Table of Contents

Cover

Additional Praise for Modeling Risk

Series Page

Title

Copyright

Dedication

Preface

What’s New in the Second Edition

Acknowledgments

About the Author

Introduction

PART ONE—RISK IDENTIFICATION

PART TWO—RISK EVALUATION

PART THREE—RISK QUANTIFICATION

PART FOUR—INDUSTRY APPLICATIONS

PART FIVE—RISK PREDICTION

PART SIX—RISK DIVERSIFICATION

PART SEVEN—RISK MITIGATION

PART EIGHT—MORE INDUSTRY APPLICATIONS

PART NINE—RISK MANAGEMENT

ADDITIONAL MATERIAL

PART One: Risk Identification

CHAPTER 1: Moving Beyond Uncertainty

A BRIEF HISTORY OF RISK: WHAT EXACTLY IS RISK?

UNCERTAINTY VERSUS RISK

WHY IS RISK IMPORTANT IN MAKING DECISIONS?

DEALING WITH RISK THE OLD-FASHIONED WAY

THE LOOK AND FEEL OF RISK AND UNCERTAINTY

INTEGRATED RISK MANAGEMENT (IRM)®

QUESTIONS

PART Two: Risk Evaluation

CHAPTER 2: From Risk to Riches

TAMING THE BEAST

THE BASICS OF RISK

THE NATURE OF RISK AND RETURN

THE STATISTICS OF RISK

THE MEASUREMENTS OF RISK

APPENDIX—COMPUTING RISK

QUESTIONS

CHAPTER 3: A Guide to Model-Building Etiquette

DOCUMENT THE MODEL

SEPARATE INPUTS, CALCULATIONS, AND RESULTS

PROTECT THE MODELS

MAKE THE MODEL USER-FRIENDLY: DATA VALIDATION AND ALERTS

TRACK THE MODEL

AUTOMATE THE MODEL WITH VBA

MODEL AESTHETICS AND CONDITIONAL FORMATTING

APPENDIX—A PRIMER ON VBA MODELING AND WRITING MACROS

EXERCISES

PART Three: Risk Quantification

CHAPTER 4: On the Shores of Monaco

WHAT IS MONTE CARLO SIMULATION?

WHY ARE SIMULATIONS IMPORTANT?

COMPARING SIMULATION WITH TRADITIONAL ANALYSES

USING RISK SIMULATOR AND EXCEL TO PERFORM SIMULATIONS

QUESTIONS

CHAPTER 5: Test Driving Risk Simulator

GETTING STARTED WITH RISK SIMULATOR

RUNNING A MONTE CARLO SIMULATION

USING FORECAST CHARTS AND CONFIDENCE INTERVALS

CORRELATIONS AND PRECISION CONTROL

APPENDIX—UNDERSTANDING PROBABILITY DISTRIBUTIONS

APPENDIX—ROV COMPILER: PROTECTS AND CONVERTS EXCEL FILES INTO EXECUTABLE EXE

APPENDIX—ROV EXTRACTOR AND EVALUATOR: RUNS EXTREME SUPER SPEED SIMULATIONS AND CONVERTS EXCEL MODELS INTO A CALCULATOR ENVIRONMENT

