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Long memory in a small stock market

Author

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  • Jussi Tolvi

    (University of Turku)

Abstract
The presence of long memory in Finnish stock market return data is tested using nonparametric methods. The data set has daily returns on six indices and forty companies. Depending on the testing method used, statistically significant long memory is detected in 24% to 67% of the series. This is considerably more than what is usually found in data of this kind.

Suggested Citation

  • Jussi Tolvi, 2003. "Long memory in a small stock market," Economics Bulletin, AccessEcon, vol. 7(3), pages 1-13.
    • Handle: RePEc:ebl:ecbull:eb-03g10001
    as

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    File URL: http://www.accessecon.com/pubs/EB/2003/Volume7/EB-03G10001A.pdf
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    References listed on IDEAS

    as
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    Cited by:

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    2. Christos Christodoulou-Volos & Fotios Siokis, 2006. "Long range dependence in stock market returns," Applied Financial Economics, Taylor & Francis Journals, vol. 16(18), pages 1331-1338.
    3. 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.
    4. Ibrahim M. Awad & Abdel-Rahman Al-Ewesat, 2017. "Volatility Persistence in Palestine Exchange Bulls and Bears: An Econometric Analysis of Time Series Data," Review of Economics & Finance, Better Advances Press, Canada, vol. 9, pages 83-97, August.
    5. Kuswanto, Heri, 2009. "A New Simple Test Against Spurious Long Memory Using Temporal Aggregation," Hannover Economic Papers (HEP) dp-425, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    6. Héctor F. Salazar-Núñez & Francisco Venegas-Martínez & Cuauhtémoc Calderón-Villareal, 2017. "¿Existe memoria larga en mercados bursátiles, o depende del modelo, periodo o frecuencia? (Is there Long Memory in Stock Markets, or Does it Depend on the Model, Period or Frequency?)," Ensayos Revista de Economia, Universidad Autonoma de Nuevo Leon, Facultad de Economia, vol. 0(1), pages 1-24, May.

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    JEL classification:

    • G1 - Financial Economics - - General Financial Markets
    • C5 - Mathematical and Quantitative Methods - - Econometric Modeling

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