{"product_id":"bubble-value-at-risk-isbn-9781118550342","title":"Bubble Value at Risk","description":"\u003cb\u003eIntroduces a powerful new approach to financial risk modeling with proven strategies for its real-world applications\u003c\/b\u003e  \u003cp\u003eThe 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 author looks at what it cannot. In clear, accessible prose, finance practitioners, Max Wong, describes the VaR measure and what it was meant to do, then explores its various failures in the real world of crisis risk management. More importantly, he lays out a revolutionary new method of measuring risks, Bubble Value at Risk, that is countercyclical and offers a well-tested buffer against market crashes.\u003c\/p\u003e \u003cul\u003e \u003cli\u003eDescribes Bubble VaR, a more macro-prudential risk measure proven to avoid the limitations of VaR and by providing a more accurate risk exposure estimation over market cycles\u003c\/li\u003e \u003cli\u003eMakes a strong case that analysts and risk managers need to unlearn our existing \"science\" of risk measurement and discover more robust approaches to calculating risk capital\u003c\/li\u003e \u003cli\u003eIllustrates every key concept or formula with an abundance of practical, numerical examples, most of them provided in interactive Excel spreadsheets\u003c\/li\u003e \u003cli\u003eFeatures numerous real-world applications, throughout, based on the author’s firsthand experience as a veteran financial risk analyst\u003c\/li\u003e \u003c\/ul\u003e  \u003cp\u003eAbout the Author xiii\u003c\/p\u003e \u003cp\u003eForeword xv\u003c\/p\u003e \u003cp\u003ePreface xvii\u003c\/p\u003e \u003cp\u003eAcknowledgments xxi\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePART ONE Background\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003eCHAPTER 1 Introduction 3\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e1.1 The Evolution of Riskometer 4\u003c\/p\u003e \u003cp\u003e1.2 Taleb’s Extremistan 6\u003c\/p\u003e \u003cp\u003e1.3 The Turner Procyclicality 7\u003c\/p\u003e \u003cp\u003e1.4 The Common Sense of Bubble Value-at-Risk (BuVaR) 8\u003c\/p\u003e \u003cp\u003eNotes 13\u003c\/p\u003e \u003cp\u003e\u003cb\u003eCHAPTER 2 Essential Mathematics 15\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e2.1 Frequentist Statistics 15\u003c\/p\u003e \u003cp\u003e2.2 Just Assumptions 18\u003c\/p\u003e \u003cp\u003e2.3 Quantiles, VaR, and Tails 26\u003c\/p\u003e \u003cp\u003e2.4 Correlation and Autocorrelation 29\u003c\/p\u003e \u003cp\u003e2.5 Regression Models and Residual Errors 35\u003c\/p\u003e \u003cp\u003e2.6 Significance Tests 38\u003c\/p\u003e \u003cp\u003e2.7 Measuring Volatility 41\u003c\/p\u003e \u003cp\u003e2.8 Markowitz Portfolio Theory 45\u003c\/p\u003e \u003cp\u003e2.9 Maximum Likelihood Method 48\u003c\/p\u003e \u003cp\u003e2.10 Cointegration 50\u003c\/p\u003e \u003cp\u003e2.11 Monte Carlo Method 52\u003c\/p\u003e \u003cp\u003e2.12 The Classical Decomposition 55\u003c\/p\u003e \u003cp\u003e2.13 Quantile Regression Model 58\u003c\/p\u003e \u003cp\u003e2.14 Spreadsheet Exercises 62\u003c\/p\u003e \u003cp\u003eNotes 64\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePART TWO Value at Risk Methodology\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003eCHAPTER 3 Preprocessing 67\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e3.1 System Architecture 67\u003c\/p\u003e \u003cp\u003e3.2 Risk Factor Mapping 70\u003c\/p\u003e \u003cp\u003e3.3 Risk Factor Proxies 75\u003c\/p\u003e \u003cp\u003e3.4 Scenario Generation 76\u003c\/p\u003e \u003cp\u003e3.5 Basic VaR Specification 79\u003c\/p\u003e \u003cp\u003eNotes 81\u003c\/p\u003e \u003cp\u003e\u003cb\u003eCHAPTER 4 Conventional VaR Methods 83\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e4.1 Parametric VaR 84\u003c\/p\u003e \u003cp\u003e4.2 Monte Carlo VaR 89\u003c\/p\u003e \u003cp\u003e4.3 Historical Simulation VaR 93\u003c\/p\u003e \u003cp\u003e4.4 Issue: Convexity, Optionality, and Fat Tails 96\u003c\/p\u003e \u003cp\u003e4.5 Issue: Hidden Correlation 102\u003c\/p\u003e \u003cp\u003e4.6 Issue: Missing