A First Course in Model Validation and Model Risk Management

Nyhet

Häftad, Engelska, 2026

AvJonathan Schachter,Martin Goldberg,Chandrakant Maheshwari

1 299 kr

Kommande

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.

Offers practical concepts for learning model validation and model risk management
Explains how to use Python-based models to assess and manage model risk
Covers the US gold standard of model risk, "Federal Reserve Board SR 11-7", including testing inputs, testing outputs, benchmarking, outcomes analysis, third party models, and compensating controls
Discusses model governance, including model inventory , risk ratings, and the three lines of defense
Provides Instructor Manuals for qualified instructors via https://www.educate.elsevier.com/book/details/9780443337468

Produktinformation

Utgivningsdatum2026-03-27
Mått191 x 235 x undefined mm
Vikt450 g
FormatHäftad
SpråkEngelska
Antal sidor400
FörlagElsevier Science
ISBN9780443337468

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Jonathan Schachter holds a PhD from University of California, Berkeley, and has over 23 years of experience as a model risk professional, with a practical background in market risk, portfolio risk, operational risk, capital model risk, and AI risk. Currently Jonathan is CEO and Founder of Delta Vega Inc, and has previously held positions at Jefferies Financial and Citibank, among other firms. Martin Goldberg holds a PhD from City University of New York, and is Vice President in Model Validation at Mizuho Americas. He has held past positions at Citigroup, Bloomberg, AIG, and Chase Manhattan Bank. He is also on the Board of Directors for Rutgers University (Newark), for their Master of Quantitative Finance (MQF) Program, and has presented widely at conferences and universities on topics related to model risk assessment. Chandrakant Maheshwari is a seasoned expert in model validation with over 20 years of experience in financial risk analytics. An alum of the Indian Institute of Technology, Delhi, he is also an avid blogger and regularly publishes articles on model validation, sharing his extensive knowledge and insights in the field.

1. Introductory Material1.1 Why Are We Writing This Book?1.2 Computer Code1.3 Note on Technical Terms, Jargon, Abbreviations, and Notation1.4 What Is Not in This Book1.5 To the Instructor2. Model Basics2.1 History of MRM2.2 What Is a Model?2.3 What Is Model Risk?2.4 What is MVal?2.5 Impact of MVal2.6 Validation Use Cases3. Standards3.1 Independence3.2 Effective Challenge3.3 Benchmarking3.4 Testing3.5 Vendors4. Techniques4.1 New Model Registration4.2 Classification and Risk Rating4.3 Replication4.4 Benchmarking4.5 Documentation4.6 Model Governance Preview4.7 Other Validation Testing Techniques4.8 Postvalidation Testing, Also Called “Ongoing Monitoring”4.9 Toolkits4.10 Job Functions and Lines of Defense4.11 Diplomacy and Communication4.12 Role of Consultants4.12 Example―Validation of Black-Scholes5. Marked-to-Market Asset Classes5.1 Introduction5.2 Fixed Income5.3 Equity5.4 FX5.5 Commodities6. Marked-to-Model Asset Classes6.1 Bonds6.2 Exotics6.3 Structured Credit and Securitizations6.4 Equity Exotics6.5 Other Asset Classes7. Market Risk I: Statistical Measures7.1 Value-at-Risk7.2 VaR Decomposition7.3 Validating VaR Assumptions7.4 Validating VaR Inputs7.5 VaR Backtesting7.6 Expected Shortfall7.7 Curing Problematic Timeseries: EWMA8. Market Risk II: Stress Testing8.1 Introduction8.2 Details of CCAR Scenarios8.3 CCAR Models8.4 Building Stress Scenarios and Applying the Stresses to the Bank’s Positions8.5 Internal Stress Tests9. Issuer Credit Risk9.1 Introduction9.2 Philosophy of Credit Ratings9.3 PD, LGD, and EAD9.4 Credit Ratings in Practice9.5 Scorecard Models10. Counterparty Credit Risk10.1 Valuation Adjustments10.2 Wrong Way Risk (WWR)10.3 Potential Future Exposure (PFE) Basics10.4 PFE Advanced Modeling Approach (AMA)10.5 SIMM: The Standard Initial Margin Model11. Correlation Credit Risk11.1 Single-Name Credit Products11.2 Simple Correlation Products11.3 Tranched Correlation Products11.4 Correlation Credit and the Great Financial Crisis12. Portfolio Risk12.1 Equity Performance12.2 Statistical Arbitrage12.3 Hedge Fund Basics12.4 Proprietary Hedge Fund Equity Models13. Operational Risk13.1 The Basel OR Event Types13.2 ORX Nonfinancial Risk Levels13.3 Standard Approach to OR Capital13.4 Advanced Approach: OR Models13.5 Key Risk Indicators13.6 OR Stress Testing14. Capital Model Risk14.1 Regulatory Capital14.2 History of U.S. Bank Capital14.3 Basel Ratios and Buffers14.4 SIFI Tests14.5 Economic Capital15. Artificial Intelligence Risk15.1 Validating Pricing and Risk AI Models15.2 MRM Assisted by AI15.3 AI Explainability15.4 Essentials of AI MRM15.5 AI Use By Central Banks15.6 AI Standards16. Miscellaneous Topics in Model Risk16.1 Transition From IBORs to RFRs: SOFR16.2 Regulatory Risk16.3 Anti—Money Laundering/Sanctions Models16.4 Fraud Detection Models16.5 Model Validation at Insurance Firms16.6 The Greeks (Sensitivities)16.7 Monte Carlo Simulations16.8 Mortgage Model Risk16.9 Validation of Qualitative Models17. Model GovernancePrologue17.1 Introduction17.2 Model Inventory17.3 Model Restrictions17.4 Internal Audit17.5 Policies and Procedures17.6 Role of Regulators17.7 Personnel17.8 Model Governance in PracticeAppendix A: Homework ProblemsAppendix B: Global MRM RegulationAppendix C: Statistics RefresherAppendix D: Online ContentIndex

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