A First Course in Model Validation and Model Risk Management

Erscheinungsjahr 2026
ISBN: 978-0-443-33746-8
Verlag: Elsevier LTD

Buch, Englisch, 400 Seiten, Format (B × H): 191 mm x 235 mm, Gewicht: 450 g

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.

Autoren/Hrsg.

Schachter, Jonathan

Goldberg, Martin

Maheshwari, Chandrakant

Fachgebiete

• Wirtschaftswissenschaften Betriebswirtschaft Unternehmensfinanzen Controlling, Wirtschaftsprüfung, Revision
• Wirtschaftswissenschaften Wirtschaftswissenschaften Wirtschaft: Sachbuch, Ratgeber

Inhaltsverzeichnis

Foundations and Applications of Game Theory
1. Applications of Game Theory in Artificial Intelligence: A Review
2. Applications of Game Theory in Climate Change Studies: A Review
3. A Review on the Applications of Game Theory in Environmental Health
4. Applications of game theory in renewable energy studies: A review
5. Tourist-resident interactions in evolutionary games: tourism and sustainability
6. Exploring the Evolution and Impact of Learning-Driven Game Theory for AI: A Bibliometric Analysis
Game Theory in Learning and AI Systems
7. Evolutionary Game Dynamics of Learning in Neural Networks Through Replicator Equations
8. Game-Based Ensemble Learning for Classifying Multi-Class Problems
9. Fair Incentive Allocation in Vertical Federated Learning Using Nucleolus

Game Theory and Explainability in AI
10. Several Perspectives on Explainable AI in Medicine: Game Theory Integrated Learning
11. Inverse Game Theory for Preference Learning in Generative AI Systems: A Computational

Complexity Framework
12. MYerson Additive Explanations on Graphs (MYER): Advancement of Explainable Artificial Intelligence Using a Graphical Approach

Mathematical Models and Adaptive Algorithms
13. Integrating Game-Theoretic Learning with AI for Lung Cancer Diagnosis and Risk Prediction
14. Truth as Geometry: A Topological Approach to Logic, Uncertainty, and AI Reasoning
15. Pursuit-Evasion Differential Games with Gronwall-Type Constraints: A Theoretical Study
16. Pursuit-Evasion Game under Lawden-Type Constraints
17. Guaranteed Pursuit Time of a Linear Pursuit Differential Game with a Mixed Constraints on Players’
Control Functions
18. Adaptive Control of Opinion Dynamics on a Social Network with a Principal
19. An Enhanced K-Means Clustering Approach: NBK-means Algorithm

Über Autor(innen)

Maheshwari, Chandrakant
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.

Goldberg, Martin
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.

Schachter, Jonathan
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.