Seminario Otoño 2018

Expositor: Pablo Roldán (Yeshiva University)

Título: Topological recognition of critical transitions in time series of cryptocurrencies 

Abstract: 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 find early warning signals for critical transitions in the cryptocurrency markets, even though the relevant time series exhibit a highly erratic behavior.