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Found 6 papers, 1 papers with code
Topological Data Analysis Ball Mapper for Finance
Finance is heavily influenced by data-driven decision-making.
Uncertainty, volatility and the persistence norms of financial time series
Norms of Persistent Homology introduced in topological data analysis are seen as indicators of system instability, analogous to the changing predictability that is captured in financial market uncertainty indexes.
Refining Understanding of Corporate Failure through a Topological Data Analysis Mapping of Altman's Z-Score Model
Value is added to the understanding of where in the parameter space failure occurs, and how firms might act to move away from financial distress.
An Economic Topology of the Brexit vote
A desire to understand the decision of the UK to leave the European Union, Brexit, in the referendum of June 2016 has continued to occupy academics, the media and politicians.
Persistence Codebooks for Topological Data Analysis
Persistent homology (PH) is a rigorous mathematical theory that provides a robust descriptor of data in the form of persistence diagrams (PDs) which are 2D multisets of points.
A persistence landscapes toolbox for topological statistics
These are intended to facilitate the combination of statistics and machine learning with topological data analysis.
Computational Geometry Mathematical Software Algebraic Topology Computation
