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Testing for long memory in ISE using Arfima-Figarch model and structural break test

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  • Korkmaz, Turhan
  • Cevik, Emrah Ismail
  • Özataç, Nesrin

Abstract

This study examines long memory in Istanbul Stock Exchange (ISE) by using the structural break test in variance and ARFIMA-FIGARCH model. Our findings indicate that long memory does not exist in the equity return; however, it exits in volatility. Consequently, ISE is found as a weak form inefficient market due to volatility as it has a predictable component.

Suggested Citation

  • Korkmaz, Turhan & Cevik, Emrah Ismail & Özataç, Nesrin, 2009. "Testing for long memory in ISE using Arfima-Figarch model and structural break test," MPRA Paper 71302, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:71302
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    References listed on IDEAS

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    Citations

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    Cited by:

    1. Quynh-Trang Nguyen & John Francis Diaz & Jo-Hui Chen & Ming-Yen Lee, 2019. "Fractional Integration in Corporate Social Responsibility Indices: A FIGARCH and HYGARCH Approach," Asian Economic and Financial Review, Asian Economic and Social Society, vol. 9(7), pages 836-850, July.
    2. Heni Boubaker & Giorgio Canarella & Rangan Gupta & Stephen M. Miller, 2023. "A Hybrid ARFIMA Wavelet Artificial Neural Network Model for DJIA Index Forecasting," Computational Economics, Springer;Society for Computational Economics, vol. 62(4), pages 1801-1843, December.
    3. Sylvain Prado, 2011. "Free lunch in the oil market: a note on Long Memory," Working Papers hal-04140982, HAL.
    4. Sándor Kovács & Prasert Chaitip & Chukiat Chaiboonsri & Péter Balogh, 2012. "The Long Memory Property of Hungarian Market Pig Prices: A Comparison of Three Different Methods," Annals of the University of Petrosani, Economics, University of Petrosani, Romania, vol. 12(3), pages 123-138.
    5. Cevik, Emrah Ismail, 2012. "İstanbul Menkul Kıymetler Borsası’nda etkin piyasa hipotezinin uzun hafıza modelleri ile analizi: sektörel bazda bir inceleme [The testing of efficient market hypothesis in the Istanbul Stock Excha," MPRA Paper 71484, University Library of Munich, Germany, revised 2012.
    6. Yalama, Abdullah & Celik, Sibel, 2013. "Real or spurious long memory characteristics of volatility: Empirical evidence from an emerging market," Economic Modelling, Elsevier, vol. 30(C), pages 67-72.
    7. Pece Andreea Maria & Ludusan (Corovei) Emilia Anuta & Mutu Simona, 2013. "Testing The Long Range-Dependence For The Central Eastern European And The Balkans Stock Markets," Annals of Faculty of Economics, University of Oradea, Faculty of Economics, vol. 1(1), pages 1113-1124, July.
    8. Hiremath, Gourishankar S & Bandi, Kamaiah, 2010. "Long Memory in Stock Market Volatility:Evidence from India," MPRA Paper 48519, University Library of Munich, Germany.
    9. John Francis Diaz & Jo-Hui Chen, 2017. "Testing for Long-memory and Chaos in the Returns of Currency Exchange-traded Notes (ETNs)," Journal of Applied Finance & Banking, SCIENPRESS Ltd, vol. 7(4), pages 1-2.
    10. Cevik, Emrah Ismail & Topaloğlu, Gültekin, 2014. "Volatilitede uzun hafıza ve yapısal kırılma: Borsa Istanbul örneği [Long memory and structural breaks on volatility: evidence from Borsa Istanbul]," MPRA Paper 71485, University Library of Munich, Germany, revised 2014.

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    More about this item

    Keywords

    Long memory; structural breaks in variance; Figarch model;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics

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