Financial modeling:
The third edition of this standard text retains the popular 'cookbook' features of the earlier editions and includes expanded and new coverage of such topics as bank valuation, the Black-Litterman portfolio selection model, Monte Carlo pricing methods, array function, and getting informati...
Gespeichert in:
| Format: | Buch |
|---|---|
| Sprache: | English |
| Veröffentlicht: |
Cambridge, Mass. [u.a.]
MIT Press
2008
|
| Ausgabe: | 3. ed. |
| Schlagworte: | |
| Online-Zugang: | Inhaltsverzeichnis Klappentext |
| Zusammenfassung: | The third edition of this standard text retains the popular 'cookbook' features of the earlier editions and includes expanded and new coverage of such topics as bank valuation, the Black-Litterman portfolio selection model, Monte Carlo pricing methods, array function, and getting information from the Internet with VBA. |
| Beschreibung: | XXVIII, 1133 S. Ill., graph. Darst. 1 CD-ROM (12 cm) |
| ISBN: | 9780262026284 |
Internformat
MARC
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| 245 | 1 | 0 | |a Financial modeling |c Simon Benninga. With a section on Visual Basic for Applications by Benjamin Czaczkes |
| 250 | |a 3. ed. | ||
| 264 | 1 | |a Cambridge, Mass. [u.a.] |b MIT Press |c 2008 | |
| 300 | |a XXVIII, 1133 S. |b Ill., graph. Darst. |e 1 CD-ROM (12 cm) | ||
| 336 | |b txt |2 rdacontent | ||
| 337 | |b n |2 rdamedia | ||
| 338 | |b nc |2 rdacarrier | ||
| 520 | |a The third edition of this standard text retains the popular 'cookbook' features of the earlier editions and includes expanded and new coverage of such topics as bank valuation, the Black-Litterman portfolio selection model, Monte Carlo pricing methods, array function, and getting information from the Internet with VBA. | ||
| 650 | 4 | |a Finances - Modèles mathématiques | |
| 650 | 4 | |a Mathematisches Modell | |
| 650 | 4 | |a Finance |x Mathematical models | |
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| 650 | 0 | 7 | |a CD-ROM |0 (DE-588)4139307-7 |2 gnd |9 rswk-swf |
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| 700 | 1 | |a Czaczkes, Benjamin |e Sonstige |4 oth | |
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Datensatz im Suchindex
| _version_ | 1804137311713099776 |
|---|---|
| adam_text | Contents
Preface
xxiii
Preface
to the Second Edition
xxix
Preface to the First Edition
xxxi
Corporate Finance Models
1
Basic Financial Calculations
3
1.1
Overview
3
1.2
Present Value and Net Present Value
4
1.3
Internal Rate of Return and Loan Tables
9
1.4
Multiple Internal Rates of Return
15
1.5
Flat Payment Schedules
17
1.6
Future Values and Applications
19
1.7
A Pension Problem
—
Complicating the Future-Value
Problem
21
1.8
Continuous Compounding
25
1.9
Discounting Using Dated Cash Flows
30
Exercises
31
Calculating the Cost of Capital
39
2.1
Overview
39
2.2
The Gordon Dividend Model
40
2.3
Adjusting the Gordon Model to Account for All Cash
Flows to Equity
44
2.4
Supernormal Growth and the Gordon Model
48
2.5
Using the Capital Asset Pricing Model to Determine the
Cost of Equity
r e
52
2.6
Using the Security Market Line to Calculate Intel s Cost
of Equity
59
2.7
Three Approaches to Computing the Expected Return
on the Market E(rM)
62
2.8
Calculating the Cost of Debt
66
2.9
Computing the WACC: Three Cases
70
2.10
Computing the WACC for Kraft Corporation
70
2.11
Computing the WACC for Tyson Foods
73
2.12
Computing the WACC for Cascade Corporation
77
2.13
When the Models Don t Work
81
Contents
2.14
Conclusion
86
Exercises
87
Appendix 1:
Why Is
β
a Good Measurement of Risk? Portfolio
β
versus Individual Stock
В
92
Appendix
2:
Getting Data from the Internet
95
Financial Statement Modeling
103
3.1
Overview
103
3.2
How Financial Models Work: Theory and an Initial
Example
103
3.3
Free Cash Flow: Measuring the Cash Produced by the
Business 111
3.4
Using the Free Cash Flow to Value the Firm and Its
Equity
113
3.5
Some Notes on the Valuation Procedure
115
3.6
Sensitivity Analysis
117
3.7
Debt as a Plug
118
3.8
Incorporating a Target Debt/Equity Ration into a Pro
Forma
121
3.9
Project Finance: Debt Repayment Schedules
122
3.10
Calculating the Return on Equity
125
3.11
Conclusion
127
Exercises
127
Appendix
1:
Calculating the Free Cash Flows When There Are
Negative Profits
130
Appendix
2:
Accelerated Depreciation in Pro Forma Models
131
Building a Financial Model: The Case of PPG Corporation
135
4.1
Overview
135
4.2
PPG Financial Statements,
1991-2000 136
4.3
Analyzing the Financial Statements
138
4.4
A Model for PPG
142
4.5
Back to Treasury Stock and the Dividend
146
4.6
The Whole Model
147
4.7
Free Cash Flows and Valuation
148
4.8
What Is PPG s Dividend Policy?
151
Contents
4.9
Modeling PPG s
Dividend
Policy
155
4.10 Computing PPG s
Cost of Equity rE and Its Cost of
Debt rD
156
4.11
What Is PPG s Weighted Average Cost of Capital?
