英文标题：
《Critical slowing down associated with critical transition and risk of
  collapse in cryptocurrency》
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作者：
Chengyi Tu, Paolo DOdorico, Samir Suweis
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最新提交年份：
2019
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英文摘要：
  The year 2017 saw the rise and fall of the crypto-currency market, followed by high variability in the price of all crypto-currencies. In this work, we study the abrupt transition in crypto-currency residuals, which is associated with the critical transition (the phenomenon of critical slowing down) or the stochastic transition phenomena. We find that, regardless of the specific crypto-currency or rolling window size, the autocorrelation always fluctuates around a high value, while the standard deviation increases monotonically. Therefore, while the autocorrelation does not display signals of critical slowing down, the standard deviation can be used to anticipate critical or stochastic transitions. In particular, we have detected two sudden jumps in the standard deviation, in the second quarter of 2017 and at the beginning of 2018, which could have served as early warning signals of two majors price collapses that have happened in the following periods. We finally propose a mean-field phenomenological model for the price of crypto-currency to show how the use of the standard deviation of the residuals is a better leading indicator of the collapse in price than the time series\' autocorrelation. Our findings represent a first step towards a better diagnostic of the risk of critical transition in the price and/or volume of crypto-currencies.
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中文摘要：
2017年，加密货币市场起伏不定，随后所有加密货币的价格都出现了很大的波动。在这项工作中，我们研究了加密货币残差中的突变，它与临界过渡（临界减速现象）或随机过渡现象有关。我们发现，无论特定的加密货币或滚动窗口大小，自相关总是在一个高值附近波动，而标准差单调增加。因此，虽然自相关不显示临界减速信号，但标准偏差可用于预测临界或随机过渡。特别是，我们检测到标准差在2017年第二季度和2018年初出现了两次突然跃升，这可能是以下时期发生的两次重大价格崩盘的预警信号。最后，我们提出了一个加密货币价格的平均场现象学模型，以说明残差的标准差是如何比时间序列的自相关更好地指示价格暴跌的。我们的研究结果为更好地诊断加密货币价格和/或数量的关键转变风险迈出了第一步。
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分类信息：

一级分类：Quantitative Finance        数量金融学
二级分类：Statistical Finance        统计金融
分类描述：Statistical, econometric and econophysics analyses with applications to financial markets and economic data
统计、计量经济学和经济物理学分析及其在金融市场和经济数据中的应用
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