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dc.contributor.authorLiu, J
dc.contributor.authorSong, Q
dc.contributor.authorQi, Y
dc.contributor.authorRahman, Sanzidur
dc.contributor.authorSriboonchitta, S
dc.date.accessioned2020-05-16T13:30:30Z
dc.date.available2020-05-16T13:30:30Z
dc.date.issued2020-05-14
dc.identifier.issn2071-1050
dc.identifier.issn2071-1050
dc.identifier.otherARTN 4000
dc.identifier.urihttp://hdl.handle.net/10026.1/15686
dc.descriptionNo embargo required
dc.description.abstract

<jats:p>The global financial crisis in 2008 spurred the need to study systemic risk in financial markets, which is of interest to both academics and practitioners alike. We first aimed to measure and forecast systemic risk in global financial markets and then to construct a trade decision model for investors and financial institutions to assist them in forecasting risk and potential returns based on the results of the analysis of systemic risk. The factor copula-generalized autoregressive conditional heteroskedasticity (GARCH) models and component expected shortfall (CES) were combined for the first time in this study to measure systemic risk and the contribution of individual countries to global systemic risk in global financial markets. The use of factor copula-based models enabled the estimation of joint models in stages, thereby considerably reducing computational burden. A high-dimensional dataset of daily stock market indices of 43 countries covering the period 2003 to 2019 was used to represent global financial markets. The CES portfolios developed in this study, based on the forecasting results of systemic risk, not only allow spreading of systemic risk but may also enable investors and financial institutions to make profits. The main policy implication of our study is that forecasting systemic risk of global financial markets and developing portfolios can provide valuable insights for financial institutions and policy makers to diversify portfolios and spread risk for future investments and trade.</jats:p>

dc.format.extent4000-4000
dc.languageen
dc.language.isoen
dc.publisherMDPI AG
dc.subjectstock markets
dc.subjectfactor copula
dc.subjectdependence
dc.subjectforecasting risk
dc.subjectfinancial crisis
dc.titleMeasurement of Systemic Risk in Global Financial Markets and Its Application in Forecasting Trading Decisions
dc.typejournal-article
dc.typeJournal Article
plymouth.author-urlhttps://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000543421400058&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=11bb513d99f797142bcfeffcc58ea008
plymouth.issue10
plymouth.volume12
plymouth.publication-statusPublished online
plymouth.journalSustainability
dc.identifier.doi10.3390/su12104000
plymouth.organisational-group/Plymouth
plymouth.organisational-group/Plymouth/Faculty of Arts, Humanities and Business
plymouth.organisational-group/Plymouth/Users by role
dcterms.dateAccepted2020-05-09
dc.rights.embargodate2020-5-28
dc.identifier.eissn2071-1050
dc.rights.embargoperiodNot known
rioxxterms.versionofrecord10.3390/su12104000
rioxxterms.licenseref.urihttp://www.rioxx.net/licenses/all-rights-reserved
rioxxterms.licenseref.startdate2020-05-14
rioxxterms.typeJournal Article/Review


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