Bubble value at risk : a countercyclical risk management approach /

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Introduces a powerful new approach to financial risk modeling with proven strategies for its real-world applications The 2008 credit crisis did much to debunk the much touted powers of Value at Risk (VaR) as a risk metric. Unlike most authors on VaR who focus on what it can do, in this book the auth...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor principal: Wong, Max C. Y. (Max Chan Yue)
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Singapore : Hoboken, N.J. : John Wiley & Sons Singapore Pte. Ltd. ; J. Wiley & Sons, ©2013.
Temas:
Risk management > Mathematical models.
Risk assessment > Mathematical models.
Financial risk management > Mathematical models.
Asset-liability management > Mathematical models.
Gestion du risque > Modèles mathématiques.
Évaluation du risque > Modèles mathématiques.
Finances > Gestion du risque > Modèles mathématiques.
Gestion des actifs et des passifs > Modèles mathématiques.
Acceso en línea:Texto completo (Requiere registro previo con correo institucional)
Tabla de Contenidos:
  • Bubble Value at Risk: A Countercyclical Risk Management Approach
  • Copyright
  • Contents
  • About the Author
  • Foreword
  • Preface
  • Audience
  • Overview of the Contents
  • Additional Materials
  • Acknowledgments
  • Part One: Background
  • Chapter 1: Introduction
  • 1.1: The Evolution of Riskometer
  • 1.2: Taleb's Extremistan
  • 1.3: The Turner Procyclicality
  • 1.4: The Common Sense of Bubble Value-at-Risk (BuVaR)
  • Notes
  • Chapter 2: Essential Mathematics
  • 2.1: Frequentist Statistics
  • 2.2: Just Assumptions
  • i.i.d. and Stationarity
  • Law of Large Numbers
  • The Quest for Invariance
  • PDF and CDF
  • Normal Distribution
  • Central Limit Theorem
  • 2.3: Quantiles, VaR, and Tails
  • 2.4: Correlation and Autocorrelation
  • Correlation
  • Autocorrelation
  • 2.5: Regression Models and Residual Errors
  • 2.6: Significance Tests
  • How to Compute t-Ratio for Regression
  • Hypothesis Testing
  • Stationarity Tests
  • 2.7: Measuring Volatility
  • 2.8: Markowitz Portfolio Theory
  • 2.9: Maximum Likelihood Method
  • 2.10: Cointegration
  • 2.11: Monte Carlo Method
  • 2.12: The Classical Decomposition
  • 2.13: Quantile Regression Model
  • 2.14: Spreadsheet Exercises
  • Notes
  • Part Two: Value at Risk Methodology
  • Chapter 3: Preprocessing
  • 3.1: System Architecture
  • 3.2: Risk Factor Mapping
  • Rationale for Risk Factor Mapping
  • Market Risks and Nonmarket Risks
  • Risk Dimensions
  • Risk Factor Universe
  • 3.3: Risk Factor Proxies
  • 3.4: Scenario Generation
  • Different Returns
  • Negative Rates
  • 3.5: Basic VaR Specification
  • The Case for Mean Adjustment
  • Notes
  • Chapter 4: Conventional VaR Methods
  • 4.1: Parametric VaR
  • Weakness of pVaR
  • 4.2: Monte Carlo VaR
  • Weakness of mcVaR
  • 4.3: Historical Simulation VaR
  • Weaknesses of hsVaR
  • 4.4: Issue: Convexity, Optionality, and Fat Tails
  • Convexity
  • Optionality
  • Fat Tails.
  • 4.5: Issue: Hidden Correlation
  • 4.6: Issue: Missing Basis and Beta Approach
  • Basis Risks
  • Beta Approach
  • 4.7: Issue: The Real Risk of Premiums
  • 4.8: Spreadsheet Exercises
  • Notes
  • Chapter 5: Advanced VaR Methods
  • 5.1: Hybrid Historical Simulation VaR
  • 5.2: Hull-White Volatility Updating VaR
  • 5.3: Conditional Autoregressive VaR (CAViaR)
  • 5.4: Extreme Value Theory VaR
  • Classical EVT
  • Peaks-over-Thresholds (POT) Method
  • 5.5: Spreadsheet Exercises
  • Notes
  • Chapter 6: VaR Reporting
  • 6.1: VaR Aggregation and Limits
  • 6.2: Diversification
  • 6.3: VaR Analytical Tools
  • The Tail Profile
  • Component VaR
  • Incremental VaR
  • 6.4: Scaling and Basel Rules
  • Basel Rules
  • Time Scaling
  • Quantile Scaling
  • 6.5: Spreadsheet Exercises
  • Notes
  • Chapter 7: The Physics of Risk and Pseudoscience
  • 7.1: Entropy, Leverage Effect, and Skewness
  • 7.2: Volatility Clustering and the Folly of i.i.d.
