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Testing for random walk behavior in euro exchange rates

Author

Listed:
  • Amélie Charles

    (Audencia Business School)

  • Olivier Darné

    (LEMNA - Laboratoire d'économie et de management de Nantes Atlantique - IEMN-IAE Nantes - Institut d'Économie et de Management de Nantes - Institut d'Administration des Entreprises - Nantes - UN - Université de Nantes)

Abstract

This study examines the random walk behavior of major Euro exchange rates. The hypothesis is tested with new variance ratio tests based on power transformation and multiple ranks from daily and weekly data. We find that Euro exchange rates for the major trading countries follow the random walk hypothesis, and therefore are significantly weak-form efficient. This outcome is not necessarily the case for non-major trading currencies, especially for the Swedish kroner, where the random walk hypothesis is rejected at the daily and weekly frequencies.

Suggested Citation

  • Amélie Charles & Olivier Darné, 2009. "Testing for random walk behavior in euro exchange rates," Post-Print hal-00771082, HAL.
    • Handle: RePEc:hal:journl:hal-00771082
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    Cited by:

    1. Fahad Almudhaf, 2014. "Testing for random walk behaviour in CIVETS exchange rates," Applied Economics Letters, Taylor & Francis Journals, vol. 21(1), pages 60-63, January.
    2. Petr Zeman & Martin Maršík, 2013. "High-frequency data and the effectiveness of the spot exchange rate EUR/USD," Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis, Mendel University Press, vol. 61(7), pages 2965-2971.
    3. Lazăr, Dorina & Todea, Alexandru & Filip, Diana, 2012. "Martingale difference hypothesis and financial crisis: Empirical evidence from European emerging foreign exchange markets," Economic Systems, Elsevier, vol. 36(3), pages 338-350.
    4. Agus Salim & Kai Shi, 2019. "A Cointegration of the Exchange Rate and Macroeconomic Fundamentals: The Case of the Indonesian Rupiah vis-á-vis Currencies of Primary Trade Partners," JRFM, MDPI, vol. 12(2), pages 1-17, May.
    5. Kuck, Konstantin & Maderitsch, Robert, 2019. "Intra-day dynamics of exchange rates: New evidence from quantile regression," The Quarterly Review of Economics and Finance, Elsevier, vol. 71(C), pages 247-257.
    6. Charles, Amélie & Darné, Olivier & Kim, Jae H., 2012. "Exchange-rate return predictability and the adaptive markets hypothesis: Evidence from major foreign exchange rates," Journal of International Money and Finance, Elsevier, vol. 31(6), pages 1607-1626.
    7. Adeyeye Patrick Olufemi & Aluko Olufemi Adewale & Migiro Stephen Oseko, 2017. "Efficiency of Foreign Exchange Markets in Sub-Saharan Africa in the Presence of Structural Break: A Linear and Non-Linear Testing Approach," Journal of Economics and Behavioral Studies, AMH International, vol. 9(4), pages 122-131.
    8. Ismael Orquín-Serrano, 2020. "Predictive Power of Adaptive Candlestick Patterns in Forex Market. Eurusd Case," Mathematics, MDPI, vol. 8(5), pages 1-34, May.
    9. Yang, Yan-Hong & Shao, Ying-Hui & Shao, Hao-Lin & Stanley, H. Eugene, 2019. "Revisiting the weak-form efficiency of the EUR/CHF exchange rate market: Evidence from episodes of different Swiss franc regimes," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 523(C), pages 734-746.

    More about this item

    Keywords

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    JEL classification:

    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets
    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General

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