Introduction | p. 1 |
Scope | p. 1 |
Realism | p. 2 |
Models, Validation, and Precision | p. 3 |
Value | p. 4 |
Examples | |
Two Approaches to Solving Decision Trees--A Class-Action-Suit Example | p. 7 |
Introduction | p. 7 |
Building the Decision Tree | p. 9 |
What Is the Question? | p. 14 |
Interpretation of the Probabilistic-Branching Model | p. 19 |
So, So What? | p. 20 |
Terrorism Risk Models--Relative and Absolute Risk | p. 21 |
Terrorism Relative-Risk Model | p. 21 |
What Is the Question? | p. 22 |
Building the Contributing-Factor Diagram for the Relative-Ranking Terrorist-Threat Risk Model | p. 23 |
Category Weights | p. 27 |
Relative-Risk Model Equations | p. 28 |
Relative-Risk Model Applied to Terrorist Organization #1 | p. 29 |
Relative-Risk Model Results from Evaluation of Terrorist Organization #1 | p. 37 |
Relative-Risk Model Applied to Terrorist Organization #2 | p. 39 |
Relative-Risk Model Results from Evaluation of Terrorist Organization #2 | p. 48 |
Comparison of the Two Terrorist Organizations | p. 49 |
Building the Terrorism Absolute-Cost Risk Model | p. 53 |
Absolute-Cost Risk Model Equations | p. 55 |
Application of the Absolute-Cost Risk Model to Terrorist Organization #2 | p. 55 |
Absolute-Cost Risk Model Results for Evaluation of Terrorist Organization #2 | p. 61 |
So, So What? | p. 62 |
Gathering Information Consistently in an Inconsistent World | p. 67 |
Introduction | p. 67 |
The Problem | p. 70 |
The Solution | p. 72 |
So, So What? | p. 75 |
New Manufacturing Facility--Business-Justification Model | p. 79 |
Introduction | p. 79 |
What Is the Question? | p. 79 |
Construction of the Contributing-Factor Diagram | p. 82 |
Populating the Model with Data | p. 84 |
Risk Model Equations | p. 92 |
Results from Model Execution | p. 94 |
So, So What? | p. 95 |
Oil-Field-Development Investment--Opportunity Risk Model | p. 101 |
Introduction | p. 101 |
What Is the Question? | p. 102 |
Categories and Variables | p. 103 |
Field-Development Risk Model Equations | p. 104 |
Populating the Model with Data | p. 107 |
Results from Model Execution | p. 113 |
So, So What? | p. 117 |
Using Chance of Failure and Risk-Weighted Values to Reflect the Effect of "Soft" Issues on the Value of an Opportunity | p. 119 |
Introduction | p. 119 |
Accurate Estimates of Value Are Essential | p. 121 |
Types of Chance of Failure | p. 121 |
How to Express and Use Chance of Failure | p. 124 |
Risk-Weighted Values and the Value of a Portfolio Element | p. 128 |
Value of a Portfolio Composed of Dissimilar Elements | p. 131 |
So, So What? | p. 134 |
Production-Sharing Agreement Risk Model | p. 135 |
Introduction | p. 135 |
What Is the Question? | p. 135 |
Building the Contributing-Factor Diagrams | p. 137 |
Risk-Model Equations | p. 139 |
Populating the Model with Technical Data | p. 146 |
Chances of Abject Failure | p. 147 |
Populating the Model with Financial Data | p. 148 |
Results from the Model | p. 152 |
So, So What? | p. 158 |
Scheduling and Optimization Risk Model | p. 163 |
Introduction | p. 163 |
The Problem | p. 164 |
Design of the Model and the Contributing-Factor Diagram | p. 166 |
The Risk-Model Code | p. 169 |
Results from Model Execution | p. 171 |
So, So What? | p. 175 |
Decision/Option-Selection Risk Model | p. 179 |
Introduction | p. 179 |
The Current Situation | p. 180 |
The Problem | p. 182 |
Results from Model Execution | p. 185 |
So, So What? | p. 191 |
Risk Process to Identify Business Drivers, Maximize Value, and Determine the Value of Potential Expenditures | p. 193 |
Introduction | p. 193 |
The Problem | p. 194 |
The Risk/Uncertainty Model | p. 195 |
Populating the Model with Data | p. 196 |
