Internal Credit Risk Models - Risk Books
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Internal Credit Risk Models

Edited By Michael K. Ong

Overview

A practical, accessible step-by-step analysis of the theory and practicalities of credit risk measurement and management.

Publish date: 1 Apr 1999

Availability: In stock

Product Unit Price Qty
Internal Credit Risk Models
£80.00
eBook - Internal Credit Risk Models
EPUB
£60.00
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Book description

  • The authoritative introduction to internal credit risk modelling and management for financial institutions
  • Topics covered include: default probabilities; expected and unexpected losses; time effects; default correlations; and loss distributions

Book details

ISBN
Book 9781899332038 / EBook 9781908823137
Publish date
1 Apr 1999
Format
Paperback
Size
155mm x 235mm

Editor biography

Michael K. Ong

Dr. Michael K. Ong is currently Professor of Finance at the Stuart School of Business, Illinois Institute of Technology.  He was formerly the Director of the Finance Program and the Executive Director of the Center for Financial Markets. Prior to his retirement from the financial industry, Professor Ong was Executive Vice President and Chief Risk Officer for Credit Agricole Indosuez in New York.  He has enterprise-wide responsibility for all risk management functions for corporate banking, merchant banking, asset management, capital markets activities, and the brokerage division.  He was a member of the Executive Committee.  Before that, he was Head of Enterprise Risk Management for ABN-AMRO Bank, responsible for management information and decision support function for the Executive Committee regarding enterprise-wide market, credit, operational, and liquidity risk, as well as RAROC, ROE, and related optimization models.  Prior to that, Dr. Ong was Head of Corporate Research Unit for First Chicago NBD Corporation. The unit supports the Bank in its global enterprise-wide risk management function – market and credit risk analyses and the allocation of economic capital – and oversees the quantitative research units of the trading areas.  Earlier on, he served as an assistant professor of mathematics at Bowdoin College for seven years with his research specialty in mathematical physics.

He is a member of the Editorial Board of the Journal of Financial Regulation and Compliance, the Journal of Credit Risk, and the Journal of Risk Management for Financial Institutions.  He was the founding editor and Editor-in-Chief of the Journal of Credit Risk, and was on the editorial board of the Journal of RISK and The RMA Journal.  

He is author or editor of the following best-selling books: Internal Credit Risk Models – Capital Allocation and Performance Measurement (Risk Books,1999); Credit Ratings – Methodologies, Rationale and Default Risk (Risk Books, 2002); The Basel Handbook – A Guide for Practitioners (Risk Books, 2004); Risk Management – A Modern Perspective (Elsevier, 2006);The Basel Handbook, 2nd Ed. (Risk Books, 2007).  

Dr. Ong is widely recognized in the financial industry for his work on portfolio credit risk modelling, RAROC, economic capital allocation, operational risk, enterprise risk management, his very active involvement in regulatory issues, and his thoughtful candor on issues affecting the financial industry in general.  

Table of contents

CONTENTS

On Basle, Regulation and Market Responses Past and Present

Origins of the Regulatory Capital Framework

Some Historical Perspectives

Historical Rational for the Capital Accord

Credit Risk, Regulatory Capital and the Basle Accord

Evolutionary Nature of Capital Regulation

Market Response: Clamour for Internal Credit Models

Game Theory: Regulatory Capital Arbitrage

Securitisation of Assets

Concerns Raised by Securitisation

Role of Credit Derivatives

Summary of Federal Deposit Insurance Corporation Improvement Act 1991

Regulatory Capital Rules

Overview of Approach

Essential Components of the Internal Credit Risk Model

Outline of Model Components

Preview of Following Chapters

Modelling Credit Risk

Elements of Credit Risk

Default Risk

Measuring Default Probability - Empirical Method

Measuring Default Probability - The Options Theory Approach

Theoretical EDFs and Agency Ratings

Credit Risk Models

Value of Risk Debt

States of the Default Process and Credit Migration

Merton’s Options Theory Approach to Risky Debt

Default Probability, the Default Point and the Distance to Default

Mathematical Preliminary

The Multi-State Default Process and the Probability Measure

Loan Portfolios and Expected Loss

Expected Loss

Adjusted Exposure: Outstandings and Commitments

Covenants

Adjusted Exposure

Usage Given Default

Loss Given Default and the Risky Part of V1

Mathematical Derivation of Expected Loss

Parameterising Credit Risk Models

Unexpected Loss

Causes of Unanticipated Risk

Unexpected Loss

Economic Capital and Unexpected Loss

Derivation of Unexpected Loss (UL)

