Coherent stress testing : a Bayesian approach to the analysis of financial stress / / Riccardo Rebonato

• Record Nr.: UNINA9910825531003321
• Autore: Rebonato Riccardo
• Pubbl/distr/stampa: Hoboken, NJ, : Wiley, 2010
• ISBN: 0-470-97148-7; 1-118-37471-1; 1-282-68378-0; 9786612683787; 0-470-66736-2
• Edizione: [1st ed.]
• Descrizione fisica: 1 online resource (241 p.)
• Disciplina: 658.15/501519542
• Soggetti: Risk management; Probabilities; Bayesian statistical decision theory
• Lingua di pubblicazione: Inglese
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Note generali: Bibliographic Level Mode of Issuance: Monograph
• Nota di contenuto: Coherent Stress Testing -- Contents -- Acknowledgements -- 1 Introduction -- 1.1 Why We Need Stress Testing -- 1.2 Plan of the Book -- 1.3 Suggestions for Further Reading -- I Data, Models and Reality -- 2 Risk and Uncertainty - or, Why Stress Testing is Not Enough -- 2.1 The Limits of Quantitative Risk Analysis -- 2.2 Risk or Uncertainty? -- 2.3 Suggested Reading -- 3 The Role of Models in Risk Management and Stress Testing -- 3.1 How Did We Get Here? -- 3.2 Statement of the Two Theses of this Chapter -- 3.3 Defence of the First Thesis (Centrality of Models) -- 3.3.1 Models as Indispensable Interpretative Tools -- 3.3.2 The Plurality-of-Models View -- 3.4 Defence of the Second Thesis (Coordination) -- 3.4.1 Traders as Agents -- 3.4.2 Agency Brings About Coordination -- 3.4.3 From Coordination to Positive Feedback -- 3.5 The Role of Stress and Scenario Analysis -- 3.6 Suggestions for Further Reading -- 4 What Kind of Probability Do We Need in Risk Management? -- 4.1 Frequentist versus Subjective Probability -- 4.2 Tail Co-dependence -- 4.3 From Structural Models to Co-dependence -- 4.4 Association or Causation? -- 4.5 Suggestions ; for Further Reading -- II The Probabilistic Tools and Concepts -- Probability with Boolean Variables I: Marginal and Conditional Probabilities -- 5.1 The Set-up and What We are Trying to Achieve -- 5.2 (Marginal) Probabilities -- 5.3 Deterministic Causal Relationship -- 5.4 Conditional Probabilities -- 5.5 Time Ordering and Causation -- 5.6 An Important Consequence: Bayes' Theorem -- 5.7 Independence -- 5.8 Two Worked-Out Examples -- 5.8.1 Dangerous Running -- 5.8.2 Rare and Even More Dangerous Diseases -- 5.9 Marginal and Conditional Probabilities: A Very Important Link -- 5.10 Interpreting and Generalizing the Factors -- 5.11 Conditional Probability Maps -- 6 Probability with Boolean Variables II: Joint Probabilities.; 6.1 Conditioning on More Than One Event -- 6.2 Joint Probabilities -- 6.3 A Remark on Notation -- 6.4 From the Joint to the Marginal and the Conditional Probabilities -- 6.5 From the Joint Distribution to Event Correlation -- 6.6 From the Conditional and Marginal to the Joint Probabilities? -- 6.7 Putting Independence to Work -- 6.8 Conditional Independence -- 6.9 Obtaining Joint Probabilities with Conditional Independence -- 6.10 At a Glance -- 6.11 Summary -- 6.12 Suggestions for Further Reading -- 7 Creating Probability Bounds -- 7.1 The Lay of the Land -- 7.2 Bounds on Joint Probabilities -- 7.3 How Tight are these Bounds in Practice? -- 8 Bayesian Nets I: An Introduction -- 8.1 Bayesian Nets: An Informal Definition -- 8.2 De.ning the Structure of Bayesian Nets -- 8.3 More About Conditional Independence -- 8.4 What Goes in the Conditional Probability Tables? -- 8.5 Useful Relationships -- 8.6 A Worked-Out Example -- 8.7 A Systematic Approach -- 8.8 What Can We Do with Bayesian Nets? -- 8.8.1 Unravelling the Causal Structure -- 8.8.2 Estimating the Joint Probabilities -- 8.9 Suggestions for Further Reading -- 9 Bayesian Nets II: Constructing Probability Tables -- 9.1 Statement of the Problem -- 9.2 Marginal Probabilities - First Approach -- 9.2.1 Starting from a Fixed Probability -- 9.2.2 Starting from a Fixed Magnitude of the Move -- 9.3 Marginal Probabilities - Second Approach -- 9.4 Handling Events of Different Probability -- 9.5 Conditional Probabilities: A Reasonable Starting Point -- 9.6 Conditional Probabilities: Checks and Constraints -- 9.6.1 Necessary Conditions -- 9.6.2 Triplet Conditions -- 9.6.3 Independence -- 9.6.4 Deterministic Causation -- 9.6.5 Incompatibility of Events -- 9.7 Internal Compatibility of Conditional Probabilities: The Need for a Systematic Approach -- III Applications.; 10 Obtaining a Coherent Solution I: Linear Programming -- 10.1 Plan of the Work Ahead -- 10.2 Coherent Solution with Conditional Probabilities Only -- 10.3 The Methodology in Practice: First Pass -- 10.4 The CPU Cost of the Approach -- 10.5 Illustration of the Linear Programming Technique -- 10.6 What Can We Do with this Information? -- 10.6.1 Extracting Information with Conditional Probabilities Only -- 10.6.2 Extracting Information with Conditional and Marginal Probabilities -- 11 Obtaining a Coherent Solution II: Bayesian Nets -- 11.1 Solution with Marginal and n-conditioned Probabilities -- 11.1.1 Generalizing the Results -- 11.2 An 'Automatic' Prescription to Build Joint Probabilities -- 11.3 What Can We Do with this Information? -- 11.3.1 Risk-Adjusting Returns -- IV Making It Work In Practice -- 12 Overcoming Our Cognitive Biases -- 12.1 Cognitive Shortcomings and Bounded Rationality -- 12.1.1 How Pervasive are Cognitive Shortcomings? -- 12.1.2 The Social Context -- 12.1.3 Adaptiveness -- 12.2 Representativeness -- 12.3 Quantification of the Representativeness Bias -- 12.4 Causal/Diagnostic and Positive/Negative Biases -- 12.5 Conclusions -- 12.6 Suggestions for Further Reading -- 13 Selecting and Combining Stress Scenarios -- 13.1 Bottom Up or Top Down? -- 13.2 Relative Strengths and ; Weaknesses of the Two Approaches -- 13.3 Possible Approaches to a Top-Down Analysis -- 13.4 Sanity Checks -- 13.5 How to Combine Stresses - Handling the Dimensionality Curse -- 13.6 Combining the Macro and Bottom-Up Approaches -- 14 Governance -- 14.1 The Institutional Aspects of Stress Testing -- 14.1.1 Transparency and Ease of Use -- 14.1.2 Challenge by Non-specialists -- 14.1.3 Checks for Completeness -- 14.1.4 Interactions among Different Specialists -- 14.1.5 Auditability of the Process and of the Results -- 14.2 Lines of Criticism.; 14.2.1 The Role of Subjective Inputs -- 14.2.2 The Complexity of the Stress-testing Process -- Appendix A Simple Introduction to Linear Programming -- A.1 Plan of the Appendix -- A.2 Linear Programming - A Refresher -- A.3 The Simplex Method -- References -- Index.