Table 34 Parameters of the best parametric models for \(T_c^{s}\) computed on real and simulated data for Netflix
From: Drawdown-based risk indicators for high-frequency financial volumes
Summary of the best statistical model selection | ||||
|---|---|---|---|---|
for \(T_c^{s}\)-NETFLIX | ||||
\(s=0\) | M | Best model | Real data (\(\mu\), \(\sigma\)) | Simulated data (\(\mu\), \(\sigma\)) |
30% | Lognormal | 0.1004–0.5073 | 0.4419–0.6602 | |
40% | Lognormal | 0.1113–0.5535 | 0.5362–0.6892 | |
80% | Lognormal | 0.1222–0.6969 | 0.7718–0.8352 | |
\(s=5\) | M | Best Model | Real data (\(\mu\), \(\sigma\)) | Simulated data (\(\mu\), \(\sigma\)) |
|---|---|---|---|---|
30% | Lognormal | 0.7698–0.8593 | 0.4267–0.6259 | |
40% | Lognormal | 1.2313–0.9856 | 0.5257–0.6786 | |
80% | Lognormal | 1.0192–1.0803 | 0.7312–0.8264 |
\(s=50\) | M | Best Model | Real data (\(\mu\), \(\sigma\)) | Simulated data (\(\mu\), \(\sigma\)) |
|---|---|---|---|---|
30% | Lognormal | 0.3247–0.6870 | 0.3054–0.5372 | |
40% | Lognormal | 0.4590–0.7731 | 0.3600–0.5819 | |
80% | Lognormal | 0.5667–0.9256 | 0.4326–0.6565 |
\(s=100\) | M | Best Model | Real data (\(\mu\), \(\sigma\)) | Simulated data (\(\mu\), \(\sigma\)) |
|---|---|---|---|---|
30% | Lognormal | 0.2669–0.5030 | 0.5806–0.6975 | |
40% | Lognormal | 0.3975–0.6388 | 0.3246–0.5710 | |
80% | Lognormal | 0.4937–0.8195 | 0.4144–0.6146 |