000			19188cam a2200601Li 4500
001			ocn900218732
003			OCoLC
005			20240726105009.0
008			140801s2014 maua ob 001 0 eng d
040			_aYDXCP _beng _erda _epn _cYDXCP _dOCLCO _dB24X7 _dSTF _dOCLCF _dE7B _dTEFOD _dCOO _dTEFOD _dNT _dOCLCQ _dEBLCP
020			_a9780262321693 _q((electronic)l(electronic)ctronic)
050	0	4	_aHG173 _b.F563 2014
049			_aMAIN
100	1		_aBenninga, Simon, _e1
245	1	0	_aFinancial modeling /Simon Benninga ; with a section on Visual Basic for applications by Benjamin Czaczkes.
250			_aFourth edition.
260			_aCambridge, Massachusetts : _bThe MIT Press, _c(c)2014.
300			_a1 online resource (xxiv, 1111 pages .)
336			_atext _btxt _2rdacontent
337			_acomputer _bc _2rdamedia
338			_aonline resource _bcr _2rdacarrier
347			_adata file _2rda
500			_a"Uses Excel"--Cover.
504			_a2
505	0	0	_aMachine generated contents note: 0.1. Data Tables -- _t0.2. What Is Getformula? -- _t0.3. How to Put Getformula into Your Excel Notebook -- _t0.4. Saving the Excel Workbook: Windows -- _t0.5. Saving the Excel Workbook: Mac -- _t0.6. Do You Have to Put Getformula into Each Excel Workbook? -- _t0.7.A Shortcut to Use Getformula -- _t0.8. Recording Getformula: The Windows Case -- _t0.9. Recording Getformula: The Mac Case -- _t1. Basic Financial Calculations -- _t1.1. Overview -- _t1.2. Present Value and Net Present Value -- _t1.3. The Internal Rate of Return (IRR) and Loan Tables -- _t1.4. Multiple Internal Rates of Return -- _t1.5. Flat Payment Schedules -- _t1.6. Future Values and Applications -- _t1.7.A Pension Problem-Complicating the Future Value Problem -- _t1.8. Continuous Compounding -- _t1.9. Discounting Using Dated Cash Flows -- _tExercises -- _t2. Corporate Valuation Overview -- _t2.1. Overview -- _t2.2. Four Methods to Compute Enterprise Value (EV).
505	0	0	_aNote continued: 2.3. Using Accounting Book Values to Value a Company: The Firm's Accounting Enterprise Value -- _t2.4. The Efficient Markets Approach to Corporate Valuation -- _t2.5. Enterprise Value (EV) as the Present Value of the Free Cash Flows: DCF "Top Down" Valuation -- _t2.6. Free Cash Flows Based on Consolidated Statement of Cash Flows (CSCF) -- _t2.7. ABC Corporation, Consolidated Statement of Cash Flows (CSCF) -- _t2.8. Free Cash Flows Based on Pro Forma Financial Statements -- _t2.9. Summary -- _tExercises -- _t3. Calculating the Weighted Average Cost of Capital (WACC) -- _t3.1. Overview -- _t3.2.Computing the Value of the Firm's Equity, E -- _t3.3.Computing the Value of the Firm's Debt, D -- _t3.4.Computing the Firm's Tax Rate, Tc -- _t3.5.Computing the Firm's Cost of Debt, rD -- _t3.6. Two Approaches to Computing the Firm's Cost of Equity, rE -- _t3.7. Implementing the Gordon Model for rE -- _t3.8. The CAPM: Computing the Beta.
505	0	0	_aNote continued: 3.9. Using the Security Market Line (SML) to Calculate Merck's Cost of Equity, rE -- _t3.10. Three Approaches to Computing the Expected Return on the Market, E(rM) -- _t3.11. What's the Risk-Free Rate rf in the CAPM? -- _t3.12.Computing the WACC, Three Cases -- _t3.13.Computing the WACC for Merck (MRK) -- _t3.14.Computing the WACC for Whole Foods (WFM) -- _t3.15.Computing the WACC for Caterpillar (CAT) -- _t3.16. When Don't the Models Work? -- _t3.17. Summary -- _tExercises -- _t4. Valuation Based on the Consolidated Statement of Cash Flows -- _t4.1. Overview -- _t4.2. Free Cash Flow (FCF): Measuring the Cash Produced by the Business -- _t4.3.A Simple Example -- _t4.4. Merck: Reverse Engineering the Market Value -- _t4.5. Summary -- _tExercise -- _t5. Pro Forma Financial Statement Modeling -- _t5.1. Overview -- _t5.2. How Financial Models Work: Theory and an Initial Example -- _t5.3. Free Cash Flow (FCF): Measuring the Cash Produced by the Business.
