IDEAS home Printed from https://ideas.repec.org/a/taf/apfiec/v14y2004i3p209-214.html
   My bibliography  Save this article

Back to the future: an empirical investigation into the validity of stock index models over time

Author

Listed:
  • Barbara Summers
  • Evan Griffiths
  • Robert Hudson

Abstract

The use of technical analysis to predict security price movements from past price series has been supported by a number of academic research studies. These studies are broadly based on the premise that a technical trading rule should have constant validity over time. This premise is in accord with the practitioner rational for technical analysis, which is that, in the securities markets, history tends to repeat itself due to the relative constancy of human behaviour. The primary purpose of this paper is to investigate the extent to which technical trading rules have constant validity over time by determining the extent to which rules derived entirely from a particular time period can have validity over a variety of different time periods. It is found that rules derived from the data from the early period can be predictive at a later date and, rather unexpectedly, can even exceed the predictive power of rules derived from more contemporary data. It is hypothesized that this may be due to a decreasing signal to noise ratio in the data as the volatility of the index increases over time. The findings tend to support the assertion that, with respect to share trading, 'history repeats itself' with the caveat that there are factors that confound modelling in later periods.

Suggested Citation

  • Barbara Summers & Evan Griffiths & Robert Hudson, 2004. "Back to the future: an empirical investigation into the validity of stock index models over time," Applied Financial Economics, Taylor & Francis Journals, vol. 14(3), pages 209-214.
    • Handle: RePEc:taf:apfiec:v:14:y:2004:i:3:p:209-214
    DOI: 10.1080/0960310042000187351
    as

    Download full text from publisher

    File URL: http://www.tandfonline.com/doi/abs/10.1080/0960310042000187351
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1080/0960310042000187351?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    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. Andrew W. Lo & Harry Mamaysky & Jiang Wang, 2000. "Foundations of Technical Analysis: Computational Algorithms, Statistical Inference, and Empirical Implementation," Journal of Finance, American Finance Association, vol. 55(4), pages 1705-1765, August.
    2. Neely, Christopher & Weller, Paul & Dittmar, Rob, 1997. "Is Technical Analysis in the Foreign Exchange Market Profitable? A Genetic Programming Approach," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 32(4), pages 405-426, December.
    3. Taylor, Mark P. & Allen, Helen, 1992. "The use of technical analysis in the foreign exchange market," Journal of International Money and Finance, Elsevier, vol. 11(3), pages 304-314, June.
    4. Brock, William & Lakonishok, Josef & LeBaron, Blake, 1992. "Simple Technical Trading Rules and the Stochastic Properties of Stock Returns," Journal of Finance, American Finance Association, vol. 47(5), pages 1731-1764, December.
    5. Franklin Allen & Risto Karjalainen, "undated". "Using Genetic Algorithms to Find Technical Trading Rules (Revised: 20-95)," Rodney L. White Center for Financial Research Working Papers 20-93, Wharton School Rodney L. White Center for Financial Research.
    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. Stephan Schulmeister, 2000. "Technical Analysis and Exchange Rate Dynamics," WIFO Studies, WIFO, number 25857.
    2. Trifan, Emanuela, 2004. "Entscheidungsregeln und ihr Einfluss auf den Aktienkurs," Darmstadt Discussion Papers in Economics 131, Darmstadt University of Technology, Department of Law and Economics.
    3. Skouras, Spyros, 2001. "Financial returns and efficiency as seen by an artificial technical analyst," Journal of Economic Dynamics and Control, Elsevier, vol. 25(1-2), pages 213-244, January.
    4. Lukas Menkhoff & Mark P. Taylor, 2007. "The Obstinate Passion of Foreign Exchange Professionals: Technical Analysis," Journal of Economic Literature, American Economic Association, vol. 45(4), pages 936-972, December.
    5. Friesen, Geoffrey C. & Weller, Paul A. & Dunham, Lee M., 2009. "Price trends and patterns in technical analysis: A theoretical and empirical examination," Journal of Banking & Finance, Elsevier, vol. 33(6), pages 1089-1100, June.
    6. Heng-Chih Chou & Dar-Hsin Chen, 2019. "The use of technical analysis in sale-and-purchase transactions of secondhand ships," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 21(2), pages 223-240, June.
    7. Trifan, Emanuela, 2004. "Decision Rules and their Influence on Asset Prices," Darmstadt Discussion Papers in Economics 139, Darmstadt University of Technology, Department of Law and Economics.
    8. Christopher J. Neely & Paul A. Weller, 2011. "Technical analysis in the foreign exchange market," Working Papers 2011-001, Federal Reserve Bank of St. Louis.
    9. Schmitt, Noemi & Westerhoff, Frank, 2021. "Trend followers, contrarians and fundamentalists: Explaining the dynamics of financial markets," Journal of Economic Behavior & Organization, Elsevier, vol. 192(C), pages 117-136.
    10. Walid Omrane & Hervé Oppens, 2006. "The performance analysis of chart patterns: Monte Carlo simulation and evidence from the euro/dollar foreign exchange market," Empirical Economics, Springer, vol. 30(4), pages 947-971, January.
    11. Trifan, Emanuela, 2004. "Decision Rules and their Influence on Asset Prices," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 37211, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    12. Senol Emir & Hasan Dincer & Umit Hacioglu & Serhat Yuksel, 2016. "Random Regression Forest Model using Technical Analysis Variables: An application on Turkish Banking Sector in Borsa Istanbul (BIST)," International Journal of Finance & Banking Studies, Center for the Strategic Studies in Business and Finance, vol. 5(3), pages 85-102, April.
    13. repec:bla:jfinan:v:58:y:2003:i:5:p:1791-1820 is not listed on IDEAS
    14. Cheol‐Ho Park & Scott H. Irwin, 2007. "What Do We Know About The Profitability Of Technical Analysis?," Journal of Economic Surveys, Wiley Blackwell, vol. 21(4), pages 786-826, September.
    15. Jacinta Chan Phooi M’ng & Rozaimah Zainudin, 2016. "Assessing the Efficacy of Adjustable Moving Averages Using ASEAN-5 Currencies," PLOS ONE, Public Library of Science, vol. 11(8), pages 1-19, August.
    16. BEN OMRANE, Walid & VAN OPPEN, Hervé, 2004. "The predictive success and profitability of chart patterns in the Euro/Dollar foreign exchange market," LIDAM Discussion Papers CORE 2004035, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    17. Hoffmann, Arvid O.I. & Shefrin, Hersh, 2014. "Technical analysis and individual investors," Journal of Economic Behavior & Organization, Elsevier, vol. 107(PB), pages 487-511.
    18. Pereira, Robert, 1999. "Forecasting Ability But No Profitability: An Empirical Evaluation of Genetic Algorithm-optimised Technical Trading Rules," MPRA Paper 9055, University Library of Munich, Germany.
    19. Bajgrowicz, Pierre & Scaillet, Olivier, 2012. "Technical trading revisited: False discoveries, persistence tests, and transaction costs," Journal of Financial Economics, Elsevier, vol. 106(3), pages 473-491.
    20. Zarrabi, Nima & Snaith, Stuart & Coakley, Jerry, 2017. "FX technical trading rules can be profitable sometimes!," International Review of Financial Analysis, Elsevier, vol. 49(C), pages 113-127.
    21. Bohm, Volker & Wenzelburger, Jan, 2005. "On the performance of efficient portfolios," Journal of Economic Dynamics and Control, Elsevier, vol. 29(4), pages 721-740, April.

    More about this item

    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:taf:apfiec:v:14:y:2004:i:3:p:209-214. 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: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/RAFE20 .

    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.