TY  - BOOK
AU  - Benninga,Simon
TI  - Financial modeling /Simon Benninga ; with a section on Visual Basic for applications by Benjamin Czaczkes
SN  - 9780262321693
AV  - HG173 .F563 2014
PY  - 2014///
CY  - Cambridge, Massachusetts
PB  - The MIT Press
KW  - Microsoft Visual Basic for applications
KW  - Finance
KW  - Mathematical models
KW  - Electronic Books
N1  - "Uses Excel"--Cover; 2; Machine generated contents note: 0.1. Data Tables --; 0.2. What Is Getformula? --; 0.3. How to Put Getformula into Your Excel Notebook --; 0.4. Saving the Excel Workbook: Windows --; 0.5. Saving the Excel Workbook: Mac --; 0.6. Do You Have to Put Getformula into Each Excel Workbook? --; 0.7.A Shortcut to Use Getformula --; 0.8. Recording Getformula: The Windows Case --; 0.9. Recording Getformula: The Mac Case --; 1. Basic Financial Calculations --; 1.1. Overview --; 1.2. Present Value and Net Present Value --; 1.3. The Internal Rate of Return (IRR) and Loan Tables --; 1.4. Multiple Internal Rates of Return --; 1.5. Flat Payment Schedules --; 1.6. Future Values and Applications --; 1.7.A Pension Problem-Complicating the Future Value Problem --; 1.8. Continuous Compounding --; 1.9. Discounting Using Dated Cash Flows --; Exercises --; 2. Corporate Valuation Overview --; 2.1. Overview --; 2.2. Four Methods to Compute Enterprise Value (EV); Note continued: 2.3. Using Accounting Book Values to Value a Company: The Firm's Accounting Enterprise Value --; 2.4. The Efficient Markets Approach to Corporate Valuation --; 2.5. Enterprise Value (EV) as the Present Value of the Free Cash Flows: DCF "Top Down" Valuation --; 2.6. Free Cash Flows Based on Consolidated Statement of Cash Flows (CSCF) --; 2.7. ABC Corporation, Consolidated Statement of Cash Flows (CSCF) --; 2.8. Free Cash Flows Based on Pro Forma Financial Statements --; 2.9. Summary --; Exercises --; 3. Calculating the Weighted Average Cost of Capital (WACC) --; 3.1. Overview --; 3.2.Computing the Value of the Firm's Equity, E --; 3.3.Computing the Value of the Firm's Debt, D --; 3.4.Computing the Firm's Tax Rate, Tc --; 3.5.Computing the Firm's Cost of Debt, rD --; 3.6. Two Approaches to Computing the Firm's Cost of Equity, rE --; 3.7. Implementing the Gordon Model for rE --; 3.8. The CAPM: Computing the Beta; Note continued: 3.9. Using the Security Market Line (SML) to Calculate Merck's Cost of Equity, rE --; 3.10. Three Approaches to Computing the Expected Return on the Market, E(rM) --; 3.11. What's the Risk-Free Rate rf in the CAPM? --; 3.12.Computing the WACC, Three Cases --; 3.13.Computing the WACC for Merck (MRK) --; 3.14.Computing the WACC for Whole Foods (WFM) --; 3.15.Computing the WACC for Caterpillar (CAT) --; 3.16. When Don't the Models Work? --; 3.17. Summary --; Exercises --; 4. Valuation Based on the Consolidated Statement of Cash Flows --; 4.1. Overview --; 4.2. Free Cash Flow (FCF): Measuring the Cash Produced by the Business --; 4.3.A Simple Example --; 4.4. Merck: Reverse Engineering the Market Value --; 4.5. Summary --; Exercise --; 5. Pro Forma Financial Statement Modeling --; 5.1. Overview --; 5.2. How Financial Models Work: Theory and an Initial Example --; 5.3. Free Cash Flow (FCF): Measuring the Cash Produced by the Business; Note continued: 5.4. Using the Free Cash Flow (FCF) to Value the Firm and Its Equity --; 5.5. Some Notes on the Valuation Procedure --; 5.6. Alternative Modeling of Fixed Assets --; 5.7. Sensitivity Analysis --; 5.8. Debt as a Plug --; 5.9. Incorporating a Target Debt/Equity Ratio into a Pro Forma --; 5.10. Project