Strengthening Essential Skills Through a Finance Exercise: Calculation of Beta Developments in Business Simulation and Experiential Learning, Volume 26, 1999 STRENGTHENING ESSENTIAL SKILLS THROUGH A FINANCE EXERCISE: CALCULATION OF BETA S. Christoffersen, Philadelphia College of Textiles and Science ABSTRACT An exercise for an introductory finance class is described. Although the assignment is to calcu- late the beta coefficient and the Capital Asset Pricing Model, the goals of the assignment are more far reaching. In addition to learning finan- cial concepts, the exercise strengthens essential writing skills, computer competency and quanti- tative skills. INTRODUCTION Although college students take courses in com- puter, communication and analytical skills, the business community decries the dearth of func- tional literacy in college graduates, Rubenstein (1998). The problem goes beyond course content and delivery; these fundamental skills must be reinforced throughout the curriculum. Advocates of “writing across the curriculum” urge us to not blame the Freshman English teachers for our students’ poor writing skills. Rather, incorporate language skills throughout the curriculum and clear writing will take on im- portance; good grammar will be more than a workbook assignment. Similar arguments can be expected from introductory computer instructors. If students are to graduate with appropriate pro- fessional competencies, professors must use the essential skills introduced in other classes. This requires careful sequencing of courses and pre- requisites, which is beyond the scope of this pa- per. Rather, this paper provides a multi-objective exercise for use in an introductory level finance class to strengthen computer, written and ana- lytical skills while teaching the financial con- cepts. OBJECTIVES This exercise requires students to use algebra, graphing, statistics, grammar, presentation skills, software and the Internet. The financial concepts include: stock market indices, rates of return, beta coefficient, the capital asset pricing model, annual percentage rate, effective annual rate, and sensitivity analysis. The exercise demands active participation on the part of the student and pa- tience on the part of the professor but the “ah- ha” factor (an indicator of comprehension rec- ommended by the Nobel Laureate, Fritz Machlup) makes the exercise worth the effort. PREPARATION Two assignments precede this exercise, one to establish the level of writing competency re- quired and the second to refresh Excel skills. The first assignment requires a literature search on an assigned topic and a concise summary and analy- sis of a relevant article. The difference between analysis and summary is clarified along with ap- propriate writing practice. This establishes a lan- guage arts benchmark while exercising their brains. The second case is a very simple Excel exercise. The students download a data set from my web- site, use cell addresses to create and copy simple formulae, and graph a data series. Once the level of acceptable writing is established and the spreadsheet refresher completed; students are ready for the “beta case”. THE “BETA CASE” The students each choose a stock listed on the NYSE and obtain pricing information for this 196 Developments in Business Simulation and Experiential Learning, Volume 26, 1999 stock, as well as the relevant stock market index, from the Internet. They then download the data into an Excel spreadsheet. The students enter formulas to calculate rates of return for the stocks as well as for the stock market index. Per- forming regression analyses on these returns, the students calculate the Beta coefficient for their stocks. The students then graph the resulting rates of return and regression lines. The students estimate the other parameters of the Capital Asset Pricing Model (CAPM), and with the calculated Beta coefficient, find the required rate of return for the chosen stock. The required rate of return is then compared to the expected rate of return. For these calculations, the students must convert the weekly rates of return to annual figures using either the formula for Effective Annual Returns or Annual Percentage Rates (APR). Finally, sensitivity analysis of the capital asset pricing model shows how sensitive the cal- culation of the required return is to various as- sumptions regarding inflation and market risk premiums. This could also be graphed. The write-up requires that students demonstrate an understanding of the data analysis and the use of such analysis in financial decision making. Equipment permitting, students present brief PowerPoint demonstrations where counter- cyclical stocks and high/low beta’s can be com- pared and the associated firm discussed. RESULTS For the students: Remarkably, not every college student uses the Internet. Those who are Internet-wary will dis- cover its usefulness when faced with the alterna- tive of searching the library shelves and entering weekly prices and indices covering three