Uncovering the network structure of the world currency market: Cross-correlations in the fluctuations of daily exchange rates

TL;DR

This paper analyzes the cross-correlations of daily exchange rate fluctuations among 74 currencies from 1995 to 2012, revealing key market modes and constructing networks that highlight influential economies and their development trajectories.

Contribution

It introduces a network reconstruction method that filters out global and random effects, uncovering meaningful currency clusters and economic influence patterns.

Findings

Eigenvalue distribution aligns with random matrix theory except for a few large eigenvalues.

Identified currency clusters and influential economies affecting global development.

Revealed potential fast-growing economies impacting the global market.

Abstract

The cross-correlations between the exchange rate fluctuations of 74 currencies over the period 1995-2012 are analyzed in this paper. The eigenvalue distribution of the cross-correlation matrix exhibits a bulk which approximately matches the bounds predicted from random matrices constructed using mutually uncorrelated time-series. However, a few large eigenvalues deviating from the bulk contain important information about the global market mode as well as important clusters of strongly interacting currencies.We reconstruct the network structure of the world currency market by using two different graph representation techniques, after filtering out the effects of global or market-wide signals on the one hand and random effects on the other. The two networks reveal complementary insights about the major motive forces of the global economy, including the identification of a group of potentially fast growing economies whose development trajectory may affect the global economy in the future as profoundly as the rise of India and China has affected it in the past decades.