**Learning Goal: **I’m working on a excel multi-part question and need an explanation and answer to help me learn.

FINAL PROJECT: INDIVIDUAL TAKE HOME Work

The excel file “130Afinalproject.xlsx” contains daily stock returns data for Microsoft, Intel, Southwest, McDonald’s, and Johnson & Johnson from 12/29/1989 to 2/25/2022, obtained from Yahoo Finance. The spreadsheet also includes a time-series of the daily risk-free rate (*R*F) obtained from Professor Kenneth French’s Data Library.

1. Construct daily total returns from the price data and use Adj Close as the ending period value to include dividends. Compute and report the daily and annualized mean and standard deviation for each stock (cf. let’s assume that there are 252 trading days within a given year; thus, annualized mean return = 252 × daily mean return; annualized standard deviation of return = sqrt(252) × standard deviation of daily return). Further report the correlation matrix and the variance-covariance matrix across the five daily return series of *R*MSFT, *R*INTC, *R*LUV, *R*MCD, and *R*JNJ.

2. Construct a mean-variance frontier combining two stocks: “Intel” and “Microsoft”. Indicate the minimum-variance portfolio and the efficient frontier formed with these two stocks. Recall that the efficient frontier is the set of expected return–risk combinations that a rational investor would want to consider investing in.

3. Add the risk-free asset and identify the tangent portfolio for the two-stock case with Intel and Microsoft. Highlight the new investment opportunity set characterized by the inclusion of a risk-free asset.

4. Add the remaining stocks to the portfolio mix. Compute the mean-variance frontier and contrast your new plot on the same chart with the graphics from the previous question #2 and #3. In addition, compute and report the optimal portfolio weight assigned for each stock given three levels of targeted portfolio expected returns: 0.05%, 0.1%, 0.15%. What can you infer from the results?

5. Estimate betas and alphas for all five stocks (Microsoft, Intel, Southwest, McDonald’s, and Johnson & Johnson). Use the daily total returns from 02/28/2020 to 02/25/2022 as your regression estimation window (i.e., do not use the entire sample period for your beta and alpha estimations in this question and use only the recent two years of data). Report the following.

- Regress excess stock returns on excess market returns to obtain coefficient estimates of the betas of all five stocks (Note that the intercept estimate from the univariate regression of Y =
*R*i – *R*F on X = *R*M – *R*F captures your estimate of alpha and the coefficient estimate is your beta estimate). Further report the standard error of your beta estimates.

- What are your estimates of the five alphas, and the standard error of these five alpha estimates?