Multi-layered Network Structure: Relationship Between Financial and Macroeconomic Dynamics
Kiran Sharma, Anindya S. Chakrabarti, Anirban Chakraborti

TL;DR
This paper uses multi-layered network analysis to reveal empirical linkages between financial market dynamics and macroeconomic variables across countries, highlighting core-periphery structures and relationships with economic complexity and trade.
Contribution
It introduces a novel multi-layered network approach combining data science and econometrics to study the interconnectedness of financial and macroeconomic systems.
Findings
Financial and macroeconomic networks are empirically linked across countries.
Core-periphery structures in networks involve similar countries, related to the gravity model.
Trade connectivity correlates with higher financial return correlations.
Abstract
We demonstrate using multi-layered networks, the existence of an empirical linkage between the dynamics of the financial network constructed from the market indices and the macroeconomic networks constructed from macroeconomic variables such as trade, foreign direct investments, etc. for several countries across the globe. The temporal scales of the dynamics of the financial variables and the macroeconomic fundamentals are very different, which make the empirical linkage even more interesting and significant. Also, we find that there exist in the respective networks, core-periphery structures (determined through centrality measures) that are composed of the similar set of countries -- a result that may be related through the `gravity model' of the country-level macroeconomic networks. Thus, from a multi-lateral openness perspective, we elucidate that for individual countries, larger…
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Taxonomy
TopicsComplex Systems and Time Series Analysis · Economic and Technological Innovation · Complex Network Analysis Techniques
