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1% ============================================================================2% UQO Working Paper No. 63% Intraday Volatility Transmission Across Asset Classes:4% A Connectedness Analysis of Equities, Fixed Income, Commodities,5% and Cryptocurrencies6% ============================================================================7\documentclass[12pt,letterpaper]{article}89% --- Encoding & Language ---10\usepackage[utf8]{inputenc}11\usepackage[T1]{fontenc}12\usepackage[english]{babel}1314% --- Page Layout ---15\usepackage[16 letterpaper,17 top=1in, bottom=1in, left=1in, right=1in,18 headheight=15pt19]{geometry}20\usepackage{setspace}21\onehalfspacing2223% --- Typography ---24\usepackage{newtxtext,newtxmath}25\usepackage{microtype}2627% --- Math ---28\usepackage{amsmath}29\let\Bbbk\relax30\usepackage{amssymb,amsfonts}31\usepackage{mathtools}3233% --- Tables ---34\usepackage{booktabs}35\usepackage{tabularx}36\usepackage{multirow}37\usepackage{threeparttable}38\usepackage{array}39\usepackage{adjustbox}40\usepackage{longtable}41\usepackage{dcolumn}42\newcolumntype{d}[1]{D{.}{.}{#1}}4344% --- Figures ---45\usepackage{graphicx}46\usepackage{float}47\usepackage[48 font = small,49 labelfont = bf,50 labelsep = period,51 skip = 6pt,52 justification = justified,53 singlelinecheck = false54]{caption}55\usepackage{subcaption}5657% --- Lists ---58\usepackage{enumitem}59\setlist{nosep,leftmargin=*}6061% --- Colors & Links ---62\usepackage[dvipsnames,table]{xcolor}63\usepackage[bookmarks, bookmarksnumbered]{hyperref}64\hypersetup{65 colorlinks = true,66 linkcolor = NavyBlue,67 citecolor = NavyBlue,68 urlcolor = NavyBlue,69 pdfauthor = {Simon-Pierre Boucher},70 pdftitle = {Intraday Volatility Transmission Across Asset Classes},71 pdfsubject = {Working Paper WP6},72 pdfkeywords = {realized volatility, spillovers, connectedness, high-frequency}73}74\usepackage{cleveref}7576% --- Landscape & Rotation ---77\usepackage{pdflscape}78\usepackage{rotating}7980% --- Bibliography ---81\usepackage{natbib}82\setcitestyle{authoryear,round,semicolon}83\bibliographystyle{apalike}8485% --- Headers & Footers ---86\usepackage{fancyhdr}87\pagestyle{fancy}88\fancyhf{}89\fancyhead[L]{\small\itshape Intraday Volatility Transmission}90\fancyhead[R]{\small\thepage}91\renewcommand{\headrulewidth}{0.4pt}92\renewcommand{\footrulewidth}{0pt}93\fancypagestyle{plain}{%94 \fancyhf{}95 \fancyfoot[C]{\small\thepage}96 \renewcommand{\headrulewidth}{0pt}97}9899% --- Section Formatting ---100\usepackage{titlesec}101\titleformat{\section}{\large\bfseries}{\thesection.}{0.5em}{}102\titleformat{\subsection}{\normalsize\bfseries}{\thesubsection.}{0.5em}{}103\titleformat{\subsubsection}{\normalsize\itshape}{\thesubsubsection.}{0.5em}{}104\titlespacing*{\section}{0pt}{18pt}{8pt}105\titlespacing*{\subsection}{0pt}{12pt}{4pt}106\titlespacing*{\subsubsection}{0pt}{10pt}{3pt}107108% --- Footnotes ---109\usepackage[bottom,hang]{footmisc}110\setlength{\footnotemargin}{0.5em}111112% --- Appendix ---113\usepackage{apptools}114\AtAppendix{%115 \renewcommand{\thetable}{A\arabic{table}}%116 \setcounter{table}{0}%117 \renewcommand{\thefigure}{A\arabic{figure}}%118 \setcounter{figure}{0}%119 \renewcommand{\theequation}{A.\arabic{equation}}%120 \setcounter{equation}{0}%121}122123% --- Graphics Path ---124\graphicspath{{figures/}}125126% --- Custom Commands ---127\newcommand{\RV}{\mathrm{RV}}128\newcommand{\GFEVD}{\mathrm{GFEVD}}129\newcommand{\TSI}{\mathrm{TSI}}130\newcommand{\ie}{\textit{i.e.}}131\newcommand{\eg}{\textit{e.g.}}132\newcommand{\etal}{\textit{et al.