Can Japanese Candlestick Patterns be Profitable on the Component Stocks of the SSE50 Index?
Shangkun Deng,
Zhihao Su,
Yanmei Ren,
Haoran Yu,
Yingke Zhu and
Chenyang Wei
SAGE Open, 2022, vol. 12, issue 3, 21582440221117803
Abstract:
In this study, we investigate the profitability of 10 well-known Japanese candlestick charting patterns using daily-based data on the component stocks of the Chinese SSE50 index, which involves a lengthy sample period from January 2000 to December 2018. The main contribution of this paper is that we conduct the first predictive power examination of Japanese candlestick patterns on the Chinese SSE50 stocks while taking into account trend and overbought/oversold conditions, and their profitability over different holding periods. Experimental results indicate that several bullish candlestick patterns such as Long White and Bullish Gap can produce a significant positive average return over certain holding periods. In addition, empirical results show that none of the bearish candlestick patterns we examined offers predictive power. However, without considering trend and overbought/oversold conditions, we find that the bearish pattern Gravestone Doji over a 10-day holding period has superior profitability if it is applied as a contrary trading signal. The robustness of our results is confirmed based upon a bootstrap analysis and an out-of-sample test. The findings of this study are beneficial for the market traders engaged in transaction of the SSE50 component stocks.
Keywords: candlestick pattern; profitability test; trend condition; overbought/oversold condition; out-of-sample test (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations:
Downloads: (external link)
https://journals.sagepub.com/doi/10.1177/21582440221117803 (text/html)
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:sae:sagope:v:12:y:2022:i:3:p:21582440221117803
DOI: 10.1177/21582440221117803
Access Statistics for this article
More articles in SAGE Open
Bibliographic data for series maintained by SAGE Publications ().