505	0	0	_aNote continued: 5.4. Using the Free Cash Flow (FCF) to Value the Firm and Its Equity -- _t5.5. Some Notes on the Valuation Procedure -- _t5.6. Alternative Modeling of Fixed Assets -- _t5.7. Sensitivity Analysis -- _t5.8. Debt as a Plug -- _t5.9. Incorporating a Target Debt/Equity Ratio into a Pro Forma -- _t5.10. Project Finance: Debt Repayment Schedules -- _t5.11. Calculating the Return on Equity -- _t5.12. Tax Loss Carryforwards -- _t5.13. Summary -- _tExercises -- _t6. Building a Pro Forma Model: The Case of Caterpillar -- _t6.1. Overview -- _t6.2. Caterpillar's Financial Statements, 2007-2011 -- _t6.3. Analyzing the Financial Statements -- _t6.4.A Model for Caterpillar -- _t6.5. Using the Model to Value Caterpillar -- _t6.6. Summary -- _t7. Financial Analysis of Leasing -- _t7.1. Overview -- _t7.2.A Simple but Misleading Example -- _t7.3. Leasing and Firm Financing-The Equivalent-Loan Method -- _t7.4. The Lessor's Problem: Calculating the Highest Acceptable Lease Rental -- _t7.5. Asset Residual Value and Other Considerations.
505	0	0	_aNote continued: 7.6. Leveraged Leasing -- _t7.7.A Leveraged Lease Example -- _t7.8. Summary -- _tExercises -- _t8. Portfolio Models-Introduction -- _t8.1. Overview -- _t8.2.Computing Returns for Apple (AAPL) and Google (GOOG) -- _t8.3. Calculating Portfolio Means and Variances -- _t8.4. Portfolio Mean and Variance-Case of N Assets -- _t8.5. Envelope Portfolios -- _t8.6. Summary -- _tExercises -- _tAppendix 8.1: Adjusting for Dividends -- _tAppendix 8.2: Continuously Compounded Versus Geometric Returns -- _t9. Calculating Efficient Portfolios -- _t9.1. Overview -- _t9.2. Some Preliminary Definitions and Notation -- _t9.3. Five Propositions on Efficient Portfolios and the CAPM -- _t9.4. Calculating the Efficient Frontier: An Example -- _t9.5. Finding Efficient Portfolios in One Step -- _t9.6. Three Notes on the Optimization Procedure -- _t9.7. Finding the Market Portfolio: The Capital Market Line (CML) -- _t9.8. Testing the SML-Implementing Propositions 3-5 -- _t9.9. Summary -- _tExercises -- _tMathematical Appendix.
505	0	0	_aNote continued: 10. Calculating the Variance-Covariance Matrix -- _t10.1. Overview -- _t10.2.Computing the Sample Variance-Covariance Matrix -- _t10.3. The Correlation Matrix -- _t10.4.Computing the Global Minimum Variance Portfolio (GMVP) -- _t10.5. Four Alternatives to the Sample Variance-Covariance Matrix -- _t10.6. Alternatives to the Sample Variance-Covariance: The Single-Index Model (SIM) -- _t10.7. Alternatives to the Sample Variance-Covariance: Constant Correlation -- _t10.8. Alternatives to the Sample Variance-Covariance: Shrinkage Methods -- _t10.9. Using Option Information to Compute the Variance Matrix -- _t10.10. Which Method to Compute the Variance-Covariance Matrix? -- _t10.11. Summary -- _tExercises -- _t11. Estimating Betas and the Security Market Line -- _t11.1. Overview -- _t11.2. Testing the SML -- _t11.3. Did We Learn Something? -- _t11.4. The Non-Efficiency of the "Market Portfolio" -- _t11.5. So What's the Real Market Portfolio? How Can We Test the CAPM? -- _t11.6. Using Excess Returns.
