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Topology Data Analysis of Critical Transitions in Financial Networks

We develop a topology data analysis-based method to detect early signs for critical transitions in financial data. From the time-series of multiple stock prices, we build time-dependent correlation networks, which exhibit topological structures. We compute the persistent homology associated to these structures in order to track the changes in topology when approaching a critical transition. As a case study, we investigate a portfolio of stocks during a period prior to the US financial crisis of 2007-2008, and show the presence of early signs of the critical transition
Year of publication:
2017
Authors: Gidea, Marian
Publisher: [2017]: [S.l.] : SSRN
freely available
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