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9 Relative Valuation Analysis of Facebook (FB) (all figures in millions, except per share data) Begin by Assuring Data Integrity Data Integrity requires validating the soundness and completeness of the data. (1) Use the data below to calculate the Market Value of each company below in Row 28. (2) Use the Market Value to calculate the Enterprise Value in Row 31. If you cannot remember the formulas for these calculations, refer to the tutorial in the prior Sheet (VALUATION Relative). You may notice the large differential between the GAAP and Non-GAAP EPS forecasts for many of these companies. Even more interesting, many publishing analysts forecast Non-GAAP EPS for 2022E and beyond as these are the figures they rely on for their valuation work. In the case of Alphabet (GOOGL), the primary difference between GAAP and Non-GAAP EPS is stock-based compensation. Analysts rarely forecast one-time items unless they are previously announced by the company (such as a write-off or legal expense). Define the 'Comps' and Calculate the Selected 'Comps' Average Multiples (1) Calculate the multiples in rows 67 to 70 for columns G to N. (2) In row 73, enter TRUE if the company is a comparable with FB and FALSE if not. Hint: There are two companies that are not strong comparables for Facebook. (3) In row 74, enter TRUE if any of the multples you calculated in Step (1) are NOT anomolous, and enter FALSE if the mulitple is anomolous. Hint: In Part I Review (Workbook 1), we discussed Data Integrity and the challenges of encountering erroneous, outlier and irregular data. Your goal is to determine if any of the companies below should be eliminated from the potential 'comp' group because the data is anomolous. In Strategic Forecasting (Workbook 9), we removed an outlier and saw a significant improvement in the relationship between capacity utilization and profitability. In this exercise, you are doing something similar and 'scrubbing' the data to remove outliers that are anomalous. Hint: Look at the TRUE and FALSE in row 75 and confirm you used the correct logic. Do your answers make sense? (5) In column P, calculate the average multiples for the Selected 'Comps' for rows 67 to 70. Hint: Use the AVERAGEIF function to make sure you only include the correct 'comps' you have selected in row 75. Hint: Look at the TRUE and FALSE in row 75 and confirm you used the correct logic. Do your answers make sense? (5) In column P, calculate the average multiples for the Selected 'Comps' for rows 67 to 70. Hint: Use the AVERAGEIF function to make sure you only include the correct 'comps' you have selected in row 75. [HINT: USE FALSE IF YOU WANT TO REMOVE THE COMPANY FROM THE ANALYSIS!] Selected 'Comps' Average Multiple Strong Comparable? Not Anomolous? Selected 'Comps' (include in Relative Valuation?) In Row 75, you selected companies that were strong comparables for Facebook. Why did you select these companies as 'comps'? a) These are all internet companies and members of the same industry sector. b) These companies have a similar revenue model which relies on Internet advertising. c) These companies have a similar customer base, consumers. 9 Relative Valuation Analysis of Facebook (FB) (all figures in millions, except per share data) Begin by Assuring Data Integrity Data Integrity requires validating the soundness and completeness of the data. (1) Use the data below to calculate the Market Value of each company below in Row 28. (2) Use the Market Value to calculate the Enterprise Value in Row 31. If you cannot remember the formulas for these calculations, refer to the tutorial in the prior Sheet (VALUATION Relative). You may notice the large differential between the GAAP and Non-GAAP EPS forecasts for many of these companies. Even more interesting, many publishing analysts forecast Non-GAAP EPS for 2022E and beyond as these are the figures they rely on for their valuation work. In the case of Alphabet (GOOGL), the primary difference between GAAP and Non-GAAP EPS is stock-based compensation. Analysts rarely forecast one-time items unless they are previously announced by the company (such as a write-off or legal expense). Define the 'Comps' and Calculate the Selected 'Comps' Average Multiples (1) Calculate the multiples in rows 67 to 70 for columns G to N. (2) In row 73, enter TRUE if the company is a comparable with FB and FALSE if not. Hint: There are two companies that are not strong comparables for Facebook. (3) In row 74, enter TRUE if any of the multples you calculated in Step (1) are NOT anomolous, and enter FALSE if the mulitple is anomolous. Hint: In Part I Review (Workbook 1), we discussed Data Integrity and the challenges of encountering erroneous, outlier and irregular data. Your goal is to determine if any of the companies below should be eliminated from the potential 'comp' group because the data is anomolous. In Strategic Forecasting (Workbook 9), we removed an outlier and saw a significant improvement in the relationship between capacity utilization and profitability. In this exercise, you are doing something similar and 'scrubbing' the data to remove outliers that are anomalous. Hint: Look at the TRUE and FALSE in row 75 and confirm you used the correct logic. Do your answers make sense? (5) In column P, calculate the average multiples for the Selected 'Comps' for rows 67 to 70. Hint: Use the AVERAGEIF function to make sure you only include the correct 'comps' you have selected in row 75. Hint: Look at the TRUE and FALSE in row 75 and confirm you used the correct logic. Do your answers make sense? (5) In column P, calculate the average multiples for the Selected 'Comps' for rows 67 to 70. Hint: Use the AVERAGEIF function to make sure you only include the correct 'comps' you have selected in row 75. [HINT: USE FALSE IF YOU WANT TO REMOVE THE COMPANY FROM THE ANALYSIS!] Selected 'Comps' Average Multiple Strong Comparable? Not Anomolous? Selected 'Comps' (include in Relative Valuation?) In Row 75, you selected companies that were strong comparables for Facebook. Why did you select these companies as 'comps'? a) These are all internet companies and members of the same industry sector. b) These companies have a similar revenue model which relies on Internet advertising. c) These companies have a similar customer base, consumers