Search for question
Question

The University of Manchester BMAN23000 Foundations of Finance Semester 2, 2023-2024 Group-based assignment Please Read This Document Carefully This document describes the coursework component for BMAN23000 which counts for 20% of the final mark for the course. You are required to complete this coursework in groups. You will be randomly allocated to a coursework group of approximately 6 students in the same workshop. Details of coursework groups and companies allocated to each coursework group will be available on Blackboard (in a file called Group and Company Allocation) by the start of Week 4. Details of the assignment are given below. The assignment will be discussed in detail in Workshop 1 in Week 4. Table of Contents 1 Assignment... 2 1.1 Part 1 2 1.2 Part 2 3 2 Collecting data 4 2.1 Equity data. 4 2.2 Debt data. 5 2.3 Estimating equity betas. 6 3 Report requirements. 7 4 Submitting the Coursework 7 5 The Groups.. 8 5.1 5.2 Simple ground rules for group work. Required (for the individual part) 8 9 6 How Do I Assess Performance?. 10 6.1 Some Words of Warning 10 6.2 Suggested Criteria.…………………….. 10 6.3 Free Rider Problems 10 6.4 How are the individual contribution marks used? 10 6.5 Assessment 11 7 Blackboard forum 11 8 Suggested readings 11 1 1 Assignment Each coursework group will be allocated two real-life companies that are publicly traded on a U.S. stock market. To find out the names of your group's two companies, please visit the BMAN23000 Blackboard site: the names of the companies allocated to each coursework group, and the names of the students allocated to each coursework group, are given in the Group and Company Allocation file available from the BMAN23000 Blackboard site at the start of week 4. The file indicates which of the two real-life companies you should treat as "Company A” and which as “Company B”. Besides the company names, the Group and Company Allocation file also provides the companies' identifiers: their PERMNO and GVKEY; these identifiers are used to collect company data from the databases as described below. No further data (besides that in the Group and Company Allocation file) is provided. It is the responsibility of each team (and all team members) to collect all necessary data required to complete the assignment. Suitable databases are available and described below. The Group and Company Allocation file will also include the email addresses of the team member. Get in touch with your group members as soon as possible, set up a meeting to get to know each other and start working on the assignment. 1.1 Part 1 To complete this part, you will require data on your two companies' monthly common- stock returns from January 2013 to December 2022. If one of your companies ceases trading before December 2022, use however many stock returns are available during this 10-year window. Required tasks: (a) Suppose you are advising an investor who is considering investing all his/her wealth in the stock of just one of the two companies allocated to your coursework group (Company A or Company B). (i) Provide brief descriptions of Company A and of Company B. (ii) Next, compare and contrast the stock return performance of the two companies' common stocks over the calendar period using monthly return data from January 2013 to December 2022. Specifically, calculate the mean, variance and standard deviation of the monthly returns of the two stocks separately. (iii) Briefly comment on your results and make a stock recommendation. (b) Now suppose you are advising an investor who is considering investing all his/her wealth in a portfolio consisting of the two companies' common stock held together. (i) Calculate the mean, variance and standard deviation of the returns of portfolio comprising the two stocks with equal weights (i.e. 50:50). Next repeat the calculations for alternative portfolio weights, including 10:90, 20:80, 40:60, 60:40, 80:20, and 90:10. You may choose to construct additional portfolios (but remember the portfolio weights need to add to 100%). Report your results in a table. Compare and contrast your findings with those of the single-stock portfolios in part (aii). (ii) Illustrate your results in part (bi), along with the single-stock results in part (aii), 2 in a graph plotting the trade-off between the mean and standard deviation of the portfolio returns. (iii) In the trade-off graph in part (ii), indicate the efficient frontier (assuming the stocks of Company A and B are the only available assets). (iv) Finally, identify the minimum variance portfolio in the tradeoff graph. To do so, you can use trial and error, or the method outlined by Copeland, Weston and Shastri (Financial Theory and Corporate Policy, 4th International Edition, pp116-7; a copy of the relevant pages will be on the BMAN23000 Blackboard site). Report the portfolio weights of the minimum-variance portfolio, and the mean, variance and standard deviation of returns of the minimum-variance portfolio. (v) Based on your findings in the previous parts, briefly explain to the investor how to choose his/her optimal portfolio assuming the two stocks are the only assets available to him/her. Also briefly indicate how your advice would change if other assets became available to the investor. 1.2 Part 2 The senior management of Company A employs you to advise them on the cost of capital the company should use to calculate the net present value and decide whether or not to undertake a new investment project. You may assume that the new project is comparable to the average of the company's existing projects in all respects. Make sure you correctly identify which of your two companies is “Company A”. Note also that you were allocated randomly drawn and randomly paired companies. Therefore, Company B is probably not a useful comparable for Company A's new project. Required tasks: When you answer each of the below sections (a), (b), and (c), clearly explain your data sources, calculations and methods. Among other things, note explicitly whether your results are in terms of monthly or yearly returns (either or both are acceptable as long as clearly labelled). Briefly describe and justify the data and (proxy) measures you are using. State and discuss any assumptions you are making (including assumptions about the financing of the project). (a) Calculate investors' required returns on Company's A's equity. Remember, there are many ways of estimating investors' required returns (see Capital Budgeting Risk, Semester 1). You should use two alternative ways of calculating the required returns to check how