Exercise

# Portfolio returns during the crisis

The first step in quantifying the effects of uncertainty on a financial portfolio is to examine the portfolio's **return**. You'll consider a portfolio of four investment bank stocks, which were both instigators and victims of the global financial crisis.

The banks are *Citibank*, *Goldman Sachs*, *J.P. Morgan*, and *Morgan Stanley*. Closing stock prices for the period 2005 - 2010 are in the available `portfolio`

DataFrame. You'll use this to examine the dramatic price changes during the depths of the crisis, 2008 - 2009. You'll also see how volatile the resulting `portfolio_returns`

were, assuming an equal-weighted portfolio with weights stored in the `weights`

list.

In this and in all future exercises, `numpy`

, `pandas`

and `matplotlib.pyplot`

are available as `np`

, `pd`

, and `plt`

respectively.

Instructions 1/2

**undefined XP**

- Create a subset of the
`portfolio`

DataFrame time series for the period 2008-2009 using`.loc[]`

, and place in`asset_prices`

. - Plot the
`asset_prices`

during this time.

*Remember that you can examine the portfolio DataFrame directly in the console.*