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Credit Risk Modeling Using Excel and VBA with DVD

Book Description

This book provides practitioners and students with a hands-on introduction to modern credit risk modeling. The authors begin each chapter with an accessible presentation of a given methodology, before providing a step-by-step guide to implementation methods in Excel and Visual Basic for Applications (VBA). The book covers default probability estimation (scoring, structural models, and transition matrices), correlation and portfolio analysis, validation, as well as credit default swaps and structured finance. Several appendices and videos increase ease of access.

The second edition includes new coverage of the important issue of how parameter uncertainty can be dealt with in the estimation of portfolio risk, as well as comprehensive new sections on the pricing of CDSs and CDOs, and a chapter on predicting borrower-specific loss given default with regression models. In all, the authors present a host of applications - many of which go beyond standard Excel or VBA usages, for example, how to estimate logit models with maximum likelihood, or how to quickly conduct large-scale Monte Carlo simulations.

Clearly written with a multitude of practical examples, the new edition of Credit Risk Modeling using Excel and VBA will prove an indispensible resource for anyone working in, studying or researching this important field.

"The ebook version does not provide access to the companion files".

Table of Contents

  1. Cover Page
  2. Title Page
  3. Copyright
  4. Dedication
  5. Contents
  6. Preface to the 2nd Edition
  7. Preface to the 1st Edition
  8. Some Hints for Troubleshooting
  9. Chapter 1: Estimating Credit Scores with Logit
    1. LINKING SCORES, DEFAULT PROBABILITIES AND OBSERVED DEFAULT BEHAVIOR
    2. ESTIMATING LOGIT COEFFICIENTS IN EXCEL
    3. COMPUTING STATISTICS AFTER MODEL ESTIMATION
    4. INTERPRETING REGRESSION STATISTICS
    5. PREDICTION AND SCENARIO ANALYSIS
    6. TREATING OUTLIERS IN INPUT VARIABLES
    7. CHOOSING THE FUNCTIONAL RELATIONSHIP BETWEEN THE SCORE AND EXPLANATORY VARIABLES
    8. CONCLUDING REMARKS
    9. NOTES AND LITERATURE
    10. APPENDIX
  10. Chapter 2: The Structural Approach to Default Prediction and Valuation
    1. DEFAULT AND VALUATION IN A STRUCTURAL MODEL
    2. IMPLEMENTING THE MERTON MODEL WITH A ONE-YEAR HORIZON
    3. IMPLEMENTING THE MERTON MODEL WITH A T-YEAR HORIZON
    4. CREDIT SPREADS
    5. CREDITGRADES
    6. APPENDIX
    7. NOTES AND LITERATURE
  11. Chapter 3: Transition Matrices
    1. COHORT APPROACH
    2. MULTI-PERIOD TRANSITIONS
    3. HAZARD RATE APPROACH
    4. OBTAINING A GENERATOR MATRIX FROM A GIVEN TRANSITION MATRIX
    5. CONFIDENCE INTERVALS WITH THE BINOMIAL DISTRIBUTION
    6. BOOTSTRAPPED CONFIDENCE INTERVALS FOR THE HAZARD APPROACH
    7. NOTES AND LITERATURE
    8. APPENDIX
  12. Chapter 4: Prediction of Default and Transition Rates
    1. CANDIDATE VARIABLES FOR PREDICTION
    2. PREDICTING INVESTMENT-GRADE DEFAULT RATES WITH LINEAR REGRESSION
    3. PREDICTING INVESTMENT-GRADE DEFAULT RATES WITH POISSON REGRESSION
    4. BACKTESTING THE PREDICTION MODELS
    5. PREDICTING TRANSITION MATRICES
    6. ADJUSTING TRANSITION MATRICES
    7. REPRESENTING TRANSITION MATRICES WITH A SINGLE PARAMETER
    8. SHIFTING THE TRANSITION MATRIX
    9. BACKTESTING THE TRANSITION FORECASTS
    10. SCOPE OF APPLICATION
