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Application of nonlinear time series analysis techniques to high-frequency currency exchange data

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  • Strozzi, Fernanda
  • Zaldı́var, José-Manuel
  • Zbilut, Joseph P
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    Abstract

    In this work we have applied nonlinear time series analysis to high-frequency currency exchange data. The time series studied are the exchange rates between the US Dollar and 18 other foreign currencies from within and without the Euro zone. Our goal was to determine if their dynamical behaviours were in some way correlated. The nonexistence of stationarity called for the application of recurrence quantification analysis as a tool for this analysis, and is based on the definition of several parameters that allow for the quantification of recurrence plots. The method was checked using the European Monetary System currency exchanges. The results show, as expected, the high correlation between the currencies that are part of the Euro, but also a strong correlation between the Japanese Yen, the Canadian Dollar and the British Pound. Singularities of the series are also demonstrated taking into account historical events, in 1996, in the Euro zone.

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    Bibliographic Info

    Article provided by Elsevier in its journal Physica A: Statistical Mechanics and its Applications.

    Volume (Year): 312 (2002)
    Issue (Month): 3 ()
    Pages: 520-538

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    Handle: RePEc:eee:phsmap:v:312:y:2002:i:3:p:520-538

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    Web page: http://www.journals.elsevier.com/physica-a-statistical-mechpplications/

    Related research

    Keywords: Econophysics; Recurrence quantification; Nonlinear dynamics; Exchange rates;

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    Cited by:
    1. D. Sornette & W. -X. Zhou, 2004. "Non-parametric Determination of Real-Time Lag Structure between Two Time Series: the "Optimal Thermal Causal Path" Method," Papers cond-mat/0408166, arXiv.org.
    2. Aparicio, Teresa & Pozo, Eduardo F. & Saura, Dulce, 2008. "Detecting determinism using recurrence quantification analysis: Three test procedures," Journal of Economic Behavior & Organization, Elsevier, vol. 65(3-4), pages 768-787, March.
    3. Goswami, B. & Ambika, G. & Marwan, N. & Kurths, J., 2012. "On interrelations of recurrences and connectivity trends between stock indices," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(18), pages 4364-4376.
    4. Erzgräber, Hartmut & Strozzi, Fernanda & Zaldívar, José-Manuel & Touchette, Hugo & Gutiérrez, Eugénio & Arrowsmith, David K., 2008. "Time series analysis and long range correlations of Nordic spot electricity market data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(26), pages 6567-6574.
    5. Didier Sornette & Wei-Xing Zhou, 2005. "Non-parametric determination of real-time lag structure between two time series: the 'optimal thermal causal path' method," Quantitative Finance, Taylor & Francis Journals, vol. 5(6), pages 577-591.
    6. Felicia Ramona Birau, 2012. "Econometric Approach Of Heteroskedasticity On Financial Time Series In A General Framework," Annals - Economy Series, Constantin Brancusi University, Faculty of Economics, vol. 4, pages 74-77, December.
    7. Kyrtsou, Catherine & Malliaris, Anastasios G. & Serletis, Apostolos, 2009. "Energy sector pricing: On the role of neglected nonlinearity," Energy Economics, Elsevier, vol. 31(3), pages 492-502, May.
    8. Catherine Kyrtsou & Michel Terraza, 2008. "Seasonal Mackey-Glass-GARCH process and short-term dynamics," Discussion Paper Series 2008_09, Department of Economics, University of Macedonia, revised Sep 2008.
    9. Marisa Faggini, 2011. "Chaotic Time Series Analysis in Economics: Balance and Perspectives," Working papers 25, Former Department of Economics and Public Finance "G. Prato", University of Torino.
    10. Zhou, Wei-Xing & Sornette, Didier, 2006. "Non-parametric determination of real-time lag structure between two time series: The "optimal thermal causal path" method with applications to economic data," Journal of Macroeconomics, Elsevier, vol. 28(1), pages 195-224, March.
    11. Joao A. Bastos & Jorge Caiado, 2010. "Recurrence quantification analysis of global stock markets," CEMAPRE Working Papers 1006, Centre for Applied Mathematics and Economics (CEMAPRE), School of Economics and Management (ISEG), Technical University of Lisbon.
    12. Belaire-Franch, Jorge, 2004. "Testing for non-linearity in an artificial financial market: a recurrence quantification approach," Journal of Economic Behavior & Organization, Elsevier, vol. 54(4), pages 483-494, August.
    13. Sato, Aki-Hiro, 2007. "Frequency analysis of tick quotes on the foreign exchange market and agent-based modeling: A spectral distance approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 382(1), pages 258-270.

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