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1%% International Review of Financial Analysis — submission manuscript2%% Elsevier elsarticle class, author-year (harvard) references.3\documentclass[preprint,12pt,authoryear]{elsarticle}45\usepackage{amsmath,amssymb}6\usepackage{booktabs}7\usepackage{threeparttable}8\usepackage{adjustbox}9\usepackage{caption}10\captionsetup{font=small,labelfont=bf}11\usepackage[hidelinks]{hyperref}12\graphicspath{{figures/}}13\biboptions{round}1415\IfFileExists{results_macros.tex}{\input{results_macros.tex}}{}1617\journal{International Review of Financial Analysis}1819\begin{document}2021\begin{frontmatter}2223\title{Faster, Wider, More Fragile? The Evolution of Intraday Shock24Propagation in U.S. Equity Markets, 1992--2026}2526\author{[Author identity withheld for review]}2728\begin{abstract}29We study how intraday shocks travel across U.S.\ equities using30\DataRowsBn{} billion one-minute bars covering the full listed and delisted31cross-section from 1992 to 2026. Three findings emerge. First, isolated32idiosyncratic shocks barely spread: across \NEventsRealMM{} million33$\pm6\sigma$ one-minute events, the abnormal share of other securities with34an extreme standardized return, measured against matched within-stock35placebos, lies between zero and about \StratShareOfBase\% of its base rate at36horizons of 1 to 120 minutes, in every decade. Second, transmission is37concentrated and has intensified: the shocked stock's twenty closest38lagged-correlation neighbors respond (+\NetDiffFive$\times10^{-4}$ in the39probability of an extreme move at five minutes), and this network channel40roughly tripled between the 1990s and the 2020s while market-wide spillover41stayed bounded near zero---a rise that partly reflects sharper identification42of the network as the Epps effect receded. Third, common information is43impounded far faster (one-minute pairwise correlation \EppsNinetySixOne{} in441996 versus \EppsFifteenOne{} in 2015), ordinary extreme minutes became an45order of magnitude rarer after decimalization, and severe co-jump46minutes---more than a tenth of the universe moving together---are roughly47ten times more frequent in 2008 and 2020 than in calm years. Modern markets48absorb the idiosyncratic, transmit it narrowly along statistical linkages,49and synchronize on the systemic.50\end{abstract}5152\begin{keyword}53Intraday shock propagation \sep market fragility \sep high-frequency data \sep54contagion \sep co-jumps \sep Epps effect \sep market microstructure55\JEL G10 \sep G12 \sep G1456\end{keyword}5758\end{frontmatter}5960\input{sections/01_introduction}61\input{sections/02_literature}62\input{sections/03_data}63\input{sections/04_measurement}64\input{sections/05_empirical_design}65\input{sections/06_results}66\input{sections/07_mechanisms}67\input{sections/08_robustness}68\input{sections/09_conclusion}69\clearpage7071\section*{Declaration of competing interest}72The author declares no known competing financial interests or personal73relationships that could have appeared to influence the work reported in this74paper.7576\section*{Data availability}77The underlying market data were originally sourced from Finnhub.io78(\url{https://finnhub.io}). The aggregated monthly archive used in this study79is publicly accessible but carries no explicit licence; the minute data are80therefore not redistributed. The exact pinned snapshot identifier and81checksums, the full replication code, the event-level estimates, and all82machine-readable results accompany the paper.8384\bibliographystyle{elsarticle-harv}85\bibliography{bibliography/references}8687\end{document}88