Topological Recognition of Critical Transitions in Time Series of Cryptocurrencies

@article{Gidea2018TopologicalRO,
  title={Topological Recognition of Critical Transitions in Time Series of Cryptocurrencies},
  author={Marian Gidea and Daniel Goldsmith and Yuri A. Katz and Pablo Rold{\'a}n and Yonah Shmalo},
  journal={Capital Markets: Asset Pricing \& Valuation eJournal},
  year={2018}
}
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… Expand
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