简介
"An updated guide to risk analysis and modeling. Although risk was once seen as something that was both unpredictable and uncontrollable, the evolution of risk analysis tools and theories has changed the way we look at this important business element. In the Second Edition of Analyzing and Modeling Risk, expert Dr. Johnathan Mun provides up-to-date coverage of risk analysis as it is applied within the realms of business risk analysis and offers an intuitive feel of what risk looks like, as well as the different ways of quantifying it. This Second Edition provides professionals in all industries a more comprehensive guide on such key concepts as risk and return, the fundamentals of model building, Monte Carlo simulation, forecasting, time-series and regression analysis, optimization, real options, and more. Includes new examples, questions, and exercises as well as updates using Excel 2007. Book supported by author's proprietary risk analysis software found on the companion CD-ROM. Offers both a qualitative and quantitative description of risk. Filled with in-depth insights and practical advice, this reliable resource covers all of the essential tools and techniques that risk managers need to successfully conduct risk analysis. Note: CD-ROM/DVD and other supplementary materials are not included as part of eBook file"--
目录
Table Of Contents:
Preface xv
What's New in the Second Edition xvii
Acknowledgments xix
About the Author xxi
Introduction 1(10)
Part One Risk Identification
Chapter 1 Moving Beyond Uncertainty 11(22)
A Brief History Of Risk: What Exactly Is Risk? 11(1)
Uncertainty Versus Risk 12(2)
Why Is Risk Important In Making Decisions? 14(4)
Dealing With Risk The Old-Fashioned Way 18(3)
The Look And Feel Of Risk And Uncertainty 21(2)
Integrated Risk Management Framework 23(6)
Questions 29(4)
Part Two Risk Evaluation
Chapter 2 From Risk To Riches 33(23)
Taming The Beast 33(2)
The Basics Of Risk 35(1)
The Nature Of Risk And Return 36(1)
The Statistics Of Risk 36(6)
The Measurements Of Risk 42(2)
Appendix鈥攃omputing Risk 44(10)
Questions 54(2)
Chapter 3 A Guide To Model-Building Etiquette 56(25)
Document The Model 56(3)
Separate Inputs, Calculations, And Results 59(2)
Protect The Models 61(1)
Make The Model User-Friendly: Data Validation And Alerts 62(2)
Track The Model 64(1)
Automate The Model With VBA 65(1)
Model Aesthetics And Conditional Formatting 66(1)
Appendix鈥擜 Primer On VBA Modeling And Writing Macros 67(9)
Exercises 76(5)
Part Three Risk Quantification
Chapter 4 On The Shores Of Monaco 81(14)
What Is Monte Carlo Simulation? 82(1)
Why Are Simulations Important? 82(3)
Comparing Simulation With Traditional Analyses 85(3)
Using Risk Simulator And Excel To Perform Simulations 88(6)
Questions 94(1)
Chapter 5 Test Driving Risk Simulator 95(83)
Getting Started With Risk Simulator 95(2)
Running A Monte Carlo Simulation 97(11)
Using Forecast Charts And Confidence Intervals 108(4)
Correlations And Precision Control 112(6)
Appendix鈥攗nderstanding Probability Distributions 118(24)
Appendix鈥擱OV Compiler: Protects And Converts Excel Files Into Executable EXE 142(4)
Appendix鈥擱OV Extractor And Evaluator: Runs Extreme Super Speed Simulations And Converts Excel Models Into A Calculator Environment 146(3)
Questions 149(1)
Exercises 149(29)
Chapter 6 Pandora's Toolbox 178(107)
Tornado And Sensitivity Tools In Simulation 178(9)
Sensitivity Analysis 187(5)
Distributional Fitting: Single Variable And Multiple Variables 192(4)
Bootstrap Simulation 196(3)
Hypothesis Testing 199(4)
