spb/wp12_uqo

1\begin{tabular}{lcccccc}2\toprule3Model & QLIKE $h{=}1$ & Ratio $h{=}1$ & QLIKE $h{=}5$ & Ratio $h{=}5$ & QLIKE $h{=}22$ & Ratio $h{=}22$ \\4\midrule5\multicolumn{7}{l}{\itshape A. GARCH family}\\6\quad GARCH & 0.338 & 1.319 & 0.302 & 1.117 & 0.341 & 1.184 \\7\quad GJR & 0.338 & 1.321 & 0.302 & 1.118 & 0.340 & 1.182 \\8\quad EGARCH & 0.401 & 1.566 & 0.335 & 1.238 & 0.355 & 1.234 \\9\quad RealGARCH & 0.200 & 0.782 & 0.179 & 0.661 & 0.253 & 0.879 \\10\multicolumn{7}{l}{\itshape B. HAR family}\\11\quad HAR & 0.256 & 1.000 & 0.271 & 1.000 & 0.288 & 1.000 \\12\quad HAR-J & 0.241 & 0.942 & 0.238 & 0.879 & 0.291 & 1.010 \\13\quad HAR-CJ & 0.240 & 0.936 & 0.238 & 0.878 & 0.304 & 1.057 \\14\quad SHAR & 0.253 & 0.988 & 0.262 & 0.968 & 0.289 & 1.003 \\15\quad HARQ & 0.516 & 2.015 & 0.466 & 1.722 & 0.482 & 1.675 \\16\quad LogHAR & 0.193 & 0.752 & 0.169 & 0.625 & 0.227 & 0.790 \\17\multicolumn{7}{l}{\itshape C. Machine learning --- HAR information set}\\18\quad Ridge-H & 0.191 & 0.746 & 0.169 & 0.626 & 0.230 & 0.797 \\19\quad LASSO-H & 0.193 & 0.752 & 0.172 & 0.637 & 0.236 & 0.819 \\20\quad ElasticNet-H & 0.191 & 0.747 & 0.170 & 0.627 & 0.230 & 0.799 \\21\quad RF-H & 0.218 & 0.851 & 0.204 & 0.753 & 0.276 & 0.960 \\22\quad XGBoost-H & 0.232 & 0.904 & 0.219 & 0.809 & 0.318 & 1.106 \\23\quad LightGBM-H & 0.239 & 0.935 & 0.224 & 0.828 & 0.320 & 1.110 \\24\multicolumn{7}{l}{\itshape D. Machine learning --- extended information set}\\25\quad Ridge-X & \textbf{0.180} & \textbf{0.702} & \textbf{0.164} & \textbf{0.606} & 0.227 & 0.789 \\26\quad LASSO-X & 0.182 & 0.710 & 0.166 & 0.613 & 0.231 & 0.800 \\27\quad ElasticNet-X & 0.180 & 0.704 & 0.164 & 0.607 & 0.226 & 0.786 \\28\quad RF-X & 0.201 & 0.786 & 0.194 & 0.716 & 0.273 & 0.947 \\29\quad XGBoost-X & 0.205 & 0.800 & 0.217 & 0.802 & 0.323 & 1.121 \\30\quad LightGBM-X & 0.218 & 0.853 & 0.230 & 0.849 & 0.333 & 1.156 \\31\multicolumn{7}{l}{\itshape E. Deep learning and pooled}\\32\quad LSTM & 0.340 & 1.329 & 0.283 & 1.046 & 0.303 & 1.053 \\33\quad Transformer & 0.484 & 1.889 & 0.399 & 1.477 & 0.420 & 1.459 \\34\quad Pooled-LGBM & 0.196 & 0.765 & 0.189 & 0.700 & 0.275 & 0.954 \\35\multicolumn{7}{l}{\itshape F. Forecast combinations}\\36\quad Comb-Mean & 0.204 & 0.796 & 0.185 & 0.684 & 0.250 & 0.867 \\37\quad Comb-InvMSE & 0.185 & 0.723 & 0.165 & 0.610 & \textbf{0.223} & \textbf{0.774} \\38\bottomrule39\end{tabular}40