Credit Risk Measurement: New Approaches to Value-at-Risk and Other Paradigms

Overview

The single most important topic in finance today is the art and science of credit risk management. Growing dissatisfaction with traditional credit risk measurement methods has combined with regulations imposed by the Bank for International Settlements (BIS) in 1993 to send numerous financial institutions in search of alternative "internal model" approaches to measuring the credit risk of a loan or portfolio of loans. This has led to a raging debate over whether internal models can replace regulatory models, and ...

See more details below
Hardcover
$51.28
BN.com price
(Save 26%)$69.95 List Price
Other sellers (Hardcover)
  • All (10) from $17.95   
  • New (4) from $17.95   
  • Used (6) from $22.00   
Sending request ...

Overview

The single most important topic in finance today is the art and science of credit risk management. Growing dissatisfaction with traditional credit risk measurement methods has combined with regulations imposed by the Bank for International Settlements (BIS) in 1993 to send numerous financial institutions in search of alternative "internal model" approaches to measuring the credit risk of a loan or portfolio of loans. This has led to a raging debate over whether internal models can replace regulatory models, and which areas of credit risk measurement and management are most amenable to internal models. Much of this highly technical debate, however, has been inaccessible to the interested practitioner, student, economist, or regulator-until now.

In Credit Risk Measurement: New Approaches to Value at Risk and Other Paradigms, Anthony Saunders invites a wider audience into the debate. Simplifying many of the technical details and analytics surrounding internal models, he concentrates on their underlying economics and economic intuition. Professor Saunders examines the approaches of these new models to the evaluation of individual borrower credit risk, portfolio credit risk, and derivative contracts. The alternative models explored include:
* Loans as options and the KMV model
* The VAR approach: J. P. Morgan's CreditMetrics and other models
* The macro simulation approach: the McKinsey and other models
* The risk-neutral valuation approach: KPMG's Loan Analysis System (LAS) and other models
* The insurance approach: mortality models and CSFP credit risk plus model
* Back testing and stress testing credit risk models
* RAROC models

With its comprehensive coverage, summary, and comparison of new internal model approaches along with clear explanations of often complex material, Credit Risk Measurement is an indispensable resource for bankers, academics and students, economists, and regulators.

Read More Show Less

Editorial Reviews

Booknews
Saunders (finance, Stern School of Business, New York U.) and Allen (finance, Zicklin School of Business at Baruch College, City U. of New York) examine models for credit risk estimation. Models applicable to both individual borrower and portfolio risk assessment are covered. Introductory chapters explore the advancement of the field since the previous edition two years earlier, traditional approaches, and explain the Basel International Capital Accord of 2002 which seeks to develop a single capital requirement for credit risk across the major banking countries. Remaining chapters focus solely on models. Annotation c. Book News, Inc., Portland, OR (booknews.com)
Read More Show Less

Product Details

  • ISBN-13: 9780471350842
  • Publisher: Wiley
  • Publication date: 7/2/1999
  • Series: Frontiers in Finance Series , #71
  • Edition number: 1
  • Pages: 240
  • Product dimensions: 6.36 (w) x 9.43 (h) x 0.87 (d)

Meet the Author

ANTHONY SAUNDERS 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 and 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.

Read More Show Less

Read an Excerpt

CHAPTER 1

Why New Approaches to Credit Risk Measurement and Management?

In recent years, a revolution has been brewing in risk as it is both measured and managed. Contradicting the relatively dull and routine history of credit risk, new technologies and ideas have emerged among a new generation of financial engineering professionals who are applying their model-building skills and analysis to this area.

The question arises: Why now? There are at least seven reasons for this sudden surge in interest.

1. STRUCTURAL INCREASE IN BANKRUPTCIES
Although the most recent recession hit at different times in different countries, most statistics show a significant increase in bankruptcies, compared to the prior recessions. To the extent that there has been a permanent or structural increase in bankruptcies worldwide--possibly due to the increase in global competition--accurate credit risk analysis becomes even more important today than in the past.

