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The Frequency of One-Day Abnormal Returns and Price Fluctuations in the FOREX

Author

Listed:
  • Guglielmo Maria Caporale
  • Alex Plastun
  • Viktor Oliinyk

Abstract

This paper analyses the explanatory power of the frequency of abnormal returns in the FOREX for the EURUSD, GBRUSD, USDJPY, EURJPY, GBPCHF, AUDUSD and USDCAD exchange rates over the period 1994-2019. Abnormal returns are detected using a dynamic trigger approach; then the following hypotheses are tested: their frequency is a significant driver of price movements (H1); it does not exhibit seasonal patterns (H2); it is stable over time (H3). For our purposes a variety of statistical methods (both parametric and non-parametric) are applied including ADF tests, Granger causality tests, correlation analysis, (multiple) regression analysis, Probit and Logit regression models. No evidence is found of either seasonal patterns or instability. However, there appears to be a strong positive (negative) relationship between returns in the FOREX and the frequency of positive (negative) abnormal returns. On the whole, the results suggest that the latter is an important driver of price dynamics in the FOREX, is informative about crises and can be the basis of profitable trading strategies, which is inconsistent with market efficiency.

Suggested Citation

  • Guglielmo Maria Caporale & Alex Plastun & Viktor Oliinyk, 2020. "The Frequency of One-Day Abnormal Returns and Price Fluctuations in the FOREX," CESifo Working Paper Series 8196, CESifo.
    • Handle: RePEc:ces:ceswps:_8196
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    References listed on IDEAS

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    More about this item

    Keywords

    FOREX; anomalies; price dynamics; frequency of abnormal returns;
    All these keywords.

    JEL classification:

    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques

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