\begin{table}[H]\centering
\caption{Risk-Adjusted Performance of the AI Long--Short Portfolio}\label{tab:alpha}
\small
\begin{tabular}{lrrrrr}\toprule
& Mean LS & CAPM $\alpha$ & \textit{t} & FF6 $\alpha$ & \textit{t} \\
Signal & (\%/yr) & (\%/yr) & & (\%/yr) & \\\midrule
AI adoption & +2.1 & +1.5 & 1.08 & +2.0 & 1.46 \\
AI infrastructure & +1.7 & +0.9 & 0.61 & +1.1 & 0.84 \\
AI composite & +2.3 & +1.4 & 0.85 & +1.9 & 1.24 \\
AI disruption risk & +3.0 & +2.1 & 1.38 & +2.8 & 2.10 \\
\bottomrule
\end{tabular}
\tablelegend{This table reports the risk-adjusted performance of the equal-weighted high-minus-low (Q5$-$Q1) long--short portfolio formed on each AI signal and rebalanced annually, over the full sample (178 monthly return observations). \emph{Mean LS} is the average raw long--short return; \emph{CAPM}~$\alpha$ and \emph{FF6}~$\alpha$ are the intercepts from time-series regressions of the long--short return on the CAPM market factor and on the Fama--French five factors plus momentum, respectively. All means and alphas are annualized and expressed in percent per year. The $t$-statistics are based on Newey--West (three-lag) heteroskedasticity- and autocorrelation-consistent standard errors. Over the full sample the alphas are economically small and, with the marginal exception of AI disruption risk, statistically insignificant.}
\end{table}