Regime switches and commonalities of the cryptocurrencies asset-class

Gianna Figá-Talamanca, S. Focardi, Marco Patacca
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Abstract

In this paper we test for regime changes in the price dynamics of Bitcoin, Ethereum, Litecoin and Monero, as representatives of the cryptocurrencies asset class. Data are observed daily from January, 1, 2016 to October, 15, 2019. Best specifications within Gaussian and Autoregressive Hidden Markov models for price differences are selected through the AIC and BIC information criteria by considering up to four hidden regimes. The empirical results suggest that at most three common states may be considered for the basket of cryptocurrencies under investigation; a fourth state may be relevant as an added factor to the dynamics description of the individual cryptocurrencies rather than to the whole basket. Finally, we test the out-of-sample performance of estimated regime switching models; optimal results, in terms of RMSE and correlation between predicted and real values, are obtained in the case of two common or three individual regimes.
加密货币资产类别的制度转换和共性
在本文中,我们测试了比特币,以太坊,莱特币和门罗币的价格动态变化,作为加密货币资产类别的代表。数据为2016年1月1日至2019年10月15日每日观测。通过AIC和BIC信息标准,通过考虑多达四种隐藏机制,选择高斯和自回归隐马尔可夫模型中价格差异的最佳规范。实证结果表明,对于正在调查的一篮子加密货币,最多可以考虑三种常见状态;第四种状态可能是与单个加密货币的动态描述相关的附加因素,而不是与整个篮子相关。最后,我们测试了估计的状态切换模型的样本外性能;在RMSE和预测值与实际值之间的相关性方面,在两个共同或三个单独制度的情况下获得了最佳结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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