Table 6 Comparative Experiments.

From: PMANet: a time series forecasting model for Chinese stock price prediction

Method

PMANet

Autoformer

Transformer

FEDformer

Informer

CEEMD-CNN-LSTM

LSTM

Metrics

MSE

MAE

MSE

MAE

MSE

MAE

MSE

MAE

MSE

MAE

MSE

MAE

MSE

MAE

JT

24

0.412

0.431

0.532

0.502

0.396

0.448

0.734

0.641

0.593

0.538

0.579

0.518

0.697

0.564

48

0.515

0.502

0.508

0.546

0.711

0.591

0.761

0.663

0.583

0.505

0.622

0.532

0.718

0.577

GL

24

0.122

0.278

0.321

0.455

1.108

1.011

0.305

0.432

0.286

0.421

0.315

0.421

0.237

0.381

48

0.124

0.278

0.192

0.351

3.874

1.946

0.327

0.438

0.315

0.429

0.284

0.409

0.284

0.409

THS

24

0.531

0.498

0.585

0.538

1.109

0.804

2.351

1.193

0.771

0.667

0.759

0.664

0.729

0.645

48

0.868

0.661

0.891

0.683

1.727

1.135

2.746

1.312

0.783

0.665

0.727

0.647

0.781

0.677

HR

24

0.182

0.352

0.336

0.473

0.583

0.672

0.477

0.497

0.67

0.555

0.261

0.397

0.654

0.717

48

0.261

0.423

0.275

0.431

0.657

0.694

0.568

0.506

0.562

0.549

0.289

0.411

0.711

0.768

KM

24

0.265

0.183

0.347

0.359

0.413

0.462

0.313

0.352

0.178

0.318

0.585

0.511

0.716

0.788

48

0.308

0.329

0.569

0.561

0.557

0.584

0.447

0.489

0.307

0.366

0.747

0.708

0.934

0.905

BYD

24

0.175

0.254

0.228

0.256

0.284

0.407

0.271

0.355

0.194

0.278

0.711

0.725

1.246

1.095

48

0.232

0.257

0.489

0.467

0.573

0.594

0.589

0.673

0.273

0.261

0.879

0.828

1.512

1.183