Modeling Volatility with GARCH models : an Application on Bitcoin, Ethereum and Ripple

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dc.contributor.advisor Mammi, Irene it_IT
dc.contributor.author Turan, Dilan <1992> it_IT
dc.date.accessioned 2020-07-15 it_IT
dc.date.accessioned 2020-09-24T11:56:15Z
dc.date.issued 2020-07-27 it_IT
dc.identifier.uri http://hdl.handle.net/10579/17301
dc.description.abstract There is a growing awareness in the financial markets, financial institutions, investors and researches for the cryptocurrencies in last few years. In parallel with this awareness and interest, highly volatile structure of the cryptocurrencies leads investors and institutions to provide some models to analyze and predict the volatility. The purpose of this study is to shed light on potential scenarios regarding the future of Bitcoin, Ethereum and Ripple by using GARCH model. In addition to this, results will be compared according to their performance in order to determine which model is the most successful in volatility modeling. Thus, it will be possible to comment on the volatility structure of cryptocurrencies, improve the financial tools used in the market and contribute to the literature by trying to guide future studies of cryptocurrencies. it_IT
dc.language.iso en it_IT
dc.publisher Università Ca' Foscari Venezia it_IT
dc.rights © Dilan Turan, 2020 it_IT
dc.title Modeling Volatility with GARCH models : an Application on Bitcoin, Ethereum and Ripple it_IT
dc.title.alternative Modelling Volatility with GARCH Models: An Application on Bitcoin, Ethereum and Ripple it_IT
dc.type Master's Degree Thesis it_IT
dc.degree.name Economia e finanza it_IT
dc.degree.level Laurea magistrale it_IT
dc.degree.grantor Dipartimento di Economia it_IT
dc.description.academicyear 2019/2020 - Sessione Estiva it_IT
dc.rights.accessrights closedAccess it_IT
dc.thesis.matricno 871400 it_IT
dc.subject.miur SECS-P/03 SCIENZA DELLE FINANZE it_IT
dc.description.note it_IT
dc.degree.discipline it_IT
dc.contributor.co-advisor it_IT
dc.date.embargoend 10000-01-01
dc.provenance.upload Dilan Turan (871400@stud.unive.it), 2020-07-15 it_IT
dc.provenance.plagiarycheck Irene Mammi (irene.mammi@unive.it), 2020-07-27 it_IT


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