  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 trade
connectivity is positively associated with higher financial return
correlations. Furthermore, we show that the Economic Complexity Index and the
equity markets have a positive relationship among themselves, as is the case
for Gross Domestic Product. The data science methodology using network theory,
coupled with standard econometric techniques constitute a new approach to
studying multi-level economic phenomena in a comprehensive manner.