Basis and Beta Approach 104\u003c\/p\u003e \u003cp\u003e4.7 Issue: The Real Risk of Premiums 106\u003c\/p\u003e \u003cp\u003e4.8 Spreadsheet Exercises 107\u003c\/p\u003e \u003cp\u003eNotes 108\u003c\/p\u003e \u003cp\u003e\u003cb\u003eCHAPTER 5 Advanced VaR Methods 111\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e5.1 Hybrid Historical Simulation VaR 111\u003c\/p\u003e \u003cp\u003e5.2 Hull-White Volatility Updating VaR 113\u003c\/p\u003e \u003cp\u003e5.3 Conditional Autoregressive VaR (CAViaR) 114\u003c\/p\u003e \u003cp\u003e5.4 Extreme Value Theory VaR 116\u003c\/p\u003e \u003cp\u003e5.5 Spreadsheet Exercises 122\u003c\/p\u003e \u003cp\u003eNotes 124\u003c\/p\u003e \u003cp\u003e\u003cb\u003eCHAPTER 6 VaR Reporting 125\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e6.1 VaR Aggregation and Limits 125\u003c\/p\u003e \u003cp\u003e6.2 Diversification 126\u003c\/p\u003e \u003cp\u003e6.3 VaR Analytical Tools 127\u003c\/p\u003e \u003cp\u003e6.4 Scaling and Basel Rules 132\u003c\/p\u003e \u003cp\u003e6.5 Spreadsheet Exercises 136\u003c\/p\u003e \u003cp\u003eNotes 137\u003c\/p\u003e \u003cp\u003e\u003cb\u003eCHAPTER 7 The Physics of Risk and Pseudoscience 139\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e7.1 Entropy, Leverage Effect, and Skewness 140\u003c\/p\u003e \u003cp\u003e7.2 Volatility Clustering and the Folly of i.i.d. 144\u003c\/p\u003e \u003cp\u003e7.3 “Volatility of Volatility” and Fat Tails 145\u003c\/p\u003e \u003cp\u003e7.4 Extremistan and the Fourth Quadrant 148\u003c\/p\u003e \u003cp\u003e7.5 Regime Change, Lagging Riskometer, and Procyclicality 151\u003c\/p\u003e \u003cp\u003e7.6 Coherence and Expected Shortfall 154\u003c\/p\u003e \u003cp\u003e7.7 Spreadsheet Exercises 156\u003c\/p\u003e \u003cp\u003eNotes 156\u003c\/p\u003e \u003cp\u003e\u003cb\u003eCHAPTER 8 Model Testing 159\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e8.1 The Precision Test 159\u003c\/p\u003e \u003cp\u003e8.2 The Frequency Back Test 160\u003c\/p\u003e \u003cp\u003e8.3 The Bunching Test 163\u003c\/p\u003e \u003cp\u003e8.4 The Whole Distribution Test 165\u003c\/p\u003e \u003cp\u003e8.5 Spreadsheet Exercises 167\u003c\/p\u003e \u003cp\u003eNotes 167\u003c\/p\u003e \u003cp\u003e\u003cb\u003eCHAPTER 9 Practical Limitations of VaR 169\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e9.1 Depegs and Changes to the Rules of the Game 169\u003c\/p\u003e \u003cp\u003e9.2 Data Integrity Problems 171\u003c\/p\u003e \u003cp\u003e9.3 Model Risk 172\u003c\/p\u003e \u003cp\u003e9.4 Politics and Gaming 174\u003c\/p\u003e \u003cp\u003eNotes 175\u003c\/p\u003e \u003cp\u003e\u003cb\u003eCHAPTER 10 Other Major Risk Classes 177\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e10.1 Credit Risk (and CreditMetrics) 177\u003c\/p\u003e \u003cp\u003e10.2 Liquidity Risk 182\u003c\/p\u003e \u003cp\u003e10.3 Operational Risk 187\u003c\/p\u003e \u003cp\u003e10.4 The Problem of Aggregation 190\u003c\/p\u003e \u003cp\u003e10.5 Spreadsheet Exercises 195\u003c\/p\u003e \u003cp\u003eNotes 195\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePART THREE The Great Regulatory Reform\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003eCHAPTER 11 Regulatory Capital Reform 199\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e11.1 Basel I and Basel II 199\u003c\/p\u003e \u003cp\u003e11.2 The Turner Review 202\u003c\/p\u003e \u003cp\u003e11.3 Revisions to Basel II Market Risk Framework (Basel 2.5) 206\u003c\/p\u003e \u003cp\u003e11.4 New Liquidity Framework 211\u003c\/p\u003e \u003cp\u003e11.5 The New Basel III 212\u003c\/p\u003e \u003cp\u003e11.6 The New Framework for the Trading Book 214\u003c\/p\u003e \u003cp\u003e11.7 The Ideal Capital Regime 215\u003c\/p\u003e \u003cp\u003eNotes 217\u003c\/p\u003e \u003cp\u003e\u003cb\u003eCHAPTER 12 Systemic Risk Initiatives 221\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e12.1 Soros’ Reflexivity, Endogenous Risks 221\u003c\/p\u003e \u003cp\u003e12.2 CrashMetrics 226\u003c\/p\u003e \u003cp\u003e12.3 New York Fed CoVaR 230\u003c\/p\u003e \u003cp\u003e12.4 The Austrian Model and BOE RAMSI 