Exercise

# CVaR and risk exposure

Recall that CVaR is the expected value of loss *given* a minimum loss threshold. So CVaR is *already* in the form of a risk exposure--it is the sum (or integral) of the probability of loss in the distribution tail multiplied, by the loss amount.

To derive the 99% CVaR you'll first fit a **T** distribution to available `crisis_losses`

portfolio data from 2008 - 2009, using the `t.fit()`

method. This returns the **T** distribution parameters `p`

used to find the VaR with the `.ppf()`

method.

Next you'll compute the 99% VaR, since it's used to find the CVaR.

Finally you'll compute the 99% CVaR measure using the `t.expect()`

method, which is the same method you used to compute CVaR for the Normal distribution in an earlier exercise.

The `t`

distribution from `scipy.stats`

is also available.

Instructions

**100 XP**

- Find the distribution parameters
`p`

using the`.fit()`

method applied to`crisis_losses`

. - Compute
`VaR_99`

using the fitted parameters`p`

and the percent point function of`t`

. - Compute
`CVaR_99`

using the`t.expect()`

method and the fitted parameters`p`

, and display the result.