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Are simple technical trading rules profitable in bitcoin markets?

Author

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  • Deprez, Niek
  • Frömmel, Michael
Abstract
This paper examines the profitability of simple technical trading rules in bitcoin markets comprehensively, by taking into account realistic investor behaviour and transaction costs, and data mining problems. Realistic investor behaviour is replicated by first employing 75,360 simple technical trading rules, divided over 6 commonly used trading rule classes and daily and intraday frequencies. Next, we select the best performing rules after transaction costs using a multiple hypothesis procedure. Finally, we form portfolios combining the selected rules and analyse their out-of-sample performance. We find that, especially risk–return wise, simple technical trading rules can outperform a buy-and-hold strategy in the bitcoin market out-of-sample.

Suggested Citation

  • Deprez, Niek & Frömmel, Michael, 2024. "Are simple technical trading rules profitable in bitcoin markets?," International Review of Economics & Finance, Elsevier, vol. 93(PB), pages 858-874.
    • Handle: RePEc:eee:reveco:v:93:y:2024:i:pb:p:858-874
    DOI: 10.1016/j.iref.2024.05.003
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    References listed on IDEAS

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    1. 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.
    2. Brownlees, C.T. & Gallo, G.M., 2006. "Financial econometric analysis at ultra-high frequency: Data handling concerns," Computational Statistics & Data Analysis, Elsevier, vol. 51(4), pages 2232-2245, December.
    3. 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.
    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. Graham Elliott & Allan Timmermann, 2016. "Economic Forecasting," Economics Books, Princeton University Press, edition 1, number 10740.
    6. Sensoy, Ahmet, 2019. "The inefficiency of Bitcoin revisited: A high-frequency analysis with alternative currencies," Finance Research Letters, Elsevier, vol. 28(C), pages 68-73.
    7. Robert Hudson & Andrew Urquhart, 2021. "Technical trading and cryptocurrencies," Annals of Operations Research, Springer, vol. 297(1), pages 191-220, February.
    8. 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.
    9. Svogun, Daniel & Bazán-Palomino, Walter, 2022. "Technical analysis in cryptocurrency markets: Do transaction costs and bubbles matter?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 79(C).
    10. Romano, Joseph P. & Shaikh, Azeem M. & Wolf, Michael, 2008. "Formalized Data Snooping Based On Generalized Error Rates," Econometric Theory, Cambridge University Press, vol. 24(2), pages 404-447, April.
    11. Urquhart, Andrew, 2016. "The inefficiency of Bitcoin," Economics Letters, Elsevier, vol. 148(C), pages 80-82.
    12. 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.
    13. Kristoufek, Ladislav, 2018. "On Bitcoin markets (in)efficiency and its evolution," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 503(C), pages 257-262.
    14. Anghel, Dan Gabriel, 2022. "No pain, no gain: You should always incorporate trading costs for a bias-free evaluation of trading rule overperformance," Economics Letters, Elsevier, vol. 216(C).
    15. Corbet, Shaen & Eraslan, Veysel & Lucey, Brian & Sensoy, Ahmet, 2019. "The effectiveness of technical trading rules in cryptocurrency markets," Finance Research Letters, Elsevier, vol. 31(C), pages 32-37.
    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. 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.
    18. Bariviera, Aurelio F. & Basgall, María José & Hasperué, Waldo & Naiouf, Marcelo, 2017. "Some stylized facts of the Bitcoin market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 484(C), pages 82-90.
    19. Nikolay Miller & Yiming Yang & Bruce Sun & Guoyi Zhang, 2019. "Identification of technical analysis patterns with smoothing splines for bitcoin prices," Journal of Applied Statistics, Taylor & Francis Journals, vol. 46(12), pages 2289-2297, September.
    20. Nadarajah, Saralees & Chu, Jeffrey, 2017. "On the inefficiency of Bitcoin," Economics Letters, Elsevier, vol. 150(C), pages 6-9.
    21. Cheah, Eng-Tuck & Fry, John, 2015. "Speculative bubbles in Bitcoin markets? An empirical investigation into the fundamental value of Bitcoin," Economics Letters, Elsevier, vol. 130(C), pages 32-36.
    22. N. Blasco & P. Corredor & N. Satrústegui, 2022. "The witching week of herding on bitcoin exchanges," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-18, December.
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    More about this item

    Keywords

    Bitcoin; Technical analysis; False discovery rate; Intraday;
    All these keywords.

    JEL classification:

    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

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