233\u003c\/p\u003e \u003cp\u003e12.5 The Global Systemic Risk Regulator 238\u003c\/p\u003e \u003cp\u003e12.6 Spreadsheet Exercises 240\u003c\/p\u003e \u003cp\u003eNotes 241\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePART FOUR Introduction to Bubble Value-at-Risk (BuVaR)\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003eCHAPTER 13 Market BuVaR 245\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e13.1 Why an Alternative to VaR? 245\u003c\/p\u003e \u003cp\u003e13.2 Classical Decomposition, New Interpretation 247\u003c\/p\u003e \u003cp\u003e13.3 Measuring the Bubble 250\u003c\/p\u003e \u003cp\u003e13.4 Calibration 254\u003c\/p\u003e \u003cp\u003e13.5 Implementing the Inflator 257\u003c\/p\u003e \u003cp\u003e13.6 Choosing the Best Tail-Risk Measure 259\u003c\/p\u003e \u003cp\u003e13.7 Effect on Joint Distribution 262\u003c\/p\u003e \u003cp\u003e13.8 The Scope of BuVaR 264\u003c\/p\u003e \u003cp\u003e13.9 How Good Is the BuVaR Buffer? 265\u003c\/p\u003e \u003cp\u003e13.10 The Brave New World 268\u003c\/p\u003e \u003cp\u003e13.11 Spreadsheet Exercises 271\u003c\/p\u003e \u003cp\u003eNotes 271\u003c\/p\u003e \u003cp\u003e\u003cb\u003eCHAPTER 14 Credit BuVaR 273\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e14.1 The Credit Bubble VaR Idea 273\u003c\/p\u003e \u003cp\u003e14.2 Model Formulation 276\u003c\/p\u003e \u003cp\u003e14.3 Behavior of Response Function 278\u003c\/p\u003e \u003cp\u003e14.4 Characteristics of Credit BuVaR 280\u003c\/p\u003e \u003cp\u003e14.5 Interpretation of Credit BuVaR 282\u003c\/p\u003e \u003cp\u003e14.6 Spreadsheet Exercises 284\u003c\/p\u003e \u003cp\u003eNotes 284\u003c\/p\u003e \u003cp\u003e\u003cb\u003eCHAPTER 15 Acceptance Tests 285\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e15.1 BuVaR Visual Checks 285\u003c\/p\u003e \u003cp\u003e15.2 BuVaR Event Timing Tests 297\u003c\/p\u003e \u003cp\u003e15.3 BuVaR Cyclicality Tests 304\u003c\/p\u003e \u003cp\u003e15.4 Credit BuVaR Parameter Tuning 306\u003c\/p\u003e \u003cp\u003eNotes 313\u003c\/p\u003e \u003cp\u003e\u003cb\u003eCHAPTER 16 Other Topics 315\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e16.1 Diversification and Basis Risks 315\u003c\/p\u003e \u003cp\u003e16.2 Regulatory Reform and BuVaR 317\u003c\/p\u003e \u003cp\u003e16.3 BuVaR and the Banking Book: Response Time as Risk 319\u003c\/p\u003e \u003cp\u003e16.4 Can BuVaR Pick Tops and Bottoms Perfectly? 321\u003c\/p\u003e \u003cp\u003e16.5 Postmodern Risk Management 321\u003c\/p\u003e \u003cp\u003e16.6 Spreadsheet Exercises 323\u003c\/p\u003e \u003cp\u003eNote 323\u003c\/p\u003e \u003cp\u003e\u003cb\u003eCHAPTER 17 Epilogue: Suggestions for Future Research 325\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eNote 327\u003c\/p\u003e \u003cp\u003eAbout the Website 329\u003c\/p\u003e \u003cp\u003eBibliography 331\u003c\/p\u003e \u003cp\u003eIndex 337\u003c\/p\u003e  \u003cp\u003e\u003cb\u003eMax C.Y. Wong\u003c\/b\u003e 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.\u003c\/p\u003e  \u003cp\u003eMost risk management books introduce Value at Risk (VaR) by focusing on what it can do and its statistical measurements. The credit crisis in 2008 was a tidal wave that debunked this well-established risk metric. In this book, the author introduces VaR by looking at its failures instead and explores possible alternatives for effective crisis risk management, including a new method of measuring risks called Bubble Value at Risk that is countercyclical and can potentially buffer against market crashes.\u003c\/p\u003e \u003cp\u003eThe frequentist statistics-based VaR is predictive during normal circumstances but often fails patently during rare crisis episodes. In reality, crisis periods span only a tiny portion of financial market history. By relying on VaR for crisis risk management, we are using a tried-and-tested tool for the wrong occasion — mistaking the trees for the forest. The book argues that we need to unlearn our existing \"science\" of risk measurement and discover more robust ways of managing risk and calculating risk capital.