英文标题:
《Topological recognition of critical transitions in time series of
cryptocurrencies》
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作者:
Marian Gidea, Daniel Goldsmith, Yuri Katz, Pablo Roldan, Yonah Shmalo
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最新提交年份:
2018
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英文摘要:
We analyze the time series of four major cryptocurrencies (Bitcoin, Ethereum, Litecoin, and Ripple) before the digital market crash at the end of 2017 - beginning 2018. We introduce a methodology that combines topological data analysis with a machine learning technique -- $k$-means clustering -- in order to automatically recognize the emerging chaotic regime in a complex system approaching a critical transition. We first test our methodology on the complex system dynamics of a Lorenz-type attractor, and then we apply it to the four major cryptocurrencies. We find early warning signals for critical transitions in the cryptocurrency markets, even though the relevant time series exhibit a highly erratic behavior.
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中文摘要:
我们分析了2017年底至2018年初数字市场崩溃之前四种主要加密货币(比特币、以太坊、莱特币和Ripple)的时间序列。我们介绍了一种将拓扑数据分析与
机器学习技术相结合的方法——$k$表示聚类——以便自动识别接近临界过渡的复杂系统中出现的混沌区域。我们首先在洛伦兹型吸引子的复杂系统动力学上测试我们的方法,然后将其应用于四种主要的加密货币。我们发现了加密货币市场关键转变的早期预警信号,尽管相关时间序列表现出高度不稳定的行为。
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分类信息:
一级分类:Quantitative Finance 数量金融学
二级分类:Mathematical Finance 数学金融学
分类描述:Mathematical and analytical methods of finance, including stochastic, probabilistic and functional analysis, algebraic, geometric and other methods
金融的数学和分析方法,包括随机、概率和泛函分析、代数、几何和其他方法
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一级分类:Mathematics 数学
二级分类:Dynamical Systems 动力系统
分类描述:Dynamics of differential equations and flows, mechanics, classical few-body problems, iterations, complex dynamics, delayed differential equations
微分方程和流动的动力学,力学,经典的少体问题,迭代,复杂动力学,延迟微分方程
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一级分类:Physics 物理学
二级分类:Physics and Society 物理学与社会
分类描述:Structure, dynamics and collective behavior of societies and groups (human or otherwise). Quantitative analysis of social networks and other complex networks. Physics and engineering of infrastructure and systems of broad societal impact (e.g., energy grids, transportation networks).
社会和团体(人类或其他)的结构、动态和集体行为。社会网络和其他复杂网络的定量分析。具有广泛社会影响的基础设施和系统(如能源网、运输网络)的物理和工程。
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