IDEAS home Printed from https://ideas.repec.org/a/eee/chsofr/v181y2024ics0960077924002030.html
   My bibliography  Save this article

Segmented multifractal detrended fluctuation analysis for assessing inefficiency in North African stock markets

Author

Listed:
  • Saâdaoui, Foued

Abstract

This study employs segmented multifractal analysis to evaluate the efficiency of key financial markets in North Africa. The proposed method, an adapted version of Multifractal Detrended Fluctuation Analysis (MF-DFA), integrates a wavelet-based change-point detection to identify and separate the two most dynamically changing phases. Subsequent multifractal measurements are then conducted for each of these identified intervals. Focusing on three equity indices—the Egyptian Exchange Index (EGX30), Moroccan All Shares Index (MASI), and Tunisian Stock Index (Tunindex)–that collectively represent the North African financial and economic landscape, empirical results reveal significant asymmetric multifractality, especially notable in the two Maghreban indices. These findings prompt inquiries into the influence of major events on financial market efficiency. Segmented multifractal analysis introduces a novel approach to explore the dynamics and resilience of these sectors, contributing to a more profound understanding of their complex behaviors and responses to various stimuli.

Suggested Citation

  • Saâdaoui, Foued, 2024. "Segmented multifractal detrended fluctuation analysis for assessing inefficiency in North African stock markets," Chaos, Solitons & Fractals, Elsevier, vol. 181(C).
    • Handle: RePEc:eee:chsofr:v:181:y:2024:i:c:s0960077924002030
    DOI: 10.1016/j.chaos.2024.114652
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0960077924002030
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.chaos.2024.114652?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Grech, Dariusz, 2016. "Alternative measure of multifractal content and its application in finance," Chaos, Solitons & Fractals, Elsevier, vol. 88(C), pages 183-195.
    2. Budaev, V.P., 2004. "Turbulence in magnetized plasmas and financial markets: comparative study of multifractal statistics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 344(1), pages 299-307.
    3. Saâdaoui, Foued & Naifar, Nader & Aldohaiman, Mohamed S., 2017. "Predictability and co-movement relationships between conventional and Islamic stock market indexes: A multiscale exploration using wavelets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 482(C), pages 552-568.
    4. Baïle, Rachel & Muzy, Jean-François & Silvani, Xavier, 2021. "Multifractal point processes and the spatial distribution of wildfires in French Mediterranean regions," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 568(C).
    5. Leonardo H. S. Fernandes & Werner Kristjanpoller & Benjamin Miranda Tabak, 2023. "Asymmetric Multifractal Cross-Correlation Dynamics Between Fiat Currencies And Cryptocurrencies," FRACTALS (fractals), World Scientific Publishing Co. Pte. Ltd., vol. 31(01), pages 1-20.
    6. Grahovac, Danijel, 2020. "Multifractal processes: Definition, properties and new examples," Chaos, Solitons & Fractals, Elsevier, vol. 134(C).
    7. Shen, Na & Chen, Jiayi, 2023. "Asymmetric multifractal spectrum distribution based on detrending moving average cross-correlation analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 615(C).
    8. Cao, Guangxi & Cao, Jie & Xu, Longbing, 2013. "Asymmetric multifractal scaling behavior in the Chinese stock market: Based on asymmetric MF-DFA," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(4), pages 797-807.
    9. Kantelhardt, Jan W. & Zschiegner, Stephan A. & Koscielny-Bunde, Eva & Havlin, Shlomo & Bunde, Armin & Stanley, H.Eugene, 2002. "Multifractal detrended fluctuation analysis of nonstationary time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 316(1), pages 87-114.
    10. Barunik, Jozef & Aste, Tomaso & Di Matteo, T. & Liu, Ruipeng, 2012. "Understanding the source of multifractality in financial markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(17), pages 4234-4251.
    11. Wei-Xing Zhou, 2009. "The components of empirical multifractality in financial returns," Papers 0908.1089, arXiv.org, revised Oct 2009.
    12. Zhuang, Xiaoyang & Wei, Dan, 2022. "Asymmetric multifractality, comparative efficiency analysis of green finance markets: A dynamic study by index-based model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 604(C).
    13. Monia Antar, 2022. "Efficiency classification among MENA region stock markets indexes: insights from multifractal spectrum and MSM forecasts," International Journal of Business and Emerging Markets, Inderscience Enterprises Ltd, vol. 14(2), pages 189-212.
    14. Saâdaoui, Foued, 2023. "Skewed multifractal scaling of stock markets during the COVID-19 pandemic," Chaos, Solitons & Fractals, Elsevier, vol. 170(C).
    15. El Alaoui, Marwane & Benbachir, Saâd, 2013. "Multifractal detrended cross-correlation analysis in the MENA area," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(23), pages 5985-5993.
    16. Verma, S. & Jha, S. & Navascués, M.A., 2023. "Smoothness analysis and approximation aspects of non-stationary bivariate fractal functions," Chaos, Solitons & Fractals, Elsevier, vol. 175(P1).
    17. Saâdaoui, Foued, 2018. "Testing for multifractality of Islamic stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 496(C), pages 263-273.
    18. Keshab Shrestha, 2021. "Multifractal Detrended Fluctuation Analysis of Return on Bitcoin," International Review of Finance, International Review of Finance Ltd., vol. 21(1), pages 312-323, March.
    19. Gajardo, Gabriel & Kristjanpoller, Werner D. & Minutolo, Marcel, 2018. "Does Bitcoin exhibit the same asymmetric multifractal cross-correlations with crude oil, gold and DJIA as the Euro, Great British Pound and Yen?," Chaos, Solitons & Fractals, Elsevier, vol. 109(C), pages 195-205.
