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Multi-fluctuation nonlinear patterns of European financial markets based on adaptive filtering with application to family business, green, Islamic, common stocks, and comparison with Bitcoin, NASDAQ, and VIX

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  • Lahmiri, Salim
  • Bekiros, Stelios
  • Bezzina, Frank

Abstract

This paper investigates power-law correlations, chaos, and randomness in prices of family business, green (low Carbon), Islamic (Shariah), and common stock indices from the European zone. Specifically, the estimations of nonlinear patterns are performed in empirical mode decomposition domain to obtain time-scale computed values. The main findings follow. For all markets, price long term fluctuations are persistent, whilst price short term fluctuations are anti-persistent. In addition, short term fluctuations are chaotic, while long term fluctuations are not. Furthermore, short term fluctuations are less affected by randomness than long term fluctuations. Moreover, the level of anti-persistence and the information content in short term fluctuations are similar across all four European markets. Besides, computed nonlinear statistics from intermediate fluctuations are in general lower than those from short fluctuations, and are higher than those from long fluctuations. Our methodology is also applied to Bitcoin, NASDAQ, and VIX indices for comparison purpose. Some similarities in terms of randomness and dissimilarities in terms of long memory are clearly observed between European and US indices. Finally, it is found that the correlation between (i) long memory and chaos is positive, low, and not statistically significant, (ii) between long memory and randomness is positive, large, and statistically significant, and (iii) between chaos and randomness is negative, low, and not statistically significant. Active traders and portfolio managers can follow our research approach to determine specific trading strategies at short and long run horizons.

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  • Lahmiri, Salim & Bekiros, Stelios & Bezzina, Frank, 2020. "Multi-fluctuation nonlinear patterns of European financial markets based on adaptive filtering with application to family business, green, Islamic, common stocks, and comparison with Bitcoin, NASDAQ, ," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 538(C).
  • Handle: RePEc:eee:phsmap:v:538:y:2020:i:c:s0378437119316243
    DOI: 10.1016/j.physa.2019.122858
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    References listed on IDEAS

    as
    1. Cheng, Anyu & Jiang, Xiao & Li, Yongfu & Zhang, Chao & Zhu, Hao, 2017. "Multiple sources and multiple measures based traffic flow prediction using the chaos theory and support vector regression method," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 466(C), pages 422-434.
    2. Tsionas, Mike G. & Michaelides, Panayotis G., 2017. "Bayesian analysis of chaos: The joint return-volatility dynamical system," MPRA Paper 80632, University Library of Munich, Germany.
    3. Lahmiri, Salim & Bekiros, Stelios, 2017. "Disturbances and complexity in volatility time series," Chaos, Solitons & Fractals, Elsevier, vol. 105(C), pages 38-42.
    4. Luo, Yi & Huang, Yirong, 2018. "A new combined approach on Hurst exponent estimate and its applications in realized volatility," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 492(C), pages 1364-1372.
    5. Lahmiri, Salim, 2016. "Clustering of Casablanca stock market based on hurst exponent estimates," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 456(C), pages 310-318.
    6. Lahmiri, Salim, 2017. "A study on chaos in crude oil markets before and after 2008 international financial crisis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 466(C), pages 389-395.
    7. Lahmiri, Salim, 2017. "Investigating existence of chaos in short and long term dynamics of Moroccan exchange rates," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 465(C), pages 655-661.
    8. Gu, Rongbao, 2017. "Multiscale Shannon entropy and its application in the stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 484(C), pages 215-224.
    9. Hodrick, Robert J & Prescott, Edward C, 1997. "Postwar U.S. Business Cycles: An Empirical Investigation," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 29(1), pages 1-16, February.
    10. Stosic, Darko & Stosic, Dusan & Ludermir, Teresa & de Oliveira, Wilson & Stosic, Tatijana, 2016. "Foreign exchange rate entropy evolution during financial crises," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 449(C), pages 233-239.
    11. He, Jiayi & Shang, Pengjian, 2017. "Comparison of transfer entropy methods for financial time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 482(C), pages 772-785.
    12. Garcin, Matthieu, 2017. "Estimation of time-dependent Hurst exponents with variational smoothing and application to forecasting foreign exchange rates," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 483(C), pages 462-479.
    13. Domino, Krzysztof, 2011. "The use of the Hurst exponent to predict changes in trends on the Warsaw Stock Exchange," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(1), pages 98-109.
    14. Tsionas, Mike G. & Michaelides, Panayotis G., 2017. "Neglected chaos in international stock markets: Bayesian analysis of the joint return–volatility dynamical system," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 482(C), pages 95-107.
    15. Lahmiri, Salim & Bekiros, Stelios & Salvi, Antonio, 2018. "Long-range memory, distributional variation and randomness of bitcoin volatility," Chaos, Solitons & Fractals, Elsevier, vol. 107(C), pages 43-48.
    16. Lahmiri, Salim & Bekiros, Stelios, 2018. "Chaos, randomness and multi-fractality in Bitcoin market," Chaos, Solitons & Fractals, Elsevier, vol. 106(C), pages 28-34.
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    3. Andr'es Garc'ia-Medina & Toan Luu Duc Huynh3, 2021. "What drives bitcoin? An approach from continuous local transfer entropy and deep learning classification models," Papers 2109.01214, arXiv.org.
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    5. Aggarwal, Divya & Chandrasekaran, Shabana & Annamalai, Balamurugan, 2020. "A complete empirical ensemble mode decomposition and support vector machine-based approach to predict Bitcoin prices," Journal of Behavioral and Experimental Finance, Elsevier, vol. 27(C).
    6. Lahmiri, Salim & Bekiros, Stelios, 2021. "The effect of COVID-19 on long memory in returns and volatility of cryptocurrency and stock markets," Chaos, Solitons & Fractals, Elsevier, vol. 151(C).
    7. Michał Szostak, 2021. "Does entrepreneurial factor influence creative identities' perception?," Entrepreneurship and Sustainability Issues, VsI Entrepreneurship and Sustainability Center, vol. 9(1), pages 150-175, September.
    8. Abdullah, Mohammad & Chowdhury, Mohammad Ashraful Ferdous & Sulong, Zunaidah, 2023. "Asymmetric efficiency and connectedness among green stocks, halal tourism stocks, cryptocurrencies, and commodities: Portfolio hedging implications," Resources Policy, Elsevier, vol. 81(C).
    9. Michal Szostak, 2020. "Does Creativity Influence the Perception of Creative Identities?," European Research Studies Journal, European Research Studies Journal, vol. 0(4), pages 312-333.
    10. Michal Szostak, 2021. "Perception of Creative Identities by Leaders and Non-leaders: Consequences for Theory and Practice of Manage-ment," European Research Studies Journal, European Research Studies Journal, vol. 0(4), pages 211-232.

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