\u003c\/p\u003e \u003cp\u003eThe book illustrates virtually every key concept or formula with a practical, numerical example, many of which are contained in interactive Excel spreadsheets.\u003c\/p\u003e  \u003cp\u003e\"Bubble Value at Risk offers a critical rethinking of some of the deficiencies in the calculation of risk capital. I particularly liked the more applied wisdom scattered throughout the text. Here is a practitioner explaining how things really work, or for that matter, don't work in the real world. These remarks will definitely open the eyes of the more academic researcher.\"\u003cbr\u003e \u003cb\u003e—Paul Embrechts, Director of RiskLab, ETH Zurich\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\"Reading Bubble Value at Risk is an intensive master class in risk management. As a busy risk management practitioner, I found Bubble Value at Risk extremely worthwhile in that Wong, with the theoretic detail of an academic but with the intuition of a practitioner, very efficiently surveys the evolution of financial risk management thought since the credit crisis. The book is well written, organized, thought-provoking, and to the point. After constructively critiquing pre-crisis risk management for its conceit that it could precisely model extreme events, Wong pragmatically breaks with risk dogma and introduces the concept of Bubble Value at Risk as a more prudent means of allocating sufficient capital to buffer tail risk in light of the fact that tail risk is inherently unknowable. The book is simply a very good use of time for anyone fighting the guerrilla war with risk.\"\u003cbr\u003e \u003cb\u003e—David P. Belmont, CFA and Chief Risk Officer, Commonfund\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\"John Maynard Keynes is famous for many things, including this quote on bankers: 'A sound banker, alas, is not one who foresees danger and avoids it, but one who, when he is ruined, is ruined in a conventional way along with his fellows, so that no one can really blame him.' This quote, originally found in The Consequences to the Banks of the Collapse of Money Values (1931), describes very accurately the robotic use of the Value at Risk concept at many financial institutions. Max Wong skewers the conventional wisdom on Value at Risk in this original book from a very talented and experienced market participant. Mr. Wong illustrates the mathematical problems with Value at Risk with many worked examples and insights from the 2007-2011 credit crisis. He suggests an alternative to the conventional wisdom, ' Bubble Value at Risk,' which addresses many of the shortcomings in conventional VaR calculations that were starkly revealed during the credit crisis. We highly recommend this candid and enlightening book to any risk analyst who finds himself surrounded by a large contingent of 'sound bankers.'\"\u003cbr\u003e \u003cb\u003e—Donald R. van Deventer, PhD, Chairman and Chief Executive Officer, Kamakura Corporation (www.kamakuraco.com), and coauthor of \u003ci\u003eAdvanced Financial Risk Management, 2nd Edition\u003c\/i\u003e\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\"Wong establishes his reputation as an inventive risk manager with the innovative idea to express expected shortfall (also called expected tail loss, or conditional VaR) in terms of previous price levels. This book also has some interesting ideas on financial regulatory reform and should be attractive to non-quant readers seeking knowledge of the pitfalls of Value at Risk, as it is usually measured.\"\u003cbr\u003e \u003cb\u003e— Professor Carol Alexander, Subject Lead, Finance and Accounting, School of Business, Management and Economics, University of Sussex\u003c\/b\u003e\u003c\/p\u003e","brand":"Wiley","offers":[{"title":"Default Title","offer_id":47988862419173,"sku":"NP9781118550342","price":114.0,"currency_code":"USD","in_stock":false}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/1842\/7735\/files\/9781118550342.jpg?v=1761781820","url":"https:\/\/k12savings.com\/es\/products\/bubble-value-at-risk-isbn-9781118550342","provider":"K12savings","version":"1.0","type":"link"}