  • 7.3: "Volatility of Volatility" and Fat Tails
  • 7.4: Extremistan and the Fourth Quadrant
  • 7.5: Regime Change, Lagging Riskometer, and Procyclicality
  • The Lagging Nature of VaR
  • Hardwired Procyclicality
  • 7.6: Coherence and Expected Shortfall
  • 7.7: Spreadsheet Exercises
  • Notes
  • Chapter 8: Model Testing
  • 8.1: The Precision Test
  • 8.2: The Frequency Back Test
  • 8.3: The Bunching Test
  • 8.4: The Whole Distribution Test
  • 8.5: Spreadsheet Exercises
  • Notes
  • Chapter 9: Practical Limitations of VaR
  • 9.1: Depegs and Changes to the Rules of the Game
  • 9.2: Data Integrity Problems
  • 9.3: Model Risk
  • Pricing Model Risk
  • Strategies and Futuristic Information
  • 9.4: Politics and Gaming
  • Notes
  • Chapter 10: Other Major Risk Classes
  • 10.1: Credit Risk (and CreditMetrics)
  • Step 1: Defining Various States of the World
  • Step 2: Revaluation of Loan Portfolio
  • Step 3: Building Correlation
  • 10.2: Liquidity Risk.
  • What Exactly Is Liquidity Risk?
  • Liquidity-Adjusted VaR or L-VaR
  • A Possible Add-On Formula
  • Taking Probability into Account
  • 10.3: Operational Risk
  • 10.4: The Problem of Aggregation
  • The Danger of Adding Apples to Oranges
  • Adding across Different Forecast Horizons
  • 10.5: Spreadsheet Exercises
  • Notes
  • Part Three: The Great Regulatory Reform
  • Chapter 11: Regulatory Capital Reform
  • 11.1: Basel I and Basel II
  • 11.2: The Turner Review
  • Fundamental Theoretical Issues
  • Avoiding Procyclicality in Basel II
  • 11.3: Revisions to Basel II Market Risk Framework (Basel 2.5)
  • Incremental Risk Charge
  • Banking Book Treatment of Securitized Credit Products
  • Stressed VaR
  • Counterparty Credit Risk: CVA VaR
  • 11.4: New Liquidity Framework
  • 11.5: The New Basel III
  • 11.6: The New Framework for the Trading Book
  • 11.7: The Ideal Capital Regime
  • Notes
  • Chapter 12: Systemic Risk Initiatives
  • 12.1: Soros' Reflexivity, Endogenous Risks
  • 12.2: CrashMetrics
  • CrashMetrics for One Stock
  • Extension to Multiasset/Multibenchmark Model
  • Simple Illustration
  • 12.3: New York Fed CoVaR
  • Estimation of CoVaR
  • 12.4: The Austrian Model and BOE RAMSI
  • 12.5: The Global Systemic Risk Regulator
  • 12.6: Spreadsheet Exercises
  • Notes
  • Part Four: Introduction to Bubble Value-at-Risk (BuVaR)
  • Chapter 13: Market BuVaR
  • 13.1: Why an Alternative to VaR?
  • 13.2: Classical Decomposition, New Interpretation
  • 13.3: Measuring the Bubble
  • The Notion of Equilibrium
  • Adaptive Moving Average
  • Using Rank Filter
  • 13.4: Calibration
  • 13.5: Implementing the Inflator
  • 13.6: Choosing the Best Tail-Risk Measure
  • Coherence
  • Responsiveness
  • Stability
  • 13.7: Effect on Joint Distribution
  • 13.8: The Scope of BuVaR
  • Price-Based Risk Factors
  • Rates-Based Risk Factors
  • Credit Spread Risk Factors.
  • Volatility-Based Risk Factors
  • 13.9: How Good Is the BuVaR Buffer?
  • 13.10: The Brave New World
  • Hidden Conditions
  • Beyond i.i.d.
  • Living with Extremistan
  • 13.11: Spreadsheet Exercises
  • Notes
  • Chapter 14: Credit BuVaR
  • 14.1: The Credit Bubble VaR Idea
  • 14.2: Model Formulation
  • 14.3: Behavior of Response Function
  • 14.4: Characteristics of Credit BuVaR
  • 14.5: Interpretation of Credit BuVaR
  • 14.6: Spreadsheet Exercises
  • Notes
  • Chapter 15: Acceptance Tests
  • 15.1: BuVaR Visual Checks
  • 15.2: BuVaR Event Timing Tests
  • 15.3: BuVaR Cyclicality Tests
  • 15.4: Credit BuVaR Parameter Tuning
  • Notes
  • Chapter 16: Other Topics
  • 16.1: Diversification and Basis Risks
  • 16.2: Regulatory Reform and BuVaR
  • Cushioning Fat-Tail Losses
  • Overtly Countercyclical
  • Other Advantages
  • 16.3: BuVaR and the Banking Book: Response Time as Risk
  • 16.4: Can BuVaR Pick Tops and Bottoms Perfectly?
  • 16.5: Postmodern Risk Management
  • 16.6: Spreadsheet Exercises
  • Note
  • Chapter 17: Epilogue: Suggestions for Future Research
  • Note
  • About the Website
  • Bibliography
  • Index
  • Descriptions of the Spreadsheets for the Book
  • Website.

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