Estimating a security beta using market data and simple regression. Complete the steps necessary to estimate the equity beta for one of the following publicly traded securities: Exxon Mobil (XOM), Yahoo beta Estimate September 2019 = 1.21 Lithia Motors (LAD), Yahoo beta Estimate September 2019 = 0.90 Nike (NKE) Yahoo beta Estimate September 2019 = 1.11 JP Morgan Chase (JPM) Yahoo beta Estimate September 2019 = 1.19 Alphabet (GOOG), Yahoo beta Estimate September 2019 = 0.96 Step 1 : Choose a company from the list above. Step 2 : Use Finance.Yahoo.com to find your selected company. Step 3 : Use Yahoo's historical data tab (located below and to the right of the current price for your company) to gather the most recent 61 monthly adjusted closing prices. (You need 61 months of prices so that you can estimate 60 monthly returns.) Yahoo can download this information to a spreadsheet. Step 4 : Repeat step 3 with the S&P 500 Index. The current index value is on the Finance.Yahoo.com homepage and if you click on the value you can find the same tab for historical information you used in step 3. Step 5 : Calculate the monthly returns for your company. e.g. (P 1 - P 0 )/P 0 gives you a return for period 1 Step 6 : Repeat step 5 using the S&P 500 prices. Step 7 : Generate in Excel a scatter plot of returns for your company and the S&P 500 Index. Step 8 : Using the regression function in Excel or in a statistics package of your choice, regress the returns of your company (dependent variable) against the returns of the S&P 500 (independent variable). Have the regression program generate a list of standardized residuals and a residual plot. Step 9: Answer the following questions: 1.How does your estimate of beta compare with the beta published by Yahoo? Why might it differ from Yahoo's published beta? 2.How much of the variability of your security's returns is "explained" by the variability of returns in the "market"? (Note: In your case, the market is represented by the S&P 500 Index.) Do you think that a different market index might be a better representation of the market for your particular security? Why/Why not? 3.What is the correlation of returns for your security with the market for the selected time period? Might this relationship change over time, and if so, how and why? 4.Does the relationship between your security and the market appear to be statistically significantly different than zero? What evidence from the regression supports your conclusion? 5.Review the standardized residuals and comment about the importance of individual data points (if any) that may have influenced your estimation of beta. 6.On what exchange is your company traded and what is the firm's market capitalization