Abstract
In the ongoing process of economic globalization, while the Chinese market gradually takes up a higher position in the world, as a high-risk and high-return investment, the market has higher demands for investors’ analytical ability and internal and external pressure management ability. Aiming at the forecast and investment problem of stock trend, this paper uses the theory of time value, factor analysis, BP neural network and other methods It also comprehensively uses MATLAB, SPSS and other software for data processing, model building and solving. Through collecting information and establishing BP neural network model based on time value, the income of each stock can be obtained by predicting the stock trend based on the existing data. The earning rate and risk level can be obtained based on the two data. Various factors affecting the stock investment plan in real life can be analyzed comprehensively. It provides reference data for rational stock selection scheme and portfolio scheme and it lowers the investment threshold. The application of this model reduces the investment risk within a certain range and predicts the stock trend to a certain extent.
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Li, C. et al. (2021). Application of Time Value Neural Network and Factor Analysis in Economic Investment. In: Xu, Z., Parizi, R.M., Loyola-González, O., Zhang, X. (eds) Cyber Security Intelligence and Analytics. CSIA 2021. Advances in Intelligent Systems and Computing, vol 1342. Springer, Cham. https://doi.org/10.1007/978-3-030-70042-3_116
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DOI: https://doi.org/10.1007/978-3-030-70042-3_116
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