Intraday price forecasts using candlestick patterns in cryptocurrency markets
Year: 2026
Type: article
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.
Authors: Stefanie Moser, Alexander Brauneis
Institution: University of Klagenfurt
Language: English
Field: Decision Sciences
Domain: Social Sciences
Open Access status: gold
Estimated APC paid: $1,930
OpenAlex ID: W7147396620