to five years into a spreadsheet. Finding the data on the Internet introduces the student to downloading which is generally quick and easy. Embedding the formulas, performing the regres- sion analysis, and creating the graph develop the student’s ability to use Excel as a powerful tool. In the introductory computer class, one often can not exploit Excel’s power to this extent. This ex- ercise requires students to develop some facility on their own. Those students unfamiliar with sta- tistics can easily handle regression analysis and others generally gain a new appreciation for the material that they learned in their statistics course. Although the book and professor discuss rates of return endlessly (seemingly), it is surprising how few students immediately grasp the meaning of (P1 - P 0 ) / P 0. Using actual prices to calculate a rate of return makes this key concept very clear. The size of the data raises protests; “Do I need three years worth of prices? Five?” These ques- tions lead to a useful discussion of the relevance of the past for predicting the future. Selecting an index makes the differences between indices relevant. Dealing with actual data prompts the student to initiate meaningful discussions, which is a far more effective pedagogy than lecturing. Much of the write-up concerns the beta coeffi- cient, specifically what it reveals about the na- ture of the stock (and firm) under analysis with regard to risk. Substitution into the capital asset market then demonstrates the usefulness of beta for decision-making. Comparing our calculated required return to the expected return leads into an understanding of how one forms expectations. The ensuing discussion highlights the differences between the Effective Annual Rate of return and APR that is more memorable than the exercises from the text on these calculations. Students generally under-estimate the task of do- ing the write up. Here clumsy language and tor- tuous phraseology are clear indicators of non- comprehension. Clarity of expression is the main criteria for grading. In the classroom presenta- tions, the explanations are quite indicative of whether the student only figured out which key to punch or actually “got it”. 197 Developments in Business Simulation and Experiential Learning, Volume 26, 1999 For the professor: As a finance professor, does the use of this case mean the professor must teach a spreadsheet program, Internet access and verb conjugation in addition to an ambitious finance syllabus? Theo- retically, the answer is no. There are learning support centers on campus for writing and com- puter lab assistants for computer assistance. The professor need only establish the requirement that students be competent in the skills that oth- ers will have taught in the earlier classes. This entails sequencing courses and appropriate pre- requisites. Scheduling can become tricky for freshman classes but upper level classes ought to be able to require freshman level competence in English and successful completion of an intro- ductory computer class. In reality, more work does fall on the professor’s shoulders. The students may have taken English classes but one still needs to explain why the pa- per is rejected, i.e. what is redundancy and how does one write in the present tense. According to complaints from various students (in panics in- duced by computer illiteracy), computer lab as- sistants are apparently chosen from the most un- pleasant, incompetent creatures on campus. One should not have to “waste” time explaining graphing, regression analysis and (P1 - P 0 ) / P 0 but expect this. The time is not really wasted if by using these constructs they achieve relevance and, once grasped, are not easily forgotten. TIMING Deadlines must be flexible to allow for students who have trouble finding or downloading data, as well as network problems originating with the University. The plethora of problems is unimag- inable, including diskettes that have been sat on, or otherwise lost, and system crashes. Due to the numerous difficulties, I assign “should” and “must” deadlines, i.e. you should have your data by Wednesday, if you have a problem, tell me Wednesday; you must have it by Friday. Using this data, you should have rates of return by Monday, you must have them by Wednesday. I break down the tasks into these assignments: 1. Download data 2. Calculate rates of return 3. Calculate beta coefficient 4. Graph regression line and rates of return 5. Write-up The total time requirement is probably two hours if you know what you are doing. I allow two weeks to complete the first four steps and require the paper in the third week. If students fall be- hind, it is difficult to catch up independently, as they can’t grasp the regression work if they aren’t clear on the rates of return. Thus the in- cremental steps seem necessary, at least for the weaker students. Thus this exercise does not re- place the regular homework assignments but are additional. CONCLUSIONS Although the Capital Asset Pricing Model is