505	0	0	_aNote continued: 11.7. Summary: Does the CAPM Have Any Uses? -- _tExercises -- _t12. Efficient Portfolios Without Short Sales -- _t12.1. Overview -- _t12.2.A Numerical Example -- _t12.3. The Efficient Frontier with Short-Sale Restrictions -- _t12.4.A VBA Program for the Efficient Frontier Without Short Sales -- _t12.5. Other Position Restrictions -- _t12.6. Summary -- _tExercise -- _t13. The Black-Litterman Approach to Portfolio Optimization -- _t13.1. Overview -- _t13.2.A Naive Problem -- _t13.3. Black and Litterman's Solution to the Optimization Problem -- _t13.4. BL Step 1: What Does the Market Think? -- _t13.5. BL Step 2: Introducing Opinions-What Does Joanna Think? -- _t13.6. Using Black-Litterman for International Asset Allocation -- _t13.7. Summary -- _tExercises -- _t14. Event Studies -- _t14.1. Overview -- _t14.2. Outline of an Event Study -- _t14.3. An Initial Event Study: Procter and Gamble Buys Gillette -- _t14.4.A Fuller Event Study: Impact of Earnings Announcements on Stock Prices.
505	0	0	_aNote continued: 14.5. Using a Two-Factor Model of Returns for an Event Study -- _t14.6. Using Excel's Offset Function to Locate a Regression in a Data Set -- _t14.7. Summary -- _t15. Introduction to Options -- _t15.1. Overview -- _t15.2. Basic Option Definitions and Terminology -- _t15.3. Some Examples -- _t15.4. Option Payoff and Profit Patterns -- _t15.5. Option Strategies: Payoffs from Portfolios of Options and Stocks -- _t15.6. Option Arbitrage Propositions -- _t15.7. Summary -- _tExercises -- _t16. The Binomial Option Pricing Model -- _t16.1. Overview -- _t16.2. Two-Date Binomial Pricing -- _t16.3. State Prices -- _t16.4. The Multi-Period Binomial Model -- _t16.5. Pricing American Options Using the Binomial Pricing Model -- _t16.6. Programming the Binomial Option Pricing Model in VBA -- _t16.7. Convergence of Binomial Pricing to the Black-Scholes Price -- _t16.8. Using the Binomial Model to Price Employee Stock Options -- _t16.9. Using the Binomial Model to Price Non-Standard Options: An Example -- _t16.10. Summary -- _tExercises.
505	0	0	_aNote continued: 17. The Black-Scholes Model -- _t17.1. Overview -- _t17.2. The Black-Scholes Model -- _t17.3. Using VBA to Define a Black-Scholes Pricing Function -- _t17.4. Calculating the Volatility -- _t17.5.A VBA Function to Find the Implied Volatility -- _t17.6. Dividend Adjustments to the Black-Scholes -- _t17.7. Using the Black-Scholes Formula to Price Structured Securities -- _t17.8. Bang for the Buck with Options -- _t17.9. The Black (1976) Model for Bond Option Valuation -- _t17.10. Summary -- _tExercises -- _t18. Option Greeks -- _t18.1. Overview -- _t18.2. Defining and Computing the Greeks -- _t18.3. Delta Hedging a Call -- _t18.4. Hedging a Collar -- _t18.5. Summary -- _tExercises -- _tAppendix: VBA for Greeks -- _t19. Real Options -- _t19.1. Overview -- _t19.2.A Simple Example of the Option to Expand -- _t19.3. The Abandonment Option -- _t19.4. Valuing the Abandonment Option as a Series of Puth -- _t19.5. Valuing a Biotechnology Project -- _t19.6. Summary -- _tExercises -- _t20. Duration -- _t20.1. Overview -- _t20.2. Two Examples.
505	0	0	_aNote continued: 20.3. What Does Duration Mean? -- _t20.4. Duration Patterns -- _t20.5. The Duration of a Bond with Uneven Payments -- _t20.6. Non-Flat Term Structures and Duration -- _t20.7. Summary -- _tExercises -- _t21. Immunization Strategies -- _t21.1. Overview -- _t21.2.A Basic Simple Model of Immunization -- _t21.3.A Numerical Example -- _t21.4. Convexity: A Continuation of Our Immunization Experiment -- _t21.5. Building a Better Mousetrap -- _t21.6. Summary -- _tExercises -- _t22. Modeling the Term Structure -- _t22.1. Overview -- _t22.2. Basic Example -- _t22.3. Several Bonds with the Same Maturity -- _t22.4. Fitting a Functional Form to the Term Structure -- _t22.5. The Properties of the Nelson-Siegel Term Structure -- _t22.6. Term Structure for Treasury Notes -- _t22.7. An Additional Computational Improvement -- _t22.8. Nelson-Siegel-Svensson Model -- _t22.9. Summary -- _tAppendix: VBA Functions Used in This Chapter -- _t23. Calculating Default-Adjusted Expected Bond Returns -- _t23.1. Overview.
