Bubble value at risk : a countercyclical risk management approach /

• Κύριος συγγραφέας: Wong, Max C. Y. (Max Chan Yue) (Συγγραφέας)
• Μορφή: Ηλ. βιβλίο
• Γλώσσα: English
• Έκδοση: Singapore : John Wiley & Sons Singapore Pte. Ltd., [2013]
• Έκδοση: Revised edition.
• Σειρά: Wiley finance series.
• Θέματα: Risk management > Mathematical models.; Risk assessment > Mathematical models.; Financial risk management > Mathematical models.; Asset-liability management > Mathematical models.; BUSINESS & ECONOMICS > Insurance > Risk Assessment & Management.; Financial risk management.; Electronic books.

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...

Πίνακας περιεχομένων:

• 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 Theorem2.3: 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 MappingRationale 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 ApproachBasis 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 RulesBasel 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.