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The Resource Financial modeling, Simon Benninga ; with a section on Visual Basic for applications by Benjamin Czaczkes

Financial modeling, Simon Benninga ; with a section on Visual Basic for applications by Benjamin Czaczkes

Label
Financial modeling
Title
Financial modeling
Statement of responsibility
Simon Benninga ; with a section on Visual Basic for applications by Benjamin Czaczkes
Creator
Author
Subject
Genre
Language
eng
Summary
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. --
Member of
Assigning source
Edited summary from book
Cataloging source
YDXCP
http://library.link/vocab/creatorName
Benninga, Simon
Dewey number
332.01/5118
Illustrations
illustrations
Index
index present
LC call number
HG173
LC item number
.B46 2014
Literary form
non fiction
Nature of contents
  • dictionaries
  • bibliography
http://library.link/vocab/subjectName
  • Finance
  • Excel
  • BUSINESS & ECONOMICS
  • Finance
  • Finanzierung
  • Mathematisches Modell
  • VisualBASIC für Applikationen
  • Wiskundige modellen
  • Bedrijfsfinanciering
Label
Financial modeling, Simon Benninga ; with a section on Visual Basic for applications by Benjamin Czaczkes
Instantiates
Publication
Copyright
Note
"Uses Excel"--Cover
Bibliography note
Includes bibliographical references and index
Carrier category
online resource
Carrier category code
  • cr
Carrier MARC source
rdacarrier
Content category
text
Content type code
  • txt
Content type MARC source
rdacontent
Contents
  • 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 Corp., 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 & 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
Control code
900218732
Dimensions
unknown
Edition
Fourth edition.
Extent
1 online resource (xxiv, 1111 pages)
Form of item
online
Isbn
9780262321693
Lccn
2013032409
Media category
computer
Media MARC source
rdamedia
Media type code
  • c
http://library.link/vocab/ext/overdrive/overdriveId
2eaea26d-a228-416a-bd4f-dca39739250f
Specific material designation
remote
System control number
(OCoLC)900218732
Label
Financial modeling, Simon Benninga ; with a section on Visual Basic for applications by Benjamin Czaczkes
Publication
Copyright
Note
"Uses Excel"--Cover
Bibliography note
Includes bibliographical references and index
Carrier category
online resource
Carrier category code
  • cr
Carrier MARC source
rdacarrier
Content category
text
Content type code
  • txt
Content type MARC source
rdacontent
Contents
  • 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 Corp., 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 & 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
Control code
900218732
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unknown
Edition
Fourth edition.
Extent
1 online resource (xxiv, 1111 pages)
Form of item
online
Isbn
9780262321693
Lccn
2013032409
Media category
computer
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rdamedia
Media type code
  • c
http://library.link/vocab/ext/overdrive/overdriveId
2eaea26d-a228-416a-bd4f-dca39739250f
Specific material designation
remote
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(OCoLC)900218732

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