Question: I he project will entail using regression analysis to calculate the Beta of the company you are using. Choose any company you desire. Try stay

I he project will entail using regression analysis to calculate the Beta of the company you are using. Choose any company you desire. Try stay away from really small ones. Calculate the beta of the company of your choice, adjusted R square, and the y intercept. E[R] = rf + beta*[E(Rmkt) - rf]...(1) Where E[R]expected return is the dependent variable and E(Ry) - rg is the independent variable. Use S&P 500 for last 5 years (monthly observations). Use only the adjusted closing price. You will have to manually type in all the observations for the adjusted closing price using the screenshot of the S&P 500 data. Please choose a big company in terms of market cap. Use Yahoo.finance to do that. You can download as an excel. Steps to follow: 1. Use the finance.yahoo.com for the company data e.g GE, LMT, BAC etc. 2. Put the ticker symbol on the search box. Look at the file named Teva and the items that | have circled. 3. Download the file for the last 5 years and use monthly observation only. The initial download will be from newest to oldest make it Convert it from_oldest to newest. IF YOU FIND A WAY TO GET S&P 500 DATA FROM ANY OTHER SOURCE PLEASE FEED FREE AND USE MONTHLY OBSERVATIONS FOR LAST 5 YEARS How to format the data 1. Make sure dates are all consistent. There are three new files added under A-project files for your help. DTB3, teva example, and the screenshot 2024 are the file names . Use the S&P number which you will have to manually type into excel. You can start with column. | am just giving some hints here 2. - Calculate return of the stock (from chapter 11). Column C in excel - Calculate market return using the same concept. Column E in excel (FOR The market return only use only ADJUSTED CLOSE - Calculate market return using the same concept. Column E in excel (FOR The market return only use only ADJUSTED CLOSE - Use the data from DTB3 from canvas files. Column F in excel. Subtract Column F from Column E. New column G which is rykt - 1+ In a new spread sheet you will have only two columns: Stock return on column A and numbers from column F (MARKET RETURN - RISK-FREE RATE) where stock return is the dependent variable and market return -riskfree rake is the independent variable. Run the regression analysis use a new page to have the result. The row with Intercept needs to be noted The row with X Variable is the slope or the beta. Show what is the value of the 'beta' in equation (1). Interpret the result in a sensible way. Submit the actual excel file with answers. \f9/1/21 22.485001 22.986 20.466999 20.716 20.682266 4998986000 10/1/21 20.75 25.709 19.555 25.566999 25.525366 4971078000 11/1/21 25.649 34.646999 25.226999 32.675999 32.622787 1.0811E+10 12/1/21 33.219002 33.289001 27.145 29.410999 29.363106 1.1059E+10 1/1/22 29.815001 30.711 20.888 24.486 24.449121 1.0682E+10 2/1/22 25.104 26.924999 20.889999 24.385 24.348274 1.0644E+10 3/1/22 24.291 28.945999 20.65 27.285999 27.244902 1.1645E+10 4/1/22 27.375 27.558001 18.290001 18.547001 18.522219 1.1114E+10 5/1/22 18.541 20.4 15.567 18.672001 18.647055 1.3833E+10 6/1/22 18.724001 19.618999 14.862 15.159 15.138747 1.0555E+10 7/1/22 14.899 18.243999 14.055 18.163 18.142569 1.0564E+10 8/1/22 18.181999 19.274 14.959 15.094 15.077021 1.207E+10 9/1/22 14.209 14.547 11.946 12.139 12.125344 1.3131E+10 10/1/22 12.347 13.85 10.813 13.497 13.485824 1.2549E+10 11/1/22 13.811 16.997999 12.956 16.923 16.908987 1.0601E+10 12/1/22 16.999001 18.790001 13.884 14.614 14.605635 8946152000 1/1/23 14.851 20.628 14.034 19.537001 19.525818 9454960000 2/1/23 19.691 23.888 19.611 23.216 23.202707 1.0393E+10 3/1/23 23.191999 27.834 22.297001 27.777 27.761097 1.1264E+10 4/1/23 27.509001 28.110001 26.219999 27.749001 27.737825 7436450000 5/1/23 27.84 41.938 27.24 37.834 37.818764 1.1698E+10 6/1/23 38.488998 43.990002 37.355999 42.301998 42.284962 1.0527E+10 7/1/23 42.516998 48.088001 41.346001 46.729 46.715015 8706845000 8/1/23 46.459999 50.265999 40.311001 49.355 49.340229 1.3632E+10 9/1/23 49.762001 49.799999 40.98 43.499001 43.485985 8579273000 10/1/23 44.029999 47.609001 39.23 40.779999 40.771152 1.0141E+10 11/1/23 40.883999 50.548 40.868999 46.77 46.759853 9144618000 12/1/23 46.525002 50.432999 45.009998 49.521999 49.511257 7411887000 1/1/24 49.243999 63.493 47.32 61.527 61.519058 9706237000 2/1/24 62.099998 82.393997 61.650002 79.112 79.101791 1.1078E+10 3/1/24 80 97.400002 79.434998 90.356003 90.344337 1.2149E+10 4/1/24 90.299004 92.224998 75.606003 86.402 86.394905 1.0074E+10 5/1/24 85.077003 115.819 81.254997 109.633003 109.624001 9647971000 6/1/24 113.621002 140.759995 112.002998 130.779999 130.769257 4943915300 6/21/24 127 130.630005 124.300003 126.829002 126.829002 309859554

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