Modeling for stock trends: A study of two-stage pattern strategy*
Abstract
This paper focuses on how to predict stock trends quantitatively and to differentiate turning point. Through the summarizing of the main theories and methods in security technical analysis, this paper propose the hypothesis that two contiguous white bars or black bars indicate the uptrend or downtrend, which is called "Two-stage pattern strategy (TSPS)". Empirical test supports the hypothesis and shows that when the forecasted short-term trend is consistent with the bullish or bearish long-term trend, the accurate rate of the hypothesis is higher. Trading rules according to the TSPS method have also been discovered and support the method's profitability.
Document Type
Conference Proceeding
Date of Publication
1-1-2022
Publication Title
2022 7th International Conference on Image, Vision and Computing, ICIVC 2022
Publisher
IEEE
School
School of Arts and Humanities
RAS ID
52115
Funders
China Postdoctoral Science Foundation (Grant No. 2018M630420) and Zhejiang Soft Science Research Program (Grant No. 2019C25022)
Copyright
subscription content
First Page
906
Last Page
912
Comments
He, Y., Zhou, H., Kimm, S., & Xue, J. (2022, July). Modeling for stock trends: A study of two-stage pattern strategy*. In 2022 7th International Conference on Image, Vision and Computing (ICIVC) (pp. 906-912). IEEE.
https://doi.org/10.1109/ICIVC55077.2022.9886250