Exercise

# Compute benchmark returns

In this exercise, we will create a benchmark to evaluate the performance of the optimization models in later exercises. An equal weight benchmark is a simple weighting scheme to construct the benchmark portfolio. The intuition of an equal weight approach is that there is no preference for any given asset. We are setting this up to answer the question, "Can optimization outperform a simple weighting scheme to construct a portfolio?"

Instructions

**100 XP**

- Load the
`PortfolioAnalytics`

package. - Load the edhec dataset.
- Assign the edhec dataset to a variable named
`asset_returns`

. - Create a vector of equal weights assigned to a variable named
`equal_weights`

. - Compute an equal weight benchmark, rebalanced quarterly, of
`asset_returns`

. - Plot the benchmark returns.