[推荐]Modeling Risk Applying Monte Carlo Simulation, Real Options Analysis, Foreca

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Introduction 1
PART ONE
Risk Identification
CHAPTER 1
Moving Beyond Uncertainty 11
A Brief History of Risk: What Exactly Is Risk? 11
Uncertainty versus Risk 12
Why Is Risk Important in Making Decisions? 14
Dealing with Risk the Old-Fashioned Way 16
The Look and Feel of Risk and Uncertainty 20
Integrated Risk Analysis Framework 22
Questions 27
PART TWO
Risk Evaluation
CHAPTER 2
From Risk to Riches 31
Taming the Beast 31
The Basics of Risk 32
The Nature of Risk and Return 33
The Statistics of Risk 34
The Measurements of Risk 39
Appendix—Computing Risk 41
Questions 48
CHAPTER 3
A Guide to Model-Building Etiquette 49
Document the Model 49
Separate Inputs, Calculations, and Results 53
Contents
Protect the Models 54
Make the Model User-Friendly: Data Validation and Alerts 55
Track the Model 57
Automate the Model with VBA 57
Model Aesthetics and Conditional Formatting 58
Appendix—A Primer on VBA Modeling and Writing Macros 59
Exercises 68
PART THREE
Risk Quantification
CHAPTER 4
On the Shores of Monaco 73
What Is Monte Carlo Simulation? 74
Why Are Simulations Important? 74
Comparing Simulation with Traditional Analyses 77
Using Risk Simulator and Excel to Perform Simulations 82
Questions 85
CHAPTER 5
Test Driving Risk Simulator 86
Getting Started with Risk Simulator 87
Running a Monte Carlo Simulation 88
Using Forecast Charts and Confidence Intervals 97
Correlations and Precision Control 100
Appendix—Understanding Probability Distributions 107
Questions 129
CHAPTER 6
Pandora’s Toolbox 142
Tornado and Sensitivity Tools in Simulation 142
Sensitivity Analysis 150
Distributional Fitting: Single Variable and Multiple Variables 154
Bootstrap Simulation 159
Hypothesis Testing 163
Data Extraction, Saving Simulation Results, and
Generating Reports 164
Custom Macros 167
Appendix—Goodness-of-Fit Tests 167
Questions 169
xii CONTENTS
PART FOUR
Industry Applications
CHAPTER 7
Extended Business Cases I:
Pharmaceutical and Biotech Negotiations, Oil and Gas Exploration,
Financial Planning with Simulation, Hospital Risk Management, and
Risk-Based Executive Compensation Valuation 187
Case Study: Pharmaceutical and Biotech Deal Structuring 188
Case Study: Oil and Gas Exploration and Production 207
Case Study: Financial Planning with Simulation 219
Case Study: Hospital Risk Management 229
Case Study: Risk-Based Executive Compensation Valuation 249
PART FIVE
Risk Prediction
CHAPTER 8
Tomorrow’s Forecast Today 261
Different Types of Forecasting Techniques 261
Running the Forecasting Tool in Risk Simulator 262
Time-Series Analysis 263
Multivariate Regression 267
Stochastic Forecasting 271
Nonlinear Extrapolation 276
Box–Jenkins ARIMA Advanced Time-Series 279
Questions 283
CHAPTER 9
Using the Past to Predict the Future 297
Time-Series Forecasting Methodology 297
No Trend and No Seasonality 298
With Trend but No Seasonality 304
No Trend but with Seasonality 308
With Seasonality and with Trend 312
Regression Analysis 314
The Pitfalls of Forecasting: Outliers, Nonlinearity,
Multicollinearity, Heteroskedasticity, Autocorrelation,
and Structural Breaks 329
Other Technical Issues in Regression Analysis 336
Appendix A—Forecast Intervals 338
Appendix B—Ordinary Least Squares 339
Contents xiii
Appendix C—Detecting and Fixing Heteroskedasticity 342
Appendix D—Detecting and Fixing Multicollinearity 343
Appendix E—Detecting and Fixing Autocorrelation 345
Questions 346
Exercise 346
PART SIX
Risk Diversification
CHAPTER 10
The Search for the Optimal Decision 349
What Is an Optimization Model? 349
The Traveling Financial Planner 350
The Lingo of Optimization 352
Solving Optimization Graphically and Using Excel’s Solver 355
Questions 361
CHAPTER 11
Optimization Under Uncertainty 362
Optimization Procedures 362
Continuous Optimization 365
Discrete Integer Optimization 371
Appendix—Computing Annualized Returns and Risk for
Portfolio Optimization 375
Question 378
Exercise 378
PART SEVEN
Risk Mitigation
CHAPTER 12
What Is So Real About Real Options, and Why Are They Optional? 381
What Are Real Options? 381
The Real Options Solution in a Nutshell 383
Issues to Consider 384
Implementing Real Options Analysis 385
Industry Leaders Embracing Real Options 386
What the Experts Are Saying 390
Criticisms, Caveats, and Misunderstandings in Real Options 392
Questions 394
xiv CONTENTS
CHAPTER 13
The Black Box Made Transparent: Real Options Super Lattice
Solver Software 395
Introduction to the Real Options Super Lattice
Solver Software 396
Single Asset Super Lattice Solver 398
Multiple Super Lattice Solver 405
Multinomial Lattice Solver 408
SLS Excel Solution 410
SLS Functions 413
Lattice Maker 415
PART EIGHT
More Industry Applications
CHAPTER 14
Extended Business Cases II:
Real Estate, Banking, Military Strategy, Automotive
Aftermarkets, Global Earth Observation Systems, and
Employee Stock Options 419
Case Study: Understanding Risk and Optimal Timing in a
Real Estate Development Using Real Options Analysis 420
Case Study: Using Stochastic Optimization and Valuation Models
to Evaluate the Credit Risk of Corporate Restructuring 435
Case Study: Real Options and KVA in Military Strategy at the
United States Navy 441
Case Study: Manufacturing and Sales in the
Automotive Aftermarket 452
Case Study: The Boeing Company’s Strategic Analysis of the
Global Earth Observation System of Systems 462
Case Study: Valuing Employee Stock Options Under the
2004 FAS 123R 472
PART NINE
Risk Management
CHAPTER 15
The Warning Signs 505
The Problem of Negligent Entrustment 505
Management’s Due Diligence 506
Contents xv
Sins of an Analyst 506
Reading the Warning Signs in Monte Carlo Simulation 508
Reading the Warning Signs in Time-Series
Forecasting and Regression 519
Reading the Warning Signs in Real Options Analysis 524
Reading the Warning Signs in Optimization Under Uncertainty 526
Questions 528
CHAPTER 16
Changing a Corporate Culture 529
How to Get Risk Analysis Accepted in an Organization 529
Change-Management Issues and Paradigm Shifts 529
Making Tomorrow’s Forecast Today 533
Notes 535
Tables You Really Need 545
Standard Normal Distribution (partial area) 546
Standard Normal Distribution (full area) 547
Student’s t-Distribution (one tail and two tails) 548
Durbin–Watson Critical Values (alpha 0.05) 549
Normal Random Numbers 550
Random Numbers (multiple digits) 552
Uniform Random Numbers 554
Chi-Square Critical Values 556
F-Distribution Critical Statistics 558
Real Options Analysis Values 566
Answers to End of Chapter Questions and Exercises 580
About the CD-ROM 588
Index 591
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