IDEAS home Printed from https://ideas.repec.org/p/ags/ncrfiv/19039.html
   My bibliography  Save this paper

A Reality Check on Technical Trading Rule Profits in US Futures Markets

Author

Listed:
  • Park, Cheol-Ho
  • Irwin, Scott H.

Abstract

This paper investigates the profitability of technical trading rules in US futures markets over the 1985-2004 period. To account for data snooping biases, we evaluate statistical significance of performance across technical trading rules using White's Bootstrap Reality Check test and Hansen's Superior Predictive Ability test. These methods directly quantify the effect of data snooping by testing the performance of the best rule in the context of the full universe of technical trading rules. Results show that the best rules generate statistically significant economic profits only for two of 17 futures contracts traded in the US. This evidence indicates that technical trading rules generally have not been profitable in US futures markets after correcting for data snooping biases.

Suggested Citation

  • Park, Cheol-Ho & Irwin, Scott H., 2005. "A Reality Check on Technical Trading Rule Profits in US Futures Markets," 2005 Conference, April 18-19, 2005, St. Louis, Missouri 19039, NCR-134 Conference on Applied Commodity Price Analysis, Forecasting, and Market Risk Management.
  • Handle: RePEc:ags:ncrfiv:19039
    DOI: 10.22004/ag.econ.19039
    as

    Download full text from publisher

    File URL: https://ageconsearch.umn.edu/record/19039/files/cp05pa01.pdf
    Download Restriction: no

