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Financial Innovation

Table 7 1-Day ahead forecasting results for daily log-returns of the NYSERAI index

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

Model

MSE

MAE

GARCH

1.6261

0.9682

ICSS-GARCH

1.5903

0.9632

PSO-LSSVM

1.6339

0.9712

EEMD-GARCH

0.9568

0.7547

EEMD-ICSS-GARCH

0.9034

0.9283

EEMD-PSO-LSSVM

0.8421

0.6611

EEMD-PSO-LSSVM-GARCH(A)

0.8410

0.6601

EEMD-PSO-LSSVM-GARCH(B)

0.7961

0.6693

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

0.6930

0.6354

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

0.7083

0.6277

  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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