505	0	0	_aNote continued: 23.2. Calculating the Expected Return in a One-Period Framework -- _t23.3. Calculating the Bond Expected Return in a Multi-Period Framework -- _t23.4.A Numerical Example -- _t23.5. Experimenting with the Example -- _t23.6.Computing the Bond Expected Return for an Actual Bond -- _t23.7. Semiannual Transition Matrices -- _t23.8.Computing Bond Beta -- _t23.9. Summary -- _tExercises -- _t24. Generating and Using Random Numbers -- _t24.1. Overview -- _t24.2. Rand() and Rnd: The Excel and VBA Random-Number Generators -- _t24.3. Testing Random-Number Generators -- _t24.4. Generating Normally Distributed Random Numbers -- _t24.5. Norm. Inv: Another Way to Generate Normal Deviates -- _t24.6. Generating Correlated Random Numbers -- _t24.7. What's Our Interest in Correlation? A Small Case -- _t24.8. Multiple Random Variables with Correlation: The Cholesky Decomposition -- _t24.9. Multivariate Normal with Non-Zero Means -- _t24.10. Multivariate Uniform Simulations -- _t24.11. Summary -- _tExercises.
505	0	0	_aNote continued: 25. An Introduction to Monte Carlo Methods -- _t25.1. Overview -- _t25.2.Computing IT Using Monte Carlo -- _t25.3. Writing a VBA Program -- _t25.4. Another Monte Carlo Problem: Investment and Retirement -- _t25.5.A Monte Carlo Simulation of the Investment Problem -- _t25.6. Summary -- _tExercises -- _t26. Simulating Stock Prices -- _t26.1. Overview -- _t26.2. What Do Stock Prices Look Like? -- _t26.3. Lognormal Price Distributions and Geometric Diffusions -- _t26.4. What Does the Lognormal Distribution Look Like? -- _t26.5. Simulating Lognormal Price Paths -- _t26.6. Technical Analysis -- _t26.7. Calculating the Parameters of the Lognormal Distribution from Stock Prices -- _t26.8. Summary -- _tExercises -- _t27. Monte Carlo Simulations for Investments -- _t27.1. Overview -- _t27.2. Simulating Price and Returns for a Single Stock -- _t27.3. Portfolio of Two Stocks -- _t27.4. Adding a Risk-Free Asset -- _t27.5. Multiple Stock Portfolios -- _t27.6. Simulating Savings for Pensions -- _t27.7. Beta and Return -- _t27.8. Summary.
505	0	0	_aNote continued: Exercises -- _t28. Value at Risk (VaR) -- _t28.1. Overview -- _t28.2.A Really Simple Example -- _t28.3. Defining Quantiles in Excel -- _t28.4.A Three-Asset Problem: The Importance of the Variance-Covariance Matrix -- _t28.5. Simulating Data: Bootstrapping -- _tAppendix: How to Bootstrap: Making a Bingo Card in Excel -- _t29. Simulating Options and Option Strategies -- _t29.1. Overview -- _t29.2. Imperfect but Cashless Replication of a Call Option -- _t29.3. Simulating Portfolio Insurance -- _t29.4. Some Properties of Portfolio Insurance -- _t29.5. Digression: Insuring Total Portfolio Returns -- _t29.6. Simulating a Butterfly -- _t29.7. Summary -- _tExercises -- _t30. Using Monte Carlo Methods for Option Pricing -- _t30.1. Overview -- _t30.2. Pricing a Plain-Vanilla Call Using Monte Carlo Methods -- _t30.3. State Prices, Probabilities, and Risk Neutrality -- _t30.4. Pricing a Call Using the Binomial Monte Carlo Model -- _t30.5. Monte Carlo Plain-Vanilla Call Pricing Converges to Black-Scholes.
505	0	0	_aNote continued: 30.6. Pricing Asian Options -- _t30.7. Pricing Asian Options with a VBA Program -- _t30.8. Pricing Barrier Options with Monte Carlo -- _t30.9. Using VBA and Monte Carlo to Price a Barrier Option -- _t30.10. Summary -- _tExercises -- _t31. Data Tables -- _t31.1. Overview -- _t31.2. An Example -- _t31.3. Setting Up a One-Dimensional Data Table -- _t31.4. Building a Two-Dimensional Data Table -- _t31.5. An Aesthetic Note: Hiding the Formula Cells -- _t31.6. Excel Data Tables Are Arrays -- _t31.7. Data Tables on Blank Cells (Advanced) -- _t31.8. Data Tables Can Stop Your Computer -- _tExercises -- _t32. Matrices -- _t32.1. Overview -- _t32.2. Matrix Operations -- _t32.3. Matrix Inverses -- _t32.4. Solving Systems of Simultaneous Linear Equations -- _t32.5. Some Homemade Matrix Functions -- _tExercises -- _t33. Excel Functions -- _t33.1. Overview -- _t33.2. Financial Functions -- _t33.3. Dates and Date Functions -- _t33.4. The Functions XIRR, XNPV -- _t33.5. Statistical Functions -- _t33.6. Regressions with Excel.
