Applied risk analysis : moving beyond uncertainty in business
著者
書誌事項
Applied risk analysis : moving beyond uncertainty in business
（Wiley finance series）
J. Wiley, c2004
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注記
Includes bibliographical references and index
内容説明・目次
内容説明
Praise for Applied Risk Analysis "Once again, Dr. Mun has created a must-have, must-read book for anyone interested in the practical application of risk analysis. Other books speak in academic generalities, or focus on one area of risk application. Applied Risk Analysis gets to the heart of the matter with applications for every area of risk analysis. You have a real option to buy almost any bookyou should exercise your option and get this one!" Glenn Kautt, MBA, CFP, EA, President and Chairman, Monitor Group, Inc. "Johnathan Muns book is a sparkling jewel in my finance library. Mun demonstrates a deep understanding of the underlying mathematical theory in his ability to reduce complex concepts to lucid explanations and applications. For this reason, hes my favorite writer in this field. " Janet Tavakoli, President, Tavakoli Structured Finance, Inc. and author of Collateralized Debt Obligations & Structured Finance
目次
- Introduction
- PART ONE: Risk Identification
- CHAPTER 1: 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
- Five-Minute Industry Spotlight: ExperCorp
- Questions
- PART TWO: Risk Evaluation
- CHAPTER 2: From Risk to Riches
- Taming the Beast
- The Basics of Risk
- The Nature of Risk and Returns
- The Statistics of Risk
- The Measurements of Risk
- Five-Minute Industry Spotlight: Farmland
- Five-Minute Industry Spotlight: Environmental Protection Agency
- Questions
- CHAPTER 3: A Gentleman's Guide to Model Building
- 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
- 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 Crystal Ball and Excel to Perform Simulations
- Five-Minute Industry Spotlight: Colorado School of Mines
- Five-Minute Industry Spotlight: Hewlett-Packard
- Appendix Simulation
- Questions
- CHAPTER 5: Peering into the Crystal Ball
- The Basics of Crystal Ball Software
- Getting Started with Crystal Ball Software
- The Simulation Environment
- Creating a Simulation
- Interpreting the Simulation Results
- Five-Minute Industry Spotlight: TRW
- Five-Minute Industry Spotlight: DuPont Merck
- Questions
- CHAPTER 6: Pandora's Tool Box
- Tornado and Sensitivity Tools in Simulation
- Correlating and Fitting a Distribution Plus Precision Control
- Precision Control
- Bootstrap Simulation
- Two-Dimensional Simulation
- Decision Tables
- Five-Minute Industry Spotlight: 3M
- Five-Minute Industry Spotlight: Deloitte & Touche Consulting
- Appendix Goodness-of-Fit Tests
- Questions
- PART FOUR: Industry Applications
- CHAPTER 7: Extended Business Cases I: From Pharma to Black Gold
- Case Study: Pharmaceutical and Biotech High Precision Quantitative Deal Structuring in the Biotechnology and Pharmaceutical Industries
- Case Study: Oil and Gas Production and Exploration
- Five-Minute Industry Spotlight: Sierra Systems
- Five-Minute Industry Spotlight: Motorola
- PART FIVE: Risk Prediction
- CHAPTER 8: Tomorrow's Forecast Today
- What Is Forecasting?
- The Nature and View of Forecasting
- Five-Minute Industry Spotlight: Hewlett-Packard
- Five-Minute Industry Spotlight: SunTrust Bank
- Questions
- 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
- Introdu
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