}}133134% --- Significance Stars ---135\newcommand{\sym}[1]{\ensuremath{^{#1}}}136\newcommand{\stmark}{\sym{***}}137\newcommand{\smark}{\sym{**}}138\newcommand{\tmark}{\sym{*}}139140% ============================================================================141% METADATA142% ============================================================================143\newcommand{\WPnumber}{6}144\newcommand{\WPtitle}{Intraday Volatility Transmission Across Asset Classes: A Connectedness Analysis of Equities, Fixed Income, Commodities, and Cryptocurrencies}145\newcommand{\WPsubtitle}{}146\newcommand{\WPdate}{May 2026}147\newcommand{\WPversion}{1.0}148\newcommand{\WPabstract}{%149This paper investigates intraday volatility transmission across equities, foreign exchange, commodities, and cryptocurrency markets using 5-minute OHLCV data spanning 2008--2026. We construct daily realized volatility measures from over 235 million intraday observations across 10 representative instruments and apply the \citet{DieboldYilmaz2012} generalized variance decomposition framework within a VAR(4) model at a 10-day forecast horizon. Our full-sample analysis reveals a total spillover index of 55.44\%, with U.S.\ equity index futures (ES, NQ) serving as the dominant volatility transmitters (net spillovers of $+26.80\%$ and $+19.72\%$, respectively), while the VIX acts primarily as a volatility receiver ($-23.37\%$). Cryptocurrencies (BTC, ETH) remain largely isolated from traditional asset volatility networks, with own-shock contributions exceeding 77\%. Rolling 200-day connectedness analysis uncovers substantial time variation, with the total spillover index peaking at 81.55\% during the February 2018 volatility implosion. Regime-specific analysis reveals dramatic shifts in the volatility hierarchy: during the COVID-19 crash, USD/JPY emerges as the dominant shock originator ($+60.29\%$), while equity futures flip from transmitters to receivers. During the 2022 rate-hiking cycle, Bitcoin transitions to a net volatility transmitter ($+7.90\%$), suggesting growing integration of crypto markets with the traditional financial system. Intraday analysis of trading sessions shows that Bitcoin maintains near-uniform volatility across Asian, European, and U.S.\ hours, contrasting sharply with the session-dependent patterns of equity and VIX markets. Granger causality tests confirm that equity futures significantly lead VIX changes ($F=19.86$, $p<0.001$), while crypto markets remain causally independent. These findings have important implications for portfolio construction, risk management, and the monitoring of systemic risk across increasingly interconnected global markets.%150}151\newcommand{\WPkeywords}{realized volatility, volatility spillovers, Diebold--Yilmaz connectedness, high-frequency data, cross-asset transmission, cryptocurrency, systemic risk}152\newcommand{\WPjel}{C32, C58, G12, G15, G17}153154% --- Author ---155\newcommand{\WPauthor}{Simon-Pierre Boucher}156\newcommand{\WPaffiliation}{%157 D\'epartement des sciences administratives\\158 Universit\'e du Qu\'ebec en Outaouais%159}160\newcommand{\WPemail}{simon-pierre.boucher@uqo.ca}161\newcommand{\WPaddress}{%162 Gatineau -- Pavillon Alexandre-Tach\'e\\163 283, boulevard Alexandre-Tach\'e\\164 Gatineau, Qu\'ebec, Canada J9A 1L8%165}166167% ============================================================================168% DOCUMENT169% ============================================================================170\begin{document}171172% --- Title Page ---173\input{sections/titlepage}174175% --- Table of Contents ---176\setcounter{page}{1}177\tableofcontents178\newpage179180% --- Main Body ---181\input{sections/introduction}182\input{sections/literature}183\input{sections/methodology}184\input{sections/data}185\input{sections/results}186\input{sections/discussion}187\input{sections/conclusion}188189% --- References ---190\input{sections/references}191192% --- Appendix ---193\newpage194\appendix195\input{appendix/appendix}196197\end{document}198