Finance: Debt Repayment Schedules --; 5.11. Calculating the Return on Equity --; 5.12. Tax Loss Carryforwards --; 5.13. Summary --; Exercises --; 6. Building a Pro Forma Model: The Case of Caterpillar --; 6.1. Overview --; 6.2. Caterpillar's Financial Statements, 2007-2011 --; 6.3. Analyzing the Financial Statements --; 6.4.A Model for Caterpillar --; 6.5. Using the Model to Value Caterpillar --; 6.6. Summary --; 7. Financial Analysis of Leasing --; 7.1. Overview --; 7.2.A Simple but Misleading Example --; 7.3. Leasing and Firm Financing-The Equivalent-Loan Method --; 7.4. The Lessor's Problem: Calculating the Highest Acceptable Lease Rental --; 7.5. Asset Residual Value and Other Considerations; Note continued: 7.6. Leveraged Leasing --; 7.7.A Leveraged Lease Example --; 7.8. Summary --; Exercises --; 8. Portfolio Models-Introduction --; 8.1. Overview --; 8.2.Computing Returns for Apple (AAPL) and Google (GOOG) --; 8.3. Calculating Portfolio Means and Variances --; 8.4. Portfolio Mean and Variance-Case of N Assets --; 8.5. Envelope Portfolios --; 8.6. Summary --; Exercises --; Appendix 8.1: Adjusting for Dividends --; Appendix 8.2: Continuously Compounded Versus Geometric Returns --; 9. Calculating Efficient Portfolios --; 9.1. Overview --; 9.2. Some Preliminary Definitions and Notation --; 9.3. Five Propositions on Efficient Portfolios and the CAPM --; 9.4. Calculating the Efficient Frontier: An Example --; 9.5. Finding Efficient Portfolios in One Step --; 9.6. Three Notes on the Optimization Procedure --; 9.7. Finding the Market Portfolio: The Capital Market Line (CML) --; 9.8. Testing the SML-Implementing Propositions 3-5 --; 9.9. Summary --; Exercises --; Mathematical Appendix; Note continued: 10. Calculating the Variance-Covariance Matrix --; 10.1. Overview --; 10.2.Computing the Sample Variance-Covariance Matrix --; 10.3. The Correlation Matrix --; 10.4.Computing the Global Minimum Variance Portfolio (GMVP) --; 10.5. Four Alternatives to the Sample Variance-Covariance Matrix --; 10.6. Alternatives to the Sample Variance-Covariance: The Single-Index Model (SIM) --; 10.7. Alternatives to the Sample Variance-Covariance: Constant Correlation --; 10.8. Alternatives to the Sample Variance-Covariance: Shrinkage Methods --; 10.9. Using Option Information to Compute the Variance Matrix --; 10.10. Which Method to Compute the Variance-Covariance Matrix? --; 10.11. Summary --; Exercises --; 11. Estimating Betas and the Security Market Line --; 11.1. Overview --; 11.2. Testing the SML --; 11.3. Did We Learn Something? --; 11.4. The Non-Efficiency of the "Market Portfolio" --; 11.5. So What's the Real Market Portfolio? How Can We Test the CAPM? --; 11.6. Using Excess Returns; Note continued: 11.7. Summary: Does the CAPM Have Any Uses? --; Exercises --; 12. Efficient Portfolios Without Short Sales --; 12.1. Overview --; 12.2.A Numerical Example --; 12.3. The Efficient Frontier with Short-Sale Restrictions --; 12.4.A VBA Program for the Efficient Frontier Without Short Sales --; 12.5. Other Position Restrictions --; 12.6. Summary --; Exercise --; 13. The Black-Litterman Approach to Portfolio Optimization --; 13.1. Overview --; 13.2.A Naive Problem --; 13.3. Black and Litterman's Solution to the Optimization Problem --; 13.4. BL Step 1: What Does the Market Think? --; 13.5. BL Step 2: Introducing Opinions-What Does Joanna Think? --; 13.6. Using Black-Litterman for International Asset Allocation --; 13.7. Summary --; Exercises --; 14. Event Studies --; 14.1. Overview --; 14.2. Outline of an Event