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Correlation Between Intensity and Recovery in Credit Risk Models

Correlation Between Intensity and Recovery in Credit Risk Models PDF Author: Raquel M. Gaspar
Publisher:
ISBN:
Category :
Languages : en
Pages : 44

Book Description
There has been increasing support in the empirical literature that both the probability of default (PD) and the loss given default (LGD) are correlated and driven by macroeconomic variables. Paradoxically, there has been very little effort from the theoretical literature to develop credit risk models that would include this possibility.The goals of this paper are: first, to develop the theoretical reduced-form framework needed to handle stochastic correlation of recovery and intensity, proposing a new class of models; second, to understand under what conditions would our class of models reflect empirically observed features and, finally, to use concrete model from our class to study the impact of this correlation in credit risk term structures.We show that, in our class of models, it is possible to model directly empirically observed features. For instance, we can define default intensity and losses given default to be higher during economic depression periods - the well-know credit risk business cycle effect. Using the concrete model we show that in reduced-form models different assumptions - concerning default intensities, distribution of losses given default, and specifically their correlation - have a significant impact on the shape of credit spread term structures, and consequently on pricing of credit products as well as credit risk assessment in general.Finally, we propose a way to calibrate this class of models to market data, and illustrate the technique using our concrete example using US market data on corporate yields.

Correlation Between Intensity and Recovery in Credit Risk Models

Correlation Between Intensity and Recovery in Credit Risk Models PDF Author: Raquel M. Gaspar
Publisher:
ISBN:
Category :
Languages : en
Pages : 44

Book Description
There has been increasing support in the empirical literature that both the probability of default (PD) and the loss given default (LGD) are correlated and driven by macroeconomic variables. Paradoxically, there has been very little effort from the theoretical literature to develop credit risk models that would include this possibility.The goals of this paper are: first, to develop the theoretical reduced-form framework needed to handle stochastic correlation of recovery and intensity, proposing a new class of models; second, to understand under what conditions would our class of models reflect empirically observed features and, finally, to use concrete model from our class to study the impact of this correlation in credit risk term structures.We show that, in our class of models, it is possible to model directly empirically observed features. For instance, we can define default intensity and losses given default to be higher during economic depression periods - the well-know credit risk business cycle effect. Using the concrete model we show that in reduced-form models different assumptions - concerning default intensities, distribution of losses given default, and specifically their correlation - have a significant impact on the shape of credit spread term structures, and consequently on pricing of credit products as well as credit risk assessment in general.Finally, we propose a way to calibrate this class of models to market data, and illustrate the technique using our concrete example using US market data on corporate yields.

On Recovery and Intensity's Correlation - A New Class of Credit Risk Models

On Recovery and Intensity's Correlation - A New Class of Credit Risk Models PDF Author: Raquel M. Gaspar
Publisher:
ISBN:
Category :
Languages : en
Pages : 28

Book Description
We start by presenting a reduced-form multiple default type of model and derive abstract results on the influence of a state variable X on credit spreads, when both the intensity and the loss quota distribution are driven by X. The aim is to apply the results to a concrete real life situation, namely, to the influence of macroeconomic risks on credit spreads term structures.There has been increasing support in the empirical literature that both the probability of default (PD) and the loss given default (LGD) are correlated and driven by macroeconomic variables. Paradoxically, there has been very little effort from the theoretical literature to develop credit risk models that would include this possibility. A possible justification has to do with the increase in complexity this leads to, even for the quot;treatablequot; default intensity models.The goal of this paper is to develop the theoretical framework needed to handle this situation and, through numerical simulation, understand the impact on credit risk term structures of the macroeconomic risks. In the proposed model the state of the economy is modeled trough the dynamics of a market index, that enters directly on the functional form of both the intensity of default and the distribution of the loss quota q given default. Given this setup, we are able to make periods of economic depression, periods of higher default intensity as well as periods where low recovery is more likely, producing a business cycle effect. Furthermore, we allow for the possibility of an index volatility that depends negatively on the index level and show that, when we include this realistic feature, the impacts on the credit spread term structure are emphasized.

