Financial Modeling with Crystal Ball and Excel: + Website

Praise for the previous edition "Professor Charnes's book drives clarity into applied Monte Carlo analysis using examples and tools relevant to real-world finance. The book will prove useful for analysts of all levels and as a supplement to academic courses in multiple disciplines." —Mark Odermann , Senior Financial Analyst, Microsoft "Think you really know financial modeling? This is a must-have for power Excel users. Professor Charnes shows how to make more realistic models that result in fewer surprises. Every analyst needs this credibility booster." —James Franklin , CEO, SendGrid "This book packs a first-year MBA's worth of financial and business modeling education into a few dozen easy-to-understand examples. Crystal Ball software does the housekeeping, so readers can concentrate on the business decision. A careful reader who works the examples on a computer will master the best general-purpose technology available for working with uncertainty." —Aaron Brown , Risk Manager, AQR Capital Management, and author of The Poker Face of Wall Street and Red-Blooded Risk "Using Crystal Ball and Excel, John Charnes takes you step by step, demonstrating a conceptual framework that turns static Excel data and financial models into true risk models. I am astonished by the clarity of the text and the hands-on, step-by-step examples using Crystal Ball and Excel; Professor Charnes is a masterful teacher, and this is an absolute gem of a book for the new generation of analyst." —Brian Watt , Chief Operating Officer, GECC, Inc. " Financial Modeling with Crystal Ball and Excel is a comprehensive, well-written guide to one of the most useful analysis tools available to professional risk managers and quantitative analysts. This is a must-have book for anyone using Crystal Ball, and anyone wanting an overview of basic risk management concepts." —Paul Dietz , Manager, Quantitative Analysis, Westar Energy "John Charnes presents an insightful exploration of techniques for analysis and understanding of risk and uncertainty in business cases. By application of real options theory and Monte Carlo simulation to planning, doors are opened to analysis of what used to be impossible, such as modeling the value today of future project choices." —Bruce Wallace , former Director of Technology Strategy and Investments, Nortel The Second Edition of Financial Modeling with Oracle® Crystal Ball and Excel ®+ Website puts an emphasis on practical application. To that end, this book provides readers with exclusive access to a companion website filled with supplementary materials, allowing you to continue to learn in a hands-on fashion long after closing the book.

