\begin{table}[H]\centering
\caption{The Post-ChatGPT Structural Break}\label{tab:break}
\small
\begin{tabular}{lccc}\toprule
& \multicolumn{2}{c}{Q5$-$Q1 spread} & Interaction \\
\cmidrule(lr){2-3}
Signal & Pre (2010--21) & Post (2022--24) & AI$\times$Post (pp/SD) \\\midrule
AI adoption & +2.2 \tstat{2.04} & +14.3 \tstat{2.15} & +2.0 \tstat{1.17} \\
AI infrastructure & +1.4 \tstat{0.91} & +13.6 \tstat{2.44} & +2.8 \tstat{2.63} \\
AI composite & +2.5 \tstat{1.58} & +14.6 \tstat{2.07} & +2.7 \tstat{1.78} \\
\bottomrule
\end{tabular}
\tablelegend{This table quantifies the change in the pricing of AI disclosure around the November 2022 launch of ChatGPT. Columns~2--3 report the equal-weighted Q5$-$Q1 forward-return spread (in percent per year) separately for the pre-period (formation years 2010--2021, twelve annual spreads) and the post-period (2022--2024, three annual spreads), with Newey--West three-lag $t$-statistics computed on the annual spreads in parentheses; with three post-period observations these $t$-statistics are reported for completeness only, and Table~\ref{tab:postinf} provides the inference the paper relies on. Column~4 reports the coefficient $\beta_2$ of equation~\eqref{eq:break}---the change in the forward return per cross-sectional standard deviation of the signal after 2022, in percentage points---from a pooled OLS regression of the winsorized forward return with size and momentum controls and standard errors clustered by formation year (fifteen clusters). The interaction is positive for every signal and statistically significant only for AI infrastructure.}
\end{table}