    File URL: https://libkey.io/10.22004/ag.econ.19039?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
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. De Long, J Bradford, et al, 1990. "Positive Feedback Investment Strategies and Destabilizing Rational Speculation," Journal of Finance, American Finance Association, vol. 45(2), pages 379-395, June.
    2. Burton G. Malkiel, 2003. "The Efficient Market Hypothesis and Its Critics," Working Papers 111, Princeton University, Department of Economics, Center for Economic Policy Studies..
    3. Slezak, Steve L., 2003. "On the Impossibility of Weak-Form Efficient Markets," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 38(3), pages 523-554, September.
    4. Park, Cheol-Ho & Irwin, Scott H., 2004. "The Profitability of Technical Analysis: A Review," AgMAS Project Research Reports 37487, University of Illinois at Urbana-Champaign, Department of Agricultural and Consumer Economics.
    5. Kidd, Willis V. & Brorsen, B. Wade, 2004. "Why have the returns to technical analysis decreased?," Journal of Economics and Business, Elsevier, vol. 56(3), pages 159-176.
    6. 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.
    7. Timmermann, Allan & Granger, Clive W. J., 2004. "Efficient market hypothesis and forecasting," International Journal of Forecasting, Elsevier, vol. 20(1), pages 15-27.
    8. West, Kenneth D, 1996. "Asymptotic Inference about Predictive Ability," Econometrica, Econometric Society, vol. 64(5), pages 1067-1084, September.
    9. Lukac, Louis P & Brorsen, B Wade, 1990. "A Comprehensive Test of Futures Market Disequilibrium," The Financial Review, Eastern Finance Association, vol. 25(4), pages 593-622, November.
    10. Kenneth A. Kavajecz, 2004. "Technical Analysis and Liquidity Provision," The Review of Financial Studies, Society for Financial Studies, vol. 17(4), pages 1043-1071.
    11. Dale, Charles & Workman, Rosemarie, 1981. "Measuring patterns of price movements in the Treasury bill futures market," MPRA Paper 48639, University Library of Munich, Germany.
    12. repec:pri:cepsud:91malkiel is not listed on IDEAS
    13. Denton, Frank T, 1985. "Data Mining as an Industry," The Review of Economics and Statistics, MIT Press, vol. 67(1), pages 124-127, February.
    14. De Long, J Bradford & Shleifer, Andrei & Summers, Lawrence H & Waldmann, Robert J, 1991. "The Survival of Noise Traders in Financial Markets," The Journal of Business, University of Chicago Press, vol. 64(1), pages 1-19, January.
    15. Michael Cooper & Huseyin Gulen, 2006. "Is Time-Series-Based Predictability Evident in Real Time?," The Journal of Business, University of Chicago Press, vol. 79(3), pages 1263-1292, May.
    16. Sullivan, Ryan & Timmermann, Allan & White, Halbert, 2003. "Forecast evaluation with shared data sets," International Journal of Forecasting, Elsevier, vol. 19(2), pages 217-227.
    17. Park, Cheol-Ho & Irwin, Scott H., 2004. "The Profitability Of Technical Trading Rules In Us Futures Markets: A Data Snooping Free Test," 2004 Conference, April 19-20, 2004, St. Louis, Missouri 19011, NCR-134 Conference on Applied Commodity Price Analysis, Forecasting, and Market Risk Management.
    18. Peter Hansen, 2003. "Asymptotic Tests of Composite Hypotheses," Working Papers 2003-09, Brown University, Department of Economics.
    19. Cheung, Yin-Wong & Chinn, Menzie David, 2001. "Currency traders and exchange rate dynamics: a survey of the US market," Journal of International Money and Finance, Elsevier, vol. 20(4), pages 439-471, August.
    20. 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.
    21. Lovell, Michael C, 1983. "Data Mining," The Review of Economics and Statistics, MIT Press, vol. 65(1), pages 1-12, February.
    22. Carol L. Osler, 2003. "Currency Orders and Exchange Rate Dynamics: An Explanation for the Predictive Success of Technical Analysis," Journal of Finance, American Finance Association, vol. 58(5), pages 1791-1820, October.
    23. Szakmary, Andrew C. & Mathur, Ike, 1997. "Central bank intervention and trading rule profits in foreign exchange markets," Journal of International Money and Finance, Elsevier, vol. 16(4), pages 513-535, August.
    24. Bong-Chan, Kho, 1996. "Time-varying risk premia, volatility, and technical trading rule profits: Evidence from foreign currency futures markets," Journal of Financial Economics, Elsevier, vol. 41(2), pages 249-290, June.
    25. Halbert White, 2000. "A Reality Check for Data Snooping," Econometrica, Econometric Society, vol. 68(5), pages 1097-1126, September.
    26. Carol L. Osler, 2003. "Currency Orders and Exchange Rate Dynamics: An Explanation for the Predictive Success of Technical Analysis," Journal of Finance, American Finance Association, vol. 58(5), pages 1791-1819, October.
