IDEAS home Printed from https://ideas.repec.org/p/pra/mprapa/76629.html
   My bibliography  Save this paper

اختبار القدرة على التنبؤ بعوائد مؤشر سوق الدار البيضاء المالي من 2007 إلى 2011
[Testing the Predictability of Casablanca Stock Exchange Returns (2007-2011)]

Author

Listed:
  • BEKHALED, Aicha
  • DADENE, Abdelghani
  • CHIKHI, Mohamed

Abstract

تهدف هذه الدراسة إلى اختبار ما إذا كانت سلسلة عائد المؤشر العام لسوق الدار البيضاء مستقلة فيما بينها وتتبع السير العشوائي، حيث قمنا بتقدير مدى انحراف سلسلة مؤشر العائد عن الكفاءة على المستوى الضعيف من خلال اختبار القدرة على التنبؤ بالعوائد على المدى القصير، باقتراح نموذج وقد شملت العينة بيانات تاريخية لسعر إغلاق المؤشر العام لسوق الدار البيضاء، خلال الفترة من 2007 إلى 2011، وهي مشاهدات يومية، تبلغ 827 مشاهدة، وقد وجدنا أن النموذج المقترح أفضل من نموذج السير لعشوائي من حيث الجودة التنبؤية، وأن عوائد مؤشر سوق الدار البيضاء المالي قابلة للتنبؤ على المدى القصير، وحركة الأسعار تظهر كنتيجة لصدمة خارجية عابرة ، وبالتالي فالسوق لا يعتبر كفؤا عند المستوى الضعيف. The study aims to test whether the Casablanca Stock exchange returns are independent and identically distributed (i.i.d.). We use ARIMA(1,1,0)-GARCH(1,1) model to test the forecastability of stock exchange returns series. The empirical study focuses on the logarithmic series of daily Moroccan stock exchange series covering a historical period from 2007 to 2011. We have found that the proposed model is better than the random walk model in terms of predictive quality, and the Casablanca Stock exchange returns is predictable for short-term and the price movements appear as a result of transitory exogenous shock, therefore the weak efficiency assumption of financial markets seems violated.

Suggested Citation

  • BEKHALED, Aicha & DADENE, Abdelghani & CHIKHI, Mohamed, 2014. "اختبار القدرة على التنبؤ بعوائد مؤشر سوق الدار البيضاء المالي من 2007 إلى 2011 [Testing the Predictability of Casablanca Stock Exchange Returns (2007-2011)]," MPRA Paper 76629, University Library of Munich, Germany, revised 2014.
  • Handle: RePEc:pra:mprapa:76629
    as

    Download full text from publisher

    File URL: https://mpra.ub.uni-muenchen.de/76629/1/MPRA_paper_76629.pdf
    File Function: original version
    Download Restriction: no

