2018
DOI: 10.1016/j.econlet.2018.01.020
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An application of extreme value theory to cryptocurrencies

Abstract: Abtract:We study the tail behaviour of the returns of five major cryptocurrencies. By employing an extreme value analysis and estimating Value-at-Risk and Expected Shortfall as tail risk measures, we find that Bitcoin Cash is the riskiest, while Bitcoin and Litecoin are the least risky cryptocurrencies.

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Cited by 214 publications
(121 citation statements)
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“…However, the authors did not study cryptocurrencies' volatility co-movements. On the other hand, Corbet et al (2018) As investors in cryptocurrencies are exposed to highly undifferentiated risks (Gkillas and Katsiampa, 2018), examination of cryptocurrency price volatility co-movements is of utmost importance in order for investors and other market participants to better understand interlinkages within the cryptocurrency market and make more informed decisions, and multivariate GARCH models are useful tools for analysing such interdependencies between heteroskedastic time series. Nonetheless, volatility dynamics between Bitcoin and Ether have not been previously explored.…”
Section: Introductionmentioning
confidence: 99%
“…However, the authors did not study cryptocurrencies' volatility co-movements. On the other hand, Corbet et al (2018) As investors in cryptocurrencies are exposed to highly undifferentiated risks (Gkillas and Katsiampa, 2018), examination of cryptocurrency price volatility co-movements is of utmost importance in order for investors and other market participants to better understand interlinkages within the cryptocurrency market and make more informed decisions, and multivariate GARCH models are useful tools for analysing such interdependencies between heteroskedastic time series. Nonetheless, volatility dynamics between Bitcoin and Ether have not been previously explored.…”
Section: Introductionmentioning
confidence: 99%
“…However, the majority of research focuses on market level information (Baek & Elbeck, 2015), which can be explained by the wide availability of market-level price information for cryptocurrencies. Furthermore, the majority of the existing academic research on cryptocurrencies focuses on Bitcoin, whereas other cryptocurrencies have only recently been considered (Gkillas & Katsiampa, 2018). We extend prior research on market dynamics and instead focus on the individuals who buy and sell cryptocurrencies and their trading behavior.…”
Section: Introductionmentioning
confidence: 99%
“…For example, from December 2016 to December 2017 the price of Bitcoin grew by 1300%, while the total market capitalization of all cryptocurrencies was over $230 billion in December 2017. Given this surge of interest, there has consequently been a stream of literature examining the properties of cryptocurrencies, documenting bubbles in Bitcoin (Cheah and Fry 2015;Corbet et al 2017), the market efficiency of Bitcoin (Urquhart 2016;Nadarajah and Chu 2017;Tiwari et al 2017;Khuntia and Pattanayak 2018), the hedging and diversification benefits of Bitcoin (Bouri et al 2017a;Corbet et al 2018a), the unique features of cryptocurrencies (Gkillas and Katsiampa 2018;Phillip et al 2018), the relationship between transaction activity and Bitcoin returns (Koutmos 2018) and price clustering within Bitcoin prices (Urquhart 2017). 1 Given the huge surge of interest by investors in cryptocurrencies, this is the first paper to examine whether forming a portfolio of the four main cryptocurrencies is worthwhile, and whether optimal or naïve diversification generates better performance for investors.…”
Section: Introductionmentioning
confidence: 99%