Preface

For more than 20 years, since the emergence of PCs, Lotus 1-2-3, and Microsoft Excel in the 1980’s, spreadsheet models have been the dominant vehicles for finance professionals in the business world to implement their financial knowledge. Yet even today, most Fundamentals of Investments textbooks rely on calculators as the primary tool and have little coverage of how to build and estimate Excel models. This book fills that gap. It teaches students how to build and estimate financial models in Excel. It provides step-by-step instructions so that students can build and estimate models themselves (active learning), rather than being handed already completed spreadsheets (passive learning). It progresses from simple examples to practical, real-world applications. It spans nearly all quantitative models in the fundamentals of investments.

My goal is simply to change finance education from being calculator based to being Excel based. This change will better prepare students for the 21^st century business world. This change will increase student evaluations of teacher performance by enabling more practical, real-world content and by allowing a more hands-on, active learning pedagogy.

Third Edition Changes

New to this edition, the biggest innovation is Ready-To-Build Spreadsheets on the CD. The CD provides ready-to-build spreadsheets for every chapter with:

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

The Third Edition advances in many ways:

·         The new Ready-To-Build spreadsheets on the CD are very popular with students. They can open a spreadsheet that is set up and ready to be constructed. Then they can follow the on-spreadsheet instructions to complete the Excel model and don’t have to refer back to the book for each step. Once they are done, they can double-check their work against the completed spreadsheet shown in the book. This approach concentrates student time on implementing financial formulas and estimation.

·         There is great new fundamentals of investments content, including:

o   Estimating the Static CAPM using the Fama-MacBeth method,

o   Estimating the APT or Intertemporal CAPM using the Fama-MacBeth method, including the Fama-French three factor model,

o   Estimating portfolio optimization with constraints (i.e. no short-sales, no borrowing, etc.),

o   A trader simulation, which requires you to determine the optimal trading strategy for a variety of trading problems in a limit order book market,

o   A dealer simulation, which requires you to determine the optimal dealer strategy for a variety of dealer problems in a dealer market – both simulations use the Excel add-in @RISK,

o   The Cox-Ingersoll-Ross term structure model,

o   The Merton corporate bond model,

o   Valuing American options with discrete dividends,

o   Black-Scholes sensitivities (Greeks), and

o   Eleven varieties of exotic options.

·         There is a new chapter on useful Excel tricks.

·         The Ready-To-Build spreadsheets on CD and the explanations in the book are based on Excel 2007 by default. However, the CD also contains a folder with Ready-To-Build spreadsheets based on Excel 97-2003 format. Also, the book contains “Excel 2003 Equivalent” boxes that explain how to do the equivalent step in Excel 2003 and earlier versions.

·         The instruction boxes on the Ready-To-Build spreadsheets are bitmapped images so that the formulas cannot just be copied to the spreadsheet. Both the instruction boxes and arrows are objects, so that all of them can be deleted in one step when the spreadsheet is complete and everything else will be left untouched. Click on Home | Editing | Find & Select down-arrow | Select Objects, then select all of the instruction boxes and arrows, and press the delete key. Furthermore, any blank rows can be deleted, leaving a clean spreadsheet for future use.

·         The book contains a significant number of comparative statics exercises (lower risk aversion, higher short-rate, etc.) and explores a variety of optional choices (alternative models to forecast expected return, alternative spreads and combinations, etc.). In each case, a picture is show of how things change and there is a discussion of what this means in economic terms. For example, below is Figure 6.16 which explores what happens to the optimal portfolio when risk aversion is lowered?

FIGURE 6.16  Risk Aversion of 1.8 and 0.2

 

What Is Unique About This Book

There are many features which distinguish this book from any other:

·         Plain Vanilla Excel. Other books on the market emphasize teaching students programming using Visual Basic for Applications (VBA) or using macros. By contrast, this book does nearly everything in plain vanilla Excel.[1] Although programming is liked by a minority of students, it is seriously disliked by the majority. Plain vanilla Excel has the advantage of being a very intuitive, user-friendly environment that is accessible to all. It is fully capable of handling a wide range of applications, including quite sophisticated ones. Further, your students already know the basics of Excel and nothing more is assumed. Students are assumed to be able to enter formulas in a cell and to copy formulas from one cell to another. All other features of Excel (such as built-in functions, Data Tables, Solver, etc.) are explained as they are used.

·         Build From Simple Examples To Practical, Real-World Applications. The general approach is to start with a simple example and build up to a practical, real-world application. In many chapters, the previous Excel model is carried forward to the next more complex model. For example, the chapter on binomial option pricing carries forward Excel models as follows: (a.) single-period model with replicating portfolio, (b.) eight-period model with replicating portfolio, (c.) eight-period model with risk-neutral probabilities, (d.) eight-period model with risk-neutral probabilities for American or European options with discrete dividends, (e.) full-scale, fifty-period model with risk-neutral probabilities for American or European options with discrete dividends using continuous or discrete annualization convention. Whenever possible, this book builds up to full-scale, practical applications using real data. Students are excited to learn practical applications that they can actually use in their future jobs. Employers are excited to hire students with Excel modeling and estimation skills, who can be more productive faster.

