scholarly journals Collateralized Debt Networks with Lender Default

2019 ◽  
Vol 2019 (083) ◽  
Author(s):  
Jin-Wook Chang ◽  
Keyword(s):  
Collateralized Debt

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

2021 ◽  
pp. 0308518X2110296
Author(s):  
Jonathan Beaverstock ◽  
Adam Leaver ◽  
Daniel Tischer
Keyword(s):  
Financial Networks ◽  
Regulatory Regime ◽  
Collateralized Debt Obligations ◽  
The Us ◽  
Collateralized Debt Obligation ◽  
Role Based ◽  
Collateralized Debt ◽  
Collateralized Loan Obligation ◽  
Debt Obligation ◽  
Peak Value

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.

scholarly journals Profit and Risk under Subprime Mortgage Securitization

2011 ◽  
Vol 2011 ◽  
pp. 1-64 ◽  
Author(s):  
M. A. Petersen ◽  
J. Mukuddem-Petersen ◽  
B. De Waal ◽  
M. C. Senosi ◽  
S. Thomas
Keyword(s):  
Risk Mitigation ◽  
Collateralized Debt Obligations ◽  
Mortgage Loans ◽  
Main Hypothesis ◽  
Subprime Mortgage ◽  
Important Indicator ◽  
Residential Mortgage ◽  
Maturity Mismatch ◽  
Mortgage Securitization ◽  
Collateralized Debt

We investigate the securitization of subprime residential mortgage loans into structured products such as subprime residential mortgage-backed securities (RMBSs) and collateralized debt obligations (CDOs). Our deliberations focus on profit and risk in a discrete-time framework as they are related to RMBSs and RMBS CDOs. In this regard, profit is known to be an important indicator of financial health. With regard to risk, we discuss credit (including counterparty and default), market (including interest rate, price, and liquidity), operational (including house appraisal, valuation, and compensation), tranching (including maturity mismatch and synthetic) and systemic (including maturity transformation) risks. Also, we consider certain aspects of Basel regulation when securitization is taken into account. The main hypothesis of this paper is that the SMC was mainly caused by the intricacy and design of subprime mortgage securitization that led to information (asymmetry, contagion, inefficiency, and loss) problems, valuation opaqueness and ineffective risk mitigation. The aforementioned hypothesis is verified in a theoretical- and numerical-quantitative context and is illustrated via several examples.

ON DEFAULT CORRELATION AND PRICING OF COLLATERALIZED DEBT OBLIGATION BY COPULA FUNCTIONS

2006 ◽  
Vol 05 (03) ◽  
pp. 483-493 ◽  
Author(s):  
PING LI ◽  
HOUSHENG CHEN ◽  
XIAOTIE DENG ◽  
SHUNMING ZHANG
Keyword(s):  
Credit Derivatives ◽  
Copula Function ◽  
Dependence Structure ◽  
Default Correlation ◽  
Specific Kind ◽  
Copula Functions ◽  
Recovery Rates ◽  
Collateralized Debt Obligation ◽  
Collateralized Debt ◽  
Debt Obligation

Default correlation is the key point for the pricing of multi-name credit derivatives. In this paper, we apply copulas to characterize the dependence structure of defaults, determine the joint default distribution, and give the price for a specific kind of multi-name credit derivative — collateralized debt obligation (CDO). We also analyze two important factors influencing the pricing of multi-name credit derivatives, recovery rates and copula function. Finally, we apply Clayton copula, in a numerical example, to simulate default times taking specific underlying recovery rates and average recovery rates, then price the tranches of a given CDO and then analyze the results.

Dynamic alpha-stable method for CDO pricing

2014 ◽  
Vol 01 (03) ◽  
pp. 1450028
Author(s):  
Hua Li ◽  
George Yuan ◽  
Weina Chen ◽  
Li Guo ◽  
Jianbin Zhao
Keyword(s):  
Risk Management ◽  
Stable Model ◽  
Stable Method ◽  
Copula Method ◽  
Static Factor ◽  
Cdo Pricing ◽  
Collateralized Debt Obligation ◽  
Collateralized Debt ◽  
Credit Portfolio ◽  
Debt Obligation

The goal of this paper is to develop the dynamic alpha (α)-stable method for collateralized debt obligation (CDO) pricing based on the α-stable distributions, which will resolve the two issues caused by using traditional static factor copula method in the practice, which means when pricing CDOs, the traditional static factor Copula method does not only exhibit the correlation smile phenomenon which is not inconsistent with the model's assumption, but also cannot be used in pricing CDOs or credit portfolio derivatives for the underlying portfolio with different maturities. As the applications, we present calibration and empirical numerical results for iTraxx Europe Tranches quotes from the market data on March 30, 2007. Thus, our new method under the framework of the dynamic α-stable model is the way for CDO pricing in the practice, and should be useful for the risk management in the practice too.

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