article compares the efforts to govern performance enhancement technologies in two seemingly different competitive arenas—financial markets and professional cycling—where the pressures to outperform are enormous. In the two decades prior to the 2007 financial crisis, new derivative financial commodities such as collateralized debt obligations (CDOs) were created to “juice up” investment returns for extraordinary profits. Over roughly the same period, the development and use of blood boosting drugs and technologies brought so-called doping by cyclists to new levels of complexity and sophistication with extraordinary race results and new levels of commercialization of the sport. The efforts to “turbocharge” their respective competitive spaces took place within complicated regimes of self-regulation that had strikingly dissimilar narratives about performance enhancement and, consequently, different technologies for control. Looking across these seemingly disparate cases draws our attention to how regulation fits into the assemblage of competition and prospects for reform.

Calibrating probability distributions with convex-concave-convex functions: application to CDO pricing

This paper considers a class of functions referred to as convex-concave-convex (CCC) functions to calibrate unimodal or multimodal probability distributions. In discrete case, this class of functions can be expressed by a system of linear constraints and incorporated into an optimization problem. We use CCC functions for calibrating a risk-neutral probability distribution of obligors default intensities (hazard rates) in collateral debt obligations (CDO). The optimal distribution is calculated by maximizing the entropy function with no-arbitrage constraints given by bid and ask prices of CDO tranches. Such distribution reflects the views of market participants on the future market environments. We provide an explanation of why CCC functions may be applicable for capturing a non-data information about the considered distribution. The numerical experiments conducted on market quotes for the iTraxx index with different maturities and starting dates support our ideas and demonstrate that the proposed approach has stable performance. Distribution generalizations with multiple humps and their applications in credit risk are also discussed.

CDO Surfaces Dynamics

Modelling the dynamics of credit derivatives is a challenging task in nance and economics. The recent crisis has shown that the standard market models fail to measure and forecast nancial risks and their characteristics. This work studies risk of collateralized debt obligations (CDOs) by investigating the evolution of tranche spread surfaces and base correlation surfaces using a dynamic semiparametric factor model (DSFM). The DSFM oers a combination of exible functional data analysis and dimension reduction methods, where the change in time is linear but the shape is nonparametric. The study provides an empirical analysis based on iTraxx Europe tranches and proposes an application to curve trading strategies. The DSFM allows us to describe the dynamics of all the tranches for all available maturities and series simultaneously which yields better understanding of the risk associated with trading

Rating Shopping or Catering?An Examination of the Response to Competitive Pressure for CDO Credit Ratings

We examine whether shopping or catering is a more accurate characterization of rating agency interactions regarding collateralized debt obligations (CDOs). Although investors paid a premium for dual ratings, AAA CDO tranches rated by both Moody's and S&P defaulted more frequently than tranches rated by only one of them, which is inconsistent with pure rating shopping. Rating agencies made upward adjustments beyond their model when their competitor had more lenient assumptions. Finally, consistent with rating catering, S&P's and Moody's adjustments and disagreements at security issuance were reflected in subsequent rating downgrades, suggesting that adjustments were harmful. The Author 2013. Published by Oxford University Press on behalf of The Society for Financial Studies. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com., Oxford University Press.

Dynamic Implied Correlation Modeling and Forecasting in Structured Finance

AbstractCorrelations are the main drivers for credit portfolio risk and constitute a major element in pricing credit derivatives such as synthetic single‐tranche collateralized debt obligation swaps. This study suggests a dynamic panel regression approach to model and forecast implied correlations. Random effects are introduced to account for unobservable time‐specific effects on implied tranche correlations. The implied‐correlation forecasts of tranche spreads are compared to forecasts using historical correlations from asset returns. The empirical findings support our proposed dynamic mixed‐effects regression correlation model. © 2013 Wiley Periodicals, Inc. Jrl Fut Mark

