IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v550y2020ics0378437119322794.html
   My bibliography  Save this article

The institutional characteristics of multifractal spectrum of China’s stock market

Author

Listed:
  • Li, Yong
  • Vilela, André L.M.
  • Stanley, H. Eugene

Abstract

This paper investigates the fractal structure of China’s stock market by calculating the multifractal singularity spectrum and comparing the scaling behavior of the bubble phase of eight abnormal volatilities with that of normal fluctuation on the timeline. We find robust evidence that the Shanghai Stock Exchange Composite Index has multifractal features in the bubble and normal fluctuation periods, where the higher multifractality is associated with a bubble and more unstable market. The short-sighted administrative policies cause over-supply of intervention, which enhances the multifractality and increases the instability of the stock market. The multifractal parameter set (α0,Δα,−B) might be used as a quantifier to characterize the status of the stock market. A policy aimed to improve the stability of the stock market should be devoted to optimizing the parameter set.

Suggested Citation

  • Li, Yong & Vilela, André L.M. & Stanley, H. Eugene, 2020. "The institutional characteristics of multifractal spectrum of China’s stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 550(C).
    • Handle: RePEc:eee:phsmap:v:550:y:2020:i:c:s0378437119322794
    DOI: 10.1016/j.physa.2019.124129
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437119322794
    Download Restriction: Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000
    File URL: https://libkey.io/10.1016/j.physa.2019.124129?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. Sandeep Patel & Asani Sarkar, 1998. "Stock market crises in developed and emerging markets," Research Paper 9809, Federal Reserve Bank of New York.
    2. Al-Yahyaee, Khamis Hamed & Mensi, Walid & Yoon, Seong-Min, 2018. "Efficiency, multifractality, and the long-memory property of the Bitcoin market: A comparative analysis with stock, currency, and gold markets," Finance Research Letters, Elsevier, vol. 27(C), pages 228-234.
    3. Katsuragi, Hiroaki, 2000. "Evidence of multi-affinity in the Japanese stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 278(1), pages 275-281.
    4. Kaushik Matia & Yosef Ashkenazy & H. Eugene Stanley, 2003. "Multifractal Properties of Price Fluctuations of Stocks and Commodities," Papers cond-mat/0308012, arXiv.org.
    5. Wang, Hong-Yong & Wang, Tong-Tong, 2018. "Multifractal analysis of the Chinese stock, bond and fund markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 512(C), pages 280-292.
    6. Zunino, L. & Tabak, B.M. & Figliola, A. & Pérez, D.G. & Garavaglia, M. & Rosso, O.A., 2008. "A multifractal approach for stock market inefficiency," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(26), pages 6558-6566.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Wang, Xiaoxuan & Gao, Xiangyun & Wu, Tao & Sun, Xiaotian, 2022. "Dynamic multiscale analysis of causality among mining stock prices," Resources Policy, Elsevier, vol. 77(C).
    2. Wang, Yi & Sun, Qi & Zhang, Zilu & Chen, Liqing, 2022. "A risk measure of the stock market that is based on multifractality," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 596(C).

    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. Diniz-Maganini, Natalia & Rasheed, Abdul A. & Sheng, Hsia Hua, 2021. "Exchange rate regimes and price efficiency: Empirical examination of the impact of financial crisis," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 73(C).
    2. Ruan, Qingsong & Zhou, Mi & Yin, Linsen & Lv, Dayong, 2021. "Hedging effectiveness of Chinese Treasury bond futures: New evidence based on nonlinear analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 565(C).
    3. Mensi, Walid & Tiwari, Aviral Kumar & Al-Yahyaee, Khamis Hamed, 2019. "An analysis of the weak form efficiency, multifractality and long memory of global, regional and European stock markets," The Quarterly Review of Economics and Finance, Elsevier, vol. 72(C), pages 168-177.
    4. Schadner, Wolfgang, 2021. "On the persistence of market sentiment: A multifractal fluctuation analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 581(C).
    5. Zhou, Yaping & Lu, Baoqun & Lv, Dayong & Ruan, Qingsong, 2019. "The informativeness of options-trading activities: Non-linear analysis based on MF-DCCA and Granger test," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 534(C).
    6. Diniz-Maganini, Natalia & Diniz, Eduardo H. & Rasheed, Abdul A., 2021. "Bitcoin’s price efficiency and safe haven properties during the COVID-19 pandemic: A comparison," Research in International Business and Finance, Elsevier, vol. 58(C).
    7. Chen, Shu-Peng & He, Ling-Yun, 2010. "Multifractal spectrum analysis of nonlinear dynamical mechanisms in China’s agricultural futures markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(7), pages 1434-1444.
    8. Zhongjun Wang & Mengye Sun & A. M. Elsawah, 2020. "Improving MF-DFA model with applications in precious metals market," Papers 2006.15214, arXiv.org.
    9. Zhang, Guofu & Li, Jingjing, 2018. "Multifractal analysis of Shanghai and Hong Kong stock markets before and after the connect program," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 503(C), pages 611-622.
    10. Diniz-Maganini, Natalia & Rasheed, Abdul A. & Sheng, Hsia Hua, 2023. "Price efficiency of the foreign exchange rates of BRICS countries: A comparative analysis," Latin American Journal of Central Banking (previously Monetaria), Elsevier, vol. 4(1).
    11. Hasan, Rashid & Mohammad, Salim M., 2015. "Multifractal analysis of Asian markets during 2007–2008 financial crisis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 419(C), pages 746-761.
    12. Rodriguez-Romo, Suemi & Sosa-Herrera, Antonio, 2013. "Lacunarity and multifractal analysis of the large DLA mass distribution," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(16), pages 3316-3328.
    13. 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.
    14. Tetsuya Takaishi, 2017. "Statistical properties and multifractality of Bitcoin," Papers 1707.07618, arXiv.org, revised May 2018.
    15. Al-Yahyaee, Khamis Hamed & Mensi, Walid & Ko, Hee-Un & Yoon, Seong-Min & Kang, Sang Hoon, 2020. "Why cryptocurrency markets are inefficient: The impact of liquidity and volatility," The North American Journal of Economics and Finance, Elsevier, vol. 52(C).
    16. 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.
    17. Tetsuya Takaishi & Takanori Adachi, 2019. "Market efficiency, liquidity, and multifractality of Bitcoin: A dynamic study," Papers 1902.09253, arXiv.org.
    18. 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).
    19. Takaishi, Tetsuya, 2018. "Statistical properties and multifractality of Bitcoin," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 506(C), pages 507-519.
    20. Ruan, Qingsong & Yang, Haiquan & Lv, Dayong & Zhang, Shuhua, 2018. "Cross-correlations between individual investor sentiment and Chinese stock market return: New perspective based on MF-DCCA," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 503(C), pages 243-256.

    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:phsmap:v:550:y:2020:i:c:s0378437119322794. 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: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/physica-a-statistical-mechpplications/ .

    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.