    11. NOTES AND LITERATURE
    12. APPENDIX
  13. Chapter 5: Prediction of Loss Given Default
    1. CANDIDATE VARIABLES FOR PREDICTION
    2. CREATING A DATA SET
    3. REGRESSION ANALYSIS OF LGD
    4. BACKTESTING PREDICTIONS
    5. NOTES AND LITERATURE
    6. APPENDIX
  14. Chapter 6: Modeling and Estimating Default Correlations with the Asset Value Approach
    1. DEFAULT CORRELATION, JOINT DEFAULT PROBABILITIES AND THE ASSET VALUE APPROACH
    2. CALIBRATING THE ASSET VALUE APPROACH TO DEFAULT EXPERIENCE: THE METHOD OF MOMENTS
    3. ESTIMATING ASSET CORRELATION WITH MAXIMUM LIKELIHOOD
    4. EXPLORING THE RELIABILITY OF ESTIMATORS WITH A MONTE CARLO STUDY
    5. CONCLUDING REMARKS
    6. NOTES AND LITERATURE
  15. Chapter 7: Measuring Credit Portfolio Risk with the Asset Value Approach
    1. A DEFAULT-MODE MODEL IMPLEMENTED IN THE SPREADSHEET
    2. VBA IMPLEMENTATION OF A DEFAULT-MODE MODEL
    3. IMPORTANCE SAMPLING
    4. QUASI MONTE CARLO
    5. ASSESSING SIMULATION ERROR
    6. EXPLOITING PORTFOLIO STRUCTURE IN THE VBA PROGRAM
    7. DEALING WITH PARAMETER UNCERTAINTY
    8. EXTENSIONS
    9. NOTES AND LITERATURE
  16. Chapter 8: Validation of Rating Systems
    1. CUMULATIVE ACCURACY PROFILE AND ACCURACY RATIOS
    2. RECEIVER OPERATING CHARACTERISTIC (ROC)
    3. BOOTSTRAPPING CONFIDENCE INTERVALS FOR THE ACCURACY RATIO
    4. INTERPRETING CAPS AND ROCS
    5. BRIER SCORE
    6. TESTING THE CALIBRATION OF RATING-SPECIFIC DEFAULT PROBABILITIES
    7. VALIDATION STRATEGIES
    8. TESTING FOR MISSING INFORMATION
    9. NOTES AND LITERATURE
  17. Chapter 9: Validation of Credit Portfolio Models
    1. TESTING DISTRIBUTIONS WITH THE BERKOWITZ TEST
    2. REPRESENTING THE LOSS DISTRIBUTION
    3. SIMULATING THE CRITICAL CHI-SQUARE VALUE
    4. TESTING MODELING DETAILS: BERKOWITZ ON SUBPORTFOLIOS
    5. ASSESSING POWER
    6. SCOPE AND LIMITS OF THE TEST
    7. NOTES AND LITERATURE
  18. Chapter 10: Credit Default Swaps and Risk-Neutral Default Probabilities
    1. DESCRIBING THE TERM STRUCTURE OF DEFAULT: PDS CUMULATIVE, MARGINAL AND SEEN FROM TODAY
    2. FROM BOND PRICES TO RISK-NEUTRAL DEFAULT PROBABILITIES
    3. PRICING A CDS
    4. REFINING THE PD ESTIMATION
    5. MARKET VALUES FOR A CDS
    6. ESTIMATING UPFRONT CDS AND THE ‘BIG BANG’ PROTOCOL
    7. PRICING OF A PRO-RATA BASKET
    8. FORWARD CDS SPREADS
    9. PRICING OF SWAPTIONS
    10. NOTES AND LITERATURE
    11. APPENDIX
  19. Chapter 11: Risk Analysis and Pricing of Structured Credit: CDOs and First-to-Default Swaps
    1. ESTIMATING CDO RISK WITH MONTE CARLO SIMULATION
    2. THE LARGE HOMOGENEOUS PORTFOLIO (LHP) APPROXIMATION
    3. SYSTEMIC RISK OF CDO TRANCHES
    4. DEFAULT TIMES FOR FIRST-TO-DEFAULT SWAPS
    5. CDO PRICING IN THE LHP FRAMEWORK
    6. SIMULATION-BASED CDO PRICING
    7. NOTES AND LITERATURE
    8. APPENDIX
  20. Chapter 12: Basel II and Internal Ratings
    1. CALCULATING CAPITAL REQUIREMENTS IN THE INTERNAL RATINGS-BASED (IRB) APPROACH
    2. ASSESSING A GIVEN GRADING STRUCTURE
    3. TOWARDS AN OPTIMAL GRADING STRUCTURE
    4. NOTES AND LITERATURE
  21. Appendix A1: Visual Basics for Applications (VBA)
    1. MACROS AND FUNCTIONS
    2. WRITING A NEW MACRO OR FUNCTION
  22. Appendix A2: Solver
  23. Appendix A3: Maximum Likelihood Estimation and Newton's Method
  24. Appendix A4: Testing and Goodness of Fit
  25. Appendix A5: User-defined Functions
    1. INSTALLATION OF THE ADD-IN
    2. FUNCTION LIST
  26. Index