Study --; 14.3. An Initial Event Study: Procter and Gamble Buys Gillette --; 14.4.A Fuller Event Study: Impact of Earnings Announcements on Stock Prices; Note continued: 14.5. Using a Two-Factor Model of Returns for an Event Study --; 14.6. Using Excel's Offset Function to Locate a Regression in a Data Set --; 14.7. Summary --; 15. Introduction to Options --; 15.1. Overview --; 15.2. Basic Option Definitions and Terminology --; 15.3. Some Examples --; 15.4. Option Payoff and Profit Patterns --; 15.5. Option Strategies: Payoffs from Portfolios of Options and Stocks --; 15.6. Option Arbitrage Propositions --; 15.7. Summary --; Exercises --; 16. The Binomial Option Pricing Model --; 16.1. Overview --; 16.2. Two-Date Binomial Pricing --; 16.3. State Prices --; 16.4. The Multi-Period Binomial Model --; 16.5. Pricing American Options Using the Binomial Pricing Model --; 16.6. Programming the Binomial Option Pricing Model in VBA --; 16.7. Convergence of Binomial Pricing to the Black-Scholes Price --; 16.8. Using the Binomial Model to Price Employee Stock Options --; 16.9. Using the Binomial Model to Price Non-Standard Options: An Example --; 16.10. Summary --; Exercises; Note continued: 17. The Black-Scholes Model --; 17.1. Overview --; 17.2. The Black-Scholes Model --; 17.3. Using VBA to Define a Black-Scholes Pricing Function --; 17.4. Calculating the Volatility --; 17.5.A VBA Function to Find the Implied Volatility --; 17.6. Dividend Adjustments to the Black-Scholes --; 17.7. Using the Black-Scholes Formula to Price Structured Securities --; 17.8. Bang for the Buck with Options --; 17.9. The Black (1976) Model for Bond Option Valuation --; 17.10. Summary --; Exercises --; 18. Option Greeks --; 18.1. Overview --; 18.2. Defining and Computing the Greeks --; 18.3. Delta Hedging a Call --; 18.4. Hedging a Collar --; 18.5. Summary --; Exercises --; Appendix: VBA for Greeks --; 19. Real Options --; 19.1. Overview --; 19.2.A Simple Example of the Option to Expand --; 19.3. The Abandonment Option --; 19.4. Valuing the Abandonment Option as a Series of Puth --; 19.5. Valuing a Biotechnology Project --; 19.6. Summary --; Exercises --; 20. Duration --; 20.1. Overview --; 20.2. Two Examples; Note continued: 20.3. What Does Duration Mean? --; 20.4. Duration Patterns --; 20.5. The Duration of a Bond with Uneven Payments --; 20.6. Non-Flat Term Structures and Duration --; 20.7. Summary --; Exercises --; 21. Immunization Strategies --; 21.1. Overview --; 21.2.A Basic Simple Model of Immunization --; 21.3.A Numerical Example --; 21.4. Convexity: A Continuation of Our Immunization Experiment --; 21.5. Building a Better Mousetrap --; 21.6. Summary --; Exercises --; 22. Modeling the Term Structure --; 22.1. Overview --; 22.2. Basic Example --; 22.3. Several Bonds with the Same Maturity --; 22.4. Fitting a Functional Form to the Term Structure --; 22.5. The Properties of the Nelson-Siegel Term Structure --; 22.6. Term Structure for Treasury Notes --; 22.7. An Additional Computational Improvement --; 22.8. Nelson-Siegel-Svensson Model --; 22.9. Summary --; Appendix: VBA Functions Used in This Chapter --; 23. Calculating Default-Adjusted Expected Bond Returns --; 23.1. Overview; Note continued: 23.2. Calculating the Expected Return in a One-Period Framework --; 23.3. Calculating the Bond Expected Return in a Multi-Period Framework --; 23.4.A Numerical Example --; 23.5. Experimenting with the Example --; 23.6.Computing the Bond Expected Return for an Actual Bond --; 23.7. Semiannual Transition Matrices --; 23.8.Computing