Publicación:
A comparison of market risk measures from a twofold perspective: accurate and loss function

dc.contributor.authorBenito Muela, Sonia
dc.contributor.authorLópez Martín, Carmen
dc.contributor.authorArguedas Sanz, Raquel
dc.date.accessioned2024-05-20T11:24:15Z
dc.date.available2024-05-20T11:24:15Z
dc.date.issued2023-06-04
dc.description.abstractUnder the new regulation based on Basel solvency framework, known as Basel III and Basel IV, financial institutions must calculate the market risk capital requirements based on the Expected Shortfall (ES) measure, replacing the Value at Risk (VaR) measure. In the financial literature, there are many papers dedicated to compare VaR approaches but there are few studies focusing in comparing ES approaches. To cover this gap, we have carried out a comprenhensive comparative of VaR and ES models applied to IBEX-35 stock index. The comparison has been carried out from a twofold perspective: accurate risk measure and loss functions. The results indicate that the method based on the conditional Extreme Value Theory (EVT) is the best in estimating market risk, outperforming Parametric method and Filter Historical Simulation.en
dc.description.versionversión publicada
dc.identifier.doihttps://doi.org/10.35944/jofrp.2022.11.1.005
dc.identifier.issn2305-7394
dc.identifier.urihttps://hdl.handle.net/20.500.14468/11905
dc.journal.titleACRN Journal of Finance and Risk Perspectives
dc.journal.volume11
dc.language.isoen
dc.publisherElsevier
dc.relation.centerFacultad de Ciencias Económicas y Empresariales
dc.relation.departmentEconomía de la Empresa y Contabilidad
dc.rightsinfo:eu-repo/semantics/openAccess
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/deed.es
dc.titleA comparison of market risk measures from a twofold perspective: accurate and loss functiones
dc.typejournal articleen
dc.typeartículoes
dspace.entity.typePublication
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relation.isAuthorOfPublicationc97e2d29-4ce5-49e3-b864-9810ead93be6
relation.isAuthorOfPublication5caf1cb0-3213-4235-ae2e-9dfe4bea1889
relation.isAuthorOfPublication.latestForDiscovery01b4ab6d-1510-434b-b108-29b4cc8746f0
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