160
4.12
Back to the Valuation
—
Sensitivity Analyses
161
Exercises
163
Appendix: Some Accounting Issues
163
Bank Valuation
177
5.1
Overview
177
5.2
Analyzing Bank Balance Sheets
177
5.3
The Bank s Free Cash Flow
185
5.4
Large Bank Corporation Buys Small Bank: A Valuation
Example
188
5.5
Calculating the Exchange Ratio
193
5.6
Alternatives to FCF Valuation of Financial Institutions
194
5.7
Valuing a Bank by Using Capital Adequacy Ratios
194
5.8
Using P/Es to Value a Bank Acquisition: First Federal
Savings Bank
196
The Financial Analysis of Leasing
203
6.1
Overview
203
6.2
A Simple Example
203
6.3
Leasing and Firm Financing: The Equivalent-Loan
Method
205
6.4
The Lessor s Problem: Calculating the Highest
Acceptable Lease Rental
208
6.5
Asset Residual Value and Other Considerations
212
6.6
Summary
214
Exercises
214
Appendix: The Tax and Accounting Treatment of Leases
215
The Financial Analysis of Leveraged Leases
219
7.1
Overview
219
7.2
An Example
220
7.3
Analyzing the Cash Flows by NPV or
IRR 224
7.4
What Does the
IRR
Mean?
226
Contents
7.5
Accounting for Leveraged Leases: The Multiple Phases
Method
230
7.6
Comparing the MPM Rate of Return with the
IRR 234
7.7
Summary
234
Exercises
235
Portfolio Models
237
Portfolio Models—Introduction
239
8.1
Overview
239
8.2
Computing Returns for Walmart and Target
239
8.3
Calculating Portfolio Means and Variances
245
8.4
Portfolio Means and Variances
—
The General Case
246
8.5
Efficient Portfolios
250
8.6
Conclusion
252
Exercises
252
Appendix
1:
Adjusting for Dividends
255
Appendix
2:
Continuously Compounded versus Geometric
Returns
257
Calculating Efficient Portfolios When There Are No
Short-Sale Restrictions
261
9.1
Overview
261
9.2
Some Preliminary Definitions and Notation
261
9.3
Some Theorems on Efficient Portfolios and CAPM
263
9.4
Calculating the Efficient Frontier: An Example
268
9.5
Three Notes on the Optimization Procedure
272
9.6
Finding Efficient Portfolios in One Step
276
9.7
Finding the Market Portfolio: The Capital Market Line
278
9.8
Testing the SML: Implementing Propositions
3-5 280
9.9
Summary
283
Exercises
283
Appendix
285
Calculating the Variance-Covariance Matrix
291
10.1
Overview
291
10.2
Computing the Sample Variance-Covariance Matrix
291
Contents
10.3
Should We Divide by
M
or by
M
- 1?
Excel versus
Statistics
295
10.4
Alternate Methods for Computing the Sample Variance-
Covariance Matrix
297
10.5
Computing the Global Minimum Variance Portfolio
299
10.6
Computing an Efficient Portfolio
301
10.7
Alternatives to the Sample Variance-Covariance: The
Single-Index Model
304
10.8
Alternatives to the Sample Variance-Covariance:
Constant Correlation
306
10.9
Shrinkage Methods
308
10.10
Alternatives to the Variance-Covariance Matrix: Impact
on the Minimum-Variance Portfolio and the Optimal
Portfolio
310
10.11
Summary
315
Exercises
315
Estimating Betas and the Security Market Line
317
11.1
Overview
317
11.2
Testing the Security Market Line
320
11.3
Did We Learn Something?
324
11.4
The Inefficiency of the Market Portfolio
326
11.5
So What s the Real Market Portfolio? How Can We Test
the CAPM?
329
11.6
Using Excess Returns
330
11.7
Does the CAPM Have Any Uses?
332
Exercises
333
Efficient Portfolios without Short Sales
335
12.1
Overview
335
12.2
A Numerical Example
336
12.3
The Efficient Frontier with Short-Sale Restrictions
341
12.4
A VBA Program to Create the Efficient Frontier
343
12.5
Other Position Restrictions
345
12.6
Conclusion
347
Exercises
347
Contents
The Black-Litterman
Approach to Portfolio Optimization
349
13.1
Overview
349
13.2
A Naive Problem
351
13.3
Black and Litterman s Solution to the Optimization
Problem
357
13.4
Black-Litterman Step
1:
What Does the Market Think?
357
13.5
Black-Litterman Step
2:
Introducing Opinions
—
What
Does Joanna Think?
360
13.6
Implementing Black-Litterman on an International
Portfolio
365
13.7
Summary
368
Exercises
369
Event Studies
371
14.1
Overview
371
14.2
Outline of an Event Study
371
14.3
An Initial Event Study. Procter
&
Gamble Buys
Gillette
375
14.4
A Fuller Event Study: Impact of Earnings
Announcements on Stock Prices
382
14.5
Using a Two-Factor Model of Returns for an Event
Study
390
14.6
Using
Exceľs
Offset Function to Locate a Regression in
a Data Set
394
14.7
Conclusion
396
Value at Risk
397
15.1
Overview
397
15.2
A Really Simple Example
397
15.3
Defining Quantiles in Excel
399
15.4
A Three-Asset Problem: The Importance of the
Variance-Covariance Matrix
402
15.5
Simulating Data
—
Bootstrapping
404
Appendix: How to Bootstrap: Making a Bingo Card in
Excel
409
Contents
Ш
Option-Pricing Models
419
16
An Introduction to Options
421
16.1
Overview
421
16.2
Basic Option Definitions and Terminology
421
16.3
Some Examples
424
16.4
Option Payoff and Profit Patterns
426
16.5
Option Strategies: Payoffs from Portfolios of Options
and Stocks
430
16.6
Option Arbitrage Propositions
432
16.7
Summary
439
Exercises
439
17
The Binomial Option-Pricing Model
443
17.1
Overview
443
17.2
Two-Date Binomial Pricing
443
17.3
State Prices
445
17.4
The Multiperiod Binomial Model
449
17.5
Pricing American Options Using the Binomial Pricing
Model
455
17.6
Programming the Binomial Option-Pricing Model in
VBA
458
17.7
Convergence of Binomial Pricing in the Black-Scholes
Price
463
17.8
Using the Binomial Model to Price Employee Stock
Options
466
17.9
Using the Binomial Model to Price
Nonstandard
Options: An Example
476
17.10
Summary
478
Exercises
478
18
The
Lognormal
Distribution
483
18.1
Overview
483
18.2
What Do Stock Prices Look Like?
