DataCamp

Effect of the return target

This exercise will show the effect of increasing your target return on the volatility of your mean-variance efficient portfolio.

The function portfolio.optim has arguments that allow for more general specifications. The arguments are as follows:

portfolio.optim(x, pm = mean(x), shorts = FALSE, reshigh = NULL)

The argument pm sets the target return, the argument reshigh specifies the upper constraints on the portfolio weights, and the argument shorts is a logical statement specifying whether negative weights are forbidden or not, by default shorts = FALSE.

You will create a portfolio that is optimized for a target return that equals the average value of the return series returns. Then you will create a portfolio that has a target return that is 10% higher than the mean return series, and calculate the proportion change in risk.

Create a portfolio using returns where the target return is the mean of returns. Store the output as the variable pf_mean.
Create a portfolio using returns where the target return is 10% greater than the mean of returns. Call this pf_10plus.
Print the standard deviations of both pf_mean and pf_10plus (2 lines of code). Remember that the portfolio standard deviation is stored in $ps.
Calculate the proportion increase in standard deviation you get by increasing your target return.

Take Hint (-30 XP)

Exercise

Effect of the return target

Instructions