Topological recognition of critical transitions in time series of cryptocurrencies

DOI10.1016/j.physa.2019.123843OpenAlexW2999954992WikidataQ126347183 ScholiaQ126347183MaRDI QIDQ2140735

Marian Gidea, Pablo Roldán, Yuri A. Katz, Yonah Shmalo, Daniel Goldsmith

Publication date: 23 May 2022

Published in: Physica A (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1809.00695

zbMATH Keywords

financial time seriestopological data analysis\(k\)-means clusteringcritical transitionscryptocurrencycomplex systems dynamics

Mathematics Subject Classification ID

Statistical mechanics, structure of matter (82-XX)

Related Items (5)

Persistence of Weighted Ordinal Partition Networks for Dynamic State Detection ⋮ Testing for local covariate trend effects in volatility models ⋮ Why topological data analysis detects financial bubbles? ⋮ Topological features of multivariate distributions: dependency on the covariance matrix ⋮ A simplified algorithm for identifying abnormal changes in dynamic networks

Uses Software

• TDA
• SW1PerS
• factoextra
• Persistence Landscape

Cites Work

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• Dynamic bifurcations on financial markets
• A persistence landscapes toolbox for topological statistics
• Stability of persistence diagrams
• Embedology
• Analysis of Kolmogorov flow and Rayleigh-Bénard convection using persistent homology
• Topological data analysis of financial time series: landscapes of crashes
• Sliding windows and persistence: an application of topological methods to signal analysis
• Topology from time series
• Critical phenomena in natural sciences. Chaos, fractals, selforganization and disorder: Concepts and tools.
• Critical transitions in a model of a genetic regulatory system
• On the non-stationarity of financial time series: impact on optimal portfolio selection
• Topology and data
• A methodology for index tracking based on time-series clustering
• Topological data analysis for true step detection in periodic piecewise constant signals
• Topological characterization and early detection of bifurcations and chaos in complex systems using persistent homology
• Automatic Recognition and Tagging of Topologically Different Regimes in Dynamical Systems
• Persistent topological features of dynamical systems
• THREE-DIMENSIONAL HÉNON-LIKE MAPS AND WILD LORENZ-LIKE ATTRACTORS
• Statistical topological data analysis using persistence landscapes

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