484
18.3 Lognormal
Price Distributions and Geometric
Diffusions
492
18.4
What Does the
Lognormal
Distribution Look Like?
495
18.5
Simulating
Lognormal
Price Paths
498
xiv Contents
18.6 Technical
Analysis
502
18.7
Calculating the Parameters of the
Lognormal
Distribution from Stock Prices
503
18.8
Summary
505
Exercises
505
19
The Black-Scholes Model
509
19.1
Overview
509
19.2
The Black-Scholes Model
509
19.3
Using VBA to Define a Black-Scholes Pricing Function
511
19.4
Calculating the Implied Volatility
513
19.5
A VBA Function to Find the Implied Variance
517
19.6
Dividend Adjustments to the Black-Scholes
520
19.7
Using the Black-Scholes Formula to Price Structured
Securities
525
19.8
Bang for the Buck with Options
539
19.9
The Black
(1976)
Model for Bond Option Valuation
541
19.10
Summary
544
Exercises
544
20
Option Greeks
549
20.1
Overview
549
20.2
Defining and Computing the Greeks
550
20.3
Delta Hedging a Call
555
20.4
Hedging a Collar
564
20.5
Summary
574
Exercises
575
21
Portfolio Insurance
577
21.1
Overview
577
21.2
Portfolio Insurance on More Complicated Assets
578
21.3
An Example
580
21.4
Some Properties of Portfolio Insurance
584
21.5
What Do Portfolio Insurance Strategies Look Like?
A Simulation
585
21.6
Insuring Total Portfolio Returns
588
21.7
Implicit Puts and Asset Values
592
Contents
21.8
Summary
593
Exercises
594
An Introduction of Monte Carlo Methods
597
22.1
Overview
597
22.2
Computing
π
Using Monte Carlo
597
22.3
Writing a VBA Program
602
22.4
Another Monte Carlo Problem: Investment and
Retirement
604
22.5
A Monte Carlo Simulation of the Investment Problem
607
22.6
Summary
610
Exercises
610
Using Monte Carlo Methods for Option Pricing
613
23.1
Overview
613
23.2
State Prices, Probabilities, and Risk Neutrality
613
23.3
Pricing a Plain-Vanilla Call Using Monte Carlo
Methods
615
23.4
Monte Carlo Plain-Vanilla Call Pricing Converges to
Biack-Scholes
618
23.5
Pricing Asian Options
625
23.6
Pricing Asian Options with a VBA Program
633
23.7
Pricing Barrier Options with Monte Carlo
638
23.8
Using VBA and Monte Carlo to Price a Barrier
Option
642
23.9
Summary
646
Exercises
646
Real Options
649
24.1
Overview
649
24.2
A Simple Example of the Option to Expand
650
24.3
The Abandonment Option
653
24.4
Valuing the Abandonment Option as a Series of Puts
659
24.5
Valuing a Biotechnology Project
662
24.6
Conclusion
667
Exercises
667
xvi Contents
IV
25
26
27
Bonds
669
Duration
671
25.1
Overview
671
25.2
Two Examples
671
25.3
What Does Duration Mean?
674
25.4
Duration Patterns
678
25.5
The Duration of a Bond with Uneven Payments
679
25.6
Nonflat Term Structures and Duration
687
25.7
Summary
689
Exercises
689
Immunization Strategies
693
26.1
Overview
693
26.2
A Basic Simple Immunization Model
693
26.3
A Numerical Example
695
26.4
Convexity: A Continuation of Our Immunization
Experiment
698
26.5
Building a Better Mousetrap
700
26.6
Summary
704
Exercises
704
Modeling the Term Structure
705
27.1
Overview
705
27.2
An Initial Example
705
27.3
Description of the Data
710
27.4
The Treasury Yield Curve
713
27.5
Computing Par Yields from a Zero-Coupon Yield Curve
715
27.6
Summary
716
Exercises
717
28
Calculating Default-Adjusted Expected Bond Returns
719
28.1
Overview
719
28.2
Calculating the Expected Bond Return in a One-Period
Framework
721
28.3
Calculating the Expected Bond Return in a Multiperiod
Framework
722
28.4
A Numerical Example
726
Contents
28.5
Experimenting with the Example
728
28.6
Computing the Bond Expected Return for an Actual
Bond
730
28.7
Semiannual Transition Matrices
734
28.8
Computing Bond Beta
737
28.9
Summary
739
Exercises
740
Technical Considerations
743
Generating Random Numbers
745
29.1
Overview
745
29.2
Rand(
)
and Rnd: The Excel and VBA Random-Number
Generators
746
29.3
Testing Random-Number Generators
749
29.4
Generating Normally Distributed Random Numbers
754
29.5
Summary
762
Exercises
762
Data Tables
765
30.1
Overview
765
30.2
An Example
765
30.3
Setting Up a Data Table
766
30.4
Building a Two-Dimensional Data Table
768
30.5
An Aesthetic Note: Hiding the Formula Cells
769
30.6
Excel Data Tables Are Arrays
770
Exercises
771
Matrices
775
31.1
Overview
775
31.2
Matrix Operations
776
31.3
Matrix Inverses
779
31.4
Solving Systems of Simultaneous Linear Equations
781
Exercises
782
The Gauss-Seidel Method
785
32.1
Overview
785
32.2
A Simple Example
785
32.3
A More Concise Solution
786
Contents
32.4
Conclusion
787
Exercises
■ 787
Excel
Functions
789
33.1
Overview
789
33.2
Financial
Functions
789
33.3
Dates
and Date Functions
796
33.4
The Functions XIRR and XNPV
802
33.5
Statistical Functions
805
33.6
Doing Regressions with Excel
808
33.7
Conditional Functions
815
33.8
Large and Rank, Percentile, and Percentrank
816
33.9
Count, CountA, CountIF