sensitive your result is to using different methods; i.e. to check the robustness of your result. For example, you could use the Fama-French three-factor model in addition to the Security Market Line (SML), which uses a single factor (beta). See e.g. the article by Fama and French (1997) in the suggested readings below. The section Equity data below provides more information. (b) Calculate Company's A's debt cost of capital. The bond yield can be calculated as Yield = risk-free rate + credit spread. Data on the approximate credit spread for a given credit rating is provided in the section on Debt data below. For simplicity, you may assume that the only securities outstanding of the 3 company are common stock (equity) and long-term debt. Note that the after-tax cost of debt is lower than the pre-tax cost of debt if there is a tax advantage of debt relative to equity (interest tax shield). (c) Calculate the cost of capital (that is, the appropriate discount rate to calculate the net present value) of Company A's new investment project. (d) Briefly discuss any limitations of your analysis and how (given more time and information) you might refine your analysis in the future. 2 Collecting data To complete the assignment, your group will need to collect various sorts of data which can be downloaded from the Wharton Research Data Services (WRDS) website, https://wrds-www.wharton.upenn.edu/ The details on how to access WRDS and how to download the data you need for the coursework will also be explained in Workshop 1 video, which will be uploaded onto Blackboard. To sign in on WRDS, use the following confidential log-in details. username: bm232023 password: coursework2024 Note the use of capitals and lower-case letters. You are not allowed to pass on the log-in details to anyone else. By logging into WRDS, you are accepting their terms and conditions of data usage. To get accustomed to downloading data, log onto WRDS database. If you first prefer to have an introduction first, click on the "Classroom" tab at the top. This will allow you to go through "INTRO TO WRDS". If you click on the tab “Get Data” and then click on “All Data”, this will take you to a screen with different sets of data sources. Most of the data you need will be on the CRSP data set, the COMPUSTAT-Capital IQ "North America - Daily” data set, and the Fama- French Portfolios and Factors → “Factors - Monthly Frequency". Please note the terms and conditions for use of the WRDS data, which you automatically accept by accessing WRDS. You are only allowed to download data for the use of this coursework and you must not share or distribute the data to anyone except when submitting this coursework on Blackboard. 2.1 Equity data Download the equity return data from the CRSP database. After signing in on WRDS, scroll down to the "Subscriptions" section and click on “CRSP”. In the “Annual Update" section, click on “Stock / Security Files” then “Stock Market Indices" for market returns and "Monthly Stock File" for stock returns. Always search by the PERMNO identifier when downloading data on your company from the CRSP data set. The PERMNO of each of your two companies is given in the Group and Company Allocation file. You will need to download the monthly Holding Period Return. Holding period returns are defined as follows: 4 rit Pit +dit Pit-1 where rit is the holding period return for company i for month t, pit is the price of company i at the end of month t, dit is any dividend declared ex div during month t adjusted to an end- of-month basis, and pit-1 is the price of company i at the start of month t (adjusted if necessary for any changes in capitalizations to make it comparable with pit). If you want to express returns in percent (%) you have to multiply the equation for the (decimal) holding return above by 100. Make sure you convert returns collected from different data sources to the same units (decimals or percent). In your baseline calculations use monthly return data from Jan 2013 to Dec 2022. To get the market value of equity (market capitalization) at fiscal year end, you need to go to the database “Compustat - Capital IQ”. Follow the steps above but instead of clicking on "CRSP", search for “Compustat” and click on “Compustat - Capital IQ” → "North America - Daily” → “Fundamentals Annual". Choose the correct date range, ignore the "Screening Variables” and “Variable Types”. The market capitalization at fiscal year end can be calculated by multiplying the number of shares outstanding (csho) by the price of the shares at fiscal year end (prcc_f). To identify your company in Compustat, use the company's GVKEY (not its PERMNO). The Fama & French factor model data can be retrieved as follows. In the “Subscriptions" section of the WRDS entry page, click on "Fama-French Portfolios” → “Factors Monthly Frequency". From the Fama-French data set, you can download the excess returns on the market (rm — rf), the Fama-French factors, and the risk-free rate (rƒ). - 2.2 Debt data The data on debt and credit ratings (if available for your company) can also be downloaded from COMPUSTAT-Capital IQ. Please follow the steps explained above for the market value of equity to access the Compustat “North America – Daily” dataset. Within “North America - Daily”, you will find the Fundamentals Annual file and the Ratings file, which are explained in more detail below. - -- Fundamentals Annual: As explained above, choose the correct date range, enter the GVKEY of your company and leave everything else unchanged. Scroll down to the window that allows you to select the variables. Within the window, press Ctrl and F on your keyboard simultaneously and search for the variable DLTT Long Term Debt Total; tick this variable and submit your query to download the data. For simplicity, you may assume that long term debt – total is equivalent to the market value of debt for your company. It is important to note the units of each variable. For example, long term debt and the number of shares outstanding (csho) are in Millions (because it is Compustat data); by contrast, data on shares outstanding in CRSP (shrout) is often in Thousands. You can find out about the units by clicking on the round blue question mark button next to the variable in the variable selection window. Ratings: Within “North-America - Daily" in the left panel further down, there is the Ratings dataset. As explained above, choose the correct date range, enter the GVKEY of your company. Under Step 3, choose the variable SPLTICRM-S&P Domestic Long Term Issuer Credit Rating. The ratings data are only available until 2017. 5