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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 facts emerge. First, markets absorb32idiosyncratic shocks: across \NEventsRealMM{} million isolated $\pm6\sigma$33one-minute events, abnormal market-wide propagation---measured against matched34within-stock placebos---is economically zero at horizons of 1 to 120 minutes,35in every decade. Second, transmission is concentrated and has intensified:36the shocked stock's twenty closest lagged-correlation neighbors respond37strongly (+\NetDiffFive$\times10^{-4}$ abnormal jump probability at five38minutes), and this network channel tripled between the 1990s and the 2020s39while market-wide spillover stayed at zero. Third, tail synchronization40migrated to the market-wide minute: ordinary extreme minute returns became41roughly \ExtremeDropFactor{} times less frequent than in the 1990s, the Epps42curve flattened (one-minute pairwise correlation \EppsNinetySixOne{} in 199643versus \EppsFifteenOne{} in 2015), and severe co-jump minutes spike by orders44of magnitude in 2008 and 2020. Modern markets absorb the idiosyncratic and45transmit the systemic.46\end{abstract}4748\begin{keyword}49Intraday shock propagation \sep market fragility \sep high-frequency data \sep50contagion \sep co-jumps \sep Epps effect \sep market microstructure51\JEL G10 \sep G12 \sep G1452\end{keyword}5354\end{frontmatter}5556\input{sections/01_introduction}57\input{sections/02_literature}58\input{sections/03_data}59\input{sections/04_measurement}60\input{sections/05_empirical_design}61\input{sections/06_results}62\input{sections/07_mechanisms}63\input{sections/08_robustness}64\input{sections/09_conclusion}6566\section*{Declaration of competing interest}67The author declares no known competing financial interests or personal68relationships that could have appeared to influence the work reported in this69paper.7071\section*{Data availability}72The underlying market data were originally sourced from Finnhub.io73(\url{https://finnhub.io}). The aggregated monthly archive used in this study is publicly accessible;74the exact pinned snapshot, full replication code, manifests, checksums, and75machine-readable results accompany the paper.7677\bibliographystyle{elsarticle-harv}78\bibliography{bibliography/references}7980\end{document}81