817
33.10
Boolean Functions
819
33.11
Offset
821
Using Array Functions and Formulas
825
34.1
Overview
825
34.2
Some Built-in Array Functions
825
34.3
Homemade Array Functions
830
34.4
Array Formulas with Matrices
833
Exercises
838
Some Excel Hints
841
35.1
Overview
841
35.2
Fast Copy: Filling in Data Next to a Filled-in Column
841
35.3
Multiline Cells
843
35.4
Writing on Multiple Spreadsheets
845
35.5
Text Functions in Excel
847
35.6
Chart Titles That Update
847
35.7
Getformula: A Useful Way of Annotating Spreadsheets
850
35.8
Putting Greek Symbols in Cells
853
35.9
Superscripts and Subscripts
854
35.10
Named Cells
856
35.11
Hiding Cells
857
35.12
Formula Auditing
859
35.13
Formulating Millions as Thousands
861
xix Contents
VI
Introduction
to
Visual Basic for Applications
865
36
User-Defined Functions with
VBA
867
36.1
Overview
867
36.2
Using the
VBA
Editor to Build a User-Defined Function
867
36.3
Providing Help for the User-Defined Functions in the
Function Wizard
872
36.4
Fixing Mistakes in VBA
875
36.5
Conditional Execution: Using If Statements in VBA
Functions
877
36.6
The Select Case Statement
882
36.7
Using Excel Functions in VBA
884
36.8
Using User-Defined Functions in User-Defined
Functions
885
Exercises
888
Appendix: Cell Errors in Excel and VBA
892
37
Types and Loops
895
37.1
Overview
895
895
897
901
904
913
913
37.2
Using Types
37.3
Variables and Variable Types
37.4
Boolean and Comparison Operators
37.5
Loops
37.6
Summary
Exercises
Macros and User Interaction
38.1
Overview
38.2
Macro Subroutines
38.3
User Output and the MsgBox Function
38.4
User Input and the InputBox Function
38.5
Modules
38.6
Summary
38
Macros and User Interaction
919
919
919
926
930
932
935
Exercises
935
39
Arrays
941
39.1
Overview
941
39.2
Simple Arrays
941
Contents
41
39.3
Multidimensional Arrays
946
39.4
Dynamic Arrays and the ReDim Statement
948
39.5
Array Assignment
959
39.6
Variants Containing an Array
960
39.7
Arrays as Parameters to Functions
963
39.8
Summary
971
Exercises
971
Objects and Add-Ins
975
40.1
Overview
975
40.2
An Introduction to Worksheet Objects
975
40.3
The Range Object
979
40.4
The With Statement
984
40.5
Collections
985
40.6
Names
991
40.7
Using the Object Browser
995
40.8
References to External Functions in Excel
997
40.9
References to External Functions in VBA
999
40.10
Add-Ins and Integration
1008
40.11
Summary
1014
Exercises
1014
Appendix
1:
The Excel Object Model
1018
Appendix
2:
Extracts from the Help File for Some Methods
1020
Information from the Web
1029
41.1
Overview
1029
41.2
Copy and Paste as a Simple Data-Acquisition
Technique
1029
41.3
Dynamic Web Queries
1035
41.4
Web Queries: The iqy File
1041
41.5
Parametric Web Pages
1047
41.6
Web Queries: Parameters
1049
41.7
Web Queries: CSV Files and Postprocessing
1056
41.8
A VBA Application: Importing Price Data from Yahoo
1059
41.9
Summary
1089
Exercises
1089
xxi
Contents
Appendix 1:
Excerpts from the Help File
1090
Appendix
2:
The RlCl Reference Style
1093
References
1095
Index
1107
economics
Financial Modeling
third edition
Simon Benninga
Too often, finance courses stop short of making a connection
of real-world business. Financial Modeling bridges this gap
nuts-and-bolts guide to solving common financial
modějs
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reader step by step through each model, showing how itcgn
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The long-awaited third edition of this standard text
dependence that have made the first and second editions
і
with new chapters covering such topics as bank valuation,
mization, Monte Carlo methods and their appli
mulas.
Other chapters, including those on basic
variance-covariance matrix, and generating random
riunì
stantially new and improved material.; Other areas
standard portfolio problems, value at risk (VaR),
ré
modeling. Technical chapters treat such topicsas data
іфіШ;$ШШі&Е,
for using Excel. The last section of the text covers th|
for the book. The accompanying CD contains Excel
Simon Benninga is Professor of Finance at
Tę!
Wharton School at the University of
Pennşylvanid.
I ve learned a great deal from
thè;
first two ediKi
edition offers both new topics and updated cpyerdge pl
well-illustrated instructions for using Excel
sophisticated, in both corporate finance and
і
pany
data, and the book gives useful tips
an outstanding resource for finance
keep my copy close at hand;
;4;í
—Robert A. Taggarf, Professor of
Financial Modeling by Simon
^nЫι^gaΐş:^:qÌ1■,òцťşte■rв..а..■;
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both undergraduates and master s; students.
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financial modeler s toolkit. ;
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— Richard
W.
