By Eduard Baumohl

In this study, we construct financial networks in which nodes are represented by assets and where edges are based on long-run correlations. We construct four networks (complete graph, a minimum spanning tree, a planar maximally filtered graph, and a threshold significance graph) and use three centrality measures (betweenness, eigenvalue centrality, and the expected force).

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By Richard Pincak

We propose new cohomology theory for financial market. We perform analysis of financial tensor network for non-equilibrium state, with closeness centrality of a tensor field of partial correlation, with planar graph of Hilbert–Huang transform with hyperbolic spectrum of IMF. We detect the 2008 market crash for Thai SET50 Index Futures market.

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By Richard Pincak

We provide the proof that the space of time series data is a Kolmogorov space with T0-separation axiom using the loop space of time series data. In our approach, we define a cyclic coordinate of intrinsic time scale of time series data after empirical mode decomposition.

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