Portfolio Effects: Risk Contribution and Unexpected Losses

Comparing Expected Loss and Unexpected Loss

The Analysis Horizon and Time to Maturity

Portfolio Expected Loss

Portfolio Unexpected Loss

Risk Contribution

Undiversifiable Risk

Risk Contribution and Correlation of Default

Variation in Asset Value due to Time Effects

Derivation of Portfolio UL

Derivation of Portfolio RCk

Correlation of Default and Credit Quality

Correlation of Credit Quality

Correlation of Default

Default Correlation Matrix and Some Important Observations

Industry Index and Asset Correlation

Estimating Asset Correlation

Obligor-Specific Risk

Further Generalisation to the Multifactor Case

Some Comments and Suggestions

Correlation of Default

First-Passage Time Model of Default Correlation

Industry Default Correlation Matrix

Correlation of Joint Credit Quality Movement

Loss Distribution for Credit Default Risk

Choosing the Proper Loss Distribution

The Beta Distribution

Economic Capital and Probability of Loss

Extreme Events: Fitting the Tail

Monte Carlo Simulation of Loss Distribution

Simulating the Loss Distribution

Some Observations From the Examples

Why EVT and not just Simulation

Mathematics of Loss Simulation

Simulating Default and the Default Point

Extreme Value Theory

Fundamental Regimes for Losses

Extreme Value Theory - Some Basics

Generalised Pareto Distribution

Convergence Criteria

Thresholds Revisited

The Mean Excess Function

History Repeating by Alexander McNeil

Risk-Adjusted Performance Measurement

Risk-Adjusted Performance Measurement

Raroc Defined

Dissecting the Raroc Equation

Approaches to Measurement: Top-Down or Bottom-Up

Revised RAPM

Implementing the Internal Model Across the Enterprise

Sample Portfolio

Negative Raroc

Parameterising and Calibrating the Internal Model

Interpreting the Results of Raroc

Enterprise-Wide Risk Management and RAPM

Sample Credit Portfolio

On to the Next Steps

Credit Concentration and Required Spread

The Credit Paradox

Causes of Concentration Risk

Credit Concentration and Required Spread

The Loan Pricing Calculator

Mathematics of the Loan Pricing Calculator

Epilogue: The Next Steps

Internal Credit Risk Ratings

Data Quality and Opaqueness

Techniques for Assessing Extreme Loss Distributions

Risk-Adjusted Performance Measurement and Risk-Adjusted Pricing

Multi-State Default Process, Marking-to-Market and Multi-Year Analysis Horizons

Differences Between Vendor Models

Integration of Market Risk and Credit Risk

The Multi-State Default Process

Matching Transition Matrices to Historical Data

Appendix

Raroc Remodelled

Tom Wilson

Many Happy Returns

Sanjeev Punjabi

Reconcilable Differences

H. Ugur Koyluoglu and Andrew Hickman

Refining Ratings

Ross Miller

A Credit Risk Toolbox

Angelo Arvanitis, Christopher Browne, Jon Gregory, and Richard Martin

Testimonials

“An excellent book... practical rigorous, well-written and easy to understand.“

Angelo Arvanitis, Egnatia Bank

“You will find no better guide to today’s spirited debateover proper methods to measure credit risk.“

Thomas Donahoe, Metropolitan Life Insurance Company

Customer Reviews

Average customer reviews for Internal Credit Risk Models
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