Assessing Risk Assessment

1 - Table of Contents [Seite 5]
2 - List of Tables and Figures [Seite 8]
3 - Abstract [Seite 10]
4 - Zusammenfassung [Seite 12]
5 - Introduction [Seite 14]
6 - Part I:Concepts, Model Level and Risk Assessment [Seite 33]
6.1 - 1. Introduction to Part I [Seite 34]
6.2 - 2. Literature Synthesis, Theoretical Background and Research Focus [Seite 36]
6.2.1 - 2.1. Complexity and Modern Financial Systems [Seite 36]
6.2.2 - 2.2. Risk and Risk Management in the Financial World [Seite 43]
6.2.2.1 - 2.2.1. Risk modeling [Seite 48]
6.2.2.2 - 2.2.2. Value at Risk (VaR) [Seite 52]
6.2.2.3 - 2.2.3. Expected Shortfall (ES) [Seite 58]
6.2.3 - 2.3. Systemic Risk Assessment [Seite 60]
6.2.3.1 - 2.3.1. Tools primarily for regulators: Conditional Value at Risk (CoVaR) and Systemic Expected Shortfall (SES) [Seite 62]
6.2.3.2 - 2.3.2. Extreme Value Theory (EVT) [Seite 64]
6.2.4 - 2.4. General Appraisal [Seite 66]
6.2.4.1 - 2.4.1. Advantages of conventional risk models and measures [Seite 67]
6.2.4.2 - 2.4.2. Weaknesses of conventional risk models and measures [Seite 69]
6.2.5 - 2.5. Excursus: Benoît Mandelbrot's Plea for Fractal Methods [Seite 74]
6.3 - 3. Research Questions [Seite 83]
6.4 - 4. On an Adequate Concept of Risk and Systemic Risk in the realm of Banking [Seite 85]
6.4.1 - 4.1. The Notion of Risk [Seite 85]
6.4.2 - 4.2. The Concept of Systemic Risk [Seite 101]
6.5 - 5. On the Relevance of Systemic Risks for Banks [Seite 113]
6.5.1 - 5.1. Why should Banks take account of, and try to deal with, Systemic Risks? [Seite 113]
6.5.2 - 5.2. What are concrete Systemic Risk Scenarios for Banks? [Seite 125]
6.6 - 6. Dealing with Quantitative Risk Management in Banking as a Complex Systems Problem [Seite 132]
6.6.1 - 6.1. A Trichotomy of Scientific Problems - Warren Weaver's Scheme as a General Answer to How to Manage Complexity [Seite 137]
6.6.1.1 - 6.1.1. Tackling disorganized complexity versus organized simplicity [Seite 137]
6.6.1.2 - 6.1.2. Disorganized complexity and statistical techniques [Seite 140]
6.6.1.3 - 6.1.3. Tackling organized complexity: open questions remain [Seite 143]
6.6.1.4 - 6.1.4. Synopsis [Seite 145]
6.6.2 - 6.2. Weaver's Taxonomy Revisited: Attempts of Clarification, Extension and Refinement [Seite 148]
6.6.2.1 - 6.2.1. Approaches towards the operationalization of Weaver's concept of organized complexity [Seite 148]
6.6.2.2 - 6.2.2. The bigger picture of complexity and randomness [Seite 151]
6.6.3 - 6.3. Organized Complexity, Financial Systems and Assessing Extreme and Systemic Risks [Seite 161]
6.6.3.1 - 6.3.1. On the level of structures [Seite 163]
6.6.3.2 - 6.3.2. On the level of events [Seite 164]
6.6.4 - 6.4. A Tentative Bottom Line [Seite 166]
6.7 - 7. The Fundamental Inadequacy of Probability Theory as a Foundation for Modeling Systemic and Extreme Risk in a Banking Context [Seite 168]
6.7.1 - 7.1. Philosophical Roots of the Problem of Induction: some Preliminaries [Seite 170]
