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Table 6 1-Day ahead forecasting results for daily log-returns of the AIRO index under alternative sample periods

From: A new hybrid method with data-characteristic-driven analysis for artificial intelligence and robotics index return forecasting

Model

MSE

MAE

GARCH

1.1642

0.8452

ICSS-GARCH

1.0946

0.8384

PSO-LSSVM

1.2654

0.8807

EEMD-GARCH

0.6614

0.6239

EEMD-ICSS-GARCH

0.6593

0.6183

EEMD-PSO-LSSVM

0.6674

0.6146

EEMD-PSO-LSSVM-GARCH(A)

0.5855

0.5935

EEMD-PSO-LSSVM-GARCH(B)

0.5592

0.5902

EEMD-PSO-LSSVM-ICSS-GARCH(A)

0.5686

0.5975

EEMD-PSO-LSSVM-ICSS-GARCH(B)

0.5474

0.5893

  1. The numbers in the table refer to the values of the two loss functions. The underlined numbers indicate that the corresponding models have the lowest forecasting losses
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