2. DISINTERMEDIATION
As capital markets have expanded and become accessible to small and mid-size firms (e.g., it is estimated that as many as 20,000 U.S. companies have actual or potential access to the U.S. commercial paper market), the firms or borrowers "left behind" to raise funds from banks and other traditional financial institutions (FIs) are increasingly likely to be smaller and to have weaker credit ratings. Capital market growth has produced a "winner's curse" effect on the credit portfolios of traditional FIs.

3. MORE COMPETITIVE MARGINS
Almost paradoxically, despite the decline in the average quality of loans (described above), interest margins or spreads, especially in wholesale loan markets, have become very thin. In short, the risk-return trade-off from lending has gotten worse. A number of reasons can be cited, but an important factor has been the enhanced competition for lower quality borrowers, especially from finance companies, much of whose lending activity has been concentrated at the higher risk/ lower quality end of the market.

4. DECLINING AND VOLATILE VALUES OF COLLATERAL

Concurrent with recent Asian and Russian debt crises, banking crises in well-developed countries such as Switzerland and Japan have shown that property values and real asset values are very hard to predict and to realize through liquidation. The weaker (and more uncertain) collateral values are, the riskier lending is likely to be. Indeed, current concerns about "deflation" worldwide have accentuated concerns about the value of real assets such as property and other physical assets.

5. THE GROWTH OF OFF-BALANCE-SHEET DERIVATIVES
Because of the phenomenal expansion of derivative markets, the growth of credit exposure, or counterparty risk, has extended the need for credit analysis beyond the loan book. In many of the very largest U.S. banks, the notional (not market) value of off-balance-sheet exposure to instruments such as over-the-counter (OTC) swaps and forwards is more than 10 times the size of their loan books. Indeed, the growth in credit risk off the balance sheet was one of the main reasons for the introduction, by the Bank for International Settlements (BIS), of risk-based capital (RBC) requirements in 1993. Under the BIS system, banks have to hold a capital requirement based on the mark-to-market current value of each OTC derivatives contract (so-called current exposure) plus an add-on for potential future exposure (see Chapter 14).

6. TECHNOLOGY
Advances in computer systems and related advances in information technology-- for example, the development of historic loan databases by the Loan Pricing Corporation and other companies--have given banks and FIs the opportunity to test high-powered modeling techniques. A survey conducted by the International Swaps and Derivatives Association (ISDA) and the Institute of International Finance (IIF) in 2000 found that survey participants (consisting of 25 commercial banks from 10 countries, with varying sizes and specialties) used commercial and internal databases to assess the credit risk on rated and unrated commercial, retail, and mortgage loans.1 For example, besides being able to analyze loan loss and value distribution functions-- and (especially) the tails of such distributions--FIs can move toward actively managing loan portfolios based on modern portfolio theory (MPT) models and techniques.2

7. THE BIS RISK-BASED CAPITAL REQUIREMENTS

Despite the importance of these six reasons, probably the greatest incentive for banks to develop new credit risk models has been dissatisfaction with the BIS and central banks' post-1992 imposition of capital requirements on loans, so-called BIS I. The current BIS approach has been described as a "one-size-fits-all" policy; virtually all loans to private-sector counterparties are subjected to the same 8 percent capital ratio (or capital reserve requirement), irrespective of the size of the loan, its maturity, and, most importantly, the credit quality of the borrowing counterparty. Thus, loans to a firm near bankruptcy are treated (in capital requirement terms) in the same fashion as loans to an AAA borrower. Further, the current capital requirement is additive across all loans; there is no allowance for lower capital requirements because of a greater degree of diversification in the loan portfolio.

At the beginning of 1998, in the United States (1997, in the European Community), regulators allowed certain large banks the discretion to calculate capital requirements for their trading books--or market risk exposures-- using "internal models" rather than the alternative regulatory ("standardized") model. Internal models have had certain constraints imposed on them by regulators and are subjected to back-testing verification; nevertheless, they potentially allow for (1) the Value at Risk (VAR) of each tradable instrument to be more accurately measured (e.g., based on its price volatility, maturity, and so on) and (2) correlations among assets to be taken into account. In the context of market risk, VAR measures the market value exposure of a financial instrument in case tomorrow is a statistically defined "bad day." For example, under the BIS market risk regulations, when banks calculate their VAR-based capital requirements using their internal models, they are required to measure the bad day as the one bad day that happens every 100 business days. (See Appendix 1.1, in this chapter, for a summary of basic VAR concepts.)