6.7.2 - 7.2. Probability Theory in a Nutshell, its Embeddedness and its Applications [Seite 173]
6.7.3 - 7.3. The Central Argument against using Probability Theory for Financial Risk Management [Seite 184]
6.7.4 - 7.4. Linking the Central Argument with the Current State of the Literature (IIIa)-c)) [Seite 192]
6.8 - 8. Conclusion to Part I [Seite 195]
6.8.1 - 8.1. Résumé [Seite 196]
6.8.2 - 8.2. Outlook: Explanatory Models for In-House Risk Management in Banking [Seite 199]
7 - Part II:The Transition to the Decision Level, Risk Assessment andManagement [Seite 203]
7.1 - 9. Introduction to Part II [Seite 204]
7.2 - 10. The Critical Turn: The Renaissance of Practical Wisdom [Seite 206]
7.3 - 11. Scenario Planning in a Nutshell and its Role in Risk Management in Banking [Seite 212]
7.4 - 12. Strengths and Weaknesses of Scenario Planning as a Risk Management Tool [Seite 220]
7.5 - 13. Deriving Lessons for Rethinking the Approach to Assessing Extreme and Systemic Risks [Seite 226]
8 - Part III:In Search of a New Paradigm: The Third Way as a Road toLogic-Based Risk Modeling (LBR) [Seite 230]
8.1 - 14. Introduction to Part III [Seite 231]
8.2 - 15. Theoretical Foundations of a Logic-Based Risk Modeling (LBR) Approach [Seite 236]
8.2.1 - 15.1. A less Restrictive Axiomatization [Seite 236]
8.2.2 - 15.2. Non-Probabilistic Models of Uncertainty [Seite 244]
8.2.3 - 15.3. Ranking Theory [Seite 248]
8.2.4 - 15.4. Syntax of a Language for Describing Contracts and Correlations [Seite 251]
8.2.5 - 15.5. Semantics: Financial Contracts as Uncertain Sequences in a Non-Probabilistic Risk Model Context [Seite 257]
8.2.5.1 - 15.5.1. Uncertain sequences by example [Seite 258]
8.2.5.2 - 15.5.2. From contract value to risk [Seite 262]
8.2.5.3 - 15.5.3. Formalization of the approach [Seite 263]
8.2.5.4 - 15.5.4. Concrete instantiations of uncertainty monads: ranking functions [Seite 1]
8.2.5.5 - 15.5.5. Evaluating risk models [Seite 275]
8.2.6 - 15.6. Model Interpretation and Output: An Exact, Explanatory Scenario Planning Method [Seite 280]
8.3 - 16. Case Study: LTCM and Extreme Risk [Seite 284]
8.3.1 - 16.1. Example Trade [Seite 285]
8.3.2 - 16.2. A Fixed Income Portfolio in LBR [Seite 286]
8.3.3 - 16.3. Analysis [Seite 289]
8.3.3.1 - 16.3.1. Overview [Seite 290]
8.3.3.2 - 16.3.2. Zoom and filter [Seite 291]
8.3.3.3 - 16.3.3. Details on demand [Seite 293]
8.3.4 - 16.4. Discussion and Conclusion [Seite 293]
8.4 - 17. Managerial Implications [Seite 296]
8.5 - 18. Scales of Measurement and Qualitative Probabilities [Seite 302]
8.6 - 19. Model Validation [Seite 308]
9 - Part IV:Meta Level: Thinking about Thinking and Practices - What itMeans to Reach Effective Risk Management Decisions [Seite 325]
9.1 - 20. Introduction to Part IV as Overall Conclusion [Seite 326]
9.2 - 21. Escaping the Traps for Logicians: Towards Decision-Making Competency in Risk Management [Seite 328]
9.3 - 22. Final Remarks and a Path for Future Research [Seite 341]
10 - References [Seite 346]
11 - Appendices [Seite 377]