IDEAS home Printed from https://ideas.repec.org/a/taf/apfiec/v19y2009i14p1171-1186.html
   My bibliography  Save this article

A study of the predictive performance of the moving average trading rule as applied to NYSE, the Athens Stock Exchange and the Vienna Stock Exchange: sensitivity analysis and implications for weak-form market efficiency testing

Author

Listed:
  • Alexandros Milionis
  • Evangelia Papanagiotou

Abstract

This work examines the variation of the simple Moving Average (MA) trading rule performance as a function of the MA length in New York Stock Exchange (NYSE), Athens Stock Exchange (ASE) and Vienna Stock Exchange (VSE) using daily data from May 1993 to April 2005. Results show that changes of the MA trading rule performance as a function of the length of the MA are in many cases random. Moreover, in the presence of a 0.5% fee per transaction, trading rule performance as a function of the MA length in several cases follow a random walk with a positive drift process, implying better performance for longer MAs. To an extent, due to the large variability of the trading rule performance observed in many cases, these results weaken previous conclusions regarding the predictive power of the rule where use was made of MAs with only specific lengths, as well as any conclusions regarding acceptance or rejection of the weak-form market efficiency hypothesis. Further, a preliminary qualitative analysis showed enhanced trading rule performance for very short MA lengths, a result which needs further investigation.

Suggested Citation

  • Alexandros Milionis & Evangelia Papanagiotou, 2009. "A study of the predictive performance of the moving average trading rule as applied to NYSE, the Athens Stock Exchange and the Vienna Stock Exchange: sensitivity analysis and implications for weak-for," Applied Financial Economics, Taylor & Francis Journals, vol. 19(14), pages 1171-1186.
    • Handle: RePEc:taf:apfiec:v:19:y:2009:i:14:p:1171-1186
    DOI: 10.1080/09603100802375519
    as

    Download full text from publisher

    File URL: http://www.tandfonline.com/doi/abs/10.1080/09603100802375519
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1080/09603100802375519?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. Ki-Yeol Kwon & Richard Kish, 2002. "Technical trading strategies and return predictability: NYSE," Applied Financial Economics, Taylor & Francis Journals, vol. 12(9), pages 639-653.
    2. Peter Huber, 1997. "Stock market returns in thin markets: evidence from the Vienna Stock Exchange," Applied Financial Economics, Taylor & Francis Journals, vol. 7(5), pages 493-498.
    3. Fang, Yue & Xu, Daming, 2003. "The predictability of asset returns: an approach combining technical analysis and time series forecasts," International Journal of Forecasting, Elsevier, vol. 19(3), pages 369-385.
    4. 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.
    5. Wing-Keung Wong & Meher Manzur & Boon-Kiat Chew, 2003. "How rewarding is technical analysis? Evidence from Singapore stock market," Applied Financial Economics, Taylor & Francis Journals, vol. 13(7), pages 543-551.
    6. 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, vol. 20(6), pages 1121-1132, July.
    7. Milionis, Alexandros E., 2007. "Efficient capital markets: A statistical definition and comments," Statistics & Probability Letters, Elsevier, vol. 77(6), pages 607-613, March.
    8. Hendrik Bessembinder & Kalok Chan, 1998. "Market Efficiency and the Returns to Technical Analysis," Financial Management, Financial Management Association, vol. 27(2), Summer.
    9. Elliott, Graham & Rothenberg, Thomas J & Stock, James H, 1996. "Efficient Tests for an Autoregressive Unit Root," Econometrica, Econometric Society, vol. 64(4), pages 813-836, July.
    10. Olson, Dennis, 2004. "Have trading rule profits in the currency markets declined over time?," Journal of Banking & Finance, Elsevier, vol. 28(1), pages 85-105, January.
    11. Mills, Terence C, 1997. "Technical Analysis and the London Stock Exchange: Testing Trading Rules Using the FT30," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 2(4), pages 319-331, October.
    12. 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.
    13. 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.
    14. Bessembinder, Hendrik & Chan, Kalok, 1995. "The profitability of technical trading rules in the Asian stock markets," Pacific-Basin Finance Journal, Elsevier, vol. 3(2-3), pages 257-284, July.
    15. F. FernAndez-RodrIguez & S. Sosvilla-Rivero & J. Andrada-FElix, 2003. "Technical analysis in foreign exchange markets: evidence from the EMS," Applied Financial Economics, Taylor & Francis Journals, vol. 13(2), pages 113-122.
    16. 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, vol. 64(4), pages 549-571, October.
    17. Fama, Eugene F, 1991. "Efficient Capital Markets: II," Journal of Finance, American Finance Association, vol. 46(5), pages 1575-1617, December.
    18. Laopodis, Nikiforos T., 2004. "Financial market liberalization and stock market efficiency: Evidence from the Athens Stock Exchange," Global Finance Journal, Elsevier, vol. 15(2), pages 103-123, August.
    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. Alexandros E. Milionis & Evangelia Papanagiotou, 2013. "Decomposing the predictive performance of the moving average trading rule of technical analysis: the contribution of linear and non-linear dependencies in stock returns," Journal of Applied Statistics, Taylor & Francis Journals, vol. 40(11), pages 2480-2494, November.
    2. Alexandros E. Milionis, 2019. "A simple return generating model in discrete time; implications for market efficiency testing," Working Papers 259, Bank of Greece.
    3. Alexandros E. Milionis & Dimitra K. Patsouri, 2011. "A conditional CAPM; implications for the estimation of systematic risk," Working Papers 131, Bank of Greece.

