Modeling for stock trends: A study of two-stage pattern strategy*

Document Type

Conference Proceeding

Publication Title

2022 7th International Conference on Image, Vision and Computing, ICIVC 2022

First Page

906

Last Page

912

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)

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

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.

DOI

10.1109/ICIVC55077.2022.9886250

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