\begin{table}[htbp]\centering\footnotesize
\caption{Model C (Bayesian control): factorial results, no leverage, means with bootstrap 95\% intervals}\label{tab:c_factorial}
\begin{tabular}{llrrrrr}\toprule
Design & $(D,M)$ & corr.\ (all) & corr.\ (delegators) & volatility (\%) & $R^2$ common & trades/period\\\midrule
walrasian & (0,1) & 0.11 [0.10,0.12] & -- & 0.29 & 0.00 & 13.1\\
walrasian & (0.5,1) & 0.32 [0.31,0.34] & 0.99 & 0.35 & 0.07 & 11.8\\
walrasian & (0.5,4) & 0.23 [0.22,0.24] & 0.44 & 0.38 & 0.04 & 12.8\\
walrasian & (1,1) & 0.97 [0.97,0.97] & 0.97 & 0.20 & 0.06 & 7.8\\
walrasian & (1,4) & 0.51 [0.48,0.53] & 0.51 & 0.38 & 0.04 & 10.6\\
walrasian & (1,8) & 0.43 [0.42,0.45] & 0.43 & 0.42 & 0.02 & 11.6\\
cda & (0,1) & 0.15 [0.14,0.16] & -- & 0.31 & 0.00 & 13.4\\
cda & (0.5,1) & 0.28 [0.27,0.29] & 0.68 & 0.35 & 0.07 & 11.8\\
cda & (0.5,4) & 0.25 [0.24,0.26] & 0.44 & 0.38 & 0.04 & 13.4\\
cda & (1,1) & 0.72 [0.71,0.73] & 0.72 & 0.31 & 0.11 & 7.4\\
cda & (1,4) & 0.45 [0.44,0.47] & 0.45 & 0.37 & 0.03 & 10.7\\
cda & (1,8) & 0.43 [0.41,0.45] & 0.43 & 0.40 & 0.02 & 11.5\\
bilateral & (0,1) & 0.17 [0.15,0.18] & -- & 0.18 & 0.00 & 8.6\\
bilateral & (0.5,1) & 0.32 [0.31,0.34] & 0.81 & 0.22 & 0.05 & 8.0\\
bilateral & (0.5,4) & 0.27 [0.25,0.29] & 0.53 & 0.22 & 0.02 & 8.9\\
bilateral & (1,1) & 0.86 [0.85,0.87] & 0.86 & 0.24 & 0.06 & 5.2\\
bilateral & (1,4) & 0.55 [0.52,0.57] & 0.55 & 0.25 & 0.02 & 7.7\\
bilateral & (1,8) & 0.51 [0.49,0.53] & 0.51 & 0.26 & 0.02 & 7.9\\
\bottomrule\end{tabular}
\begin{tablenotes}\footnotesize\item Order-flow correlation is computed after residualising each agent's flow on public information. Source: \texttt{scripts/30\_model\_c.py}.\end{tablenotes}\end{table}