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The profitability of technical trading rules in the Bitcoin market

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  • Gerritsen, Dirk F.
  • Bouri, Elie
  • Ramezanifar, Ehsan
  • Roubaud, David

Abstract

We apply seven trend-following indicators to assess the profitability of technical trading rules in the Bitcoin market. Using daily price data from July 2010 to January 2019, our main results show that specific technical analysis trading rules, mainly trading range breakout, contain significant forecasting power for Bitcoin prices, allowing the outperformance of the buy-and-hold strategy through the Sharpe ratio computed via the bootstrapping method. Results from various sub-periods, representing normal and boom markets, generally confirm our main finding and show that the added value of the trading range breakout rule delivers outperformance in strongly trending markets.

Suggested Citation

  • Gerritsen, Dirk F. & Bouri, Elie & Ramezanifar, Ehsan & Roubaud, David, 2020. "The profitability of technical trading rules in the Bitcoin market," Finance Research Letters, Elsevier, vol. 34(C).
    • Handle: RePEc:eee:finlet:v:34:y:2020:i:c:s1544612319303770
    DOI: 10.1016/j.frl.2019.08.011
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    1. 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.
    2. Tiwari, Aviral Kumar & Jana, R.K. & Das, Debojyoti & Roubaud, David, 2018. "Informational efficiency of Bitcoin—An extension," Economics Letters, Elsevier, vol. 163(C), pages 106-109.
    3. Ledoit, Oliver & Wolf, Michael, 2008. "Robust performance hypothesis testing with the Sharpe ratio," Journal of Empirical Finance, Elsevier, vol. 15(5), pages 850-859, December.
    4. Demir, Ender & Gozgor, Giray & Lau, Chi Keung Marco & Vigne, Samuel A., 2018. "Does economic policy uncertainty predict the Bitcoin returns? An empirical investigation," Finance Research Letters, Elsevier, vol. 26(C), pages 145-149.
    5. Bouri, Elie & Gupta, Rangan & Tiwari, Aviral Kumar & Roubaud, David, 2017. "Does Bitcoin hedge global uncertainty? Evidence from wavelet-based quantile-in-quantile regressions," Finance Research Letters, Elsevier, vol. 23(C), pages 87-95.
    6. Balcilar, Mehmet & Bouri, Elie & Gupta, Rangan & Roubaud, David, 2017. "Can volume predict Bitcoin returns and volatility? A quantiles-based approach," Economic Modelling, Elsevier, vol. 64(C), pages 74-81.
    7. Bouri, Elie & Gupta, Rangan & Lahiani, Amine & Shahbaz, Muhammad, 2018. "Testing for asymmetric nonlinear short- and long-run relationships between bitcoin, aggregate commodity and gold prices," Resources Policy, Elsevier, vol. 57(C), pages 224-235.
    8. Aysan, Ahmet Faruk & Demir, Ender & Gozgor, Giray & Lau, Chi Keung Marco, 2019. "Effects of the geopolitical risks on Bitcoin returns and volatility," Research in International Business and Finance, Elsevier, vol. 47(C), pages 511-518.
    9. Christopher J. Neely & David E. Rapach & Jun Tu & Guofu Zhou, 2014. "Forecasting the Equity Risk Premium: The Role of Technical Indicators," Management Science, INFORMS, vol. 60(7), pages 1772-1791, July.
    10. Bouri, Elie & Shahzad, Syed Jawad Hussain & Roubaud, David, 2019. "Co-explosivity in the cryptocurrency market," Finance Research Letters, Elsevier, vol. 29(C), pages 178-183.
    11. Dastgir, Shabbir & Demir, Ender & Downing, Gareth & Gozgor, Giray & Lau, Chi Keung Marco, 2019. "The causal relationship between Bitcoin attention and Bitcoin returns: Evidence from the Copula-based Granger causality test," Finance Research Letters, Elsevier, vol. 28(C), pages 160-164.
    12. 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.
    13. Dyhrberg, Anne Haubo, 2016. "Bitcoin, gold and the dollar – A GARCH volatility analysis," Finance Research Letters, Elsevier, vol. 16(C), pages 85-92.
    14. Han, Yufeng & Zhou, Guofu & Zhu, Yingzi, 2016. "A trend factor: Any economic gains from using information over investment horizons?," Journal of Financial Economics, Elsevier, vol. 122(2), pages 352-375.
    15. 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.
    16. 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.
    17. 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.
    18. Ji, Qiang & Bouri, Elie & Lau, Chi Keung Marco & Roubaud, David, 2019. "Dynamic connectedness and integration in cryptocurrency markets," International Review of Financial Analysis, Elsevier, vol. 63(C), pages 257-272.
    19. 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.
    20. Adam Hayes, 2015. "A Cost of Production Model for Bitcoin," Working Papers 1505, New School for Social Research, Department of Economics.
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    Cited by:

    1. Chen, Kuan-Hau & Su, Xuan-Qi & Lin, Li-Feng & Shih, Yi-Cheng, 2021. "Profitability of moving-average technical analysis over the firm life cycle: Evidence from Taiwan," Pacific-Basin Finance Journal, Elsevier, vol. 69(C).
    2. Aslan, Aylin & Sensoy, Ahmet, 2020. "Intraday efficiency-frequency nexus in the cryptocurrency markets," Finance Research Letters, Elsevier, vol. 35(C).
    3. Sapkota, Niranjan & Grobys, Klaus, 2021. "Asset market equilibria in cryptocurrency markets: Evidence from a study of privacy and non-privacy coins," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 74(C).
    4. Pattnaik, Debidutta & Hassan, M. Kabir & Dsouza, Arun & Tiwari, Aviral & Devji, Shridev, 2023. "Ex-post facto analysis of cryptocurrency literature over a decade using bibliometric technique," Technological Forecasting and Social Change, Elsevier, vol. 189(C).
    5. Ouandlous, Arav & Barkoulas, John T. & Pantos, Themis D., 2022. "Extremity in bitcoin market activity," The Journal of Economic Asymmetries, Elsevier, vol. 26(C).
    6. Fan Fang & Carmine Ventre & Michail Basios & Leslie Kanthan & Lingbo Li & David Martinez-Regoband & Fan Wu, 2020. "Cryptocurrency Trading: A Comprehensive Survey," Papers 2003.11352, arXiv.org, revised Jan 2022.
    7. Luís Almeida & Elisabete Vieira, 2023. "Technical Analysis, Fundamental Analysis, and Ichimoku Dynamics: A Bibliometric Analysis," Risks, MDPI, vol. 11(8), pages 1-24, August.
    8. Umar, Muhammad & Shahzad, Fakhar & Ullah, Irfan & Fanghua, Tong, 2023. "A comparative analysis of cryptocurrency returns and economic policy uncertainty pre- and post-Covid-19," Research in International Business and Finance, Elsevier, vol. 65(C).
    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. Łęt Blanka & Sobański Konrad & Świder Wojciech & Włosik Katarzyna, 2022. "Is the cryptocurrency market efficient? Evidence from an analysis of fundamental factors for Bitcoin and Ethereum," International Journal of Management and Economics, Warsaw School of Economics, Collegium of World Economy, vol. 58(4), pages 351-370, December.
    11. Imran Yousaf & Shoaib Ali & Elie Bouri & Anupam Dutta, 2021. "Herding on Fundamental/Nonfundamental Information During the COVID-19 Outbreak and Cyber-Attacks: Evidence From the Cryptocurrency Market," SAGE Open, , vol. 11(3), pages 21582440211, July.
    12. Thierry Warin & Aleksandar Stojkov, 2021. "Machine Learning in Finance: A Metadata-Based Systematic Review of the Literature," JRFM, MDPI, vol. 14(7), pages 1-31, July.
    13. Tan, Xilong & Tao, Yubo, 2023. "Trend-based forecast of cryptocurrency returns," Economic Modelling, Elsevier, vol. 124(C).
    14. Li, Yi & Urquhart, Andrew & Wang, Pengfei & Zhang, Wei, 2021. "MAX momentum in cryptocurrency markets," International Review of Financial Analysis, Elsevier, vol. 77(C).
    15. Berend Jelmer Dirk Gort & Xiao-Yang Liu & Xinghang Sun & Jiechao Gao & Shuaiyu Chen & Christina Dan Wang, 2022. "Deep Reinforcement Learning for Cryptocurrency Trading: Practical Approach to Address Backtest Overfitting," Papers 2209.05559, arXiv.org, revised Jan 2023.
    16. Bouri, Elie & Shahzad, Syed Jawad Hussain & Roubaud, David & Kristoufek, Ladislav & Lucey, Brian, 2020. "Bitcoin, gold, and commodities as safe havens for stocks: New insight through wavelet analysis," The Quarterly Review of Economics and Finance, Elsevier, vol. 77(C), pages 156-164.
    17. Rina Astini & Kehkashan Ishrat & Yanto Ramli & Tafiprios Tafiprios & Kwong Wing Chong & Ooi Chee Keong, 2023. "Nexus among Crypto Trading, Environmental Degradation, Economic Growth and Energy Usage: Analysis of Top 10 Cryptofriendly Asian Economies," International Journal of Energy Economics and Policy, Econjournals, vol. 13(5), pages 339-347, September.
    18. Ahmed, Shaker & Grobys, Klaus & Sapkota, Niranjan, 2020. "Profitability of technical trading rules among cryptocurrencies with privacy function," Finance Research Letters, Elsevier, vol. 35(C).
    19. Jiqian Wang & Feng Ma & Elie Bouri & Yangli Guo, 2023. "Which factors drive Bitcoin volatility: Macroeconomic, technical, or both?," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(4), pages 970-988, July.
    20. Ladislav Kristoufek, 2022. "On the role of stablecoins in cryptoasset pricing dynamics," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-26, December.
    21. Marina Resta & Paolo Pagnottoni & Maria Elena De Giuli, 2020. "Technical Analysis on the Bitcoin Market: Trading Opportunities or Investors’ Pitfall?," Risks, MDPI, vol. 8(2), pages 1-15, May.
    22. Gerritsen, Dirk F. & Lugtigheid, Rick A.C. & Walther, Thomas, 2022. "Can Bitcoin Investors Profit from Predictions by Crypto Experts?," Finance Research Letters, Elsevier, vol. 46(PA).
    23. Umar, Muhammad & Su, Chi-Wei & Rizvi, Syed Kumail Abbas & Shao, Xue-Feng, 2021. "Bitcoin: A safe haven asset and a winner amid political and economic uncertainties in the US?," Technological Forecasting and Social Change, Elsevier, vol. 167(C).
    24. Bazán-Palomino, Walter & Svogun, Daniel, 2023. "On the drivers of technical analysis profits in cryptocurrency markets: A Distributed Lag approach," International Review of Financial Analysis, Elsevier, vol. 86(C).
    25. Gradojevic, Nikola & Kukolj, Dragan & Adcock, Robert & Djakovic, Vladimir, 2023. "Forecasting Bitcoin with technical analysis: A not-so-random forest?," International Journal of Forecasting, Elsevier, vol. 39(1), pages 1-17.

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    More about this item

    Keywords

    Technical analysis; Trading rules; Profitability; Excess return; Bitcoin;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)

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