    File URL: https://mpra.ub.uni-muenchen.de/76714/1/MPRA_paper_76629.pdf
    File Function: revised version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Patro, Dilip K. & Wu, Yangru, 2004. "Predictability of short-horizon returns in international equity markets," Journal of Empirical Finance, Elsevier, vol. 11(4), pages 553-584, September.
    2. Fama, Eugene F, 1970. "Efficient Capital Markets: A Review of Theory and Empirical Work," Journal of Finance, American Finance Association, vol. 25(2), pages 383-417, May.
    3. Jensen, Michael C., 1978. "Some anomalous evidence regarding market efficiency," Journal of Financial Economics, Elsevier, vol. 6(2-3), pages 95-101.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Christiane Goodfellow & Dirk Schiereck & Steffen Wippler, 2013. "Are behavioural finance equity funds a superior investment? A note on fund performance and market efficiency," Journal of Asset Management, Palgrave Macmillan, vol. 14(2), pages 111-119, April.
    2. Thomas Delcey, 2019. "Samuelson vs Fama on the Efficient Market Hypothesis: The Point of View of Expertise [Samuelson vs Fama sur l’efficience informationnelle des marchés financiers : le point de vue de l’expertise]," Post-Print hal-01618347, HAL.
    3. Raushan Kumar, 2021. "Predicting Wheat Futures Prices in India," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 28(1), pages 121-140, March.
    4. 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.
    5. Guglielmo Caporale & Luis Gil-Alana & Alex Plastun & Inna Makarenko, 2016. "Intraday Anomalies and Market Efficiency: A Trading Robot Analysis," Computational Economics, Springer;Society for Computational Economics, vol. 47(2), pages 275-295, February.
    6. Kühl, Michael, 2007. "Cointegration in the foreign exchange market and market efficiency since the introduction of the Euro: Evidence based on bivariate cointegration analyses," University of Göttingen Working Papers in Economics 68, University of Goettingen, Department of Economics.
    7. Michael Demmler & Amilcar Orlian Fernández Domínguez, 2021. "Bitcoin and the South Sea Company: A comparative analysis," Revista Finanzas y Politica Economica, Universidad Católica de Colombia, vol. 13(1), pages 197-224, March.
    8. Stefan Nagel, 2013. "Empirical Cross-Sectional Asset Pricing," Annual Review of Financial Economics, Annual Reviews, vol. 5(1), pages 167-199, November.
    9. Juan Reboredo & José Matías & Raquel Garcia-Rubio, 2012. "Nonlinearity in Forecasting of High-Frequency Stock Returns," Computational Economics, Springer;Society for Computational Economics, vol. 40(3), pages 245-264, October.
    10. Michail Karoglou, 2009. "Stock Market Efficiency before and after a Financial Liberalisation Reform," Journal of Emerging Market Finance, Institute for Financial Management and Research, vol. 8(3), pages 315-340, September.
    11. Lim, Kian-Ping & Kim, Jae H., 2011. "Trade openness and the informational efficiency of emerging stock markets," Economic Modelling, Elsevier, vol. 28(5), pages 2228-2238, September.
    12. Dichtl, Hubert & Drobetz, Wolfgang, 2015. "Sell in May and Go Away: Still good advice for investors?," International Review of Financial Analysis, Elsevier, vol. 38(C), pages 29-43.
    13. Oussama Tilfani & My Youssef El Boukfaoui, 2020. "Multifractal Analysis of African Stock Markets During the 2007–2008 US Crisis," Review of Pacific Basin Financial Markets and Policies (RPBFMP), World Scientific Publishing Co. Pte. Ltd., vol. 22(04), pages 1-31, January.
    14. Khalil Jebran & Shihua Chen, 2017. "Examining anomalies in Islamic equity market of Pakistan," Journal of Sustainable Finance & Investment, Taylor & Francis Journals, vol. 7(3), pages 275-289, July.
    15. Philip Maymin, 2010. "Markets are efficient if and only if P = NP," Papers 1002.2284, arXiv.org, revised May 2010.
    16. Godfrey, Keith R.L., 2017. "Toward a model-free measure of market efficiency," Pacific-Basin Finance Journal, Elsevier, vol. 44(C), pages 97-112.
    17. Felicia Ramona Birau, 2011. "An Analysis Of Weak-Form Efficiency On The Bucharest Stock Exchange," Annals of University of Craiova - Economic Sciences Series, University of Craiova, Faculty of Economics and Business Administration, vol. 3(39), pages 194-205.
    18. Haugom, Erik & Ullrich, Carl J., 2012. "Market efficiency and risk premia in short-term forward prices," Energy Economics, Elsevier, vol. 34(6), pages 1931-1941.
    19. Peter Christoffersen & Francis X. Diebold, 2002. "Financial Asset Returns, Market Timing, and Volatility Dynamics," CIRANO Working Papers 2002s-02, CIRANO.
    20. Roland Rothenstein, 2018. "Quantification of market efficiency based on informational-entropy," Papers 1812.02371, arXiv.org.

    More about this item

    Keywords

    الكفاءة عند المستوى الضعيف، اختبار الارتباط الذاتي، السير العشوائي، سوق الدار البيضاء المالي، نموذج GARCH. Casablanca Stock Exchange; Weak efficiency; random walk; autocorrelation test; GARCH.;
    All these keywords.

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • 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
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

    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:pra:mprapa:76629. See general information about how to correct material in RePEc.

    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 bibliographic 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.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Joachim Winter (email available below). General contact details of provider: https://edirc.repec.org/data/vfmunde.html .

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

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.