A Multivariate Default Model with Spread and Event Risk

We present a new portfolio default model based on a conditionally independent and identically distributed (CIID) structure of the default times. It combines an intensity-based ansatz in the spirit of Duffie and Gârleanu (2001). Risk and valuation of collateralized debt obligations. Financial Analysts Journal, 57(1), 41–59. with the Lévy subordinator concept introduced in Mai and Scherer (2009). A tractable multivariate default model based on a stochastic time-change. International Journal of Theoretical and Applied Finance, 12(2), 227–249. We aim at exploiting the computational advantages of the CIID framework for evaluating multiname credit derivatives, while incorporating two central drivers for credit products. More precisely, we allow for both a dynamic evolution of the portfolio credit default swap (CDS) spread (unlike static copula models) and cataclysmic events allowing for simultaneous defaults (unlike intensity-based portfolio loss processes). While the former feature is considered to be crucial for consistently hedging credit products, the second property is supposed to take into account default clusters and the market’s fear of extreme events. For applications, the model is approximated by a related top-down representation of the portfolio loss process. It is shown how to coherently calculate hedging deltas for collateralized debt obligations (CDOs) w.r.t. portfolio CDS and how to consistently calibrate the model to the two products. Both tasks solely require the computation of one-dimensional (Laplace inversion) integrals and can be carried out within fractions of a second. Illustrating the stability and functionality of the pricing approach, the new model and the models it is related to are calibrated to a daily time-series of iTraxx Europe index CDS and CDOs. We find the fitting results of the presented model to be very promising and conclude that it may be used for the dynamic pricing and hedging of credit derivatives.

Swaps Regulation: Commodity Pools, Clearing, and Margin

This panel was held on Monday, January 28, 2013, at the ASF 2013 conference. Panelists discussed the developing impact of swap regulation on securitization and what it means for the ability to use swaps in securitization as new regulations take effect. The Dodd–Frank Act added a definition of the term “commodity pool,” and the Commodity Exchange Act revised the definition of the term “commodity pool operator.” As a result, many securitizations that held swaps, often solely to hedge interest rate or currency mismatches between their assets and their liabilities, were at risk of being considered commodity pools. By the time the panel took place, however, the Commodities Futures Trading Commission had granted two significant pieces of interpretive guidance and no-action relief that together excluded most traditional securitizations (e.g., credit card or auto loan securitizations), most asset-backed commercial paper programs, many CLOs and CDOs (collateralized loan obligations and collateralized debt obligations), and most covered bond transactions from the definition of a commodity pool. The panel focused on the relief that was granted and the issues that remained to be resolved. The panel also discussed the aspects of entering a swap that would be different for a securitization now than it would have been a year ago. The most significant changes have not yet become effective. Those include clearing and margin requirements and, eventually, a requirement to transact on a designated contract market or swap execution facility if the swap has been “made available to trade” on such a facility. One of the cornerstones of Dodd–Frank’s swap regulations is the requirement that swaps be cleared through a central counterparty. Whether a swap will need to be cleared depends on the identities of the counterparties, the nature of the swap, and whether a derivatives clearing organization is willing to clear it. Even if a swap is not required to be cleared, it may still be subject to margin requirements and margin calls. <b>TOPICS:</b>Interest-rate and currency swaps, credit default swaps

An analytical approach for systematic risk sensitivity of structured finance products

The global financial crisis has shown that many financial institutions dealing with credit derivatives were exposed to severe unexpected losses. This indicates that systematic influences are decisively underestimated particularly with regard to structured products like securitized tranches of collateralized debt obligations. Our analytical study addresses these systematic effects: We provide a simple model which allows a closed-form comparison of both bonds and tranches with respect to their systematic risk. We demonstrate that the exposure to systematic risk of tranches may be many times higher than the exposure of bonds, even if both products share the same rating grade, e.g., an ‘AAA’ rating, measured by either default probability or expected loss. Particularly in economic downturns, default rates of tranches may be multiples of those of bonds. Our results help understand high default rates of tranches during the financial crisis and show that classical ratings are insufficient metrics for measuring risks of structured products.

On Dynamic Hedging of Single-Tranche Collateralized Debt Obligations

This study deals with the dynamic hedging of single-tranche collateralized debt obligations (STCDOs). As a first step, we specify a top-down affine factor model in which a catastrophic risk component is incorporated in order to capture the dynamics of super-senior tranches. Next, we derive the model-based variance-minimizing strategy for the hedging of STCDOs with a dynamically rebalanced portfolio on the underlying index swap. We analyze the actual performance of the variance-minimizing and the model-free regression-based hedging on the iTraxx Europe data. Results of the in-sample hedging analysis indicate that the regression-based hedge outperforms the variance-minimizing hedge based on various criteria. In order to assess the two hedging strategies further, we run a simulation analysis where normal and extreme loss scenarios are generated via the method of importance sampling. Performing the hedging analysis on the set of simulated scenarios we find that, overall, the variance-minimizing strategy is more effective in terms of yielding less riskier hedging portfolios.

Anatomy of ABS CDO: Why Do ABS CDOs Exist?

