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Topological Machine Learning for Financial Crisis Detection: Early Warning Signals from Persistent Homology

We propose a strictly causal early–warning framework for financial crises based on topological signal extraction from multivariate return streams. Sliding windows of daily log–returns are mapped to point clouds, from which Vietoris–Rips persistence diagrams are computed and summarised by persistence...

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Bibliografische gegevens
Hoofdauteurs: Ecaterina Guritanu, Enrico Barbierato, Alice Gatti
Formaat: Artigo
Taal:Inglês
Gepubliceerd in: MDPI AG 2025-09-01
Reeks:Computers
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Online toegang:https://www.mdpi.com/2073-431X/14/10/408
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