Statistical Methods in Finance 2017

Abstract

Multiplex networks: Financial markets and economic fundamentals

by Kiran Sharma

A financial market is a striking example of a complex socio-economic system. We will focus on the application of network theories in establishing empirical linkages between the nominal financial networks and the underlying economic fundamentals across countries, at the mesoscopic level [1, 2] and the macroscopic level. At the mesoscopic level, we construct the nominal return correlation networks from daily data to encapsulate sector-level dynamics and figure out the relative importance of 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. 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. At the macroscopic level, we show that there exists a relationship between the financial network constructed from market indices and the trade network, which may actually be a manifestation of the centrality-size relationship, similar to the finding in the sectoral dynamics of the meso-level. In addition, we show that there exists a relationship between the FDI network and the trade network, and also the FDI network and financial network. We demonstrate these using the data for 18 European countries.

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