Topology Data Analysis Using Mean Persistence Landscapes in Financial Crashes

ISSN Print: 2162-2434
ISSN Online: 2162-2442
www.scirp.org/journal/jmf
E-mail: jmf@scirp.org

Citations

"Topology Data Analysis Using Mean Persistence Landscapes in Financial Crashes"
written by Alejandro Aguilar, Katherine Ensor,
published by Journal of Mathematical Finance, Vol.10 No.4, 2020

has been cited by the following article(s):

[1]	Identifying Extreme Events in the Stock Market: A Topological Data Analysis
	arXiv preprint arXiv …, 2024

[2]	Applications of Topological Data Analysis in Economics
	Available at SSRN 4378151, 2023

[3]	Hypothesis testing for shapes using vectorized persistence diagrams
	Journal of the Royal Statistical Society …, 2023

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[2]	Topological Machine Learning for Financial Crisis Detection: Early Warning Signals from Persistent Homology Computers, 2025 DOI:10.3390/computers14100408

[3]	Change Point Detection in Financial Market Using Topological Data Analysis Systems, 2025 DOI:10.3390/systems13100875

[4]	Identifying extreme events in the stock market: A topological data analysis Chaos: An Interdisciplinary Journal of Nonlinear Science, 2024 DOI:10.1063/5.0220424

[5]	Proceedings of the Fifth International Conference on Emerging Trends in Mathematical Sciences & Computing (IEMSC-24) Information Systems Engineering and Management, 2024 DOI:10.1007/978-3-031-71125-1_33

[6]	Hypothesis testing for shapes using vectorized persistence diagrams Journal of the Royal Statistical Society Series C: Applied Statistics, 2023 DOI:10.1093/jrsssc/qlad024