Interdependencies and Causalities in Coupled Financial Networks

PLoS One. 2016 Mar 15;11(3):e0150994. doi: 10.1371/journal.pone.0150994. eCollection 2016.

Abstract

We explore the foreign exchange and stock market networks for 48 countries from 1999 to 2012 and propose a model, based on complex Hilbert principal component analysis, for extracting significant lead-lag relationships between these markets. The global set of countries, including large and small countries in Europe, the Americas, Asia, and the Middle East, is contrasted with the limited scopes of targets, e.g., G5, G7 or the emerging Asian countries, adopted by previous works. We construct a coupled synchronization network, perform community analysis, and identify formation of four distinct network communities that are relatively stable over time. In addition to investigating the entire period, we divide the time period into into "mild crisis," (1999-2002), "calm," (2003-2006) and "severe crisis" (2007-2012) sub-periods and find that the severe crisis period behavior dominates the dynamics in the foreign exchange-equity synchronization network. We observe that in general the foreign exchange market has predictive power for the global stock market performances. In addition, the United States, German and Mexican markets have forecasting power for the performances of other global equity markets.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Internationality*
  • Investments*
  • Models, Theoretical
  • Principal Component Analysis

Grants and funding

This work was supported by Grant-in-Aid for Scientific Research (KAKENHI) Grant Numbers 25282094 and 25400393 by JSPS, the Program for Promoting Methodological Innovation in Humanities and Social Sciences by Cross-Disciplinary Fusing of the JSPS, the National Science Foundation (NSF) Grant SES 1452061, and the European Community Seventh Framework Programme (FP7/2007–2013) under Socio-economic Sciences and Humanities, grant agreement no. 255987 (FOC-II) and 297149 (FOC-INCO).