Data Extraction, Saving Simulation Results, And Generating Reports 203(1)
Custom Macros 204(1)
Distributional Analysis Tool 204(5)
Scenario Analysis Tool 209(1)
Segmentation Clustering Tool 209(1)
Structural Break Analysis 210(2)
Detrending And Deseasonalizing 212(1)
Principal Component Analysis 212(1)
Appendix鈥攇oodness-Of-Fit Tests 213(2)
Questions 215(1)
Exercises 216(69)
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, Risk-Based Executive Compensation Valuation, And Risk-Based Schedule Planning 285(86)
Case Study: Pharmaceutical And Biotech Deal Structuring 286(20)
Case Study: Oil And Gas Exploration And Production 306(12)
Case Study: Financial Planning With Simulation 318(10)
Case Study: Hospital Risk Management 328(20)
Case Study: Risk-Based Executive Compensation Valuation 348(9)
Case Study: Risk-Based Schedule Planning With Simulation 357(14)
Part Five Risk Prediction
Chapter 8 Tomorrow's Forecast Today 371(55)
Different Types Of Forecasting Techniques 371(4)
Running The Forecasting Tool In Risk Simulator 375(1)
Time-Series Analysis 376(4)
Multivariate Regression 380(3)
Stepwise Regression 383(3)
Stochastic Forecasting 386(4)
Nonlinear Extrapolation 390(2)
Box鈥揓enkins ARIMA Advanced Time-Series 392(5)
Auto Arima (Box鈥揓enkins ARIMA Advanced Time-Series) 397(2)
Basic Econometrics 399(2)
J-Curve And S-Curve Forecasts 401(2)
GARCH Volatility Forecasts 403(3)
Markov Chains 406(2)
Maximum Likelihood Models On Logit, Probit, And Tobit 408(3)
Spline (Cubic Spline Interpolation And Extrapolation) 411(1)
Questions 411(2)
Exercise: Forecasting 413(13)
Chapter 9 Using The Past To Predict The Future 426(75)
Time-Series Forecasting Methodology 426(1)
No Trend And No Seasonality 427(6)
With Trend But No Seasonality 433(2)
No Trend But With Seasonality 435(4)
With Seasonality And With Trend 439(2)
Regression Analysis 441(16)
The Pitfalls Of Forecasting: Outliers, Nonlinearity, Multicollinearity, Heteroskedasticity, Autocorrelation, And Structural Breaks 457(14)
Other Technical Issues In Regression Analysis 471(2)
Regression And Forecasting Diagnostic Tool 473(10)
Statistical Analysis Tool 483(6)
Appendix鈥攆orecast Intervals 489(1)
Appendix鈥攐rdinary Least Squares 490(3)
Appendix鈥攄etecting And Fixing Heteroskedasticity 493(1)
Appendix鈥攄etecting And Fixing Multicollinearity 494(2)
Appendix鈥攄etecting And Fixing Autocorrelation 496(1)
Questions 497(1)
Exercise 497(4)
Part Six Risk Diversification
Chapter 10 The Search For The Optimal Decision 501(13)
What Is An Optimization Model? 501(1)
The Traveling Financial Planner 502(2)
The Lingo Of Optimization 504(3)
Solving Optimization Graphically And Using Excel's Solver 507(6)
Questions 513(1)
Chapter 11 Optimization Under Uncertainty 514(69)
Optimization Procedures 514(3)
Continuous Optimization 517(6)
Discrete Integer Optimization 523(3)
Efficient Frontier And Advanced Optimization Settings 526(4)
Stochastic Optimization 530 (5)
Optimization Application Example: Military Portfolio And Efficient Frontier 535 (4)
Optimization Application Example: Optimal Pricing With Elasticity 539 (5)
Appendix鈥擱OV Modeler Suite: Server-Based Applications For Running Data-Intensive Models At Extremely High Speeds 544 (18)
Appendix鈥攃omputing Annualized Returns And Risk For Portfolio Optimization 562(4)
Exercise: Optimization 566(13)
Questions 579(4)
Part Seven Risk Mitigation
Chapter 12 What Is So Real About Real Options, And Why Are They Optional? 583(30)
What Are Real Options? 583(2)
The Real Options Solution In A Nutshell 585(1)
Issues To Consider 586(1)
