Financial Modeling with Crystal Ball and Excel

Name: Financial Modeling with Crystal Ball and Excel
Brand: Wiley
Price: 60.99 EUR
Availability: OnlineOnly

John Charnes(Autor*in)

Wiley (Verlag)

2. Auflage

Erschienen am 27. April 2012

336 Seiten

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Inhalt

Intro
Financial Modeling with Crystal Ball and Excel
Contents
Preface
Acknowledgments
About the Author
CHAPTER 1 Introduction
1.1 FINANCIAL MODELING
1.2 RISK ANALYSIS
1.3 MONTE CARLO SIMULATION
1.4 RISK MANAGEMENT
1.5 BENEFITS AND LIMITATIONS OF USING CRYSTAL BALL
1.5.1 Benefits
1.5.2 Limitations
CHAPTER 2 Analyzing Crystal Ball Forecasts
2.1 SIMULATING A 50-50 PORTFOLIO
2.1.1 Accumulate.xls
2.1.2 Frequency Chart
2.1.3 Cumulative Frequency Chart
2.1.4 Statistics View
2.1.5 Forecast Window Percentiles View
2.2 VARYING THE ALLOCATIONS
2.2.1 Decision Table Tool
2.2.2 Trend Chart
2.2.3 Overlay Chart
2.3 PRESENTING THE RESULTS
CHAPTER 3 Building A Crystal Ball Model
3.1 SIMULATION MODELING PROCESS
3.1.1 Example: AKGolf.xls
3.2 DEFINING CRYSTAL BALL ASSUMPTIONS AND FORECASTS
3.2.1 Defining Assumptions
3.2.2 Defining Profit as a Forecast Cell
3.3 RUNNING CRYSTAL BALL
3.4 SOURCES OF ERROR
3.5 CONTROLLING MODEL ERROR
CHAPTER 4 Selecting Crystal Ball Assumptions
4.1 CRYSTAL BALL'S BASIC DISTRIBUTIONS
4.1.1 Yes-No
4.1.2 Binomial
4.1.3 Discrete Uniform
4.1.4 Uniform
4.1.5 Triangular
4.1.6 Normal
4.1.7 Lognormal
4.2 USING HISTORICAL DATA TO CHOOSE DISTRIBUTIONS
4.2.1 Direct Sampling
4.2.2 Sampling from a Fitted Distribution
4.2.3 Fitting Distributions to Data
4.2.4 Goodness-of-Fit Testing
4.2.5 Eyeball Test
4.2.6 Caveats
4.2.7 What If No Historical Data Are Available?
4.3 SPECIFYING CORRELATIONS
4.3.1 Pearson Correlation Statistic
4.3.2 Spearman (Rank) Correlation Statistic
4.3.3 Using Crystal Ball to Calculate Correlations Between Two Assumptions
4.3.4 Batch Fit
4.3.5 Correlation Tool
CHAPTER 5 Using Decision Variables
5.1 DEFINING DECISION VARIABLES
5.2 DECISION TABLE WITH ONE DECISION VARIABLE
5.2.1 Trend Chart
5.2.2 Overlay Chart
5.3 DECISION TABLE WITH TWO DECISION VARIABLES
5.3.1 Model
5.3.2 Threshold Values
5.3.3 Two-Way Decision Table
5.3.4 Interpreting the Results
5.4 USING OPTQUEST
5.4.1 Terminology
5.4.2 Example
CHAPTER 6 Selecting Run Preferences
6.1 TRIALS
6.1.1 Number of Trials to Run
6.1.2 Stop on Calculation Errors
6.1.3 Stop When Precision Control Limits Are Reached
6.2 SAMPLING
6.2.1 Random Number Generation
6.2.2 Sampling Method
6.3 SPEED
6.3.1 Run Mode
6.3.2 Chart Windows
6.4 OPTIONS
6.5 STATISTICS
CHAPTER 7 Net Present Value and Internal Rate of Return
7.1 DETERMINISTIC NPV AND IRR
7.2 SIMULATING NPV AND IRR
7.3 CAPITAL BUDGETING
7.3.1 Tornado Chart Tool
7.3.2 Risk Analysis
7.3.3 Caveats
7.4 CUSTOMER NET PRESENT VALUE
7.4.1 Results
CHAPTER 8 Modeling Financial Statements
8.1 DETERMINISTIC MODEL
8.2 TORNADO CHART AND SENSITIVITY ANALYSIS
8.3 CRYSTAL BALL SENSITIVITY CHART