QUESTIONS

EXERCISES

CHAPTER 6: Pandora’s Toolbox

TORNADO AND SENSITIVITY TOOLS IN SIMULATION

SENSITIVITY ANALYSIS

DISTRIBUTIONAL FITTING: SINGLE VARIABLE AND MULTIPLE VARIABLES

BOOTSTRAP SIMULATION

HYPOTHESIS TESTING

DATA EXTRACTION, SAVING SIMULATION RESULTS, AND GENERATING REPORTS

CUSTOM MACROS

DISTRIBUTIONAL ANALYSIS TOOL

SCENARIO ANALYSIS TOOL

SEGMENTATION CLUSTERING TOOL

STRUCTURAL BREAK ANALYSIS

DETRENDING AND DESEASONALIZING

PRINCIPAL COMPONENT ANALYSIS

APPENDIX—GOODNESS-OF-FIT TESTS

QUESTIONS

EXERCISES

PART Four: Industry Applications

CHAPTER 7: Extended Business Cases I

CASE STUDY: PHARMACEUTICAL AND BIOTECH DEAL STRUCTURING

CASE STUDY: OIL AND GAS EXPLORATION AND PRODUCTION

CASE STUDY: FINANCIAL PLANNING WITH SIMULATION

CASE STUDY: HOSPITAL RISK MANAGEMENT

CASE STUDY: RISK-BASED EXECUTIVE COMPENSATION VALUATION

CASE STUDY: RISK-BASED SCHEDULE PLANNING WITH SIMULATION

PART Five: Risk Prediction

CHAPTER 8: Tomorrow’s Forecast Today

DIFFERENT TYPES OF FORECASTING TECHNIQUES

RUNNING THE FORECASTING TOOL IN RISK SIMULATOR

TIME-SERIES ANALYSIS

MULTIVARIATE REGRESSION

STEPWISE REGRESSION

STOCHASTIC FORECASTING

NONLINEAR EXTRAPOLATION

BOX–JENKINS ARIMA ADVANCED TIME-SERIES

AUTO ARIMA (BOX–JENKINS ARIMA ADVANCED TIME-SERIES)

BASIC ECONOMETRICS

J-CURVE AND S-CURVE FORECASTS

GARCH VOLATILITY FORECASTS

MARKOV CHAINS

MAXIMUM LIKELIHOOD MODELS ON LOGIT, PROBIT, AND TOBIT

SPLINE (CUBIC SPLINE INTERPOLATION AND EXTRAPOLATION)

QUESTIONS

EXERCISE: FORECASTING

CHAPTER 9: Using the Past to Predict the Future

TIME-SERIES FORECASTING METHODOLOGY

NO TREND AND NO SEASONALITY

WITH TREND BUT NO SEASONALITY

NO TREND BUT WITH SEASONALITY

WITH SEASONALITY AND WITH TREND

REGRESSION ANALYSIS

THE PITFALLS OF FORECASTING: OUTLIERS, NONLINEARITY, MULTICOLLINEARITY, HETEROSKEDASTICITY, AUTOCORRELATION, AND STRUCTURAL BREAKS

OTHER TECHNICAL ISSUES IN REGRESSION ANALYSIS

REGRESSION AND FORECASTING DIAGNOSTIC TOOL

STATISTICAL ANALYSIS TOOL

APPENDIX—FORECAST INTERVALS

APPENDIX—ORDINARY LEAST SQUARES

APPENDIX—DETECTING AND FIXING HETEROSKEDASTICITY

APPENDIX—DETECTING AND FIXING MULTICOLLINEARITY

APPENDIX—DETECTING AND FIXING AUTOCORRELATION

QUESTIONS

EXERCISE

PART Six: Risk Diversification

CHAPTER 10: The Search for the Optimal Decision

WHAT IS AN OPTIMIZATION MODEL?

THE TRAVELING FINANCIAL PLANNER

THE LINGO OF OPTIMIZATION

SOLVING OPTIMIZATION GRAPHICALLY AND USING EXCEL’S SOLVER

QUESTIONS

CHAPTER 11: Optimization Under Uncertainty

OPTIMIZATION PROCEDURES

CONTINUOUS OPTIMIZATION

DISCRETE INTEGER OPTIMIZATION

EFFICIENT FRONTIER AND ADVANCED OPTIMIZATION SETTINGS

STOCHASTIC OPTIMIZATION

OPTIMIZATION APPLICATION EXAMPLE: MILITARY PORTFOLIO AND EFFICIENT FRONTIER

OPTIMIZATION APPLICATION EXAMPLE: OPTIMAL PRICING WITH ELASTICITY

APPENDIX—ROV MODELER SUITE: SERVER-BASED APPLICATIONS FOR RUNNING DATA-INTENSIVE MODELS AT EXTREMELY HIGH SPEEDS

APPENDIX—COMPUTING ANNUALIZED RETURNS AND RISK FOR PORTFOLIO OPTIMIZATION

EXERCISE: OPTIMIZATION

QUESTIONS

PART Seven: Risk Mitigation

CHAPTER 12: What Is So Real About Real Options, and Why Are They Optional?

WHAT ARE REAL OPTIONS?

