IDEAS home Printed from https://ideas.repec.org/p/fgv/eesptd/181.html
   My bibliography  Save this paper

Ombro-cabeça-ombro: testando a lucratividade do padrão gráfico de análise técnica no mercado de ações brasileiro

Author

Listed:
  • Pereira, Pedro L. Valls

Abstract

Starting from an adapted version of Osler and Chang (1995) methodology, this article empirically evaluates the profitability of investment strategies based on identification of the Head and Shoulders chart pattern in the Brazilian stock market. For that purpose, several investment strategies conditioned by the identification of the Head and Shoulders pattern (in its basic and inverted forms) by a computer algorithm in daily price series of 47 stocks from January 1994 to August 2006 were defined. Confidence intervals consistent with the null hypothesis that no strategies with positive returns can be based only on historical data were constructed using the Bootstrap sample inference technique in order to test the predictive power of each strategy. More specifically, the mean returns obtained by each strategy when applied to the stocks price series were compared to those obtained by the same strategies when applied to 1.000 artificial price series - for each stock - generated by two widely used stock price models: Random Walk and E-GARCH. Overall, our results show that it is possible to create strategies conditioned by the occurrence of Head and Shoulders, with positive returns, which indicates that these patterns can capture from stock historical prices some signals about their future price trend which are neither explained by a Random Walk nor by an E-GARCH. Nevertheless, when the effects of taxes and transaction costs are considered, depending on their magnitude, these conclusions are maintained only for the pattern in its inverted form

Suggested Citation

  • Pereira, Pedro L. Valls, 2009. "Ombro-cabeça-ombro: testando a lucratividade do padrão gráfico de análise técnica no mercado de ações brasileiro," Textos para discussão 181, FGV EESP - Escola de Economia de São Paulo, Fundação Getulio Vargas (Brazil).
    • Handle: RePEc:fgv:eesptd:181
    as

    Download full text from publisher

    File URL: https://repositorio.fgv.br/bitstreams/3e695cd1-9b0e-43eb-95ea-2b1c3a8fccc4/download
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Baptista, Ricardo F. de F. & Valls Pereira, Pedro L., 2008. "Análise do Desempenho de Regras de Análise Técnica Aplicada ao Mercado Intradiário do Contrato Futuro do Índice Bovespa [Analysis of the performance of Technical Analysis startegies applied to Intr," MPRA Paper 10351, University Library of Munich, Germany.
    2. Andrew W. Lo, A. Craig MacKinlay, 1988. "Stock Market Prices do not Follow Random Walks: Evidence from a Simple Specification Test," The Review of Financial Studies, Society for Financial Studies, vol. 1(1), pages 41-66.
    3. repec:bla:jfinan:v:55:y:2000:i:4:p:1705-1770 is not listed on IDEAS
    4. Chang, Eui Jung & Lima, Eduardo Jose Araujo & Tabak, Benjamin Miranda, 2004. "Testing for predictability in emerging equity markets," Emerging Markets Review, Elsevier, vol. 5(3), pages 295-316, September.
    5. 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.
    6. Cajueiro, Daniel O. & Tabak, Benjamin M. & Souza, Nathalia A., 2005. "Periodic market closures and the long-range dependence phenomena in the Brazilian equity market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 351(2), pages 512-522.
    7. P.H. Kevin Chang & Carol L. Osler, 1995. "Head and shoulders: not just a flaky pattern," Staff Reports 4, Federal Reserve Bank of New York.
    8. Jensen, Michael C., 1978. "Some anomalous evidence regarding market efficiency," Journal of Financial Economics, Elsevier, vol. 6(2-3), pages 95-101.
    9. G. Caginalp & H. Laurent, 1998. "The predictive power of price patterns," Applied Mathematical Finance, Taylor & Francis Journals, vol. 5(3-4), pages 181-205.
    10. Torres, Ricardo & Bonomo, Marco Antonio Cesar & Fernandes, Cristiano, 2002. "A Aleatoriedade do Passeio na Bovespa: Testando a Eficiência do Mercado Acionário Brasileiro," Revista Brasileira de Economia - RBE, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil), vol. 56(2), April.
    11. Jensen, Michael C & Bennington, George A, 1970. "Random Walks and Technical Theories: Some Additional Evidence," Journal of Finance, American Finance Association, vol. 25(2), pages 469-482, May.
    12. Saffi, Pedro A. C., 2003. "Análise Técnica: Sorte ou Realidade?," Revista Brasileira de Economia - RBE, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil), vol. 57(4), October.
    13. 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.
    14. 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.
    15. Cajueiro, Daniel O. & Tabak, Benjamin M., 2005. "Possible causes of long-range dependence in the Brazilian stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 345(3), pages 635-645.
    16. 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.
    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. Rodrigo Chicaroli & Pedro L. Valls Pereira, 2015. "Predictability of Equity Models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 34(6), pages 427-440, September.

