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Table 26 Selection of the best parametric model as a function of s and M for the measure \(T_c^{s}\) computed on Apple simulated data

From: Drawdown-based risk indicators for high-frequency financial volumes

Model selection for \(T_c^{s}\)-simulated data for Apple

 

Lognormal

 

Exponential

 

Weibull

 

Gamma

 

\(M \mid s=0\)

AIC

BIC

AIC

BIC

AIC

BIC

AIC

BIC

\(30\%\)

386.5363

392.2088

450.6833

453.5196

434.6305

440.3031

419.5173

425.1898

\(40\%\)

415.2923

420.9649

473.4487

476.2850

449.3003

454.9729

436.1147

441.7873

\(80\%\)

526.7210

532.3935

564.5002

567.3365

562.0952

567.7678

555.0535

560.7261

\(M \mid s=5\)

AIC

BIC

AIC

BIC

AIC

BIC

AIC

BIC

\(30\%\)

323.6672

329.3398

411.0725

413.9088

376.8005

382.4781

354.3558

360.0284

\(40\%\)

498.5114

504.1840

551.9424

554.7787

553.6295

559.3021

547.8367

553.5093

\(80\%\)

571.3338

577.0064

604.8417

607.6780

603.8852

609.5577

598.2251

603.8976

\(M \mid s=50\)

AIC

BIC

AIC

BIC

AIC

BIC

AIC

BIC

\(30\%\)

296.4357

2302.1083

392.2497

394.9860

340.7143

346.3868

320.0435

325.7161

\(40\%\)

434.3274

440.0000

488.0851

490.9214

482.0709

487.7435

470.4413

476.1139

\(80\%\)

496.8472

502.5198

543.8429

546.6791

545.2509

550.9234

540.0761

545.7487

\(M \mid s=100\)

AIC

BIC

AIC

BIC

AIC

BIC

AIC

BIC

\(30\%\)

321.8317

327.5043

404.5549

407.3912

371.8132

377.4858

352.2819

357.9545

\(40\%\)

395.5809

401.2534

458.7985

461.6347

445.0042

450.6768

429.8998

435.5724

\(80\%\)

450.1114

455.7839

501.9179

504.7541

502.3582

508.0308

495.7474

501.4200

  1. The best parametric model is chosen by means of the AIC and BIC criteria. The smallest AIC and BIC values are in bold