Part 1: Portfolio Return and Risk

Compute the portfolio returns and risk measures of a portfolio you create.

You can pick any two companies to download stock data for (daily or monthly). For the data you will need to attain about 50 observations (prices and returns for each stock).

Task 1: Compute the respective average, standard deviation, and covariance of monthly or daily stock returns.

Covariance table will be in the form:

Var(stock1, stock1)	Cov(stock1, stock2)
Cov(stock1, stock2)	Var(stock2, stock2)

Note: Use STDEV.P in Excel for the standard deviation

Task 2: Using the obtained statistics fromQ1, calculate an equal weighted portfolio return and portfolio variance for the first portfolio using the below equations:

Equal weighted portfolio return:

E(RP) = w1(avg(r1)) + w2(avg(r2));

where w is the weight of each stock in the portfolio. And avg(r1) is the mean return for stock 1 and avg(r2) is the mean return for stock 2.

Portfolio variance:

2p = w12( 2s1) + w22( 2s2) + 2*w1 w2 * s1 s2

Task 3:

Now using a matrix multiplication (i.e. MMULT in Excel.), compute two portfolio returns and portfolio variances.

Use the formula: portfolio return: E(RP) = w * rT

portfolio variance: P2 =wwT

Task 4:

With either portfolio, create a table that shows the benefit of diversification using Data Table in Excel. (Note that the table shows portfolio returns and portfolio standard deviation with respect to scenarios of weights on one of the stocks of your choosing from the portfolio)

Task 5:

Using the table obtained from task 5, Plot expected returns against portfolio risk (standard deviations) displaying efficient portfolios.

Task 6:

Using the first portfolio, find out optimal weights that minimizes the portfolio standard deviation (Minimum Variance Portfolio).

Use the formula: P2 =w**wT subject to w*rT =E(RP)