Table 1 Performance comparison of different models on four stock datasets.
From: RCSAN residual enhanced channel spatial attention network for stock price forecasting
Model | Dataset | RMSE | MAE | MAPE (%) | \({R^2}\) (%) | Return (%) |
|---|---|---|---|---|---|---|
Our improved model | Amazon | 18.73 | 12.47 | 0.98 | 92.35 | 463.25 |
ARIMA | Amazon | 35.48 | 35.41 | 2.70 | 67.94 | 211.36 |
LSTM | Amazon | 25.74 | 19.68 | 1.48 | 79.83 | 397.84 |
CNN-LSTM | Amazon | 21.05 | 16.25 | 1.21 | 84.76 | 412.57 |
Random Forest | Amazon | 27.36 | 21.15 | 1.59 | 77.52 | 378.92 |
LLM-Aug LT-CNN | Amazon | 19.03 | 14.81 | 1.06 | 89.73 | 438.63 |
Informer | Amazon | 20.84 | 13.96 | 1.11 | 89.32 | 439.47 |
Autoformer | Amazon | 21.27 | 14.20 | 1.17 | 88.51 | 426.73 |
iTransformer | Amazon | 19.92 | 13.62 | 1.08 | 90.47 | 448.31 |
Our improved model | Maotai | 32.16 | 24.86 | 1.12 | 90.83 | 378.59 |
ARIMA | Maotai | 67.32 | 58.93 | 2.87 | 65.27 | 185.42 |
LSTM | Maotai | 48.75 | 41.52 | 1.95 | 78.64 | 304.68 |
CNN-LSTM | Maotai | 42.83 | 32.46 | 1.43 | 82.59 | 328.71 |
Random Forest | Maotai | 51.24 | 43.87 | 2.03 | 76.31 | 295.43 |
LLM-Aug LT-CNN | Maotai | 36.47 | 27.53 | 1.25 | 87.65 | 356.92 |
Informer | Maotai | 34.89 | 26.45 | 1.20 | 88.24 | 362.79 |
Autoformer | Maotai | 35.74 | 27.08 | 1.22 | 87.41 | 351.64 |
iTransformer | Maotai | 33.28 | 25.01 | 1.16 | 89.17 | 371.85 |
Our improved model | Pingan | 21.58 | 16.73 | 1.04 | 91.62 | 425.38 |
ARIMA | Pingan | 42.65 | 39.82 | 2.63 | 68.52 | 205.73 |
LSTM | Pingan | 31.48 | 26.37 | 1.57 | 77.85 | 352.46 |
CNN-LSTM | Pingan | 25.91 | 19.84 | 1.19 | 83.94 | 387.25 |
Random Forest | Pingan | 33.57 | 28.62 | 1.74 | 75.26 | 341.89 |
LLM-Aug LT-CNN | Pingan | 23.76 | 18.65 | 1.13 | 88.47 | 402.17 |
Informer | Pingan | 24.92 | 18.41 | 1.10 | 88.96 | 408.42 |
Autoformer | Pingan | 25.35 | 18.76 | 1.14 | 87.83 | 397.89 |
iTransformer | Pingan | 22.68 | 17.04 | 1.06 | 90.23 | 417.56 |
Our improved model | Wanke | 15.32 | 10.89 | 0.92 | 93.17 | 482.64 |
ARIMA | Wanke | 29.76 | 28.53 | 2.42 | 71.38 | 227.85 |
LSTM | Wanke | 21.85 | 17.29 | 1.36 | 81.97 | 412.36 |
CNN-LSTM | Wanke | 18.47 | 13.78 | 1.09 | 86.82 | 435.28 |
Random Forest | Wanke | 23.54 | 19.45 | 1.48 | 79.64 | 398.73 |
LLM-Aug LT-CNN | Wanke | 16.85 | 12.36 | 0.98 | 90.59 | 456.41 |
Informer | Wanke | 17.64 | 12.92 | 0.99 | 91.27 | 460.14 |
Autoformer | Wanke | 18.02 | 13.17 | 1.01 | 90.68 | 449.71 |
iTransformer | Wanke | 16.39 | 11.68 | 0.95 | 91.92 | 471.26 |
