  We demonstrate the existence of an empirical linkage between the nominal
financial networks and the underlying economic fundamentals across countries.
We construct the nominal return correlation networks from daily data to
encapsulate sector-level dynamics and figure the relative importance of the
sectors in the nominal network through a measure of centrality and clustering
algorithms. The eigenvector centrality robustly identifies the backbone of the
minimum spanning tree defined on the return networks as well as the primary
cluster in the multidimensional scaling map. We show that the sectors that are
relatively large in size, defined with the metrics market capitalization,
revenue and number of employees, constitute the core of the return networks,
whereas the periphery is mostly populated by relatively smaller sectors.
Therefore, sector-level nominal return dynamics is anchored to the real size
effect, which ultimately shapes the optimal portfolios for risk management. Our
results are reasonably robust across 27 countries of varying degrees of
prosperity and across periods of market turbulence (2008-09) as well as
relative calmness (2015-16).
