garch_models = pd.DataFrame(columns=['AIC','Log-Likelihood'],index=garch_columns)
for i in np.arange(len(garch_models)):
    AEX_GARCH_0 = arch_model(log_r['AEX'], lags=i, vol='Garch', p=1, o=0, q=1, dist='t')
    res_AEX = AEX_GARCH_0.fit()
    res_AEX.summary()
    garch_models.iloc[i,0]= res_AEX.aic
    garch_models.iloc[i,1]= res_AEX.loglikelihood