Implementing Real Options Analysis 587(1)
Types Of Real Options Strategies 588(2)
Industry Leaders Embracing Real Options 590(3)
More Sample Applications And Short Cases 593(13)
What The Experts Are Saying 606(3)
Criticisms, Caveats, And Misunderstandings In Real Options 609(3)
Questions 612(1)
Chapter 13 The Black Box Made Transparent: Real Options Super Lattice Solver Software 613(62)
Single Asset Super Lattice Solver 615(9)
Multiple Asset Super Lattice Solver 624(2)
Multinomial Super Lattice Solver 626(2)
SLS Lattice Maker 628 (1)
SLS Excel Solution (SLS, MSLS, And Changing Volatility Models In Excel) 628(3)
SLS Functions 631(4)
Exotic Financial Options Valuator 635 (1)
Payoff Charts, Tornado Sensitivity, Scenario, And Convergence Analysis 635(6)
Key SLS Notes And Tips 641(3)
Exercises 644(31)
Part Eight More Industry Applications
Chapter 14 Extended Business Cases II: Real Estate, Banking, Military Strategy, Automotive Aftermarkets, Global Earth Observation Systems, Employee Stock Options, Oil And Gas Royalty Lease Negotiations, Real Options And IT Enterprise Risk Security, Basel II Credit And Market Risk Analysis, and IT Information Security Intrusion Risk Management 675 (210)
Case Study: Understanding Risk And Optimal Timing In A Real Estate Development Using Real Options Analysis 676(16)
Case Study: Using Stochastic Optimization And Valuation Models To Evaluate The Credit Risk Of Corporate Restructuring 692(6)
Case Study: Real Options And KVA In Military Strategy At The United States Navy 698 (11)
Case Study: Manufacturing And Sales In The Automotive Aftermarket 709(10)
Case Study: The Boeing Company's Strategic Analysis Of The Global Earth Observation System Of Systems 719(10)
Case Study: Valuing Employee Stock Options Under The 2004 FAS 123R 729(31)
Case Study: Oil And Gas Royalty Lease Negotiation 760(20)
Case Study: How Real Options Mitigates It Enterprise Security Risks 780(15)
Case Study: Basel II Credit Risk And Market Risk 795(46)
Case Study: IT Information Security Intrusion Risk Management 841(44)
Part Nine Risk Management
Chapter 15 The Warning Signs 885(4)
The Problem Of Negligent Entrustment 865(1)
Management's Due Diligence 866(1)
Sins Of An Analyst 866(2)
Reading The Warning Signs In Monte Carlo Simulation 868(11)
Reading The Warning Signs In Time-Series Forecasting And Regression 879(5)
Reading The Warning Signs In Real Options Analysis 884(3)
Reading The Warning Signs In Optimization Under Uncertainty 887(1)
Questions 888(1)
Chapter 16 Changing A Corporate Culture 889(26)
How To Get Risk Analysis Accepted In An Organization 889(1)
Change-Management Issues And Paradigm Shifts 889(4)
Making Tomorrow's Forecast Today 893(1)
Parting Shots And A Word Of Caution From The Author 894(11)
Notes 905(10)
Tables You Really Need 915(36)
Standard Normal Distribution (Partial Area) 916(1)
Standard Normal Distribution (Full Area) 917(1)
Student's T-Distribution (One And Two Tails) 918(1)
Durbin鈥擶atson Critical Values (Alpha 0.05) 919(1)
Normal Random Numbers (Standard Normal Distribution's Random Number Generated 藴 (N(0, 1)) 920(2)
Random Numbers (Multiple Digits) 922(2)
Uniform Random Numbers (Uniform Distribution's Random Number Generated Between 0.0000 And 1.0000) 924(2)
Chi-Square Critical Values 926(2)
F-Distribution Critical Statistics (Alpha One Tail 0.10) 928(2)
F-Distribution Critical Statistics (Alpha One Tail 0.05) 930(2)
F-Distribution Critical Statistics (Alpha One Tail 0.025) 932(2)
F-Distribution Critical Statistics (Alpha One Tail 0.01) 934(2)
