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Long memory in the Portuguese stock market

Author

Listed:
  • Christos Floros
  • Shabbar Jaffry
  • Goncalo Valle Lima

Abstract

Purpose - This paper's aim is to test for the presence of fractional integration, or long memory, in the daily returns of the Portuguese stock market using autoregressive fractionally integrated moving average (ARFIMA), generalised autoregressive conditional heteroskedasticity (GARCH) and ARFIMA‐FIGARCH models. Design/methodology/approach - The data cover two periods: 4 January 1993‐13 January 2006 (full sample), and 1 February 2002‐13 January 2006 (that is, data are considered after the merger of the Portuguese Stock Exchange with Euronext). Findings - The results from the full sample show strong evidence of long memory in stock returns. When data after the merger are considered, weaker evidence of long memory is found. It is concluded that the Portuguese stock market is more efficient after the merger with Euronext. Originality/value - The findings of this paper are helpful to financial managers and investors dealing with Portuguese stock indices.

Suggested Citation

  • Christos Floros & Shabbar Jaffry & Goncalo Valle Lima, 2007. "Long memory in the Portuguese stock market," Studies in Economics and Finance, Emerald Group Publishing Limited, vol. 24(3), pages 220-232, August.
    • Handle: RePEc:eme:sefpps:v:24:y:2007:i:3:p:220-232
    DOI: 10.1108/10867370710817400
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    Citations

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    Cited by:

    1. Fu, Hui & Chen, Wenting & He, Xin-Jiang, 2018. "On a class of estimation and test for long memory," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 509(C), pages 906-920.
    2. Hiremath, Gourishankar S & Bandi, Kamaiah, 2011. "Testing Long Memory in Stock Returns of Emerging Markets: Some Further Evidence," MPRA Paper 48517, University Library of Munich, Germany.
    3. Christos Floros, 2011. "On the relationship between weather and stock market returns," Studies in Economics and Finance, Emerald Group Publishing Limited, vol. 28(1), pages 5-13, March.
    4. Kunal Saha & Vinodh Madhavan & Chandrashekhar G. R. & David McMillan, 2020. "Pitfalls in long memory research," Cogent Economics & Finance, Taylor & Francis Journals, vol. 8(1), pages 1733280-173, January.
    5. 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.
    6. Hiremath, Gourishankar S & Bandi, Kamaiah, 2010. "Long Memory in Stock Market Volatility:Evidence from India," MPRA Paper 48519, University Library of Munich, Germany.
    7. Biswajit Patra & Puja Padhi, 2015. "Backtesting of Value at Risk Methodology: Analysis of Banking Shares in India," Margin: The Journal of Applied Economic Research, National Council of Applied Economic Research, vol. 9(3), pages 254-277, August.
    8. Adnan Kasman & Erdost Torun, 2007. "Long Memory in the Turkish Stock Market Return and Volatility," Central Bank Review, Research and Monetary Policy Department, Central Bank of the Republic of Turkey, vol. 7(2), pages 13-27.
    9. 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.
    10. Mohammad Nazeri-Tahroudi & Yousef Ramezani & Carlo Michele & Rasoul Mirabbasi, 2022. "Bivariate Simulation of Potential Evapotranspiration Using Copula-GARCH Model," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 36(3), pages 1007-1024, February.
    11. Ding, Liang & Luo, Yi & Lin, Yan & Huang, Yirong, 2021. "Revisiting the relations between Hurst exponent and fractional differencing parameter for long memory," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 566(C).
    12. Pilar Iglesias & Jaime San Martín & Soledad Torres & Frederi Viens, 2011. "Option pricing under a Gamma-modulated diffusion process," Annals of Finance, Springer, vol. 7(2), pages 199-219, May.
    13. Kasman, Adnan & Kasman, Saadet & Torun, Erdost, 2009. "Dual long memory property in returns and volatility: Evidence from the CEE countries' stock markets," Emerging Markets Review, Elsevier, vol. 10(2), pages 122-139, June.

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