Mastering Python for Finance - Second Edition

Finding model parameters by grid search

A grid search, also known as the hyperparameter optimization method, can be used to iteratively explore different combinations of parameters for fitting our ARIMA model. We can fit a seasonal ARIMA model with the SARIMAX() function of the statsmodels module in each iteration, returning an object of the MLEResults class. The MLEResults object holds an aic attribute for returning the AIC value. The model with the lowest AIC value gives us the best-fitting model that determines our parameters of p, d, and q. More information on SARIMAX can be found at https://www.statsmodels.org/dev/generated/statsmodels.tsa.statespace.sarimax.SARIMAX.html.

We define the grid search procedure as the arima_grid_search() ...