    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. Farias Nazário, Rodolfo Toríbio & e Silva, Jéssica Lima & Sobreiro, Vinicius Amorim & Kimura, Herbert, 2017. "A literature review of technical analysis on stock markets," The Quarterly Review of Economics and Finance, Elsevier, vol. 66(C), pages 115-126.
    2. Matheus José Silva de Souza & Danilo Guimarães Franco Ramos & Marina Garcia Pena & Vinicius Amorim Sobreiro & Herbert Kimura, 2018. "Examination of the profitability of technical analysis based on moving average strategies in BRICS," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 4(1), pages 1-18, December.
    3. Christopher J. Neely & Paul A. Weller, 2011. "Technical analysis in the foreign exchange market," Working Papers 2011-001, Federal Reserve Bank of St. Louis.
    4. 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.
    5. Adam Zaremba & Jacob Koby Shemer, 2018. "Price-Based Investment Strategies," Springer Books, Springer, number 978-3-319-91530-2, January.
    6. Jin, Xiaoye, 2021. "What do we know about the popularity of technical analysis in foreign exchange markets? A skewness preference perspective," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 71(C).
    7. Gerritsen, Dirk F., 2016. "Are chartists artists? The determinants and profitability of recommendations based on technical analysis," International Review of Financial Analysis, Elsevier, vol. 47(C), pages 179-196.
    8. Zhu, Yingzi & Zhou, Guofu, 2009. "Technical analysis: An asset allocation perspective on the use of moving averages," Journal of Financial Economics, Elsevier, vol. 92(3), pages 519-544, June.
    9. Yochanan Shachmurove & Uri BenZion & Paul Klein & Joseph Yagil, 2001. "A Moving Average Comparison of the Tel-Aviv 25 and S&P 500 Stock Indices," Penn CARESS Working Papers 4731f3394c43bebf4d3191c81, Penn Economics Department.
    10. Leković Miljan, 2018. "Evidence for and Against the Validity of Efficient Market Hypothesis," Economic Themes, Sciendo, vol. 56(3), pages 369-387, September.
    11. Jying‐Nan Wang & Hung‐Chun Liu & Jiangze Du & Yuan‐Teng Hsu, 2019. "Economic benefits of technical analysis in portfolio management: Evidence from global stock markets," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 24(2), pages 890-902, April.
    12. Jia Wang & Tong Sun & Benyuan Liu & Yu Cao & Degang Wang, 2021. "Financial Markets Prediction with Deep Learning," Papers 2104.05413, arXiv.org.
    13. Rapach, David & Zhou, Guofu, 2013. "Forecasting Stock Returns," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 328-383, Elsevier.
    14. Lubnau, Thorben, 2014. "Spread trading strategies in the crude oil futures market," Discussion Papers 353, European University Viadrina Frankfurt (Oder), Department of Business Administration and Economics.
    15. Cajueiro, Daniel O. & Tabak, Benjamin M., 2006. "Testing for predictability in equity returns for European transition markets," Economic Systems, Elsevier, vol. 30(1), pages 56-78, March.
    16. U, JuHyok & Lu, PengYu & Kim, ChungSong & Ryu, UnSok & Pak, KyongSok, 2020. "A new LSTM based reversal point prediction method using upward/downward reversal point feature sets," Chaos, Solitons & Fractals, Elsevier, vol. 132(C).
    17. Dockery, Everton & Todorov, Ivan, 2023. "Further evidence on the returns to technical trading rules: Insights from fourteen currencies," Journal of Multinational Financial Management, Elsevier, vol. 69(C).
    18. Meredith Beechey & David Gruen & James Vickery, 2000. "The Efficient Market Hypothesis: A Survey," RBA Research Discussion Papers rdp2000-01, Reserve Bank of Australia.
    19. Erdemlioglu, Deniz & Petitjean, Mikael & Vargas, Nicolas, 2021. "Market instability and technical trading at high frequency: Evidence from NASDAQ stocks," Economic Modelling, Elsevier, vol. 102(C).
    20. 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.

    More about this item

    JEL classification:

    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods

    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:fgv:eesptd:181. 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: Núcleo de Computação da FGV EPGE (email available below). General contact details of provider: https://edirc.repec.org/data/eegvfbr.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.