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Performance of intraday technical trading in China’s gold market

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  • Jin, Xiaoye

Abstract

This paper investigates the predictive power of intraday technical trading in China’s gold market. We conduct this study by employing a 5-min intraday data from the most active futures contract listed on the Shanghai Futures Exchange covering the period spanning from 12th March 2018 to 10th March 2021. Our empirical evidence suggests that after comprehensively considering data snooping, transaction costs, market conditions, and frequencies of portfolio rebalancing, investors are unlikely to choose technical trading rules that persistently yield attractive out-of-sample performance, indicating that the predictive power of intraday technical trading in China’s gold market is illusory.

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  • Jin, Xiaoye, 2022. "Performance of intraday technical trading in China’s gold market," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 76(C).
  • Handle: RePEc:eee:intfin:v:76:y:2022:i:c:s1042443121001876
    DOI: 10.1016/j.intfin.2021.101481
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    as
    1. 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.
    2. Joseph P. Romano & Michael Wolf, 2005. "Stepwise Multiple Testing as Formalized Data Snooping," Econometrica, Econometric Society, vol. 73(4), pages 1237-1282, July.
    3. 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.
    4. Hendrik Bessembinder & Kalok Chan, 1998. "Market Efficiency and the Returns to Technical Analysis," Financial Management, Financial Management Association, vol. 27(2), Summer.
    5. 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.
    6. Narayan, Paresh Kumar & Mishra, Sagarika & Narayan, Seema & Thuraisamy, Kannan, 2015. "Is Exchange Rate Trading Profitable?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 38(C), pages 217-229.
    7. Hansen, Peter Reinhard, 2005. "A Test for Superior Predictive Ability," Journal of Business & Economic Statistics, American Statistical Association, vol. 23, pages 365-380, October.
    8. Ryan Sullivan & Allan Timmermann & Halbert White, 1999. "Data‐Snooping, Technical Trading Rule Performance, and the Bootstrap," Journal of Finance, American Finance Association, vol. 54(5), pages 1647-1691, October.
    9. Laurent Barras & Olivier Scaillet & Russ Wermers, 2010. "False Discoveries in Mutual Fund Performance: Measuring Luck in Estimated Alphas," Journal of Finance, American Finance Association, vol. 65(1), pages 179-216, February.
    10. 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.
    11. Graham Elliott & Allan Timmermann, 2016. "Economic Forecasting," Economics Books, Princeton University Press, edition 1, number 10740.
    12. Narayan, Paresh Kumar & Narayan, Seema & Sharma, Susan Sunila, 2013. "An analysis of commodity markets: What gain for investors?," Journal of Banking & Finance, Elsevier, vol. 37(10), pages 3878-3889.
    13. Kuang, P. & Schröder, M. & Wang, Q., 2014. "Illusory profitability of technical analysis in emerging foreign exchange markets," International Journal of Forecasting, Elsevier, vol. 30(2), pages 192-205.
    14. Joseph P. Romano & Michael Wolf, "undated". "Control of Generalized Error Rates in Multiple Testing," IEW - Working Papers 245, Institute for Empirical Research in Economics - University of Zurich.
    15. Peter Hansen, 2003. "Asymptotic Tests of Composite Hypotheses," Working Papers 2003-09, Brown University, Department of Economics.
    16. Edward R Dawson & James M. Steeley, 2003. "On the Existence of Visual Technical Patterns in the UK Stock Market," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 30(1‐2), pages 263-293, January.
    17. Jegadeesh, Narasimhan, 1990. "Evidence of Predictable Behavior of Security Returns," Journal of Finance, American Finance Association, vol. 45(3), pages 881-898, July.
    18. Ebert, Sebastian & Hilpert, Christian, 2019. "Skewness preference and the popularity of technical analysis," Journal of Banking & Finance, Elsevier, vol. 109(C).
    19. Huang, Jing-Zhi & Huang, Zhijian (James), 2020. "Testing moving average trading strategies on ETFs," Journal of Empirical Finance, Elsevier, vol. 57(C), pages 16-32.
    20. 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.
    21. 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, vol. 17(3), pages 471-484, June.
    22. Brian M. Lucey & Charles Larkin & Fergal O'Connor, 2014. "Gold markets around the world - who spills over what, to whom, when?," Applied Economics Letters, Taylor & Francis Journals, vol. 21(13), pages 887-892, September.