Advances in Credit Risk Modeling and Management

Advances in Credit Risk Modeling and Management PDF Author: Frédéric Vrins
Publisher: MDPI
ISBN: 3039287605
Category : Business & Economics
Languages : en
Pages : 190

Book Description
Credit risk remains one of the major risks faced by most financial and credit institutions. It is deeply connected to the real economy due to the systemic nature of some banks, but also because well-managed lending facilities are key for wealth creation and technological innovation. This book is a collection of innovative papers in the field of credit risk management. Besides the probability of default (PD), the major driver of credit risk is the loss given default (LGD). In spite of its central importance, LGD modeling remains largely unexplored in the academic literature. This book proposes three contributions in the field. Ye & Bellotti exploit a large private dataset featuring non-performing loans to design a beta mixture model. Their model can be used to improve recovery rate forecasts and, therefore, to enhance capital requirement mechanisms. François uses instead the price of defaultable instruments to infer the determinants of market-implied recovery rates and finds that macroeconomic and long-term issuer specific factors are the main determinants of market-implied LGDs. Cheng & Cirillo address the problem of modeling the dependency between PD and LGD using an original, urn-based statistical model. Fadina & Schmidt propose an improvement of intensity-based default models by accounting for ambiguity around both the intensity process and the recovery rate. Another topic deserving more attention is trade credit, which consists of the supplier providing credit facilities to his customers. Whereas this is likely to stimulate exchanges in general, it also magnifies credit risk. This is a difficult problem that remains largely unexplored. Kanapickiene & Spicas propose a simple but yet practical model to assess trade credit risk associated with SMEs and microenterprises operating in Lithuania. Another topical area in credit risk is counterparty risk and all other adjustments (such as liquidity and capital adjustments), known as XVA. Chataignier & Crépey propose a genetic algorithm to compress CVA and to obtain affordable incremental figures. Anagnostou & Kandhai introduce a hidden Markov model to simulate exchange rate scenarios for counterparty risk. Eventually, Boursicot et al. analyzes CoCo bonds, and find that they reduce the total cost of debt, which is positive for shareholders. In a nutshell, all the featured papers contribute to shedding light on various aspects of credit risk management that have, so far, largely remained unexplored.

Credit Risk: Modeling, Valuation and Hedging

Credit Risk: Modeling, Valuation and Hedging PDF Author: Tomasz R. Bielecki
Publisher: Springer Science & Business Media
ISBN: 3662048213
Category : Business & Economics
Languages : en
Pages : 517

Book Description
The motivation for the mathematical modeling studied in this text on developments in credit risk research is the bridging of the gap between mathematical theory of credit risk and the financial practice. Mathematical developments are covered thoroughly and give the structural and reduced-form approaches to credit risk modeling. Included is a detailed study of various arbitrage-free models of default term structures with several rating grades.

Credit Risk Management In and Out of the Financial Crisis

Credit Risk Management In and Out of the Financial Crisis PDF Author: Anthony Saunders
Publisher: John Wiley & Sons
ISBN: 0470622369
Category : Business & Economics
Languages : en
Pages : 373

Book Description
A classic book on credit risk management is updated to reflect the current economic crisis Credit Risk Management In and Out of the Financial Crisis dissects the 2007-2008 credit crisis and provides solutions for professionals looking to better manage risk through modeling and new technology. This book is a complete update to Credit Risk Measurement: New Approaches to Value at Risk and Other Paradigms, reflecting events stemming from the recent credit crisis. Authors Anthony Saunders and Linda Allen address everything from the implications of new regulations to how the new rules will change everyday activity in the finance industry. They also provide techniques for modeling-credit scoring, structural, and reduced form models-while offering sound advice for stress testing credit risk models and when to accept or reject loans. Breaks down the latest credit risk measurement and modeling techniques and simplifies many of the technical and analytical details surrounding them Concentrates on the underlying economics to objectively evaluate new models Includes new chapters on how to prevent another crisis from occurring Understanding credit risk measurement is now more important than ever. Credit Risk Management In and Out of the Financial Crisis will solidify your knowledge of this dynamic discipline.

Credit Risk Measurement

Credit Risk Measurement PDF Author: Anthony Saunders
Publisher: John Wiley & Sons
ISBN: 0471274763
Category : Business & Economics
Languages : en
Pages : 337

