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.