Preface xi Acknowledgments xvii About the Author xix CHAPTER 1 Introduction 1 1.1 Financial Modeling 2 1.2 Risk Analysis 2 1.3 Monte Carlo Simulation 4 1.4 Risk Management 8 1.5 Benefits and Limitations of Using Crystal Ball 9 CHAPTER 2 Analyzing Crystal Ball Forecasts 11 2.1 Simulating a 50–50 Portfolio 11 2.2 Varying the Allocations 22 2.3 Presenting the Results 27 CHAPTER 3 Building A Crystal Ball Model 29 3.1 Simulation Modeling Process 29 3.2 Defining Crystal Ball Assumptions and Forecasts 30 3.3 Running Crystal Ball 33 3.4 Sources of Error 34 3.5 Controlling Model Error 36 CHAPTER 4 Selecting Crystal Ball Assumptions 37 4.1 Crystal Ball’s Basic Distributions 37 4.2 Using Historical Data to Choose Distributions 55 4.3 Specifying Correlations 64 CHAPTER 5 Using Decision Variables 79 5.1 Defining Decision Variables 79 5.2 Decision Table with One Decision Variable 81 5.3 Decision Table with Two Decision Variables 87 5.4 Using OptQuest 98 CHAPTER 6 Selecting Run Preferences 105 6.1 Trials 105 6.2 Sampling 109 6.3 Speed 111 6.4 Options 113 6.5 Statistics 115 CHAPTER 7 Net Present Value and Internal Rate of Return 117 7.1 Deterministic NPV and IRR 117 7.2 Simulating NPV and IRR 119 7.3 Capital Budgeting 123 7.4 Customer Net Present Value 133 CHAPTER 8 Modeling Financial Statements 137 8.1 Deterministic Model 137 8.2 Tornado Chart and Sensitivity Analysis 138 8.3 Crystal Ball Sensitivity Chart 139 8.4 Conclusion 143 CHAPTER 9 Portfolio Models 145 9.1 Single–period Crystal Ball Model 145 9.2 Single–period Analytical Solution 148 9.3 Multi–period Crystal Ball Model 149 CHAPTER 10 Value at Risk 155 10.1 VaR 155 10.2 Shortcomings of VaR 157 10.3 Conditional Value at Risk 157 CHAPTER 11 Simulating Financial Time Series 163 11.1 White Noise 163 11.2 Random Walk 165 11.3 Autocorrelation 166 11.4 Additive Random Walk with Drift 170 11.5 Multiplicative Random Walk Model 173 11.6 Geometric Brownian Motion Model 176 11.7 Mean–reverting Model 180 CHAPTER 12 Financial Options 187 12.1 Types of Options 187 12.2 Risk–neutral Pricing and the Black–Scholes Model 188 12.3 Portfolio Insurance 192 12.4 American Option Pricing 194 12.5 Exotic Option Pricing 197 12.6 Bull Spread 201 12.7 Principal–protected Instrument 201 CHAPTER 13 Real Options 205 13.1 Financial Options and Real Options 205 13.2 Applications of Real Options Analysis 206 13.3 Black–Scholes Real Options Insights 209 13.4 Real Options Valuation Tool 211 CHAPTER 14 Credit Risk 221 14.1 Expected Loss 221 14.2 Credit Risk Simulation Model 223 14.3 Conditional Value at Risk 225 14.4 Using CVaR to Manage Credit Risk 227 CHAPTER 15 Construction Project Management 229 15.1 Project Description 229 15.2 Choosing Construction Methods 231 15.3 Risk Analysis 231 15.4 Stochastic Optimization 234 CHAPTER 16 Oil and Gas Exploration 235 16.1 Well Properties 235 16.2 Statistical Models 236 16.3 Conclusion 239 APPENDIX A Crystal Ball’s Probability Distributions 241 A.1 Bernoulli 241 A.2 Beta 243 A.3 Beta PERT 244 A.4 Binomial 246 A.5 Custom 247 A.6 Discrete Uniform 251 A.7 Exponential 252 A.8 Gamma 254 A.9 Geometric 255 A.10 Hypergeometric 257 A.11 Logistic 259 A.12 Lognormal 260 A.13 Maximum Extreme 262 A.14 Minimum Extreme 263 A.15 Negative Binomial 264 A.16 Normal 266 A.17 Pareto 267 A.18 Poisson 269 A.19 Student’s t 270 A.20 Triangular 272 A.21 Uniform 273 A.22 Weibull 275 A.23 Yes–No 276 APPENDIX B Generating Assumption Values 279 B.1 Generating Random Numbers 279 B.2 Generating Random Variates 282 B.3 Latin Hypercube Sampling 284 APPENDIX C Variance Reduction Techniques 287 C.1 Using Crystal Ball to Value an Asian Option 288 C.2 Antithetic Variates 289 C.3 Control Variates 289 C.4 Comparison 290 C.5 Conclusion 292 APPENDIX D About the Download 293 Glossary 297 References 301 Index 311

John Charnes, PhD, MBA, is President of the Risk Analytics and Predictive Intelligence Division (RAPID) of Syntelli Solutions Inc. Prior to this, he was finance department chair at the University of Kansas and senior vice president of global portfolio strategies at Bank of America. Charnes created the Crystal Ball Training CD, a multimedia course on the basic elements of stochastic modeling with Crystal Ball, acquired by Oracle. His specialty is the application of computer simulation and statistical methods for identifying and solving business problems, including the use of simulation for option pricing and hedging with derivatives to comply with Financial Accounting Standard (FAS) 133.