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
Covariance table will be in the form:
Var(stock1, stock 1)
Cov (stock1, stock 2)
Cov(stock1, stock 2)
Var(stock2, stock 2)
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.
σ2p = w12 ( σ 2s1) + w22 ( σ2s2) + 2*w1 w2 * σs1 σs2
Task 3: Select two different stocks and repeat task 1 and 2
Again: you can pick any two companies (except the ones you used for part 1) to download stock data for
(daily or monthly). For the data you will need to attain about 50 observations (prices and returns for
Task 4: 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: σP2 =w·Σ·wT
Task 5: 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 scenariosof weights on one of the stocks – of your choosing – from the portfolio)
Task 6: Using the table obtained from task 5, Plot expected returns against portfolio risk (standard deviations)displaying efficient portfolios.
Task 7: Using the first portfolio, find out optimal weights that minimizes the portfolio standard deviation
(Minimum Variance Portfolio).
Use the formula (from Slides 6 and 7): σp2 =w*Σ*wT subject to w*rT =E(RP)