    27. Burton G. Malkiel, 2003. "The Efficient Market Hypothesis and Its Critics," Journal of Economic Perspectives, American Economic Association, vol. 17(1), pages 59-82, Winter.
    28. 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.
    29. Burton G. Malkiel, 2003. "The Efficient Market Hypothesis and Its Critics," Working Papers 111, Princeton University, Department of Economics, Center for Economic Policy Studies..
    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. Montgomery, William & Raza, Ahmad & Ülkü, Numan, 2019. "Tests of technical trading rules and the 52-week high strategy in the corporate bond market," Global Finance Journal, Elsevier, vol. 40(C), pages 85-103.
    2. 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.
    3. Wang, Shan & Jiang, Zhi-Qiang & Li, Sai-Ping & Zhou, Wei-Xing, 2015. "Testing the performance of technical trading rules in the Chinese markets based on superior predictive test," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 439(C), pages 114-123.
    4. Flavio Ivo Riedlinger & João Nicolau, 2020. "The Profitability in the FTSE 100 Index: A New Markov Chain Approach," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 27(1), pages 61-81, March.
    5. Ikhlaas Gurrib & Mohammad Nourani & Rajesh Kumar Bhaskaran, 2022. "Energy crypto currencies and leading U.S. energy stock prices: are Fibonacci retracements profitable?," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-27, December.
    6. Jasdeep S. Banga & B. Wade Brorsen, 2019. "Profitability of alternative methods of combining the signals from technical trading systems," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 26(1), pages 32-45, January.
    7. Han, Yufeng & Hu, Ting & Yang, Jian, 2016. "Are there exploitable trends in commodity futures prices?," Journal of Banking & Finance, Elsevier, vol. 70(C), pages 214-234.
    8. Ioana-Andreea Boboc & Mihai-Cristian Dinică, 2013. "An Algorithm for Testing the Efficient Market Hypothesis," PLOS ONE, Public Library of Science, vol. 8(10), pages 1-11, October.
    9. Andrei Shynkevich, 2021. "Impact of bitcoin futures on the informational efficiency of bitcoin spot market," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 41(1), pages 115-134, January.
    10. Chiang, Mi-Hsiu & Chiu, Hsin-Yu & Kuo, Wei-Yu, 2021. "Predictive ability of similarity-based futures trading strategies," Pacific-Basin Finance Journal, Elsevier, vol. 68(C).
    11. Hsu, Po-Hsuan & Taylor, Mark P. & Wang, Zigan, 2016. "Technical trading: Is it still beating the foreign exchange market?," Journal of International Economics, Elsevier, vol. 102(C), pages 188-208.
    12. Nicolás Acevedo Vélez, 2007. "The cattle crush strategy: trading opportunities for cattle producers," Revista Ecos de Economía, Universidad EAFIT, October.
    13. Ikhlaas Gurrib & Firuz Kamalov & Elgilani Elshareif, 2021. "Can the Leading US Energy Stock Prices be Predicted using the Ichimoku Cloud?," International Journal of Energy Economics and Policy, Econjournals, vol. 11(1), pages 41-51.
    14. Qi Xu & Ying Wang, 2021. "Managing volatility in commodity momentum," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 41(5), pages 758-782, May.
    15. 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.
    16. Mihai Cristian Dinică & Erica Cristina (Balea) Dinică, 2015. "Testing the Weak-Form Market Eficiency of the Euronext Wheat," Romanian Economic Journal, Department of International Business and Economics from the Academy of Economic Studies Bucharest, vol. 18(55), pages 25-38, March.
    17. Taylor, Mark & Hsu, Po-Hsuan, 2014. "Forty Years, Thirty Currencies and 21,000 Trading Rules: A Large-scale, Data-Snooping Robust Analysis of Technical Trading in t," CEPR Discussion Papers 10018, C.E.P.R. Discussion Papers.
    18. Shynkevich, Andrei, 2016. "Predictability in bond returns using technical trading rules," Journal of Banking & Finance, Elsevier, vol. 70(C), pages 55-69.
    19. Benjamin R. Auer, 2021. "Have trend-following signals in commodity futures markets become less reliable in recent years?," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 35(4), pages 533-553, December.
    20. Yamani, Ehab, 2021. "Foreign exchange market efficiency and the global financial crisis: Fundamental versus technical information," The Quarterly Review of Economics and Finance, Elsevier, vol. 79(C), pages 74-89.
    21. Xiaojie Xu & Yun Zhang, 2022. "Commodity price forecasting via neural networks for coffee, corn, cotton, oats, soybeans, soybean oil, sugar, and wheat," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 29(3), pages 169-181, July.
    22. Ikhlaas Gurrib & Firuz Kamalov & Olga Starkova & Adham Makki & Anita Mirchandani & Namrata Gupta, 2023. "Performance of Equity Investments in Sustainable Environmental Markets," Sustainability, MDPI, vol. 15(9), pages 1-28, May.

