\begin{table}[H]\centering
\caption{Portfolio Sorts on AI Disclosure}\label{tab:sorts}
\small
\begin{tabular}{lrrrrrrr}\toprule
Signal (weighting) & Q1 & Q2 & Q3 & Q4 & Q5 & Q5$-$Q1 & \textit{t} \\\midrule
AI adoption (EW) & 16.2 & 17.9 & 19.1 & 18.6 & 20.8 & +4.6 & 1.83 \\
\quad value-weighted & 12.8 & 15.6 & 19.1 & 16.9 & 15.4 & +2.6 & 0.84 \\
AI infrastructure (EW) & 16.8 & 18.4 & 17.3 & 19.6 & 20.6 & +3.9 & 1.58 \\
\quad value-weighted & 11.4 & 18.2 & 15.0 & 20.0 & 16.9 & +5.5 & 2.01 \\
AI disruption risk (EW) & 16.1 & 18.7 & 17.2 & 19.2 & 21.4 & +5.3 & 2.27 \\
\quad value-weighted & 13.7 & 17.6 & 16.7 & 17.1 & 17.6 & +3.9 & 1.74 \\
\midrule
AI composite (EW) & 16.1 & 19.0 & 17.3 & 19.2 & 21.0 & +4.9 & 1.88 \\
\quad value-weighted & 11.7 & 17.8 & 16.2 & 19.5 & 16.6 & +4.9 & 1.61 \\
\bottomrule
\end{tabular}
\tablelegend{This table reports mean forward 12-month returns (in percent) for portfolios sorted into quintiles on each within-year standardized AI-disclosure signal, over the full sample of formation years 2010--2024 (equation~\eqref{eq:spread}). For each signal we report both the equal-weighted (EW) and value-weighted portfolio returns; Q1 is the lowest-disclosure quintile and Q5 the highest. The column Q5$-$Q1 is the high-minus-low spread, and \textit{t} is its Newey--West (three-lag) $t$-statistic computed on the time series of 15 annual spreads. Equal-weighted spreads that exceed their value-weighted counterparts indicate that the relation is stronger among smaller index members.}
\end{table}