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Nonlinearity and efficiency dynamics of foreign exchange markets: evidence from multifractality and volatility of major exchange rates

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  • Chenyu Han
  • Yiming Wang
  • Yingying Xu

Abstract

This study investigates the efficiencies of the exchange markets for four major currencies—the euro (EUR), the pound (GBP), the Canadian dollar (CAD) and the Japanese yen (JPY)—from 2005 to 2019 by using multifractal detrended fluctuation analysis (MF-DFA). This study also investigates the causes of these efficiencies. Significant multifractal properties are demonstrated by the four markets, and long-range correlation and fat-tail distribution properties are the main causes. We calculate and compare the multifractal degrees in three subsamples, which are classified based on their temporal relation to two economic events: the 2008 financial crisis and the announcement by the Federal Reserve of its withdrawal from the quantitative easing policy in 2014. Empirical results suggest that multifractal properties exist at different levels in the subsamples, thus showing that these events affect foreign exchange market efficiencies in terms of statistics and the fractal market. The JPY exchange market has the fewest multifractal properties, thus indicating that this exchange market has the highest market efficiency among these four exchange markets. The empirical results have implications for the nonlinear mechanism and efficiency in foreign exchange markets, which may help investors effectively manage market risks and benefit a stable global economy.

Suggested Citation

  • Chenyu Han & Yiming Wang & Yingying Xu, 2020. "Nonlinearity and efficiency dynamics of foreign exchange markets: evidence from multifractality and volatility of major exchange rates," Economic Research-Ekonomska Istraživanja, Taylor & Francis Journals, vol. 33(1), pages 731-751, January.
    • Handle: RePEc:taf:reroxx:v:33:y:2020:i:1:p:731-751
    DOI: 10.1080/1331677X.2020.1734852
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    Cited by:

    1. Lee, Min-Jae & Choi, Sun-Yong, 2024. "Insights into the dynamics of market efficiency spillover of financial assets in different equity markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 641(C).
    2. Mohammed Alhagyan, 2024. "Forecasting the Performance of the Energy Sector at the Saudi Stock Exchange Market by Using GBM and GFBM Models," JRFM, MDPI, vol. 17(5), pages 1-10, April.

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