Intraday price forecasts using candlestick patterns in cryptocurrency markets

We investigate the predictive power of candlestick patterns for short-term cryptocurrency price movements. Using hourly OHLC data from the period 07/2018 to 01/2022 for nearly 400 cryptocurrencies, 2000 trading pairs, and 36 exchanges (200 million observations), we examine 55 reversal patterns identified via python’s TA-Lib package. Certain bullish patterns, such as the Bullish Harami and Hikkake, precede statistically significant positive returns, while bearish patterns, including the Bearish Harami and Hanging Man, anticipate significant declines. Profitability is assessed using the stepwise superior predictive ability test to mitigate data-snooping, supported by several robustness checks. Results remain consistent across time, market conditions, cryptocurrencies, and exchanges, and are unaffected by volume or volatility. Our findings offer robust evidence that some candlestick patterns can serve as reliable tools for cryptocurrency market forecasting.

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Publication Details

Journal
International Review of Economics & Finance
Published
2026-04-01
DOI
https://doi.org/10.1016/j.iref.2026.105158
Primary Topic
Blockchain Technology Applications and Security
Type
article
Field-Weighted Citation Impact
0.00
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article

Intraday price forecasts using candlestick patterns in cryptocurrency markets

Alexander Brauneis, Stefanie Moser
International Review of Economics & Finance
Blockchain Technology Applications and Security
article

Intraday price forecasts using candlestick patterns in cryptocurrency markets

Alexander Brauneis, Stefanie Moser
article en

Abstract

We investigate the predictive power of candlestick patterns for short-term cryptocurrency price movements. Using hourly OHLC data from the period 07/2018 to 01/2022 for nearly 400 cryptocurrencies, 2000 trading pairs, and 36 exchanges (200 million observations), we examine 55 reversal patterns identified via python’s TA-Lib package. Certain bullish patterns, such as the Bullish Harami and Hikkake, precede statistically significant positive returns, while bearish patterns, including the Bearish Harami and Hanging Man, anticipate significant declines. Profitability is assessed using the stepwise superior predictive ability test to mitigate data-snooping, supported by several robustness checks. Results remain consistent across time, market conditions, cryptocurrencies, and exchanges, and are unaffected by volume or volatility. Our findings offer robust evidence that some candlestick patterns can serve as reliable tools for cryptocurrency market forecasting.

International Review of Economics & FinanceVol. 108
Openalex Percentile: Top 29%
Blockchain Technology Applications and Security
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