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1\begin{table}[H]2\centering3\caption{In-sample fit of realized-variance forecasting models (common sample).}4\label{tab:rq2}5\begin{threeparttable}6\small7\begin{tabular}{@{}lrrrrr@{}}8\toprule9& & \multicolumn{2}{c}{$RV_{t+1}$} & \multicolumn{2}{c}{$\sum_{j=1}^{5} RV_{t+j}$} \\10\cmidrule(lr){3-4}\cmidrule(lr){5-6}11Model & $k$ & $R^2$ & $\Delta R^2$ (\%) & $R^2$ & $\Delta R^2$ (\%) \\12\midrule13$RV_t + r_t^2$ (ARCH-type) & 2 & 0.360 & $-$13.3 & 0.317 & $-$24.7 \\14HAR-RV & 3 & 0.415 & +0.0 & 0.421 & +0.0 \\15IV only (30d, 90d) & 2 & 0.355 & $-$14.6 & 0.463 & +9.8 \\16IV surface & 5 & 0.361 & $-$13.1 & 0.466 & +10.5 \\17HAR-RV $+$ IV surface & 8 & 0.457 & +9.9 & 0.515 & +22.3 \\18\bottomrule19\end{tabular}20\begin{tablenotes}[flushleft]\footnotesize21\item \textit{Notes.} Pooled OLS on the common sample of 119{,}093 ticker-days (69 tickers) for which every regressor of the largest model is observed; regressors and targets winsorized at the 1st and 99th percentiles within ticker and standardized. $k$ is the number of regressors. $\Delta R^2$ is the change relative to HAR-RV in percent of the HAR-RV $R^2$. Model definitions in Section~\ref{sec:method}.22\end{tablenotes}23\end{threeparttable}24\end{table}25