Updated look at financial modeling and Monte Carlo simulation with software by Oracle Crystal Ball This revised and updated edition of the bestselling book on financial modeling provides the tools and techniques needed to perform spreadsheet simulation. It answers the essential question of why risk analysis is vital to the decision-making process, for any problem posed in finance and investment. This reliable resource reviews the basics and covers how to define and refine probability distributions in financial modeling, and explores the concepts driving the simulation modeling process. It also discusses simulation controls and analysis of simulation results. The second edition of Financial Modeling with Crystal Ball and Excel contains instructions, theory, and practical example models to help apply risk analysis to such areas as derivative pricing, cost estimation, portfolio allocation and optimization, credit risk, and cash flow analysis. It includes the resources needed to develop essential skills in the areas of valuation, pricing, hedging, trading, risk management, project evaluation, credit risk, and portfolio management. * Offers an updated edition of the bestselling book covering the newest version of Oracle Crystal Ball* Contains valuable insights on Monte Carlo simulation-an essential skill applied by many corporate finance and investment professionals* Written by John Charnes, the former finance department chair at the University of Kansas and senior vice president of global portfolio strategies at Bank of America, who is currently President and Chief Data Scientist at Syntelli Solutions, Inc. Risk Analytics and Predictive Intelligence Division (Syntelli RAPID) Engaging and informative, this book is a vital resource designed to help you become more adept at financial modeling and simulation.
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
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