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Title: Measures of risk in cryptocurrency market using extreme value theory
Authors: Sleiman, Nicole
Advisors: Assaf, Ata 
Subjects: Cryptocurrencies
Electronic commerce
Dissertations, Academic
University of Balamand--Dissertations
Issue Date: 2020
This 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.
Includes bibliographical references (p. 43-47).
Rights: This 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 holder
Ezproxy URL: Link to full text
Type: Project
Appears in Collections:UOB Theses and Projects

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