    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. 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.
    2. Park, Cheol-Ho & Irwin, Scott H., 2004. "The Profitability Of Technical Trading Rules In Us Futures Markets: A Data Snooping Free Test," 2004 Conference, April 19-20, 2004, St. Louis, Missouri 19011, NCR-134 Conference on Applied Commodity Price Analysis, Forecasting, and Market Risk Management.
    3. 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.
    4. 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.
    5. Christopher J. Neely & Paul A. Weller, 2011. "Technical analysis in the foreign exchange market," Working Papers 2011-001, Federal Reserve Bank of St. Louis.
    6. Menkhoff, Lukas, 2010. "The use of technical analysis by fund managers: International evidence," Journal of Banking & Finance, Elsevier, vol. 34(11), pages 2573-2586, November.
    7. Robert Ślepaczuk & Grzegorz Zakrzewski & Paweł Sakowski, 2012. "Investment strategies beating the market. What can we squeeze from the market?," Working Papers 2012-04, Faculty of Economic Sciences, University of Warsaw.
    8. Ślepaczuk Robert & Sakowski Paweł & Zakrzewski Grzegorz, 2018. "Investment Strategies that Beat the Market. What Can We Squeeze from the Market?," Financial Internet Quarterly (formerly e-Finanse), Sciendo, vol. 14(4), pages 36-55, December.
    9. Taylor, Mark & Hsu, Po-Hsuan, 2014. "Forty Years, Thirty Currencies and 21,000 Trading Rules: A Large-scale, Data-Snooping Robust Analysis of Technical Trading in t," CEPR Discussion Papers 10018, C.E.P.R. Discussion Papers.
    10. Yamamoto, Ryuichi, 2012. "Intraday technical analysis of individual stocks on the Tokyo Stock Exchange," Journal of Banking & Finance, Elsevier, vol. 36(11), pages 3033-3047.
    11. Stephan Schulmeister, 2009. "Technical Trading and Trends in the Dollar-Euro Exchange Rate," WIFO Studies, WIFO, number 37582, June.
    12. Olivier Brandouy & Philippe Mathieu, 2006. "A Broad-Spectrum Computational Approach for Market Efficiency," Computing in Economics and Finance 2006 492, Society for Computational Economics.
    13. Neely, Christopher J. & Weller, Paul A. & Ulrich, Joshua M., 2009. "The Adaptive Markets Hypothesis: Evidence from the Foreign Exchange Market," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 44(2), pages 467-488, April.
    14. Hung, Chiayu & Lai, Hung-Neng, 2022. "Information asymmetry and the profitability of technical analysis," Journal of Banking & Finance, Elsevier, vol. 134(C).
    15. James K. Self, 2006. "Asymmetric Stationarity in National Stock Market Indices: An MTAR Analysis," The Journal of Business, University of Chicago Press, vol. 79(6), pages 3153-3174, November.
    16. Hsu, Po-Hsuan & Taylor, Mark P. & Wang, Zigan, 2016. "Technical trading: Is it still beating the foreign exchange market?," Journal of International Economics, Elsevier, vol. 102(C), pages 188-208.
    17. 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.
    18. Isakov, Dusan & Marti, Didier, 2011. "Technical Analysis with a Long-Term Perspective: Trading Strategies and Market Timing Ability," FSES Working Papers 421, Faculty of Economics and Social Sciences, University of Freiburg/Fribourg Switzerland.
    19. Firat Melih Yilmaz & Engin Yildiztepe, 2024. "Statistical Evaluation of Deep Learning Models for Stock Return Forecasting," Computational Economics, Springer;Society for Computational Economics, vol. 63(1), pages 221-244, January.
    20. Chen, Cheng-Wei & Huang, Chin-Sheng & Lai, Hung-Wei, 2009. "The impact of data snooping on the testing of technical analysis: An empirical study of Asian stock markets," Journal of Asian Economics, Elsevier, vol. 20(5), pages 580-591, September.

    More about this item

    Keywords

    Marketing;

    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:ags:ncrfiv:19039. 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: AgEcon Search (email available below). General contact details of provider: https://edirc.repec.org/data/dauiuus.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.