WACC Project for Apple, Inc.

I.Pages showing equations with data and brief description

There is no page length given for this as it can vary greatly. This section is to be divided up based on the topics. In each section, you must show and explain the equations that are used. In addition, you are to draw any conclusions on the company you can from this data. Please note that detailed worksheets showing all of the calculations for this section are to be included in an appendix.

1. Cost of Equity (Common Stock)

a. Beta from Regression and two Betas from analysts

b. Beta Chosen for CAPM and why

c. Capital Assets Pricing Model (include how determined R_F and[ R_M or (R_M - R_F)]

d. Discounted Cash Flow (DCF) (only if dividends - include how determined)

e. Own-Bond-Yield-plus-Judgmental-Risk-Premium (include how determine risk premium)

**Please help me calculate the following equations for my WACC project. The company chosen for this project is Apple, Inc. Below you will find examples to help calculate.

Calculating the Required Return on Common Stock

CAPM

Determining Beta

1. Find the beta from Yahoo Finance and Value line for your firm.

1. Perform a regression using stock returns versus the appropriate market return.

For most firms, the S&P 500 will be sufficient; if you chose a relatively small

firm, you might want to use the NASDAQ returns.

EXAMPLE:

The example that I show you uses IBM and 60 months of historical monthly price data. I also used the monthly price data for the S&P 500.

This information is downloaded first and then only the needed columns are cut and pasted into the spreadsheet and the monthly returns will be automatically calculated.

Data on stock prices and dividends can be downloaded from the web and used to make betas for real companies.I demonstrate the process for IBM in this section. I downloaded stock prices and dividends from http://finance.yahoo.com for IBM using its ticker symbol IBM. I also downloaded data for the S&P 500 Index,whose symbol is ^GSPC to represent the market.Here are the steps I followed:

Steps:

1. Access the Internet, then go tohttp://finance.yahoo.com/
2. Enter IBM in the symbol slot and then clickGet quotes.
3. Click on "Historical prices" to get a history of IBM prices.
4. Enter a Start Date 5 years ago and a current ending date .
5. Click the "monthly" button. then"Get prices" to get 5 years of monthlyprices for IBM.The closing prices are adjusted for dividends and splits.
6. Note that Yahoo's data is downloaded as a CSV file. Save the file as an excel spreadsheet. Save as IBM
7. Repeat the process to get the S&P index, symbol ^GSPC .Save this file as SP500 and in excel format.
8. Open the IBM file and delete the columns except for the date and closing prices. Then open the SP500 file, copy the closing price data, and paste it into Column B on the IBM file.
9. Now move the IBM data over to column D and then calculate the monthly returns on the market and on IBM
10. Now you can run the regression of IBM's returns on the market to find its beta

Regression analysis is performed by following this command path: Tools => Data Analysis => Regression.

This will yield the Regression input box.If Data Analysis is not an option in your Tools menu, you will have to load that program.Loading the Analysis ToolPak is different in each version of Office so you will have to determine how to find it. Once it is loaded, you will now be able to access Data Analysis. From this point, you must designate the Y input range (stock returns) and the X input range (market returns).You can have the summary output placed in a new worksheet, or you can have it shown directly in the worksheet, as I did, but be careful that you place it in a blank area of your spreadsheet.

You may decide that a years worth of weekly data would be better, perhaps if there were something unusual two years ago. You could also use daily data, generally 200 days worth. In these cases you will have to adjust the spreadsheet for fewer/more data points.

1. You must now decide if you want to average your betas or drop one of them. In our example , the calculated beta was .643 and we had two other estimates of .66 and .85. It would be your choice to either drop the .85 and average the other two, or average all three.

You must justify your choices and provide citations in the body of your report and references at the end.

You must now decide what value you will use for R_F and either R_M or RP_Mwhere

oCAPM:R_E = R_RF + (R_M - R_RF)b

= R_RF + (RP_M)b.

Again, You must justify your choices for R_F and either R_M or RP_Mand provide citations in the body of your report and references at the end.