Real Options Analysis Values (1-Year Maturity At 5% Risk-Free Rate) 936(2)
Real Options Analysis Values (3-Year Maturity At 5% Risk-Free Rate) 938(2)
Real Options Analysis Values (5-Year Maturity At 5% Risk-Free Rate) 940(2)
Real Options Analysis Values (7-Year Maturity At 5% Risk-Free Rate) 942(2)
Real Options Analysis Values (10-Year Maturity At 5% Risk-Free Rate) 944(2)
Real Options Analysis Values (15-Year Maturity At 5% Risk-Free Rate) 946(2)
Real Options Analysis Values (30-Year Maturity At 5% Risk-Free Rate) 948(3)
Answers To End Of Chapter Questions 951(8)
About The DVD-ROM 959(4)
System Requirements 959(1)
What's On The DVD 959(1)
Customer Care 960(3)
Index 963
Preface xv
What's New in the Second Edition xvii
Acknowledgments xix
About the Author xxi
Introduction 1(10)
Part One Risk Identification
Chapter 1 Moving Beyond Uncertainty 11(22)
A Brief History Of Risk: What Exactly Is Risk? 11(1)
Uncertainty Versus Risk 12(2)
Why Is Risk Important In Making Decisions? 14(4)
Dealing With Risk The Old-Fashioned Way 18(3)
The Look And Feel Of Risk And Uncertainty 21(2)
Integrated Risk Management Framework 23(6)
Questions 29(4)
Part Two Risk Evaluation
Chapter 2 From Risk To Riches 33(23)
Taming The Beast 33(2)
The Basics Of Risk 35(1)
The Nature Of Risk And Return 36(1)
The Statistics Of Risk 36(6)
The Measurements Of Risk 42(2)
Appendix鈥攃omputing Risk 44(10)
Questions 54(2)
Chapter 3 A Guide To Model-Building Etiquette 56(25)
Document The Model 56(3)
Separate Inputs, Calculations, And Results 59(2)
Protect The Models 61(1)
Make The Model User-Friendly: Data Validation And Alerts 62(2)
Track The Model 64(1)
Automate The Model With VBA 65(1)
Model Aesthetics And Conditional Formatting 66(1)
Appendix鈥擜 Primer On VBA Modeling And Writing Macros 67(9)
Exercises 76(5)
Part Three Risk Quantification
Chapter 4 On The Shores Of Monaco 81(14)
What Is Monte Carlo Simulation? 82(1)
Why Are Simulations Important? 82(3)
Comparing Simulation With Traditional Analyses 85(3)
Using Risk Simulator And Excel To Perform Simulations 88(6)
Questions 94(1)
Chapter 5 Test Driving Risk Simulator 95(83)
Getting Started With Risk Simulator 95(2)
Running A Monte Carlo Simulation 97(11)
Using Forecast Charts And Confidence Intervals 108(4)
Correlations And Precision Control 112(6)
Appendix鈥攗nderstanding Probability Distributions 118(24)
Appendix鈥擱OV Compiler: Protects And Converts Excel Files Into Executable EXE 142(4)
Appendix鈥擱OV Extractor And Evaluator: Runs Extreme Super Speed Simulations And Converts Excel Models Into A Calculator Environment 146(3)
Questions 149(1)
Exercises 149(29)
Chapter 6 Pandora's Toolbox 178(107)
Tornado And Sensitivity Tools In Simulation 178(9)
Sensitivity Analysis 187(5)
Distributional Fitting: Single Variable And Multiple Variables 192(4)
Bootstrap Simulation 196(3)
Hypothesis Testing 199(4)
Data Extraction, Saving Simulation Results, And Generating Reports 203(1)
Custom Macros 204(1)
Distributional Analysis Tool 204(5)
Scenario Analysis Tool 209(1)
Segmentation Clustering Tool 209(1)
Structural Break Analysis 210(2)
Detrending And Deseasonalizing 212(1)
Principal Component Analysis 212(1)
Appendix鈥攇oodness-Of-Fit Tests 213(2)
Questions 215(1)
Exercises 216(69)
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, Risk-Based Executive Compensation Valuation, And Risk-Based Schedule Planning 285(86)
Case Study: Pharmaceutical And Biotech Deal Structuring 286(20)
Case Study: Oil And Gas Exploration And Production 306(12)
Case Study: Financial Planning With Simulation 318(10)
Case Study: Hospital Risk Management 328(20)
