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Assessing world-wide financial integration constitutes a recurrent challengein macroeconometrics, often addressed by visual inspections searching for datapatterns. Econophysics literature enables us to build complementary,data-driven measures of financial integration using graphs. The presentcontribution investigates the potential and interests of a novel 3-stepapproach that combines several state-of-the-art procedures to i) computegraph-based representations of the multivariate dependence structure of assetprices time series representing the financial states of 32 countries world-wide(1955-2015); ii) compute time series of 5 graph-based indices that characterizethe time evolution of the topologies of the graph; iii) segment these timeevolutions in piece-wise constant eras, using an optimization frameworkconstructed on a multivariate multi-norm total variation penalized functional.The method shows first that it is possible to find endogenous stable eras ofworld-wide financial integration. Then, our results suggest that the mostrelevant globalization eras would be based on the historical patterns of globalcapital flows, while the major regulatory events of the 1970s would only appearas a cause of sub-segmentation.

Graph-based era segmentation of international financial integration