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On Chaotic Nature of the Emerging European Forex Markets

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  • S. Anoop Kumar
  • B. Kamaiah

Abstract

This study attempts to analyze the presence deterministic chaos in the forex markets of select European countries namely Bulgaria, Croatia, Czech Republic, Hungary Poland, Romania, Russia, Slovakia and Slovenia. Monthly NEER data ranging from jan-1994 to Dec-2013 is used for the purpose of analysis. A two step methodology is employed where in the first step, non-linear dependence structure in the underlying time series is verified using BDS test. The results show that all the markets under study exhibit non-linear dependence. In the next stage, it is enquired whether this non-linear behavior is due to the presence of chaotic dynamics in the markets. This is achieved by estimating Lyapunov exponents for the time series under analysis. An EGARCH (1, 1) filter is applied to see if the non-linearity could be explained by a GARCH process. From the Lyapunov exponent values, it is found that the GARCH process is unable to explain the forex markets behavior in a satisfying manner. It is concluded that the forex markets under study exhibit deterministic chaotic behavior.

Suggested Citation

  • S. Anoop Kumar & B. Kamaiah, 2014. "On Chaotic Nature of the Emerging European Forex Markets," Romanian Economic Journal, Department of International Business and Economics from the Academy of Economic Studies Bucharest, vol. 17(53), pages 25-40, September.
    • Handle: RePEc:rej:journl:v:17:y:2014:i:53:p:25-40
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    References listed on IDEAS

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    1. Gilmore, Claire G., 2001. "An examination of nonlinear dependence in exchange rates, using recent methods from chaos theory," Global Finance Journal, Elsevier, vol. 12(1), pages 139-151.
    2. Guglielmo Maria Caporale & Nicola Spagnolo, 2004. "Modelling East Asian exchange rates: a Markov-switching approach," Applied Financial Economics, Taylor & Francis Journals, vol. 14(4), pages 233-242.
    3. Jorge Belaire-Franch, & Dulce Contreras & Lorena Tordera-Lledo, 2002. "Assessing Non-Linear Structures in Real Exchange Rates Using Recurrence Plot Strategies," Computing in Economics and Finance 2002 239, Society for Computational Economics.
    4. S. Anoop Kumar & Bandi Kamaiah, 2014. "Efficient Market Hypothesis: Some Evidences from Emerging European Forex Markets," Romanian Economic Journal, Department of International Business and Economics from the Academy of Economic Studies Bucharest, vol. 17(52), pages 27-44, June.
    5. Hsieh, David A, 1989. "Testing for Nonlinear Dependence in Daily Foreign Exchange Rates," The Journal of Business, University of Chicago Press, vol. 62(3), pages 339-368, July.
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    Cited by:

    1. Ngo Thai Hung, 2021. "Volatility Behaviour of the Foreign Exchange Rate and Transmission Among Central and Eastern European Countries: Evidence from the EGARCH Model," Global Business Review, International Management Institute, vol. 22(1), pages 36-56, February.
    2. Ngo Thai Hung, 2020. "Market integration among foreign exchange rate movements in central and eastern European countries," Society and Economy, Akadémiai Kiadó, Hungary, vol. 42(1), pages 1-20, March.

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    More about this item

    Keywords

    Non-Linearity; Chaos; Foreign Exchange markets; Europe;
    All these keywords.

    JEL classification:

    • F31 - International Economics - - International Finance - - - Foreign Exchange
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets

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