Much of the current interest in fine-tuning credit risk measurement models has been fueled by the proposed BIS New Capital Accord (or so-called BIS II), which would more closely link capital charges to the credit risk exposures for individual retail, commercial, sovereign, and interbank credits. Controversy regarding this proposal (discussed at length in Chapter 3) is evident from the one-year delay in finalization and implementation of BIS II (now proposed to be implemented in 2005). This delay occurred because of difficulties in: agreeing on how credit risk should be modeled, technical problems arising from the nontradability of loans compared to marketable instruments, and the lack of deep historic databases on loan defaults. For this reason, BIS II offers three alternative approaches to the calculation of capital requirements for regulatory purposes: a standardized approach (which utilizes external credit ratings to assess risk weights for capital charges) and two separate internal ratings-based approaches (which utilize the bank's internal database to assess a loan's default probability and loss given default). The internal ratings-based approaches are patterned after the market risk capital regulations using internal models, such that the capital required is calibrated to cover a "bad credit period," defined to be the worst year out of 1,000 years.3

Regardless of whether internal models are used to set bank capital requirements, the new models have contributed to the lending process. Specifically, internal models potentially offer better ways to value outstanding loans and credit-risk-exposed instruments such as bonds (corporate and emerging market), as well as better methods for predicting default risk exposures to borrowers and derivative counterparties. Moreover, internal models (1) allow (in many cases) the credit risk of portfolios of loans and credit-risk-sensitive instruments to be better evaluated and (2) can be used to improve the pricing of new loans, in the context of an FI's risk-adjusted return on capital (RAROC), as well as the pricing of relatively new instruments in the credit-derivatives markets, such as credit options, credit swaps, and credit forwards. Finally, the models provide an opportunity to measure the privately optimal or economic amount of capital a bank (or FI) should hold as part of its capital structure.

Before we look at some of these new approaches to credit risk measurement, a brief analysis of the more traditional approaches will heighten the contrast between the new and traditional approaches to credit risk measurement.

APPENDIX 1.1:
A BRIEF OVERVIEW OF KEY VAR CONCEPTS

The Role of Capital
Banks hold capital (mostly equity and long-term subordinated debt obligations) as a cushion against losses stemming from adverse credit, market, and operational circumstances. By absorbing these losses, capital protects the bank from insolvency. Bank regulators set minimum capital requirements so as to reduce the likelihood of bank insolvencies that are costly to the economy. To determine how much capital should be required, two questions must be answered. First, what is the acceptable probability of bank insolvency? It is neither practical nor desirable to completely indemnify the banking system against all insolvencies; instead, an "acceptable" level of risk is necessary to prevent moral hazard considerations that would encourage banks to take on excessive risk exposures. The proposed BIS II Internal Ratings-Based model sets this risk threshold at the 99.9 percentile; that is, the capital charge is sufficient to cover losses in all but the worst 0.1 percent of adverse credit risk events. Stated directly: There is a 0.1 percent chance that adverse credit conditions will cause bank insolvency.

Measuring Expected and Unexpected Losses
The second input into capital regulations is a methodology for measuring losses in the event of adverse market conditions called credit events. Losses are defined as the change in the security's (loan's) value over a fixed period of time ("the credit horizon period"). Typically, the credit horizon period is chosen to be one year. Thus, losses are calculated as the impact of a credit event on the security's market value, 4 less any cash flows received during the one-year credit horizon period. Losses may be negative (that is, there are gains) if the security's value increases over the year and if a credit event does not occur.

Figure 1.1 illustrates a loss distribution that relates all possible values of securities' losses/ gains to the probability of occurrence for each value (determined by the likelihood that a credit event will occur). The area under the probability distribution of security losses must sum to one. The probability distribution in Figure 1.1 is a normal distribution, which suggests that losses or gains are symmetrically distributed around the mean value. Two important loss concepts are illustrated in Figure 1.1. Expected losses (EL) are estimated by the mean of the distribution, and unexpected losses (UL) are measured by the chosen percentile cutoff of extreme losses. If the loss percentile cutoff is set at 0.1 percent (as in BIS II proposals), then UL is the value that just marks off the shaded area in Figure 1.1, which comprises 0.1 percent of the area under the entire loss distribution. That is, there is only a 0.1 percent likelihood that losses will exceed UL. The UL is considered the measure of Value at Risk (VAR).