·         Supplement For All Popular Fundamentals of Investments Textbooks. This book is a supplement to be combined with a primary textbook. This means that you can keep using whatever textbook you like best. You don’t have to switch. It also means that you can take an incremental approach to incorporating Excel modeling and estimation. You can start modestly and build up from there.

·         A Change In Content Too. Excel modeling and estimation is not merely a new medium, but an opportunity to cover some unique content items which require computer support to be feasible. For example, using 10 years of monthly returns for individual stocks, U.S. portfolios, and country portfolios to estimate the (unconstrained) Risky Opportunity Set and the (unconstrained) Complete Opportunity Set. The same data is used by Solver to numerically solver for the Constrained Risky Opportunity Set and the Constrained Complete Opportunity Set. The same data is used to estimate the Static CAPM using the Fama-MacBeth method and to estimate the APT or Intertemporal CAPM using the Fama-MacBeth method. A Trader Simulation in a limit order market and a Dealer Simulation in a dealer market make sophisticated use @RISK (an Excel Add-in) to simulate the arrival of orders and information. The Excel model in US Yield Curve Dynamics shows 37 years of monthly US yield curve history in just a few minutes. Real call and put prices are fed into the Black Scholes Option Pricing model and Excel’s Solver is used to back-solve for the implied volatilities. Then the “smile” pattern (or more like a “scowl” pattern) of implied volatilities is graphed. As a practical matter, all of these sophisticated applications require Excel.

Conventions Used In This Book

This book uses a number of conventions.

·         Time Goes Across The Columns And Variables Go Down The Rows. When something happens over time, I let each column represent a period of time. For example in life-cycle financial planning, date 0 is in column B, date 1 is in column C, date 2 is in column D, etc. Each row represents a different variable, which is usually a labeled in column A. This manner of organizing Excel models is so common because it is how financial statements are organized.

·         Color Coding. A standard color scheme is used to clarify the structure of the Excel models. The Ready-To-Build spreadsheets on CD uses: (1) yellow shading for input values, (2) no shading (i.e. white) for throughput formulas, and (3) green shading for final results ("the bottom line"). A few Excel models include choice variables. Choice variables use blue shading. The Constrained Portfolio Optimization spreadsheet includes constraints. Constaints use pink-purple shading.

·         The Time Line Technique. The most natural technique for discounting cash flows in an Excel model is the time line technique, where each column corresponds to a period of time. As an example, see the section labeled Calculate Bond Price using a Timeline in the figure below.

     

·         Using As Many Different Techniques As Possible. In the figure above, the bond price is calculated using as many different techniques as possible. Specifically, it is calculated three ways: (1) discounting each cash flow on a time line, (2) using the closed-form formula, and (3) using Excel’s PV function. This approach makes the point that all three techniques are equivalent. This approach also develops skill at double-checking these calculations, which is a very important method for avoiding errors in practice.

·         Symbolic Notation is Self-Contained. Every spreadsheet that contains symbolic notation in the instruction boxes is self-contained (i.e., all symbolic notation is defined on the spreadsheet). Further, I have stopped using symbolic notation for named ranges that was used in prior editions. Therefore, there is no need for alternative notation versions that were provided on the CD in the prior edition and they have been eliminated.

Craig’s Challenge

I challenge the readers of this book to dramatically improve your finance education by personally constructing all of the Excel models in this book. This will take you about 7 – 15 hours hours depending on your current Excel modeling skills. Let me assure you that it will be an excellent investment. You will: 

·         gain a practical understanding of the core concepts of Investments,

·         develop hands-on, Excel modeling skills, and

·         build an entire suite of finance applications, which you fully understand.

When you complete this challenge, I invite you to send an e-mail to me at cholden@indiana.edu to share the good news. Please tell me your name, school, (prospective) graduation year, and which Excel modeling book you completed. I will add you to a web-based honor roll at:   

                   http://www.excelmodeling.com/honor-roll.htm

We can celebrate together!

The Excel Modeling and Estimation Series

This book is part of a series on Excel Modeling and Estimation by Craig W. Holden, published by Pearson / Prentice Hall. The series includes:

·         Excel Modeling and Estimation in Corporate Finance,

·         Excel Modeling and Estimation in the Fundamentals of Corporate Finance,

·         Excel Modeling and Estimation in Investments, and

·         Excel Modeling and Estimation in the Fundamentals of Investments. 

Each book teaches value-added skills in constructing financial models in Excel. Complete information about the Excel Modeling and Estimation series is available at my web site:

http://www.excelmodeling.com

All of the Excel Modeling and Estimation books can be purchased any time at:

http://www.amazon.com

If you have any suggestions or corrections, please e-mail them to me at cholden@indiana.edu. I will consider your suggestions and will implement any corrections in the next edition.

