Optimizing candlesticks patterns for Bitcoin's trading systems

Gil Cohen ()
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Gil Cohen: Western Galilee Academic College

Review of Quantitative Finance and Accounting, 2021, vol. 57, issue 3, No 12, 1155-1167

Abstract: Abstract In this research we make the first attempt to construct automated Bitcoin trading systems that are based on classical candlesticks patterns. We than tried to alter the classical formations for better trading results. Our data consists Bitcoins prices from the beginning of 2012 till the end of July 2020. WE found that that out of the tree classical candlesticks pattern only Engulfing has been fertile in predicting Bitcoin's price trends shifts. The classical Engulfing pattern generated Profit Factor (PF) of 3.54 and $38,349 Net Profit (NP). We also found that using a strength proxy of 0.9% may improve the classical pattern results. The classical Harami formation failed to produce positive trading results and therefore does not fit Bitcoin trading platforms. On the other hand, a reversed Harami was proven to be a fertile Bitcoin trading strategy. Our research also finds that classical four bars Kicker signals seldom appears and therefore cannot help Bitcoin traders. On the other hand, a reversed Kicker pattern has found to be a winning strategy with relatively low risk. This strategy fits particularly long positions with 74.36% Percent of Profitable (PP) trades and 6.92 PF. We also find that all the examined candlesticks patterns better predict long trends than short trends.

Keywords: Bitcoin; Algorithmic trading; Candlestick; Patterns (search for similar items in EconPapers)
JEL-codes: G11 G15 (search for similar items in EconPapers)
Date: 2021
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Citations: View citations in EconPapers (6)

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DOI: 10.1007/s11156-021-00973-6

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