This paper investigates the ABS CDOs (Asset-Backed Security Collateralized Debt Obligations) market between 2005 and 2007 and answers the question of why ABS CDOs exist. The dataset used in this paper contains 516 ABS CDOs, 4,023 CDO tranches, and 79,724 securities used as the collateral of ABS CDOs. Using detailed collateral information on ABS CDOs, I find that there is a large re-securitization rate distinction between AAA- and non AAA-rated tranches. Less than 1% of AAA-rated subprime MBS tranches were used as collateral for cash flow ABS CDOs. In contrast, more than half of non AAA-rated subprime tranches were re-securitized through cash flow CDO.I also show that the reference portfolio of synthetic CDOs consists to a large degree of BBB rated subprime mortgage backed securities. As a notional amount, $94 billion out of $172 billion, which was the total collateral amount of synthetic CDOs, was comprised of BBB-rated subprime MBS tranches. It is evident that the synthetic CDO market deteriorated due to short demand in the housing sector, but there is no evidence that the cash flow ABS CDO market deteriorated between 2005 and 2007.

A Dynamic Affine Factor Model for the Pricing of Collateralized Debt Obligations

We propose an affine two-factor model for the pricing of single-tranche collateralized debt obligations by following the general top-down framework introduced in Filipovic et al. [2011]. Apart from being analytically tractable, this model has the feature that it incorporates a catastrophic risk component as a tool to capture the dynamics of super-senior tranches. To appraise the actual performance of the model we run an estimation analysis based on the quasi-maximum likelihood approach in conjunction with the Kalman filter. Our findings suggest that the two-factor model is successful in describing the iTraxx Europe data set which covers the time period including the recent credit crisis.

Pricing synthetic collateralized debt obligations based on exponential approximations to the payoff function

Pricing synthetic collateralized debt obligations based on exponential approximations to the payoff function

A mathematical model for multi-name credit based on community flocking

We present a new mathematical model for multi-name credit that employs stochastic flocking. Flocking mechanisms have been used in a variety of models of biological, sociological and physical aggregation phenomena. As a direct application of a flocking mechanism, we introduce a credit risk model based on community flocking for a credit worthiness index. Correlations between different credit worthiness indices are explained in terms of communication rates and coupling strengths from the flocking system. Based on the flocking model, we compute credit curves for individual names and default time distributions. We also apply the proposed model to the pricing of credit derivatives such as credit default swaps and collateralized debt obligations.

Research Analyst Perspectives: FindingRelative Value in the CLO Market

This panel covered how collateralized loan obligations (CLOs) are similar or different from collateralized debt obligations (CDOs) and other ABS products, the inherent CLO liquidity premium, how value is analyzed across a CLO’s capital structure, how to distinguish between values in the primary (new issue) and secondary CLO markets, whether various CLOs today seem rich or cheap, risks related to differences in CLO documentation across different deals, and how CLO equity compares to other alternative investments.

Credit derivatives and the Dodd–Frank Act: Is the regulatory response appropriate?

Credit derivatives played an important role in the Credit Crisis of 2008-09. The US Congress enacted the Dodd-Frank Wall Street Reform and Consumer Protection Act in 2010 as a comprehensive response to the Credit Crisis. Collateralized Debt Obligations (CDO) and Credit Default Swaps (CDS), which are among the major credit derivatives developed by the financial industry in the recent decades, are among the subjects covered in the lengthy Dodd-Frank legislation. Regulation seeks to streamline trade in derivatives and promote smooth clearing and settlement of transactions. There is little effort either to identify the systemic risk in credit derivatives or to address the issue of risk.In this paper, I review the measures proposed in the Dodd-Frank Act for regulating credit derivatives and question their adequacy. The Dodd-Frank Act merely attempts to improve the procedures or mechanics governing the trade in credit derivatives and promote prudential standards for the entities dealing in swaps. These are obviously inspired by experience – namely, freezing of the market during the Credit Crisis and companies such as AIG issuing Credit Default Swaps without serious concern about their ability to honor the obligations assumed under the contracts.The issue is whether the regulatory response is adequate from a systemic perspective. This question is important if the goal is to prevent a recurrence of events like the Credit Crisis and the events that led up to the Crisis. In considering this question, a major issue with the Dodd-Frank Act is its failure to sufficiently address the character of the swap instruments, in particular the credit derivatives as they were developed in the market and the risk potential that is engineered in them.I present a proposal in the paper for a screening procedure before the launch of financial instruments. Screening can help generate an informed and reasonably disinterested debate on the planned instruments, and this can lead to a better understanding of their characteristics and risk potential. The procedure would not seriously interfere with the freedom of the market to innovate and devise new financial products, but at the same time it can instill elements of caution and deliberation in the process. The paper also deals with other issues such as the transaction cost of the screening process, any intellectual property rights in the new products and a more basic constitutional issue – the liberty of contract.