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Upward and Downward Multifractality and Efficiency of Chinese and Hong Kong Stock Markets

Author

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  • Walid Mensi

    (College of Economics and Political Science, Sultan Qaboos University
    University of Economics Ho Chi Minh City)

  • Xuan Vinh Vo

    (University of Economics Ho Chi Minh City)

  • Sang Hoon Kang

    (Pusan National University)

Abstract

This study examines the upward and downward multifractality, long-memory process, and efficiency of the Shanghai stock exchange composite index of mainland China and the Hang Seng index (HSI) of Hong Kong using the symmetric multifractal detrended fluctuation analysis (MF-DFA), asymmetric MF-DFA (A-MF-DFA), and the Hurst exponent. The results reveal significant differences in upward and downward multifractality, indicating asymmetric multifractality regardless of the frequencies. Moreover, we find evidence of excess asymmetry in multifractality for both markets and for all frequencies, which is more pronounced during downward stock price movements for Hang Seng Index (HSI) markets. The Hong Kong market is less inefficient than Chinese markets. Additionally, Bitcoin (BTC) volumes and BTC trading capitalizations affect the efficiency level across quantiles. Finally, robustness tests confirm our results are robust.

Suggested Citation

  • Walid Mensi & Xuan Vinh Vo & Sang Hoon Kang, 2024. "Upward and Downward Multifractality and Efficiency of Chinese and Hong Kong Stock Markets," Computational Economics, Springer;Society for Computational Economics, vol. 64(6), pages 3207-3242, December.
  • Handle: RePEc:kap:compec:v:64:y:2024:i:6:d:10.1007_s10614-023-10526-9
    DOI: 10.1007/s10614-023-10526-9
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    1. Kwiatkowski, Denis & Phillips, Peter C. B. & Schmidt, Peter & Shin, Yongcheol, 1992. "Testing the null hypothesis of stationarity against the alternative of a unit root : How sure are we that economic time series have a unit root?," Journal of Econometrics, Elsevier, vol. 54(1-3), pages 159-178.
    2. Nguyen, Khanh Quoc, 2022. "The correlation between the stock market and Bitcoin during COVID-19 and other uncertainty periods," Finance Research Letters, Elsevier, vol. 46(PA).
    3. Uzonwanne, Godfrey, 2021. "Volatility and return spillovers between stock markets and cryptocurrencies," The Quarterly Review of Economics and Finance, Elsevier, vol. 82(C), pages 30-36.
    4. Rabeh Khalfaoui & Sami Ben Jabeur & Buhari Dogan, 2022. "The spillover effects and connectedness among green commodities, Bitcoins, and US stock markets: Evidence from the quantile VAR network," Post-Print hal-03797573, HAL.
    5. Lo, Andrew W, 1991. "Long-Term Memory in Stock Market Prices," Econometrica, Econometric Society, vol. 59(5), pages 1279-1313, September.
    6. Kee-Hong Bae & G. Andrew Karolyi & René M. Stulz, 2003. "A New Approach to Measuring Financial Contagion," The Review of Financial Studies, Society for Financial Studies, vol. 16(3), pages 717-763, July.
    7. Singh, Amanjot, 2021. "Investigating the dynamic relationship between litigation funding, gold, bitcoin and the stock market: The case of Australia," Economic Modelling, Elsevier, vol. 97(C), pages 45-57.
    8. Robert F. Engle, 2000. "The Econometrics of Ultra-High Frequency Data," Econometrica, Econometric Society, vol. 68(1), pages 1-22, January.
    9. Wang, Yudong & Liu, Li & Gu, Rongbao, 2009. "Analysis of efficiency for Shenzhen stock market based on multifractal detrended fluctuation analysis," International Review of Financial Analysis, Elsevier, vol. 18(5), pages 271-276, December.
    10. Zhang, Yue-Jun & Bouri, Elie & Gupta, Rangan & Ma, Shu-Jiao, 2021. "Risk spillover between Bitcoin and conventional financial markets: An expectile-based approach," The North American Journal of Economics and Finance, Elsevier, vol. 55(C).
    11. Salisu, Afees A. & Isah, Kazeem & Akanni, Lateef O., 2019. "Improving the predictability of stock returns with Bitcoin prices," The North American Journal of Economics and Finance, Elsevier, vol. 48(C), pages 857-867.
    12. François Longin & Bruno Solnik, 2001. "Extreme Correlation of International Equity Markets," Journal of Finance, American Finance Association, vol. 56(2), pages 649-676, April.
    13. Koenker, Roger & Bassett, Gilbert, Jr, 1982. "Robust Tests for Heteroscedasticity Based on Regression Quantiles," Econometrica, Econometric Society, vol. 50(1), pages 43-61, January.
    14. Dwita Mariana, Christy & Ekaputra, Irwan Adi & Husodo, Zaäfri Ananto, 2021. "Are Bitcoin and Ethereum safe-havens for stocks during the COVID-19 pandemic?," Finance Research Letters, Elsevier, vol. 38(C).
    15. Jin, Xiaoye, 2016. "The impact of 2008 financial crisis on the efficiency and contagion of Asian stock markets: A Hurst exponent approach," Finance Research Letters, Elsevier, vol. 17(C), pages 167-175.
    16. Goodell, John W. & Goutte, Stephane, 2021. "Diversifying equity with cryptocurrencies during COVID-19," International Review of Financial Analysis, Elsevier, vol. 76(C).
    17. Li, Shi, 2022. "Spillovers between Bitcoin and Meme stocks," Finance Research Letters, Elsevier, vol. 50(C).
    18. Ahmed, Walid M.A., 2021. "Stock market reactions to upside and downside volatility of Bitcoin: A quantile analysis," The North American Journal of Economics and Finance, Elsevier, vol. 57(C).
    19. Mensi, Walid & Lee, Yun-Jung & Vinh Vo, Xuan & Yoon, Seong-Min, 2021. "Does oil price variability affect the long memory and weak form efficiency of stock markets in top oil producers and oil Consumers? Evidence from an asymmetric MF-DFA approach," The North American Journal of Economics and Finance, Elsevier, vol. 57(C).
    20. Dimitriou, Dimitrios & Kenourgios, Dimitris & Simos, Theodore, 2020. "Are there any other safe haven assets? Evidence for “exotic” and alternative assets," International Review of Economics & Finance, Elsevier, vol. 69(C), pages 614-628.
    21. Dyhrberg, Anne Haubo, 2016. "Hedging capabilities of bitcoin. Is it the virtual gold?," Finance Research Letters, Elsevier, vol. 16(C), pages 139-144.
    22. Wen, Fenghua & Tong, Xi & Ren, Xiaohang, 2022. "Gold or Bitcoin, which is the safe haven during the COVID-19 pandemic?," International Review of Financial Analysis, Elsevier, vol. 81(C).
    23. Merton, Robert C., 1980. "On estimating the expected return on the market : An exploratory investigation," Journal of Financial Economics, Elsevier, vol. 8(4), pages 323-361, December.
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    More about this item

    Keywords

    Asian stock markets; Bitcoin; High frequency; Hurst exponent; A-MF-DFA;
    All these keywords.

    JEL classification:

    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading

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