Candlestick Analysis in Forecasting US Stock Market: Are They Informative and Effective

被引:0
|
作者
Qiu, Haoxuan [1 ]
Liu, Fanzhuoqun [2 ]
机构
[1] Cent China Normal Univ, 152 Luoyu Rd, Wuhan, Hubei, Peoples R China
[2] Southwestern Univ Finance & Econ, 555 Liutai Rd, Chengdu, Sichuan, Peoples R China
关键词
trading strategy; techinical analysis; candlestick; stock price;
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Stock price prediction is one of the hottest topics of research in both academia and industry. Being able to predict the trend of price correctly allows investors to gain profit. There have been multiple strategies in stock price prediction, such as multiple machine learning methodologies and forecast from sentiment analysis of the public and news feedings. Among these strategies, one of the oldest but still widely used strategy is the candlestick analysis, which is a simple way that allows general investors to predict the market trend. However, there lacks an unbiased estimation of the effectiveness of such a method. In this paper, using an unbiased and rigorous way to test multiple U.S. stocks, we were able to show that most of the candlestick patterns were not informative, while a small fraction of them provides some correct information for market trend compared with random guesses. Our study serves as a stepping-stone for re-evaluating the candlestick analysis and urges more similar and thorough studies to be conducted to guide the general public in stock market investment better.
引用
收藏
页码:325 / 328
页数:4
相关论文
共 50 条
  • [21] Detrended fluctuation analysis of the US stock market
    Department of Economics, University of Calgary, Calgary, AL T2N 1N4, Canada
    不详
    不详
    [J]. Int. J. Bifurcation Chaos, 2 (599-603):
  • [22] Investigating Deep Stock Market Forecasting with Sentiment Analysis
    Liapis, Charalampos M.
    Karanikola, Aikaterini
    Kotsiantis, Sotiris
    [J]. ENTROPY, 2023, 25 (02)
  • [23] A stock time series forecasting approach incorporating candlestick patterns and sequence similarity
    Liang, Mengxia
    Wu, Shaocong
    Wang, Xiaolong
    Chen, Qingcai
    [J]. EXPERT SYSTEMS WITH APPLICATIONS, 2022, 205
  • [24] Expert system for predicting stock market timing using a candlestick chart
    Lee, KH
    Jo, GS
    [J]. EXPERT SYSTEMS WITH APPLICATIONS, 1999, 16 (04) : 357 - 364
  • [25] Forecasting Stock Market Volatility
    Stamos, Michael
    [J]. JOURNAL OF PORTFOLIO MANAGEMENT, 2023, 49 (03): : 129 - 137
  • [26] Practical stock market forecasting
    Bratt, Elmer C.
    [J]. AMERICAN ECONOMIC REVIEW, 1931, 21 (03): : 566 - 567
  • [27] Forecasting Stock Market Trends
    Hoffman, Wright
    [J]. ANNALS OF THE AMERICAN ACADEMY OF POLITICAL AND SOCIAL SCIENCE, 1928, 139 (228): : 211 - 212
  • [28] Forecasting stock market indexes using principle component analysis and stochastic time effective neural networks
    Wang, Jie
    Wang, Jun
    [J]. NEUROCOMPUTING, 2015, 156 : 68 - 78
  • [29] PRACTICAL STOCK MARKET FORECASTING
    Thornton, F. W.
    [J]. JOURNAL OF ACCOUNTANCY, 1931, 52 (01): : 65 - 66
  • [30] Technological forecasting at the stock market
    Modis, T
    [J]. TECHNOLOGICAL FORECASTING AND SOCIAL CHANGE, 1999, 62 (03) : 173 - 202