Stock market tumble sparks crypto chaos: A crash risk spillover analysis

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dc.authorid0000-0002-5131-577X
dc.authorid0000-0002-5738-7563
dc.authorid0000-0002-7340-3551
dc.authorid0000-0001-9969-5903
dc.contributor.authorKhan, Asad ul Islam
dc.contributor.authorÖzcan, Rasim
dc.contributor.authorAbdul Rahman, Mutawakil
dc.contributor.authorWaheed, Abdul
dc.contributor.otherYönetim Bilimleri Fakültesi, İktisat Bölümü
dc.date.accessioned2024-08-08T06:25:33Z
dc.date.available2024-08-08T06:25:33Z
dc.date.issued2024
dc.departmentİHÜ, Yönetim Bilimleri Fakültesi, İktisat Bölümü
dc.departmentİHÜ, Lisansüstü Eğitim Enstitüsü, İktisat Ana Bilim Dalı
dc.description.abstractThe study employs an empirical Bayesian estimation approach to examine how the crash risk of the G-7 (United States [US], United Kingdom [UK], Japan, Germany, Canada, and France excluding Italy) and Chinese equity markets affects the crash risk of the top 11 cryptocurrencies. Two crash risk measures were adopted to determine the monthly crash risk of the two types of markets, which are the most appropriate for skewed returns. Four separate models were estimated using the empirical Bayes estimation method because it considers heterogeneity, is more efficient than least squares, and facilitates more accurate coefficient estimation. The results reveal that the German stock market's crash risks are significantly and contemporaneously associated with the crash risk of all 11 cryptocurrencies, indicating that the German equity market is not a reliable diversifier for cryptocurrencies. The crash risks of the US, UK, and Japanese (German and Canadian) equity markets have a positive (negative) impact on the crash risk of cryptocurrency markets with a one-month lag. Generally, lagged crash risks have a more substantial influence on cryptocurrency crash risk, suggesting that historical crashes in equity markets are better predictors of cryptocurrency crashes. The one-month significant delay effect may present arbitrage opportunities because the risk of crashes in stock markets may signal potential crashes in cryptocurrencies one month in advance. A series of robustness checks confirmed the results of the analysis and the validity of our conclusions. These findings suggest that crypto investors and policy-makers should pay attention to historical events in equity markets. Investors and portfolio managers in the cryptocurrency market should monitor unexpected fluctuations in the stock market, particularly significant declines that could result in significant losses in the future.
dc.identifier.citationKhan, A. I., Özcan, R., Abdul Rahman, M. ve Waheed, A. (2024). Stock market tumble sparks crypto chaos: A crash risk spillover analysis. Regional Statistics, 14(3), 540-565. https://www.doi.org/10.15196/RS140306
dc.identifier.doi10.15196/RS140306
dc.identifier.endpage565
dc.identifier.issn2063-9538
dc.identifier.issue3
dc.identifier.scopus2-s2.0-85197250146
dc.identifier.scopusqualityQ1
dc.identifier.startpage540
dc.identifier.urihttps://www.doi.org/10.15196/RS140306
dc.identifier.urihttps://hdl.handle.net/20.500.12154/2935
dc.identifier.volume14
dc.indekslendigikaynakScopus
dc.institutionauthorKhan, Asad ıl Islam
dc.institutionauthorAbdul Rahman, Mutawakil
dc.institutionauthorid0000-0002-5131-577X
dc.institutionauthorid0000-0002-7340-3551
dc.language.isoen
dc.publisherHungarian Central Statistical Office
dc.relation.ispartofRegional Statistics
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.relation.publicationcategoryÖğrenci
dc.rightsinfo:eu-repo/semantics/openAccess
dc.subjectBayesian Estimation
dc.subjectCrash Risk
dc.subjectCryptocurrency
dc.subjectSpillover
dc.subjectStock Market
dc.titleStock market tumble sparks crypto chaos: A crash risk spillover analysis
dc.typeArticle
dspace.entity.typePublication
relation.isAuthorOfPublication5d56d061-267c-4b33-8b78-b50e651ee5aa
relation.isAuthorOfPublication.latestForDiscovery5d56d061-267c-4b33-8b78-b50e651ee5aa
relation.isOrgUnitOfPublication9d1809d1-3541-41aa-94ed-639736b7e16f
relation.isOrgUnitOfPublication.latestForDiscovery9d1809d1-3541-41aa-94ed-639736b7e16f

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