Roll, Professor of
¡Management, qpd
The new edition of Simon
Benninga ş
doing tool in motivating users and jrigking easily
investments, and derivatives. In the real wprld ol
practitioner to search the Internet for financial dqtoy
financial decisions. I strongly recommend it to the
—George Constantinides, Leo Melamed Professor
óf Fi
of Business
|
| adam_txt |
Contents
Preface
xxiii
Preface
to the Second Edition
xxix
Preface to the First Edition
xxxi
Corporate Finance Models
1
Basic Financial Calculations
3
1.1
Overview
3
1.2
Present Value and Net Present Value
4
1.3
Internal Rate of Return and Loan Tables
9
1.4
Multiple Internal Rates of Return
15
1.5
Flat Payment Schedules
17
1.6
Future Values and Applications
19
1.7
A Pension Problem
—
Complicating the Future-Value
Problem
21
1.8
Continuous Compounding
25
1.9
Discounting Using Dated Cash Flows
30
Exercises
31
Calculating the Cost of Capital
39
2.1
Overview
39
2.2
The Gordon Dividend Model
40
2.3
Adjusting the Gordon Model to Account for All Cash
Flows to Equity
44
2.4
"Supernormal Growth" and the Gordon Model
48
2.5
Using the Capital Asset Pricing Model to Determine the
Cost of Equity
r e
52
2.6
Using the Security Market Line to Calculate Intel's Cost
of Equity
59
2.7
Three Approaches to Computing the Expected Return
on the Market E(rM)
62
2.8
Calculating the Cost of Debt
66
2.9
Computing the WACC: Three Cases
70
2.10
Computing the WACC for Kraft Corporation
70
2.11
Computing the WACC for Tyson Foods
73
2.12
Computing the WACC for Cascade Corporation
77
2.13
When the Models Don't Work
81
Contents
2.14
Conclusion
86
Exercises
87
Appendix 1:
Why Is
β
a Good Measurement of Risk? Portfolio
β
versus Individual Stock
В
92
Appendix
2:
Getting Data from the Internet
95
Financial Statement Modeling
103
3.1
Overview
103
3.2
How Financial Models Work: Theory and an Initial
Example
103
3.3
Free Cash Flow: Measuring the Cash Produced by the
Business 111
3.4
Using the Free Cash Flow to Value the Firm and Its
Equity
113
3.5
Some Notes on the Valuation Procedure
115
3.6
Sensitivity Analysis
117
3.7
Debt as a Plug
118
3.8
Incorporating a Target Debt/Equity Ration into a Pro
Forma
121
3.9
Project Finance: Debt Repayment Schedules
122
3.10
Calculating the Return on Equity
125
3.11
Conclusion
127
Exercises
127
Appendix
1:
Calculating the Free Cash Flows When There Are
Negative Profits
130
Appendix
2:
Accelerated Depreciation in Pro Forma Models
131
Building a Financial Model: The Case of PPG Corporation
135
4.1
Overview
135
4.2
PPG Financial Statements,
1991-2000 136
4.3
Analyzing the Financial Statements
138
4.4
A Model for PPG
142
4.5
Back to Treasury Stock and the Dividend
146
4.6
The Whole Model
147
4.7
Free Cash Flows and Valuation
148
4.8
What Is PPG's Dividend Policy?
151
Contents
4.9
Modeling PPG's
Dividend
Policy
155
4.10 Computing PPG's
Cost of Equity rE and Its Cost of
Debt rD
156
4.11
What Is PPG's Weighted Average Cost of Capital?
160
4.12
Back to the Valuation
—
Sensitivity Analyses
161
Exercises
163
Appendix: Some Accounting Issues
163
Bank Valuation
177
5.1
Overview
177
5.2
Analyzing Bank Balance Sheets
177
5.3
The Bank's Free Cash Flow
185
5.4
Large Bank Corporation Buys Small Bank: A Valuation
Example
188
5.5
Calculating the Exchange Ratio
193
5.6
Alternatives to FCF Valuation of Financial Institutions
194
5.7
Valuing a Bank by Using Capital Adequacy Ratios
194
5.8
Using P/Es to Value a Bank Acquisition: First Federal
Savings Bank
196
The Financial Analysis of Leasing
203
6.1
Overview
203
6.2
A Simple Example
203
6.3
Leasing and Firm Financing: The Equivalent-Loan
Method
205
6.4
The Lessor's Problem: Calculating the Highest
Acceptable Lease Rental
208
6.5
Asset Residual Value and Other Considerations
212
6.6
Summary
214
Exercises
214
Appendix: The Tax and Accounting Treatment of Leases
215
The Financial Analysis of Leveraged Leases
219
7.1
Overview
219
7.2
An Example
220
7.3
Analyzing the Cash Flows by NPV or
IRR 224
7.4
What Does the
IRR
Mean?
226
Contents
7.5
Accounting for Leveraged Leases: The "Multiple Phases
Method"
230
7.6
Comparing the MPM Rate of Return with the
IRR 234
7.7
Summary
234
Exercises
235
Portfolio Models
237
Portfolio Models—Introduction
239
8.1
Overview
239
8.2
Computing Returns for Walmart and Target
239
8.3
Calculating Portfolio Means and Variances
245
8.4
Portfolio Means and Variances
—
The General Case
246
8.5
Efficient Portfolios
250
8.6
Conclusion
252
Exercises
252
Appendix
1:
Adjusting for Dividends
255
Appendix
2:
Continuously Compounded versus Geometric
Returns
257
Calculating Efficient Portfolios When There Are No
Short-Sale Restrictions
261
9.1
Overview
261
9.2
Some Preliminary Definitions and Notation
261
9.3
Some Theorems on Efficient Portfolios and CAPM
263
9.4
Calculating the Efficient Frontier: An Example
268
9.5
Three Notes on the Optimization Procedure
272
9.6
Finding Efficient Portfolios in One Step
276
9.7
Finding the Market Portfolio: The Capital Market Line
278
9.8
Testing the SML: Implementing Propositions
3-5 280
9.9
Summary
283
Exercises
283
Appendix
285
Calculating the Variance-Covariance Matrix
291
10.1
Overview
291
10.2
Computing the Sample Variance-Covariance Matrix
291
Contents
10.3
Should We Divide by
M
or by
M
- 1?
Excel versus
Statistics
295
10.4
Alternate Methods for Computing the Sample Variance-
Covariance Matrix
297
10.5
Computing the Global Minimum Variance Portfolio
299
10.6
Computing an Efficient Portfolio
301
10.7
Alternatives to the Sample Variance-Covariance: The
Single-Index Model
304
10.8
Alternatives to the Sample Variance-Covariance:
Constant Correlation
306
10.9
Shrinkage Methods
308
10.10
Alternatives to the Variance-Covariance Matrix: Impact
on the Minimum-Variance Portfolio and the Optimal
Portfolio
310
10.11
Summary
315
Exercises
315
Estimating Betas and the Security Market Line
317
11.1
Overview
317
11.2
Testing the Security Market Line
320
11.3
Did We Learn Something?
324
11.4
The Inefficiency of the "Market Portfolio"
326
11.5
So What's the Real Market Portfolio? How Can We Test
the CAPM?
329
11.6
Using Excess Returns
330
11.7
Does the CAPM Have Any Uses?
