Table 2 Performance of models for SZII using train and test datasets
From: Performance evaluation of series and parallel strategies for financial time series forecasting
Model | Train | Test | ||||||
|---|---|---|---|---|---|---|---|---|
MAE | MAE | MAPE | RMSE | MAE | MSE | MAPE | RMSE | |
ARIMA-MLP | 212.39 | 91,955 | 7.22% | 303.24 | 1082.88 | 1,915,716 | 9.52% | 1384.09 |
MLP-ARIMA | 210.91 | 86,221 | 7.23% | 293.63 | 1064.91 | 1,915,422 | 10.16% | 1383.98 |
SAHM | 217.78 | 95,399 | 7.12% | 308.86 | 1123.87 | 1,997,323 | 9.91% | 1388.69 |
GAHM | 215.38 | 94,577 | 7.08% | 307.53 | 1102.75 | 1,969,593 | 9.79% | 1403.42 |
LRHM | 215.54 | 94,573 | 7.09% | 307.52 | 1074.87 | 1,928,479 | 9.64% | 1388.69 |
ARIMA | 224.45 | 99,255 | 7.30% | 315.04 | 1166.17 | 2,221,776 | 10.26% | 1490.56 |
MLP | 215.38 | 94,577 | 7.30% | 307.53 | 1102.33 | 1,974,479 | 9.80% | 1405.16 |