Calculate the monthly returns of $10$ assets using data from Bloomberg, Capital IQ$,$ FactSet, FINRA, or Reuters. These can be stocks, mutual funds, or ETFs. You should have a minimum of $40$ observations in each asset. Hint: $($new$/$old$)-1$ OR $($new$-$old$)/$old

Find or calculate the $1-$month yield on a US treasury bond

Hint: The Fed has an index called "Constant Maturity" and uses the series name $"$DGS$1$MO$".$ Use monthly, $$nd$-$of$-$period $($eop$).$

Calculate excess returns by subtracting each month's risk$-$free rate from each stock return in each month.

Calculate the covariance matrix using the excess returns from the $10$ assets. The covariance function can be found in data analysis under the data tab. Remember to fill in the other triangle since the matrix is symmetric. The matrix should be $1010.$

Calculate the average excess return for each asset. This will be your expectation for future returns in a single period. $($In reality, we would use a forward$-$looking prediction but we are keeping it simple here.$)$

Calculate the portfolio excess return using matrix multiplication. Hint: Use the mmult function and Shift$-$Control$-$Enter when done. ret $=w^{\text{'}}r$

Calculate the portfolio variance using matrix multiplication. Keep in mind whether your weight vector is already transposed or not. Hint: var $=w^{\text{'}}w$

Calculate the Sharpe ratio, and the sum of the weights

Use the solver to find the weights that maximize the Sharpe ratio. The sum of all weights must equal $100\%.($Make sure that the solving method is set to GRG Nonlinear in the Solver dialog box. If the results appear to be unreasonable, try running the solver a few more times with a different set of starting weights.$)$

Annualize the portfolio excess return, standard deviation, and Sharpe ratio Hint: $[1+r{]}^{12}-1,\sqrt[\phantom{2}]{?}12$