spb/wp17_uqo

1\begin{table}[H]\centering2\caption{How Much Evidence Is There in the Post-ChatGPT Period?}\label{tab:postinf}3\small4\begin{tabular}{lcc}\toprule5\multicolumn{3}{l}{\textit{Panel A. Post-period cohorts (AI composite, EW Q5$-$Q1, \%)}}\\6& Spread & Post mean excluding this cohort \\\midrule7Cohort 2022 (holding July 2023--June 2024) & +9.3 & +17.2 \\8Cohort 2023 (holding July 2024--June 2025) & -4.0 & +23.8 \\9Cohort 2024 (holding July 2025--June 2026) & +38.4 & +2.6 \\10\midrule11Post-period mean (three cohorts) & +14.6 & \\12Pre-period mean (twelve cohorts; share positive 75\%) & +2.4 & \\13\midrule14\multicolumn{3}{l}{\textit{Panel B. Pooled firm-level tests (Q5 vs.\ Q1 firm-years, year dummies, SE clustered by firm)}}\\15& Spread (\%) & \textit{t} \\\midrule16Post cohorts 2022--2024 (raw returns), $n=594$ & +14.7 & 2.18 \\17Post cohorts 2022--2024 (winsorized returns) & +7.2 & 2.21 \\18Post cohorts 2022--2023 only, $n=394$ & +2.6 & 0.46 \\19Pre cohorts 2010--2021, $n=2{,}156$ & +2.5 & 1.84 \\20Post minus pre (interaction) & +12.1 & 1.79 \\21\bottomrule22\end{tabular}2324\vspace{0.6em}25{\footnotesize\begin{tabular}{lrrrrrrr}\toprule26\multicolumn{8}{l}{\textit{Panel C. Monthly long--short series (AI composite, EW, annually rebalanced)}}\\27Period & Months & Mean (\%/yr) & Sharpe & HAC \textit{t} & FF6 $\alpha$ (\%/yr) & FF6+TECH $\alpha$ & $\beta_{\text{TECH}}$ \\\midrule28Full sample & 180 & +2.4 & 0.45 & 1.55 & +1.9 \tstat{1.24} & +0.4 \tstat{0.36} & 0.35 \tstat{11.11} \\29Pre-ChatGPT & 144 & +1.1 & 0.22 & 0.67 & +1.0 \tstat{0.59} & -0.4 \tstat{-0.29} & 0.35 \tstat{10.51} \\30Post-ChatGPT & 36 & +7.5 & 1.32 & 2.20 & +5.2 \tstat{1.72} & +1.9 \tstat{0.86} & 0.47 \tstat{6.53} \\31\bottomrule32\end{tabular}}33\tablelegend{Panel~A reports the equal-weighted Q5$-$Q1 forward-return spread on the AI composite for each post-ChatGPT formation cohort and the post-period mean obtained when that cohort is dropped. Panel~B pools the firm-years in the top and bottom quintiles and regresses the forward return on a top-quintile indicator and formation-year dummies, with standard errors clustered by firm; the last row interacts the indicator with a post-2022 dummy in the pooled pre- and post-period sample. Panel~C describes the monthly return of the self-financing high-minus-low portfolio in each sub-period (the post-period starts in July 2023, the first holding month of the 2022 cohort); the HAC $t$-statistic tests the mean with Newey--West (three-lag) errors; FF6 is the Fama--French five-factor model plus momentum; TECH is the equal-weighted return of the Information Technology constituents in the panel minus the equal-weighted return of all constituents, and $\beta_{\text{TECH}}$ its loading. Factor regressions use the 34 (post) and 144 (pre) months for which the French factors are available. Source: \texttt{scripts/11\_review\_reanalysis.py}.}34\end{table}