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首页> 外文期刊>Journal of Economics and Finance >Time series analysis of Cryptocurrency returns and volatilities
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Time series analysis of Cryptocurrency returns and volatilities

机译：Cryptocurrency Returency Returns和BlastIvities的时间序列分析

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摘要

There is a significant interest in the growth and development of cryptocurrencies, the most notable ones being Bitcoin and Ripple. Global trading in these cryptocurrencies has led to highly speculative and "bubble-like" price movements. Since these cryptocurrencies trade like stocks, provide a feasible alternative to gold and appreciate during uncertain times, it can be hypothesized that their prices are partly determined by the global stock indices, gold prices, and fear gauges such as the VEX and the US Economic Policy Uncertainty Index. In this paper, we test this hypothesis by conducting a time series analysis of returns and volatilities of Bitcoin and of Ripple. We use the Autoregressive-moving-average model with exogenous inputs model (ARMAX), Generalized Autoregressive Conditionally Heteroscedastic (GARCH) model, Vector Autoregression (VAR) model, and Granger causality tests to determine linkages between returns and volatilities of Bitcoin and of Ripple. We find that the Bitcoin crash of 2018 could have been explained using these time series methods. We also find that returns of global stock markets and of gold do not have a causal effect on Bitcoin returns, but we do find returns on Ripple have a causal effect on Bitcoin prices.
机译：对加密货币的增长和发展有很大的兴趣，最值得注意的是比特币和涟漪。这些加密货币中的全球交易导致高度投机和“泡沫状”价格变动。由于这些加密货币等同股票，在不确定时期提供了可行的替代品，可以解析其价格部分由全球库存指数，金价和恐惧仪（如沃克斯和美国经济政策）决定不确定性指数。在本文中，我们通过对比特币和涟漪的回报和挥发性进行时间序列分析来测试这一假设。我们使用自回归移动平均模型与外源输入模型（ARMAX），广义自回归条件异源型（GARCH）模型，载体归源（var）模型，并格兰杰因果关系测试，以确定比特币和波纹的返回和挥发性之间的联系。我们发现2018年比特币崩溃可以使用这些时间序列方法来解释。我们还发现全球股市和黄金的回报对比特币回报没有因果影响，但我们确实发现涟漪的回报对比特币价格的因果影响。

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