Exercise

# Equal weighted portfolios

When comparing different portfolios, you often want to consider performance versus a naive equally-weighted portfolio. If the portfolio doesn't outperform a simple equally weighted portfolio, you might want to consider another strategy, or simply opt for the naive approach if all else fails. You can expect equally-weighted portfolios to tend to outperform the market when the largest companies are doing poorly. This is because even tiny companies would have the same weight in your equally-weighted portfolio as Apple or Amazon, for example.

To make it easier for you to visualize the cumulative returns of portfolios, we defined the function `cumulative_returns_plot()`

in your workspace.

Instructions

**100 XP**

- Set
`numstocks`

equal to`9`

, which is the number of stocks in your portfolio. - Use
`np.repeat()`

to set`portfolio_weights_ew`

equal to an array with an equal weights for each of the 9 stocks. - Use the
`.iloc`

accessor to select all rows and the first 9 columns when calculating the portfolio return. - Finally, review the plot of cumulative returns over time.