Case Study: Risk-Based Executive Compensation Valuation 348(9)
Case Study: Risk-Based Schedule Planning With Simulation 357(14)
Part Five Risk Prediction
Chapter 8 Tomorrow's Forecast Today 371(55)
Different Types Of Forecasting Techniques 371(4)
Running The Forecasting Tool In Risk Simulator 375(1)
Time-Series Analysis 376(4)
Multivariate Regression 380(3)
Stepwise Regression 383(3)
Stochastic Forecasting 386(4)
Nonlinear Extrapolation 390(2)
Box鈥揓enkins ARIMA Advanced Time-Series 392(5)
Auto Arima (Box鈥揓enkins ARIMA Advanced Time-Series) 397(2)
Basic Econometrics 399(2)
J-Curve And S-Curve Forecasts 401(2)
GARCH Volatility Forecasts 403(3)
Markov Chains 406(2)
Maximum Likelihood Models On Logit, Probit, And Tobit 408(3)
Spline (Cubic Spline Interpolation And Extrapolation) 411(1)
Questions 411(2)
Exercise: Forecasting 413(13)
Chapter 9 Using The Past To Predict The Future 426(75)
Time-Series Forecasting Methodology 426(1)
No Trend And No Seasonality 427(6)
With Trend But No Seasonality 433(2)
No Trend But With Seasonality 435(4)
With Seasonality And With Trend 439(2)
Regression Analysis 441(16)
The Pitfalls Of Forecasting: Outliers, Nonlinearity, Multicollinearity, Heteroskedasticity, Autocorrelation, And Structural Breaks 457(14)
Other Technical Issues In Regression Analysis 471(2)
Regression And Forecasting Diagnostic Tool 473(10)
Statistical Analysis Tool 483(6)
Appendix鈥攆orecast Intervals 489(1)
Appendix鈥攐rdinary Least Squares 490(3)
Appendix鈥攄etecting And Fixing Heteroskedasticity 493(1)
Appendix鈥攄etecting And Fixing Multicollinearity 494(2)
Appendix鈥攄etecting And Fixing Autocorrelation 496(1)
Questions 497(1)
Exercise 497(4)
Part Six Risk Diversification
Chapter 10 The Search For The Optimal Decision 501(13)
What Is An Optimization Model? 501(1)
The Traveling Financial Planner 502(2)
The Lingo Of Optimization 504(3)
Solving Optimization Graphically And Using Excel's Solver 507(6)
Questions 513(1)
Chapter 11 Optimization Under Uncertainty 514(69)
Optimization Procedures 514(3)
Continuous Optimization 517(6)
Discrete Integer Optimization 523(3)
Efficient Frontier And Advanced Optimization Settings 526(4)
Stochastic Optimization 530 (5)
Optimization Application Example: Military Portfolio And Efficient Frontier 535 (4)
Optimization Application Example: Optimal Pricing With Elasticity 539 (5)
Appendix鈥擱OV Modeler Suite: Server-Based Applications For Running Data-Intensive Models At Extremely High Speeds 544 (18)
Appendix鈥攃omputing Annualized Returns And Risk For Portfolio Optimization 562(4)
Exercise: Optimization 566(13)
Questions 579(4)
Part Seven Risk Mitigation
Chapter 12 What Is So Real About Real Options, And Why Are They Optional? 583(30)
What Are Real Options? 583(2)
The Real Options Solution In A Nutshell 585(1)
Issues To Consider 586(1)
Implementing Real Options Analysis 587(1)
Types Of Real Options Strategies 588(2)
Industry Leaders Embracing Real Options 590(3)
More Sample Applications And Short Cases 593(13)
What The Experts Are Saying 606(3)
Criticisms, Caveats, And Misunderstandings In Real Options 609(3)
Questions 612(1)
Chapter 13 The Black Box Made Transparent: Real Options Super Lattice Solver Software 613(62)
Single Asset Super Lattice Solver 615(9)
Multiple Asset Super Lattice Solver 624(2)
Multinomial Super Lattice Solver 626(2)
SLS Lattice Maker 628 (1)
SLS Excel Solution (SLS, MSLS, And Changing Volatility Models In Excel) 628(3)
SLS Functions 631(4)
Exotic Financial Options Valuator 635 (1)
