Exercise

# Visualizing risk factor correlation

Investment banks heavily invested in mortgage-backed securities (MBS) before and during the financial crisis. This makes MBS a likely risk factor for the investment bank portfolio. You'll assess this using scatterplots between `portfolio returns`

and an MBS risk measure, the 90-day mortgage delinquency rate `mort_del`

.

`mort_del`

is only available as quarterly data. So `portfolio_returns`

first needs to be transformed from daily to quarterly frequency using the DataFrame `.resample()`

method.

Your workspace contains both `portfolio_returns`

for an equal-weighted portfolio and the delinquency rate `mort_del`

variable. For the scatterplots, `plot_average`

and `plot_min`

are plot axes in your workspace--you'll add your scatterplots to them using the `.scatter()`

method.

Instructions

**100 XP**

- Transform the daily
`portfolio_returns`

data into average quarterly data using the`.resample()`

and`.mean()`

methods. - Add a scatterplot between
`mort_del`

and`portfolio_q_average`

to`plot_average`

. Is there a strong correlation? - Now create minimum quarterly data using
`.min()`

instead of`.mean()`

. - Add a scatterplot between
`mort_del`

and`portfolio_q_min`

to`plot_min`

.