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Scaling and correlations in foreign exchange market

Author

Listed:
  • Jiang, J.
  • Ma, K.
  • Cai, X.

Abstract

We observe that the distribution of the relative return, describing the variation of a certain currency, of 74 global currencies obeys a power-law. By using the random matrix theory we find that the distribution of eigenvalues of correlation matrix of relative return also follows a power-law. Using a scaled factorial moment we investigate the distribution of correlation coefficients of the relative return and observe intermittence phenomenon. Furthermore, we define the influence strength for a certain currency, which reflects the influence of its price change to the community interested. By doing that, we find that the distribution of influence strength is again a power-law. Beyond that, we compare the influence strength of Chinese Yuan (RMB) to those of other seven important currencies, which may have some interesting indications.

Suggested Citation

  • Jiang, J. & Ma, K. & Cai, X., 2007. "Scaling and correlations in foreign exchange market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 375(1), pages 274-280.
    • Handle: RePEc:eee:phsmap:v:375:y:2007:i:1:p:274-280
    DOI: 10.1016/j.physa.2006.08.073
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    Citations

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    Cited by:

    1. Nie, Chun-Xiao, 2021. "Analyzing financial correlation matrix based on the eigenvector–eigenvalue identity," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 567(C).
    2. Tilly Stephanie, 2010. "Das Zulieferproblem aus institutionenökonomischer Sicht. Die westdeutsche Automobil-Zulieferindustrie zwischen Produktionsund Marktorientierung (1960-1980)," Jahrbuch für Wirtschaftsgeschichte / Economic History Yearbook, De Gruyter, vol. 51(1), pages 137-160, June.
    3. Ledenyov, Dimitri O. & Ledenyov, Viktor O., 2015. "Wave function method to forecast foreign currencies exchange rates at ultra high frequency electronic trading in foreign currencies exchange markets," MPRA Paper 67470, University Library of Munich, Germany.
    4. Prince Osei Mensah & Anokye M. Adam, 2020. "Copula-Based Assessment of Co-Movement and Tail Dependence Structure Among Major Trading Foreign Currencies in Ghana," Risks, MDPI, vol. 8(2), pages 1-20, June.
    5. Simona Moagăr-Poladian & Dorina Clichici & Cristian-Valeriu Stanciu, 2019. "The Comovement of Exchange Rates and Stock Markets in Central and Eastern Europe," Sustainability, MDPI, vol. 11(14), pages 1-22, July.
    6. Kin-Yip Ho & Albert K Tsui, 2008. "Volatility Dynamics in Foreign Exchange Rates : Further Evidence from the Malaysian Ringgit and Singapore Dollar," Finance Working Papers 22571, East Asian Bureau of Economic Research.
    7. Albulescu, Claudiu Tiberiu & Aubin, Christian & Goyeau, Daniel & Tiwari, Aviral Kumar, 2018. "Extreme co-movements and dependencies among major international exchange rates: A copula approach," The Quarterly Review of Economics and Finance, Elsevier, vol. 69(C), pages 56-69.
    8. Trenca Ioan & Plesoianu Anita & Capusan Razvan, 2012. "Multifractal Structure Of Central And Eastern European Foreign Exchange Markets," Annals of Faculty of Economics, University of Oradea, Faculty of Economics, vol. 1(1), pages 784-790, July.
    9. Xin Yang & Shigang Wen & Zhifeng Liu & Cai Li & Chuangxia Huang, 2019. "Dynamic Properties of Foreign Exchange Complex Network," Mathematics, MDPI, vol. 7(9), pages 1-19, September.

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