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Probability rough set and portfolio optimization integrated three-way predication decisions approach to stock price

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Abstract

In the stock market, accurate trend judgment and reasonable asset distribution are effective ways to obtain ideal return. However, the real stock market is affected by the objective economic environment, investors’ expected return and other potential factors, which makes the classical portfolio strategy face more challenges and pressures. How to build a reliable portfolio strategy in an uncertain environment will be a scientific problem worthy of in-depth discussion. To address this issue, this paper combines machine learning with rough set to establish a new rough set theory prediction model, quantitatively dividing the stock data into three categories and targetedly predicting the future trend according to the complexity. Based on the proposed prediction model, a new portfolio strategy is proposed by integrating the mean-variance model. Firstly, for reducing the volatility and noise of the original data of stock price, outlier processing (OP) and wavelet denoising (WD) are utilized. Secondly, for the sake of pertinently forecasting the future trend of different characteristic stock price, a three-way prediction (TWP) decisions approach is constructed based on multiscale permutation entropy (MPE), probabilistic rough set (PRS), variational modal decomposition (VMD) and deep learning. Finally, 20 stocks of Shanghai and Shenzhen stock exchanges are taken as research samples to verify the scientificity and rationality of the portfolio strategy. The results show that the proposed approach not only provides scientific support and reference for investors’ investment decisions, but also provides a new investment strategy theory and method for the investment decisions of the stock market.

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Acknowledgements

The work was partly supported by the National Natural Science Foundation of China (No. 72071152), Shaanxi National Funds for Distinguished Young Scientists, China (No. 2023-JC-JQ-11), Xi’an Science and Technology Projects, China (No. 2022RKYJ0030), the Youth Innovation Team of Shaanxi Universities (2019), the Humanities and Social Science Research Program of Ministry of Education (No. 22YJA630008), the Fundamental Research Funds for the Central Universities (No. 20101236618, 20101236262), Guangzhou Key Research and Development Program (No. 202206010101), Guangdong Basic and Applied Basic Research Foundation (No. 2022A1515110703), Guangdong Provincial Hospital of Chinese Medicine Science and Technology Research Project (No. YN2022QN33).

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Authors and Affiliations

  1. School of Economics and Management, Xidian University, Xi’an, 710126, China

    Juncheng Bai, Bingzhen Sun, Yuqi Guo & Youwei Chen

  2. School of Economics and Management, Xi’an University of Posts and Telecommunications, Xi’an, 710121, China

    Jianfeng Guo

  3. School of Economics and Management, Shanghai University of Political Science and Law, Shanghai, 201701, China

    Xia Xiao

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  1. Juncheng Bai
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Correspondence to Jianfeng Guo or Bingzhen Sun.

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Bai, J., Guo, J., Sun, B. et al. Probability rough set and portfolio optimization integrated three-way predication decisions approach to stock price. Appl Intell 53, 29918–29942 (2023). https://doi.org/10.1007/s10489-023-05085-3

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