Exercise

# 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.

Instructions

**100 XP**

- 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.