    20. Lee, Hojin & Chang, Woojin, 2015. "Multifractal regime detecting method for financial time series," Chaos, Solitons & Fractals, Elsevier, vol. 70(C), pages 117-129.
    21. Ibrahim A. Onour, 2010. "North Africa stock markets: analysis of long memory and persistence of shocks," International Journal of Monetary Economics and Finance, Inderscience Enterprises Ltd, vol. 3(2), pages 101-111.
    22. Jiang, Zhi-Qiang & Zhou, Wei-Xing, 2007. "Scale invariant distribution and multifractality of volatility multipliers in stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 381(C), pages 343-350.
    23. Sensoy, A., 2013. "Generalized Hurst exponent approach to efficiency in MENA markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(20), pages 5019-5026.
    24. Xu, Zhaoxia & Gençay, Ramazan, 2003. "Scaling, self-similarity and multifractality in FX markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 323(C), pages 578-590.
    25. Chuang, Wen-I & Huang, Teng-Ching & Lin, Bing-Huei, 2013. "Predicting volatility using the Markov-switching multifractal model: Evidence from S&P 100 index and equity options," The North American Journal of Economics and Finance, Elsevier, vol. 25(C), pages 168-187.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Choi, Sun-Yong, 2021. "Analysis of stock market efficiency during crisis periods in the US stock market: Differences between the global financial crisis and COVID-19 pandemic," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 574(C).
    2. Chen, Wang & Wei, Yu & Lang, Qiaoqi & Lin, Yu & Liu, Maojuan, 2014. "Financial market volatility and contagion effect: A copula–multifractal volatility approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 398(C), pages 289-300.
    3. Marcin Wk{a}torek & Stanis{l}aw Dro.zd.z & Jaros{l}aw Kwapie'n & Ludovico Minati & Pawe{l} O'swik{e}cimka & Marek Stanuszek, 2020. "Multiscale characteristics of the emerging global cryptocurrency market," Papers 2010.15403, arXiv.org, revised Mar 2021.
    4. Shen, Na & Chen, Jiayi, 2023. "Asymmetric multifractal spectrum distribution based on detrending moving average cross-correlation analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 615(C).
    5. Schadner, Wolfgang, 2021. "On the persistence of market sentiment: A multifractal fluctuation analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 581(C).
    6. Akash P. POOJARI & Siva Kiran GUPTHA & G Raghavender RAJU, 2022. "Multifractal analysis of equities. Evidence from the emerging and frontier banking sectors," Theoretical and Applied Economics, Asociatia Generala a Economistilor din Romania / Editura Economica, vol. 0(3(632), A), pages 61-80, Autumn.
    7. Wang, Dong-Hua & Yu, Xiao-Wen & Suo, Yuan-Yuan, 2012. "Statistical properties of the yuan exchange rate index," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(12), pages 3503-3512.
    8. Cao, Guangxi & Xu, Wei, 2016. "Nonlinear structure analysis of carbon and energy markets with MFDCCA based on maximum overlap wavelet transform," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 444(C), pages 505-523.
    9. Lee, Hojin & Song, Jae Wook & Chang, Woojin, 2016. "Multifractal Value at Risk model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 451(C), pages 113-122.
    10. Ruan, Qingsong & Zhang, Manqian & Lv, Dayong & Yang, Haiquan, 2018. "SAD and stock returns revisited: Nonlinear analysis based on MF-DCCA and Granger test," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 509(C), pages 1009-1022.
    11. Saâdaoui, Foued, 2023. "Skewed multifractal scaling of stock markets during the COVID-19 pandemic," Chaos, Solitons & Fractals, Elsevier, vol. 170(C).
    12. Kakinaka, Shinji & Umeno, Ken, 2021. "Exploring asymmetric multifractal cross-correlations of price–volatility and asymmetric volatility dynamics in cryptocurrency markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 581(C).
    13. Kristjanpoller, Werner & Bouri, Elie & Takaishi, Tetsuya, 2020. "Cryptocurrencies and equity funds: Evidence from an asymmetric multifractal analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 545(C).
    14. Ning, Ye & Han, Chenyu & Wang, Yiming, 2018. "The multifractal properties of Euro and Pound exchange rates and comparisons," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 509(C), pages 578-587.
    15. Xiao, Di & Wang, Jun, 2021. "Attitude interaction for financial price behaviours by contact system with small-world network topology," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 572(C).
    16. Liu, Zhichao & Ma, Feng & Long, Yujia, 2015. "High and low or close to close prices? Evidence from the multifractal volatility," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 427(C), pages 50-61.
    17. Yang, Liansheng & Zhu, Yingming & Wang, Yudong, 2016. "Multifractal characterization of energy stocks in China: A multifractal detrended fluctuation analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 451(C), pages 357-365.
    18. 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).
    19. Zhuang, Xiaoyang & Wei, Dan, 2022. "Asymmetric multifractality, comparative efficiency analysis of green finance markets: A dynamic study by index-based model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 604(C).
    20. Ruan, Qingsong & Cui, Hao & Fan, Liming, 2020. "China’s soybean crush spread: Nonlinear analysis based on MF-DCCA," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 554(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:chsofr:v:181:y:2024:i:c:s0960077924002030. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Thayer, Thomas R. (email available below). General contact details of provider: https://www.journals.elsevier.com/chaos-solitons-and-fractals .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.