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Long-Term Memory In Emerging Markets: Evidence From The Chinese Stock Market

Author

Listed:
  • CHAOQUN MA

    (Department of Management Science and Engineering, College of Business Administration, Hunan University, Hunan Province, P. R. China, 410082, P. R. China)

  • HONGQUAN LI

    (School of Business, Hunan Normal University, Changsha, Hunan 410081, China)

  • LIN ZOU

    (College of Business Administration, Hunan University, Changsha, Hunan 410082, China)

  • ZHIJIAN WU

    (Department of Mathematics, The University of Alabama, Tuscaloosa, AL 35487-0350, USA)

Abstract

The notion of long-term memory has received considerable attention in empirical finance. This paper makes two main contributions. First one is, the paper provides evidence of long-term memory dynamics in the equity market of China. An analysis of market patterns in the Chinese market (a typical emerging market) instead of US market (a developed market) will be meaningful because little research on the behaviors of emerging markets has been carried out previously. Second one is, we present a comprehensive research on the long-term memory characteristics in the Chinese stock market returns as well as volatilities. While many empirical results have been obtained on the detection of long-term memory in returns series, very few investigations are focused on the market volatility, though the long-term dependence in volatility may lead to some types of volatility persistence as observed in financial markets and affect volatility forecasts and derivative pricing formulas. By means of using modified rescaled range analysis and Autoregressive Fractally Integrated Moving Average model testing, this study examines the long-term dependence in Chinese stock market returns and volatility. The results show that although the returns themselves contain little serial correlation, the variability of returns has significant long-term dependence. It would be beneficial to encompass long-term memory structure to assess the behavior of stock prices and to research on financial market theory.

Suggested Citation

  • Chaoqun Ma & Hongquan Li & Lin Zou & Zhijian Wu, 2006. "Long-Term Memory In Emerging Markets: Evidence From The Chinese Stock Market," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 5(03), pages 495-501.
    • Handle: RePEc:wsi:ijitdm:v:05:y:2006:i:03:n:s0219622006002088
    DOI: 10.1142/S0219622006002088
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    Cited by:

    1. Viorica Chirilă & Ciprian Chirilă, 2020. "Asymmetric Return and Volatility Transmission in Euro Zone and Baltic Countries Stock Markets," Ovidius University Annals, Economic Sciences Series, Ovidius University of Constantza, Faculty of Economic Sciences, vol. 0(2), pages 2-11, December.
    2. Payal Jain & Sanjay Sehgal, 2019. "An examination of return and volatility spillovers between mature equity markets," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 43(1), pages 180-210, January.
    3. Ziliang Yu & Jian Yang & Robert I. Webb, 2023. "Price discovery in China's crude oil futures markets: An emerging Asian benchmark?," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 43(3), pages 297-324, March.
    4. Anju Bala & Kapil Gupta, 2020. "Examining The Long Memory In Stock Returns And Liquidity In India," Copernican Journal of Finance & Accounting, Uniwersytet Mikolaja Kopernika, vol. 9(3), pages 25-43.
    5. Yang, Jian & Yu, Ziliang & Deng, Yongheng, 2018. "Housing price spillovers in China: A high-dimensional generalized VAR approach," Regional Science and Urban Economics, Elsevier, vol. 68(C), pages 98-114.
    6. Pan, Shuiyang & Long, Suwan(Cheng) & Wang, Yiming & Xie, Ying, 2023. "Nonlinear asset pricing in Chinese stock market: A deep learning approach," International Review of Financial Analysis, Elsevier, vol. 87(C).

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