Advanced Search
MyIDEAS: Login to save this paper or follow this series

Technical Analysis with a Long-Term Perspective: Trading Strategies and Market Timing Ability

Contents:

Author Info

  • Isakov, Dusan
  • Marti, Didier

Abstract

This paper extends the literature on the profitability of technical analysis in three directions. First, we investigate the performance of complex trading rules based on moving averages computed over longer periods than those usually considered. Different trading rules are simulated on daily prices of the Standard & Poor’s 500 index and we find that trading rules are more profitable when signals are generated over long horizons. Second, we analyse whether financial leverage can improve the profitability of different strategies, which appears to be the case when leverage is achieved with debt. Third, we propose a new market timing test that assesses whether a trading strategy can generate signals corresponding to bull and bear markets. The results of this test show that complex rules produce high proportions of accurate signals.

Download Info

If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
File URL: http://doc.rero.ch/lm.php?url=1000,44,2,20110817143137-RE/WP_SES_421.pdf
Download Restriction: no

Bibliographic Info

Paper provided by Faculty of Economics and Social Sciences, University of Freiburg/Fribourg Switzerland in its series FSES Working Papers with number 421.

as in new window
Length: 41 pages
Date of creation: 17 Aug 2011
Date of revision:
Handle: RePEc:fri:fribow:fribow00421

Contact details of provider:
Postal: Bd de Pérolles 90, CH-1700 Fribourg
Phone: +41 26 300 8200
Fax: +41 26 300 9725
Email:
Web page: http://www.unifr.ch/ses/
More information through EDIRC

Order Information:
Email:

Related research

Keywords: Technical trading ; Moving average ; Forecasting ; Leverage ; Market timing;

Find related papers by JEL classification:

This paper has been announced in the following NEP Reports:

References

References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
as in new window
  1. Joseph P. Romano & Michael Wolf, 2003. "Stepwise Multiple Testing as Formalized Data Snooping," Working Papers 17, Barcelona Graduate School of Economics.
  2. Kian‐Ping Lim & Robert Brooks, 2011. "The Evolution Of Stock Market Efficiency Over Time: A Survey Of The Empirical Literature," Journal of Economic Surveys, Wiley Blackwell, Wiley Blackwell, vol. 25(1), pages 69-108, 02.
  3. Fong, Wai Mun & Yong, Lawrence H. M., 2005. "Chasing trends: recursive moving average trading rules and internet stocks," Journal of Empirical Finance, Elsevier, Elsevier, vol. 12(1), pages 43-76, January.
  4. Dueker, Michael & Neely, Christopher J., 2007. "Can Markov switching models predict excess foreign exchange returns?," Journal of Banking & Finance, Elsevier, Elsevier, vol. 31(2), pages 279-296, February.
  5. Skouras, Spyros, 2001. "Financial returns and efficiency as seen by an artificial technical analyst," Journal of Economic Dynamics and Control, Elsevier, Elsevier, vol. 25(1-2), pages 213-244, January.
  6. Allan Timmermann & Halbert White & Ryan Sullivan, 1998. "Data-Snooping, Technical Trading, Rule Performance and the Bootstrap," FMG Discussion Papers, Financial Markets Group dp303, Financial Markets Group.
  7. Alan Goodacre & Jacqueline Bosher & Andrew Dove, 1999. "Testing the CRISMA trading system: evidence from the UK market," Applied Financial Economics, Taylor & Francis Journals, Taylor & Francis Journals, vol. 9(5), pages 455-468.
  8. Hans Dewachter & Marco Lyrio, 2002. "The Economic Value of Technical Trading Rules: A Non-parametric Utility-based Approach," International Economics Working Papers Series, Katholieke Universiteit Leuven, Centrum voor Economische Studiën, International Economics ces0203, Katholieke Universiteit Leuven, Centrum voor Economische Studiën, International Economics.
  9. Hendrik Bessembinder & Kalok Chan, 1998. "Market Efficiency and the Returns to Technical Analysis," Financial Management, Financial Management Association, Financial Management Association, vol. 27(2), Summer.
  10. Burton G. Malkiel, 2003. "The Efficient Market Hypothesis and Its Critics," Working Papers, Princeton University, Department of Economics, Center for Economic Policy Studies. 111, Princeton University, Department of Economics, Center for Economic Policy Studies..
  11. Brock, William & Lakonishok, Josef & LeBaron, Blake, 1992. " Simple Technical Trading Rules and the Stochastic Properties of Stock Returns," Journal of Finance, American Finance Association, American Finance Association, vol. 47(5), pages 1731-64, December.
  12. Dewachter, Hans, 2001. "Can Markov switching models replicate chartist profits in the foreign exchange market?," Journal of International Money and Finance, Elsevier, Elsevier, vol. 20(1), pages 25-41, February.
  13. Hudson, Robert & Dempsey, Michael & Keasey, Kevin, 1996. "A note on the weak form efficiency of capital markets: The application of simple technical trading rules to UK stock prices - 1935 to 1994," Journal of Banking & Finance, Elsevier, Elsevier, vol. 20(6), pages 1121-1132, July.
  14. Burton G. Malkiel, 2003. "The Efficient Market Hypothesis and Its Critics," Journal of Economic Perspectives, American Economic Association, American Economic Association, vol. 17(1), pages 59-82, Winter.
  15. Cheol-Ho Park & Scott H. Irwin, 2007. "What Do We Know About The Profitability Of Technical Analysis?," Journal of Economic Surveys, Wiley Blackwell, Wiley Blackwell, vol. 21(4), pages 786-826, 09.
  16. 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, Elsevier, vol. 17(3), pages 471-484, June.
  17. Allen, Franklin & Karjalainen, Risto, 1999. "Using genetic algorithms to find technical trading rules," Journal of Financial Economics, Elsevier, Elsevier, vol. 51(2), pages 245-271, February.
  18. Zhu, Yingzi & Zhou, Guofu, 2009. "Technical analysis: An asset allocation perspective on the use of moving averages," Journal of Financial Economics, Elsevier, Elsevier, vol. 92(3), pages 519-544, June.
  19. Po-Hsuan Hsu & Chung-Ming Kuan, 2005. "Reexamining the Profitability of Technical Analysis with Data Snooping Checks," Journal of Financial Econometrics, Society for Financial Econometrics, vol. 3(4), pages 606-628.
  20. Adrian R. Pagan & Kirill A. Sossounov, 2003. "A simple framework for analysing bull and bear markets," Journal of Applied Econometrics, John Wiley & Sons, Ltd., John Wiley & Sons, Ltd., vol. 18(1), pages 23-46.
  21. Neftci, Salih N, 1991. "Naive Trading Rules in Financial Markets and Wiener-Kolmogorov Prediction Theory: A Study of "Technical Analysis."," The Journal of Business, University of Chicago Press, University of Chicago Press, vol. 64(4), pages 549-71, October.
  22. Thomas Gehrig & Lukas Menkhoff, 2006. "Extended evidence on the use of technical analysis in foreign exchange," International Journal of Finance & Economics, John Wiley & Sons, Ltd., John Wiley & Sons, Ltd., vol. 11(4), pages 327-338.
  23. Halbert White, 2000. "A Reality Check for Data Snooping," Econometrica, Econometric Society, Econometric Society, vol. 68(5), pages 1097-1126, September.
  24. Kidd, Willis V. & Brorsen, B. Wade, 2004. "Why have the returns to technical analysis decreased?," Journal of Economics and Business, Elsevier, Elsevier, vol. 56(3), pages 159-176.
  25. Hansen, Peter Reinhard, 2005. "A Test for Superior Predictive Ability," Journal of Business & Economic Statistics, American Statistical Association, American Statistical Association, vol. 23, pages 365-380, October.
Full references (including those not matched with items on IDEAS)

Citations

Lists

This item is not listed on Wikipedia, on a reading list or among the top items on IDEAS.

Statistics

Access and download statistics

Corrections

When requesting a correction, please mention this item's handle: RePEc:fri:fribow:fribow00421. 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: (Ivo raemy).

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 references are entirely missing, you can add them using this form.

If the full references list an item that is present in RePEc, but the system did not link 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 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.