The standard deviation, denoted s, is a commonly used measure of risk because it measures the loss dispersion around EL weighted by the likelihood of occurrence. For the normal distribution, there is approximately a 67 percent probability that losses will fall within the region from EL - s to EL + s, which is called the confidence interval.

The loss distribution shown in Figure 1.1 is normal, although most financial loss distributions are skewed with fat tails; that is, there is a greater likelihood of extreme outcomes than is shown by the normal distribution. Figure 1.2 shows a skewed loss distribution with the loss measures EL and UL. We can solve for the of the loss distribution in Figure 1.2, but because it is not normal, we cannot specify the likelihood that losses will fall within the EL - s to EL + s confidence interval unless we have information about the particular shape of the distribution, for example, its skewness (lack of symmetry) and its kurtosis (the probability of extreme loss outcomes).

Figures 1.1 and 1.2 are loss distributions for individual security (loan) investments. However, diversification across different securities causes the risk of a portfolio to be lower than the risk of individual security investments. The lower the correlation between pairs of securities, the greater the benefits of diversification in reducing the risk of the portfolio. The correlation coefficient, denoted ?, measures the comovement between pairs of securities on a scale of -1 to + 1: -1 for perfectly negatively correlated (the securities' values move in exactly opposite directions), 0 for uncorrelated, and +1 for perfectly positively correlated (the securities' values move together in lock step). Most securities are positively correlated (thereby preventing the elimination of risk through simple portfolio creation), but not perfectly positively correlated (thereby providing substantial benefits to diversification).

As we will see in later chapters (for example, Chapter 6), estimating UL (or VAR) for credit risk is challenging. Not only do volatilities and correlations have to be estimated for both probability of default (PD) and the loss given default (LGD), but the definition of a credit event must also be determined. A credit event may be defined only as default, as in default mode (DM) models. However, mark-to-market (MTM) models define a credit event to be any migration in credit quality, including, but not limited to, default. Thus, if a particular loan or bond is downgraded from an A to a B rating, the adverse change in the bond's price would be included in the loss distribution of an MTM model, whereas it would not be included for a DM model. Moreover, since credit events (particularly default) are somewhat rare events, historical loss rates may not provide accurate estimates of future exposures such as EL and UL. Finally, data availability problems plague credit risk measurement models, in contrast to the market risk VAR models that can use series of daily price databases. The challenge, for the modern models of credit risk measurement, is to compensate for these problems.

Read More Show Less

Table of Contents

Why New Approaches to Credit Risk Measurement and Management?

Traditional Approaches to Credit Risk Measurement.

Loans as Options and the KMV Model.

The VAR Approach: J.P. Morgan's CreditMetrics and Other Models.

The Macro Simulation Approach: The McKinsey Model and Other Models.

The Risk-Neutral Valuation Approach: KPMG's Loan Analysis System (LAS) and Other Models.

The Insurance Approach: Mortality Models and the CSFP Credit Risk Plus Model.

A Summary and Comparison of New Internal Model Approaches.

An Overview of Modern Portfolio Theory and Its Application to Loan Portfolios.

Loan Portfolio Selection and Risk Measurement.

Back-Testing and Stress- Testing Credit Risk Models.

RAROC Models.

Off-Balance-Sheet Credit Risk.

Credit Derivatives.

Bibliography.

Index.

Read More Show Less

First Chapter

Note: The Figures and/or Tables mentioned in this sample chapter do not appear on the Web.

Chapter 1

Why New Approaches to Credit Risk Measurement and Management?

INTRODUCTION

In recent years, a revolution has been brewing in the way credit risk is both measured and managed. Contradicting the relatively dull and routine history of credit risk, new technologies and ideas have emerged among a new generation of financial engineering professionals who are applying their model-building skills and analysis to this area.
The question arises: Why now? There are at least seven reasons for this sudden surge in interest.

