Risk Financial - Risk Management - M Crouhy, R Mark

Risk Financial - Risk Management - M Crouhy, R Mark

(Parte 1 de 5)

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Risk Management

Michel Crouhy

Dan Galai Robert Mark

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Foreword By Robert C. Merton xiii

Introduction By John Hunkin xvii

Preface xix

Chapter 1 The Need for Risk Management Systems 1

1. Introduction 1 2. Historical Evolution 4 3. The Regulatory Environment 19 4. The Academic Background and Technological Changes 21 5. Accounting Systems versus Risk Management Systems 29 6. Lessons from Recent Financial Disasters 31 7. Typology of Risk Exposures 34

8. Extending Risk Management Systems to NonfinancialCorporations 39

Notes 41

Chapter 2 The New Regulatory and Corporate Environment 45

Chapter 3 Structuring and Managing the Risk Management Function in a Bank 97

2. Organizing the Risk Management Function: Three-PillarFramework 9

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3. Data and Technological Infrastructure 109 4. Risk Authorities and Risk Control 116 5. Establishing Risk Limits for Gap and Liquidity Management 126 6. Conclusion: Steps to Success 133 Notes 135

Chapter 4 The New BIS Capital Requirements for Financial Risks 137

4. Pros and Cons of the Standardized and Internal Models Approaches: A New Proposal—the "Precommitment Approach" 162

5. Comparisons of the Capital Charges for Various Portfolios According to the Standardized and the Internal Models Approaches 165

Chapter 5 Measuring Market Risk: The VaR Approach 177

1. Introduction 177 2. Measuring Risk: A Historical Perspective 179 3. Defining Value at Risk 187 4. Calculating Value at Risk 196 5. Conclusion: Pros and Cons of the Different Approaches 216 Appendix 1: Duration and Convexity of a Bond 218 Notes 225

Chapter 6 Measuring Market Risk: Extensions of the VaR Approach and Testing the Models

3. Stress Testing and Scenario Analysis 232

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4. Dynamic-VaR241

5. Measurement Errors and Back-Testing of VaR Models243

6. Improved Variance-Covariance VaR Model249

7. Limitations of VaR as a Risk Measure252

Appendix: Proof of the Deltavar Property255 Notes 257

Chapter 7Credit Rating Systems 259

1. Introduction259

2. Rating Agencies261

3. Introduction to Internal Risk Rating269

4. Debt Rating and Migration275

5. Financial Assessment (Step 1)282

6. First Group of Adjustment Factors for Obligor Credit Rating290

7. Second Group of Adjustment Factors for Facility Rating298

8. Conclusion301

Appendix 1: Definitions of Key Ratios302

Appendix 2: Key Financial Analysis Measures303

Appendix 3A: Prototype Industry Assessment: Telecommunications in Canada306

Appendix 3B: Prototype Industry Assessment: Footwear and Clothing in Canada308

Appendix 4: Prototype Country Analysis Report (Condensed Version): Brazil310 Notes 312

Chapter 8Credit Migration Approach to Measuring Credit Risk 315

1. Introduction315

2. CreditMetrics Framework319

3. Credit VaR for a Bond (Building Block 1)321

4. Credit VaR for a Loan or Bond Portfolio (Building Block 2)329

5. Analysis of Credit Diversification (Building Block 2, Continuation)338 6. Credit VaR and the Calculation of the Capital Charge339

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7. CreditMetrics as a Loan/Bond Portfolio Management Tool: Marginal Risk Measures (Building Block 2, Continuation) 340

8. Estimation of Asset Correlations (Building Block 3)342

9. Exposures (Building Block 4)343

10. Conditional Transition Probabilities: CreditPortfolioView344

1. Appendix 1: Elements of Merton's Model347

Appendix 2: Default Prediction—The Econometric Model350

Appendix 3: Transition Matrix over a Period of Less than One Year352 Notes 352

Chapter 9The Contingent Claim Approach to Measuring Credit Risk 357

1. Introduction357

2. A Structural Model of Default Risk: Merton's (1974) Model360

3. Probability of Default, Conditional Expected Recovery Value, and Default Spread364

4. Estimating Credit Risk as a Function of Equity Value366

5. KMV Approach368

6. KMV's Valuation Model for Cash Flows Subject to Default Risk381

7. Asset Return Correlation Model384

Appendix 1: Integrating Yield Spread with Options Approach389

Appendix 2: Risk-Neutral Valuation Using "Risk-Neutral" EDFs392

Appendix 3: Limitations of the Merton Model and Some Extensions395 Notes 399

Chapter 10Other Approaches: The Actuarial and Reduced-Form Approaches to Measuring Credit Risk 403