Results from Model Execution | p. 199 |
Determining Business Drivers and Maximizing Value | p. 201 |
Determining the Value of Potential Expenditures | p. 206 |
So, So What? | p. 206 |
Summary | p. 209 |
Other Applications | p. 209 |
Insurance Example | p. 209 |
Pricing Example | p. 210 |
Environmental Applications | p. 211 |
Legal Applications | p. 211 |
Security Applications | p. 212 |
It Is Mostly the Process--Not the Technology | p. 213 |
Accomplishment of Vision Generates Real Returns | p. 215 |
Exploration Example | p. 215 |
Maintenance/Construction Example | p. 216 |
Fundamentals of Risk Assessment | |
Building a Consensus Model | p. 221 |
What Is the Question?--Most of the Time and Effort | p. 221 |
Consensus Model | p. 222 |
Group Dynamics | p. 223 |
Write It Down | p. 224 |
Sort It Out | p. 225 |
Group Dynamics Again | p. 226 |
Units | p. 227 |
Overarching Categories | p. 228 |
Build a Contributing-Factor Diagram | p. 229 |
The Contributing-Factor Diagram--Getting Started | p. 229 |
Identify and Define Variables | p. 233 |
Ask the Right Question | p. 234 |
Double Dipping | p. 235 |
Double Dipping and Counting the Chickens | p. 236 |
Fixing the Double Dipping and Counting-the-Chickens Problem | p. 236 |
CFD-Building Example | p. 237 |
Short List of Hints for Building a CFD | p. 241 |
Monte Carlo Analysis | p. 243 |
A Bit of History | p. 243 |
For What Is It Good? | p. 244 |
Simple Monte Carlo Example | p. 244 |
How Many Random Comparisons Are Enough? | p. 245 |
Output from Monte Carlo Analysis--The Frequency and Cumulative Frequency Plots | p. 246 |
Interpreting Cumulative Frequency Plots | p. 247 |
Combining Monte Carlo Output Curves | p. 253 |
Decisions and Distributions | p. 255 |
Decisions | p. 255 |
Just What Is a Distribution? | p. 255 |
Distributions--How to Approach Them | p. 260 |
Symmetrical Distributions | p. 261 |
Skewed Distributions | p. 262 |
Spiked Distributions | p. 263 |
Flat Distributions | p. 265 |
Truncated Distributions | p. 266 |
Discrete Distributions | p. 266 |
Bimodal Distributions | p. 268 |
Reading Data from a File | p. 270 |
Peakedness | p. 271 |
Specific Distribution Types | p. 273 |
Chance of Failure | p. 275 |
Chance of Failure--What Is It? | p. 275 |
Failure of a Risk Component | p. 276 |
Chance of Failure That Does Not Affect an Input Distribution | p. 277 |
Incorporating Chance of Failure in a Plot of Cumulative Frequency | p. 278 |
Another Reason for Chance of Failure | p. 280 |
The "Inserting 0s Work Around" | p. 282 |
COF and Multiple Output Variables | p. 284 |
Time-Series Analysis and Dependence | p. 285 |
Introduction to Time-Series Analysis and Dependence | p. 285 |
Time-Series Analysis--Why? | p. 285 |
Time-Series Analysis--How? | p. 286 |
Time-Series Analysis--Results | p. 287 |
Some Things To Consider | p. 288 |
Dependence--What Is It? | p. 290 |
Independent and Dependent Variables | p. 291 |
Degree of Dependence | p. 291 |
Multiple Dependencies and Circular Dependence | p. 294 |
Effect of Dependence on Monte Carlo Output | p. 295 |
Dependence--It's Ubiquitous | p. 295 |
Risk-Weighted Values and Sensitivity Analysis | p. 299 |
Introduction to Risk-Weighted Values and Sensitivity Analysis | p. 299 |
Risk-Weighted Values--Why? | p. 299 |
Risk-Weighted Values--How? | p. 301 |
The Net Risk-Weighted Value | p. 303 |
The Economic Risk-Weighted Resource Value | p. 304 |
Risk-Weighted Values--The Answer | p. 305 |
Sensitivity Analysis--Why? | p. 306 |
Sensitivity Analysis--How? | p. 308 |
Sensitivity Analysis--Results | p. 311 |
Selected Readings | p. 313 |
Index | p. 317 |
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