Book Description
The most cutting-edge read on the pricing, modeling, and management of credit risk available The rise of credit risk measurement and the credit derivatives market started in the early 1990s and has grown ever since. For many professionals, understanding credit risk measurement as a discipline is now more important than ever. Credit Risk Measurement, Second Edition has been fully revised to reflect the latest thinking on credit risk measurement and to provide credit risk professionals with a solid understanding of the alternative approaches to credit risk measurement. This readable guide discusses the latest pricing, modeling, and management techniques available for dealing with credit risk. New chapters highlight the latest generation of credit risk measurement models, including a popular class known as intensity-based models. Credit Risk Measurement, Second Edition also analyzes significant changes in banking regulations that are impacting credit risk measurement at financial institutions. With fresh insights and updated information on the world of credit risk measurement, this book is a must-read reference for all credit risk professionals. Anthony Saunders (New York, NY) is the John M. Schiff Professor of Finance and Chair of the Department of Finance at the Stern School of Business at New York University. He holds positions on the Board of Academic Consultants of the Federal Reserve Board of Governors as well as the Council of Research Advisors for the Federal National Mortgage Association. He is the editor of the Journal of Banking and Finance and the Journal of Financial Markets, Instruments and Institutions. Linda Allen (New York, NY) is Professor of Finance at Baruch College and Adjunct Professor of Finance at the Stern School of Business at New York University. She also is author of Capital Markets and Institutions: A Global View (Wiley: 0471130494). Over the years, financial professionals around the world have looked to the Wiley Finance series and its wide array of bestselling books for the knowledge, insights, and techniques that are essential to success in financial markets. As the pace of change in financial markets and instruments quickens, Wiley Finance continues to respond. With critically acclaimed books by leading thinkers on value investing, risk management, asset allocation, and many other critical subjects, the Wiley Finance series provides the financial community with information they want. Written to provide professionals and individuals with the most current thinking from the best minds in the industry, it is no wonder that the Wiley Finance series is the first and last stop for financial professionals looking to increase their financial expertise.

Credit Risk

Credit Risk PDF Author: Darrell Duffie
Publisher: Princeton University Press
ISBN: 1400829178
Category : Business & Economics
Languages : en
Pages : 415

Book Description
In this book, two of America's leading economists provide the first integrated treatment of the conceptual, practical, and empirical foundations for credit risk pricing and risk measurement. Masterfully applying theory to practice, Darrell Duffie and Kenneth Singleton model credit risk for the purpose of measuring portfolio risk and pricing defaultable bonds, credit derivatives, and other securities exposed to credit risk. The methodological rigor, scope, and sophistication of their state-of-the-art account is unparalleled, and its singularly in-depth treatment of pricing and credit derivatives further illuminates a problem that has drawn much attention in an era when financial institutions the world over are revising their credit management strategies. Duffie and Singleton offer critical assessments of alternative approaches to credit-risk modeling, while highlighting the strengths and weaknesses of current practice. Their approach blends in-depth discussions of the conceptual foundations of modeling with extensive analyses of the empirical properties of such credit-related time series as default probabilities, recoveries, ratings transitions, and yield spreads. Both the "structura" and "reduced-form" approaches to pricing defaultable securities are presented, and their comparative fits to historical data are assessed. The authors also provide a comprehensive treatment of the pricing of credit derivatives, including credit swaps, collateralized debt obligations, credit guarantees, lines of credit, and spread options. Not least, they describe certain enhancements to current pricing and management practices that, they argue, will better position financial institutions for future changes in the financial markets. Credit Risk is an indispensable resource for risk managers, traders or regulators dealing with financial products with a significant credit risk component, as well as for academic researchers and students.

Recovery Risk

Recovery Risk PDF Author: Edward I. Altman
Publisher: Bloomberg Press
ISBN: 9781904339502
Category : Business & Economics
Languages : en
Pages : 364

Book Description
In this ground-breaking new title, Risk Books brings together three prominent editors to provide a timely reference text on loss given default (LGD) measurement and management and the requirements of the Basel II Capital Accord.

Default Recovery Rates in Credit Risk Modeling

Default Recovery Rates in Credit Risk Modeling PDF Author: Edward I. Altman
Publisher:
ISBN:
Category :
Languages : en
Pages : 33

Book Description
Evidence from many countries in recent years suggests that collateral values and recovery rates on corporate defaults can be volatile and, moreover, that they tend to go down just when the number of defaults goes up in economic downturns. This link between recovery rates and default rates has traditionally been neglected by credit risk models, as most of them focused on default risk and adopted static loss assumptions, treating the recovery rate either as a constant parameter or as a stochastic variable independent from the probability of default. This traditional focus on default analysis has been partly reversed by the recent significant increase in the number of studies dedicated to the subject of recovery rate estimation and the relationship between default and recovery rates. This paper presents a detailed review of the way credit risk models, developed during the last thirty years, treat the recovery rate and, more specifically, its relationship with the probability of default of an obligor. Recent empirical evidence concerning this issue is also presented and discussed.

Credit Risk

Credit Risk PDF Author: Niklas Wagner
Publisher: CRC Press
ISBN: 1584889950
Category : Business & Economics
Languages : en
Pages : 600

Book Description
Featuring contributions from leading international academics and practitioners, Credit Risk: Models, Derivatives, and Management illustrates how a risk management system can be implemented through an understanding of portfolio credit risks, a set of suitable models, and the derivation of reliable empirical results. Divided into six sectio