    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. Alexandros E. Milionis & Evangelia Papanagiotou, 2008. "A Note on the Use of Moving Average Trading Rules to Test For Weak from Efficiency in Capital Markets," Working Papers 91, Bank of Greece.
    2. Alexandros E. Milionis & Evangelia Papanagiotou, 2008. "On the Use of the Moving Average Trading Rule to Test for Weak Form Efficiency in Capital Markets," Economic Notes, Banca Monte dei Paschi di Siena SpA, vol. 37(2), pages 181-201, July.
    3. 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.
    4. Alexandros E. Milionis & Evangelia Papanagiotou, 2013. "Decomposing the predictive performance of the moving average trading rule of technical analysis: the contribution of linear and non-linear dependencies in stock returns," Journal of Applied Statistics, Taylor & Francis Journals, vol. 40(11), pages 2480-2494, November.
    5. Michael McAleer & John Suen & Wing Keung Wong, 2016. "Profiteering from the Dot-Com Bubble, Subprime Crisis and Asian Financial Crisis," The Japanese Economic Review, Springer, vol. 67(3), pages 257-279, September.
    6. R. Rosillo & D. de la Fuente & J. A. L. Brugos, 2013. "Technical analysis and the Spanish stock exchange: testing the RSI, MACD, momentum and stochastic rules using Spanish market companies," Applied Economics, Taylor & Francis Journals, vol. 45(12), pages 1541-1550, April.
    7. Marshall, Ben R. & Cahan, Rochester H., 2005. "Is technical analysis profitable on a stock market which has characteristics that suggest it may be inefficient?," Research in International Business and Finance, Elsevier, vol. 19(3), pages 384-398, September.
    8. Elaine Y. L. Loh, 2007. "An alternative test for weak form efficiency based on technical analysis," Applied Financial Economics, Taylor & Francis Journals, vol. 17(12), pages 1003-1012.
    9. Strobel, Marcus & Auer, Benjamin R., 2018. "Does the predictive power of variable moving average rules vanish over time and can we explain such tendencies?," International Review of Economics & Finance, Elsevier, vol. 53(C), pages 168-184.
    10. Martín García, Rodrigo & Ventura Pérez, Enrique & Arguedas Sanz, Raquel, 2020. "Temporal optimisation of signals emitted automatically by securities exchange indicators," Cuadernos de Gestión, Universidad del País Vasco - Instituto de Economía Aplicada a la Empresa (IEAE).
    11. 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.
    12. Schulmeister, Stephan, 2009. "Profitability of technical stock trading: Has it moved from daily to intraday data?," Review of Financial Economics, Elsevier, vol. 18(4), pages 190-201, October.
    13. Stephan Schulmeister, 2007. "The Interaction Between the Aggregate Behaviour of Technical Trading Systems and Stock Price Dynamics," WIFO Working Papers 290, WIFO.
    14. Kung, James J., 2009. "Predictability of Technical Trading Rules: Evidence from the Taiwan Stock Market," Review of Applied Economics, Lincoln University, Department of Financial and Business Systems, vol. 5(1-2), pages 1-17, March.
    15. Terence Tai-Leung Chong & Wing-Kam Ng & Venus Khim-Sen Liew, 2014. "Revisiting the Performance of MACD and RSI Oscillators," JRFM, MDPI, vol. 7(1), pages 1-12, February.
    16. Chong, Terence Tai-Leung & Lam, Tau-Hing & Yan, Isabel Kit-Ming, 2012. "Is the Chinese stock market really inefficient?," China Economic Review, Elsevier, vol. 23(1), pages 122-137.
    17. Shynkevich, Andrei, 2012. "Performance of technical analysis in growth and small cap segments of the US equity market," Journal of Banking & Finance, Elsevier, vol. 36(1), pages 193-208.
    18. Yung-Ho Chang & Massoud Metghalchi & Chia-Chung Chan, 2006. "Technical trading strategies and cross-national information linkage: the case of Taiwan stock market," Applied Financial Economics, Taylor & Francis Journals, vol. 16(10), pages 731-743.
    19. Metghalchi, Massoud & Chen, Chien-Ping & Hayes, Linda A., 2015. "History of share prices and market efficiency of the Madrid general stock index," International Review of Financial Analysis, Elsevier, vol. 40(C), pages 178-184.
    20. Metghalchi, Massoud & Chang, Yung-Ho & Marcucci, Juri, 2008. "Is the Swedish stock market efficient? Evidence from some simple trading rules," International Review of Financial Analysis, Elsevier, vol. 17(3), pages 475-490, June.

    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:19:y:2009:i:14:p:1171-1186. 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.