Bond Beta --; 23.9. Summary --; Exercises --; 24. Generating and Using Random Numbers --; 24.1. Overview --; 24.2. Rand() and Rnd: The Excel and VBA Random-Number Generators --; 24.3. Testing Random-Number Generators --; 24.4. Generating Normally Distributed Random Numbers --; 24.5. Norm. Inv: Another Way to Generate Normal Deviates --; 24.6. Generating Correlated Random Numbers --; 24.7. What's Our Interest in Correlation? A Small Case --; 24.8. Multiple Random Variables with Correlation: The Cholesky Decomposition --; 24.9. Multivariate Normal with Non-Zero Means --; 24.10. Multivariate Uniform Simulations --; 24.11. Summary --; Exercises; Note continued: 25. An Introduction to Monte Carlo Methods --; 25.1. Overview --; 25.2.Computing IT Using Monte Carlo --; 25.3. Writing a VBA Program --; 25.4. Another Monte Carlo Problem: Investment and Retirement --; 25.5.A Monte Carlo Simulation of the Investment Problem --; 25.6. Summary --; Exercises --; 26. Simulating Stock Prices --; 26.1. Overview --; 26.2. What Do Stock Prices Look Like? --; 26.3. Lognormal Price Distributions and Geometric Diffusions --; 26.4. What Does the Lognormal Distribution Look Like? --; 26.5. Simulating Lognormal Price Paths --; 26.6. Technical Analysis --; 26.7. Calculating the Parameters of the Lognormal Distribution from Stock Prices --; 26.8. Summary --; Exercises --; 27. Monte Carlo Simulations for Investments --; 27.1. Overview --; 27.2. Simulating Price and Returns for a Single Stock --; 27.3. Portfolio of Two Stocks --; 27.4. Adding a Risk-Free Asset --; 27.5. Multiple Stock Portfolios --; 27.6. Simulating Savings for Pensions --; 27.7. Beta and Return --; 27.8. Summary; Note continued: Exercises --; 28. Value at Risk (VaR) --; 28.1. Overview --; 28.2.A Really Simple Example --; 28.3. Defining Quantiles in Excel --; 28.4.A Three-Asset Problem: The Importance of the Variance-Covariance Matrix --; 28.5. Simulating Data: Bootstrapping --; Appendix: How to Bootstrap: Making a Bingo Card in Excel --; 29. Simulating Options and Option Strategies --; 29.1. Overview --; 29.2. Imperfect but Cashless Replication of a Call Option --; 29.3. Simulating Portfolio Insurance --; 29.4. Some Properties of Portfolio Insurance --; 29.5. Digression: Insuring Total Portfolio Returns --; 29.6. Simulating a Butterfly --; 29.7. Summary --; Exercises --; 30. Using Monte Carlo Methods for Option Pricing --; 30.1. Overview --; 30.2. Pricing a Plain-Vanilla Call Using Monte Carlo Methods --; 30.3. State Prices, Probabilities, and Risk Neutrality --; 30.4. Pricing a Call Using the Binomial Monte Carlo Model --; 30.5. Monte Carlo Plain-Vanilla Call Pricing Converges to Black-Scholes; Note continued: 30.6. Pricing Asian Options --; 30.7. Pricing Asian Options with a VBA Program --; 30.8. Pricing Barrier Options with Monte Carlo --; 30.9. Using VBA and Monte Carlo to Price a Barrier Option --; 30.10. Summary --; Exercises --; 31. Data Tables --; 31.1. Overview --; 31.2. An Example --; 31.3. Setting Up a One-Dimensional Data Table --; 31.4. Building a Two-Dimensional Data Table --; 31.5. An Aesthetic Note: Hiding the Formula Cells --; 31.6. Excel Data Tables Are Arrays --; 31.7. Data Tables on Blank Cells (Advanced) --; 31.8. Data Tables Can Stop Your Computer --; Exercises --; 32. Matrices --; 32.1. Overview --; 32.2. Matrix Operations --; 32.3. Matrix Inverses --; 32.4. Solving Systems of Simultaneous Linear Equations --; 32.5. Some Homemade Matrix Functions --; Exercises --; 33. Excel Functions --; 33.1. Overview --; 33.2. Financial