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Multifractality, efficiency and cross-correlations analysis of the American ETF market: Evidence from SPY, DIA and QQQ

Author

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  • Zhu, Xiaoyu
  • Bao, Si

Abstract

Exchange-traded funds (ETFs) are the most popular products in the financial industry today. Although an extensive body of literature focuses on the multifractal analysis of some stock markets, the multifractal behavior of the ETF market have not been very widely studied. This paper aims to compare and examine the weak form efficiency and interdependence about the American ETF market comprehensively. The main contribution of this paper is as follows. First, as far as the empirical methodological framework is concerned, we apply the MF-DFA and MF-X-DFA to test and rank the efficiency of three major ETFs in the American stock market, such as SPY, DIA and QQQ. Moreover, MF-DMA and MF-X-DMA are considered to make the results more robust. Our results provided clear evidence that the American ETF market was multifractal in nature. It is noticed that QQQ exhibits the strongest level of efficiency. Second, the efficiency of the American ETF market was diminished after the global financial crisis, which is consistent with the results of Tiwari et al [1]. Furthermore, time-varying efficiency levels are determined through a rolling window approach. Third, using MF-X-DFA and MF-X-DMA, we show that there also exists multifractal characters in cross-correlations and it is anti-persistent. To the best of our knowledge, no attention has been given to investigation on cross-correlations of the American ETF market. Finally, in order to study the impacts of the global financial crisis on the multifractal behavior, we investigate and compare the multifractal properties before and after the global financial crisis. We find the multifractal characteristics of cross-correlations have been stronger after the global financial crisis.

Suggested Citation

  • Zhu, Xiaoyu & Bao, Si, 2019. "Multifractality, efficiency and cross-correlations analysis of the American ETF market: Evidence from SPY, DIA and QQQ," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 533(C).
    • Handle: RePEc:eee:phsmap:v:533:y:2019:i:c:s0378437119305126
    DOI: 10.1016/j.physa.2019.121942
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    Citations

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    Cited by:

    1. Haider Ali & Faheem Aslam & Paulo Ferreira, 2021. "Modeling Dynamic Multifractal Efficiency of US Electricity Market," Energies, MDPI, vol. 14(19), pages 1-16, September.
    2. Day, Min-Yuh & Ni, Yensen, 2023. "Be greedy when others are fearful: Evidence from a two-decade assessment of the NDX 100 and S&P 500 indexes," International Review of Financial Analysis, Elsevier, vol. 90(C).
    3. Kristjanpoller, Werner & Nekhili, Ramzi & Bouri, Elie, 2024. "Blockchain ETFs and the cryptocurrency and Nasdaq markets: Multifractal and asymmetric cross-correlations," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 637(C).
    4. Kunal Saha & Vinodh Madhavan & G. R. Chandrashekhar, 2022. "Effect of COVID-19 on ETF and index efficiency: evidence from an entropy-based analysis," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 46(2), pages 347-359, April.

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