spb/wp12_uqo

1\begin{tabular}{lccc ccc}2\toprule3 & \multicolumn{3}{c}{VaR 1\%} & \multicolumn{3}{c}{VaR 5\%} \\4\cmidrule(lr){2-4}\cmidrule(lr){5-7}5Model & \makecell{Viol.\\(\%)} & \makecell{Kupiec\\pass (\%)} & \makecell{CC\\pass (\%)} & \makecell{Viol.\\(\%)} & \makecell{Kupiec\\pass (\%)} & \makecell{CC\\pass (\%)} \\6\midrule7\multicolumn{7}{l}{\itshape A. GARCH family}\\8\quad GARCH & 1.89 & 12 & 12 & 5.26 & 80 & 84 \\9\quad GJR & 1.89 & 8 & 8 & 5.25 & 80 & 84 \\10\quad EGARCH & 2.21 & 4 & 8 & 5.62 & 72 & 56 \\11\quad RealGARCH & 1.79 & 24 & 24 & 5.18 & 92 & 88 \\12\multicolumn{7}{l}{\itshape B. HAR family}\\13\quad HAR & 1.73 & 12 & 20 & 5.04 & 96 & 84 \\14\quad HAR-CJ & 1.71 & 20 & 28 & 5.08 & 96 & 80 \\15\quad SHAR & 1.79 & 16 & 28 & 5.22 & 76 & 76 \\16\quad HARQ & 1.94 & 8 & 12 & 5.33 & 76 & 84 \\17\quad LogHAR & 1.79 & 20 & 20 & 5.16 & 96 & 92 \\18\multicolumn{7}{l}{\itshape D. Machine learning --- extended information set}\\19\quad Ridge-X & 1.79 & 16 & 28 & 5.16 & 96 & 96 \\20\quad LASSO-X & 1.77 & 16 & 32 & 5.14 & 100 & 96 \\21\quad RF-X & 1.68 & 24 & 40 & 5.06 & 96 & 88 \\22\quad XGBoost-X & 1.84 & 16 & 24 & 5.24 & 92 & 88 \\23\quad LightGBM-X & 1.93 & 12 & 16 & 5.37 & 88 & 84 \\24\multicolumn{7}{l}{\itshape E. Deep learning and pooled}\\25\quad LSTM & 1.87 & 16 & 12 & 5.13 & 80 & 56 \\26\quad Transformer & 1.97 & 16 & 12 & 5.14 & 88 & 44 \\27\quad Pooled-LGBM & 1.90 & 4 & 20 & 5.38 & 84 & 84 \\28\multicolumn{7}{l}{\itshape F. Forecast combinations}\\29\quad Comb-Mean & 1.62 & 32 & 40 & 4.90 & 100 & 88 \\30\quad Comb-InvMSE & 1.64 & 24 & 40 & 4.97 & 100 & 92 \\31\bottomrule32\end{tabular}33