    23. 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.
    24. Perez-Rodriguez, Jorge V. & Torra, Salvador & Andrada-Felix, Julian, 2005. "STAR and ANN models: forecasting performance on the Spanish "Ibex-35" stock index," Journal of Empirical Finance, Elsevier, vol. 12(3), pages 490-509, June.
    25. 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.
    26. Wei Huang & Qianqiu Liu & S. Ghon Rhee & Liang Zhang, 2010. "Return Reversals, Idiosyncratic Risk, and Expected Returns," Review of Financial Studies, Society for Financial Studies, vol. 23(1), pages 147-168, January.
    27. Yang, Xiaolan & Zhu, Li, 2016. "Ambiguity vs risk: An experimental study of overconfidence, gender and trading activity," Journal of Behavioral and Experimental Finance, Elsevier, vol. 9(C), pages 125-131.
    28. Kim, O & Verrecchia, Re, 1991. "Trading Volume And Price Reactions To Public Announcements," Journal of Accounting Research, Wiley Blackwell, vol. 29(2), pages 302-321.
    29. Torben G. Andersen & Tim Bollerslev & Francis X. Diebold & Paul Labys, 2003. "Modeling and Forecasting Realized Volatility," Econometrica, Econometric Society, vol. 71(2), pages 579-625, March.
    30. 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.
    31. Hudson, Robert & McGroarty, Frank & Urquhart, Andrew, 2017. "Sampling frequency and the performance of different types of technical trading rules," Finance Research Letters, Elsevier, vol. 22(C), pages 136-139.
    32. Frömmel, Michael & Lampaert, Kevin, 2016. "Does frequency matter for intraday technical trading?," Finance Research Letters, Elsevier, vol. 18(C), pages 177-183.
    33. Peter R. Locke & P. C. Venkatesh, 1997. "Futures market transaction costs," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 17(2), pages 229-245, April.
    34. 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.
    35. 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.
    36. Elżbieta Kubińska & Marcin Czupryna & Łukasz Markiewicz & Jan Czekaj, 2016. "Technical Analysis as a Rational Tool of Decision Making for Professional Traders," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 52(12), pages 2756-2771, December.
    37. Narayan, Paresh Kumar & Mishra, Sagarika & Thuraisamy, Kannan, 2015. "Is exchange rate trading profitable?," Working Papers fe_2015_09, Deakin University, Department of Economics.
    38. Blume, Lawrence & Easley, David & O'Hara, Maureen, 1994. "Market Statistics and Technical Analysis: The Role of Volume," Journal of Finance, American Finance Association, vol. 49(1), pages 153-181, March.
    39. Antonio E. Bernardo & Olivier Ledoit, 2000. "Gain, Loss, and Asset Pricing," Journal of Political Economy, University of Chicago Press, vol. 108(1), pages 144-172, February.
    40. Ioannis Psaradellis & Jason Laws & Athanasios A. Pantelous & Georgios Sermpinis, 2019. "Performance of technical trading rules: evidence from the crude oil market," The European Journal of Finance, Taylor & Francis Journals, vol. 25(17), pages 1793-1815, November.
    41. Batten, Jonathan A. & Lucey, Brian M. & McGroarty, Frank & Peat, Maurice & Urquhart, Andrew, 2018. "Does intraday technical trading have predictive power in precious metal markets?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 52(C), pages 102-113.
    42. Halbert White, 2000. "A Reality Check for Data Snooping," Econometrica, Econometric Society, vol. 68(5), pages 1097-1126, September.
    43. Marshall, Ben R. & Cahan, Rochester H. & Cahan, Jared M., 2008. "Does intraday technical analysis in the U.S. equity market have value?," Journal of Empirical Finance, Elsevier, vol. 15(2), pages 199-210, March.
    44. George H. K. Wang & Jot Yau & Tony Baptiste, 1997. "Trading volume and transaction costs in futures markets," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 17(7), pages 757-780, October.
    45. 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.
    46. John D. Storey, 2002. "A direct approach to false discovery rates," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 64(3), pages 479-498, August.
    47. Marshall, Ben R. & Cahan, Rochester H. & Cahan, Jared M., 2008. "Can commodity futures be profitably traded with quantitative market timing strategies?," Journal of Banking & Finance, Elsevier, vol. 32(9), pages 1810-1819, September.
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    More about this item

    Keywords

    China’s gold market; Technical analysis; Data snooping bias; Transaction costs; Intraday predictability;
    All these keywords.

    JEL classification:

    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation
    • Q02 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - General - - - Commodity Market

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