Assessing Risk Assessment: Towards Alternative Risk Measures for Complex Financial Systems

Christian Hugo Hoffmann undermines the citadel of risk assessment and management, arguing that classical probability theory is not an adequate foundation for modeling systemic and extreme risk in complex financial systems. He proposes a new class of models which focus on the knowledge dimension by precisely describing market participants’ own positions and their propensity to react to outside changes. The author closes his thesis by a synthetical reflection on methods and elaborates on the meaning of decision-making competency in a risk management context in banking. By choosing this poly-dimensional approach, the purpose of his work is to explore shortcomings of risk management approaches of financial institutions and to point out how they might be overcome.

Table of Contents

Part I:Concepts, Model Level and Risk Assessment
Chapter 1. Introduction To Part I
Chapter 2. Literature Synthesis, Theoretical Background And Research Focus
Chapter 3. Research Questions
Chapter 4. On An Adequate Concept Of Risk And Systemic Risk In The Realm Of Banking
Chapter 5. On The Relevance Of Systemic Risks For Banks
Chapter 6. Dealing With Quantitative Risk Management In Banking As A Complex Systems Problem
Chapter 7. The Fundamental Inadequacy Of Probability Theory As A Foundation For Modeling Systemic And Extreme Risk In A Banking Context
Chapter 8. Conclusion To Part I

Part II:The Transition to the Decision Level, Risk Assessment andManagement
Chapter 9. Introduction To Part Ii
Chapter 10. The Critical Turn: The Renaissance Of Practical Wisdom
Chapter 11. Scenario Planning In A Nutshell And Its Role In Risk Management In Banking
Chapter 12. Strengths And Weaknesses Of Scenario Planning As A Risk Management Tool
Chapter 13. Deriving Lessons For Rethinking The Approach To Assessing Extreme And Systemic Risks

Part III:In Search of a New Paradigm: The Third Way as a Road toLogic-Based Risk Modeling (LBR)
Chapter 14. Introduction To Part Iii
Chapter 15. Theoretical Foundations Of A Logic-Based Risk Modeling (Lbr) Approach
Chapter 16. Case Study: Ltcm And Extreme Risk
Chapter 17. Managerial Implications
Chapter 18. Scales Of Measurement And Qualitative Probabilities
Chapter 19. Model Validation

Part IV:Meta Level: Thinking about Thinking and Practices – What itMeans to Reach Effective Risk Management Decisions
Chapter 20. Introduction To Part Iv As Overall Conclusion
Chapter 21. Escaping The Traps For Logicians: Towards Decision-Making Competency In Risk Management
Chapter 22. Final Remarks And A Path For Future Research