Credit Derivatives and Collateralized Debt Obligations

2013 ◽  
pp. 473-492
Keyword(s):  
Credit Derivatives ◽  
Collateralized Debt Obligations ◽  
Collateralized Debt

scholarly journals Mathematical Estimation Methods and Models for Industrial Companies

2021 ◽  
Vol 248 ◽  
pp. 03001
Author(s):  
Olga Stikhova
Keyword(s):  
Risk Estimation ◽  
Credit Derivatives ◽  
Secondary Market ◽  
Estimation Methods ◽  
Collateralized Debt Obligations ◽  
Industrial Companies ◽  
Modeling Process ◽  
Credit Default ◽  
Collateralized Debt ◽  
The Given

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.

Financial Innovation and Institutional Voices in the Canadian Press: A Look at the Roaring 2000s

2018 ◽  
Vol 55 (3) ◽  
pp. 383-405 ◽  
Author(s):  
Pier-Pascale Boulanger ◽  
Chantal Gagnon
Keyword(s):  
Critical Discourse Analysis ◽  
Credit Derivatives ◽  
Critical Discourse ◽  
Collateralized Debt Obligations ◽  
Financial Innovations ◽  
Credit Default ◽  
The Press ◽  
Commercial Paper ◽  
Collateralized Debt ◽  
Assisted Analysis

This corpus-assisted analysis examines seven Canadian newspapers from 2001 to 2008 in English and in French. It focuses on the speech that journalists reported when covering new financial instruments, namely collateralized debt obligations, credit default swaps, and asset-backed commercial paper. Eight years of news were surveyed with a concordancer and the data were analyzed using critical discourse analysis. The data show a wider range of voices in the English subcorpus when compared with the French. In both subcorpora, however, journalistic attitude was neutral and critical voices were deselected, while institutional voices such as those of banks were foregrounded. If polyphony is understood as the inclusion of an array of voices from the community, our study shows that the press was monophonic. Concurrently, our investigation of the Canadian press reveals that financial innovations were not covered until 2007, when credit derivatives started to falter.

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.

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