A First Course in Model Validation and Model Risk Management offers robust coverage for current and future financial engineers. Useful as part of a masters program, for self-study, or as a valuable reference, the textbook explains in step-by-step, practical terms how mathematical models owned by financial institutions are essential to their public activities, including sales, trading, risk management, and internal audits. Like a diverse fleet of cars maintained by a rental car location, a bank must make sure customers can "drive" any of its models for a specific financial product. The book covers both pricing and risk models. Chapters consider modeling basics, marked-to-market and marked-to-model asset classes, market risk, credit risk, portfolio risk, operational risk, capital model risk, and financial crime, along with machine learning/AI.
To support course use and practical applications, the text provides examples in Python throughout, as well as an appendix containing homework problems for all chapters, further supported by an ftp site for data and sample code. Additional appendices cover global model risk management, and a refresher in statistics.
1. Introduction - p. xxix 2. Chapter 1. Introductory Material - p. 1 3. Chapter 2. Model Basics - p. 9 4. Chapter 3. Standards - p. 31 5. Chapter 4. Techniques - p. 41 6. Chapter 5. Marked-to-Market Asset Classes - p. 79 7. Chapter 6. Marked-to-Model Asset Classes - p. 91 8. Chapter 7. Market Risk I: Statistical Measures - p. 101 9. Chapter 8. Market Risk II: Stress Testing - p. 129 10. Chapter 9. Issuer Credit Risk - p. 151 11. Chapter 10. Counterparty Credit Risk - p. 183 12. Chapter 11. Correlation Credit Risk - p. 197 13. Chapter 12. Portfolio Risk - p. 219 14. Chapter 13. Operational Risk - p. 237 15. Chapter 14. Capital Model Risk - p. 259 16. Chapter 15. Artificial Intelligence Risk - p. 269 17. Chapter 16. Miscellaneous Topics in Model Risk - p. 307 18. 16.1 Transition From IBORS to RFRS: SOFR - p. 307 19. 16.2 Regulatory Risk - p. 318 20. 16.3 Anti–Money Laundering/Sanctions Models - p. 323 21. 16.4 Fraud Detection Models - p. 326 22. 16.5 Model Validation at Insurance Firms - p. 339 23. 16.6 The Greeks (Sensitivities) - p. 340 24. 16.7 Monte Carlo Simulations - p. 347 25. 16.8 Mortgage Model Risk - p. 363 26. 16.9 Validation of Qualitative Models - p. 372 27. Chapter 17. Model Governance - p. 375 28. Appendix A:. Homework Problems - p. 389 29. Chapter 1: Introductory Material - p. 389 30. Chapter 2: Model Basics - p. 390 31. Answers - p. 391 32. Chapter 3: Standards - p. 392 33. Chapter 4: Techniques - p. 394 34. Chapter 5: Marked-to-Market Asset Classes - p. 404 35. Chapter 6: Marked-to-Model Asset Classes - p. 405 36. Chapter 7: Market Risk I: Statistical Measures - p. 405 37. Chapter 8: Market Risk II: Stress Testing - p. 409 38. Chapter 9: Issuer Credit Risk - p. 412 39. Chapter 10: Counterparty Credit Risk - p. 412 40. Chapter 11: Correlation Credit Risk - p. 414 41. Chapter 12: Portfolio Risk - p. 416 42. Chapter 13: Operational Risk - p. 419 43. Chapter 14: Capital Model Risk - p. 421 44. Chapter 15: Artificial Intelligence: Models, Enhancements to MRM, and Regulation - p. 422 45. Chapter 16: Miscellaneous Topics in Model Risk - p. 430 46. Chapter 17: Model Governance - p. 438 47. Appendix C: Statistics Refresher - p. 440 48. Appendix B:. Global MRM Regulation - p. 447 49. Appendix C:. Statistics Refresher - p. 471 50. Appendix D:. Online Content - p. 505 51. Bibliography - p. 533 52. Index - p. 545
A First Course in Model Validation and Model Risk Management offers robust coverage for current and future financial engineers. Useful as part of a masters program, for self-study, or as a valuable reference, the textbook explains in step-by-step, practical terms how mathematical models owned by financial institutions are essential to their public activities, including sales, trading, risk management, and internal audits. Like a diverse fleet of cars maintained by a rental car location, a bank must make sure customers can "drive" any of its models for a specific financial product. The book covers both pricing and risk models. Chapters consider modeling basics, marked-to-market and marked-to-model asset classes, market risk, credit risk, portfolio risk, operational risk, capital model risk, and financial crime, along with machine learning/AI.
