AcF606 Lent Term 2020 Workshop 5: Valuation by the multiple method: Large sample analysis Due: Case Workshop 5 Submission of preparatory work: One mark per submission (up to the maximum 4 marks), provided that you (i) submit the work on Moodle before the start of the earlier workshop of the week (even if you are assigned to a later one); and (ii) have made genuine effort (regardless whether you get correct answers or not). • If you have submitted the four cases already, you have reached the maximum of 4 marks, and this submission would not earn you extra marks. • If you do not feel proficient in programming STATA at this moment, you may describe what each set of codes is meant to achieve. For this workshop, please use the STATA codes and datasets posted on Moodle. Requirements: 1. Selectively read the paper “Who is My Peer? A Valuation-Based Approach to the Selection of Comparable Firms” by Bhojraj and Lee (2002). The link (also on the module reading list) is: https://doi-org.ezproxy.lancs.ac.uk/10.1111/1475- 679X.00054 Using your own, nontechnical words, briefly answer: (i) What is the paper’s research question? Why is it important? (ii) What is the main idea for the proposed “warranted multiple” method? (iii) What are the main steps of the research design? 2. The STATA do-file “CW5_Q2.do” contains the programming codes. Run them with the dataset “CW5_Q2.dta”. Briefly discuss: (i) What are the main challenges in operationalizing the research design steps outlined in Question 1? (ii) How do you interpret the results? 3. Use one of the discounted models from Lectures 8-9 to derive the theoretical determinants of the multiple EV/EBITDA1 (i.e., one-year-ahead forecasted EBITDA1). Hint: For this question, you may treat EBITDA as if it were free cash flow or operating income. 4. Describe the research design to test the effectiveness of selecting comparable firms based on the “warranted EV/EBITDA1” (“WEVE1”). The benchmark is the method of selecting comparables from the same industry. 5. The dataset “CW5_Q5.dta” contains the following variables: AcF606 Lent Term 2020 Variable Explanation (same as those in the original paper, except EVE1 and IndEVE1) GVKEY Firm ID FYEAR Fiscal year, time ID SIC2 Industry ID EVE1 The multiple of EV/EBITDA1, for individual firms IndEVE1 Harmonic mean of EVE1 in an industry (similar to IndEVS in the original paper) IndPB Industry harmonic mean of PB AdjPM Difference between the firm’s and the industry’s operating profit margins LossPM AdjPM times an indicator variable, where the indicator variable is 1 if profit margin≤0 and 0 otherwise AdjGro Difference between analyst consensus forecast of the firm’s long-term growth and the industry average Lev Total long-term debt scaled by book value of ordinary equity RNOA Operating profit scaled by net operating assets RD The firm’s R&D expressed as a percentage of net sales. Use this dataset to execute the research design in the preceding question. Hint: The dataset has four years, so you will implement the warranted multiple method three times (each time utilizes two year’s data). Make necessary changes to the STATA codes from Question 2, which in its current form doesn’t allow for multiple-year implementations.
