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Analyzing the Dual Long Memory in Stock Market Returns

Author

Listed:
  • Mert URAL

    (Dokuz Eylul University, Faculty of Economics and Administrative Sciences, Department of Economics)

  • C. Coskun KUCUKOZMEN

    (Izmir University of Economics, Faculty of Economics and Administrative Sciences, Department of International Trade and Finance)

Abstract

The purpose of this study is to examine the dual long memory properties for five stock market returns by using joint ARFIMA-FIGARCH model and structural break test in context of weak form efficient market hypothesis. The models are estimated by using daily closing prices for S&P500, FTSE100, DAX, CAC40 and ISE100. In an effort to assess the impact of structural breaks in volatility persistence, the breaks in variance are detected by using the Iterated Cumulative Sums of Squares (ICSS) algorithm, and dummy variables are incorporated to the models. Empirical findings show that the dual long memory exists for all stock markets. Also the volatility has a predictable structure and indicates that all stock markets are weak form inefficient. Further, it is found that incorporating information on structural breaks in variance improves the accuracy of esti-mating volatility dynamics and effectively reduces the persistence of volatility.

Suggested Citation

  • Mert URAL & C. Coskun KUCUKOZMEN, 2011. "Analyzing the Dual Long Memory in Stock Market Returns," Ege Academic Review, Ege University Faculty of Economics and Administrative Sciences, vol. 11(Special I), pages 19-28.
    • Handle: RePEc:ege:journl:v:11:y:2011:i:specialissue:p:19-28
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    Cited by:

    1. Kisswell Basira & Lawrence Dhliwayo & Knowledge Chinhamu & Retius Chifurira & Florence Matarise, 2024. "Estimation and Prediction of Commodity Returns Using Long Memory Volatility Models," Risks, MDPI, vol. 12(5), pages 1-20, April.
    2. Avci-Surucu, Ezgi & Aydogan, A. Kursat & Akgul, Doganbey, 2016. "Bidding structure, market efficiency and persistence in a multi-time tariff setting," Energy Economics, Elsevier, vol. 54(C), pages 77-87.
    3. Tan, Zhengxun & Xiao, Binuo & Huang, Yilong & Zhou, Li, 2021. "Value at risk and return in Chinese and the US stock markets: Double long memory and fractional cointegration," The North American Journal of Economics and Finance, Elsevier, vol. 56(C).

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