THE REAL OPTIONS SOLUTION IN A NUTSHELL

ISSUES TO CONSIDER

IMPLEMENTING REAL OPTIONS ANALYSIS

TYPES OF REAL OPTIONS STRATEGIES

INDUSTRY LEADERS EMBRACING REAL OPTIONS

MORE SAMPLE APPLICATIONS AND SHORT CASES

WHAT THE EXPERTS ARE SAYING

CRITICISMS, CAVEATS, AND MISUNDERSTANDINGS IN REAL OPTIONS

QUESTIONS

CHAPTER 13: The Black Box Made Transparent: Real Options Super Lattice Solver Software

SINGLE ASSET SUPER LATTICE SOLVER

MULTIPLE ASSET SUPER LATTICE SOLVER

MULTINOMIAL SUPER LATTICE SOLVER

SLS LATTICE MAKER

SLS EXCEL SOLUTION (SLS, MSLS, AND CHANGING VOLATILITY MODELS IN EXCEL)

SLS FUNCTIONS

EXOTIC FINANCIAL OPTIONS VALUATOR

PAYOFF CHARTS, TORNADO SENSITIVITY, SCENARIO, AND CONVERGENCE ANALYSIS

KEYSLSNOTESANDTIPS

EXERCISES

PART Eight: More Industry Applications

CHAPTER 14: Extended Business Cases II

CASE STUDY: UNDERSTANDING RISK AND OPTIMAL TIMING IN A REAL ESTATE DEVELOPMENT USING REAL OPTIONS ANALYSIS

CASE STUDY: USING STOCHASTIC OPTIMIZATION AND VALUATION MODELS TO EVALUATE THE CREDIT RISK OF CORPORATE RESTRUCTURING

CASE STUDY: REAL OPTIONS AND KVA IN MILITARY STRATEGY AT THE UNITED STATES NAVY

CASE STUDY: MANUFACTURING AND SALES IN THE AUTOMOTIVE AFTERMARKET

CASE STUDY: THE BOEING COMPANY’S STRATEGIC ANALYSIS OF THE GLOBAL EARTH OBSERVATION SYSTEM OF SYSTEMS

CASE STUDY: VALUING EMPLOYEE STOCK OPTIONS UNDER THE 2004 FAS 123R

CASE STUDY: OIL AND GAS ROYALTY LEASE NEGOTIATION

CHAPTER 14: Extended Business Cases II

CASE STUDY: HOW REAL OPTIONS MITIGATES IT ENTERPRISE SECURITY RISKS

CASE STUDY: BASEL II CREDIT RISK AND MARKET RISK

CASE STUDY: IT INFORMATION SECURITY INTRUSION RISK MANAGEMENT

PART Nine: Risk Management

CHAPTER 15: The Warning Signs

THE PROBLEM OF NEGLIGENT ENTRUSTMENT

MANAGEMENT’S DUE DILIGENCE

SINS OF AN ANALYST

READING THE WARNING SIGNS IN MONTE CARLO SIMULATION

READING THE WARNING SIGNS IN TIME-SERIES FORECASTING AND REGRESSION

READING THE WARNING SIGNS IN REAL OPTIONS ANALYSIS

READING THE WARNING SIGNS IN OPTIMIZATION UNDER UNCERTAINTY

QUESTIONS

CHAPTER 16: Changing a Corporate Culture

HOW TO GET RISK ANALYSIS ACCEPTED IN AN ORGANIZATION

CHANGE-MANAGEMENT ISSUES AND PARADIGM SHIFTS

MAKING TOMORROW’S FORECAST TODAY

PARTING SHOTS AND A WORD OF CAUTION FROM THE AUTHOR

Tables You Really Need

Answers to End of Chapter Questions

About the DVD-ROM

SYSTEM REQUIREMENTS

WHAT’S ON THE DVD

CUSTOMER CARE

Index

END USER LICENSE AGREEMENT

List of Tables

CHAPTER 6: Culture

TABLE 6.1 Sensitivity Table

TABLE 6.2 Chi-Square Test

CHAPTER 7: Management Support

TABLE 7.1 Historical Financial Terms Granted to the Licensor of the Signed Biomedical Collaborative Deal Valued and Optimized in This Case Study

TABLE 7.2 Deal Scenario Summary Table as Calculated by Monte Carlo Analysis

TABLE 7.3 Deal Component Weights, Component CVs, Weighted Average Deal CVs, and Calculated Deal CVs

TABLE 7.4 The Deterministic Plan

TABLE 7.5 The Actual Results

TABLE 7.6 Portfolio Balance Analysis

TABLE 7.7 Reversed Returns

TABLE 7.8 Returns Analysis Without Withdrawals

TABLE 7.9 Simulation-Based Withdrawal Rates

TABLE 7.10 Utilization Trends for 2014 by Service Line

TABLE 7.11 Priority Orthopedic/Neurosurgery Admissions Classified by Admission

TABLE 7.12 MGK Blocking Model Showing Bed Need Service Targets

TABLE 7.13 Availability MGK Blocking Model with Determination of Beds and Probability of

TABLE 7.14 Solutions Results of Bed Need Projections for Both Current and New Campus

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