IDEAS home Printed from https://ideas.repec.org/a/mth/ber888/v3y2013i1p498-511.html
   My bibliography  Save this article

Technical Analysis on Markets with Memory

Author

Listed:
  • PhD Flifel Kaouther

Abstract

Economists note that financial markets are experiencing alternating periods of euphoria and depression. The question they ask is to know how to "beat the market". Some, relying on the analysis of covariance, affirm portfolio diversification, others lean towards the reflexive interaction "players" and the market, others base their theory on their own experiences, give particular attention to the intrinsic value of the business and provide a strong distinction between the investor and the speculator. In this article we will discuss the relative merits of two classic strategies of prediction, "fundamental analysis" versus "technical analysis "(or" Chartism ") and this for different cases of figs for markets with and without memory.

Suggested Citation

  • PhD Flifel Kaouther, 2013. "Technical Analysis on Markets with Memory," Business and Economic Research, Macrothink Institute, vol. 3(1), pages 498-511, June.
    • Handle: RePEc:mth:ber888:v:3:y:2013:i:1:p:498-511
    as

    Download full text from publisher

    File URL: http://www.macrothink.org/journal/index.php/ber/article/view/3420/3169
    Download Restriction: no
    File URL: http://www.macrothink.org/journal/index.php/ber/article/view/3420
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Sweeney, Richard J., 1988. "Some New Filter Rule Tests: Methods and Results," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 23(3), pages 285-300, September.
    2. Limam Imed, 2003. "Is Long Memory a Property of Thin Stock Markets? International Evidence Using Arab Countries," Review of Middle East Economics and Finance, De Gruyter, vol. 1(3), pages 56-71, December.
    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. Enrique Rafael González Pozo, 2020. "An Argument Against Stock-Picking and Market-Timing: An Empirical Approach," Investigación & Desarrollo 0620, Universidad Privada Boliviana, revised Nov 2020.
    2. Charfeddine, Lanouar & Ajmi, Ahdi Noomen, 2013. "The Tunisian stock market index volatility: Long memory vs. switching regime," Emerging Markets Review, Elsevier, vol. 16(C), pages 170-182.
    3. Pierre Giot & Mikael Petitjean, 2011. "On the statistical and economic performance of stock return predictive regression models: an international perspective," Quantitative Finance, Taylor & Francis Journals, vol. 11(2), pages 175-193.
    4. Shynkevich, Andrei, 2013. "Time-series momentum as an intra- and inter-industry effect: Implications for market efficiency," Journal of Economics and Business, Elsevier, vol. 69(C), pages 64-85.
    5. Bhandari, Avishek, 2020. "Long memory and fractality among global equity markets: A multivariate wavelet approach," MPRA Paper 99653, University Library of Munich, Germany.
    6. Anju Bala & Kapil Gupta, 2020. "Examining The Long Memory In Stock Returns And Liquidity In India," Copernican Journal of Finance & Accounting, Uniwersytet Mikolaja Kopernika, vol. 9(3), pages 25-43.
    7. Lin, Xiaoqiang & Chen, Qiang & Tang, Zhenpeng, 2014. "Dynamic hedging strategy in incomplete market: Evidence from Shanghai fuel oil futures market," Economic Modelling, Elsevier, vol. 40(C), pages 81-90.
    8. Suzanne Fifield & David Power & C. Donald Sinclair, 2005. "An analysis of trading strategies in eleven European stock markets," The European Journal of Finance, Taylor & Francis Journals, vol. 11(6), pages 531-548.
    9. Nauzer Balsara & Jason Chen & Lin Zheng, 2009. "Profiting from a contrarian application of technical trading rules in the US stock market," Journal of Asset Management, Palgrave Macmillan, vol. 10(2), pages 97-123, June.
    10. Michael McAleer & John Suen & Wing Keung Wong, 2016. "Profiteering from the Dot-Com Bubble, Subprime Crisis and Asian Financial Crisis," The Japanese Economic Review, Japanese Economic Association, vol. 67(3), pages 257-279, September.
    11. Hsu, Po-Hsuan & Hsu, Yu-Chin & Kuan, Chung-Ming, 2010. "Testing the predictive ability of technical analysis using a new stepwise test without data snooping bias," Journal of Empirical Finance, Elsevier, vol. 17(3), pages 471-484, June.
    12. Qi Liu & Ka Po Kung, 2023. "Optimality of Buy-and-Hold Strategies," Eurasian Journal of Business and Management, Eurasian Publications, vol. 11(1), pages 32-45.
    13. Po-Hsuan Hsu & Chung-Ming Kuan, 2004. "Re-Examining the Profitability of Technical Analysis with White’s Reality Check," IEAS Working Paper : academic research 04-A003, Institute of Economics, Academia Sinica, Taipei, Taiwan.
    14. Charles J. Corrado & Suk-Hun Lee, 1992. "Filter Rule Tests Of The Economic Significance Of Serial Dependencies In Daily Stock Returns," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 15(4), pages 369-387, December.
    15. Žmuk Berislav, 2016. "Capabilities of Statistical Residual-Based Control Charts in Short- and Long-Term Stock Trading," Naše gospodarstvo/Our economy, Sciendo, vol. 62(1), pages 12-26, March.
    16. Ellis, Craig A. & Parbery, Simon A., 2005. "Is smarter better? A comparison of adaptive, and simple moving average trading strategies," Research in International Business and Finance, Elsevier, vol. 19(3), pages 399-411, September.
    17. Julián Andrada Félix & Fernando Fernández Rodríguez & María Dolores García Artiles, 2004. "Non-linear trading rules in the New York Stock Exchange," Documentos de trabajo conjunto ULL-ULPGC 2004-05, Facultad de Ciencias Económicas de la ULPGC.
    18. Kwon, Ki-Yeol & Kish, Richard J., 2002. "A comparative study of technical trading strategies and return predictability: an extension of Brock, Lakonishok, and LeBaron (1992) using NYSE and NASDAQ indices," The Quarterly Review of Economics and Finance, Elsevier, vol. 42(3), pages 611-631.
    19. Gu, Rongbao & Xiong, Wei & Li, Xinjie, 2015. "Does the singular value decomposition entropy have predictive power for stock market? — Evidence from the Shenzhen stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 439(C), pages 103-113.
    20. Saadet Kasman & Evrim Turgutlu & A. Duygu Ayhan, 2009. "Long memory in stock returns: evidence from the major emerging Central European stock markets," Applied Economics Letters, Taylor & Francis Journals, vol. 16(17), pages 1763-1768.

    More about this item

    Keywords

    Technical analysis; Fundamental analysis; Technical indicator; Long memory.;
    All these keywords.

    JEL classification:

    • R00 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General - - - General
    • Z0 - Other Special Topics - - General

    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:mth:ber888:v:3:y:2013:i:1:p:498-511. 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: Technical Support Office (email available below). General contact details of provider: http://www.macrothink.org/journal/index.php/ber .

    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.