IDEAS home Printed from https://ideas.repec.org/a/eee/ecmode/v50y2015icp254-265.html
   My bibliography  Save this article

Semiparametric generalized long-memory modeling of some mena stock market returns: A wavelet approach

Author

Listed:
  • Boubaker, Heni
  • Sghaier, Nadia

Abstract

This paper proposes a new class of semiparametric generalized long-memory models with FIAPARCH errors that extends the conventional GARMA model to incorporate nonlinear deterministic trend and allows for time-varying volatility. To estimate the parameters, we implement a wavelet theory. We provide an empirical application to some MENA stock markets and find that the proposed model offers an interesting framework to describe seasonal long-range dependence and nonlinear trend in return as well as persistence to shocks in conditional volatility. The predictive results also indicate that this model outperforms the traditional FARMA-FIAPARCH process.

Suggested Citation

  • Boubaker, Heni & Sghaier, Nadia, 2015. "Semiparametric generalized long-memory modeling of some mena stock market returns: A wavelet approach," Economic Modelling, Elsevier, vol. 50(C), pages 254-265.
  • Handle: RePEc:eee:ecmode:v:50:y:2015:i:c:p:254-265
    DOI: 10.1016/j.econmod.2015.06.027
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0264999315001844
    Download Restriction: Full text for ScienceDirect subscribers only

