Please use this identifier to cite or link to this item: https://scholarhub.balamand.edu.lb/handle/uob/3596
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dc.contributor.advisorAssaf, Ataen_US
dc.contributor.authorMourad, Mohamaden_US
dc.date.accessioned2020-12-23T14:37:10Z-
dc.date.available2020-12-23T14:37:10Z-
dc.date.issued2020-
dc.identifier.urihttps://scholarhub.balamand.edu.lb/handle/uob/3596-
dc.descriptionIncludes bibliographical references (p. 48-54).en_US
dc.description.abstractIn this paper, we are trying to check the effect of google trends searches amount on the return of 5 different cryptocurrencies: Bitcoin, Dash, Litecoin, Stellar and XRP. And Autoregressive Distributed Lag Model (ARDL) approach was used in this paper which will allow us to overcome the problem of our tested series being non-stationary in the long run. Our study was done using weekly google trends data and weekly cryptocurrencys returns data for a 5 years period from November 2014 until November 2019. Stellar had the highest returns the highest average during these 5 years but being at the same time the most volatile Cryptocurrency, while Bitcoin being the least volatile and thus the safest cryptocurrency to invest on. The ARDL approach was successfully applied using our abovementioned data where we found results showing that Dash and Bitcoin returns are the most affected by the google trends searches amount, while Litecoin and XRP are less affected by these trends and finally Stellar returns were never significantly affected by these returns being the most efficient Cryptocurrency among these 5.en_US
dc.description.statementofresponsibilityby Mohamad Mouraden_US
dc.format.extent1 online resource (vii, 54 pages) :ill., tablesen_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.titleHow google trends can affect the return of different cryptocurencies [sic] cryptocurrencies : application of autoregressive distributed lag modelen_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.catalogued2020-06-19-
dc.description.degreeMS in Accounting and Finance.en_US
dc.description.statusPublisheden_US
dc.identifier.ezproxyURLhttp://ezsecureaccess.balamand.edu.lb/login?url=http://olib.balamand.edu.lb/projects_and_theses/253771.pdfen_US
dc.identifier.OlibID253771-
dc.provenance.recordsourceOliben_US
Appears in Collections:UOB Theses and Projects
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