Infrastructure vs Regulatory Shocks: Asymmetric Volatility Response in Cryptocurrency Markets

Infrastructure vs Regulatory Shocks: Asymmetric Volatility Response in Cryptocurrency Markets | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Infrastructure vs Regulatory Shocks: Asymmetric Volatility Response in Cryptocurrency Markets Murad Farzulla This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8323026/v1 This work is licensed under a CC BY 4.0 License Status: Under Revision Version 1 posted 9 You are reading this latest preprint version Abstract Infrastructure failures generate 5.7 \((\times)\) larger volatility shocks than regulatory announcements in cryptocurrency markets (2.385% vs 0.419%, \((p=0.0008)\) , Cohen's \((d=2.753)\) ), challenging assumptions that ``all bad news is equivalent'' for portfolio risk management. This asymmetry is robust across six major cryptocurrencies (January 2019--August 2025), multiple statistical tests, and validation approaches including Bayesian inference (Bayes Factors \((>)\) 10 for 4/6 assets), machine learning clustering, network spillover analysis, and Markov regime-switching models.We analyze 50 major events using GJR-GARCH-X models incorporating infrastructure disruptions (exchange outages, protocol exploits, network failures) and regulatory announcements (enforcement actions, policy changes) as exogenous variance drivers. A novel GDELT sentiment decomposition separates regulatory from infrastructure-related news coverage, enabling event-specific sentiment analysis.Critically, even degraded sentiment proxies---weekly aggregation creating 7-day temporal mismatch with daily volatility, 7% missing values, and systematic negative bias---improve model fit for 83% of assets. This suggests sentiment's true information content is substantially underestimated in our results: cryptocurrency markets appear sufficiently sentiment-driven that any reasonable proxy captures tradeable signal, implying higher-frequency sentiment data would yield considerably stronger effects.Network analysis reveals ETH, not BTC, serves as the primary systemic risk hub (eigenvector centrality 0.89 vs 0.71), challenging conventional assumptions about Bitcoin dominance. Regime-switching models detect 5 \((\times)\) sensitivity amplification during crisis periods ( \((F=45.23)\) , \((p<0.001)\) ), with infrastructure sensitivity increasing from 2.3% to 11.2% during market stress---implying traditional VaR models assuming linear risk scaling catastrophically underestimate tail risk.Portfolio managers should allocate 4--5 \((\times)\) higher capital buffers for infrastructure events. The near-integrated volatility persistence ( \((\alpha+\beta \approx 0.999)\) ) suggests cryptocurrency markets operate in a distinct regime where shocks become absorbed into long-memory processes, posing fundamental challenges for traditional risk management frameworks. Cryptocurrency Volatility Event study GJR-GARCH-X Infrastructure risk Regulatory uncertainty Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Revision Version 1 posted Editorial decision: Revision requested 19 Feb, 2026 Reviews received at journal 19 Feb, 2026 Reviewers agreed at journal 07 Jan, 2026 Reviews received at journal 06 Jan, 2026 Reviewers agreed at journal 06 Jan, 2026 Reviewers invited by journal 17 Dec, 2025 Editor assigned by journal 12 Dec, 2025 Submission checks completed at journal 10 Dec, 2025 First submitted to journal 09 Dec, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8323026","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":557985835,"identity":"263e73d9-b62d-476b-9b66-cfdfdd440ba5","order_by":0,"name":"Murad 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Markets","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"digital-finance","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"dfin","sideBox":"Learn more about [Digital Finance](http://link.springer.com/journal/42521)","snPcode":"42521","submissionUrl":"https://submission.nature.com/new-submission/42521/3","title":"Digital Finance","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Cryptocurrency, Volatility, Event study, GJR-GARCH-X, Infrastructure risk, Regulatory uncertainty","lastPublishedDoi":"10.21203/rs.3.rs-8323026/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8323026/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eInfrastructure failures generate 5.7\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\((\\times)\\)\u003c/span\u003e\u003c/span\u003e larger volatility shocks than regulatory announcements in cryptocurrency markets (2.385% vs 0.419%, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\((p=0.0008)\\)\u003c/span\u003e\u003c/span\u003e, Cohen's \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\((d=2.753)\\)\u003c/span\u003e\u003c/span\u003e), challenging assumptions that ``all bad news is equivalent'' for portfolio risk management. This asymmetry is robust across six major cryptocurrencies (January 2019--August 2025), multiple statistical tests, and validation approaches including Bayesian inference (Bayes Factors \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\((\u0026gt;)\\)\u003c/span\u003e\u003c/span\u003e10 for 4/6 assets), machine learning clustering, network spillover analysis, and Markov regime-switching models.We analyze 50 major events using GJR-GARCH-X models incorporating infrastructure disruptions (exchange outages, protocol exploits, network failures) and regulatory announcements (enforcement actions, policy changes) as exogenous variance drivers. A novel GDELT sentiment decomposition separates regulatory from infrastructure-related news coverage, enabling event-specific sentiment analysis.Critically, even degraded sentiment proxies---weekly aggregation creating 7-day temporal mismatch with daily volatility, 7% missing values, and systematic negative bias---improve model fit for 83% of assets. This suggests sentiment's true information content is substantially \u003cem\u003eunderestimated\u003c/em\u003e in our results: cryptocurrency markets appear sufficiently sentiment-driven that any reasonable proxy captures tradeable signal, implying higher-frequency sentiment data would yield considerably stronger effects.Network analysis reveals ETH, not BTC, serves as the primary systemic risk hub (eigenvector centrality 0.89 vs 0.71), challenging conventional assumptions about Bitcoin dominance. Regime-switching models detect 5\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\((\\times)\\)\u003c/span\u003e\u003c/span\u003e sensitivity amplification during crisis periods (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\((F=45.23)\\)\u003c/span\u003e\u003c/span\u003e, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\((p\u0026lt;0.001)\\)\u003c/span\u003e\u003c/span\u003e), with infrastructure sensitivity increasing from 2.3% to 11.2% during market stress---implying traditional VaR models assuming linear risk scaling catastrophically underestimate tail risk.Portfolio managers should allocate 4--5\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\((\\times)\\)\u003c/span\u003e\u003c/span\u003e higher capital buffers for infrastructure events. The near-integrated volatility persistence (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\((\\alpha+\\beta \\approx 0.999)\\)\u003c/span\u003e\u003c/span\u003e) suggests cryptocurrency markets operate in a distinct regime where shocks become absorbed into long-memory processes, posing fundamental challenges for traditional risk management frameworks.\u003c/p\u003e","manuscriptTitle":"Infrastructure vs Regulatory Shocks: Asymmetric Volatility Response in Cryptocurrency Markets","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-12-11 14:17:26","doi":"10.21203/rs.3.rs-8323026/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-02-19T11:24:11+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-02-19T09:26:19+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"92583628548380163585554883931741056912","date":"2026-01-07T07:47:49+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-01-06T21:44:16+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"279356103403483550835412815663323978945","date":"2026-01-06T16:40:58+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-12-17T20:43:14+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-12-12T09:03:18+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-12-11T04:59:05+00:00","index":"","fulltext":""},{"type":"submitted","content":"Digital Finance","date":"2025-12-10T04:51:49+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"digital-finance","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"dfin","sideBox":"Learn more about [Digital Finance](http://link.springer.com/journal/42521)","snPcode":"42521","submissionUrl":"https://submission.nature.com/new-submission/42521/3","title":"Digital Finance","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"15b65883-8d6e-4e72-8de3-9a7f39c998ab","owner":[],"postedDate":"December 11th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"in-revision","subjectAreas":[],"tags":[],"updatedAt":"2026-02-19T11:38:23+00:00","versionOfRecord":[],"versionCreatedAt":"2025-12-11 14:17:26","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8323026","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8323026","identity":"rs-8323026","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}