Publication: Topological data analysis for identifying critical transitions in cryptocurrency time series
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Issued Date
2020-12-14
Resource Type
ISSN
2157362X
21573611
21573611
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2-s2.0-85099748967
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Mahidol University
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SCOPUS
Bibliographic Citation
IEEE International Conference on Industrial Engineering and Engineering Management. Vol.2020-December, (2020), 933-938
Suggested Citation
P. Saengduean, S. Noisagool, F. Chamchod Topological data analysis for identifying critical transitions in cryptocurrency time series. IEEE International Conference on Industrial Engineering and Engineering Management. Vol.2020-December, (2020), 933-938. doi:10.1109/IEEM45057.2020.9309855 Retrieved from: https://repository.li.mahidol.ac.th/handle/123456789/60887
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Title
Topological data analysis for identifying critical transitions in cryptocurrency time series
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Abstract
© 2020 IEEE. In this study, we investigate financial crashes in the cryptocurrency market including both mini and major crashes for two cryptocurrencies, Bitcoin and Ethereum, during the period that the digital market crashed in 2018. By applying techniques in topological data analysis, we are able to predict financial transitions and explore optimal values of the window size and the dimension of point cloud data to obtain good early warning signals. Our results demonstrate good early warning signals before the financial crashes and also show that the L1-norm and C1 - norm of persistent landscapes peak before the crashes occur.