332
Exercises
333
Efficient Portfolios without Short Sales
335
12.1
Overview
335
12.2
A Numerical Example
336
12.3
The Efficient Frontier with Short-Sale Restrictions
341
12.4
A VBA Program to Create the Efficient Frontier
343
12.5
Other Position Restrictions
345
12.6
Conclusion
347
Exercises
347
Contents
The Black-Litterman
Approach to Portfolio Optimization
349
13.1
Overview
349
13.2
A Naive Problem
351
13.3
Black and Litterman's Solution to the Optimization
Problem
357
13.4
Black-Litterman Step
1:
What Does the Market Think?
357
13.5
Black-Litterman Step
2:
Introducing Opinions
—
What
Does Joanna Think?
360
13.6
Implementing Black-Litterman on an International
Portfolio
365
13.7
Summary
368
Exercises
369
Event Studies
371
14.1
Overview
371
14.2
Outline of an Event Study
371
14.3
An Initial Event Study. Procter
&
Gamble Buys
Gillette
375
14.4
A Fuller Event Study: Impact of Earnings
Announcements on Stock Prices
382
14.5
Using a Two-Factor Model of Returns for an Event
Study
390
14.6
Using
Exceľs
Offset Function to Locate a Regression in
a Data Set
394
14.7
Conclusion
396
Value at Risk
397
15.1
Overview
397
15.2
A Really Simple Example
397
15.3
Defining Quantiles in Excel
399
15.4
A Three-Asset Problem: The Importance of the
Variance-Covariance Matrix
402
15.5
Simulating Data
—
Bootstrapping
404
Appendix: How to Bootstrap: Making a Bingo Card in
Excel
409
Contents
Ш
Option-Pricing Models
419
16
An Introduction to Options
421
16.1
Overview
421
16.2
Basic Option Definitions and Terminology
421
16.3
Some Examples
424
16.4
Option Payoff and Profit Patterns
426
16.5
Option Strategies: Payoffs from Portfolios of Options
and Stocks
430
16.6
Option Arbitrage Propositions
432
16.7
Summary
439
Exercises
439
17
The Binomial Option-Pricing Model
443
17.1
Overview
443
17.2
Two-Date Binomial Pricing
443
17.3
State Prices
445
17.4
The Multiperiod Binomial Model
449
17.5
Pricing American Options Using the Binomial Pricing
Model
455
17.6
Programming the Binomial Option-Pricing Model in
VBA
458
17.7
Convergence of Binomial Pricing in the Black-Scholes
Price
463
17.8
Using the Binomial Model to Price Employee Stock
Options
466
17.9
Using the Binomial Model to Price
Nonstandard
Options: An Example
476
17.10
Summary
478
Exercises
478
18
The
Lognormal
Distribution
483
18.1
Overview
483
18.2
What Do Stock Prices Look Like?
484
18.3 Lognormal
Price Distributions and Geometric
Diffusions
492
18.4
What Does the
Lognormal
Distribution Look Like?
495
18.5
Simulating
Lognormal
Price Paths
498
xiv Contents
18.6 Technical
Analysis
502
18.7
Calculating the Parameters of the
Lognormal
Distribution from Stock Prices
503
18.8
Summary
505
Exercises
505
19
The Black-Scholes Model
509
19.1
Overview
509
19.2
The Black-Scholes Model
509
19.3
Using VBA to Define a Black-Scholes Pricing Function
511
19.4
Calculating the Implied Volatility
513
19.5
A VBA Function to Find the Implied Variance
517
19.6
Dividend Adjustments to the Black-Scholes
520
19.7
Using the Black-Scholes Formula to Price Structured
Securities
525
19.8
Bang for the Buck with Options
539
19.9
The Black
(1976)
Model for Bond Option Valuation
541
19.10
Summary
544
Exercises
544
20
Option Greeks
549
20.1
Overview
549
20.2
Defining and Computing the Greeks
550
20.3
Delta Hedging a Call
555
20.4
Hedging a Collar
564
20.5
Summary
574
Exercises
575
21
Portfolio Insurance
577
21.1
Overview
577
21.2
Portfolio Insurance on More Complicated Assets
578
21.3
An Example
580
21.4
Some Properties of Portfolio Insurance
584
21.5
What Do Portfolio Insurance Strategies Look Like?
A Simulation
585
21.6
Insuring Total Portfolio Returns
588
21.7
Implicit Puts and Asset Values
592
Contents
21.8
Summary
593
Exercises
594
An Introduction of Monte Carlo Methods
597
22.1
Overview
597
22.2
Computing
π
Using Monte Carlo
597
22.3
Writing a VBA Program
602
22.4
Another Monte Carlo Problem: Investment and
Retirement
604
22.5
A Monte Carlo Simulation of the Investment Problem
607
22.6
Summary
610
Exercises
610
Using Monte Carlo Methods for Option Pricing
613
23.1
Overview
613
23.2
State Prices, Probabilities, and Risk Neutrality
613
23.3
Pricing a Plain-Vanilla Call Using Monte Carlo
Methods
615
23.4
Monte Carlo Plain-Vanilla Call Pricing Converges to
Biack-Scholes
618
23.5
Pricing Asian Options
625
23.6
Pricing Asian Options with a VBA Program
633
23.7
Pricing Barrier Options with Monte Carlo
638
23.8
Using VBA and Monte Carlo to Price a Barrier
Option
642
23.9
Summary
646
Exercises
646
Real Options
649
24.1
Overview
649
24.2
A Simple Example of the Option to Expand
650
24.3
The Abandonment Option
653
24.4
Valuing the Abandonment Option as a Series of Puts
659
24.5
Valuing a Biotechnology Project
662
24.6
Conclusion
667
Exercises
667
xvi Contents
IV
25
26
27
Bonds
669
Duration
671
25.1
Overview
671
25.2
Two Examples
671
25.3
What Does Duration Mean?