1. Introduction403

2. The Actuarial Approach: CreditRisk+404

3. The Reduced-Form Approach or Intensity-Based Models411 Notes 422

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Chapter 11Comparison of Industry-Sponsored Credit Models and Associated Back-Testing Issues 425

1. Introduction425

2. Comparison of Industry-Sponsored Credit Risk Models427

3. Stress Testing and Scenario Analysis430

4. Implementation and Validation Issues436 Notes 438

Chapter 12Hedging Credit Risk 441

1. Introduction441

2. Credit Risk Enhancement443

3. Derivative Product Companies446

4. Credit Derivatives448

5. Types of Credit Derivatives452

6. Credit Risk Securitization for Loans and High Yield Bonds461

7. Regulatory Issues466 Notes 470

Chapter 13Managing Operational Risk 475

1. Introduction475

2. Typology of Operational Risks478

3. Who Should Manage Operational Risk?482 4. The Key to Implementing Bank-Wide Operational Risk Management486

5. A Four-Step Measurement Process for Operational Risk489

6. Capital Attribution for Operational Risks505

7. Self-Assessment versus Risk Management Assessment509

8. Integrated Operational Risk511

9. Conclusion513

Appendix 1: Group of Thirty Recommendations: Derivatives and Operational Risk514 Appendix 2: Types of Operational Risk Losses518

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Appendix 3: Severity versus Likelihood519

Appendix 4: Training and Risk Education519

Appendix 5: Identifying and Quantifying Operational Risk523 Notes 526

Chapter 14Capital Allocation and Performance Measurement 529

1. Introduction529

2. Guiding Principles of RAROC Implementation538

3. Relationship of RAROC Capital to Market, Credit, and Operational Risks543

4. Loan Equivalent Approach549

5. Measuring Exposures and Losses for Derivatives551

6. Measuring Risk Adjusted Performance: Second Generation of RAROC Model559 7. Concluding Remarks566

Appendix 1: First Generation of RAROC Model—Assumptions in Calculating Exposures, Expected Default, and Expected Losses 570

Notes 577

Chapter 15Model Risk 579

1. Introduction579

2. Valuation Models and Sources of Model Risk581

3. Typology of Model Risks585

4. What Can Go Wrong?594 5. What Can Market Risk Management Do to Mitigate Model Risk?606

6. Conclusions610 Notes 611

Chapter 16Risk Management in Nonbank Corporations 615

1. Introduction615 2. Why Manage Risks?617

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3. Procedure for Risk Management622

4. Accounting Reports630

5. Reporting Requirements by Securities Authorities634

Appendix 1: Examples of Reports on Risk Exposure by Nike, Merck, and Microsoft, 1988645 Notes 659

Chapter 17Risk Management in the Future 661

2. External Client ProfitabilityA Partner PlusTM Approach669

1. The Total Risk-Enabled Bank661

3. Process for Reviewing Risk in Extreme Markets Will Become Standardized674

4. The Credit Analysis Process and the Need for Integrating Risks678

5. An Idealized Bank of the Future684

Appendix: The Relationship between Market Risk, Business Risk, and Credit Risk685

Notes 690

References 693 Index 709

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Risk is the fundamental element that influences financial behavior. In its absence, the financial system necessary for efficient allocations of resources would be vastly simplified. In that world, only a few institutions and financial instruments would be needed, and the practice of finance would require relatively elementary analytical tools. But, of course, in the real world, risk is ubiquitous. Much of the structure of the financial system we see serves the function of the efficient distribution of risk. Much of the financial decision making by households, business firms, governments, and especially financial institutions is focused on the management of risk. Measuring the influence of risk, and analyzing ways of controlling and allocating it, require a wide range of sophisticated mathematical and computational tools. Indeed, mathematical models of modern finance practice contain some of the most complex applications of probability, optimization, and estimation theories. Those applications challenge the most powerful of computational technologies.

Risk Management provides a comprehensive introduction to the subject. Presented within the framework of a financial institution, it covers the design and operation of a risk-management system, the technical modeling within that system, and the interplay between the internal oversight and the external regulatory components of the system. That its authors, Michel Crouhy, Dan Galai, and Robert Mark, are significant contributors to the science of finance, active practitioners of finance, and experienced teachers of finance is apparent from both its substance and form. The range of topics is broad but evidently carefully chosen for its applicability to practice. The mathematical models and methodology of risk management are presented rigorously, and they are seamlessly integrated with the empirical and clinical evidence on their applications. The book also patiently provides readers without an advanced mathematical background the essential analytical foundations of risk management.

