Table 35 Parameters of the best parametric models for \(T_c^{s}\) computed on real and simulated data for Apple
From: Drawdown-based risk indicators for high-frequency financial volumes
Summary of the best statistical model selection | ||||
|---|---|---|---|---|
for \(T_c^{s}\)-APPLE | ||||
\(s=0\) | M | Best model | Real data (\(\mu\), \(\sigma\)) | Simulated data (\(\mu\), \(\sigma\)) |
30% | Lognormal | 0.0330–0.1482 | 0.5250–0.6557 | |
40% | Lognormal | 0.0495–0.2349 | 0.6359–0.6579 | |
80% | Lognormal | 0.0770–0.3069 | 0.8650–0.8141 | |
\(s=5\) | M | Best model | Real data (\(\mu\), \(\sigma\)) | Simulated data (\(\mu\), \(\sigma\)) |
|---|---|---|---|---|
30% | Lognormal | 0.5917–0.6636 | 0.4381–0.5573 | |
40% | Lognormal | 0.8012–0.7931 | 0.7647–0.8047 | |
80% | Lognormal | 0.9900–0.8993 | 1.0009–0.8483 |
\(s=50\) | M | Best model | Real data (\(\mu\), \(\sigma\)) | Simulated data (\(\mu\), \(\sigma\)) |
|---|---|---|---|---|
30% | Lognormal | 0.3130–0.4504 | 0.3922–0.5238 | |
40% | Lognormal | 0.5157–0.6311 | 0.6145–0.7248 | |
80% | Lognormal | 0.8013–0.7750 | 0.7285–0.8288 |
\(s=100\) | M | Best model | Real data (\(\mu\), \(\sigma\)) | Simulated data (\(\mu\), \(\sigma\)) |
|---|---|---|---|---|
30% | Lognormal | 0.3517-0.4951 | 0.4024-0.5734 | |
40% | Lognormal | 0.4972–0.5911 | 0.5489–0.6637 | |
80% | Lognormal | 0.6628–0.7115 | 0.5882–0.7923 |