674
25.4
Duration Patterns
678
25.5
The Duration of a Bond with Uneven Payments
679
25.6
Nonflat Term Structures and Duration
687
25.7
Summary
689
Exercises
689
Immunization Strategies
693
26.1
Overview
693
26.2
A Basic Simple Immunization Model
693
26.3
A Numerical Example
695
26.4
Convexity: A Continuation of Our Immunization
Experiment
698
26.5
Building a Better Mousetrap
700
26.6
Summary
704
Exercises
704
Modeling the Term Structure
705
27.1
Overview
705
27.2
An Initial Example
705
27.3
Description of the Data
710
27.4
The Treasury Yield Curve
713
27.5
Computing Par Yields from a Zero-Coupon Yield Curve
715
27.6
Summary
716
Exercises
717
28
Calculating Default-Adjusted Expected Bond Returns
719
28.1
Overview
719
28.2
Calculating the Expected Bond Return in a One-Period
Framework
721
28.3
Calculating the Expected Bond Return in a Multiperiod
Framework
722
28.4
A Numerical Example
726
Contents
28.5
Experimenting with the Example
728
28.6
Computing the Bond Expected Return for an Actual
Bond
730
28.7
Semiannual Transition Matrices
734
28.8
Computing Bond Beta
737
28.9
Summary
739
Exercises
740
Technical Considerations
743
Generating Random Numbers
745
29.1
Overview
745
29.2
Rand(
)
and Rnd: The Excel and VBA Random-Number
Generators
746
29.3
Testing Random-Number Generators
749
29.4
Generating Normally Distributed Random Numbers
754
29.5
Summary
762
Exercises
762
Data Tables
765
30.1
Overview
765
30.2
An Example
765
30.3
Setting Up a Data Table
766
30.4
Building a Two-Dimensional Data Table
768
30.5
An Aesthetic Note: Hiding the Formula Cells
769
30.6
Excel Data Tables Are Arrays
770
Exercises
771
Matrices
775
31.1
Overview
775
31.2
Matrix Operations
776
31.3
Matrix Inverses
779
31.4
Solving Systems of Simultaneous Linear Equations
781
Exercises
782
The Gauss-Seidel Method
785
32.1
Overview
785
32.2
A Simple Example
785
32.3
A More Concise Solution
786
Contents
32.4
Conclusion
787
Exercises
■ 787
Excel
Functions
789
33.1
Overview
789
33.2
Financial
Functions
789
33.3
Dates
and Date Functions
796
33.4
The Functions XIRR and XNPV
802
33.5
Statistical Functions
805
33.6
Doing Regressions with Excel
808
33.7
Conditional Functions
815
33.8
Large and Rank, Percentile, and Percentrank
816
33.9
Count, CountA, CountIF
817
33.10
Boolean Functions
819
33.11
Offset
821
Using Array Functions and Formulas
825
34.1
Overview
825
34.2
Some Built-in Array Functions
825
34.3
Homemade Array Functions
830
34.4
Array Formulas with Matrices
833
Exercises
838
Some Excel Hints
841
35.1
Overview
841
35.2
Fast Copy: Filling in Data Next to a Filled-in Column
841
35.3
Multiline Cells
843
35.4
Writing on Multiple Spreadsheets
845
35.5
Text Functions in Excel
847
35.6
Chart Titles That Update
847
35.7
Getformula: A Useful Way of Annotating Spreadsheets
850
35.8
Putting Greek Symbols in Cells
853
35.9
Superscripts and Subscripts
854
35.10
Named Cells
856
35.11
Hiding Cells
857
35.12
Formula Auditing
859
35.13
Formulating Millions as Thousands
861
xix Contents
VI
Introduction
to
Visual Basic for Applications
865
36
User-Defined Functions with
VBA
867
36.1
Overview
867
36.2
Using the
VBA
Editor to Build a User-Defined Function
867
36.3
Providing Help for the User-Defined Functions in the
Function Wizard
872
36.4
Fixing Mistakes in VBA
875
36.5
Conditional Execution: Using If Statements in VBA
Functions
877
36.6
The Select Case Statement
882
36.7
Using Excel Functions in VBA
884
36.8
Using User-Defined Functions in User-Defined
Functions
885
Exercises
888
Appendix: Cell Errors in Excel and VBA
892
37
Types and Loops
895
37.1
Overview
895
895
897
901
904
913
913
37.2
Using Types
37.3
Variables and Variable Types
37.4
Boolean and Comparison Operators
37.5
Loops
37.6
Summary
Exercises
Macros and User Interaction
38.1
Overview
38.2
Macro Subroutines
38.3
User Output and the MsgBox Function
38.4
User Input and the InputBox Function
38.5
Modules
38.6
Summary
38
Macros and User Interaction
919
919
919
926
930
932
935
Exercises
935
39
Arrays
941
39.1
Overview
941
39.2
Simple Arrays
941
Contents
41
39.3
Multidimensional Arrays
946
39.4
Dynamic Arrays and the ReDim Statement
948
39.5
Array Assignment
959
39.6
Variants Containing an Array
960
39.7
Arrays as Parameters to Functions
963
39.8
Summary
971
Exercises
971
Objects and Add-Ins
975
40.1
Overview
975
40.2
An Introduction to Worksheet Objects
975
40.3
The Range Object
979
40.4
The With Statement
984
40.5
Collections
985
40.6
Names
991
40.7
Using the Object Browser
995
40.8
References to External Functions in Excel
997
40.9
References to External Functions in VBA
999
40.10
Add-Ins and Integration
1008
40.11
Summary
1014
Exercises
1014
Appendix
1:
The Excel Object Model
1018
Appendix
2:
Extracts from the Help File for Some Methods
1020
Information from the Web
1029
41.1
Overview
1029
41.2
Copy and Paste as a Simple Data-Acquisition
Technique
1029
41.3
Dynamic Web Queries
1035
41.4
Web Queries: The iqy File
1041
41.5
Parametric Web Pages
1047
41.6
Web Queries: Parameters
1049
41.7
Web Queries: CSV Files and Postprocessing
1056
41.8
A VBA Application: Importing Price Data from Yahoo
1059
41.9
Summary
1089
Exercises
1089
xxi
Contents
Appendix 1:
Excerpts from the Help File
1090
Appendix
2:
The RlCl Reference Style
1093
References
1095
Index
1107
economics
Financial Modeling
third edition
Simon Benninga
Too often, finance courses stop short of making a connection
of real-world business. Financial Modeling bridges this gap
nuts-and-bolts guide to solving common financial
modějs
witjr
ѕргШаѕ1тШ|^
reader step by step through each model, showing how itcgn
Ľ-rí-
i^-i^vhek
The long-awaited third edition of this standard text
dependence that have made the first and second editions
і
with new chapters covering such topics as bank valuation,
mization, Monte Carlo methods and their appli
mulas.