only briefly treated in the text, it is used here as a focal point due to the linkage of many aspects of finance as well as the incorporation of various and sundry skills. One advantage is that it builds on fundamentals such as calculating rates of re- turn. Do not assume that the students can do this just because they have been reading about rates and doing calculations with them the entire se- mester. The exercise progresses from simple to sophisti- cated concepts and these are now comprehended rather than memorized. A lot of grumbling ac- companies the beginning of the project but once results start to emerge the students relent and admit that the work can be rewarding. The student assignment for this case follows. Use it with the author’s blessings but please send notification of its use and any feedback or sug- gestions. 198 Developments in Business Simulation and Experiential Learning, Volume 26, 1999 CASE #3 Data: Using the Internet, obtain pricing information for any stock of your choosing that is listed on the New York Stock Exchange (NYSE). Record closing prices for the end of the week for at least a three-year period. This should give you about 156 data points. If there is a holiday, use the closing price for the previous day; do not enter zero. An easily accessible site is http://investor.msn.com. Also download the ap- propriate stock market index for the same time frame. An alternative for those who are absolutely un- able to use the Internet is to visit the Reference section of the library and use the Standard and Poor’s (S&P) Daily Price Quotations for the New York Stock Exchange. This will involve a significant amount of data entry (over 300 4- digit numbers) from 12 different volumes. Note that prices are recorded as fractions of a dollar, not dollars and cents. Thus you must convert the fraction (in eighths) to decimals (cents). For ex- ample, if the price is 10-02, this means ten dol- lars and two eighths, which should be converted to $10.25. Use the S&P Composite Index for the measure of the Market’s overall performance. This can be found in the front of the book of price quotations. Analysis: Calculate the rates of return for your stock and for the market index. Using these rates of return calculate the Beta co- efficient for your stock by regressing the stock’s return on the market’s performance. This can be done in an Excel worksheet, using the Tools menu, under Data Analysis (Regression) OR us- ing the function wizard, and specifying the statis- tical function: slope. Create a scatter graph of rates of return, with the Market rates of return on the X-axis and the Stock’s rate of return on the Y-axis, as shown in the textbook. Reference the textbook appendix for chapter five, pg. 222, Weston, Besley and Brigham (1996). Write-up: • Explain the key concepts: rate of return and Beta coefficient. • Report your results and explain their implica- tions. Attach your data sets as well as the scatter diagram. • What is the required rate of return for your stock? Explain the parameters used in your calculations. • Given the required rate of return, recommend a buy/sell decision for an investor and ex- plain the basis for your recommendation. • Using sensitivity analysis, determine the sen- sitivity of your required return to changes in risk-aversion and then to changes in T-bill rates. Please use correct grammar and spelling. Organ- ize your presentation and proof read your paper. It should be about one page in length. Presentation: Prepare either PowerPoint slides or overhead projection transparencies to briefly explain your results to the class. REFERENCES Rubenstein, E. S. (1998). The College Payoff Illusion. American Outlook, Fall, 14-18. Weston, J.F., Besley, S. & Brigham, E.F. (1996). Essentials of Managerial Finance., 11th Edi- tion, Fort Worth, TX: Dryden Press. 199 http://investor.msn.com/ Table of Contents Volume 26, 1999 ABSEL's Historical Research Interests Back From the Future: An ABSEL Merlin Exercise for the Year 2005 The Contributions of ABSEL During the 1980's ABSEL's Contributions to Experiential Exercises in the 90's ABSEL's Contributions to Experiential learning/Experiential Exercises: The Decade of the 1970's Business Simulations - Algorithms and Model Enhancements: A 25 year Review A Study of the ETS General Field Test as an AACSB Assessment Tool and the Impact of Experiential Exercises and Simulation on Learning A Framework for Assessing the Competencies Reflected in Simulation Performance Developing A Learning Culture: Assessing Changes in Student Performance and Perception Financial Simulation Using Distributed Computing Technology Analyzing Managers' Judgements and Decisions with an Educational Business Simulation Understanding Your Business through Home-Made Simulator Development An Examination of a Reanalysis of the Impact of a Market Leader on Simulation Competitors' Strategies Applying Shocks to TE Simulations: A Demonstration Increasing Efficiency of Management Skill Assessment A Testbank for Measuring Total Enterprise