April 2019
Intermediate to advanced
426 pages
11h 13m
English
Content preview from Mastering Python for Finance - Second Edition
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Fitting the SARIMAX model
Having obtained the optimal model parameters, inspect the model properties using the summary() method on the fitted results to view detailed statistical information:
In [ ]: model = SARIMAX( df_settle, order=order, seasonal_order=seasonal_order, enforce_stationarity=False, enforce_invertibility=False, disp=False ) model_results = model.fit(maxiter=200, disp=False) print(model_results.summary())
This gives us the following output:
Statespace Model Results ========================================================================================== Dep. Variable: Settle No. Observations: 226 Model: SARIMAX(0, 1, 1)x(0, 1, 1, 12) Log Likelihood -1087.247 Date: Sun, 02 Dec 2018 AIC 2180.495 Time: 17:38:32 BIC 2190.375 ...
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