This book provides educational examples of how to estimate financial models from real data. In doing so, this book uses a tiny amount of data that is copyrighted by others. I rely upon the fair use provision of law (Section 107 of the Copyright Act of 1976) as the legal and legitimate basis for doing so.[2]

Suggestions for Faculty Members

There is no single best way to use Excel Modeling and Estimation in the Fundamentals of Investments. There are as many different techniques as there are different styles and philosophies of teaching. You need to discover what works best for you. Let me highlight several possibilities:

1.      Out-of-class individual projects with help. This is a technique that I have used and it works well. I require completion of several short Excel modeling projects of every individual student in the class. To provide help, I schedule special “help lab” sessions in a computer lab during which time myself and my graduate assistant are available to answer questions while students do each assignment in about an hour. Typically about half the questions are Excel questions and half are finance questions. I have always graded such projects, but an alternative approach would be to treat them as ungraded homework.

2.      Out-of-class individual projects without help. Another technique is to assign Excel modeling projects for individual students to do on their own out of class. One instructor assigns seven Excel modeling projects at the beginning of the semester and has individual students turn in all seven completed Excel models for grading at the end of the semester. At the end of each chapter are problems that can be assigned with or without help. Faculty members can download the completed Excel models at http://www.prenhall.com/holden. See your local Pearson / Prentice Hall (or Pearson Education) representative to gain access.

3.      Out-of-class group projects. A technique that I have used for the last fifteen years is to require students to do big Excel modeling projects in groups. I have students write a report to a hypothetical boss, which intuitively explains their method of analysis, key assumptions, and key results.

4.      In-class reinforcement of key concepts. The class session is scheduled in a computer lab or equivalently students are required to bring their (required) laptop computers to a technology classroom, which has a data jack and a power outlet at every student station. I explain a key concept in words and equations. Then I turn to a 10-15 minute segment in which students open a Ready-To-Build spreadsheet and build the Excel model in real-time in the class. This provides real-time, hands-on reinforcement of a key concept. This technique can be done often throughout the semester.

5.      In-class demonstration of Excel modeling. The instructor can perform an in-class demonstration of how to build Excel models. Typically, only a small portion of the total Excel model would be demonstrated.

6.      In-class demonstration of key relationships using Spin Buttons, Option Buttons, and Charts. The instructor can dynamically illustrate comparative statics or dynamic properties over time using visual, interactive elements. For example, one spreadsheet provides a “movie” of 37 years of U.S. term structure dynamics. Another spreadsheet provides an interactive graph of the sensitivity of bond prices to changes in the coupon rate, yield-to-maturity, number of payments / year, and face value.

I’m sure I haven’t exhausted the list of potential teaching techniques. Feel free to send an e-mail to cholden@indiana.edu to let me know novel ways in which you use this book.

Acknowledgements

I thank Mark Pfaltzgraff, David Alexander, Jackie Aaron, P.J. Boardman, Mickey Cox, Maureen Riopelle, and Paul Donnelly of Pearson / Prentice Hall for their vision, innovativeness, and encouragement of Excel Modeling and Estimation in the Fundamentals of Investments. I thank Susan Abraham, Kate Murray, Lori Braumberger, Holly Brown, Debbie Clare, Cheryl Clayton, Kevin Hancock, Josh McClary, Bill Minic, Melanie Olsen, Beth Ann Romph, Erika Rusnak, Gladys Soto, and Lauren Tarino of Pearson / Prentice Hall for many useful contributions. I thank Professors Alan Bailey (University of Texas at San Antonio), Zvi Bodie (Boston University), Jack Francis (Baruch College), David Griswold (Boston University), Carl Hudson (Auburn University), Robert Kleiman (Oakland University), Mindy Nitkin (Simmons College), Steve Rich (Baylor University), Tim Smaby (Penn State University), Charles Trzcinka (Indiana University), Sorin Tuluca (Fairleigh Dickinson University), Marilyn Wiley (Florida Atlantic University), and Chad Zutter (University of Pittsburgh) for many thoughtful comments. I thank my graduate students Scott Marolf, Heath Eckert, Ryan Brewer, Ruslan Goyenko, Wendy Liu, and Wannie Park for careful error-checking. I thank Jim Finnegan and many other students for providing helpful comments. I thank my family, Kathryn, Diana, and Jimmy, for their love and support.

About The Author

CRAIG W. HOLDEN                

Craig Holden is the Max Barney Faculty Fellow and Associate Professor of Finance at the Kelley School of Business at Indiana University. His M.B.A. and Ph.D. are from the Anderson School at UCLA. He is the winner of many teaching and research awards. His research on security trading and market making (“market microstructure”) has been published in leading academic journals. He has written four books on Excel Modeling and Estimation in finance, which are published by Pearson / Prentice Hall and Chinese editions are published by China Renmin University Press. He has chaired sixteen dissertations, been a member or chair of 46 dissertations, served on the program committee of the Western Finance Association for nine years, and served as an associate editor of the Journal of Financial Markets for eleven years. He chaired the department undergraduate committee for eleven years, chaired three different schoolwide committees over six years, and is currently chairing the department doctoral committee. He has lead several major curriculum innovations in the finance department. More information is available at Craig’s home page:  www.kelley.iu.edu/cholden.