Please use this identifier to cite or link to this item: https://scholarhub.balamand.edu.lb/handle/uob/3592
DC FieldValueLanguage
dc.contributor.advisorAssaf, Ataen_US
dc.contributor.authorSleiman, Nicoleen_US
dc.date.accessioned2020-12-23T14:37:07Z-
dc.date.available2020-12-23T14:37:07Z-
dc.date.issued2020-
dc.identifier.urihttps://scholarhub.balamand.edu.lb/handle/uob/3592-
dc.descriptionIncludes bibliographical references (p. 43-47).en_US
dc.description.abstractThis paper attempts to compute the risk measures in cryptocurrency market using extreme value theory. The extreme market value theory focuses on extreme and rare events that happened in each cryptocurrency in order to calculate the extreme risk measures such as the Value at Risk and the Expected Shortfall. In this paper, the extreme value theory was successfully applied to the cryptocurrency market log returns, and the VaR and ES was successfully predicted. The study was done on seven cryptocurrencies from August 2014 to March 2019. The major findings of this paper are 1-) The VaR, ES and other risk measures estimations using historical simulation, show that Monero, Bitshares, Stellar and Ripple have the highest VaR and the highest ES at 1% and 5% significance. 2-) The extreme value theory was successfully applied and showed that Stellar, Ripple, and Bitshares enclosed the highest VaR and ES at 95% and 99% confidence interval.en_US
dc.description.statementofresponsibilityby Nicole Sleimanen_US
dc.format.extentvii, 47 p. :ill., tables ;30 cmen_US
dc.language.isoengen_US
dc.rightsThis object is protected by copyright, and is made available here for research and educational purposes. Permission to reuse, publish, or reproduce the object beyond the personal and educational use exceptions must be obtained from the copyright holderen_US
dc.subject.lcshCryptocurrenciesen_US
dc.subject.lcshElectronic commerceen_US
dc.subject.lcshDissertations, Academicen_US
dc.subject.lcshUniversity of Balamand--Dissertationsen_US
dc.titleMeasures of risk in cryptocurrency market using extreme value theoryen_US
dc.typeProjecten_US
dc.contributor.departmentDepartment of Business Administrationen_US
dc.contributor.facultyFaculty of Business and Managementen_US
dc.contributor.institutionUniversity of Balamanden_US
dc.date.catalogued2020-01-24-
dc.description.degreeMaster of Science in Accounting and Finance (MSAF)en_US
dc.description.statusPublisheden_US
dc.identifier.ezproxyURLhttp://ezsecureaccess.balamand.edu.lb/login?url=http://olib.balamand.edu.lb/projects_and_theses/GP-MBA-195.pdfen_US
dc.identifier.OlibID248473-
dc.provenance.recordsourceOliben_US
Appears in Collections:UOB Theses and Projects
Show simple item record

Record view(s)

52
checked on Sep 23, 2022

Google ScholarTM

Check


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.