Bubble Value at Risk: A Countercyclical Risk Management Approach(Wiley Finance)

Table of Contents:
About the Author xiii Foreword xv Preface xvii Acknowledgments xxi PART ONE Background CHAPTER 1 Introduction 3 1.1 The Evolution of Riskometer 4 1.2 Taleb’s Extremistan 6 1.3 The Turner Procyclicality 7 1.4 The Common Sense of Bubble Value-at-Risk (BuVaR) 8 Notes 13 CHAPTER 2 Essential Mathematics 15 2.1 Frequentist Statistics 15 2.2 Just Assumptions 18 2.3 Quantiles, VaR, and Tails 26 2.4 Correlation and Autocorrelation 29 2.5 Regression Models and Residual Errors 35 2.6 Significance Tests 38 2.7 Measuring Volatility 41 2.8 Markowitz Portfolio Theory 45 2.9 Maximum Likelihood Method 48 2.10 Cointegration 50 2.11 Monte Carlo Method 52 2.12 The Classical Decomposition 55 2.13 Quantile Regression Model 58 2.14 Spreadsheet Exercises 62 Notes 64 PART TWO Value at Risk Methodology CHAPTER 3 Preprocessing 67 3.1 System Architecture 67 3.2 Risk Factor Mapping 70 3.3 Risk Factor Proxies 75 3.4 Scenario Generation 76 3.5 Basic VaR Specification 79 Notes 81 CHAPTER 4 Conventional VaR Methods 83 4.1 Parametric VaR 84 4.2 Monte Carlo VaR 89 4.3 Historical Simulation VaR 93 4.4 Issue: Convexity, Optionality, and Fat Tails 96 4.5 Issue: Hidden Correlation 102 4.6 Issue: Missing Basis and Beta Approach 104 4.7 Issue: The Real Risk of Premiums 106 4.8 Spreadsheet Exercises 107 Notes 108 CHAPTER 5 Advanced VaR Methods 111 5.1 Hybrid Historical Simulation VaR 111 5.2 Hull-White Volatility Updating VaR 113 5.3 Conditional Autoregressive VaR (CAViaR) 114 5.4 Extreme Value Theory VaR 116 5.5 Spreadsheet Exercises 122 Notes 124 CHAPTER 6 VaR Reporting 125 6.1 VaR Aggregation and Limits 125 6.2 Diversification 126 6.3 VaR Analytical Tools 127 6.4 Scaling and Basel Rules 132 6.5 Spreadsheet Exercises 136 Notes 137 CHAPTER 7 The Physics of Risk and Pseudoscience 139 7.1 Entropy, Leverage Effect, and Skewness 140 7.2 Volatility Clustering and the Folly of i.i.d. 144 7.3 “Volatility of Volatility” and Fat Tails 145 7.4 Extremistan and the Fourth Quadrant 148 7.5 Regime Change, Lagging Riskometer, and Procyclicality 151 7.6 Coherence and Expected Shortfall 154 7.7 Spreadsheet Exercises 156 Notes 156 CHAPTER 8 Model Testing 159 8.1 The Precision Test 159 8.2 The Frequency Back Test 160 8.3 The Bunching Test 163 8.4 The Whole Distribution Test 165 8.5 Spreadsheet Exercises 167 Notes 167 CHAPTER 9 Practical Limitations of VaR 169 9.1 Depegs and Changes to the Rules of the Game 169 9.2 Data Integrity Problems 171 9.3 Model Risk 172 9.4 Politics and Gaming 174 Notes 175 CHAPTER 10 Other Major Risk Classes 177 10.1 Credit Risk (and CreditMetrics) 177 10.2 Liquidity Risk 182 10.3 Operational Risk 187 10.4 The Problem of Aggregation 190 10.5 Spreadsheet Exercises 195 Notes 195 PART THREE The Great Regulatory Reform CHAPTER 11 Regulatory Capital Reform 199 11.1 Basel I and Basel II 199 11.2 The Turner Review 202 11.3 Revisions to Basel II Market Risk Framework (Basel 2.5) 206 11.4 New Liquidity Framework 211 11.5 The New Basel III 212 11.6 The New Framework for the Trading Book 214 11.7 The Ideal Capital Regime 215 Notes 217 CHAPTER 12 Systemic Risk Initiatives 221 12.1 Soros’ Reflexivity, Endogenous Risks 221 12.2 CrashMetrics 226 12.3 New York Fed CoVaR 230 12.4 The Austrian Model and BOE RAMSI 233 12.5 The Global Systemic Risk Regulator 238 12.6 Spreadsheet Exercises 240 Notes 241 PART FOUR Introduction to Bubble Value-at-Risk (BuVaR) CHAPTER 13 Market BuVaR 245 13.1 Why an Alternative to VaR? 245 13.2 Classical Decomposition, New Interpretation 247 13.3 Measuring the Bubble 250 13.4 Calibration 254 13.5 Implementing the Inflator 257 13.6 Choosing the Best Tail-Risk Measure 259 13.7 Effect on Joint Distribution 262 13.8 The Scope of BuVaR 264 13.9 How Good Is the BuVaR Buffer? 265 13.10 The Brave New World 268 13.11 Spreadsheet Exercises 271 Notes 271 CHAPTER 14 Credit BuVaR 273 14.1 The Credit Bubble VaR Idea 273 14.2 Model Formulation 276 14.3 Behavior of Response Function 278 14.4 Characteristics of Credit BuVaR 280 14.5 Interpretation of Credit BuVaR 282 14.6 Spreadsheet Exercises 284 Notes 284 CHAPTER 15 Acceptance Tests 285 15.1 BuVaR Visual Checks 285 15.2 BuVaR Event Timing Tests 297 15.3 BuVaR Cyclicality Tests 304 15.4 Credit BuVaR Parameter Tuning 306 Notes 313 CHAPTER 16 Other Topics 315 16.1 Diversification and Basis Risks 315 16.2 Regulatory Reform and BuVaR 317 16.3 BuVaR and the Banking Book: Response Time as Risk 319 16.4 Can BuVaR Pick Tops and Bottoms Perfectly? 321 16.5 Postmodern Risk Management 321 16.6 Spreadsheet Exercises 323 Note 323 CHAPTER 17 Epilogue: Suggestions for Future Research 325 Note 327 About the Website 329 Bibliography 331 Index 337

About the Author :
Max C.Y. Wong is a specialist in the area of risk modeling and Basel III. He started his career as a derivatives consultant at Credit Suisse First Boston in 1996. During the Asian crisis in 1998 he traded index futures at the open-outcry floor of SIMEX (now SGX). From 2003 to 2011, he worked for Standard Chartered Bank as a risk manager and senior quant. He is currently head of VaR model testing at the Royal Bank of Scotland. He has published papers on VaR models and Basel capital, recently looking at innovative ways to model risk more effectively during crises and to deal with the issues of procyclicality and Black Swan event in our financial system. He has spoken on the subject at various conferences and seminars. He holds a B.Sc. Physics from University of Malaya (1994) and a M.Sc. financial engineering from National University of Singapore (2004). He is an adjunct at Singapore Management University, a member of the editorial board of the Journal of Risk Management in Financial Institutions, and a member of the steering committee of PRMIA Singapore chapter.