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Ariss, Rima Turk & Rezvanian, Rasoul & Mehdian, Seyed M., 2011. "Calendar anomalies in the Gulf Cooperation Council stock markets," Emerging Markets Review, Elsevier, vol. 12(3), pages 293-307, September.
    2. Abraham Abraham, 2002. "Testing the Random Walk Behavior and Efficiency of the Gulf Stock Markets," The Financial Review, Eastern Finance Association, vol. 37(3), pages 469-480, August.
    3. Joakim Westerlund & Paresh Narayan, 2013. "Testing the Efficient Market Hypothesis in Conditionally Heteroskedastic Futures Markets," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 33(11), pages 1024-1045, November.
    4. Baillie, Richard T. & Bollerslev, Tim & Mikkelsen, Hans Ole, 1996. "Fractionally integrated generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 74(1), pages 3-30, September.
    5. Kang, Sang Hoon & Yoon, Seong-Min, 2008. "Long memory features in the high frequency data of the Korean stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(21), pages 5189-5196.
    6. Phan, Dinh Hoang Bach & Sharma, Susan Sunila & Narayan, Paresh Kumar, 2015. "Stock return forecasting: Some new evidence," International Review of Financial Analysis, Elsevier, vol. 40(C), pages 38-51.
    7. Bollerslev, Tim & Ole Mikkelsen, Hans, 1996. "Modeling and pricing long memory in stock market volatility," Journal of Econometrics, Elsevier, vol. 73(1), pages 151-184, July.
    8. Floros, Christos & Salvador, Enrique, 2014. "Calendar anomalies in cash and stock index futures: International evidence," Economic Modelling, Elsevier, vol. 37(C), pages 216-223.
    9. Abdmoulah, Walid, 2010. "Testing the evolving efficiency of Arab stock markets," International Review of Financial Analysis, Elsevier, vol. 19(1), pages 25-34, January.
    10. Narayan, Paresh Kumar & Sharma, Susan Sunila & Thuraisamy, Kannan Sivananthan, 2014. "An analysis of price discovery from panel data models of CDS and equity returns," Journal of Banking & Finance, Elsevier, vol. 41(C), pages 167-177.
    11. Phan, Dinh Hoang Bach & Sharma, Susan Sunila & Narayan, Paresh Kumar, 2015. "Oil price and stock returns of consumers and producers of crude oil," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 34(C), pages 245-262.
    12. Al Janabi, Mazin A.M. & Hatemi-J, Abdulnasser & Irandoust, Manuchehr, 2010. "An empirical investigation of the informational efficiency of the GCC equity markets: Evidence from bootstrap simulation," International Review of Financial Analysis, Elsevier, vol. 19(1), pages 47-54, January.
    13. Granger, Clive W. J. & Hyung, Namwon, 2004. "Occasional structural breaks and long memory with an application to the S&P 500 absolute stock returns," Journal of Empirical Finance, Elsevier, vol. 11(3), pages 399-421, June.
    14. Boubaker Heni & Boutahar Mohamed, 2011. "A wavelet-based approach for modelling exchange rates," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 20(2), pages 201-220, June.
    15. Guglielmo Maria Caporale & Juncal Cuñado & Luis A. Gil-Alana, 2013. "Modelling long-run trends and cycles in financial time series data," Journal of Time Series Analysis, Wiley Blackwell, vol. 34(3), pages 405-421, May.
    16. Guglielmo Maria Caporale & Luis Gil‐Alana, 2014. "Long‐Run and Cyclical Dynamics in the US Stock Market," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 33(2), pages 147-161, March.
    17. Mohamed Chikhi & Anne Péguin-Feissolle & Michel Terraza, 2013. "SEMIFARMA-HYGARCH Modeling of Dow Jones Return Persistence," Computational Economics, Springer;Society for Computational Economics, vol. 41(2), pages 249-265, February.
    18. Bordignon, Silvano & Caporin, Massimiliano & Lisi, Francesco, 2007. "Generalised long-memory GARCH models for intra-daily volatility," Computational Statistics & Data Analysis, Elsevier, vol. 51(12), pages 5900-5912, August.
    19. Chung, Ching-Fan, 1996. "Estimating a generalized long memory process," Journal of Econometrics, Elsevier, vol. 73(1), pages 237-259, July.
    20. Hammoudeh, Shawkat & Li, Huimin, 2008. "Sudden changes in volatility in emerging markets: The case of Gulf Arab stock markets," International Review of Financial Analysis, Elsevier, vol. 17(1), pages 47-63.
    21. Perron, Pierre & Qu, Zhongjun, 2010. "Long-Memory and Level Shifts in the Volatility of Stock Market Return Indices," Journal of Business & Economic Statistics, American Statistical Association, vol. 28(2), pages 275-290.
    22. Bley, Jorg, 2011. "Are GCC stock markets predictable?," Emerging Markets Review, Elsevier, vol. 12(3), pages 217-237, September.
    23. Sang Hoon Kang & SEONG-MIN YOON, 2008. "Asymmetry and Long Memory Features in Volatility: Evidence From Korean Stock Market," Korean Economic Review, Korean Economic Association, vol. 24, pages 383-412.
    24. Susan Sunila Sharma & Paresh Kumar Narayan, 2012. "Firm heterogeneity and calendar anomalies," Applied Financial Economics, Taylor & Francis Journals, vol. 22(23), pages 1931-1949, December.
    25. Beran, Jan & Feng, Yuanhua & Ghosh, Sucharita & Sibbertsen, Philipp, 2002. "On robust local polynomial estimation with long-memory errors," International Journal of Forecasting, Elsevier, vol. 18(2), pages 227-241.
    26. Narayan, Paresh Kumar & Sharma, Susan Sunila, 2015. "Does data frequency matter for the impact of forward premium on spot exchange rate?," International Review of Financial Analysis, Elsevier, vol. 39(C), pages 45-53.
    27. Caetano, Marco Antonio Leonel & Yoneyama, Takashi, 2012. "A method for detection of abrupt changes in the financial market combining wavelet decomposition and correlation graphs," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(20), pages 4877-4882.
    28. Jan Beran & Yuanhua Feng, 2002. "Local Polynomial Fitting with Long-Memory, Short-Memory and Antipersistent Errors," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 54(2), pages 291-311, June.
    29. Y. K. Tse, 1998. "The conditional heteroscedasticity of the yen-dollar exchange rate," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 13(1), pages 49-55.
    30. Robinson, Peter M., 1997. "Large-sample inference for nonparametric regression with dependent errors," LSE Research Online Documents on Economics 302, London School of Economics and Political Science, LSE Library.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. repec:eee:finana:v:56:y:2018:i:c:p:167-180 is not listed on IDEAS
    2. Belasen, Ariel R. & Kutan, Ali M. & Belasen, Alan T., 2017. "The impact of unsuccessful pirate attacks on financial markets: Evidence in support of Leeson's reputation-building theory," Economic Modelling, Elsevier, vol. 60(C), pages 344-351.
    3. repec:eee:riibaf:v:42:y:2017:i:c:p:39-60 is not listed on IDEAS

    More about this item

    Keywords

    SEMIGARMA process; FIAPARCH errors; Wavelet domain; Stock markets;

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:ecmode:v:50:y:2015:i:c:p:254-265. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Dana Niculescu). General contact details of provider: http://www.elsevier.com/locate/inca/30411 .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.