Exercise

# Fitting an ARIMA model

In this exercise you'll learn how to be lazy in time series modeling. Instead of taking the difference, modeling the difference and then integrating, you're just going to lets `statsmodels`

do the hard work for you.

You'll repeat the same exercise that you did before, of forecasting the absolute values of the Amazon stocks dataset, but this time with an ARIMA model.

A subset of the stocks dataset is available in your environment as `amazon`

and so is the `SARIMAX`

model class.

Instructions

**100 XP**

- Create an ARIMA(2,1,2) model, using the
`SARIMAX`

class, passing it the Amazon stocks data`amazon`

. - Fit the model.
- Make a forecast of mean values of the Amazon data for the next 10 time steps. Assign the result to
`arima_value_forecast`

.