Payoff Charts, Tornado Sensitivity, Scenario, And Convergence Analysis 635(6)
Key SLS Notes And Tips 641(3)
Exercises 644(31)
Part Eight More Industry Applications
Chapter 14 Extended Business Cases II: Real Estate, Banking, Military Strategy, Automotive Aftermarkets, Global Earth Observation Systems, Employee Stock Options, Oil And Gas Royalty Lease Negotiations, Real Options And IT Enterprise Risk Security, Basel II Credit And Market Risk Analysis, and IT Information Security Intrusion Risk Management 675 (210)
Case Study: Understanding Risk And Optimal Timing In A Real Estate Development Using Real Options Analysis 676(16)
Case Study: Using Stochastic Optimization And Valuation Models To Evaluate The Credit Risk Of Corporate Restructuring 692(6)
Case Study: Real Options And KVA In Military Strategy At The United States Navy 698 (11)
Case Study: Manufacturing And Sales In The Automotive Aftermarket 709(10)
Case Study: The Boeing Company's Strategic Analysis Of The Global Earth Observation System Of Systems 719(10)
Case Study: Valuing Employee Stock Options Under The 2004 FAS 123R 729(31)
Case Study: Oil And Gas Royalty Lease Negotiation 760(20)
Case Study: How Real Options Mitigates It Enterprise Security Risks 780(15)
Case Study: Basel II Credit Risk And Market Risk 795(46)
Case Study: IT Information Security Intrusion Risk Management 841(44)
Part Nine Risk Management
Chapter 15 The Warning Signs 885(4)
The Problem Of Negligent Entrustment 865(1)
Management's Due Diligence 866(1)
Sins Of An Analyst 866(2)
Reading The Warning Signs In Monte Carlo Simulation 868(11)
Reading The Warning Signs In Time-Series Forecasting And Regression 879(5)
Reading The Warning Signs In Real Options Analysis 884(3)
Reading The Warning Signs In Optimization Under Uncertainty 887(1)
Questions 888(1)
Chapter 16 Changing A Corporate Culture 889(26)
How To Get Risk Analysis Accepted In An Organization 889(1)
Change-Management Issues And Paradigm Shifts 889(4)
Making Tomorrow's Forecast Today 893(1)
Parting Shots And A Word Of Caution From The Author 894(11)
Notes 905(10)
Tables You Really Need 915(36)
Standard Normal Distribution (Partial Area) 916(1)
Standard Normal Distribution (Full Area) 917(1)
Student's T-Distribution (One And Two Tails) 918(1)
Durbin鈥擶atson Critical Values (Alpha 0.05) 919(1)
Normal Random Numbers (Standard Normal Distribution's Random Number Generated 藴 (N(0, 1)) 920(2)
Random Numbers (Multiple Digits) 922(2)
Uniform Random Numbers (Uniform Distribution's Random Number Generated Between 0.0000 And 1.0000) 924(2)
Chi-Square Critical Values 926(2)
F-Distribution Critical Statistics (Alpha One Tail 0.10) 928(2)
F-Distribution Critical Statistics (Alpha One Tail 0.05) 930(2)
F-Distribution Critical Statistics (Alpha One Tail 0.025) 932(2)
F-Distribution Critical Statistics (Alpha One Tail 0.01) 934(2)
Real Options Analysis Values (1-Year Maturity At 5% Risk-Free Rate) 936(2)
Real Options Analysis Values (3-Year Maturity At 5% Risk-Free Rate) 938(2)
Real Options Analysis Values (5-Year Maturity At 5% Risk-Free Rate) 940(2)
Real Options Analysis Values (7-Year Maturity At 5% Risk-Free Rate) 942(2)
Real Options Analysis Values (10-Year Maturity At 5% Risk-Free Rate) 944(2)
Real Options Analysis Values (15-Year Maturity At 5% Risk-Free Rate) 946(2)
Real Options Analysis Values (30-Year Maturity At 5% Risk-Free Rate) 948(3)
Answers To End Of Chapter Questions 951(8)
About The DVD-ROM 959(4)
System Requirements 959(1)
What's On The DVD 959(1)
Customer Care 960(3)
Index 963
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