\begin{table}[H]\centering
\caption{Robustness of the AI Return Spread}\label{tab:robust}
\small
\begin{tabular}{lcc}\toprule
& Pre (2010--21) & Post (2022--24) \\\midrule
\multicolumn{3}{l}{\textit{Panel A. Alternative signal definition (composite)}}\\
Section-weighted (base) & +2.5 \tstat{1.58} & +14.6 \tstat{2.07} \\
Simple mean & +2.3 \tstat{1.50} & +13.4 \tstat{2.23} \\
Top-5\% tail & +1.5 \tstat{1.04} & +14.9 \tstat{2.47} \\
\midrule\multicolumn{3}{l}{\textit{Panel B. Alternative holding horizon}}\\
6-month forward return & -0.1 \tstat{-0.10} & +1.1 \\
24-month forward return & +9.3 \tstat{2.86} & +23.0 \\
\midrule\multicolumn{3}{l}{\textit{Panel C. Construction / universe}}\\
Sector-neutral composite & +2.3 \tstat{3.35} & +3.8 \tstat{0.84} \\
First principal component & +2.6 \tstat{2.25} & +13.4 \tstat{1.97} \\
Excl.\ Magnificent-7 & +1.7 \tstat{1.07} & +14.1 \tstat{1.92} \\
Excl.\ top-10 by market cap & --- & +14.5 \tstat{1.93} \\
\bottomrule
\end{tabular}
\tablelegend{This table assesses the robustness of the AI composite Q5$-$Q1 forward-return spread (in percent per year, with Newey--West $t$-statistics) across alternative research-design choices, reported separately for the pre-period (2010--2021) and post-period (2022--2024). Panel~A varies the signal definition (section-weighted mean, simple mean, top-5\% tail); Panel~B varies the holding horizon (6- and 24-month forward returns); and Panel~C varies the construction and universe (sector-neutralization, replacing the three signals with their first principal component, and excluding the Magnificent~7 or the ten largest firms by market capitalization). The post-ChatGPT spread is stable across signal definitions, grows with the horizon, survives the exclusion of mega-cap winners, and shrinks markedly only under sector-neutralization---locating much of the premium in a between-sector channel.}
\end{table}