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.
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Acknowledgements
We would like to thank R K Pan who helped in developing the software used for the analysis reported here and S Sridhar for stimulating discussions. Part of the work was supported by the Department of Atomic Energy, Government of India through the IMSc Complex Systems Project (XII Plan).
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Sinha, S., Kovur, U. (2014). Uncovering the Network Structure of the World Currency Market: Cross-Correlations in the Fluctuations of Daily Exchange Rates. In: Abergel, F., Aoyama, H., Chakrabarti, B., Chakraborti, A., Ghosh, A. (eds) Econophysics of Agent-Based Models. New Economic Windows. Springer, Cham. https://doi.org/10.1007/978-3-319-00023-7_11
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DOI: https://doi.org/10.1007/978-3-319-00023-7_11
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