Functions --; 33.3. Dates and Date Functions --; 33.4. The Functions XIRR, XNPV --; 33.5. Statistical Functions --; 33.6. Regressions with Excel; Note continued: 33.7. Conditional Functions --; 33.8. Large and Rank, Percentile, and PercentRank --; 33.9. Count, CountA, CountIf, CountIfs, AverageIf, AverageIfs --; 33.10. Boolean Functions --; 33.11. Offset --; 34. Array Functions --; 34.1. Overview --; 34.2. Some Built-In Excel Array Functions --; 34.3. Homemade Array Functions --; 34.4. Array Formulas with Matrices --; Exercises --; 35. Some Excel Hints --; 35.1. Overview --; 35.2. Fast Copy: Filling in Data Next to Filled-In Column --; 35.3. Filling Cells with a Series --; 35.4. Multi-Line Cells --; 35.5. Multi-Line Cells with Text Formulas --; 35.6. Writing on Multiple Spreadsheets --; 35.7. Moving Multiple Sheets of an Excel Notebook --; 35.8. Text Functions in Excel --; 35.9. Chart Titles That Update --; 35.10. Putting Greek Symbols in Cells --; 35.11. Superscripts and Subscripts --; 35.12. Named Cells --; 35.13. Hiding Cells (in Data Tables and Other Places) --; 35.14. Formula Auditing --; 35.15. Formatting Millions as Thousands; Note continued: 35.16. Excel's Personal Notebook: Automating Frequent Procedures --; 36. User-Defined Functions with VBA --; 36.1. Overview --; 36.2. Using the VBA Editor to Build a User-Defined Function --; 36.3. Providing Help for User-Defined Functions in the Function Wizard --; 36.4. Saving Excel Workbook with VBA Content --; 36.5. Fixing Mistakes in VBA --; 36.6. Conditional Execution: Using If Statements in VBA Functions --; 36.7. The Boolean and Comparison Operators --; 36.8. Loops --; 36.9. Using Excel Functions in VBA --; 36.10. Using User-Defined Functions in User-Defined Functions --; Exercises --; Appendix: Cell Errors in Excel and VBA --; 37. Variables and Arrays --; 37.1. Overview --; 37.2. Defining Function Variables --; 37.3. Arrays and Excel Ranges --; 37.4. Simple VBA Arrays --; 37.5. Multidimensional Arrays --; 37.6. Dynamic Arrays and the ReDim Statement --; 37.7. Array Assignment --; 37.8. Variants Containing an Array --; 37.9. Arrays as Parameters to Functions --; 37.10. Using Types; Note continued: 37.11. Summary --; Exercises --; 38. Subroutines and User Interaction --; 38.1. Overview --; 38.2. Subroutines --; 38.3. User Interaction --; 38.4. Using Subroutines to Change the Excel Workbook --; 38.5. Modules --; 38.6. Summary --; Exercises --; 39. Objects and Add-Ins --; 39.1. Overview --; 39.2. Introduction to Worksheet Objects --; 39.3. The Range Object --; 39.4. The With Statement --; 39.5. Collections --; 39.6. Names --; 39.7. Add-Ins and Integration --; 39.8. Summary --; Exercises; 2; b
N2  - This book is the standard text for explaining the implementation of financial models in Excel. As in previous editions, this fourth edition maintains the "cookbook" features and Excel dependence; it explains basic and advanced models in the areas of corporate finance, portfolio management, options, and bonds with detailed Excel spreadsheets. It also includes: a new section explaining the principles of Monte Carlo methods and their application to portfolio management and exotic option valuation; a new chapter discussing term structure modeling, with special emphasis on the Nelson-Siegel model; and a discussion of corporate valuation using pro forma models with the introduction of a new, simple model for corporate valuation based on accounting data and a minimal number of valuation parameters. --
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