Other chapters, including those on basic
variance-covariance matrix, and generating random
riunì
stantially new and improved material.; Other areas
standard portfolio problems, value at risk (VaR),
ré
modeling. Technical chapters treat such topicsas data
іфіШ;$ШШі&Е,
for using Excel. The last section of the text covers th|
for the book. The accompanying CD contains Excel
Simon Benninga is Professor of Finance at
Tę!
Wharton School at the University of
Pennşylvanid.
"I've learned a great deal from
thè;
first two ediKi
edition offers both new topics and updated cpyerdge'pl
well-illustrated instructions for using Excel
sophisticated, in both corporate finance and
і
pany
data, and the book gives useful tips
an outstanding resource for finance
keep my copy close at hand;"
;4;í
—Robert A. Taggarf, Professor of
"Financial Modeling by Simon
^nЫι^gaΐş:^:qÌ1■,òцťşte■rв.а.■;
w?
both undergraduates and master's; students.
Il·
is
Шшр|еКёА||й
financial modeler's toolkit.";
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| any_adam_object | 1 |
| any_adam_object_boolean | 1 |
| building | Verbundindex |
| bvnumber | BV023069296 |
| callnumber-first | H - Social Science |
| callnumber-label | HG173 |
| callnumber-raw | HG173 |
| callnumber-search | HG173 |
| callnumber-sort | HG 3173 |
| callnumber-subject | HG - Finance |
| classification_rvk | QP 700 QP 730 |
| classification_tum | WIR 680f |
| ctrlnum | (OCoLC)141383024 (DE-599)BVBBV023069296 |
| dewey-full | 332.01/5118 |
| dewey-hundreds | 300 - Social sciences |
| dewey-ones | 332 - Financial economics |
| dewey-raw | 332.01/5118 |
| dewey-search | 332.01/5118 |
| dewey-sort | 3332.01 45118 |
| dewey-tens | 330 - Economics |
| discipline | Wirtschaftswissenschaften |
| discipline_str_mv | Wirtschaftswissenschaften |
| edition | 3. ed. |
| format | Book |
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| id | DE-604.BV023069296 |
| illustrated | Illustrated |
| index_date | 2024-07-02T19:32:21Z |
| indexdate | 2024-07-09T21:10:17Z |
| institution | BVB |
| isbn | 9780262026284 |
| language | English |
| lccn | 2007038629 |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-016272459 |
| oclc_num | 141383024 |
| open_access_boolean | |
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| physical | XXVIII, 1133 S. Ill., graph. Darst. 1 CD-ROM (12 cm) |
| publishDate | 2008 |
| publishDateSearch | 2008 |
| publishDateSort | 2008 |
| publisher | MIT Press |
| record_format | marc |
| spelling | Financial modeling Simon Benninga. With a section on Visual Basic for Applications by Benjamin Czaczkes 3. ed. Cambridge, Mass. [u.a.] MIT Press 2008 XXVIII, 1133 S. Ill., graph. Darst. 1 CD-ROM (12 cm) txt rdacontent n rdamedia nc rdacarrier The third edition of this standard text retains the popular 'cookbook' features of the earlier editions and includes expanded and new coverage of such topics as bank valuation, the Black-Litterman portfolio selection model, Monte Carlo pricing methods, array function, and getting information from the Internet with VBA. Finances - Modèles mathématiques Mathematisches Modell Finance Mathematical models Mathematisches Modell (DE-588)4114528-8 gnd rswk-swf CD-ROM (DE-588)4139307-7 gnd rswk-swf Finanzierung (DE-588)4017182-6 gnd rswk-swf Finanzierung (DE-588)4017182-6 s Mathematisches Modell (DE-588)4114528-8 s CD-ROM (DE-588)4139307-7 s 1\p DE-604 Benninga, Simon Sonstige oth Czaczkes, Benjamin Sonstige oth Digitalisierung UB Passau application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=016272459&sequence=000003&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis Digitalisierung UB Passau application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=016272459&sequence=000004&line_number=0002&func_code=DB_RECORDS&service_type=MEDIA Klappentext 1\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk |
| spellingShingle | Financial modeling Finances - Modèles mathématiques Mathematisches Modell Finance Mathematical models Mathematisches Modell (DE-588)4114528-8 gnd CD-ROM (DE-588)4139307-7 gnd Finanzierung (DE-588)4017182-6 gnd |
| subject_GND | (DE-588)4114528-8 (DE-588)4139307-7 (DE-588)4017182-6 |
| title | Financial modeling |
| title_auth | Financial modeling |
| title_exact_search | Financial modeling |
| title_exact_search_txtP | Financial modeling |
| title_full | Financial modeling Simon Benninga. With a section on Visual Basic for Applications by Benjamin Czaczkes |
| title_fullStr | Financial modeling Simon Benninga. With a section on Visual Basic for Applications by Benjamin Czaczkes |
| title_full_unstemmed | Financial modeling Simon Benninga. With a section on Visual Basic for Applications by Benjamin Czaczkes |
| title_short | Financial modeling |
| title_sort | financial modeling |
| topic | Finances - Modèles mathématiques Mathematisches Modell Finance Mathematical models Mathematisches Modell (DE-588)4114528-8 gnd CD-ROM (DE-588)4139307-7 gnd Finanzierung (DE-588)4017182-6 gnd |
| topic_facet | Finances - Modèles mathématiques Mathematisches Modell Finance Mathematical models CD-ROM Finanzierung |
| url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=016272459&sequence=000003&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=016272459&sequence=000004&line_number=0002&func_code=DB_RECORDS&service_type=MEDIA |
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