Exercise

# Backtesting with MAE, MSE

In this exercise, you will practice how to evaluate model performance by conducting backtesting. The out-of-sample forecast accuracy is assessed by calculating MSE and MAE.

You can easily estimate prediction errors MSE and MAE with pre-defined functions in the `sklearn.metrics`

package. The actual variance and predicted variance have been preloaded in `actual_var`

and `forecast_var`

respectively.

Instructions

**100 XP**

- In
`evaluate()`

, perform the MAE calculation by calling the corresponding function from`sklean.metrics`

. - In
`evaluate()`

, perform the MSE calculation by calling the corresponding function from`sklean.metrics`

. - Pass variables to
`evaluate()`

in order to perform the backtest.