505	0	0	_aNote continued: 33.7. Conditional Functions -- _t33.8. Large and Rank, Percentile, and PercentRank -- _t33.9. Count, CountA, CountIf, CountIfs, AverageIf, AverageIfs -- _t33.10. Boolean Functions -- _t33.11. Offset -- _t34. Array Functions -- _t34.1. Overview -- _t34.2. Some Built-In Excel Array Functions -- _t34.3. Homemade Array Functions -- _t34.4. Array Formulas with Matrices -- _tExercises -- _t35. Some Excel Hints -- _t35.1. Overview -- _t35.2. Fast Copy: Filling in Data Next to Filled-In Column -- _t35.3. Filling Cells with a Series -- _t35.4. Multi-Line Cells -- _t35.5. Multi-Line Cells with Text Formulas -- _t35.6. Writing on Multiple Spreadsheets -- _t35.7. Moving Multiple Sheets of an Excel Notebook -- _t35.8. Text Functions in Excel -- _t35.9. Chart Titles That Update -- _t35.10. Putting Greek Symbols in Cells -- _t35.11. Superscripts and Subscripts -- _t35.12. Named Cells -- _t35.13. Hiding Cells (in Data Tables and Other Places) -- _t35.14. Formula Auditing -- _t35.15. Formatting Millions as Thousands.
505	0	0	_aNote continued: 35.16. Excel's Personal Notebook: Automating Frequent Procedures -- _t36. User-Defined Functions with VBA -- _t36.1. Overview -- _t36.2. Using the VBA Editor to Build a User-Defined Function -- _t36.3. Providing Help for User-Defined Functions in the Function Wizard -- _t36.4. Saving Excel Workbook with VBA Content -- _t36.5. Fixing Mistakes in VBA -- _t36.6. Conditional Execution: Using If Statements in VBA Functions -- _t36.7. The Boolean and Comparison Operators -- _t36.8. Loops -- _t36.9. Using Excel Functions in VBA -- _t36.10. Using User-Defined Functions in User-Defined Functions -- _tExercises -- _tAppendix: Cell Errors in Excel and VBA -- _t37. Variables and Arrays -- _t37.1. Overview -- _t37.2. Defining Function Variables -- _t37.3. Arrays and Excel Ranges -- _t37.4. Simple VBA Arrays -- _t37.5. Multidimensional Arrays -- _t37.6. Dynamic Arrays and the ReDim Statement -- _t37.7. Array Assignment -- _t37.8. Variants Containing an Array -- _t37.9. Arrays as Parameters to Functions -- _t37.10. Using Types.
505	0	0	_aNote continued: 37.11. Summary -- _tExercises -- _t38. Subroutines and User Interaction -- _t38.1. Overview -- _t38.2. Subroutines -- _t38.3. User Interaction -- _t38.4. Using Subroutines to Change the Excel Workbook -- _t38.5. Modules -- _t38.6. Summary -- _tExercises -- _t39. Objects and Add-Ins -- _t39.1. Overview -- _t39.2. Introduction to Worksheet Objects -- _t39.3. The Range Object -- _t39.4. The With Statement -- _t39.5. Collections -- _t39.6. Names -- _t39.7. Add-Ins and Integration -- _t39.8. Summary -- _tExercises.
520	0		_aThis 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. -- _cEdited summary from book.
530			_a2 _ub
630	0	0	_aMicrosoft Visual Basic for applications.
650		0	_aFinance _xMathematical models.
650		4	_aFinance _xMathematical models.
650		4	_aMicrosoft Visual Basic for applications.
655		1	_aElectronic Books.
856	4	0	_uhttps://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&db=nlabk&AN=1089520&site=eds-live&custid=s3260518 _zClick to access digital title | log in using your CIU ID number and my.ciu.edu password
942			_cOB _D _eEB _hHG _m2014 _QOL _R _x _8NFIC _2LOC
994			_a92 _bNT
999			_c85446 _d85446
902			_a1 _bCynthia Snell _c1 _dCynthia Snell