Graph-based era segmentation of international financial integration
arXiv:1905.11842 · doi:10.1016/j.physa.2019.122877
Abstract
Assessing world-wide financial integration constitutes a recurrent challenge in macroeconometrics, often addressed by visual inspections searching for data patterns. Econophysics literature enables us to build complementary, data-driven measures of financial integration using graphs. The present contribution investigates the potential and interests of a novel 3-step approach that combines several state-of-the-art procedures to i) compute graph-based representations of the multivariate dependence structure of asset prices time series representing the financial states of 32 countries world-wide (1955-2015); ii) compute time series of 5 graph-based indices that characterize the time evolution of the topologies of the graph; iii) segment these time evolutions in piece-wise constant eras, using an optimization framework constructed on a multivariate multi-norm total variation penalized functional. The method shows first that it is possible to find endogenous stable eras of world-wide financial integration. Then, our results suggest that the most relevant globalization eras would be based on the historical patterns of global capital flows, while the major regulatory events of the 1970s would only appear as a cause of sub-segmentation.
18 pages, 3 figures
References in corpus (6)
- Hierarchical Structure in Financial Markets
- Correlation, hierarchies, and networks in financial markets
- Evolution of worldwide stock markets, correlation structure and correlation based graphs
- Taxonomy of Stock Market Indices
- Multiple break detection in the correlation structure of random variables
- On-the-fly Approximation of Multivariate Total Variation Minimization