Simulation Learning Developing Leadership Skills - Video Live! LEADSIMM: Collaborative Leadership Development for the Knowledge Society A Team Approach to Producing Multi-Media Laptop and Video Formatted Presentation Tinkertoys Revisited: Exploring Trust Based Relationships Overall Dominance in Total Enterprise Simulation Performance Success or Bankruptcy: The Relationship between Personal and Goal Orientation and Simulation Performance Assessing the Effects of Feedback: Muti-method and Muti-directions in Multi-pedagogical Courses The Missing Ingredients in Experiential Learning Purpose and Learning Benefits of Business Simulations: A Design and Development Perspective Building Capabilities for Change through Laboratory Simulations Modeling Innovation as a Process of Design in Educational Business Simulation The Need to Measurer variance in Experiential Learning and a New Statistic to do so Assessing Effectiveness of an Experiential Oriented Course Over Time Developing Participant Satisfaction Models of Experiential Exercises in Business Education Perceptions of Learning in TE Simulations Students' View on the Use of Business Gaming in Hong Kong Management Gaming's Lost Opportunity: Meditations about the Russian Experience and Prospects for the Future Unanticipated Enhancements in the Business Strategy and Policy Game when Running in Windows 95 Using a Business Game to Demonstrate Broad Business Concepts A New Model for Business Courses (Getting the Student Connected) Seeing the Forest and the Trees: Integrating Knowledge Using Large Scale Simulations in Capstone Business Strategy Classes Is It Here To Stay? A Roundtable Discussion of the Inter-Group Interaction Interactive Tools Used in Applying Financial Concepts Strengthening Essential Skills through a Finance Exercise: Calculation of Beta A Model of Currency Exchange Rates Understanding Currency Exchange Rates: A three-part Exercise Student Experiences in the World Intercollegiate Business Game Competition Student Experiences in the International-Collegiate Business Policy Game Competition Using Boards of Directors in Simulation Environments: Comments From Board Members Sharing Best Practices: Teaching Smarter, Not Harder Star Power: A Simulation for Understanding Power and Empowerment The Marketing Game: A Marketing Principles Simulation Alexander Islands: GSSM Tiny Business Simulator on the WWW Putting Strategy into Strategic Business Games Industry Analysis, Porter's Five Forces Model and Strategic Group Maps in the Business Strategy Game Simulation The Use of Concept Mapping to Improve Student Performance and Understanding of Strategic Management Concepts: A Comparison of Techniques Transformational thinking in the Organizational Behavior Course: The Use of Metaphor as an Assessment Tool Creation of a Virtual Learning Community for the Global Virtual Enterprise Project Inter Institutional use of Educational Resources: Joint Use of Management Simulation Games Business Insights: Theory and Practice with the Aid of a Business Simulation Progress: An Experiential Exercise in Development Marketing The ABC's of teaching the Theory of Constraints to Undergraduate Business Students Demonstrating Principles of Organizational Purchasing Behavior through an Experiential Exercise The Virtual Manager: A Different Simulation for Managing Complexity When the Rules are changing and Chaos Breeds Innovation: Recapturing the Value of Constructive Thinking and Play in Simulation Training The Pitfalls, and Potential, of Actual Events as Problem Drivers Using Business Games to teach Environmental Awareness and Green Management: The International Experience with the ENSIM Game A Review of my ABSEL-Related Work Simulation of Government: A Workshop Using GEO Creating Internet-Based Games Using Perl and JavaScript Who's on First? Exploring the Concepts of Problem-Based Learning, Experiential Learning, and Lifelong Learning Students Learn Customer Service and Selling while Conducting Research So You Want to Run an NFL Football Team–An Honors Interdisciplinary Project Supervised Internship: The Employer's Perspective Using Computer Assisted Simulation to Teach International Business Strategy: A Case of the Multinational Management Game (MMG) Multi-Cultural Experiential Learning: A Computer Simulation in China An Appreciative Stance on Diversity as We Move into the 21st Century: A Timeline Exercise to Identify Key Experiences in Good Work Relationships between Black and White Peers A Day in the Life of an Interactive, Real Time, and Internet Delivered Course: A Demonstration Comparing Internet Search Engines: An Experiential Learning Exercise Total Enterprise Simulations and the Internet: Assessing Student Perceptions and Preferences Teaching Accounting Information Systems in a Practicum Format Providing Experiential Learning in Accounting through a Field Study Payroll Project A Spreadsheet Based Business Simulation Game Computer-Behavioral Simulations Training for Project Managers Simulation Scenarios - Rationale and Illustration