To support course use and practical applications, the text provides examples in Python throughout, as well as an appendix containing homework problems for all chapters, further supported by an ftp site for data and sample code. Additional appendices cover global model risk management, and a refresher in statistics.
1. Introduction - p. xxix 2. Chapter 1. Introductory Material - p. 1 3. Chapter 2. Model Basics - p. 9 4. Chapter 3. Standards - p. 31 5. Chapter 4. Techniques - p. 41 6. Chapter 5. Marked-to-Market Asset Classes - p. 79 7. Chapter 6. Marked-to-Model Asset Classes - p. 91 8. Chapter 7. Market Risk I: Statistical Measures - p. 101 9. Chapter 8. Market Risk II: Stress Testing - p. 129 10. Chapter 9. Issuer Credit Risk - p. 151 11. Chapter 10. Counterparty Credit Risk - p. 183 12. Chapter 11. Correlation Credit Risk - p. 197 13. Chapter 12. Portfolio Risk - p. 219 14. Chapter 13. Operational Risk - p. 237 15. Chapter 14. Capital Model Risk - p. 259 16. Chapter 15. Artificial Intelligence Risk - p. 269 17. Chapter 16. Miscellaneous Topics in Model Risk - p. 307 18. 16.1 Transition From IBORS to RFRS: SOFR - p. 307 19. 16.2 Regulatory Risk - p. 318 20. 16.3 Anti–Money Laundering/Sanctions Models - p. 323 21. 16.4 Fraud Detection Models - p. 326 22. 16.5 Model Validation at Insurance Firms - p. 339 23. 16.6 The Greeks (Sensitivities) - p. 340 24. 16.7 Monte Carlo Simulations - p. 347 25. 16.8 Mortgage Model Risk - p. 363 26. 16.9 Validation of Qualitative Models - p. 372 27. Chapter 17. Model Governance - p. 375 28. Appendix A:. Homework Problems - p. 389 29. Chapter 1: Introductory Material - p. 389 30. Chapter 2: Model Basics - p. 390 31. Answers - p. 391 32. Chapter 3: Standards - p. 392 33. Chapter 4: Techniques - p. 394 34. Chapter 5: Marked-to-Market Asset Classes - p. 404 35. Chapter 6: Marked-to-Model Asset Classes - p. 405 36. Chapter 7: Market Risk I: Statistical Measures - p. 405 37. Chapter 8: Market Risk II: Stress Testing - p. 409 38. Chapter 9: Issuer Credit Risk - p. 412 39. Chapter 10: Counterparty Credit Risk - p. 412 40. Chapter 11: Correlation Credit Risk - p. 414 41. Chapter 12: Portfolio Risk - p. 416 42. Chapter 13: Operational Risk - p. 419 43. Chapter 14: Capital Model Risk - p. 421 44. Chapter 15: Artificial Intelligence: Models, Enhancements to MRM, and Regulation - p. 422 45. Chapter 16: Miscellaneous Topics in Model Risk - p. 430 46. Chapter 17: Model Governance - p. 438 47. Appendix C: Statistics Refresher - p. 440 48. Appendix B:. Global MRM Regulation - p. 447 49. Appendix C:. Statistics Refresher - p. 471 50. Appendix D:. Online Content - p. 505 51. Bibliography - p. 533 52. Index - p. 545