STRUCTURAL INCREASE IN BANKRUPTCIES

Although the most recent recession hit at different times in different countries, most bankruptcy statistics showed a significant increase in bankruptcies, compared to the prior recession. To the extent that there has been a permanent or structural increase in bankruptcies worldwide— possibly due to the increase in global competition— accurate credit risk analysis becomes even more important today than in the past.

DISINTERMEDIATION

As capital markets have expanded and become accessible to small and middle market firms (e. g., it is estimated that as many as 20,000 U. S. companies have actual or potential access to the U. S. commercial paper market), the firms or borrowers "left behind" to raise funds from banks and other traditional financial institutions (henceforth, FIs) are increasingly likely to be smaller and have weaker credit ratings. Capital market growth has produced a "winner's curse" effect on the credit portfolios of traditional FIs.

MORE COMPETITIVE MARGINS

Almost paradoxically, despite a decline in the average quality of loans (due to the second reason above), interest margins or spreads, especially in wholesale loan markets, have become very thin— that is, the risk— return trade-off from lending has gotten worse. A number of reasons can be cited, but an important factor has been the enhanced competition for lower-quality borrowers, such as from finance companies, much of whose lending activity has been concentrated at the higher risk— lower quality end of the market.

DECLINING AND VOLATILE VALUES OF COLLATERAL

Concurrent with the recent Asian crisis, banking crises in well-developed countries such as Switzerland and Japan have shown that property values and real asset values are very hard to predict and to realize through liquidation. The weaker and more uncertain collateral values are, the more risky lending is likely to be. Indeed, current concerns about "deflation" worldwide have accentuated concerns about the value of real assets such as property and other physical assets.

THE GROWTH OF OFF-BALANCE-SHEET DERIVATIVES

The growth of credit exposure, or counterparty risk, because of the phenomenal expansion of derivative markets, has extended the need for credit analysis beyond the loan book. In many of the very largest U. S. banks, the notional (not market) value of their off-balance-sheet exposure to instruments such as over-the-counter (OTC) swaps and forwards is more than ten times the size of their loan books. Indeed, the growth in credit risk off the balance sheet was one of the main reasons for the introduction, by the Bank for International Settlements (BIS), of risk-based capital (RBC) requirements in 1993. Under the BIS system, banks have to hold a capital requirement based on the marked-to-market current value of each OTC derivatives contract (so-called current exposure) plus an add-on for potential future exposure.

TECHNOLOGY

Advances in computer systems and related advances in information technology— such as the development of historic loan databases by the Loan Pricing Corporation and other companies— have given banks and FIs the opportunity to test high-powered modeling techniques. For example, besides being able to analyze loan loss and value distribution functions and (especially) the tails of such distributions, they can move toward actively managing loan portfolios based on modern portfolio theory (MPT) models and techniques.

THE BIS RISK-BASED CAPITAL REQUIREMENTS

Despite the importance of the six reasons discussed above, probably the greatest incentive for banks to develop new credit risk models has been dissatisfaction with the BIS and central banks' post-1992 imposition of capital requirements on loans. The current BIS approach has been described as a "one size fits all" policy; virtually all loans to private-sector counterparties are subjected to the same 8 percent capital ratio (or capital reserve requirement), irrespective of the size of the loan, its maturity, and, most importantly, the credit quality of the borrowing counter-party (see Appendix 1.1). Thus, loans to a firm near bankruptcy are treated (in capital requirement terms) in the same fashion as loans to a AAA borrower. Further, the current capital requirement is additive across all loans; there is no allowance for lower capital requirements because of a greater degree of diversification in the loan portfolio.
At the beginning of 1998 in the United States (1997 in the European Community), regulators allowed certain large banks, the discretion to calculate capital requirements for their trading books— or market risk exposures— using "internal models" rather than the alternative regulatory (" standardized") model. Internal models have had certain constraints imposed on them by regulators and are subjected to back-testing verification; nevertheless, they potentially allow for (1) the value at risk (VAR) of each tradable instrument to be more accurately measured (e. g., based on its price volatility, maturity, etc.) and (2) correlations among assets to be taken into account. In the context of market risk, VAR measures the market value exposure of a financial instrument in case tomorrow is a "bad day," defined statistically. For example, under the BIS market risk regulations, when banks calculate their VAR-based capital requirements using their internal models, they are required to measure the bad day as the 1 bad day that happens once every 100 business days.
The questions for bankers and regulators, and among the major questions analyzed in this book, are:

1. Can an "internal model" approach be used to measure the value at risk or capital exposure of (nontradable) loans?

2. Do internal models have sufficient flexibility and accuracy to supplant the current standardized 8 percent risk-based capital ratio that imposes the same capital requirement on virtually all private-sector loans?