The opening four chapters provide a fine introduction to the function of the risk management system within the institution and

Page xiv on the management of the system itself. Recent regulatory trends are presented to illustrate the expanded role that the internal system plays in informing and meeting the requirements of the external overseers of the institution.

With this as background, the book turns to the core substance of a risk management system with the analysis and modeling of risk measurement and control. Market risk is the first topic explored, including the ubiquitous VaR models and stress testing for identifying and measuring risk exposures to stock market, interest rate, currency, and commodity prices. The analysis shows how to incorporate option, derivative and other ''nonlinear" security exposures into those models.

Nearly a third of the book is devoted to the management of credit risk, and for good reason. Banks are in the business of making loans and they also issue guarantees of financial performance for their customers. They enter into bilateral contractual agreements such as swaps, forward contracts, and options on enormous scales that expose them to the risk that their counterparts to those contracts will not fulfill their obligations. Similarly, insurance companies hold corporate bonds that may default and some guarantee the performance of bonds issued by municipal governments. The credit derivatives business is one of the fastest growing areas for financial products. However, credit risk analysis has even greater importance to risk management in its application to the soundness of the institution itself. Indeed, for financial institutions with principal businesses, which involve issuing contingentpayment contracts such as deposits, annuities, and insurance to their customers, creditworthiness is the central financial issue. The mere prospect of a future default by an institution on its customer obligations can effectively destroy those businesses. Unlike investors in an institution, its customers do not want to bear its credit risk, even for a price. The book presents the major competing models for measuring and valuing credit risk and evaluates them, both theoretically and empirically.

In addition to market and credit risk exposures, a comprehensive approach to risk measurement and risk management must also include operational risks, which is the subject of Chapter 13. Furthermore, no risk management system can be effective without well-designed performance measurement and testing. This is

Page xv needed both to estimate the risk exposures ex ante and to provide an ex post assessment of those estimates relative to predictions, as a feedback on the performance of the system. As laid out in Chapter 14, the system's risk estimates provide the basis for capital attribution among the activities and the accuracy of those estimates determine the amount of equity capital "cushion" needed as a whole.

Mathematical models of valuation and risk assessment are at the core of modern risk management systems. Every major financial institution in the world, including sovereign central banks, depends on these models and none could function without them. Although mainstream and indispensable, these models are by necessity abstractions of the complex real world. Although there is continuing improvement in those models, their accuracy as useful approximations to that world varies significantly across time and situation. Thus, a dimension of risk management that by definition is outside the formal risk management model is model risk. Chapter 15 explores that issue. It drives home the point that there is no "safe harbor" in model error, whether complex mathematical models or traditional measures with rules of thumb. For example, in the case of financial institutions, the traditional accounting leverage ratio measured by total assets/equity can be cut in half by using a "borrow-versus-pledge" method to finance security inventory versus using a "repo-reverse repo" method even though the economic risk of the two methods is identical. Furthermore, the institution can use derivative securities to greatly alter its measured leverage ratio without changing its economic risk. The risk-measurement approaches emphasized in the book are ones that give consistent readings among these different institutional ways of taking on the same risk exposure.

The pace of financial innovation has been extraordinary over the past quarter century and there is no sign of abatement in either product and service innovation or changes in the institutional structures of the providers. As discussed in Chapter 16, a major growth area will be in providing integrated risk management to nonfinancial firms. More generally, from individual households to government users, the trend in financial services lies with integrated products that are smarter, more comprehensive, simpler to understand, and more reliable for those users. The future of risk management, as articulated in Chapter 17, rests in helping the pro-

Page xvi ducer handle the greater complexity of creating and maintaining those products. The prescriptions contained herein will age well.

To the reader: Learn and enjoy.

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The traditional role of the risk manager as corporate steward is evolving as organizations face an increasingly complex and uncertain future. The mandate to clearly identify, measure, manage, and control risk has been expanded and integrated into best practice management of a bank. Today's risk manager is a key member of the senior executive team who helps define business opportunities from a risk-return perspective, presents unique ways of looking at them, has direct input into the configuration of products and services, and ensures the transparency of all the risks. Innovation necessitates new yardsticks for measuring and monitoring the resulting activities. The savvy corporate leader uses risk management as both a sword and a shield.

At the end of the last millennium, financial institutions and investors experienced increased volatility in the major financial and commodity markets, with many financial crises. At the start of the new millennium, we are in the midst of a technological revolution resulting in changes in the operation of markets, increased access to information, changes in the types of services available to investors, as well as major changes in the production and distribution of financial services.

(Parte 1 de 5)