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Enterprise Credit Risk Using Mark-to-Future
"Credit Risk - Enterprise Credit Risk Using Mark-to-Future" is a compilation of research articles taken from the Algo Research Quarterly and external contributors. First published in 2001, this book focuses on key components of credit risk using a Mark-to-Future framework.
Guest Editorial
Charles Smithson
Introduction
Enterprise Credit Risk Management
Credit risk comes in many different colours, styles and shapes, and is traditionally managed strictly in silos. This introduction motivates the development of a framework for integrating credit risk and reward across the enterprise and describes its necessary components.
Part One: Obligor Creditworthiness Assessment
Benchmarking Quantitative Default Risk Models: A Validation Methodology
Jorge Sobehart, Sean Keenan and Roger Stein
As a leader in credit risk assessment, Moody's has also been active in developing and testing quantitative methods that can be used for credit risk management. This article presents a summary of the approach Moody's used to validate and benchmark a series of popular quantitative default risk models, including our own Public Firm model.
Regularization Algorithms for Transition Matrices
Alexander Kreinin and Marina Sidelnikova
Both estimating portfolio credit risk and pricing credit risky securities require transition matrices for arbitrary time horizons. Simply computing the root of the annual transition matrix is unacceptable because the resulting matrices often contain negative elements.
Suddenly Structure Mattered: Insights into Recoveries from Defaulted Debt
Karen Van de Castle, David Keisman and Ruth Yang
This study analyses default loss experience for a sample of 690 bonds and 264 bank loans between 1987 and 1996. It is an update of a Standard and Poor's study done one year ago that first reported that the amount of debt subordinate to an obligation has a powerful influence on that obligation's loss in default.
Bank-Loan Loss Given Default
Greg M. Gupton, Daniel Gates and Lea V. Carty
This paper, an update on Moody's November 1996 study, examines borrowers of bank loans, rather than the banks that made defaulted loans. It looks at secondary market price quotes of bank loans one month after the time of default, thereby allowing markets to process the default news and revalue the debt.
Measuring Default Correlation
Krishan Nagpal and Reza Bahar
This paper examines the structure of the correlation between defaults of US corporates. This study is based on historical default data over a period of 18 years.
Appendix: Modelling Default Correlation
Krishan Nagpal and Reza Bahar
This article, a follow-up to "Measuring Default Correlation," builds on a previously presented model relating default probabilities and correlations to the region and industry sector that a firm is in.
Part Two: Valuation Of Credit-Risky Instruments
Fundamental Theorem of Asset Pricing for Credit-Risky Securities
Andrew Aziz
In this paper, we examine the pricing of credit-risky securities by applying the Fundamental Theorem of Asset Pricing to both reduced-form and structural models. In a reduced-form model, default is introduced as an exogenous event while, in the case of a structural model, the event of default is driven by the realization of firm value over future states.
Building a Credit Risk Valuation Framework for Loan Instruments
Scott Aguais, Larry Forest and Dan Rosen
We present a general option-valuation framework for loans that provides valuation information at loan origination and supports mark-to-market analysis, portfolio credit risk and asset and liability management for the entire portfolio.
Part Three: Counterparty Credit Exposure Measurement And Control
Calculating Credit Exposure and Credit Loss: A Case Study
Jeff Aziz and Narat Charupat
We report a study of the estimation of credit exposure and credit loss of a portfolio of derivative transactions. The estimation is performed using a Monte Carlo simulation.
A Multi-factor Statistical Model for Interest Rates
Mark Reimers and Michael Zerbs
A term structure model that produces realistic scenarios of future interest rates is critical to the effective measurement of counterparty credit exposures. Scenarios are realistic when observed interest rates and actual exposures over time are consistent with the predicted distribution of interest rates and potential exposures.
Using Scenario Banding to Stress Test Counterparty Credit Exposures
Paola Cartolano and Savita Verma
A pair of extreme scenarios on a risk factor create a banded scenario. This paper explores the use of scenario banding over multiple factors for systematic stress testing of counterparty credit exposures over a large number of time steps.
Part Four: Portfolio Credit Risk Measurement And Management
An Integrated Market and Credit Risk Portfolio Model
Ian Iscoe, Alexander Kreinin and Dan Rosen
We present a multi-step model to measure portfolio credit risk that integrates exposure simulation and portfolio credit risk techniques. Thus, it overcomes the major limitation currently shared by portfolio models with derivatives.
Integrated Market and Credit Risk Scenarios: An Example
Credit Risk of an International Bond Portfolio: A case study
Nisso Bucay and Dan Rosen
We apply the CreditMetrics methodology to estimate the credit risk of a portfolio of long-dated corporate and sovereign bonds issued in emerging markets. Credit risk is decomposed into default and downgrade risk.
Applying Portfolio Credit Risk Models to Retail Portfolios
Nisso Bucay and Dan Rosen
We present a simulation-based model to estimate the credit loss distribution of retail loan portfolios and apply the model to a sample credit card portfolio of a North American financial institution. Within the portfolio model, we test three default models that describe the joint behavior of default events.
Applying Scenario Optimization to Portfolio Credit Risk
Helmut Mausser and Dan Rosen
Standard market risk optimization tools, based on assumptions of normality, are ineffective for credit risk. In this paper, we develop three scenario optimization models for portfolio credit risk.
Efficient Risk/Return Frontiers for Credit Risk
Helmut Mausser and Dan Rosen
We construct efficient frontiers for relevant measures of credit risk, including expected shortfall, maximum (percentile) losses and unexpected (percentile) losses, and show that minimum-variance portfolios are markedly inefficient with respect to these measures.
Related Information
Credit Risk Solutions
Gain real-time access to accurate data, analytics and tools to manage limits and exposure calculations across multiple business lines.
Understanding Mark-to-Future Methodology
A forward-looking, scenario-based framework that calculates the risk-reward trade-off within a single, unified architecture.