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Modeling stock market using new hybrid intelligent method based on MFNN and IBHA

  • Soft computing in decision making and in modeling in economics
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Abstract

Based on the basic principles of system dynamics, the mathematic description for the stock market evolution which is a typical complicated dynamic system is provided. And according to this mathematic description, a new hybrid intelligent method based on multi-layer feed-forward neural network (MFNN) which is the most widely used neural network and new improved black hole algorithm (IBHA) which is a new nature-inspired metaheuristic algorithm is proposed to model the stock market. In this new hybrid intelligent method, the new IBHA whose structure is simple and which can be implemented easily, and the modified back propagation algorithm have been used to optimize the architectural and algorithmic parameters of MFNN simultaneously. This new method is applied to model two data groups of Shanghai stock market in 2015.9–2018.8 of China to show that the computing results of the new method coincide well with the real data and that the forecasting precision is highly accurate in these cases. At last, the new method has been applied to model seven other stock market data sets and compared with five state-of-the-art hybrid algorithms proposed in previous studies. The results show that the performance of the new method (including modeling effect and efficiency) has been demonstrated to be satisfactory by using for different problem settings and market situations and it is also easy to be implemented.

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Data availability

I declared that materials described in the manuscript, including all relevant raw data, will be freely available to any scientist wishing to use them for non-commercial purposes, without breaching participant confidentiality.

Code availability

Not applicable.

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Authors and Affiliations

  1. College of Civil and Transportation Engineering, Hohai University, 1 Xikang Road, Nanjing, 210098, People’s Republic of China

    Wei Gao

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  1. Wei Gao
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Conceptualization, Methodology, Manuscript writing, Data curation, and software are all conducted by Wei Gao.

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Correspondence to Wei Gao.

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Gao, W. Modeling stock market using new hybrid intelligent method based on MFNN and IBHA. Soft Comput 26, 7317–7337 (2022). https://doi.org/10.1007/s00500-022-06941-z

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