Even if it is felt that internal models have some way to go before they can replace the 8 percent rule— especially because of the nontradability of loans compared to marketable instruments, and the lack of deep historic databases on loan defaults— the new internal models may still have significant value to bankers, FI risk managers, regulators, and corporate treasurers. Specifically, internal models potentially offer better ways to value outstanding loans and credit-risk-exposed instruments such as bonds (corporate and emerging market), as well as better methods for predicting default risk exposures to borrowers and derivative counterparties. Moreover, internal models (1) allow (in many cases) the credit risk of portfolios of loans and credit-risk-sensitive instruments to be better evaluated, and (2) can be used to improve the pricing of new loans, in the context of an FI's risk-adjusted return on capital (RAROC), and of relatively new instruments in the credit-derivatives markets, such as credit options, credit swaps, and credit forwards. Finally, the models provide an opportunity to measure the privately optimal or economic amount of capital a bank (or FI) should hold as part of its capital structure.
Before we look at some of these new approaches to credit risk measurement, a brief analysis of the more traditional approaches will heighten the contrast between the new and traditional approaches to credit-risk measurement.

Read More Show Less

Customer Reviews

Be the first to write a review
( 0 )
Rating Distribution

5 Star

(0)

4 Star

(0)

3 Star

(0)

2 Star

(0)

1 Star

(0)

Your Rating:

Your Name: Create a Pen Name or

Barnes & Noble.com Review Rules

Our reader reviews allow you to share your comments on titles you liked, or didn't, with others. By submitting an online review, you are representing to Barnes & Noble.com that all information contained in your review is original and accurate in all respects, and that the submission of such content by you and the posting of such content by Barnes & Noble.com does not and will not violate the rights of any third party. Please follow the rules below to help ensure that your review can be posted.

Reviews by Our Customers Under the Age of 13

We highly value and respect everyone's opinion concerning the titles we offer. However, we cannot allow persons under the age of 13 to have accounts at BN.com or to post customer reviews. Please see our Terms of Use for more details.

What to exclude from your review:

Please do not write about reviews, commentary, or information posted on the product page. If you see any errors in the information on the product page, please send us an email.

Reviews should not contain any of the following:

  • - HTML tags, profanity, obscenities, vulgarities, or comments that defame anyone
  • - Time-sensitive information such as tour dates, signings, lectures, etc.
  • - Single-word reviews. Other people will read your review to discover why you liked or didn't like the title. Be descriptive.
  • - Comments focusing on the author or that may ruin the ending for others
  • - Phone numbers, addresses, URLs
  • - Pricing and availability information or alternative ordering information
  • - Advertisements or commercial solicitation

Reminder:

  • - By submitting a review, you grant to Barnes & Noble.com and its sublicensees the royalty-free, perpetual, irrevocable right and license to use the review in accordance with the Barnes & Noble.com Terms of Use.
  • - Barnes & Noble.com reserves the right not to post any review -- particularly those that do not follow the terms and conditions of these Rules. Barnes & Noble.com also reserves the right to remove any review at any time without notice.
  • - See Terms of Use for other conditions and disclaimers.
Search for Products You'd Like to Recommend

Recommend other products that relate to your review. Just search for them below and share!

Create a Pen Name

Your Pen Name is your unique identity on BN.com. It will appear on the reviews you write and other website activities. Your Pen Name cannot be edited, changed or deleted once submitted.

 
Your Pen Name can be any combination of alphanumeric characters (plus - and _), and must be at least two characters long.

Continue Anonymously

    If you find inappropriate content, please report it to Barnes & Noble
    Why is this product inappropriate?
    Comments (optional)