Preface | p. xi |
Acknowledgments | p. xv |
Part 1 An Introduction to the Crisis | p. 1 |
Chapter 1 Healthy Skepticism for Risk Management | p. 3 |
Common Mode Failure | p. 4 |
What Counts as Risk Management | p. 8 |
Anecdote: The Risk of Outsourcing Drug Manufacturing | p. 11 |
What Failure Means | p. 16 |
Scope and Objectives of This Book | p. 18 |
Chapter 2 Risk Management: A Very Short Introduction to Where We've Been and Where (We Think) We Are | p. 21 |
The Entire History of Risk Management (in 800 Words or Less) | p. 22 |
Methods of Assessing Risks | p. 24 |
Risk Mitigation | p. 26 |
The State of Risk Management According to Surveys | p. 31 |
Chapter 3 How Do We Know What Works? | p. 37 |
An Assessment of Self-Assessments | p. 37 |
Potential Objective Evaluations of Risk Management | p. 42 |
What We May Find | p. 49 |
Part 2 Why It's Broken | p. 53 |
Chapter 4 The "Four Horsemen" of Risk Management: Some (Mostly) Sincere Attempts to Prevent an Apocalypse | p. 55 |
Actuaries | p. 57 |
War Quants: How World War II Changed Risk Analysis Forever | p. 59 |
Economists | p. 63 |
Management Consulting: How a Power Tie and a Good Pitch Changed Risk Management | p. 68 |
Comparing the Horsemen | p. 74 |
Major Risk Management Problems to Be Addressed | p. 76 |
Chapter 5 An Ivory Tower of Babel: Fixing the Confusion about Risk | p. 79 |
The Frank Knight Definition | p. 81 |
Risk as Volatility | p. 84 |
A Construction Engineering Definition | p. 86 |
Risk as Expected Loss | p. 86 |
Risk as a Good Thing | p. 88 |
Risk Analysis and Risk Management versus Decision Analysis | p. 90 |
Enriching the Lexicon | p. 91 |
Chapter 6 The Limits of Expert Knowledge: Why We Don't Know What We Think We Know about Uncertainty | p. 95 |
The Right Stuff: How a Group of Psychologists Saved Risk Analysis | p. 97 |
Mental Math: Why We Shouldn't Trust the Numbers in Our Heads | p. 99 |
"Catastrophic" Overconfidence | p. 102 |
The Mind of "Aces": Possible Causes and Consequences of Overconfidence | p. 107 |
Inconsistencies and Artifacts: What Shouldn't Matter Does | p. 111 |
Answers to Calibration Tests | p. 115 |
Chapter 7 Worse Than Useless: The Most Popular Risk Assessment Method and Why It Doesn't Work | p. 117 |
A Basic Course in Scoring Methods (Actually, It's the Advanced Course, Too-There's Not Much to Know) | p. 118 |
Does That Come in "Medium"?: Why Ambiguity Does Not Offset Uncertainty | p. 123 |
Unintended Effects of Scales: What You Don't Know Can Hurt You | p. 130 |
Clarification of Scores and Preferences: Different but Similar-Sounding Methods and Similar but Different-Sounding Methods | p. 135 |
Chapter 8 Black Swans, Red Herrings, and Invisible Dragons: Overcoming Conceptual Obstacles to Improved Risk Management | p. 145 |
Risk and Righteous Indignation: The Belief that Quantitative Risk Analysis Is Impossible | p. 146 |
A Note about Black Swans | p. 151 |
Frequentist versus Subjectivist | p. 158 |
We're Special: The Belief that Risk Analysis Might Work, But Not Here | p. 161 |
Chapter 9 Where Even the Quants Go Wrong: Common and Fundamental Errors in Quantitative Models | p. 167 |
Introduction to Monte Carlo Concepts | p. 168 |
Survey of Monte Carlo Users | p. 172 |
The Risk Paradox | p. 174 |
The Measurement Inversion | p. 176 |
Where's the Science? The Lack of Empiricism in Risk Models | p. 178 |
Financial Models and the Shape of Disaster: Why Normal Isn't so Normal | p. 181 |
Following Your Inner Cow: The Problem with Correlations | p. 187 |
"That's Too Uncertain": How Modelers Justify Excluding the Biggest Risks | p. 191 |
Is Monte Carlo Too Complicated? | p. 195 |
Part 3 How to Fix It | p. 199 |
Chapter 10 The Language of Uncertain Systems: The First Step Toward Improved Risk Management | p. 201 |
Getting Your Probabilities Calibrated | p. 203 |
The Model of Uncertainty: Decomposing Risk with Monte Carlos | p. 208 |
Decomposing Probabilities: Thinking about Chance the Way You Think about a Budget | p. 212 |
A Few Modeling Principles | p. 213 |
Modeling the Mechanism | p. 215 |
Chapter 11 The Outward-Looking Modeler: Adding Empirical Science to Risk | p. 221 |
Why Your Model Won't Behave | p. 223 |
Empirical Inputs | p. 224 |
Introduction to Bayes: One Way to Get around that "Limited Data for Disasters" Problem | p. 227 |
Self-Examinations for Modelers Who Care about Quality | p. 233 |
Chapter 12 The Risk Community: Intra-and Extraorganizational Issues of Risk Management | p. 241 |
Getting Organized | p. 242 |
Managing the Global Probability Model | p. 244 |
Incentives for a Calibrated Culture | p. 250 |
Extraorganizational Issues: Solutions beyond Your Office Building | p. 254 |
Miscellaneous Topics | p. 256 |
Final Thoughts on Quantitative Models and Better Decisions | p. 258 |
Appendix Calibration Tests and Answers | p. 261 |
Index | p. 273 |