Table 51 Kullback–Leibler divergence computed on the risk measure \(T_c^{s}\) as a function of M and s for Tesla, Netflix and Apple
From: Drawdown-based risk indicators for high-frequency financial volumes
Kullback-Leibler divergence for \(T_c^{s}\) | |||
|---|---|---|---|
\(s=0\) | \(D(P \Vert Q)\) | \(D(P \Vert Q)\) | \(D(P \Vert Q)\) |
\(M=30\%\) | 0.8473 | 0.2776 | 1.8671 |
\(M=40\%\) | 0.9402 | 0.3344 | 1.4934 |
\(M=80\%\) | 1.1248 | 0.4784 | 1.3141 |
\(s=5\) | \(D(P \Vert Q)\) | \(D(P \Vert Q)\) | \(D(P \Vert Q)\) |
|---|---|---|---|
\(M=30\%\) | 0.1221 | 0.1993 | 0.1044 |
\(M=40\%\) | 0.2544 | 0.1881 | 0.0018 |
\(M=80\%\) | 0.2100 | 0.2124 | 0.0052 |
\(s=50\) | \(D(P \Vert Q)\) | \(D(P \Vert Q)\) | \(D(P \Vert Q)\) |
|---|---|---|---|
\(M=30\%\) | 0.0795 | 0.1045 | 0.0463 |
\(M=40\%\) | 0.0108 | 0.1629 | 0.0387 |
\(M=80\%\) | 0.0147 | 0.2471 | 0.0118 |
\(s=100\) | \(D(P \Vert Q)\) | \(D(P \Vert Q)\) | \(D(P \Vert Q)\) |
|---|---|---|---|
\(M=30\%\) | 0.2625 | 0.0153 | 0.0339 |
\(M=40\%\) | 0.1066 | 0.0314 | 0.0223 |
\(M=80\%\) | 0.0684 | 0.1581 | 0.0220 |