运用广义自回归条件异方差（GARCH）模型估计加密货币在熊市期间的波动性。
Estimating the volatility of cryptocurrencies during bearish markets by employing GARCH models.
作者信息
Kyriazis Νikolaos A, Daskalou Kalliopi, Arampatzis Marios, Prassa Paraskevi, Papaioannou Evangelia
机构信息
Department of Economics, University of Thessaly, 28 October 78 Street, 38333, Volos, Greece.
出版信息
Heliyon. 2019 Aug 13;5(8):e02239. doi: 10.1016/j.heliyon.2019.e02239. eCollection 2019 Aug.
This study examines the volatility of certain cryptocurrencies and how they are influenced by the three highest capitalization digital currencies, namely the Bitcoin, the Ethereum and the Ripple. We use daily data for the period 1 January 2018-16 September 2018, which represents the bearish market of cryptocurrencies. The impact of the decline of these three cryptocurrencies on the returns of the other virtual currencies is examined with models of the ARCH and GARCH family, as well as the DCC-GARCH. The main conclusion of the study is that the majority of cryptocurrencies are complementary with Bitcoin, Ethereum and Ripple and that no hedging abilities exist among principal digital currencies in distressed times.
本研究考察了某些加密货币的波动性，以及它们如何受到市值最高的三种数字货币（即比特币、以太坊和瑞波币）的影响。我们使用了2018年1月1日至2018年9月16日的每日数据，这段时间代表了加密货币的熊市。通过自回归条件异方差（ARCH）和广义自回归条件异方差（GARCH）族模型以及动态条件相关系数GARCH（DCC-GARCH）模型，研究了这三种加密货币价格下跌对其他虚拟货币回报的影响。该研究的主要结论是，大多数加密货币与比特币、以太坊和瑞波币呈互补关系，并且在市场低迷时期，主要数字货币之间不存在套期保值能力。
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