8.4 CONCLUSION
CHAPTER 9 Portfolio Models
9.1 SINGLE-PERIOD CRYSTAL BALL MODEL
9.2 SINGLE-PERIOD ANALYTICAL SOLUTION
9.3 MULTI-PERIOD CRYSTAL BALL MODEL
CHAPTER 10 Value at Risk
10.1 VAR
10.2 SHORTCOMINGS OF VAR
10.3 CONDITIONAL VALUE AT RISK
10.3.1 CVaR.xls
10.3.2 CVaRSubadditivity.xls
CHAPTER 11 Simulating Financial Time Series
11.1 WHITE NOISE
11.2 RANDOM WALK
11.3 AUTOCORRELATION
11.4 ADDITIVE RANDOM WALK WITH DRIFT
11.4.1 Generating Values from a Scalar Random Walk with Drift Process
11.4.2 Forecasting with Vector Random Walk Model
11.5 MULTIPLICATIVE RANDOM WALK MODEL
11.6 GEOMETRIC BROWNIAN MOTION MODEL
11.6.1 Generating Stock Prices with GBM
11.6.2 Estimating GBM Parameters
11.6.3 Generating Correlated Stock Prices
11.7 MEAN-REVERTING MODEL
11.7.1 AR(1) Process
11.7.2 AR( p) Process
CHAPTER 12 Financial Options
12.1 TYPES OF OPTIONS
12.2 RISK-NEUTRAL PRICING AND THE BLACK-SCHOLES MODEL
12.2.1 Option Pricing with Crystal Ball
12.3 PORTFOLIO INSURANCE
12.4 AMERICAN OPTION PRICING
12.5 EXOTIC OPTION PRICING
12.5.1 Digital Options
12.5.2 Barrier Options
12.5.3 Asian Options
12.6 BULL SPREAD
12.7 PRINCIPAL-PROTECTED INSTRUMENT
CHAPTER 13 Real Options
13.1 FINANCIAL OPTIONS AND REAL OPTIONS
13.2 APPLICATIONS OF REAL OPTIONS ANALYSIS
13.2.1 Black-Scholes Method
13.2.2 Lattice Methods
13.3 BLACK-SCHOLES REAL OPTIONS INSIGHTS
13.4 REAL OPTIONS VALUATION TOOL
13.4.1 ROV Modeling Process
13.4.2 Value Added by Using ROV Tool
13.4.3 Use of ROV Tool in New Product Development
13.4.4 Summary
CHAPTER 14 Credit Risk
14.1 EXPECTED LOSS
14.1.1 Probability of Default
14.1.2 Loss Given Default
14.1.3 Exposure at Default
14.2 CREDIT RISK SIMULATION MODEL
14.3 CONDITIONAL VALUE AT RISK
14.4 USING CVAR TO MANAGE CREDIT RISK
CHAPTER 15 Construction Project Management
15.1 PROJECT DESCRIPTION
15.2 CHOOSING CONSTRUCTION METHODS
15.3 RISK ANALYSIS
15.4 STOCHASTIC OPTIMIZATION
CHAPTER 16 Oil and Gas Exploration
16.1 WELL PROPERTIES
16.2 STATISTICAL MODELS
16.3 CONCLUSION
APPENDIX A Crystal Ball's Probability Distributions
A.1 BERNOULLI
A.2 BETA
A.3 BETA PERT
A.4 BINOMIAL
A.5 CUSTOM
A.6 DISCRETE UNIFORM
A.7 EXPONENTIAL
A.8 GAMMA
A.9 GEOMETRIC
A.10 HYPERGEOMETRIC
A.11 LOGISTIC
A.12 LOGNORMAL
A.13 MAXIMUM EXTREME
A.14 MINIMUM EXTREME
A.15 NEGATIVE BINOMIAL
A.16 NORMAL
A.17 PARETO
A.18 POISSON
A.19 STUDENT'S T
A.20 TRIANGULAR
A.21 UNIFORM
A.22 WEIBULL
A.23 YES-NO
APPENDIX B Generating Assumption Values
B.1 GENERATING RANDOM NUMBERS
B.1.1 Example LCG
B.1.2 Crystal Ball's LCG
B.1.3 Excel's Random Number Generator
B.2 GENERATING RANDOM VARIATES
B.2.1 Inverse-transform Method
B.3 LATIN HYPERCUBE SAMPLING
APPENDIX C Variance Reduction Techniques
C.1 USING CRYSTAL BALL TO VALUE AN ASIAN OPTION
C.2 ANTITHETIC VARIATES
C.3 CONTROL VARIATES
C.4 COMPARISON
C.5 CONCLUSION
APPENDIX D About the Download
Trialware
Glossary
References
Index

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